tensorflow-core-ops-0.2.0.0: Haskell wrappers for Core Tensorflow Ops.

Safe HaskellNone
LanguageHaskell2010

TensorFlow.GenOps.Core

Synopsis

Documentation

abort :: forall m'. MonadBuild m' => m' ControlNode Source #

abort' :: forall m'. MonadBuild m' => OpParams -> m' ControlNode Source #

abs Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

abs' Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

accumulatorApplyGradient Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int64

local_step

-> Tensor v'3 dtype

gradient

-> m' ControlNode 

accumulatorApplyGradient' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Int64

local_step

-> Tensor v'3 dtype

gradient

-> m' ControlNode 

accumulatorNumAccumulated Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

handle

-> m' (Tensor Value Int32)

num_accumulated

accumulatorNumAccumulated' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

handle

-> m' (Tensor Value Int32)

num_accumulated

accumulatorSetGlobalStep Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int64

new_global_step

-> m' ControlNode 

accumulatorSetGlobalStep' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Int64

new_global_step

-> m' ControlNode 

accumulatorTakeGradient Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

num_required

-> m' (Tensor Value dtype)

average

addManySparseToTensorsMap Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 Int64

sparse_indices

-> Tensor v'2 t

sparse_values

-> Tensor v'3 Int64

sparse_shape

-> m' (Tensor Value Int64)

sparse_handles

addManySparseToTensorsMap' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 Int64

sparse_indices

-> Tensor v'2 t

sparse_values

-> Tensor v'3 Int64

sparse_shape

-> m' (Tensor Value Int64)

sparse_handles

addSparseToTensorsMap Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 Int64

sparse_indices

-> Tensor v'2 t

sparse_values

-> Tensor v'3 Int64

sparse_shape

-> m' (Tensor Value Int64)

sparse_handle

addSparseToTensorsMap' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 Int64

sparse_indices

-> Tensor v'2 t

sparse_values

-> Tensor v'3 Int64

sparse_shape

-> m' (Tensor Value Int64)

sparse_handle

adjustContrast Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word8, Double, Float] t 
=> Tensor v'1 t

images

-> Tensor v'2 Float

contrast_factor

-> Tensor v'3 Float

min_value

-> Tensor v'4 Float

max_value

-> Tensor Build Float

output

adjustContrast' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

images

-> Tensor v'2 Float

contrast_factor

-> Tensor v'3 Float

min_value

-> Tensor v'4 Float

max_value

-> Tensor Build Float

output

adjustContrastv2 Source #

Arguments

:: Tensor v'1 Float

images

-> Tensor v'2 Float

contrast_factor

-> Tensor Build Float

output

adjustContrastv2' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

images

-> Tensor v'2 Float

contrast_factor

-> Tensor Build Float

output

adjustHue Source #

Arguments

:: Tensor v'1 Float

images

-> Tensor v'2 Float

delta

-> Tensor Build Float

output

adjustHue' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

images

-> Tensor v'2 Float

delta

-> Tensor Build Float

output

adjustSaturation Source #

Arguments

:: Tensor v'1 Float

images

-> Tensor v'2 Float

scale

-> Tensor Build Float

output

adjustSaturation' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

images

-> Tensor v'2 Float

scale

-> Tensor Build Float

output

all Source #

Arguments

:: OneOf '[Int32, Int64] tidx 
=> Tensor v'1 Bool

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build Bool

output

all' Source #

Arguments

:: OneOf '[Int32, Int64] tidx 
=> OpParams 
-> Tensor v'1 Bool

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build Bool

output

allCandidateSampler Source #

Arguments

:: MonadBuild m' 
=> Int64

num_sampled

-> Int64

num_true

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

allCandidateSampler' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

num_sampled

-> Int64

num_true

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

angle Source #

Arguments

:: (OneOf '[Complex Double, Complex Float] t, OneOf '[Double, Float] tout) 
=> Tensor v'1 t

input

-> Tensor Build tout

output

angle' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float] t, OneOf '[Double, Float] tout) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build tout

output

anonymousIterator Source #

Arguments

:: MonadBuild m' 
=> [DataType]

output_types

-> m' (Tensor Value ResourceHandle)

handle

anonymousIterator' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

output_types

-> m' (Tensor Value ResourceHandle)

handle

any Source #

Arguments

:: OneOf '[Int32, Int64] tidx 
=> Tensor v'1 Bool

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build Bool

output

any' Source #

Arguments

:: OneOf '[Int32, Int64] tidx 
=> OpParams 
-> Tensor v'1 Bool

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build Bool

output

applyAdaMax Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

m

-> Tensor Ref t

v

-> Tensor v'4 t

beta1_power

-> Tensor v'5 t

lr

-> Tensor v'6 t

beta1

-> Tensor v'7 t

beta2

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> m' (Tensor Ref t)

out

applyAdaMax' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

m

-> Tensor Ref t

v

-> Tensor v'4 t

beta1_power

-> Tensor v'5 t

lr

-> Tensor v'6 t

beta1

-> Tensor v'7 t

beta2

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> m' (Tensor Ref t)

out

applyAdadelta Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

accum_update

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

epsilon

-> Tensor v'7 t

grad

-> m' (Tensor Ref t)

out

applyAdadelta' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

accum_update

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

epsilon

-> Tensor v'7 t

grad

-> m' (Tensor Ref t)

out

applyAdagrad Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> m' (Tensor Ref t)

out

applyAdagrad' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> m' (Tensor Ref t)

out

applyAdagradDA Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

gradient_accumulator

-> Tensor Ref t

gradient_squared_accumulator

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 Int64

global_step

-> m' (Tensor Ref t)

out

applyAdagradDA' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

gradient_accumulator

-> Tensor Ref t

gradient_squared_accumulator

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 Int64

global_step

-> m' (Tensor Ref t)

out

applyAdam Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

m

-> Tensor Ref t

v

-> Tensor v'4 t

beta1_power

-> Tensor v'5 t

beta2_power

-> Tensor v'6 t

lr

-> Tensor v'7 t

beta1

-> Tensor v'8 t

beta2

-> Tensor v'9 t

epsilon

-> Tensor v'10 t

grad

-> m' (Tensor Ref t)

out

applyAdam' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

m

-> Tensor Ref t

v

-> Tensor v'4 t

beta1_power

-> Tensor v'5 t

beta2_power

-> Tensor v'6 t

lr

-> Tensor v'7 t

beta1

-> Tensor v'8 t

beta2

-> Tensor v'9 t

epsilon

-> Tensor v'10 t

grad

-> m' (Tensor Ref t)

out

applyAddSign Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

m

-> Tensor v'3 t

lr

-> Tensor v'4 t

alpha

-> Tensor v'5 t

sign_decay

-> Tensor v'6 t

beta

-> Tensor v'7 t

grad

-> m' (Tensor Ref t)

out

applyAddSign' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

m

-> Tensor v'3 t

lr

-> Tensor v'4 t

alpha

-> Tensor v'5 t

sign_decay

-> Tensor v'6 t

beta

-> Tensor v'7 t

grad

-> m' (Tensor Ref t)

out

applyCenteredRMSProp Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

mg

-> Tensor Ref t

ms

-> Tensor Ref t

mom

-> Tensor v'5 t

lr

-> Tensor v'6 t

rho

-> Tensor v'7 t

momentum

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> m' (Tensor Ref t)

out

applyCenteredRMSProp' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

mg

-> Tensor Ref t

ms

-> Tensor Ref t

mom

-> Tensor v'5 t

lr

-> Tensor v'6 t

rho

-> Tensor v'7 t

momentum

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> m' (Tensor Ref t)

out

applyFtrl Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

linear

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 t

lr_power

-> m' (Tensor Ref t)

out

applyFtrl' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

linear

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 t

lr_power

-> m' (Tensor Ref t)

out

applyFtrlV2 Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

linear

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 t

l2_shrinkage

-> Tensor v'9 t

lr_power

-> m' (Tensor Ref t)

out

applyFtrlV2' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

linear

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 t

l2_shrinkage

-> Tensor v'9 t

lr_power

-> m' (Tensor Ref t)

out

applyGradientDescent Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor v'2 t

alpha

-> Tensor v'3 t

delta

-> m' (Tensor Ref t)

out

applyGradientDescent' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor v'2 t

alpha

-> Tensor v'3 t

delta

-> m' (Tensor Ref t)

out

applyMomentum Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> Tensor v'5 t

momentum

-> m' (Tensor Ref t)

out

applyMomentum' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> Tensor v'5 t

momentum

-> m' (Tensor Ref t)

out

applyPowerSign Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

m

-> Tensor v'3 t

lr

-> Tensor v'4 t

logbase

-> Tensor v'5 t

sign_decay

-> Tensor v'6 t

beta

-> Tensor v'7 t

grad

-> m' (Tensor Ref t)

out

applyPowerSign' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

m

-> Tensor v'3 t

lr

-> Tensor v'4 t

logbase

-> Tensor v'5 t

sign_decay

-> Tensor v'6 t

beta

-> Tensor v'7 t

grad

-> m' (Tensor Ref t)

out

applyProximalAdagrad Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

l1

-> Tensor v'5 t

l2

-> Tensor v'6 t

grad

-> m' (Tensor Ref t)

out

applyProximalAdagrad' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

l1

-> Tensor v'5 t

l2

-> Tensor v'6 t

grad

-> m' (Tensor Ref t)

out

applyProximalGradientDescent Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor v'2 t

alpha

-> Tensor v'3 t

l1

-> Tensor v'4 t

l2

-> Tensor v'5 t

delta

-> m' (Tensor Ref t)

out

applyProximalGradientDescent' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor v'2 t

alpha

-> Tensor v'3 t

l1

-> Tensor v'4 t

l2

-> Tensor v'5 t

delta

-> m' (Tensor Ref t)

out

applyRMSProp Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

var

-> Tensor Ref t

ms

-> Tensor Ref t

mom

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

momentum

-> Tensor v'7 t

epsilon

-> Tensor v'8 t

grad

-> m' (Tensor Ref t)

out

applyRMSProp' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

ms

-> Tensor Ref t

mom

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

momentum

-> Tensor v'7 t

epsilon

-> Tensor v'8 t

grad

-> m' (Tensor Ref t)

out

argMax Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx, OneOf '[Int32, Int64] output_type) 
=> Tensor v'1 t

input

-> Tensor v'2 tidx

dimension

-> Tensor Build output_type

output

argMax' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx, OneOf '[Int32, Int64] output_type) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tidx

dimension

-> Tensor Build output_type

output

argMin Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx, OneOf '[Int32, Int64] output_type) 
=> Tensor v'1 t

input

-> Tensor v'2 tidx

dimension

-> Tensor Build output_type

output

argMin' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx, OneOf '[Int32, Int64] output_type) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tidx

dimension

-> Tensor Build output_type

output

asString Source #

Arguments

:: OneOf '[Complex Float, Bool, Int32, Int64, Int8, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build ByteString

output

asString' Source #

Arguments

:: OneOf '[Complex Float, Bool, Int32, Int64, Int8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build ByteString

output

assert Source #

Arguments

:: (MonadBuild m', TensorTypes t) 
=> Tensor v'1 Bool

condition

-> TensorList v'2 t

data

-> m' ControlNode 

assert' Source #

Arguments

:: (MonadBuild m', TensorTypes t) 
=> OpParams 
-> Tensor v'1 Bool

condition

-> TensorList v'2 t

data

-> m' ControlNode 

assign Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref t

ref

-> Tensor v'2 t

value

-> m' (Tensor Ref t)

output_ref

assign' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 t

value

-> m' (Tensor Ref t)

output_ref

assignAdd Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

ref

-> Tensor v'2 t

value

-> m' (Tensor Ref t)

output_ref

assignAdd' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 t

value

-> m' (Tensor Ref t)

output_ref

assignAddVariableOp Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 dtype

value

-> m' ControlNode 

assignAddVariableOp' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 dtype

value

-> m' ControlNode 

assignSub Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor Ref t

ref

-> Tensor v'2 t

value

-> m' (Tensor Ref t)

output_ref

assignSub' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 t

value

-> m' (Tensor Ref t)

output_ref

assignSubVariableOp Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 dtype

value

-> m' ControlNode 

assignSubVariableOp' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 dtype

value

-> m' ControlNode 

assignVariableOp Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 dtype

value

-> m' ControlNode 

assignVariableOp' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 dtype

value

-> m' ControlNode 

atan2 Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

y

-> Tensor v'2 t

x

-> Tensor Build t

z

atan2' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

y

-> Tensor v'2 t

x

-> Tensor Build t

z

audioSpectrogram Source #

Arguments

:: Int64

stride

-> Int64

window_size

-> Tensor v'1 Float

input

-> Tensor Build Float

spectrogram

audioSpectrogram' Source #

Arguments

:: OpParams 
-> Int64

stride

-> Int64

window_size

-> Tensor v'1 Float

input

-> Tensor Build Float

spectrogram

audioSummary Source #

Arguments

:: Float

sample_rate

-> Tensor v'1 ByteString

tag

-> Tensor v'2 Float

tensor

-> Tensor Build ByteString

summary

audioSummary' Source #

Arguments

:: OpParams 
-> Float

sample_rate

-> Tensor v'1 ByteString

tag

-> Tensor v'2 Float

tensor

-> Tensor Build ByteString

summary

audioSummaryV2 Source #

Arguments

:: Tensor v'1 ByteString

tag

-> Tensor v'2 Float

tensor

-> Tensor v'3 Float

sample_rate

-> Tensor Build ByteString

summary

audioSummaryV2' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

tag

-> Tensor v'2 Float

tensor

-> Tensor v'3 Float

sample_rate

-> Tensor Build ByteString

summary

avgPool Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

value

-> Tensor Build t

output

avgPool' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

value

-> Tensor Build t

output

avgPool3D Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

avgPool3D' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

avgPool3DGrad Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 Int32

orig_input_shape

-> Tensor v'2 t

grad

-> Tensor Build t

output

avgPool3DGrad' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int32

orig_input_shape

-> Tensor v'2 t

grad

-> Tensor Build t

output

avgPoolGrad Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 Int32

orig_input_shape

-> Tensor v'2 t

grad

-> Tensor Build t

output

avgPoolGrad' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int32

orig_input_shape

-> Tensor v'2 t

grad

-> Tensor Build t

output

barrier Source #

Arguments

:: MonadBuild m' 
=> [DataType]

component_types

-> m' (Tensor Ref ByteString)

handle

barrier' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

component_types

-> m' (Tensor Ref ByteString)

handle

barrierInsertMany Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Int64

component_index

-> Tensor Ref ByteString

handle

-> Tensor v'2 ByteString

keys

-> Tensor v'3 t

values

-> m' ControlNode 

barrierInsertMany' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Int64

component_index

-> Tensor Ref ByteString

handle

-> Tensor v'2 ByteString

keys

-> Tensor v'3 t

values

-> m' ControlNode 

barrierTakeMany Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

num_elements

-> m' (Tensor Value Int64, Tensor Value ByteString, TensorList Value component_types)

(indices, keys, values)

  • indices
  • keys
  • values

barrierTakeMany' Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

num_elements

-> m' (Tensor Value Int64, Tensor Value ByteString, TensorList Value component_types)

(indices, keys, values)

  • indices
  • keys
  • values

batch Source #

Arguments

:: TensorTypes t 
=> Int64

batch_timeout_micros

-> Int64

grad_timeout_micros

-> Int64

max_batch_size

-> Int64

num_batch_threads

-> TensorList v'1 t

in_tensors

-> (TensorList Build t, Tensor Build Int64, Tensor Build Int64)

(batched_tensors, batch_index, id)

  • batched_tensors
  • batch_index
  • id

batch' Source #

Arguments

:: TensorTypes t 
=> OpParams 
-> Int64

batch_timeout_micros

-> Int64

grad_timeout_micros

-> Int64

max_batch_size

-> Int64

num_batch_threads

-> TensorList v'1 t

in_tensors

-> (TensorList Build t, Tensor Build Int64, Tensor Build Int64)

(batched_tensors, batch_index, id)

  • batched_tensors
  • batch_index
  • id

batchCholesky Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

batchCholesky' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

batchCholeskyGrad Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

l

-> Tensor v'2 t

grad

-> Tensor Build t

output

batchCholeskyGrad' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

l

-> Tensor v'2 t

grad

-> Tensor Build t

output

batchDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

batch_size

-> Tensor Build Variant

handle

batchDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

batch_size

-> Tensor Build Variant

handle

batchFFT Source #

Arguments

:: Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchFFT' Source #

Arguments

:: OpParams 
-> Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchFFT2D Source #

Arguments

:: Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchFFT2D' Source #

Arguments

:: OpParams 
-> Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchFFT3D Source #

Arguments

:: Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchFFT3D' Source #

Arguments

:: OpParams 
-> Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchIFFT Source #

Arguments

:: Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchIFFT' Source #

Arguments

:: OpParams 
-> Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchIFFT2D Source #

Arguments

:: Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchIFFT2D' Source #

Arguments

:: OpParams 
-> Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchIFFT3D Source #

Arguments

:: Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchIFFT3D' Source #

Arguments

:: OpParams 
-> Tensor v'1 (Complex Float)

input

-> Tensor Build (Complex Float)

output

batchMatMul Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

output

batchMatMul' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

output

batchMatrixBandPart Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor v'2 Int64

num_lower

-> Tensor v'3 Int64

num_upper

-> Tensor Build t

band

batchMatrixBandPart' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Int64

num_lower

-> Tensor v'3 Int64

num_upper

-> Tensor Build t

band

batchMatrixDiag Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

diagonal

-> Tensor Build t

output

batchMatrixDiag' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

diagonal

-> Tensor Build t

output

batchMatrixDiagPart Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor Build t

diagonal

batchMatrixDiagPart' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

diagonal

batchMatrixInverse Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

batchMatrixInverse' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

batchMatrixSetDiag Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor v'2 t

diagonal

-> Tensor Build t

output

batchMatrixSetDiag' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

diagonal

-> Tensor Build t

output

batchMatrixSolve Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor Build t

output

batchMatrixSolve' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor Build t

output

batchMatrixSolveLs Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor v'3 Double

l2_regularizer

-> Tensor Build t

output

batchMatrixSolveLs' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor v'3 Double

l2_regularizer

-> Tensor Build t

output

batchMatrixTriangularSolve Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor Build t

output

batchMatrixTriangularSolve' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor Build t

output

batchNormWithGlobalNormalization Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Bool

scale_after_normalization

-> Float

variance_epsilon

-> Tensor v'1 t

t

-> Tensor v'2 t

m

-> Tensor v'3 t

v

-> Tensor v'4 t

beta

-> Tensor v'5 t

gamma

-> Tensor Build t

result

batchNormWithGlobalNormalization' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Bool

scale_after_normalization

-> Float

variance_epsilon

-> Tensor v'1 t

t

-> Tensor v'2 t

m

-> Tensor v'3 t

v

-> Tensor v'4 t

beta

-> Tensor v'5 t

gamma

-> Tensor Build t

result

batchNormWithGlobalNormalizationGrad Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Bool

scale_after_normalization

-> Float

variance_epsilon

-> Tensor v'1 t

t

-> Tensor v'2 t

m

-> Tensor v'3 t

v

-> Tensor v'4 t

gamma

-> Tensor v'5 t

backprop

-> (Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t)

(dx, dm, dv, db, dg)

  • dx
  • dm
  • dv
  • db
  • dg

batchNormWithGlobalNormalizationGrad' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Bool

scale_after_normalization

-> Float

variance_epsilon

-> Tensor v'1 t

t

-> Tensor v'2 t

m

-> Tensor v'3 t

v

-> Tensor v'4 t

gamma

-> Tensor v'5 t

backprop

-> (Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t)

(dx, dm, dv, db, dg)

  • dx
  • dm
  • dv
  • db
  • dg

batchSelfAdjointEig Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

batchSelfAdjointEig' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

batchSelfAdjointEigV2 Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t)

(e, v)

  • e
  • v

batchSelfAdjointEigV2' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t)

(e, v)

  • e
  • v

batchSvd Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t, Tensor Build t)

(s, u, v)

  • s
  • u
  • v

batchSvd' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t, Tensor Build t)

(s, u, v)

  • s
  • u
  • v

batchToSpace Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tidx) 
=> Int64

block_size

-> Tensor v'1 t

input

-> Tensor v'2 tidx

crops

-> Tensor Build t

output

batchToSpace' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Int64

block_size

-> Tensor v'1 t

input

-> Tensor v'2 tidx

crops

-> Tensor Build t

output

batchToSpaceND Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tblock_shape, OneOf '[Int32, Int64] tcrops) 
=> Tensor v'1 t

input

-> Tensor v'2 tblock_shape

block_shape

-> Tensor v'3 tcrops

crops

-> Tensor Build t

output

batchToSpaceND' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tblock_shape, OneOf '[Int32, Int64] tcrops) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tblock_shape

block_shape

-> Tensor v'3 tcrops

crops

-> Tensor Build t

output

betainc Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

a

-> Tensor v'2 t

b

-> Tensor v'3 t

x

-> Tensor Build t

z

betainc' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

a

-> Tensor v'2 t

b

-> Tensor v'3 t

x

-> Tensor Build t

z

biasAdd Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

value

-> Tensor v'2 t

bias

-> Tensor Build t

output

biasAdd' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

value

-> Tensor v'2 t

bias

-> Tensor Build t

output

biasAddGrad Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

out_backprop

-> Tensor Build t

output

biasAddV1 Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

value

-> Tensor v'2 t

bias

-> Tensor Build t

output

biasAddV1' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

value

-> Tensor v'2 t

bias

-> Tensor Build t

output

bigQueryReader Source #

Arguments

:: MonadBuild m' 
=> Int64

timestamp_millis: Table snapshot timestamp in millis since epoch. Relative (negative or zero) snapshot times are not allowed. For more details, see 'Table Decorators' in BigQuery docs.

-> m' (Tensor Ref ByteString)

reader_handle: The handle to reference the Reader.

A Reader that outputs rows from a BigQuery table as tensorflow Examples.

bigQueryReader' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

timestamp_millis: Table snapshot timestamp in millis since epoch. Relative (negative or zero) snapshot times are not allowed. For more details, see 'Table Decorators' in BigQuery docs.

-> m' (Tensor Ref ByteString)

reader_handle: The handle to reference the Reader.

bincount Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> Tensor v'1 Int32

arr

-> Tensor v'2 Int32

size

-> Tensor v'3 t

weights

-> Tensor Build t

bins

bincount' Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int32

arr

-> Tensor v'2 Int32

size

-> Tensor v'3 t

weights

-> Tensor Build t

bins

bitwiseAnd Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

bitwiseAnd' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

bitwiseOr Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

bitwiseOr' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

bitwiseXor Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

bitwiseXor' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

boostedTreesCalculateBestGainsPerFeature Source #

Arguments

:: Int64

max_splits

-> Tensor v'1 Int32

node_id_range

-> [Tensor v'2 Float]

stats_summary_list

-> Tensor v'3 Float

l1

-> Tensor v'4 Float

l2

-> Tensor v'5 Float

tree_complexity

-> Tensor v'6 Float

min_node_weight

-> ([Tensor Build Int32], [Tensor Build Float], [Tensor Build Int32], [Tensor Build Float], [Tensor Build Float])

(node_ids_list, gains_list, thresholds_list, left_node_contribs_list, right_node_contribs_list)

  • node_ids_list
  • gains_list
  • thresholds_list
  • left_node_contribs_list
  • right_node_contribs_list

boostedTreesCalculateBestGainsPerFeature' Source #

Arguments

:: OpParams 
-> Int64

max_splits

-> Tensor v'1 Int32

node_id_range

-> [Tensor v'2 Float]

stats_summary_list

-> Tensor v'3 Float

l1

-> Tensor v'4 Float

l2

-> Tensor v'5 Float

tree_complexity

-> Tensor v'6 Float

min_node_weight

-> ([Tensor Build Int32], [Tensor Build Float], [Tensor Build Int32], [Tensor Build Float], [Tensor Build Float])

(node_ids_list, gains_list, thresholds_list, left_node_contribs_list, right_node_contribs_list)

  • node_ids_list
  • gains_list
  • thresholds_list
  • left_node_contribs_list
  • right_node_contribs_list

boostedTreesCreateEnsemble Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> Tensor v'2 Int64

stamp_token

-> Tensor v'3 ByteString

tree_ensemble_serialized

-> m' ControlNode 

boostedTreesCreateEnsemble' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> Tensor v'2 Int64

stamp_token

-> Tensor v'3 ByteString

tree_ensemble_serialized

-> m' ControlNode 

boostedTreesDeserializeEnsemble Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> Tensor v'2 Int64

stamp_token

-> Tensor v'3 ByteString

tree_ensemble_serialized

-> m' ControlNode 

boostedTreesDeserializeEnsemble' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> Tensor v'2 Int64

stamp_token

-> Tensor v'3 ByteString

tree_ensemble_serialized

-> m' ControlNode 

boostedTreesGetEnsembleStates Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> m' (Tensor Value Int64, Tensor Value Int32, Tensor Value Int32, Tensor Value Int32, Tensor Value Int32)

(stamp_token, num_trees, num_finalized_trees, num_attempted_layers, last_layer_nodes_range)

  • stamp_token
  • num_trees
  • num_finalized_trees
  • num_attempted_layers
  • last_layer_nodes_range

boostedTreesGetEnsembleStates' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> m' (Tensor Value Int64, Tensor Value Int32, Tensor Value Int32, Tensor Value Int32, Tensor Value Int32)

(stamp_token, num_trees, num_finalized_trees, num_attempted_layers, last_layer_nodes_range)

  • stamp_token
  • num_trees
  • num_finalized_trees
  • num_attempted_layers
  • last_layer_nodes_range

boostedTreesMakeStatsSummary Source #

Arguments

:: Int64

max_splits

-> Int64

num_buckets

-> Tensor v'1 Int32

node_ids

-> Tensor v'2 Float

gradients

-> Tensor v'3 Float

hessians

-> [Tensor v'4 Int32]

bucketized_features_list

-> Tensor Build Float

stats_summary

boostedTreesMakeStatsSummary' Source #

Arguments

:: OpParams 
-> Int64

max_splits

-> Int64

num_buckets

-> Tensor v'1 Int32

node_ids

-> Tensor v'2 Float

gradients

-> Tensor v'3 Float

hessians

-> [Tensor v'4 Int32]

bucketized_features_list

-> Tensor Build Float

stats_summary

boostedTreesPredict Source #

Arguments

:: MonadBuild m' 
=> Int64

logits_dimension

-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> [Tensor v'2 Int32]

bucketized_features

-> m' (Tensor Value Float)

logits

boostedTreesPredict' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

logits_dimension

-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> [Tensor v'2 Int32]

bucketized_features

-> m' (Tensor Value Float)

logits

boostedTreesSerializeEnsemble Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> m' (Tensor Value Int64, Tensor Value ByteString)

(stamp_token, tree_ensemble_serialized)

  • stamp_token
  • tree_ensemble_serialized

boostedTreesSerializeEnsemble' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> m' (Tensor Value Int64, Tensor Value ByteString)

(stamp_token, tree_ensemble_serialized)

  • stamp_token
  • tree_ensemble_serialized

boostedTreesTrainingPredict Source #

Arguments

:: MonadBuild m' 
=> Int64

logits_dimension

-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> Tensor v'2 Int32

cached_tree_ids

-> Tensor v'3 Int32

cached_node_ids

-> [Tensor v'4 Int32]

bucketized_features

-> m' (Tensor Value Float, Tensor Value Int32, Tensor Value Int32)

(partial_logits, tree_ids, node_ids)

  • partial_logits
  • tree_ids
  • node_ids

boostedTreesTrainingPredict' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

logits_dimension

-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> Tensor v'2 Int32

cached_tree_ids

-> Tensor v'3 Int32

cached_node_ids

-> [Tensor v'4 Int32]

bucketized_features

-> m' (Tensor Value Float, Tensor Value Int32, Tensor Value Int32)

(partial_logits, tree_ids, node_ids)

  • partial_logits
  • tree_ids
  • node_ids

boostedTreesUpdateEnsemble Source #

Arguments

:: MonadBuild m' 
=> Int64

pruning_mode

-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> Tensor v'2 Int32

feature_ids

-> [Tensor v'3 Int32]

node_ids

-> [Tensor v'4 Float]

gains

-> [Tensor v'5 Int32]

thresholds

-> [Tensor v'6 Float]

left_node_contribs

-> [Tensor v'7 Float]

right_node_contribs

-> Tensor v'8 Int32

max_depth

-> Tensor v'9 Float

learning_rate

-> m' ControlNode 

boostedTreesUpdateEnsemble' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

pruning_mode

-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> Tensor v'2 Int32

feature_ids

-> [Tensor v'3 Int32]

node_ids

-> [Tensor v'4 Float]

gains

-> [Tensor v'5 Int32]

thresholds

-> [Tensor v'6 Float]

left_node_contribs

-> [Tensor v'7 Float]

right_node_contribs

-> Tensor v'8 Int32

max_depth

-> Tensor v'9 Float

learning_rate

-> m' ControlNode 

broadcastArgs Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> Tensor v'1 t

s0

-> Tensor v'2 t

s1

-> Tensor Build t

r0

broadcastArgs' Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> OpParams 
-> Tensor v'1 t

s0

-> Tensor v'2 t

s1

-> Tensor Build t

r0

broadcastGradientArgs Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> Tensor v'1 t

s0

-> Tensor v'2 t

s1

-> (Tensor Build t, Tensor Build t)

(r0, r1)

  • r0
  • r1

broadcastGradientArgs' Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> OpParams 
-> Tensor v'1 t

s0

-> Tensor v'2 t

s1

-> (Tensor Build t, Tensor Build t)

(r0, r1)

  • r0
  • r1

broadcastTo Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

input

-> Tensor v'2 tidx

shape

-> Tensor Build t

output

broadcastTo' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tidx

shape

-> Tensor Build t

output

bucketize Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build Int32

output

bucketize' Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build Int32

output

bytesProducedStatsDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 ByteString

tag

-> Tensor Build Variant

handle

bytesProducedStatsDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 ByteString

tag

-> Tensor Build Variant

handle

cTCBeamSearchDecoder Source #

Arguments

:: Int64

beam_width

-> Int64

top_paths

-> Tensor v'1 Float

inputs

-> Tensor v'2 Int32

sequence_length

-> ([Tensor Build Int64], [Tensor Build Int64], [Tensor Build Int64], Tensor Build Float)

(decoded_indices, decoded_values, decoded_shape, log_probability)

  • decoded_indices
  • decoded_values
  • decoded_shape
  • log_probability

cTCBeamSearchDecoder' Source #

Arguments

:: OpParams 
-> Int64

beam_width

-> Int64

top_paths

-> Tensor v'1 Float

inputs

-> Tensor v'2 Int32

sequence_length

-> ([Tensor Build Int64], [Tensor Build Int64], [Tensor Build Int64], Tensor Build Float)

(decoded_indices, decoded_values, decoded_shape, log_probability)

  • decoded_indices
  • decoded_values
  • decoded_shape
  • log_probability

cTCGreedyDecoder Source #

Arguments

:: Tensor v'1 Float

inputs

-> Tensor v'2 Int32

sequence_length

-> (Tensor Build Int64, Tensor Build Int64, Tensor Build Int64, Tensor Build Float)

(decoded_indices, decoded_values, decoded_shape, log_probability)

  • decoded_indices
  • decoded_values
  • decoded_shape
  • log_probability

cTCGreedyDecoder' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

inputs

-> Tensor v'2 Int32

sequence_length

-> (Tensor Build Int64, Tensor Build Int64, Tensor Build Int64, Tensor Build Float)

(decoded_indices, decoded_values, decoded_shape, log_probability)

  • decoded_indices
  • decoded_values
  • decoded_shape
  • log_probability

cTCLoss Source #

Arguments

:: Tensor v'1 Float

inputs

-> Tensor v'2 Int64

labels_indices

-> Tensor v'3 Int32

labels_values

-> Tensor v'4 Int32

sequence_length

-> (Tensor Build Float, Tensor Build Float)

(loss, gradient)

  • loss
  • gradient

cTCLoss' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

inputs

-> Tensor v'2 Int64

labels_indices

-> Tensor v'3 Int32

labels_values

-> Tensor v'4 Int32

sequence_length

-> (Tensor Build Float, Tensor Build Float)

(loss, gradient)

  • loss
  • gradient

cacheDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 ByteString

filename

-> Tensor Build Variant

handle

cacheDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 ByteString

filename

-> Tensor Build Variant

handle

cast Source #

Arguments

:: (TensorType srcT, TensorType dstT) 
=> Tensor v'1 srcT

x

-> Tensor Build dstT

y

cast' Source #

Arguments

:: (TensorType srcT, TensorType dstT) 
=> OpParams 
-> Tensor v'1 srcT

x

-> Tensor Build dstT

y

ceil Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

ceil' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

checkNumerics Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

tensor

-> Tensor Build t

output

checkNumerics' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

tensor

-> Tensor Build t

output

cholesky Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

cholesky' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

choleskyGrad Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

l

-> Tensor v'2 t

grad

-> Tensor Build t

output

choleskyGrad' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

l

-> Tensor v'2 t

grad

-> Tensor Build t

output

clipByValue Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

t

-> Tensor v'2 t

clip_value_min

-> Tensor v'3 t

clip_value_max

-> Tensor Build t

output

clipByValue' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

t

-> Tensor v'2 t

clip_value_min

-> Tensor v'3 t

clip_value_max

-> Tensor Build t

output

collectiveBcastRecv Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64, Word16, Double, Float] t) 
=> Int64

group_key

-> Int64

group_size

-> Int64

instance_key

-> Shape

shape

-> m' (Tensor Value t)

data

collectiveBcastRecv' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64, Word16, Double, Float] t) 
=> OpParams 
-> Int64

group_key

-> Int64

group_size

-> Int64

instance_key

-> Shape

shape

-> m' (Tensor Value t)

data

collectiveBcastSend Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64, Word16, Double, Float] t) 
=> Int64

group_key

-> Int64

group_size

-> Int64

instance_key

-> Shape

shape

-> Tensor v'1 t

input

-> m' (Tensor Value t)

data

collectiveBcastSend' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64, Word16, Double, Float] t) 
=> OpParams 
-> Int64

group_key

-> Int64

group_size

-> Int64

instance_key

-> Shape

shape

-> Tensor v'1 t

input

-> m' (Tensor Value t)

data

collectiveReduce Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64, Word16, Double, Float] t) 
=> Int64

group_key

-> Int64

group_size

-> Int64

instance_key

-> Tensor v'1 t

input

-> m' (Tensor Value t)

data

collectiveReduce' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64, Word16, Double, Float] t) 
=> OpParams 
-> Int64

group_key

-> Int64

group_size

-> Int64

instance_key

-> Tensor v'1 t

input

-> m' (Tensor Value t)

data

compareAndBitpack Source #

Arguments

:: OneOf '[Bool, Int16, Int32, Int64, Int8, Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

threshold

-> Tensor Build Word8

output

compareAndBitpack' Source #

Arguments

:: OneOf '[Bool, Int16, Int32, Int64, Int8, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

threshold

-> Tensor Build Word8

output

complex Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Complex Double, Complex Float] tout) 
=> Tensor v'1 t

real

-> Tensor v'2 t

imag

-> Tensor Build tout

out

complex' Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Complex Double, Complex Float] tout) 
=> OpParams 
-> Tensor v'1 t

real

-> Tensor v'2 t

imag

-> Tensor Build tout

out

complexAbs Source #

Arguments

:: (OneOf '[Complex Double, Complex Float] t, OneOf '[Double, Float] tout) 
=> Tensor v'1 t

x

-> Tensor Build tout

y

complexAbs' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float] t, OneOf '[Double, Float] tout) 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build tout

y

computeAccidentalHits Source #

Arguments

:: Int64

num_true

-> Tensor v'1 Int64

true_classes

-> Tensor v'2 Int64

sampled_candidates

-> (Tensor Build Int32, Tensor Build Int64, Tensor Build Float)

(indices, ids, weights)

  • indices
  • ids
  • weights

computeAccidentalHits' Source #

Arguments

:: OpParams 
-> Int64

num_true

-> Tensor v'1 Int64

true_classes

-> Tensor v'2 Int64

sampled_candidates

-> (Tensor Build Int32, Tensor Build Int64, Tensor Build Float)

(indices, ids, weights)

  • indices
  • ids
  • weights

concat Source #

Arguments

:: TensorType t 
=> Tensor v'1 Int32

concat_dim

-> [Tensor v'2 t]

values

-> Tensor Build t

output

concat' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 Int32

concat_dim

-> [Tensor v'2 t]

values

-> Tensor Build t

output

concatOffset Source #

Arguments

:: Tensor v'1 Int32

concat_dim

-> [Tensor v'2 Int32]

shape

-> [Tensor Build Int32]

offset

concatOffset' Source #

Arguments

:: OpParams 
-> Tensor v'1 Int32

concat_dim

-> [Tensor v'2 Int32]

shape

-> [Tensor Build Int32]

offset

concatV2 Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tidx) 
=> [Tensor v'1 t]

values

-> Tensor v'2 tidx

axis

-> Tensor Build t

output

concatV2' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> [Tensor v'1 t]

values

-> Tensor v'2 tidx

axis

-> Tensor Build t

output

concatenateDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Variant

another_dataset

-> Tensor Build Variant

handle

concatenateDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Variant

another_dataset

-> Tensor Build Variant

handle

conditionalAccumulator Source #

Arguments

:: MonadBuild m' 
=> DataType

dtype

-> Shape

shape

-> m' (Tensor Ref ByteString)

handle

conditionalAccumulator' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

dtype

-> Shape

shape

-> m' (Tensor Ref ByteString)

handle

configureDistributedTPU Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Value ByteString)

topology: A serialized tensorflow.tpu.TopologyProto that describes the TPU topology.

An op that sets up the centralized structures for a distributed TPU

system.

configureDistributedTPU' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Value ByteString)

topology: A serialized tensorflow.tpu.TopologyProto that describes the TPU topology.

conj Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Variant] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

conj' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Variant] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

conjugateTranspose Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tperm) 
=> Tensor v'1 t

x

-> Tensor v'2 tperm

perm

-> Tensor Build t

y

conjugateTranspose' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tperm) 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 tperm

perm

-> Tensor Build t

y

const Source #

Arguments

:: TensorType dtype 
=> Tensor Build dtype

output

const' Source #

Arguments

:: TensorType dtype 
=> OpParams 
-> Tensor Build dtype

output

consumeMutexLock Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 Variant

mutex_lock

-> m' ControlNode 

consumeMutexLock' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 Variant

mutex_lock

-> m' ControlNode 

conv2D Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor Build t

output

conv2D' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor Build t

output

conv2DBackpropFilter Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 Int32

filter_sizes

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv2DBackpropFilter' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Int32

filter_sizes

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv2DBackpropInput Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 Int32

input_sizes

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv2DBackpropInput' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int32

input_sizes

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv3D Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor Build t

output

conv3D' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor Build t

output

conv3DBackpropFilter Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv3DBackpropFilter' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv3DBackpropFilterV2 Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 Int32

filter_sizes

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv3DBackpropFilterV2' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Int32

filter_sizes

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv3DBackpropInput Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv3DBackpropInput' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv3DBackpropInputV2 Source #

Arguments

:: (OneOf '[Word16, Double, Float] t, OneOf '[Int32, Int64] tshape) 
=> Tensor v'1 tshape

input_sizes

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

conv3DBackpropInputV2' Source #

Arguments

:: (OneOf '[Word16, Double, Float] t, OneOf '[Int32, Int64] tshape) 
=> OpParams 
-> Tensor v'1 tshape

input_sizes

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

copy Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input: Input tensor.

-> Tensor Build t

output: Output tensor, deep-copied from input.

Copy Op.

Performs CPU-to-CPU or GPU-to-GPU deep-copying of tensor, depending on the device on which the tensor is allocated. N.B.: If the all downstream attached debug ops are disabled given the current gRPC gating status, the output will simply forward the input tensor without deep-copying. See the documentation of Debug* ops for more details.

Unlike the CopyHost Op, this op does not have HostMemory constraint on its input or output.

copy' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input: Input tensor.

-> Tensor Build t

output: Output tensor, deep-copied from input.

copyHost Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input: Input tensor.

-> Tensor Build t

output: Output tensor, deep-copied from input.

Copy Host Op.

Performs CPU-to-CPU deep-copying of tensor. N.B.: If the all downstream attached debug ops are disabled given the current gRPC gating status, the output will simply forward the input tensor without deep-copying. See the documentation of Debug* ops for more details.

Unlike the Copy Op, this op has HostMemory constraint on its input or output.

copyHost' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input: Input tensor.

-> Tensor Build t

output: Output tensor, deep-copied from input.

countUpTo Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] t) 
=> Int64

limit

-> Tensor Ref t

ref

-> m' (Tensor Value t)

output

countUpTo' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] t) 
=> OpParams 
-> Int64

limit

-> Tensor Ref t

ref

-> m' (Tensor Value t)

output

createSummaryDbWriter Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 ByteString

db_uri

-> Tensor v'3 ByteString

experiment_name

-> Tensor v'4 ByteString

run_name

-> Tensor v'5 ByteString

user_name

-> m' ControlNode 

createSummaryDbWriter' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 ByteString

db_uri

-> Tensor v'3 ByteString

experiment_name

-> Tensor v'4 ByteString

run_name

-> Tensor v'5 ByteString

user_name

-> m' ControlNode 

createSummaryFileWriter Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 ByteString

logdir

-> Tensor v'3 Int32

max_queue

-> Tensor v'4 Int32

flush_millis

-> Tensor v'5 ByteString

filename_suffix

-> m' ControlNode 

createSummaryFileWriter' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 ByteString

logdir

-> Tensor v'3 Int32

max_queue

-> Tensor v'4 Int32

flush_millis

-> Tensor v'5 ByteString

filename_suffix

-> m' ControlNode 

cropAndResize Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

image

-> Tensor v'2 Float

boxes

-> Tensor v'3 Int32

box_ind

-> Tensor v'4 Int32

crop_size

-> Tensor Build Float

crops

cropAndResize' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

image

-> Tensor v'2 Float

boxes

-> Tensor v'3 Int32

box_ind

-> Tensor v'4 Int32

crop_size

-> Tensor Build Float

crops

cropAndResizeGradBoxes Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 Float

grads

-> Tensor v'2 t

image

-> Tensor v'3 Float

boxes

-> Tensor v'4 Int32

box_ind

-> Tensor Build Float

output

cropAndResizeGradBoxes' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 Float

grads

-> Tensor v'2 t

image

-> Tensor v'3 Float

boxes

-> Tensor v'4 Int32

box_ind

-> Tensor Build Float

output

cropAndResizeGradImage Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 Float

grads

-> Tensor v'2 Float

boxes

-> Tensor v'3 Int32

box_ind

-> Tensor v'4 Int32

image_size

-> Tensor Build t

output

cropAndResizeGradImage' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 Float

grads

-> Tensor v'2 Float

boxes

-> Tensor v'3 Int32

box_ind

-> Tensor v'4 Int32

image_size

-> Tensor Build t

output

cross Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

a

-> Tensor v'2 t

b

-> Tensor Build t

product

cross' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

a

-> Tensor v'2 t

b

-> Tensor Build t

product

crossReplicaSum Source #

Arguments

:: OneOf '[Word16, Float] t 
=> Tensor v'1 t

input: The local input to the sum.

-> Tensor Build t

output: The sum of all the distributed inputs.

An Op to sum inputs across replicated TPU instances. Each

instance supplies its own input, and the output of each is the sum of all the inputs.

crossReplicaSum' Source #

Arguments

:: OneOf '[Word16, Float] t 
=> OpParams 
-> Tensor v'1 t

input: The local input to the sum.

-> Tensor Build t

output: The sum of all the distributed inputs.

cudnnRNN Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] t) 
=> Tensor v'1 t

input

-> Tensor v'2 t

input_h

-> Tensor v'3 t

input_c

-> Tensor v'4 t

params

-> m' (Tensor Value t, Tensor Value t, Tensor Value t, Tensor Value t)

(output, output_h, output_c, reserve_space)

  • output
  • output_h
  • output_c
  • reserve_space

cudnnRNN' Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] t) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

input_h

-> Tensor v'3 t

input_c

-> Tensor v'4 t

params

-> m' (Tensor Value t, Tensor Value t, Tensor Value t, Tensor Value t)

(output, output_h, output_c, reserve_space)

  • output
  • output_h
  • output_c
  • reserve_space

cudnnRNNBackprop Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] t) 
=> Tensor v'1 t

input

-> Tensor v'2 t

input_h

-> Tensor v'3 t

input_c

-> Tensor v'4 t

params

-> Tensor v'5 t

output

-> Tensor v'6 t

output_h

-> Tensor v'7 t

output_c

-> Tensor v'8 t

output_backprop

-> Tensor v'9 t

output_h_backprop

-> Tensor v'10 t

output_c_backprop

-> Tensor v'11 t

reserve_space

-> m' (Tensor Value t, Tensor Value t, Tensor Value t, Tensor Value t)

(input_backprop, input_h_backprop, input_c_backprop, params_backprop)

  • input_backprop
  • input_h_backprop
  • input_c_backprop
  • params_backprop

cudnnRNNBackprop' Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] t) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

input_h

-> Tensor v'3 t

input_c

-> Tensor v'4 t

params

-> Tensor v'5 t

output

-> Tensor v'6 t

output_h

-> Tensor v'7 t

output_c

-> Tensor v'8 t

output_backprop

-> Tensor v'9 t

output_h_backprop

-> Tensor v'10 t

output_c_backprop

-> Tensor v'11 t

reserve_space

-> m' (Tensor Value t, Tensor Value t, Tensor Value t, Tensor Value t)

(input_backprop, input_h_backprop, input_c_backprop, params_backprop)

  • input_backprop
  • input_h_backprop
  • input_c_backprop
  • params_backprop

cudnnRNNBackpropV2 Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] t) 
=> Tensor v'1 t

input

-> Tensor v'2 t

input_h

-> Tensor v'3 t

input_c

-> Tensor v'4 t

params

-> Tensor v'5 t

output

-> Tensor v'6 t

output_h

-> Tensor v'7 t

output_c

-> Tensor v'8 t

output_backprop

-> Tensor v'9 t

output_h_backprop

-> Tensor v'10 t

output_c_backprop

-> Tensor v'11 t

reserve_space

-> Tensor v'12 Int8

host_reserved

-> m' (Tensor Value t, Tensor Value t, Tensor Value t, Tensor Value t)

(input_backprop, input_h_backprop, input_c_backprop, params_backprop)

  • input_backprop
  • input_h_backprop
  • input_c_backprop
  • params_backprop

cudnnRNNBackpropV2' Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] t) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

input_h

-> Tensor v'3 t

input_c

-> Tensor v'4 t

params

-> Tensor v'5 t

output

-> Tensor v'6 t

output_h

-> Tensor v'7 t

output_c

-> Tensor v'8 t

output_backprop

-> Tensor v'9 t

output_h_backprop

-> Tensor v'10 t

output_c_backprop

-> Tensor v'11 t

reserve_space

-> Tensor v'12 Int8

host_reserved

-> m' (Tensor Value t, Tensor Value t, Tensor Value t, Tensor Value t)

(input_backprop, input_h_backprop, input_c_backprop, params_backprop)

  • input_backprop
  • input_h_backprop
  • input_c_backprop
  • params_backprop

cudnnRNNCanonicalToParams Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 Int32

num_layers

-> Tensor v'2 Int32

num_units

-> Tensor v'3 Int32

input_size

-> [Tensor v'4 t]

weights

-> [Tensor v'5 t]

biases

-> Tensor Build t

params

cudnnRNNCanonicalToParams' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int32

num_layers

-> Tensor v'2 Int32

num_units

-> Tensor v'3 Int32

input_size

-> [Tensor v'4 t]

weights

-> [Tensor v'5 t]

biases

-> Tensor Build t

params

cudnnRNNParamsSize Source #

Arguments

:: OneOf '[Int32, Int64] s 
=> DataType

T

-> Tensor v'1 Int32

num_layers

-> Tensor v'2 Int32

num_units

-> Tensor v'3 Int32

input_size

-> Tensor Build s

params_size

cudnnRNNParamsSize' Source #

Arguments

:: OneOf '[Int32, Int64] s 
=> OpParams 
-> DataType

T

-> Tensor v'1 Int32

num_layers

-> Tensor v'2 Int32

num_units

-> Tensor v'3 Int32

input_size

-> Tensor Build s

params_size

cudnnRNNParamsToCanonical Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Int64

num_params

-> Tensor v'1 Int32

num_layers

-> Tensor v'2 Int32

num_units

-> Tensor v'3 Int32

input_size

-> Tensor v'4 t

params

-> ([Tensor Build t], [Tensor Build t])

(weights, biases)

  • weights
  • biases

cudnnRNNParamsToCanonical' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Int64

num_params

-> Tensor v'1 Int32

num_layers

-> Tensor v'2 Int32

num_units

-> Tensor v'3 Int32

input_size

-> Tensor v'4 t

params

-> ([Tensor Build t], [Tensor Build t])

(weights, biases)

  • weights
  • biases

cudnnRNNV2 Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] t) 
=> Tensor v'1 t

input

-> Tensor v'2 t

input_h

-> Tensor v'3 t

input_c

-> Tensor v'4 t

params

-> m' (Tensor Value t, Tensor Value t, Tensor Value t, Tensor Value t, Tensor Value Int8)

(output, output_h, output_c, reserve_space, host_reserved)

  • output
  • output_h
  • output_c
  • reserve_space
  • host_reserved

cudnnRNNV2' Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] t) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

input_h

-> Tensor v'3 t

input_c

-> Tensor v'4 t

params

-> m' (Tensor Value t, Tensor Value t, Tensor Value t, Tensor Value t, Tensor Value Int8)

(output, output_h, output_c, reserve_space, host_reserved)

  • output
  • output_h
  • output_c
  • reserve_space
  • host_reserved

cumprod Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

x

-> Tensor v'2 tidx

axis

-> Tensor Build t

out

cumprod' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 tidx

axis

-> Tensor Build t

out

cumsum Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

x

-> Tensor v'2 tidx

axis

-> Tensor Build t

out

cumsum' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 tidx

axis

-> Tensor Build t

out

dataFormatDimMap Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

dataFormatDimMap' Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

dataFormatVecPermute Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

dataFormatVecPermute' Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

datasetToSingleElement Source #

Arguments

:: TensorTypes output_types 
=> Tensor v'1 Variant

dataset

-> TensorList Build output_types

components

datasetToSingleElement' Source #

Arguments

:: TensorTypes output_types 
=> OpParams 
-> Tensor v'1 Variant

dataset

-> TensorList Build output_types

components

datasetToTFRecord Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 Variant

input_dataset

-> Tensor v'2 ByteString

filename

-> Tensor v'3 ByteString

compression_type

-> m' ControlNode 

datasetToTFRecord' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 ByteString

filename

-> Tensor v'3 ByteString

compression_type

-> m' ControlNode 

debugGradientIdentity Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor Build t

output

debugGradientIdentity' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

debugGradientRefIdentity Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref t

input

-> m' (Tensor Ref t)

output

debugGradientRefIdentity' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref t

input

-> m' (Tensor Ref t)

output

debugIdentity Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input: Input tensor, non-Reference type.

-> Tensor Build t

output: Output tensor that equals the input tensor.

Debug Identity Op.

Provides an identity mapping of the non-Ref type input tensor for debugging.

debugIdentity' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input: Input tensor, non-Reference type.

-> Tensor Build t

output: Output tensor that equals the input tensor.

debugNanCount Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input: Input tensor, non-Reference type.

-> Tensor Build Int64

output: An integer output tensor that is the number of NaNs in the input.

Debug NaN Value Counter Op

Counts number of NaNs in the input tensor, for debugging.

debugNanCount' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input: Input tensor, non-Reference type.

-> Tensor Build Int64

output: An integer output tensor that is the number of NaNs in the input.

debugNumericSummary Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input: Input tensor, non-Reference type, float or double.

-> Tensor Build Double

output: A double tensor of shape [14 + nDimensions], where nDimensions is the the number of dimensions of the tensor's shape. The elements of output are: [0]: is initialized (1.0) or not (0.0). [1]: total number of elements [2]: NaN element count [3]: generalized -inf count: elements <= lower_bound. lower_bound is -inf by default. [4]: negative element count (excluding -inf), if lower_bound is the default -inf. Otherwise, this is the count of elements > lower_bound and < 0. [5]: zero element count [6]: positive element count (excluding +inf), if upper_bound is the default -inf. Otherwise, this is the count of elements and 0. [7]: generalized +inf count, elements >= upper_bound. upper_bound is +inf by default. Output elements [1:8] are all zero, if the tensor is uninitialized. [8]: minimum of all non-inf and non-NaN elements. If uninitialized or no such element exists: +inf. [9]: maximum of all non-inf and non-NaN elements. If uninitialized or no such element exists: -inf. [10]: mean of all non-inf and non-NaN elements. If uninitialized or no such element exists: NaN. [11]: variance of all non-inf and non-NaN elements. If uninitialized or no such element exists: NaN. [12]: Data type of the tensor encoded as an enum integer. See the DataType proto for more details. [13]: Number of dimensions of the tensor (ndims). [14+]: Sizes of the dimensions.

Debug Numeric Summary Op.

Provide a basic summary of numeric value types, range and distribution.

debugNumericSummary' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input: Input tensor, non-Reference type, float or double.

-> Tensor Build Double

output: A double tensor of shape [14 + nDimensions], where nDimensions is the the number of dimensions of the tensor's shape. The elements of output are: [0]: is initialized (1.0) or not (0.0). [1]: total number of elements [2]: NaN element count [3]: generalized -inf count: elements <= lower_bound. lower_bound is -inf by default. [4]: negative element count (excluding -inf), if lower_bound is the default -inf. Otherwise, this is the count of elements > lower_bound and < 0. [5]: zero element count [6]: positive element count (excluding +inf), if upper_bound is the default -inf. Otherwise, this is the count of elements and 0. [7]: generalized +inf count, elements >= upper_bound. upper_bound is +inf by default. Output elements [1:8] are all zero, if the tensor is uninitialized. [8]: minimum of all non-inf and non-NaN elements. If uninitialized or no such element exists: +inf. [9]: maximum of all non-inf and non-NaN elements. If uninitialized or no such element exists: -inf. [10]: mean of all non-inf and non-NaN elements. If uninitialized or no such element exists: NaN. [11]: variance of all non-inf and non-NaN elements. If uninitialized or no such element exists: NaN. [12]: Data type of the tensor encoded as an enum integer. See the DataType proto for more details. [13]: Number of dimensions of the tensor (ndims). [14+]: Sizes of the dimensions.

decodeAndCropJpeg Source #

Arguments

:: Tensor v'1 ByteString

contents

-> Tensor v'2 Int32

crop_window

-> Tensor Build Word8

image

decodeAndCropJpeg' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

contents

-> Tensor v'2 Int32

crop_window

-> Tensor Build Word8

image

decodeBmp Source #

Arguments

:: Tensor v'1 ByteString

contents

-> Tensor Build Word8

image

decodeBmp' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

contents

-> Tensor Build Word8

image

decodeCSV Source #

Arguments

:: OneOfs '[ByteString, Int32, Int64, Double, Float] oUT_TYPE 
=> Tensor v'1 ByteString

records

-> TensorList v'2 oUT_TYPE

record_defaults

-> TensorList Build oUT_TYPE

output

decodeCSV' Source #

Arguments

:: OneOfs '[ByteString, Int32, Int64, Double, Float] oUT_TYPE 
=> OpParams 
-> Tensor v'1 ByteString

records

-> TensorList v'2 oUT_TYPE

record_defaults

-> TensorList Build oUT_TYPE

output

decodeGif Source #

Arguments

:: Tensor v'1 ByteString

contents

-> Tensor Build Word8

image

decodeGif' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

contents

-> Tensor Build Word8

image

decodeJSONExample Source #

Arguments

:: Tensor v'1 ByteString

json_examples

-> Tensor Build ByteString

binary_examples

decodeJSONExample' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

json_examples

-> Tensor Build ByteString

binary_examples

decodeJpeg Source #

Arguments

:: Tensor v'1 ByteString

contents

-> Tensor Build Word8

image

decodeJpeg' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

contents

-> Tensor Build Word8

image

decodePng Source #

Arguments

:: OneOf '[Word16, Word8] dtype 
=> Tensor v'1 ByteString

contents

-> Tensor Build dtype

image

decodePng' Source #

Arguments

:: OneOf '[Word16, Word8] dtype 
=> OpParams 
-> Tensor v'1 ByteString

contents

-> Tensor Build dtype

image

decodeProtoV2 Source #

Arguments

:: TensorTypes output_types 
=> Tensor v'1 ByteString

bytes

-> (Tensor Build Int32, TensorList Build output_types)

(sizes, values)

  • sizes
  • values

decodeProtoV2' Source #

Arguments

:: TensorTypes output_types 
=> OpParams 
-> Tensor v'1 ByteString

bytes

-> (Tensor Build Int32, TensorList Build output_types)

(sizes, values)

  • sizes
  • values

decodeRaw Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] out_type 
=> Tensor v'1 ByteString

bytes

-> Tensor Build out_type

output

decodeRaw' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] out_type 
=> OpParams 
-> Tensor v'1 ByteString

bytes

-> Tensor Build out_type

output

decodeWav Source #

Arguments

:: Tensor v'1 ByteString

contents

-> (Tensor Build Float, Tensor Build Int32)

(audio, sample_rate)

  • audio
  • sample_rate

decodeWav' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

contents

-> (Tensor Build Float, Tensor Build Int32)

(audio, sample_rate)

  • audio
  • sample_rate

deepCopy Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 t

x

-> m' (Tensor Value t)

y

deepCopy' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 t

x

-> m' (Tensor Value t)

y

denseToDenseSetOperation Source #

Arguments

:: OneOf '[ByteString, Int16, Int32, Int64, Int8, Word16, Word8] t 
=> Tensor v'1 t

set1

-> Tensor v'2 t

set2

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(result_indices, result_values, result_shape)

  • result_indices
  • result_values
  • result_shape

denseToDenseSetOperation' Source #

Arguments

:: OneOf '[ByteString, Int16, Int32, Int64, Int8, Word16, Word8] t 
=> OpParams 
-> Tensor v'1 t

set1

-> Tensor v'2 t

set2

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(result_indices, result_values, result_shape)

  • result_indices
  • result_values
  • result_shape

denseToSparseBatchDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

batch_size

-> Tensor v'3 Int64

row_shape

-> Tensor Build Variant

handle

denseToSparseBatchDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

batch_size

-> Tensor v'3 Int64

row_shape

-> Tensor Build Variant

handle

denseToSparseSetOperation Source #

Arguments

:: OneOf '[ByteString, Int16, Int32, Int64, Int8, Word16, Word8] t 
=> Tensor v'1 t

set1

-> Tensor v'2 Int64

set2_indices

-> Tensor v'3 t

set2_values

-> Tensor v'4 Int64

set2_shape

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(result_indices, result_values, result_shape)

  • result_indices
  • result_values
  • result_shape

denseToSparseSetOperation' Source #

Arguments

:: OneOf '[ByteString, Int16, Int32, Int64, Int8, Word16, Word8] t 
=> OpParams 
-> Tensor v'1 t

set1

-> Tensor v'2 Int64

set2_indices

-> Tensor v'3 t

set2_values

-> Tensor v'4 Int64

set2_shape

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(result_indices, result_values, result_shape)

  • result_indices
  • result_values
  • result_shape

depthToSpace Source #

Arguments

:: TensorType t 
=> Int64

block_size

-> Tensor v'1 t

input

-> Tensor Build t

output

depthToSpace' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Int64

block_size

-> Tensor v'1 t

input

-> Tensor Build t

output

depthwiseConv2dNative Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor Build t

output

depthwiseConv2dNative' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor Build t

output

depthwiseConv2dNativeBackpropFilter Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 Int32

filter_sizes

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

depthwiseConv2dNativeBackpropFilter' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Int32

filter_sizes

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

depthwiseConv2dNativeBackpropInput Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 Int32

input_sizes

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

depthwiseConv2dNativeBackpropInput' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int32

input_sizes

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

output

dequantize Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] t 
=> Tensor v'1 t

input

-> Tensor v'2 Float

min_range

-> Tensor v'3 Float

max_range

-> Tensor Build Float

output

dequantize' Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Float

min_range

-> Tensor v'3 Float

max_range

-> Tensor Build Float

output

deserializeIterator Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

resource_handle

-> Tensor v'2 Variant

serialized

-> m' ControlNode 

deserializeIterator' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource_handle

-> Tensor v'2 Variant

serialized

-> m' ControlNode 

deserializeManySparse Source #

Arguments

:: TensorType dtype 
=> Tensor v'1 ByteString

serialized_sparse

-> (Tensor Build Int64, Tensor Build dtype, Tensor Build Int64)

(sparse_indices, sparse_values, sparse_shape)

  • sparse_indices
  • sparse_values
  • sparse_shape

deserializeManySparse' Source #

Arguments

:: TensorType dtype 
=> OpParams 
-> Tensor v'1 ByteString

serialized_sparse

-> (Tensor Build Int64, Tensor Build dtype, Tensor Build Int64)

(sparse_indices, sparse_values, sparse_shape)

  • sparse_indices
  • sparse_values
  • sparse_shape

deserializeSparse Source #

Arguments

:: (TensorType dtype, OneOf '[ByteString, Variant] tserialized) 
=> Tensor v'1 tserialized

serialized_sparse

-> (Tensor Build Int64, Tensor Build dtype, Tensor Build Int64)

(sparse_indices, sparse_values, sparse_shape)

  • sparse_indices
  • sparse_values
  • sparse_shape

deserializeSparse' Source #

Arguments

:: (TensorType dtype, OneOf '[ByteString, Variant] tserialized) 
=> OpParams 
-> Tensor v'1 tserialized

serialized_sparse

-> (Tensor Build Int64, Tensor Build dtype, Tensor Build Int64)

(sparse_indices, sparse_values, sparse_shape)

  • sparse_indices
  • sparse_values
  • sparse_shape

destroyTemporaryVariable Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref t

ref

-> m' (Tensor Value t)

value

destroyTemporaryVariable' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref t

ref

-> m' (Tensor Value t)

value

diag Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

diagonal

-> Tensor Build t

output

diag' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

diagonal

-> Tensor Build t

output

diagPart Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

diagonal

diagPart' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

diagonal

digamma Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

digamma' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

dilation2D Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor Build t

output

dilation2D' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor Build t

output

dilation2DBackpropFilter Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

filter_backprop

dilation2DBackpropFilter' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

filter_backprop

dilation2DBackpropInput Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

in_backprop

dilation2DBackpropInput' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

filter

-> Tensor v'3 t

out_backprop

-> Tensor Build t

in_backprop

drawBoundingBoxes Source #

Arguments

:: OneOf '[Word16, Float] t 
=> Tensor v'1 t

images

-> Tensor v'2 Float

boxes

-> Tensor Build t

output

drawBoundingBoxes' Source #

Arguments

:: OneOf '[Word16, Float] t 
=> OpParams 
-> Tensor v'1 t

images

-> Tensor v'2 Float

boxes

-> Tensor Build t

output

dynamicPartition Source #

Arguments

:: TensorType t 
=> Int64

num_partitions

-> Tensor v'1 t

data

-> Tensor v'2 Int32

partitions

-> [Tensor Build t]

outputs

dynamicPartition' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Int64

num_partitions

-> Tensor v'1 t

data

-> Tensor v'2 Int32

partitions

-> [Tensor Build t]

outputs

dynamicStitch Source #

Arguments

:: TensorType t 
=> [Tensor v'1 Int32]

indices

-> [Tensor v'2 t]

data

-> Tensor Build t

merged

dynamicStitch' Source #

Arguments

:: TensorType t 
=> OpParams 
-> [Tensor v'1 Int32]

indices

-> [Tensor v'2 t]

data

-> Tensor Build t

merged

editDistance Source #

Arguments

:: TensorType t 
=> Tensor v'1 Int64

hypothesis_indices

-> Tensor v'2 t

hypothesis_values

-> Tensor v'3 Int64

hypothesis_shape

-> Tensor v'4 Int64

truth_indices

-> Tensor v'5 t

truth_values

-> Tensor v'6 Int64

truth_shape

-> Tensor Build Float

output

editDistance' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 Int64

hypothesis_indices

-> Tensor v'2 t

hypothesis_values

-> Tensor v'3 Int64

hypothesis_shape

-> Tensor v'4 Int64

truth_indices

-> Tensor v'5 t

truth_values

-> Tensor v'6 Int64

truth_shape

-> Tensor Build Float

output

elu Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

features

-> Tensor Build t

activations

elu' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

features

-> Tensor Build t

activations

eluGrad Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

gradients

-> Tensor v'2 t

outputs

-> Tensor Build t

backprops

eluGrad' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

gradients

-> Tensor v'2 t

outputs

-> Tensor Build t

backprops

empty Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 Int32

shape

-> m' (Tensor Value dtype)

output

empty' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 Int32

shape

-> m' (Tensor Value dtype)

output

emptyTensorList Source #

Arguments

:: OneOf '[Int32, Int64] shape_type 
=> DataType

element_dtype

-> Tensor v'1 shape_type

element_shape

-> Tensor Build Variant

handle

emptyTensorList' Source #

Arguments

:: OneOf '[Int32, Int64] shape_type 
=> OpParams 
-> DataType

element_dtype

-> Tensor v'1 shape_type

element_shape

-> Tensor Build Variant

handle

encodeJpeg Source #

Arguments

:: Tensor v'1 Word8

image

-> Tensor Build ByteString

contents

encodeJpeg' Source #

Arguments

:: OpParams 
-> Tensor v'1 Word8

image

-> Tensor Build ByteString

contents

encodePng Source #

Arguments

:: OneOf '[Word16, Word8] t 
=> Tensor v'1 t

image

-> Tensor Build ByteString

contents

encodePng' Source #

Arguments

:: OneOf '[Word16, Word8] t 
=> OpParams 
-> Tensor v'1 t

image

-> Tensor Build ByteString

contents

encodeProto Source #

Arguments

:: TensorTypes tinput_types 
=> Tensor v'1 Int32

sizes

-> TensorList v'2 tinput_types

values

-> Tensor Build ByteString

bytes

encodeProto' Source #

Arguments

:: TensorTypes tinput_types 
=> OpParams 
-> Tensor v'1 Int32

sizes

-> TensorList v'2 tinput_types

values

-> Tensor Build ByteString

bytes

encodeWav Source #

Arguments

:: Tensor v'1 Float

audio

-> Tensor v'2 Int32

sample_rate

-> Tensor Build ByteString

contents

encodeWav' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

audio

-> Tensor v'2 Int32

sample_rate

-> Tensor Build ByteString

contents

enqueueInQueueDataset Source #

Arguments

:: (MonadBuild m', TensorTypes tcomponents) 
=> Tensor v'1 Variant

queue

-> TensorList v'2 tcomponents

components

-> m' ControlNode 

enqueueInQueueDataset' Source #

Arguments

:: (MonadBuild m', TensorTypes tcomponents) 
=> OpParams 
-> Tensor v'1 Variant

queue

-> TensorList v'2 tcomponents

components

-> m' ControlNode 

enter Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

data

-> Tensor Build t

output

enter' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor Build t

output

erf Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

erf' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

erfc Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

erfc' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

exit Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

data

-> Tensor Build t

output

exit' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor Build t

output

expandDims Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tdim) 
=> Tensor v'1 t

input

-> Tensor v'2 tdim

dim

-> Tensor Build t

output

expandDims' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tdim) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tdim

dim

-> Tensor Build t

output

extractGlimpse Source #

Arguments

:: Tensor v'1 Float

input

-> Tensor v'2 Int32

size

-> Tensor v'3 Float

offsets

-> Tensor Build Float

glimpse

extractGlimpse' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

input

-> Tensor v'2 Int32

size

-> Tensor v'3 Float

offsets

-> Tensor Build Float

glimpse

extractImagePatches Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

images

-> Tensor Build t

patches

extractJpegShape Source #

Arguments

:: OneOf '[Int32, Int64] output_type 
=> Tensor v'1 ByteString

contents

-> Tensor Build output_type

image_shape

extractJpegShape' Source #

Arguments

:: OneOf '[Int32, Int64] output_type 
=> OpParams 
-> Tensor v'1 ByteString

contents

-> Tensor Build output_type

image_shape

fFT Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

fFT' Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> OpParams 
-> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

fFT2D Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

fFT2D' Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> OpParams 
-> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

fFT3D Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

fFT3D' Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> OpParams 
-> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

fIFOQueue Source #

Arguments

:: MonadBuild m' 
=> [DataType]

component_types

-> m' (Tensor Ref ByteString)

handle

fIFOQueue' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

component_types

-> m' (Tensor Ref ByteString)

handle

fIFOQueueV2 Source #

Arguments

:: MonadBuild m' 
=> [DataType]

component_types

-> m' (Tensor Value ResourceHandle)

handle

fIFOQueueV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

component_types

-> m' (Tensor Value ResourceHandle)

handle

fakeQuantWithMinMaxArgsGradient Source #

Arguments

:: Tensor v'1 Float

gradients

-> Tensor v'2 Float

inputs

-> Tensor Build Float

backprops

fakeQuantWithMinMaxArgsGradient' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

gradients

-> Tensor v'2 Float

inputs

-> Tensor Build Float

backprops

fakeQuantWithMinMaxVars Source #

Arguments

:: Tensor v'1 Float

inputs

-> Tensor v'2 Float

min

-> Tensor v'3 Float

max

-> Tensor Build Float

outputs

fakeQuantWithMinMaxVars' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

inputs

-> Tensor v'2 Float

min

-> Tensor v'3 Float

max

-> Tensor Build Float

outputs

fakeQuantWithMinMaxVarsGradient Source #

Arguments

:: Tensor v'1 Float

gradients

-> Tensor v'2 Float

inputs

-> Tensor v'3 Float

min

-> Tensor v'4 Float

max

-> (Tensor Build Float, Tensor Build Float, Tensor Build Float)

(backprops_wrt_input, backprop_wrt_min, backprop_wrt_max)

  • backprops_wrt_input
  • backprop_wrt_min
  • backprop_wrt_max

fakeQuantWithMinMaxVarsGradient' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

gradients

-> Tensor v'2 Float

inputs

-> Tensor v'3 Float

min

-> Tensor v'4 Float

max

-> (Tensor Build Float, Tensor Build Float, Tensor Build Float)

(backprops_wrt_input, backprop_wrt_min, backprop_wrt_max)

  • backprops_wrt_input
  • backprop_wrt_min
  • backprop_wrt_max

fakeQuantWithMinMaxVarsPerChannelGradient Source #

Arguments

:: Tensor v'1 Float

gradients

-> Tensor v'2 Float

inputs

-> Tensor v'3 Float

min

-> Tensor v'4 Float

max

-> (Tensor Build Float, Tensor Build Float, Tensor Build Float)

(backprops_wrt_input, backprop_wrt_min, backprop_wrt_max)

  • backprops_wrt_input
  • backprop_wrt_min
  • backprop_wrt_max

fakeQuantWithMinMaxVarsPerChannelGradient' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

gradients

-> Tensor v'2 Float

inputs

-> Tensor v'3 Float

min

-> Tensor v'4 Float

max

-> (Tensor Build Float, Tensor Build Float, Tensor Build Float)

(backprops_wrt_input, backprop_wrt_min, backprop_wrt_max)

  • backprops_wrt_input
  • backprop_wrt_min
  • backprop_wrt_max

fakeQueue Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

resource

-> m' (Tensor Ref ByteString)

handle

fakeQueue' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> m' (Tensor Ref ByteString)

handle

fill Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] index_type) 
=> Tensor v'1 index_type

dims

-> Tensor v'2 t

value

-> Tensor Build t

output

fill' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] index_type) 
=> OpParams 
-> Tensor v'1 index_type

dims

-> Tensor v'2 t

value

-> Tensor Build t

output

fixedLengthRecordDataset Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

filenames

-> Tensor v'2 Int64

header_bytes

-> Tensor v'3 Int64

record_bytes

-> Tensor v'4 Int64

footer_bytes

-> Tensor v'5 Int64

buffer_size

-> m' (Tensor Value Variant)

handle

fixedLengthRecordDataset' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

filenames

-> Tensor v'2 Int64

header_bytes

-> Tensor v'3 Int64

record_bytes

-> Tensor v'4 Int64

footer_bytes

-> Tensor v'5 Int64

buffer_size

-> m' (Tensor Value Variant)

handle

fixedLengthRecordReader Source #

Arguments

:: MonadBuild m' 
=> Int64

record_bytes

-> m' (Tensor Ref ByteString)

reader_handle

fixedLengthRecordReader' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

record_bytes

-> m' (Tensor Ref ByteString)

reader_handle

fixedLengthRecordReaderV2 Source #

Arguments

:: MonadBuild m' 
=> Int64

record_bytes

-> m' (Tensor Value ResourceHandle)

reader_handle

fixedLengthRecordReaderV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

record_bytes

-> m' (Tensor Value ResourceHandle)

reader_handle

fixedUnigramCandidateSampler Source #

Arguments

:: MonadBuild m' 
=> Int64

num_sampled

-> Int64

num_true

-> Int64

range_max

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

fixedUnigramCandidateSampler' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

num_sampled

-> Int64

num_true

-> Int64

range_max

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

floor Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

floor' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

floorMod Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

floorMod' Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

fractionalAvgPool Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> Tensor v'1 t

value

-> (Tensor Build t, Tensor Build Int64, Tensor Build Int64)

(output, row_pooling_sequence, col_pooling_sequence)

  • output
  • row_pooling_sequence
  • col_pooling_sequence

fractionalAvgPool' Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

value

-> (Tensor Build t, Tensor Build Int64, Tensor Build Int64)

(output, row_pooling_sequence, col_pooling_sequence)

  • output
  • row_pooling_sequence
  • col_pooling_sequence

fractionalAvgPoolGrad Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> Tensor v'1 Int64

orig_input_tensor_shape

-> Tensor v'2 t

out_backprop

-> Tensor v'3 Int64

row_pooling_sequence

-> Tensor v'4 Int64

col_pooling_sequence

-> Tensor Build t

output

fractionalAvgPoolGrad' Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

orig_input_tensor_shape

-> Tensor v'2 t

out_backprop

-> Tensor v'3 Int64

row_pooling_sequence

-> Tensor v'4 Int64

col_pooling_sequence

-> Tensor Build t

output

fractionalMaxPool Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> Tensor v'1 t

value

-> (Tensor Build t, Tensor Build Int64, Tensor Build Int64)

(output, row_pooling_sequence, col_pooling_sequence)

  • output
  • row_pooling_sequence
  • col_pooling_sequence

fractionalMaxPool' Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

value

-> (Tensor Build t, Tensor Build Int64, Tensor Build Int64)

(output, row_pooling_sequence, col_pooling_sequence)

  • output
  • row_pooling_sequence
  • col_pooling_sequence

fractionalMaxPoolGrad Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

out_backprop

-> Tensor v'4 Int64

row_pooling_sequence

-> Tensor v'5 Int64

col_pooling_sequence

-> Tensor Build t

output

fractionalMaxPoolGrad' Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

out_backprop

-> Tensor v'4 Int64

row_pooling_sequence

-> Tensor v'5 Int64

col_pooling_sequence

-> Tensor Build t

output

fusedBatchNorm Source #

Arguments

:: OneOf '[Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

scale

-> Tensor v'3 t

offset

-> Tensor v'4 t

mean

-> Tensor v'5 t

variance

-> (Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t)

(y, batch_mean, batch_variance, reserve_space_1, reserve_space_2)

  • y
  • batch_mean
  • batch_variance
  • reserve_space_1
  • reserve_space_2

fusedBatchNorm' Source #

Arguments

:: OneOf '[Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

scale

-> Tensor v'3 t

offset

-> Tensor v'4 t

mean

-> Tensor v'5 t

variance

-> (Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t)

(y, batch_mean, batch_variance, reserve_space_1, reserve_space_2)

  • y
  • batch_mean
  • batch_variance
  • reserve_space_1
  • reserve_space_2

fusedBatchNormGrad Source #

Arguments

:: OneOf '[Float] t 
=> Tensor v'1 t

y_backprop

-> Tensor v'2 t

x

-> Tensor v'3 t

scale

-> Tensor v'4 t

reserve_space_1

-> Tensor v'5 t

reserve_space_2

-> (Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t)

(x_backprop, scale_backprop, offset_backprop, reserve_space_3, reserve_space_4)

  • x_backprop
  • scale_backprop
  • offset_backprop
  • reserve_space_3
  • reserve_space_4

fusedBatchNormGrad' Source #

Arguments

:: OneOf '[Float] t 
=> OpParams 
-> Tensor v'1 t

y_backprop

-> Tensor v'2 t

x

-> Tensor v'3 t

scale

-> Tensor v'4 t

reserve_space_1

-> Tensor v'5 t

reserve_space_2

-> (Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t, Tensor Build t)

(x_backprop, scale_backprop, offset_backprop, reserve_space_3, reserve_space_4)

  • x_backprop
  • scale_backprop
  • offset_backprop
  • reserve_space_3
  • reserve_space_4

fusedBatchNormGradV2 Source #

Arguments

:: (OneOf '[Word16, Float] t, OneOf '[Float] u) 
=> Tensor v'1 t

y_backprop

-> Tensor v'2 t

x

-> Tensor v'3 Float

scale

-> Tensor v'4 u

reserve_space_1

-> Tensor v'5 u

reserve_space_2

-> (Tensor Build t, Tensor Build u, Tensor Build u, Tensor Build u, Tensor Build u)

(x_backprop, scale_backprop, offset_backprop, reserve_space_3, reserve_space_4)

  • x_backprop
  • scale_backprop
  • offset_backprop
  • reserve_space_3
  • reserve_space_4

fusedBatchNormGradV2' Source #

Arguments

:: (OneOf '[Word16, Float] t, OneOf '[Float] u) 
=> OpParams 
-> Tensor v'1 t

y_backprop

-> Tensor v'2 t

x

-> Tensor v'3 Float

scale

-> Tensor v'4 u

reserve_space_1

-> Tensor v'5 u

reserve_space_2

-> (Tensor Build t, Tensor Build u, Tensor Build u, Tensor Build u, Tensor Build u)

(x_backprop, scale_backprop, offset_backprop, reserve_space_3, reserve_space_4)

  • x_backprop
  • scale_backprop
  • offset_backprop
  • reserve_space_3
  • reserve_space_4

fusedBatchNormV2 Source #

Arguments

:: (OneOf '[Word16, Float] t, OneOf '[Float] u) 
=> Tensor v'1 t

x

-> Tensor v'2 u

scale

-> Tensor v'3 u

offset

-> Tensor v'4 u

mean

-> Tensor v'5 u

variance

-> (Tensor Build t, Tensor Build u, Tensor Build u, Tensor Build u, Tensor Build u)

(y, batch_mean, batch_variance, reserve_space_1, reserve_space_2)

  • y
  • batch_mean
  • batch_variance
  • reserve_space_1
  • reserve_space_2

fusedBatchNormV2' Source #

Arguments

:: (OneOf '[Word16, Float] t, OneOf '[Float] u) 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 u

scale

-> Tensor v'3 u

offset

-> Tensor v'4 u

mean

-> Tensor v'5 u

variance

-> (Tensor Build t, Tensor Build u, Tensor Build u, Tensor Build u, Tensor Build u)

(y, batch_mean, batch_variance, reserve_space_1, reserve_space_2)

  • y
  • batch_mean
  • batch_variance
  • reserve_space_1
  • reserve_space_2

fusedPadConv2D Source #

Arguments

:: OneOf '[Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 Int32

paddings

-> Tensor v'3 t

filter

-> Tensor Build t

output

fusedPadConv2D' Source #

Arguments

:: OneOf '[Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Int32

paddings

-> Tensor v'3 t

filter

-> Tensor Build t

output

fusedResizeAndPadConv2D Source #

Arguments

:: OneOf '[Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 Int32

size

-> Tensor v'3 Int32

paddings

-> Tensor v'4 t

filter

-> Tensor Build t

output

fusedResizeAndPadConv2D' Source #

Arguments

:: OneOf '[Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Int32

size

-> Tensor v'3 Int32

paddings

-> Tensor v'4 t

filter

-> Tensor Build t

output

gather Source #

Arguments

:: (TensorType tparams, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 tparams

params

-> Tensor v'2 tindices

indices

-> Tensor Build tparams

output

gather' Source #

Arguments

:: (TensorType tparams, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 tparams

params

-> Tensor v'2 tindices

indices

-> Tensor Build tparams

output

gatherNd Source #

Arguments

:: (TensorType tparams, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 tparams

params

-> Tensor v'2 tindices

indices

-> Tensor Build tparams

output

gatherNd' Source #

Arguments

:: (TensorType tparams, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 tparams

params

-> Tensor v'2 tindices

indices

-> Tensor Build tparams

output

gatherV2 Source #

Arguments

:: (TensorType tparams, OneOf '[Int32, Int64] tindices, OneOf '[Int32, Int64] taxis) 
=> Tensor v'1 tparams

params

-> Tensor v'2 tindices

indices

-> Tensor v'3 taxis

axis

-> Tensor Build tparams

output

gatherV2' Source #

Arguments

:: (TensorType tparams, OneOf '[Int32, Int64] tindices, OneOf '[Int32, Int64] taxis) 
=> OpParams 
-> Tensor v'1 tparams

params

-> Tensor v'2 tindices

indices

-> Tensor v'3 taxis

axis

-> Tensor Build tparams

output

gcsConfigureBlockCache Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 Word64

max_cache_size

-> Tensor v'2 Word64

block_size

-> Tensor v'3 Word64

max_staleness

-> m' ControlNode 

gcsConfigureBlockCache' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 Word64

max_cache_size

-> Tensor v'2 Word64

block_size

-> Tensor v'3 Word64

max_staleness

-> m' ControlNode 

generateBigQueryReaderPartitions Source #

Arguments

:: Int64

num_partitions: Number of partitions to split the table into.

-> Int64

timestamp_millis: Table snapshot timestamp in millis since epoch. Relative (negative or zero) snapshot times are not allowed. For more details, see 'Table Decorators' in BigQuery docs.

-> Tensor Build ByteString

partitions: Serialized table partitions.

Generates serialized partition messages suitable for batch reads.

This op should not be used directly by clients. Instead, the bigquery_reader_ops.py file defines a clean interface to the reader.

generateBigQueryReaderPartitions' Source #

Arguments

:: OpParams 
-> Int64

num_partitions: Number of partitions to split the table into.

-> Int64

timestamp_millis: Table snapshot timestamp in millis since epoch. Relative (negative or zero) snapshot times are not allowed. For more details, see 'Table Decorators' in BigQuery docs.

-> Tensor Build ByteString

partitions: Serialized table partitions.

generateVocabRemapping Source #

Arguments

:: Int64

new_vocab_offset

-> Int64

num_new_vocab

-> Tensor v'1 ByteString

new_vocab_file

-> Tensor v'2 ByteString

old_vocab_file

-> (Tensor Build Int64, Tensor Build Int32)

(remapping, num_present)

  • remapping
  • num_present

generateVocabRemapping' Source #

Arguments

:: OpParams 
-> Int64

new_vocab_offset

-> Int64

num_new_vocab

-> Tensor v'1 ByteString

new_vocab_file

-> Tensor v'2 ByteString

old_vocab_file

-> (Tensor Build Int64, Tensor Build Int32)

(remapping, num_present)

  • remapping
  • num_present

getSessionHandle Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 t

value

-> m' (Tensor Value ByteString)

handle

getSessionHandle' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 t

value

-> m' (Tensor Value ByteString)

handle

getSessionHandleV2 Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 t

value

-> m' (Tensor Value ResourceHandle)

handle

getSessionHandleV2' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 t

value

-> m' (Tensor Value ResourceHandle)

handle

getSessionTensor Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 ByteString

handle

-> m' (Tensor Value dtype)

value

getSessionTensor' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 ByteString

handle

-> m' (Tensor Value dtype)

value

greater Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build Bool

z

guaranteeConst Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 t

input

-> m' (Tensor Value t)

output

guaranteeConst' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 t

input

-> m' (Tensor Value t)

output

hSVToRGB Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

images

-> Tensor Build t

output

hSVToRGB' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

images

-> Tensor Build t

output

hashTable Source #

Arguments

:: MonadBuild m' 
=> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Ref ByteString)

table_handle

hashTable' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Ref ByteString)

table_handle

hashTableV2 Source #

Arguments

:: MonadBuild m' 
=> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Value ResourceHandle)

table_handle

hashTableV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Value ResourceHandle)

table_handle

histogramFixedWidth Source #

Arguments

:: (OneOf '[Int32, Int64, Double, Float] t, OneOf '[Int32, Int64] dtype) 
=> Tensor v'1 t

values

-> Tensor v'2 t

value_range

-> Tensor v'3 Int32

nbins

-> Tensor Build dtype

out

histogramFixedWidth' Source #

Arguments

:: (OneOf '[Int32, Int64, Double, Float] t, OneOf '[Int32, Int64] dtype) 
=> OpParams 
-> Tensor v'1 t

values

-> Tensor v'2 t

value_range

-> Tensor v'3 Int32

nbins

-> Tensor Build dtype

out

iFFT Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

iFFT' Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> OpParams 
-> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

iFFT2D Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

iFFT2D' Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> OpParams 
-> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

iFFT3D Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

iFFT3D' Source #

Arguments

:: OneOf '[Complex Double, Complex Float] tcomplex 
=> OpParams 
-> Tensor v'1 tcomplex

input

-> Tensor Build tcomplex

output

iRFFT Source #

Arguments

:: Tensor v'1 (Complex Float)

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build Float

output

iRFFT' Source #

Arguments

:: OpParams 
-> Tensor v'1 (Complex Float)

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build Float

output

iRFFT2D Source #

Arguments

:: Tensor v'1 (Complex Float)

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build Float

output

iRFFT2D' Source #

Arguments

:: OpParams 
-> Tensor v'1 (Complex Float)

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build Float

output

iRFFT3D Source #

Arguments

:: Tensor v'1 (Complex Float)

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build Float

output

iRFFT3D' Source #

Arguments

:: OpParams 
-> Tensor v'1 (Complex Float)

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build Float

output

identity Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor Build t

output

identity' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

identityN Source #

Arguments

:: TensorTypes t 
=> TensorList v'1 t

input

-> TensorList Build t

output

identityN' Source #

Arguments

:: TensorTypes t 
=> OpParams 
-> TensorList v'1 t

input

-> TensorList Build t

output

identityReader Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Ref ByteString)

reader_handle

identityReader' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Ref ByteString)

reader_handle

identityReaderV2 Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Value ResourceHandle)

reader_handle

identityReaderV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Value ResourceHandle)

reader_handle

igamma Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

a

-> Tensor v'2 t

x

-> Tensor Build t

z

igamma' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

a

-> Tensor v'2 t

x

-> Tensor Build t

z

igammac Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

a

-> Tensor v'2 t

x

-> Tensor Build t

z

igammac' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

a

-> Tensor v'2 t

x

-> Tensor Build t

z

imag Source #

Arguments

:: (OneOf '[Complex Double, Complex Float] t, OneOf '[Double, Float] tout) 
=> Tensor v'1 t

input

-> Tensor Build tout

output

imag' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float] t, OneOf '[Double, Float] tout) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build tout

output

imageSummary Source #

Arguments

:: OneOf '[Word16, Word8, Double, Float] t 
=> Tensor v'1 ByteString

tag

-> Tensor v'2 t

tensor

-> Tensor Build ByteString

summary

imageSummary' Source #

Arguments

:: OneOf '[Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 ByteString

tag

-> Tensor v'2 t

tensor

-> Tensor Build ByteString

summary

immutableConst Source #

Arguments

:: TensorType dtype 
=> Shape

shape

-> Tensor Build dtype

tensor

immutableConst' Source #

Arguments

:: TensorType dtype 
=> OpParams 
-> Shape

shape

-> Tensor Build dtype

tensor

importEvent Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 ByteString

event

-> m' ControlNode 

importEvent' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 ByteString

event

-> m' ControlNode 

inTopK Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> Int64

k

-> Tensor v'1 Float

predictions

-> Tensor v'2 t

targets

-> Tensor Build Bool

precision

inTopK' Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> OpParams 
-> Int64

k

-> Tensor v'1 Float

predictions

-> Tensor v'2 t

targets

-> Tensor Build Bool

precision

inTopKV2 Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> Tensor v'1 Float

predictions

-> Tensor v'2 t

targets

-> Tensor v'3 t

k

-> Tensor Build Bool

precision

inTopKV2' Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> OpParams 
-> Tensor v'1 Float

predictions

-> Tensor v'2 t

targets

-> Tensor v'3 t

k

-> Tensor Build Bool

precision

infeedDequeue Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Shape

shape: The shape of the tensor.

-> m' (Tensor Value dtype)

output: A tensor that will be provided using the infeed mechanism.

A placeholder op for a value that will be fed into the computation.

infeedDequeue' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Shape

shape: The shape of the tensor.

-> m' (Tensor Value dtype)

output: A tensor that will be provided using the infeed mechanism.

infeedDequeueTuple Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> m' (TensorList Value dtypes)

outputs: A list of tensors that will be provided using the infeed mechanism.

A placeholder op for multiple values that will be fed into the computation

simultaneously as an XLA tuple.

infeedDequeueTuple' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> m' (TensorList Value dtypes)

outputs: A list of tensors that will be provided using the infeed mechanism.

infeedEnqueue Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 dtype

input: A tensor that will be provided using the infeed mechanism.

-> m' ControlNode 

An op which feeds a single Tensor value into the computation.

infeedEnqueue' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 dtype

input: A tensor that will be provided using the infeed mechanism.

-> m' ControlNode 

infeedEnqueueTuple Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> TensorList v'1 dtypes

inputs: A list of tensors that will be provided using the infeed mechanism.

-> m' ControlNode 

An op which feeds multiple Tensor values into the computation as an XLA tuple.

infeedEnqueueTuple' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> TensorList v'1 dtypes

inputs: A list of tensors that will be provided using the infeed mechanism.

-> m' ControlNode 

initializeTable Source #

Arguments

:: (MonadBuild m', TensorType tkey, TensorType tval) 
=> Tensor Ref ByteString

table_handle

-> Tensor v'2 tkey

keys

-> Tensor v'3 tval

values

-> m' ControlNode 

initializeTable' Source #

Arguments

:: (MonadBuild m', TensorType tkey, TensorType tval) 
=> OpParams 
-> Tensor Ref ByteString

table_handle

-> Tensor v'2 tkey

keys

-> Tensor v'3 tval

values

-> m' ControlNode 

initializeTableFromTextFile Source #

Arguments

:: MonadBuild m' 
=> Int64

key_index

-> Int64

value_index

-> Tensor Ref ByteString

table_handle

-> Tensor v'2 ByteString

filename

-> m' ControlNode 

initializeTableFromTextFile' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

key_index

-> Int64

value_index

-> Tensor Ref ByteString

table_handle

-> Tensor v'2 ByteString

filename

-> m' ControlNode 

initializeTableFromTextFileV2 Source #

Arguments

:: MonadBuild m' 
=> Int64

key_index

-> Int64

value_index

-> Tensor v'1 ResourceHandle

table_handle

-> Tensor v'2 ByteString

filename

-> m' ControlNode 

initializeTableFromTextFileV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

key_index

-> Int64

value_index

-> Tensor v'1 ResourceHandle

table_handle

-> Tensor v'2 ByteString

filename

-> m' ControlNode 

initializeTableV2 Source #

Arguments

:: (MonadBuild m', TensorType tkey, TensorType tval) 
=> Tensor v'1 ResourceHandle

table_handle

-> Tensor v'2 tkey

keys

-> Tensor v'3 tval

values

-> m' ControlNode 

initializeTableV2' Source #

Arguments

:: (MonadBuild m', TensorType tkey, TensorType tval) 
=> OpParams 
-> Tensor v'1 ResourceHandle

table_handle

-> Tensor v'2 tkey

keys

-> Tensor v'3 tval

values

-> m' ControlNode 

inplaceAdd Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

x

-> Tensor v'2 Int32

i

-> Tensor v'3 t

v

-> Tensor Build t

y

inplaceAdd' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 Int32

i

-> Tensor v'3 t

v

-> Tensor Build t

y

inplaceSub Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

x

-> Tensor v'2 Int32

i

-> Tensor v'3 t

v

-> Tensor Build t

y

inplaceSub' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 Int32

i

-> Tensor v'3 t

v

-> Tensor Build t

y

inplaceUpdate Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

x

-> Tensor v'2 Int32

i

-> Tensor v'3 t

v

-> Tensor Build t

y

inplaceUpdate' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 Int32

i

-> Tensor v'3 t

v

-> Tensor Build t

y

invGrad Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Word16, Double, Float] t 
=> Tensor v'1 t

y

-> Tensor v'2 t

dy

-> Tensor Build t

z

invGrad' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

y

-> Tensor v'2 t

dy

-> Tensor Build t

z

invert Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

invert' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

invertPermutation Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

invertPermutation' Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

isBoostedTreesEnsembleInitialized Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> m' (Tensor Value Bool)

is_initialized

isBoostedTreesEnsembleInitialized' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

tree_ensemble_handle

-> m' (Tensor Value Bool)

is_initialized

isFinite Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build Bool

y

isFinite' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build Bool

y

isInf Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build Bool

y

isInf' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build Bool

y

isNan Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build Bool

y

isNan' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build Bool

y

isVariableInitialized Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor Ref dtype

ref

-> m' (Tensor Value Bool)

is_initialized

isVariableInitialized' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor Ref dtype

ref

-> m' (Tensor Value Bool)

is_initialized

iterator Source #

Arguments

:: MonadBuild m' 
=> [DataType]

output_types

-> m' (Tensor Value ResourceHandle)

handle

iterator' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

output_types

-> m' (Tensor Value ResourceHandle)

handle

iteratorFromStringHandle Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

string_handle

-> m' (Tensor Value ResourceHandle)

resource_handle

iteratorFromStringHandle' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

string_handle

-> m' (Tensor Value ResourceHandle)

resource_handle

iteratorGetNext Source #

Arguments

:: (MonadBuild m', TensorTypes output_types) 
=> Tensor v'1 ResourceHandle

iterator

-> m' (TensorList Value output_types)

components

iteratorGetNext' Source #

Arguments

:: (MonadBuild m', TensorTypes output_types) 
=> OpParams 
-> Tensor v'1 ResourceHandle

iterator

-> m' (TensorList Value output_types)

components

iteratorGetNextSync Source #

Arguments

:: (MonadBuild m', TensorTypes output_types) 
=> Tensor v'1 ResourceHandle

iterator

-> m' (TensorList Value output_types)

components

iteratorGetNextSync' Source #

Arguments

:: (MonadBuild m', TensorTypes output_types) 
=> OpParams 
-> Tensor v'1 ResourceHandle

iterator

-> m' (TensorList Value output_types)

components

iteratorToStringHandle Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

resource_handle

-> m' (Tensor Value ByteString)

string_handle

iteratorToStringHandle' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource_handle

-> m' (Tensor Value ByteString)

string_handle

l2Loss Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

t

-> Tensor Build t

output

l2Loss' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

t

-> Tensor Build t

output

lMDBReader Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Ref ByteString)

reader_handle

lMDBReader' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Ref ByteString)

reader_handle

lRN Source #

Arguments

:: OneOf '[Word16, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

lRN' Source #

Arguments

:: OneOf '[Word16, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

lRNGrad Source #

Arguments

:: OneOf '[Word16, Float] t 
=> Tensor v'1 t

input_grads

-> Tensor v'2 t

input_image

-> Tensor v'3 t

output_image

-> Tensor Build t

output

lRNGrad' Source #

Arguments

:: OneOf '[Word16, Float] t 
=> OpParams 
-> Tensor v'1 t

input_grads

-> Tensor v'2 t

input_image

-> Tensor v'3 t

output_image

-> Tensor Build t

output

latencyStatsDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 ByteString

tag

-> Tensor Build Variant

handle

latencyStatsDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 ByteString

tag

-> Tensor Build Variant

handle

learnedUnigramCandidateSampler Source #

Arguments

:: MonadBuild m' 
=> Int64

num_sampled

-> Int64

num_true

-> Int64

range_max

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

learnedUnigramCandidateSampler' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

num_sampled

-> Int64

num_true

-> Int64

range_max

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

leftShift Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

leftShift' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

less Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build Bool

z

less' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build Bool

z

lgamma Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

lgamma' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

linSpace Source #

Arguments

:: (OneOf '[Word16, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

start

-> Tensor v'2 t

stop

-> Tensor v'3 tidx

num

-> Tensor Build t

output

linSpace' Source #

Arguments

:: (OneOf '[Word16, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

start

-> Tensor v'2 t

stop

-> Tensor v'3 tidx

num

-> Tensor Build t

output

listDiff Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_idx) 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> (Tensor Build t, Tensor Build out_idx)

(out, idx)

  • out
  • idx

listDiff' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_idx) 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> (Tensor Build t, Tensor Build out_idx)

(out, idx)

  • out
  • idx

loadAndRemapMatrix Source #

Arguments

:: MonadBuild m' 
=> Int64

num_cols

-> Int64

num_rows

-> Tensor v'1 ByteString

ckpt_path

-> Tensor v'2 ByteString

old_tensor_name

-> Tensor v'3 Int64

row_remapping

-> Tensor v'4 Int64

col_remapping

-> Tensor v'5 Float

initializing_values

-> m' (Tensor Value Float)

output_matrix

loadAndRemapMatrix' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

num_cols

-> Int64

num_rows

-> Tensor v'1 ByteString

ckpt_path

-> Tensor v'2 ByteString

old_tensor_name

-> Tensor v'3 Int64

row_remapping

-> Tensor v'4 Int64

col_remapping

-> Tensor v'5 Float

initializing_values

-> m' (Tensor Value Float)

output_matrix

logMatrixDeterminant Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t)

(sign, log_abs_determinant)

  • sign
  • log_abs_determinant

logMatrixDeterminant' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t)

(sign, log_abs_determinant)

  • sign
  • log_abs_determinant

logSoftmax Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

logits

-> Tensor Build t

logsoftmax

logSoftmax' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

logits

-> Tensor Build t

logsoftmax

logUniformCandidateSampler Source #

Arguments

:: MonadBuild m' 
=> Int64

num_sampled

-> Int64

num_true

-> Int64

range_max

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

logUniformCandidateSampler' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

num_sampled

-> Int64

num_true

-> Int64

range_max

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

logicalAnd Source #

Arguments

:: Tensor v'1 Bool

x

-> Tensor v'2 Bool

y

-> Tensor Build Bool

z

logicalOr Source #

Arguments

:: Tensor v'1 Bool

x

-> Tensor v'2 Bool

y

-> Tensor Build Bool

z

logicalOr' Source #

Arguments

:: OpParams 
-> Tensor v'1 Bool

x

-> Tensor v'2 Bool

y

-> Tensor Build Bool

z

lookupTableExport Source #

Arguments

:: (MonadBuild m', TensorType tkeys, TensorType tvalues) 
=> Tensor Ref ByteString

table_handle

-> m' (Tensor Value tkeys, Tensor Value tvalues)

(keys, values)

  • keys
  • values

lookupTableExport' Source #

Arguments

:: (MonadBuild m', TensorType tkeys, TensorType tvalues) 
=> OpParams 
-> Tensor Ref ByteString

table_handle

-> m' (Tensor Value tkeys, Tensor Value tvalues)

(keys, values)

  • keys
  • values

lookupTableExportV2 Source #

Arguments

:: (MonadBuild m', TensorType tkeys, TensorType tvalues) 
=> Tensor v'1 ResourceHandle

table_handle

-> m' (Tensor Value tkeys, Tensor Value tvalues)

(keys, values)

  • keys
  • values

lookupTableExportV2' Source #

Arguments

:: (MonadBuild m', TensorType tkeys, TensorType tvalues) 
=> OpParams 
-> Tensor v'1 ResourceHandle

table_handle

-> m' (Tensor Value tkeys, Tensor Value tvalues)

(keys, values)

  • keys
  • values

lookupTableFind Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> Tensor Ref ByteString

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

default_value

-> m' (Tensor Value tout)

values

lookupTableFind' Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> OpParams 
-> Tensor Ref ByteString

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

default_value

-> m' (Tensor Value tout)

values

lookupTableFindV2 Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> Tensor v'1 ResourceHandle

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

default_value

-> m' (Tensor Value tout)

values

lookupTableFindV2' Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> OpParams 
-> Tensor v'1 ResourceHandle

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

default_value

-> m' (Tensor Value tout)

values

lookupTableImport Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> Tensor Ref ByteString

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

values

-> m' ControlNode 

lookupTableImport' Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> OpParams 
-> Tensor Ref ByteString

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

values

-> m' ControlNode 

lookupTableImportV2 Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> Tensor v'1 ResourceHandle

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

values

-> m' ControlNode 

lookupTableImportV2' Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> OpParams 
-> Tensor v'1 ResourceHandle

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

values

-> m' ControlNode 

lookupTableInsert Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> Tensor Ref ByteString

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

values

-> m' ControlNode 

lookupTableInsert' Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> OpParams 
-> Tensor Ref ByteString

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

values

-> m' ControlNode 

lookupTableInsertV2 Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> Tensor v'1 ResourceHandle

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

values

-> m' ControlNode 

lookupTableInsertV2' Source #

Arguments

:: (MonadBuild m', TensorType tin, TensorType tout) 
=> OpParams 
-> Tensor v'1 ResourceHandle

table_handle

-> Tensor v'2 tin

keys

-> Tensor v'3 tout

values

-> m' ControlNode 

lookupTableSize Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

table_handle

-> m' (Tensor Value Int64)

size

lookupTableSize' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

table_handle

-> m' (Tensor Value Int64)

size

lookupTableSizeV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

table_handle

-> m' (Tensor Value Int64)

size

lookupTableSizeV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

table_handle

-> m' (Tensor Value Int64)

size

loopCond Source #

Arguments

:: Tensor v'1 Bool

input

-> Tensor Build Bool

output

loopCond' Source #

Arguments

:: OpParams 
-> Tensor v'1 Bool

input

-> Tensor Build Bool

output

makeIterator Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 Variant

dataset

-> Tensor v'2 ResourceHandle

iterator

-> m' ControlNode 

makeIterator' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 Variant

dataset

-> Tensor v'2 ResourceHandle

iterator

-> m' ControlNode 

mapClear Source #

Arguments

:: MonadBuild m' 
=> [DataType]

dtypes

-> m' ControlNode 

mapClear' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

dtypes

-> m' ControlNode 

mapIncompleteSize Source #

Arguments

:: MonadBuild m' 
=> [DataType]

dtypes

-> m' (Tensor Value Int32)

size

mapIncompleteSize' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

dtypes

-> m' (Tensor Value Int32)

size

mapPeek Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> m' (TensorList Value dtypes)

values

mapPeek' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> m' (TensorList Value dtypes)

values

mapSize Source #

Arguments

:: MonadBuild m' 
=> [DataType]

dtypes

-> m' (Tensor Value Int32)

size

mapSize' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

dtypes

-> m' (Tensor Value Int32)

size

mapStage Source #

Arguments

:: (MonadBuild m', TensorTypes fake_dtypes) 
=> [DataType]

dtypes

-> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> TensorList v'3 fake_dtypes

values

-> m' ControlNode 

mapStage' Source #

Arguments

:: (MonadBuild m', TensorTypes fake_dtypes) 
=> OpParams 
-> [DataType]

dtypes

-> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> TensorList v'3 fake_dtypes

values

-> m' ControlNode 

mapUnstage Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> m' (TensorList Value dtypes)

values

mapUnstage' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> m' (TensorList Value dtypes)

values

mapUnstageNoKey Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> Tensor v'1 Int32

indices

-> m' (Tensor Value Int64, TensorList Value dtypes)

(key, values)

  • key
  • values

mapUnstageNoKey' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> Tensor v'1 Int32

indices

-> m' (Tensor Value Int64, TensorList Value dtypes)

(key, values)

  • key
  • values

matMul Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Word16, Double, Float] t 
=> Tensor v'1 t

a

-> Tensor v'2 t

b

-> Tensor Build t

product

matMul' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

a

-> Tensor v'2 t

b

-> Tensor Build t

product

matchingFiles Source #

Arguments

:: Tensor v'1 ByteString

pattern

-> Tensor Build ByteString

filenames

matchingFiles' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

pattern

-> Tensor Build ByteString

filenames

matrixBandPart Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tindex) 
=> Tensor v'1 t

input

-> Tensor v'2 tindex

num_lower

-> Tensor v'3 tindex

num_upper

-> Tensor Build t

band

matrixBandPart' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tindex) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tindex

num_lower

-> Tensor v'3 tindex

num_upper

-> Tensor Build t

band

matrixDeterminant Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

matrixDeterminant' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

matrixDiag Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

diagonal

-> Tensor Build t

output

matrixDiag' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

diagonal

-> Tensor Build t

output

matrixDiagPart Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor Build t

diagonal

matrixDiagPart' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

diagonal

matrixExponential Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

matrixExponential' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

matrixInverse Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

matrixInverse' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

matrixLogarithm Source #

Arguments

:: OneOf '[Complex Double, Complex Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

matrixLogarithm' Source #

Arguments

:: OneOf '[Complex Double, Complex Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

matrixSetDiag Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor v'2 t

diagonal

-> Tensor Build t

output

matrixSetDiag' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

diagonal

-> Tensor Build t

output

matrixSolve Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor Build t

output

matrixSolve' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor Build t

output

matrixSolveLs Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor v'3 Double

l2_regularizer

-> Tensor Build t

output

matrixSolveLs' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor v'3 Double

l2_regularizer

-> Tensor Build t

output

matrixTriangularSolve Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor Build t

output

matrixTriangularSolve' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

matrix

-> Tensor v'2 t

rhs

-> Tensor Build t

output

max Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build t

output

max' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build t

output

maxPool Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

maxPool' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

maxPool3D Source #

Arguments

:: OneOf '[Word16, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

maxPool3D' Source #

Arguments

:: OneOf '[Word16, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

maxPool3DGrad Source #

Arguments

:: (OneOf '[Word16, Float] t, OneOf '[Word16, Float] tInput) 
=> Tensor v'1 tInput

orig_input

-> Tensor v'2 tInput

orig_output

-> Tensor v'3 t

grad

-> Tensor Build t

output

maxPool3DGrad' Source #

Arguments

:: (OneOf '[Word16, Float] t, OneOf '[Word16, Float] tInput) 
=> OpParams 
-> Tensor v'1 tInput

orig_input

-> Tensor v'2 tInput

orig_output

-> Tensor v'3 t

grad

-> Tensor Build t

output

maxPool3DGradGrad Source #

Arguments

:: OneOf '[Float] t 
=> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

grad

-> Tensor Build t

output

maxPool3DGradGrad' Source #

Arguments

:: OneOf '[Float] t 
=> OpParams 
-> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

grad

-> Tensor Build t

output

maxPoolGrad Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

grad

-> Tensor Build t

output

maxPoolGrad' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

grad

-> Tensor Build t

output

maxPoolGradGrad Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

grad

-> Tensor Build t

output

maxPoolGradGrad' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

grad

-> Tensor Build t

output

maxPoolGradGradV2 Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

grad

-> Tensor v'4 Int32

ksize

-> Tensor v'5 Int32

strides

-> Tensor Build t

output

maxPoolGradGradV2' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

grad

-> Tensor v'4 Int32

ksize

-> Tensor v'5 Int32

strides

-> Tensor Build t

output

maxPoolGradGradWithArgmax Source #

Arguments

:: (OneOf '[Int32, Int64] targmax, OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 t

input

-> Tensor v'2 t

grad

-> Tensor v'3 targmax

argmax

-> Tensor Build t

output

maxPoolGradGradWithArgmax' Source #

Arguments

:: (OneOf '[Int32, Int64] targmax, OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

grad

-> Tensor v'3 targmax

argmax

-> Tensor Build t

output

maxPoolGradV2 Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

grad

-> Tensor v'4 Int32

ksize

-> Tensor v'5 Int32

strides

-> Tensor Build t

output

maxPoolGradV2' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

orig_input

-> Tensor v'2 t

orig_output

-> Tensor v'3 t

grad

-> Tensor v'4 Int32

ksize

-> Tensor v'5 Int32

strides

-> Tensor Build t

output

maxPoolGradWithArgmax Source #

Arguments

:: (OneOf '[Int32, Int64] targmax, OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 t

input

-> Tensor v'2 t

grad

-> Tensor v'3 targmax

argmax

-> Tensor Build t

output

maxPoolGradWithArgmax' Source #

Arguments

:: (OneOf '[Int32, Int64] targmax, OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

grad

-> Tensor v'3 targmax

argmax

-> Tensor Build t

output

maxPoolV2 Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 Int32

ksize

-> Tensor v'3 Int32

strides

-> Tensor Build t

output

maxPoolV2' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Int32

ksize

-> Tensor v'3 Int32

strides

-> Tensor Build t

output

maxPoolWithArgmax Source #

Arguments

:: (OneOf '[Int32, Int64] targmax, OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build targmax)

(output, argmax)

  • output
  • argmax

maxPoolWithArgmax' Source #

Arguments

:: (OneOf '[Int32, Int64] targmax, OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build targmax)

(output, argmax)

  • output
  • argmax

maximum Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

maximum' Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

mean Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build t

output

mean' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build t

output

merge Source #

Arguments

:: TensorType t 
=> [Tensor v'1 t]

inputs

-> (Tensor Build t, Tensor Build Int32)

(output, value_index)

  • output
  • value_index

merge' Source #

Arguments

:: TensorType t 
=> OpParams 
-> [Tensor v'1 t]

inputs

-> (Tensor Build t, Tensor Build Int32)

(output, value_index)

  • output
  • value_index

mergeSummary Source #

Arguments

:: [Tensor v'1 ByteString]

inputs

-> Tensor Build ByteString

summary

mergeSummary' Source #

Arguments

:: OpParams 
-> [Tensor v'1 ByteString]

inputs

-> Tensor Build ByteString

summary

mergeV2Checkpoints Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

checkpoint_prefixes

-> Tensor v'2 ByteString

destination_prefix

-> m' ControlNode 

mergeV2Checkpoints' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

checkpoint_prefixes

-> Tensor v'2 ByteString

destination_prefix

-> m' ControlNode 

mfcc Source #

Arguments

:: Tensor v'1 Float

spectrogram

-> Tensor v'2 Int32

sample_rate

-> Tensor Build Float

output

mfcc' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

spectrogram

-> Tensor v'2 Int32

sample_rate

-> Tensor Build Float

output

min Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build t

output

min' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build t

output

minimum Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

minimum' Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

mirrorPad Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tpaddings) 
=> Tensor v'1 t

input

-> Tensor v'2 tpaddings

paddings

-> Tensor Build t

output

mirrorPad' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tpaddings) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tpaddings

paddings

-> Tensor Build t

output

mirrorPadGrad Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tpaddings) 
=> Tensor v'1 t

input

-> Tensor v'2 tpaddings

paddings

-> Tensor Build t

output

mirrorPadGrad' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tpaddings) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tpaddings

paddings

-> Tensor Build t

output

mod Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

mod' Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

multinomial Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] output_dtype) 
=> Tensor v'1 t

logits

-> Tensor v'2 Int32

num_samples

-> m' (Tensor Value output_dtype)

output

multinomial' Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] output_dtype) 
=> OpParams 
-> Tensor v'1 t

logits

-> Tensor v'2 Int32

num_samples

-> m' (Tensor Value output_dtype)

output

mutableDenseHashTable Source #

Arguments

:: (MonadBuild m', TensorType key_dtype) 
=> DataType

value_dtype

-> Tensor v'1 key_dtype

empty_key

-> m' (Tensor Ref ByteString)

table_handle

mutableDenseHashTable' Source #

Arguments

:: (MonadBuild m', TensorType key_dtype) 
=> OpParams 
-> DataType

value_dtype

-> Tensor v'1 key_dtype

empty_key

-> m' (Tensor Ref ByteString)

table_handle

mutableDenseHashTableV2 Source #

Arguments

:: (MonadBuild m', TensorType key_dtype) 
=> DataType

value_dtype

-> Tensor v'1 key_dtype

empty_key

-> m' (Tensor Value ResourceHandle)

table_handle

mutableDenseHashTableV2' Source #

Arguments

:: (MonadBuild m', TensorType key_dtype) 
=> OpParams 
-> DataType

value_dtype

-> Tensor v'1 key_dtype

empty_key

-> m' (Tensor Value ResourceHandle)

table_handle

mutableHashTable Source #

Arguments

:: MonadBuild m' 
=> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Ref ByteString)

table_handle

mutableHashTable' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Ref ByteString)

table_handle

mutableHashTableOfTensors Source #

Arguments

:: MonadBuild m' 
=> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Ref ByteString)

table_handle

mutableHashTableOfTensors' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Ref ByteString)

table_handle

mutableHashTableOfTensorsV2 Source #

Arguments

:: MonadBuild m' 
=> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Value ResourceHandle)

table_handle

mutableHashTableOfTensorsV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Value ResourceHandle)

table_handle

mutableHashTableV2 Source #

Arguments

:: MonadBuild m' 
=> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Value ResourceHandle)

table_handle

mutableHashTableV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

key_dtype

-> DataType

value_dtype

-> m' (Tensor Value ResourceHandle)

table_handle

mutexLock Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

mutex

-> m' (Tensor Value Variant)

mutex_lock

mutexLock' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

mutex

-> m' (Tensor Value Variant)

mutex_lock

mutexV2 Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Value ResourceHandle)

resource

mutexV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Value ResourceHandle)

resource

negTrain Source #

Arguments

:: MonadBuild m' 
=> Int64

num_negative_samples

-> Tensor Ref Float

w_in

-> Tensor Ref Float

w_out

-> Tensor v'3 Int32

examples

-> Tensor v'4 Int32

labels

-> Tensor v'5 Float

lr

-> m' ControlNode 

negTrain' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

num_negative_samples

-> Tensor Ref Float

w_in

-> Tensor Ref Float

w_out

-> Tensor v'3 Int32

examples

-> Tensor v'4 Int32

labels

-> Tensor v'5 Float

lr

-> m' ControlNode 

nextIteration Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

data

-> Tensor Build t

output

nextIteration' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor Build t

output

noOp :: forall m'. MonadBuild m' => m' ControlNode Source #

noOp' :: forall m'. MonadBuild m' => OpParams -> m' ControlNode Source #

nonMaxSuppression Source #

Arguments

:: Tensor v'1 Float

boxes

-> Tensor v'2 Float

scores

-> Tensor v'3 Int32

max_output_size

-> Tensor Build Int32

selected_indices

nonMaxSuppression' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

boxes

-> Tensor v'2 Float

scores

-> Tensor v'3 Int32

max_output_size

-> Tensor Build Int32

selected_indices

nonMaxSuppressionV2 Source #

Arguments

:: Tensor v'1 Float

boxes

-> Tensor v'2 Float

scores

-> Tensor v'3 Int32

max_output_size

-> Tensor v'4 Float

iou_threshold

-> Tensor Build Int32

selected_indices

nonMaxSuppressionV2' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

boxes

-> Tensor v'2 Float

scores

-> Tensor v'3 Int32

max_output_size

-> Tensor v'4 Float

iou_threshold

-> Tensor Build Int32

selected_indices

nonMaxSuppressionV3 Source #

Arguments

:: Tensor v'1 Float

boxes

-> Tensor v'2 Float

scores

-> Tensor v'3 Int32

max_output_size

-> Tensor v'4 Float

iou_threshold

-> Tensor v'5 Float

score_threshold

-> Tensor Build Int32

selected_indices

nonMaxSuppressionV3' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

boxes

-> Tensor v'2 Float

scores

-> Tensor v'3 Int32

max_output_size

-> Tensor v'4 Float

iou_threshold

-> Tensor v'5 Float

score_threshold

-> Tensor Build Int32

selected_indices

nthElement Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 Int32

n

-> Tensor Build t

values

nthElement' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Int32

n

-> Tensor Build t

values

oneHot Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64, Word8] tI) 
=> Tensor v'1 tI

indices

-> Tensor v'2 Int32

depth

-> Tensor v'3 t

on_value

-> Tensor v'4 t

off_value

-> Tensor Build t

output

oneHot' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64, Word8] tI) 
=> OpParams 
-> Tensor v'1 tI

indices

-> Tensor v'2 Int32

depth

-> Tensor v'3 t

on_value

-> Tensor v'4 t

off_value

-> Tensor Build t

output

orderedMapClear Source #

Arguments

:: MonadBuild m' 
=> [DataType]

dtypes

-> m' ControlNode 

orderedMapClear' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

dtypes

-> m' ControlNode 

orderedMapIncompleteSize Source #

Arguments

:: MonadBuild m' 
=> [DataType]

dtypes

-> m' (Tensor Value Int32)

size

orderedMapPeek Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> m' (TensorList Value dtypes)

values

orderedMapPeek' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> m' (TensorList Value dtypes)

values

orderedMapSize Source #

Arguments

:: MonadBuild m' 
=> [DataType]

dtypes

-> m' (Tensor Value Int32)

size

orderedMapSize' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

dtypes

-> m' (Tensor Value Int32)

size

orderedMapStage Source #

Arguments

:: (MonadBuild m', TensorTypes fake_dtypes) 
=> [DataType]

dtypes

-> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> TensorList v'3 fake_dtypes

values

-> m' ControlNode 

orderedMapStage' Source #

Arguments

:: (MonadBuild m', TensorTypes fake_dtypes) 
=> OpParams 
-> [DataType]

dtypes

-> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> TensorList v'3 fake_dtypes

values

-> m' ControlNode 

orderedMapUnstage Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> m' (TensorList Value dtypes)

values

orderedMapUnstage' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> Tensor v'1 Int64

key

-> Tensor v'2 Int32

indices

-> m' (TensorList Value dtypes)

values

orderedMapUnstageNoKey Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> Tensor v'1 Int32

indices

-> m' (Tensor Value Int64, TensorList Value dtypes)

(key, values)

  • key
  • values

orderedMapUnstageNoKey' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> Tensor v'1 Int32

indices

-> m' (Tensor Value Int64, TensorList Value dtypes)

(key, values)

  • key
  • values

outfeedDequeue Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Shape

shape: The shape of the tensor.

-> m' (Tensor Value dtype)

output: A tensor that will be read from the device outfeed.

Retrieves a single tensor from the computation outfeed. This operation will

block indefinitely until data is available.

outfeedDequeue' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Shape

shape: The shape of the tensor.

-> m' (Tensor Value dtype)

output: A tensor that will be read from the device outfeed.

outfeedDequeueTuple Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> m' (TensorList Value dtypes)

outputs: A list of tensors that will be read from the outfeed.

Retrieve multiple values that will be emitted by the computation as an XLA

tuple. This operations will block indefinitely until data is available. Output i corresponds to XLA tuple element i.

outfeedDequeueTuple' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> m' (TensorList Value dtypes)

outputs: A list of tensors that will be read from the outfeed.

outfeedEnqueue Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 dtype

input: A tensor that will be inserted into the outfeed queue.

-> m' ControlNode 

An op which emits a single Tensor value from an XLA computation.

outfeedEnqueue' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 dtype

input: A tensor that will be inserted into the outfeed queue.

-> m' ControlNode 

outfeedEnqueueTuple Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> TensorList v'1 dtypes

inputs: A list of tensors that will be inserted into the outfeed queue as an XLA tuple.

-> m' ControlNode 

An op which emits multiple Tensor values from an XLA computation.

outfeedEnqueueTuple' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> TensorList v'1 dtypes

inputs: A list of tensors that will be inserted into the outfeed queue as an XLA tuple.

-> m' ControlNode 

pack Source #

Arguments

:: TensorType t 
=> [Tensor v'1 t]

values

-> Tensor Build t

output

pack' Source #

Arguments

:: TensorType t 
=> OpParams 
-> [Tensor v'1 t]

values

-> Tensor Build t

output

pad Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tpaddings) 
=> Tensor v'1 t

input

-> Tensor v'2 tpaddings

paddings

-> Tensor Build t

output

pad' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tpaddings) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tpaddings

paddings

-> Tensor Build t

output

padV2 Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tpaddings) 
=> Tensor v'1 t

input

-> Tensor v'2 tpaddings

paddings

-> Tensor v'3 t

constant_values

-> Tensor Build t

output

padV2' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tpaddings) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tpaddings

paddings

-> Tensor v'3 t

constant_values

-> Tensor Build t

output

paddedBatchDataset Source #

Arguments

:: TensorTypes toutput_types 
=> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

batch_size

-> [Tensor v'3 Int64]

padded_shapes

-> TensorList v'4 toutput_types

padding_values

-> Tensor Build Variant

handle

paddedBatchDataset' Source #

Arguments

:: TensorTypes toutput_types 
=> OpParams 
-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

batch_size

-> [Tensor v'3 Int64]

padded_shapes

-> TensorList v'4 toutput_types

padding_values

-> Tensor Build Variant

handle

paddingFIFOQueue Source #

Arguments

:: MonadBuild m' 
=> [DataType]

component_types

-> m' (Tensor Ref ByteString)

handle

paddingFIFOQueue' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

component_types

-> m' (Tensor Ref ByteString)

handle

paddingFIFOQueueV2 Source #

Arguments

:: MonadBuild m' 
=> [DataType]

component_types

-> m' (Tensor Value ResourceHandle)

handle

paddingFIFOQueueV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

component_types

-> m' (Tensor Value ResourceHandle)

handle

parallelConcat Source #

Arguments

:: TensorType t 
=> Shape

shape

-> [Tensor v'1 t]

values

-> Tensor Build t

output

parallelConcat' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Shape

shape

-> [Tensor v'1 t]

values

-> Tensor Build t

output

parallelDynamicStitch Source #

Arguments

:: TensorType t 
=> [Tensor v'1 Int32]

indices

-> [Tensor v'2 t]

data

-> Tensor Build t

merged

parallelDynamicStitch' Source #

Arguments

:: TensorType t 
=> OpParams 
-> [Tensor v'1 Int32]

indices

-> [Tensor v'2 t]

data

-> Tensor Build t

merged

parameterizedTruncatedNormal Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t) 
=> Tensor v'1 t

shape

-> Tensor v'2 dtype

means

-> Tensor v'3 dtype

stdevs

-> Tensor v'4 dtype

minvals

-> Tensor v'5 dtype

maxvals

-> m' (Tensor Value dtype)

output

parameterizedTruncatedNormal' Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t) 
=> OpParams 
-> Tensor v'1 t

shape

-> Tensor v'2 dtype

means

-> Tensor v'3 dtype

stdevs

-> Tensor v'4 dtype

minvals

-> Tensor v'5 dtype

maxvals

-> m' (Tensor Value dtype)

output

parseExample Source #

Arguments

:: (OneOfs '[ByteString, Int64, Float] sparse_types, OneOfs '[ByteString, Int64, Float] tdense) 
=> Tensor v'1 ByteString

serialized

-> Tensor v'2 ByteString

names

-> [Tensor v'3 ByteString]

sparse_keys

-> [Tensor v'4 ByteString]

dense_keys

-> TensorList v'5 tdense

dense_defaults

-> ([Tensor Build Int64], TensorList Build sparse_types, [Tensor Build Int64], TensorList Build tdense)

(sparse_indices, sparse_values, sparse_shapes, dense_values)

  • sparse_indices
  • sparse_values
  • sparse_shapes
  • dense_values

parseExample' Source #

Arguments

:: (OneOfs '[ByteString, Int64, Float] sparse_types, OneOfs '[ByteString, Int64, Float] tdense) 
=> OpParams 
-> Tensor v'1 ByteString

serialized

-> Tensor v'2 ByteString

names

-> [Tensor v'3 ByteString]

sparse_keys

-> [Tensor v'4 ByteString]

dense_keys

-> TensorList v'5 tdense

dense_defaults

-> ([Tensor Build Int64], TensorList Build sparse_types, [Tensor Build Int64], TensorList Build tdense)

(sparse_indices, sparse_values, sparse_shapes, dense_values)

  • sparse_indices
  • sparse_values
  • sparse_shapes
  • dense_values

parseSingleExample Source #

Arguments

:: (OneOfs '[ByteString, Int64, Float] sparse_types, OneOfs '[ByteString, Int64, Float] tdense) 
=> Int64

num_sparse

-> Tensor v'1 ByteString

serialized

-> TensorList v'2 tdense

dense_defaults

-> ([Tensor Build Int64], TensorList Build sparse_types, [Tensor Build Int64], TensorList Build tdense)

(sparse_indices, sparse_values, sparse_shapes, dense_values)

  • sparse_indices
  • sparse_values
  • sparse_shapes
  • dense_values

parseSingleExample' Source #

Arguments

:: (OneOfs '[ByteString, Int64, Float] sparse_types, OneOfs '[ByteString, Int64, Float] tdense) 
=> OpParams 
-> Int64

num_sparse

-> Tensor v'1 ByteString

serialized

-> TensorList v'2 tdense

dense_defaults

-> ([Tensor Build Int64], TensorList Build sparse_types, [Tensor Build Int64], TensorList Build tdense)

(sparse_indices, sparse_values, sparse_shapes, dense_values)

  • sparse_indices
  • sparse_values
  • sparse_shapes
  • dense_values

parseSingleSequenceExample Source #

Arguments

:: (OneOfs '[ByteString, Int64, Float] context_sparse_types, OneOfs '[ByteString, Int64, Float] tcontext_dense, OneOfs '[ByteString, Int64, Float] feature_list_dense_types, OneOfs '[ByteString, Int64, Float] feature_list_sparse_types) 
=> Tensor v'1 ByteString

serialized

-> Tensor v'2 ByteString

feature_list_dense_missing_assumed_empty

-> [Tensor v'3 ByteString]

context_sparse_keys

-> [Tensor v'4 ByteString]

context_dense_keys

-> [Tensor v'5 ByteString]

feature_list_sparse_keys

-> [Tensor v'6 ByteString]

feature_list_dense_keys

-> TensorList v'7 tcontext_dense

context_dense_defaults

-> Tensor v'8 ByteString

debug_name

-> ([Tensor Build Int64], TensorList Build context_sparse_types, [Tensor Build Int64], TensorList Build tcontext_dense, [Tensor Build Int64], TensorList Build feature_list_sparse_types, [Tensor Build Int64], TensorList Build feature_list_dense_types)

(context_sparse_indices, context_sparse_values, context_sparse_shapes, context_dense_values, feature_list_sparse_indices, feature_list_sparse_values, feature_list_sparse_shapes, feature_list_dense_values)

  • context_sparse_indices
  • context_sparse_values
  • context_sparse_shapes
  • context_dense_values
  • feature_list_sparse_indices
  • feature_list_sparse_values
  • feature_list_sparse_shapes
  • feature_list_dense_values

parseSingleSequenceExample' Source #

Arguments

:: (OneOfs '[ByteString, Int64, Float] context_sparse_types, OneOfs '[ByteString, Int64, Float] tcontext_dense, OneOfs '[ByteString, Int64, Float] feature_list_dense_types, OneOfs '[ByteString, Int64, Float] feature_list_sparse_types) 
=> OpParams 
-> Tensor v'1 ByteString

serialized

-> Tensor v'2 ByteString

feature_list_dense_missing_assumed_empty

-> [Tensor v'3 ByteString]

context_sparse_keys

-> [Tensor v'4 ByteString]

context_dense_keys

-> [Tensor v'5 ByteString]

feature_list_sparse_keys

-> [Tensor v'6 ByteString]

feature_list_dense_keys

-> TensorList v'7 tcontext_dense

context_dense_defaults

-> Tensor v'8 ByteString

debug_name

-> ([Tensor Build Int64], TensorList Build context_sparse_types, [Tensor Build Int64], TensorList Build tcontext_dense, [Tensor Build Int64], TensorList Build feature_list_sparse_types, [Tensor Build Int64], TensorList Build feature_list_dense_types)

(context_sparse_indices, context_sparse_values, context_sparse_shapes, context_dense_values, feature_list_sparse_indices, feature_list_sparse_values, feature_list_sparse_shapes, feature_list_dense_values)

  • context_sparse_indices
  • context_sparse_values
  • context_sparse_shapes
  • context_dense_values
  • feature_list_sparse_indices
  • feature_list_sparse_values
  • feature_list_sparse_shapes
  • feature_list_dense_values

parseTensor Source #

Arguments

:: TensorType out_type 
=> Tensor v'1 ByteString

serialized

-> Tensor Build out_type

output

parseTensor' Source #

Arguments

:: TensorType out_type 
=> OpParams 
-> Tensor v'1 ByteString

serialized

-> Tensor Build out_type

output

placeholder Source #

Arguments

:: TensorType dtype 
=> Tensor Build dtype

output

placeholder' Source #

Arguments

:: TensorType dtype 
=> OpParams 
-> Tensor Build dtype

output

placeholderV2 Source #

Arguments

:: TensorType dtype 
=> Shape

shape

-> Tensor Build dtype

output

placeholderV2' Source #

Arguments

:: TensorType dtype 
=> OpParams 
-> Shape

shape

-> Tensor Build dtype

output

placeholderWithDefault Source #

Arguments

:: TensorType dtype 
=> Shape

shape

-> Tensor v'1 dtype

input

-> Tensor Build dtype

output

placeholderWithDefault' Source #

Arguments

:: TensorType dtype 
=> OpParams 
-> Shape

shape

-> Tensor v'1 dtype

input

-> Tensor Build dtype

output

polygamma Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

a

-> Tensor v'2 t

x

-> Tensor Build t

z

polygamma' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

a

-> Tensor v'2 t

x

-> Tensor Build t

z

pow Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

pow' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

prefetchDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

buffer_size

-> Tensor Build Variant

handle

prefetchDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

buffer_size

-> Tensor Build Variant

handle

prependFromQueueAndPaddedBatchDataset Source #

Arguments

:: TensorTypes toutput_types 
=> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

batch_size

-> [Tensor v'3 Int64]

padded_shapes

-> TensorList v'4 toutput_types

padding_values

-> Tensor Build Variant

handle

prependFromQueueAndPaddedBatchDataset' Source #

Arguments

:: TensorTypes toutput_types 
=> OpParams 
-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

batch_size

-> [Tensor v'3 Int64]

padded_shapes

-> TensorList v'4 toutput_types

padding_values

-> Tensor Build Variant

handle

preventGradient Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor Build t

output

preventGradient' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

print Source #

Arguments

:: (MonadBuild m', TensorType t, TensorTypes u) 
=> Tensor v'1 t

input

-> TensorList v'2 u

data

-> m' (Tensor Value t)

output

print' Source #

Arguments

:: (MonadBuild m', TensorType t, TensorTypes u) 
=> OpParams 
-> Tensor v'1 t

input

-> TensorList v'2 u

data

-> m' (Tensor Value t)

output

priorityQueue Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Ref ByteString)

handle

priorityQueue' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Ref ByteString)

handle

prod Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build t

output

prod' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build t

output

qr Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t)

(q, r)

  • q
  • r

qr' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t)

(q, r)

  • q
  • r

quantizeAndDequantize Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

quantizeAndDequantize' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

quantizeAndDequantizeV2 Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

input_min

-> Tensor v'3 t

input_max

-> Tensor Build t

output

quantizeAndDequantizeV2' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

input_min

-> Tensor v'3 t

input_max

-> Tensor Build t

output

quantizeAndDequantizeV3 Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 t

input_min

-> Tensor v'3 t

input_max

-> Tensor v'4 Int32

num_bits

-> Tensor Build t

output

quantizeAndDequantizeV3' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 t

input_min

-> Tensor v'3 t

input_max

-> Tensor v'4 Int32

num_bits

-> Tensor Build t

output

quantizeDownAndShrinkRange Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> Tensor v'1 tinput

input

-> Tensor v'2 Float

input_min

-> Tensor v'3 Float

input_max

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(output, output_min, output_max)

  • output
  • output_min
  • output_max

quantizeDownAndShrinkRange' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> OpParams 
-> Tensor v'1 tinput

input

-> Tensor v'2 Float

input_min

-> Tensor v'3 Float

input_max

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(output, output_min, output_max)

  • output
  • output_min
  • output_max

quantizeV2 Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] t 
=> Tensor v'1 Float

input

-> Tensor v'2 Float

min_range

-> Tensor v'3 Float

max_range

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(output, output_min, output_max)

  • output
  • output_min
  • output_max

quantizeV2' Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] t 
=> OpParams 
-> Tensor v'1 Float

input

-> Tensor v'2 Float

min_range

-> Tensor v'3 Float

max_range

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(output, output_min, output_max)

  • output
  • output_min
  • output_max

quantizedAdd Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] t1, OneOf '[Int16, Int32, Word16, Word8] t2, OneOf '[Int16, Int32, Word16, Word8] toutput) 
=> Tensor v'1 t1

x

-> Tensor v'2 t2

y

-> Tensor v'3 Float

min_x

-> Tensor v'4 Float

max_x

-> Tensor v'5 Float

min_y

-> Tensor v'6 Float

max_y

-> (Tensor Build toutput, Tensor Build Float, Tensor Build Float)

(z, min_z, max_z)

  • z
  • min_z
  • max_z

quantizedAdd' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] t1, OneOf '[Int16, Int32, Word16, Word8] t2, OneOf '[Int16, Int32, Word16, Word8] toutput) 
=> OpParams 
-> Tensor v'1 t1

x

-> Tensor v'2 t2

y

-> Tensor v'3 Float

min_x

-> Tensor v'4 Float

max_x

-> Tensor v'5 Float

min_y

-> Tensor v'6 Float

max_y

-> (Tensor Build toutput, Tensor Build Float, Tensor Build Float)

(z, min_z, max_z)

  • z
  • min_z
  • max_z

quantizedAvgPool Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] t 
=> Tensor v'1 t

input

-> Tensor v'2 Float

min_input

-> Tensor v'3 Float

max_input

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(output, min_output, max_output)

  • output
  • min_output
  • max_output

quantizedAvgPool' Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Float

min_input

-> Tensor v'3 Float

max_input

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(output, min_output, max_output)

  • output
  • min_output
  • max_output

quantizedBatchNormWithGlobalNormalization Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> Bool

scale_after_normalization

-> Float

variance_epsilon

-> Tensor v'1 tinput

t

-> Tensor v'2 Float

t_min

-> Tensor v'3 Float

t_max

-> Tensor v'4 tinput

m

-> Tensor v'5 Float

m_min

-> Tensor v'6 Float

m_max

-> Tensor v'7 tinput

v

-> Tensor v'8 Float

v_min

-> Tensor v'9 Float

v_max

-> Tensor v'10 tinput

beta

-> Tensor v'11 Float

beta_min

-> Tensor v'12 Float

beta_max

-> Tensor v'13 tinput

gamma

-> Tensor v'14 Float

gamma_min

-> Tensor v'15 Float

gamma_max

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(result, result_min, result_max)

  • result
  • result_min
  • result_max

quantizedBatchNormWithGlobalNormalization' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> OpParams 
-> Bool

scale_after_normalization

-> Float

variance_epsilon

-> Tensor v'1 tinput

t

-> Tensor v'2 Float

t_min

-> Tensor v'3 Float

t_max

-> Tensor v'4 tinput

m

-> Tensor v'5 Float

m_min

-> Tensor v'6 Float

m_max

-> Tensor v'7 tinput

v

-> Tensor v'8 Float

v_min

-> Tensor v'9 Float

v_max

-> Tensor v'10 tinput

beta

-> Tensor v'11 Float

beta_min

-> Tensor v'12 Float

beta_max

-> Tensor v'13 tinput

gamma

-> Tensor v'14 Float

gamma_min

-> Tensor v'15 Float

gamma_max

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(result, result_min, result_max)

  • result
  • result_min
  • result_max

quantizedBiasAdd Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] t1, OneOf '[Int16, Int32, Word16, Word8] t2, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> Tensor v'1 t1

input

-> Tensor v'2 t2

bias

-> Tensor v'3 Float

min_input

-> Tensor v'4 Float

max_input

-> Tensor v'5 Float

min_bias

-> Tensor v'6 Float

max_bias

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(output, min_out, max_out)

  • output
  • min_out
  • max_out

quantizedBiasAdd' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] t1, OneOf '[Int16, Int32, Word16, Word8] t2, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> OpParams 
-> Tensor v'1 t1

input

-> Tensor v'2 t2

bias

-> Tensor v'3 Float

min_input

-> Tensor v'4 Float

max_input

-> Tensor v'5 Float

min_bias

-> Tensor v'6 Float

max_bias

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(output, min_out, max_out)

  • output
  • min_out
  • max_out

quantizedConcat Source #

Arguments

:: TensorType t 
=> Tensor v'1 Int32

concat_dim

-> [Tensor v'2 t]

values

-> [Tensor v'3 Float]

input_mins

-> [Tensor v'4 Float]

input_maxes

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(output, output_min, output_max)

  • output
  • output_min
  • output_max

quantizedConcat' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 Int32

concat_dim

-> [Tensor v'2 t]

values

-> [Tensor v'3 Float]

input_mins

-> [Tensor v'4 Float]

input_maxes

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(output, output_min, output_max)

  • output
  • output_min
  • output_max

quantizedConv2D Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] tfilter, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> Tensor v'1 tinput

input

-> Tensor v'2 tfilter

filter

-> Tensor v'3 Float

min_input

-> Tensor v'4 Float

max_input

-> Tensor v'5 Float

min_filter

-> Tensor v'6 Float

max_filter

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(output, min_output, max_output)

  • output
  • min_output
  • max_output

quantizedConv2D' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] tfilter, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> OpParams 
-> Tensor v'1 tinput

input

-> Tensor v'2 tfilter

filter

-> Tensor v'3 Float

min_input

-> Tensor v'4 Float

max_input

-> Tensor v'5 Float

min_filter

-> Tensor v'6 Float

max_filter

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(output, min_output, max_output)

  • output
  • min_output
  • max_output

quantizedInstanceNorm Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] t 
=> Tensor v'1 t

x

-> Tensor v'2 Float

x_min

-> Tensor v'3 Float

x_max

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(y, y_min, y_max)

  • y
  • y_min
  • y_max

quantizedInstanceNorm' Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 Float

x_min

-> Tensor v'3 Float

x_max

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(y, y_min, y_max)

  • y
  • y_min
  • y_max

quantizedMatMul Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] t1, OneOf '[Int16, Int32, Word16, Word8] t2, OneOf '[Int16, Int32, Word16, Word8] toutput) 
=> Tensor v'1 t1

a

-> Tensor v'2 t2

b

-> Tensor v'3 Float

min_a

-> Tensor v'4 Float

max_a

-> Tensor v'5 Float

min_b

-> Tensor v'6 Float

max_b

-> (Tensor Build toutput, Tensor Build Float, Tensor Build Float)

(out, min_out, max_out)

  • out
  • min_out
  • max_out

quantizedMatMul' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] t1, OneOf '[Int16, Int32, Word16, Word8] t2, OneOf '[Int16, Int32, Word16, Word8] toutput) 
=> OpParams 
-> Tensor v'1 t1

a

-> Tensor v'2 t2

b

-> Tensor v'3 Float

min_a

-> Tensor v'4 Float

max_a

-> Tensor v'5 Float

min_b

-> Tensor v'6 Float

max_b

-> (Tensor Build toutput, Tensor Build Float, Tensor Build Float)

(out, min_out, max_out)

  • out
  • min_out
  • max_out

quantizedMaxPool Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] t 
=> Tensor v'1 t

input

-> Tensor v'2 Float

min_input

-> Tensor v'3 Float

max_input

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(output, min_output, max_output)

  • output
  • min_output
  • max_output

quantizedMaxPool' Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Float

min_input

-> Tensor v'3 Float

max_input

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(output, min_output, max_output)

  • output
  • min_output
  • max_output

quantizedMul Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] t1, OneOf '[Int16, Int32, Word16, Word8] t2, OneOf '[Int16, Int32, Word16, Word8] toutput) 
=> Tensor v'1 t1

x

-> Tensor v'2 t2

y

-> Tensor v'3 Float

min_x

-> Tensor v'4 Float

max_x

-> Tensor v'5 Float

min_y

-> Tensor v'6 Float

max_y

-> (Tensor Build toutput, Tensor Build Float, Tensor Build Float)

(z, min_z, max_z)

  • z
  • min_z
  • max_z

quantizedMul' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] t1, OneOf '[Int16, Int32, Word16, Word8] t2, OneOf '[Int16, Int32, Word16, Word8] toutput) 
=> OpParams 
-> Tensor v'1 t1

x

-> Tensor v'2 t2

y

-> Tensor v'3 Float

min_x

-> Tensor v'4 Float

max_x

-> Tensor v'5 Float

min_y

-> Tensor v'6 Float

max_y

-> (Tensor Build toutput, Tensor Build Float, Tensor Build Float)

(z, min_z, max_z)

  • z
  • min_z
  • max_z

quantizedRelu Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> Tensor v'1 tinput

features

-> Tensor v'2 Float

min_features

-> Tensor v'3 Float

max_features

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(activations, min_activations, max_activations)

  • activations
  • min_activations
  • max_activations

quantizedRelu' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> OpParams 
-> Tensor v'1 tinput

features

-> Tensor v'2 Float

min_features

-> Tensor v'3 Float

max_features

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(activations, min_activations, max_activations)

  • activations
  • min_activations
  • max_activations

quantizedRelu6 Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> Tensor v'1 tinput

features

-> Tensor v'2 Float

min_features

-> Tensor v'3 Float

max_features

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(activations, min_activations, max_activations)

  • activations
  • min_activations
  • max_activations

quantizedRelu6' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> OpParams 
-> Tensor v'1 tinput

features

-> Tensor v'2 Float

min_features

-> Tensor v'3 Float

max_features

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(activations, min_activations, max_activations)

  • activations
  • min_activations
  • max_activations

quantizedReluX Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> Tensor v'1 tinput

features

-> Tensor v'2 Float

max_value

-> Tensor v'3 Float

min_features

-> Tensor v'4 Float

max_features

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(activations, min_activations, max_activations)

  • activations
  • min_activations
  • max_activations

quantizedReluX' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> OpParams 
-> Tensor v'1 tinput

features

-> Tensor v'2 Float

max_value

-> Tensor v'3 Float

min_features

-> Tensor v'4 Float

max_features

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(activations, min_activations, max_activations)

  • activations
  • min_activations
  • max_activations

quantizedReshape Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tshape) 
=> Tensor v'1 t

tensor

-> Tensor v'2 tshape

shape

-> Tensor v'3 Float

input_min

-> Tensor v'4 Float

input_max

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(output, output_min, output_max)

  • output
  • output_min
  • output_max

quantizedReshape' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tshape) 
=> OpParams 
-> Tensor v'1 t

tensor

-> Tensor v'2 tshape

shape

-> Tensor v'3 Float

input_min

-> Tensor v'4 Float

input_max

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(output, output_min, output_max)

  • output
  • output_min
  • output_max

quantizedResizeBilinear Source #

Arguments

:: OneOf '[Int32, Word8, Float] t 
=> Tensor v'1 t

images

-> Tensor v'2 Int32

size

-> Tensor v'3 Float

min

-> Tensor v'4 Float

max

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(resized_images, out_min, out_max)

  • resized_images
  • out_min
  • out_max

quantizedResizeBilinear' Source #

Arguments

:: OneOf '[Int32, Word8, Float] t 
=> OpParams 
-> Tensor v'1 t

images

-> Tensor v'2 Int32

size

-> Tensor v'3 Float

min

-> Tensor v'4 Float

max

-> (Tensor Build t, Tensor Build Float, Tensor Build Float)

(resized_images, out_min, out_max)

  • resized_images
  • out_min
  • out_max

queueClose Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

handle

-> m' ControlNode 

queueCloseV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

handle

-> m' ControlNode 

queueCloseV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> m' ControlNode 

queueDequeue Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> Tensor Ref ByteString

handle

-> m' (TensorList Value component_types)

components

queueDequeue' Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> m' (TensorList Value component_types)

components

queueDequeueMany Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

n

-> m' (TensorList Value component_types)

components

queueDequeueMany' Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

n

-> m' (TensorList Value component_types)

components

queueDequeueManyV2 Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

n

-> m' (TensorList Value component_types)

components

queueDequeueManyV2' Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

n

-> m' (TensorList Value component_types)

components

queueDequeueUpTo Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

n

-> m' (TensorList Value component_types)

components

queueDequeueUpTo' Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

n

-> m' (TensorList Value component_types)

components

queueDequeueUpToV2 Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

n

-> m' (TensorList Value component_types)

components

queueDequeueUpToV2' Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

n

-> m' (TensorList Value component_types)

components

queueDequeueV2 Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> Tensor v'1 ResourceHandle

handle

-> m' (TensorList Value component_types)

components

queueDequeueV2' Source #

Arguments

:: (MonadBuild m', TensorTypes component_types) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> m' (TensorList Value component_types)

components

queueEnqueue Source #

Arguments

:: (MonadBuild m', TensorTypes tcomponents) 
=> Tensor Ref ByteString

handle

-> TensorList v'2 tcomponents

components

-> m' ControlNode 

queueEnqueue' Source #

Arguments

:: (MonadBuild m', TensorTypes tcomponents) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> TensorList v'2 tcomponents

components

-> m' ControlNode 

queueEnqueueMany Source #

Arguments

:: (MonadBuild m', TensorTypes tcomponents) 
=> Tensor Ref ByteString

handle

-> TensorList v'2 tcomponents

components

-> m' ControlNode 

queueEnqueueMany' Source #

Arguments

:: (MonadBuild m', TensorTypes tcomponents) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> TensorList v'2 tcomponents

components

-> m' ControlNode 

queueEnqueueManyV2 Source #

Arguments

:: (MonadBuild m', TensorTypes tcomponents) 
=> Tensor v'1 ResourceHandle

handle

-> TensorList v'2 tcomponents

components

-> m' ControlNode 

queueEnqueueManyV2' Source #

Arguments

:: (MonadBuild m', TensorTypes tcomponents) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> TensorList v'2 tcomponents

components

-> m' ControlNode 

queueEnqueueV2 Source #

Arguments

:: (MonadBuild m', TensorTypes tcomponents) 
=> Tensor v'1 ResourceHandle

handle

-> TensorList v'2 tcomponents

components

-> m' ControlNode 

queueEnqueueV2' Source #

Arguments

:: (MonadBuild m', TensorTypes tcomponents) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> TensorList v'2 tcomponents

components

-> m' ControlNode 

queueIsClosed Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

handle

-> m' (Tensor Value Bool)

is_closed

queueIsClosed' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

handle

-> m' (Tensor Value Bool)

is_closed

queueIsClosedV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

handle

-> m' (Tensor Value Bool)

is_closed

queueIsClosedV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> m' (Tensor Value Bool)

is_closed

queueSize Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

handle

-> m' (Tensor Value Int32)

size

queueSize' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

handle

-> m' (Tensor Value Int32)

size

queueSizeV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

handle

-> m' (Tensor Value Int32)

size

queueSizeV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> m' (Tensor Value Int32)

size

rFFT Source #

Arguments

:: Tensor v'1 Float

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build (Complex Float)

output

rFFT' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build (Complex Float)

output

rFFT2D Source #

Arguments

:: Tensor v'1 Float

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build (Complex Float)

output

rFFT2D' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build (Complex Float)

output

rFFT3D Source #

Arguments

:: Tensor v'1 Float

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build (Complex Float)

output

rFFT3D' Source #

Arguments

:: OpParams 
-> Tensor v'1 Float

input

-> Tensor v'2 Int32

fft_length

-> Tensor Build (Complex Float)

output

rGBToHSV Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

images

-> Tensor Build t

output

rGBToHSV' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

images

-> Tensor Build t

output

randomCrop Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word8, Double, Float] t) 
=> Tensor v'1 t

image

-> Tensor v'2 Int64

size

-> m' (Tensor Value t)

output

randomCrop' Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 t

image

-> Tensor v'2 Int64

size

-> m' (Tensor Value t)

output

randomDataset Source #

Arguments

:: MonadBuild m' 
=> [DataType]

output_types

-> Tensor v'1 Int64

seed

-> Tensor v'2 Int64

seed2

-> m' (Tensor Value Variant)

handle

randomDataset' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

output_types

-> Tensor v'1 Int64

seed

-> Tensor v'2 Int64

seed2

-> m' (Tensor Value Variant)

handle

randomGamma Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] s, OneOf '[Word16, Double, Float] t) 
=> Tensor v'1 s

shape

-> Tensor v'2 t

alpha

-> m' (Tensor Value t)

output

randomGamma' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] s, OneOf '[Word16, Double, Float] t) 
=> OpParams 
-> Tensor v'1 s

shape

-> Tensor v'2 t

alpha

-> m' (Tensor Value t)

output

randomPoisson Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] s, OneOf '[Word16, Double, Float] dtype) 
=> Tensor v'1 s

shape

-> Tensor v'2 dtype

rate

-> m' (Tensor Value dtype)

output

randomPoisson' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] s, OneOf '[Word16, Double, Float] dtype) 
=> OpParams 
-> Tensor v'1 s

shape

-> Tensor v'2 dtype

rate

-> m' (Tensor Value dtype)

output

randomPoissonV2 Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] s, OneOf '[Int32, Int64, Word16, Double, Float] r, OneOf '[Int32, Int64, Word16, Double, Float] dtype) 
=> Tensor v'1 s

shape

-> Tensor v'2 r

rate

-> m' (Tensor Value dtype)

output

randomPoissonV2' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] s, OneOf '[Int32, Int64, Word16, Double, Float] r, OneOf '[Int32, Int64, Word16, Double, Float] dtype) 
=> OpParams 
-> Tensor v'1 s

shape

-> Tensor v'2 r

rate

-> m' (Tensor Value dtype)

output

randomShuffle Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 t

value

-> m' (Tensor Value t)

output

randomShuffle' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 t

value

-> m' (Tensor Value t)

output

randomShuffleQueue Source #

Arguments

:: MonadBuild m' 
=> [DataType]

component_types

-> m' (Tensor Ref ByteString)

handle

randomShuffleQueue' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

component_types

-> m' (Tensor Ref ByteString)

handle

randomShuffleQueueV2 Source #

Arguments

:: MonadBuild m' 
=> [DataType]

component_types

-> m' (Tensor Value ResourceHandle)

handle

randomShuffleQueueV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

component_types

-> m' (Tensor Value ResourceHandle)

handle

randomStandardNormal Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t) 
=> Tensor v'1 t

shape

-> m' (Tensor Value dtype)

output

randomStandardNormal' Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t) 
=> OpParams 
-> Tensor v'1 t

shape

-> m' (Tensor Value dtype)

output

randomUniform Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t) 
=> Tensor v'1 t

shape

-> m' (Tensor Value dtype)

output

randomUniform' Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t) 
=> OpParams 
-> Tensor v'1 t

shape

-> m' (Tensor Value dtype)

output

randomUniformInt Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] tout, OneOf '[Int32, Int64] t) 
=> Tensor v'1 t

shape

-> Tensor v'2 tout

minval

-> Tensor v'3 tout

maxval

-> m' (Tensor Value tout)

output

randomUniformInt' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] tout, OneOf '[Int32, Int64] t) 
=> OpParams 
-> Tensor v'1 t

shape

-> Tensor v'2 tout

minval

-> Tensor v'3 tout

maxval

-> m' (Tensor Value tout)

output

range Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] tidx 
=> Tensor v'1 tidx

start

-> Tensor v'2 tidx

limit

-> Tensor v'3 tidx

delta

-> Tensor Build tidx

output

range' Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] tidx 
=> OpParams 
-> Tensor v'1 tidx

start

-> Tensor v'2 tidx

limit

-> Tensor v'3 tidx

delta

-> Tensor Build tidx

output

rangeDataset Source #

Arguments

:: MonadBuild m' 
=> [DataType]

output_types

-> Tensor v'1 Int64

start

-> Tensor v'2 Int64

stop

-> Tensor v'3 Int64

step

-> m' (Tensor Value Variant)

handle

rangeDataset' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

output_types

-> Tensor v'1 Int64

start

-> Tensor v'2 Int64

stop

-> Tensor v'3 Int64

step

-> m' (Tensor Value Variant)

handle

rank Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor Build Int32

output

rank' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build Int32

output

readFile Source #

Arguments

:: Tensor v'1 ByteString

filename

-> Tensor Build ByteString

contents

readFile' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

filename

-> Tensor Build ByteString

contents

readVariableOp Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 ResourceHandle

resource

-> m' (Tensor Value dtype)

value

readVariableOp' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> m' (Tensor Value dtype)

value

readerNumRecordsProduced Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

reader_handle

-> m' (Tensor Value Int64)

records_produced

readerNumRecordsProduced' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

reader_handle

-> m' (Tensor Value Int64)

records_produced

readerNumRecordsProducedV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

reader_handle

-> m' (Tensor Value Int64)

records_produced

readerNumRecordsProducedV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

reader_handle

-> m' (Tensor Value Int64)

records_produced

readerNumWorkUnitsCompleted Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

reader_handle

-> m' (Tensor Value Int64)

units_completed

readerNumWorkUnitsCompleted' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

reader_handle

-> m' (Tensor Value Int64)

units_completed

readerNumWorkUnitsCompletedV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

reader_handle

-> m' (Tensor Value Int64)

units_completed

readerNumWorkUnitsCompletedV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

reader_handle

-> m' (Tensor Value Int64)

units_completed

readerRead Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

reader_handle

-> Tensor Ref ByteString

queue_handle

-> m' (Tensor Value ByteString, Tensor Value ByteString)

(key, value)

  • key
  • value

readerRead' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

reader_handle

-> Tensor Ref ByteString

queue_handle

-> m' (Tensor Value ByteString, Tensor Value ByteString)

(key, value)

  • key
  • value

readerReadUpTo Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

reader_handle

-> Tensor Ref ByteString

queue_handle

-> Tensor v'3 Int64

num_records

-> m' (Tensor Value ByteString, Tensor Value ByteString)

(keys, values)

  • keys
  • values

readerReadUpTo' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

reader_handle

-> Tensor Ref ByteString

queue_handle

-> Tensor v'3 Int64

num_records

-> m' (Tensor Value ByteString, Tensor Value ByteString)

(keys, values)

  • keys
  • values

readerReadUpToV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

reader_handle

-> Tensor v'2 ResourceHandle

queue_handle

-> Tensor v'3 Int64

num_records

-> m' (Tensor Value ByteString, Tensor Value ByteString)

(keys, values)

  • keys
  • values

readerReadUpToV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

reader_handle

-> Tensor v'2 ResourceHandle

queue_handle

-> Tensor v'3 Int64

num_records

-> m' (Tensor Value ByteString, Tensor Value ByteString)

(keys, values)

  • keys
  • values

readerReadV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

reader_handle

-> Tensor v'2 ResourceHandle

queue_handle

-> m' (Tensor Value ByteString, Tensor Value ByteString)

(key, value)

  • key
  • value

readerReadV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

reader_handle

-> Tensor v'2 ResourceHandle

queue_handle

-> m' (Tensor Value ByteString, Tensor Value ByteString)

(key, value)

  • key
  • value

readerReset Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

reader_handle

-> m' ControlNode 

readerReset' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

reader_handle

-> m' ControlNode 

readerResetV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

reader_handle

-> m' ControlNode 

readerResetV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

reader_handle

-> m' ControlNode 

readerRestoreState Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

reader_handle

-> Tensor v'2 ByteString

state

-> m' ControlNode 

readerRestoreState' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

reader_handle

-> Tensor v'2 ByteString

state

-> m' ControlNode 

readerRestoreStateV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

reader_handle

-> Tensor v'2 ByteString

state

-> m' ControlNode 

readerRestoreStateV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

reader_handle

-> Tensor v'2 ByteString

state

-> m' ControlNode 

readerSerializeState Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

reader_handle

-> m' (Tensor Value ByteString)

state

readerSerializeStateV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

reader_handle

-> m' (Tensor Value ByteString)

state

readerSerializeStateV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

reader_handle

-> m' (Tensor Value ByteString)

state

real Source #

Arguments

:: (OneOf '[Complex Double, Complex Float] t, OneOf '[Double, Float] tout) 
=> Tensor v'1 t

input

-> Tensor Build tout

output

real' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float] t, OneOf '[Double, Float] tout) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build tout

output

recordInput Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Value ByteString)

records

recordInput' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Value ByteString)

records

reduceJoin Source #

Arguments

:: Tensor v'1 ByteString

inputs

-> Tensor v'2 Int32

reduction_indices

-> Tensor Build ByteString

output

reduceJoin' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

inputs

-> Tensor v'2 Int32

reduction_indices

-> Tensor Build ByteString

output

refEnter Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref t

data

-> m' (Tensor Ref t)

output

refEnter' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref t

data

-> m' (Tensor Ref t)

output

refExit Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref t

data

-> m' (Tensor Ref t)

output

refExit' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref t

data

-> m' (Tensor Ref t)

output

refIdentity Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref t

input

-> m' (Tensor Ref t)

output

refIdentity' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref t

input

-> m' (Tensor Ref t)

output

refMerge Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> [Tensor Ref t]

inputs

-> m' (Tensor Ref t, Tensor Value Int32)

(output, value_index)

  • output
  • value_index

refMerge' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> [Tensor Ref t]

inputs

-> m' (Tensor Ref t, Tensor Value Int32)

(output, value_index)

  • output
  • value_index

refNextIteration Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref t

data

-> m' (Tensor Ref t)

output

refNextIteration' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref t

data

-> m' (Tensor Ref t)

output

refSelect Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 Int32

index

-> [Tensor Ref t]

inputs

-> m' (Tensor Ref t)

output

refSelect' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 Int32

index

-> [Tensor Ref t]

inputs

-> m' (Tensor Ref t)

output

refSwitch Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref t

data

-> Tensor v'2 Bool

pred

-> m' (Tensor Ref t, Tensor Ref t)

(output_false, output_true)

  • output_false
  • output_true

refSwitch' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref t

data

-> Tensor v'2 Bool

pred

-> m' (Tensor Ref t, Tensor Ref t)

(output_false, output_true)

  • output_false
  • output_true

regexFullMatch Source #

Arguments

:: Tensor v'1 ByteString

input

-> Tensor v'2 ByteString

pattern

-> Tensor Build Bool

output

regexFullMatch' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

input

-> Tensor v'2 ByteString

pattern

-> Tensor Build Bool

output

regexReplace Source #

Arguments

:: Tensor v'1 ByteString

input

-> Tensor v'2 ByteString

pattern

-> Tensor v'3 ByteString

rewrite

-> Tensor Build ByteString

output

regexReplace' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

input

-> Tensor v'2 ByteString

pattern

-> Tensor v'3 ByteString

rewrite

-> Tensor Build ByteString

output

relu Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

features

-> Tensor Build t

activations

relu' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

features

-> Tensor Build t

activations

relu6 Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

features

-> Tensor Build t

activations

relu6' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

features

-> Tensor Build t

activations

relu6Grad Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

gradients

-> Tensor v'2 t

features

-> Tensor Build t

backprops

relu6Grad' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

gradients

-> Tensor v'2 t

features

-> Tensor Build t

backprops

reluGrad Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

gradients

-> Tensor v'2 t

features

-> Tensor Build t

backprops

reluGrad' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

gradients

-> Tensor v'2 t

features

-> Tensor Build t

backprops

remoteFusedGraphExecute Source #

Arguments

:: (TensorTypes tinputs, TensorTypes toutputs) 
=> TensorList v'1 tinputs

inputs

-> TensorList Build toutputs

outputs

remoteFusedGraphExecute' Source #

Arguments

:: (TensorTypes tinputs, TensorTypes toutputs) 
=> OpParams 
-> TensorList v'1 tinputs

inputs

-> TensorList Build toutputs

outputs

repeatDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

count

-> Tensor Build Variant

handle

repeatDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

count

-> Tensor Build Variant

handle

requantizationRange Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] tinput 
=> Tensor v'1 tinput

input

-> Tensor v'2 Float

input_min

-> Tensor v'3 Float

input_max

-> (Tensor Build Float, Tensor Build Float)

(output_min, output_max)

  • output_min
  • output_max

requantizationRange' Source #

Arguments

:: OneOf '[Int16, Int32, Word16, Word8] tinput 
=> OpParams 
-> Tensor v'1 tinput

input

-> Tensor v'2 Float

input_min

-> Tensor v'3 Float

input_max

-> (Tensor Build Float, Tensor Build Float)

(output_min, output_max)

  • output_min
  • output_max

requantize Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> Tensor v'1 tinput

input

-> Tensor v'2 Float

input_min

-> Tensor v'3 Float

input_max

-> Tensor v'4 Float

requested_output_min

-> Tensor v'5 Float

requested_output_max

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(output, output_min, output_max)

  • output
  • output_min
  • output_max

requantize' Source #

Arguments

:: (OneOf '[Int16, Int32, Word16, Word8] tinput, OneOf '[Int16, Int32, Word16, Word8] out_type) 
=> OpParams 
-> Tensor v'1 tinput

input

-> Tensor v'2 Float

input_min

-> Tensor v'3 Float

input_max

-> Tensor v'4 Float

requested_output_min

-> Tensor v'5 Float

requested_output_max

-> (Tensor Build out_type, Tensor Build Float, Tensor Build Float)

(output, output_min, output_max)

  • output
  • output_min
  • output_max

reshape Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tshape) 
=> Tensor v'1 t

tensor

-> Tensor v'2 tshape

shape

-> Tensor Build t

output

reshape' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tshape) 
=> OpParams 
-> Tensor v'1 t

tensor

-> Tensor v'2 tshape

shape

-> Tensor Build t

output

resizeArea Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

images

-> Tensor v'2 Int32

size

-> Tensor Build Float

resized_images

resizeArea' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

images

-> Tensor v'2 Int32

size

-> Tensor Build Float

resized_images

resizeBicubic Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

images

-> Tensor v'2 Int32

size

-> Tensor Build Float

resized_images

resizeBicubic' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

images

-> Tensor v'2 Int32

size

-> Tensor Build Float

resized_images

resizeBicubicGrad Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 Float

grads

-> Tensor v'2 t

original_image

-> Tensor Build t

output

resizeBicubicGrad' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 Float

grads

-> Tensor v'2 t

original_image

-> Tensor Build t

output

resizeBilinear Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

images

-> Tensor v'2 Int32

size

-> Tensor Build Float

resized_images

resizeBilinear' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

images

-> Tensor v'2 Int32

size

-> Tensor Build Float

resized_images

resizeBilinearGrad Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 Float

grads

-> Tensor v'2 t

original_image

-> Tensor Build t

output

resizeBilinearGrad' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 Float

grads

-> Tensor v'2 t

original_image

-> Tensor Build t

output

resizeNearestNeighbor Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

images

-> Tensor v'2 Int32

size

-> Tensor Build t

resized_images

resizeNearestNeighbor' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

images

-> Tensor v'2 Int32

size

-> Tensor Build t

resized_images

resizeNearestNeighborGrad Source #

Arguments

:: OneOf '[Int32, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

grads

-> Tensor v'2 Int32

size

-> Tensor Build t

output

resizeNearestNeighborGrad' Source #

Arguments

:: OneOf '[Int32, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

grads

-> Tensor v'2 Int32

size

-> Tensor Build t

output

resourceApplyAdaMax Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

m

-> Tensor v'3 ResourceHandle

v

-> Tensor v'4 t

beta1_power

-> Tensor v'5 t

lr

-> Tensor v'6 t

beta1

-> Tensor v'7 t

beta2

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> m' ControlNode 

resourceApplyAdaMax' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

m

-> Tensor v'3 ResourceHandle

v

-> Tensor v'4 t

beta1_power

-> Tensor v'5 t

lr

-> Tensor v'6 t

beta1

-> Tensor v'7 t

beta2

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> m' ControlNode 

resourceApplyAdadelta Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

accum_update

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

epsilon

-> Tensor v'7 t

grad

-> m' ControlNode 

resourceApplyAdadelta' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

accum_update

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

epsilon

-> Tensor v'7 t

grad

-> m' ControlNode 

resourceApplyAdagradDA Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

gradient_accumulator

-> Tensor v'3 ResourceHandle

gradient_squared_accumulator

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 Int64

global_step

-> m' ControlNode 

resourceApplyAdagradDA' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

gradient_accumulator

-> Tensor v'3 ResourceHandle

gradient_squared_accumulator

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 Int64

global_step

-> m' ControlNode 

resourceApplyAdam Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

m

-> Tensor v'3 ResourceHandle

v

-> Tensor v'4 t

beta1_power

-> Tensor v'5 t

beta2_power

-> Tensor v'6 t

lr

-> Tensor v'7 t

beta1

-> Tensor v'8 t

beta2

-> Tensor v'9 t

epsilon

-> Tensor v'10 t

grad

-> m' ControlNode 

resourceApplyAdam' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

m

-> Tensor v'3 ResourceHandle

v

-> Tensor v'4 t

beta1_power

-> Tensor v'5 t

beta2_power

-> Tensor v'6 t

lr

-> Tensor v'7 t

beta1

-> Tensor v'8 t

beta2

-> Tensor v'9 t

epsilon

-> Tensor v'10 t

grad

-> m' ControlNode 

resourceApplyAddSign Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

m

-> Tensor v'3 t

lr

-> Tensor v'4 t

alpha

-> Tensor v'5 t

sign_decay

-> Tensor v'6 t

beta

-> Tensor v'7 t

grad

-> m' ControlNode 

resourceApplyAddSign' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

m

-> Tensor v'3 t

lr

-> Tensor v'4 t

alpha

-> Tensor v'5 t

sign_decay

-> Tensor v'6 t

beta

-> Tensor v'7 t

grad

-> m' ControlNode 

resourceApplyCenteredRMSProp Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

mg

-> Tensor v'3 ResourceHandle

ms

-> Tensor v'4 ResourceHandle

mom

-> Tensor v'5 t

lr

-> Tensor v'6 t

rho

-> Tensor v'7 t

momentum

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> m' ControlNode 

resourceApplyCenteredRMSProp' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

mg

-> Tensor v'3 ResourceHandle

ms

-> Tensor v'4 ResourceHandle

mom

-> Tensor v'5 t

lr

-> Tensor v'6 t

rho

-> Tensor v'7 t

momentum

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> m' ControlNode 

resourceApplyFtrl Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

linear

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 t

lr_power

-> m' ControlNode 

resourceApplyFtrl' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

linear

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 t

lr_power

-> m' ControlNode 

resourceApplyFtrlV2 Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

linear

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 t

l2_shrinkage

-> Tensor v'9 t

lr_power

-> m' ControlNode 

resourceApplyFtrlV2' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

linear

-> Tensor v'4 t

grad

-> Tensor v'5 t

lr

-> Tensor v'6 t

l1

-> Tensor v'7 t

l2

-> Tensor v'8 t

l2_shrinkage

-> Tensor v'9 t

lr_power

-> m' ControlNode 

resourceApplyPowerSign Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

m

-> Tensor v'3 t

lr

-> Tensor v'4 t

logbase

-> Tensor v'5 t

sign_decay

-> Tensor v'6 t

beta

-> Tensor v'7 t

grad

-> m' ControlNode 

resourceApplyPowerSign' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

m

-> Tensor v'3 t

lr

-> Tensor v'4 t

logbase

-> Tensor v'5 t

sign_decay

-> Tensor v'6 t

beta

-> Tensor v'7 t

grad

-> m' ControlNode 

resourceApplyRMSProp Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

ms

-> Tensor v'3 ResourceHandle

mom

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

momentum

-> Tensor v'7 t

epsilon

-> Tensor v'8 t

grad

-> m' ControlNode 

resourceApplyRMSProp' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

ms

-> Tensor v'3 ResourceHandle

mom

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

momentum

-> Tensor v'7 t

epsilon

-> Tensor v'8 t

grad

-> m' ControlNode 

resourceCountUpTo Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] t) 
=> Int64

limit

-> Tensor v'1 ResourceHandle

resource

-> m' (Tensor Value t)

output

resourceCountUpTo' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] t) 
=> OpParams 
-> Int64

limit

-> Tensor v'1 ResourceHandle

resource

-> m' (Tensor Value t)

output

resourceGather Source #

Arguments

:: (MonadBuild m', TensorType dtype, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> m' (Tensor Value dtype)

output

resourceGather' Source #

Arguments

:: (MonadBuild m', TensorType dtype, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> m' (Tensor Value dtype)

output

resourceScatterAdd Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterAdd' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterDiv Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterDiv' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterMax Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterMax' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterMin Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterMin' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterMul Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterMul' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterNdUpdate Source #

Arguments

:: (MonadBuild m', TensorType t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' ControlNode 

resourceScatterNdUpdate' Source #

Arguments

:: (MonadBuild m', TensorType t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' ControlNode 

resourceScatterSub Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterSub' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterUpdate Source #

Arguments

:: (MonadBuild m', TensorType dtype, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceScatterUpdate' Source #

Arguments

:: (MonadBuild m', TensorType dtype, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> Tensor v'2 tindices

indices

-> Tensor v'3 dtype

updates

-> m' ControlNode 

resourceSparseApplyAdadelta Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

accum_update

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

epsilon

-> Tensor v'7 t

grad

-> Tensor v'8 tindices

indices

-> m' ControlNode 

resourceSparseApplyAdadelta' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

accum_update

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

epsilon

-> Tensor v'7 t

grad

-> Tensor v'8 tindices

indices

-> m' ControlNode 

resourceSparseApplyAdagrad Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> m' ControlNode 

resourceSparseApplyAdagrad' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> m' ControlNode 

resourceSparseApplyAdagradDA Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

gradient_accumulator

-> Tensor v'3 ResourceHandle

gradient_squared_accumulator

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 Int64

global_step

-> m' ControlNode 

resourceSparseApplyAdagradDA' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

gradient_accumulator

-> Tensor v'3 ResourceHandle

gradient_squared_accumulator

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 Int64

global_step

-> m' ControlNode 

resourceSparseApplyCenteredRMSProp Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

mg

-> Tensor v'3 ResourceHandle

ms

-> Tensor v'4 ResourceHandle

mom

-> Tensor v'5 t

lr

-> Tensor v'6 t

rho

-> Tensor v'7 t

momentum

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> Tensor v'10 tindices

indices

-> m' ControlNode 

resourceSparseApplyCenteredRMSProp' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

mg

-> Tensor v'3 ResourceHandle

ms

-> Tensor v'4 ResourceHandle

mom

-> Tensor v'5 t

lr

-> Tensor v'6 t

rho

-> Tensor v'7 t

momentum

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> Tensor v'10 tindices

indices

-> m' ControlNode 

resourceSparseApplyFtrl Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

linear

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 t

lr_power

-> m' ControlNode 

resourceSparseApplyFtrl' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

linear

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 t

lr_power

-> m' ControlNode 

resourceSparseApplyFtrlV2 Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

linear

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 t

l2_shrinkage

-> Tensor v'10 t

lr_power

-> m' ControlNode 

resourceSparseApplyFtrlV2' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 ResourceHandle

linear

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 t

l2_shrinkage

-> Tensor v'10 t

lr_power

-> m' ControlNode 

resourceSparseApplyMomentum Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

momentum

-> m' ControlNode 

resourceSparseApplyMomentum' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

momentum

-> m' ControlNode 

resourceSparseApplyProximalAdagrad Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

l1

-> Tensor v'5 t

l2

-> Tensor v'6 t

grad

-> Tensor v'7 tindices

indices

-> m' ControlNode 

resourceSparseApplyProximalAdagrad' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

l1

-> Tensor v'5 t

l2

-> Tensor v'6 t

grad

-> Tensor v'7 tindices

indices

-> m' ControlNode 

resourceSparseApplyProximalGradientDescent Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 t

alpha

-> Tensor v'3 t

l1

-> Tensor v'4 t

l2

-> Tensor v'5 t

grad

-> Tensor v'6 tindices

indices

-> m' ControlNode 

resourceSparseApplyProximalGradientDescent' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 t

alpha

-> Tensor v'3 t

l1

-> Tensor v'4 t

l2

-> Tensor v'5 t

grad

-> Tensor v'6 tindices

indices

-> m' ControlNode 

resourceSparseApplyRMSProp Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

ms

-> Tensor v'3 ResourceHandle

mom

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

momentum

-> Tensor v'7 t

epsilon

-> Tensor v'8 t

grad

-> Tensor v'9 tindices

indices

-> m' ControlNode 

resourceSparseApplyRMSProp' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 ResourceHandle

var

-> Tensor v'2 ResourceHandle

ms

-> Tensor v'3 ResourceHandle

mom

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

momentum

-> Tensor v'7 t

epsilon

-> Tensor v'8 t

grad

-> Tensor v'9 tindices

indices

-> m' ControlNode 

resourceStridedSliceAssign Source #

Arguments

:: (MonadBuild m', TensorType t, OneOf '[Int32, Int64] index) 
=> Tensor v'1 ResourceHandle

ref

-> Tensor v'2 index

begin

-> Tensor v'3 index

end

-> Tensor v'4 index

strides

-> Tensor v'5 t

value

-> m' ControlNode 

resourceStridedSliceAssign' Source #

Arguments

:: (MonadBuild m', TensorType t, OneOf '[Int32, Int64] index) 
=> OpParams 
-> Tensor v'1 ResourceHandle

ref

-> Tensor v'2 index

begin

-> Tensor v'3 index

end

-> Tensor v'4 index

strides

-> Tensor v'5 t

value

-> m' ControlNode 

restore Source #

Arguments

:: (MonadBuild m', TensorType dt) 
=> Tensor v'1 ByteString

file_pattern

-> Tensor v'2 ByteString

tensor_name

-> m' (Tensor Value dt)

tensor

restore' Source #

Arguments

:: (MonadBuild m', TensorType dt) 
=> OpParams 
-> Tensor v'1 ByteString

file_pattern

-> Tensor v'2 ByteString

tensor_name

-> m' (Tensor Value dt)

tensor

restoreSlice Source #

Arguments

:: (MonadBuild m', TensorType dt) 
=> Tensor v'1 ByteString

file_pattern

-> Tensor v'2 ByteString

tensor_name

-> Tensor v'3 ByteString

shape_and_slice

-> m' (Tensor Value dt)

tensor

restoreSlice' Source #

Arguments

:: (MonadBuild m', TensorType dt) 
=> OpParams 
-> Tensor v'1 ByteString

file_pattern

-> Tensor v'2 ByteString

tensor_name

-> Tensor v'3 ByteString

shape_and_slice

-> m' (Tensor Value dt)

tensor

restoreV2 Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> Tensor v'1 ByteString

prefix

-> Tensor v'2 ByteString

tensor_names

-> Tensor v'3 ByteString

shape_and_slices

-> m' (TensorList Value dtypes)

tensors

restoreV2' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> Tensor v'1 ByteString

prefix

-> Tensor v'2 ByteString

tensor_names

-> Tensor v'3 ByteString

shape_and_slices

-> m' (TensorList Value dtypes)

tensors

reverse Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Bool, ByteString, Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

tensor

-> Tensor v'2 Bool

dims

-> Tensor Build t

output

reverse' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Bool, ByteString, Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

tensor

-> Tensor v'2 Bool

dims

-> Tensor Build t

output

reverseSequence Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tlen) 
=> Int64

seq_dim

-> Tensor v'1 t

input

-> Tensor v'2 tlen

seq_lengths

-> Tensor Build t

output

reverseSequence' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tlen) 
=> OpParams 
-> Int64

seq_dim

-> Tensor v'1 t

input

-> Tensor v'2 tlen

seq_lengths

-> Tensor Build t

output

reverseV2 Source #

Arguments

:: (OneOf '[Int32, Int64] tidx, OneOf '[Complex Double, Complex Float, Bool, ByteString, Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t) 
=> Tensor v'1 t

tensor

-> Tensor v'2 tidx

axis

-> Tensor Build t

output

reverseV2' Source #

Arguments

:: (OneOf '[Int32, Int64] tidx, OneOf '[Complex Double, Complex Float, Bool, ByteString, Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 t

tensor

-> Tensor v'2 tidx

axis

-> Tensor Build t

output

rightShift Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

rightShift' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

rint Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor Build t

y

rint' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

roll Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tshift, OneOf '[Int32, Int64] taxis) 
=> Tensor v'1 t

input

-> Tensor v'2 tshift

shift

-> Tensor v'3 taxis

axis

-> Tensor Build t

output

roll' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tshift, OneOf '[Int32, Int64] taxis) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tshift

shift

-> Tensor v'3 taxis

axis

-> Tensor Build t

output

rpc Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

address

-> Tensor v'2 ByteString

method

-> Tensor v'3 ByteString

request

-> m' (Tensor Value ByteString)

response

rpc' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

address

-> Tensor v'2 ByteString

method

-> Tensor v'3 ByteString

request

-> m' (Tensor Value ByteString)

response

rsqrtGrad Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Word16, Double, Float] t 
=> Tensor v'1 t

y

-> Tensor v'2 t

dy

-> Tensor Build t

z

rsqrtGrad' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

y

-> Tensor v'2 t

dy

-> Tensor Build t

z

sampleDistortedBoundingBox Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word8] t) 
=> Tensor v'1 t

image_size

-> Tensor v'2 Float

bounding_boxes

-> m' (Tensor Value t, Tensor Value t, Tensor Value Float)

(begin, size, bboxes)

  • begin
  • size
  • bboxes

sampleDistortedBoundingBox' Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word8] t) 
=> OpParams 
-> Tensor v'1 t

image_size

-> Tensor v'2 Float

bounding_boxes

-> m' (Tensor Value t, Tensor Value t, Tensor Value Float)

(begin, size, bboxes)

  • begin
  • size
  • bboxes

sampleDistortedBoundingBoxV2 Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word8] t) 
=> Tensor v'1 t

image_size

-> Tensor v'2 Float

bounding_boxes

-> Tensor v'3 Float

min_object_covered

-> m' (Tensor Value t, Tensor Value t, Tensor Value Float)

(begin, size, bboxes)

  • begin
  • size
  • bboxes

sampleDistortedBoundingBoxV2' Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word8] t) 
=> OpParams 
-> Tensor v'1 t

image_size

-> Tensor v'2 Float

bounding_boxes

-> Tensor v'3 Float

min_object_covered

-> m' (Tensor Value t, Tensor Value t, Tensor Value Float)

(begin, size, bboxes)

  • begin
  • size
  • bboxes

save Source #

Arguments

:: (MonadBuild m', TensorTypes t) 
=> Tensor v'1 ByteString

filename

-> Tensor v'2 ByteString

tensor_names

-> TensorList v'3 t

data

-> m' ControlNode 

save' Source #

Arguments

:: (MonadBuild m', TensorTypes t) 
=> OpParams 
-> Tensor v'1 ByteString

filename

-> Tensor v'2 ByteString

tensor_names

-> TensorList v'3 t

data

-> m' ControlNode 

saveSlices Source #

Arguments

:: (MonadBuild m', TensorTypes t) 
=> Tensor v'1 ByteString

filename

-> Tensor v'2 ByteString

tensor_names

-> Tensor v'3 ByteString

shapes_and_slices

-> TensorList v'4 t

data

-> m' ControlNode 

saveSlices' Source #

Arguments

:: (MonadBuild m', TensorTypes t) 
=> OpParams 
-> Tensor v'1 ByteString

filename

-> Tensor v'2 ByteString

tensor_names

-> Tensor v'3 ByteString

shapes_and_slices

-> TensorList v'4 t

data

-> m' ControlNode 

saveV2 Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> Tensor v'1 ByteString

prefix

-> Tensor v'2 ByteString

tensor_names

-> Tensor v'3 ByteString

shape_and_slices

-> TensorList v'4 dtypes

tensors

-> m' ControlNode 

saveV2' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> Tensor v'1 ByteString

prefix

-> Tensor v'2 ByteString

tensor_names

-> Tensor v'3 ByteString

shape_and_slices

-> TensorList v'4 dtypes

tensors

-> m' ControlNode 

scatterAdd Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterAdd' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterDiv Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterDiv' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterMax Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64, Word16, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterMax' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64, Word16, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterMin Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64, Word16, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterMin' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64, Word16, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterMul Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterMul' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterNd Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 tindices

indices

-> Tensor v'2 t

updates

-> Tensor v'3 tindices

shape

-> Tensor Build t

output

scatterNd' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 tindices

indices

-> Tensor v'2 t

updates

-> Tensor v'3 tindices

shape

-> Tensor Build t

output

scatterNdAdd Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterNdAdd' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterNdNonAliasingAdd Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 t

input

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> Tensor Build t

output

scatterNdNonAliasingAdd' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> Tensor Build t

output

scatterNdSub Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterNdSub' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterNdUpdate Source #

Arguments

:: (MonadBuild m', TensorType t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterNdUpdate' Source #

Arguments

:: (MonadBuild m', TensorType t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterSub Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterSub' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterUpdate Source #

Arguments

:: (MonadBuild m', TensorType t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

scatterUpdate' Source #

Arguments

:: (MonadBuild m', TensorType t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 tindices

indices

-> Tensor v'3 t

updates

-> m' (Tensor Ref t)

output_ref

sdcaFprint Source #

Arguments

:: Tensor v'1 ByteString

input

-> Tensor Build Int64

output

sdcaFprint' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

input

-> Tensor Build Int64

output

sdcaOptimizer Source #

Arguments

:: Float

l1

-> Float

l2

-> Int64

num_inner_iterations

-> Int64

num_loss_partitions

-> [Tensor v'1 Int64]

sparse_example_indices

-> [Tensor v'2 Int64]

sparse_feature_indices

-> [Tensor v'3 Float]

sparse_feature_values

-> [Tensor v'4 Float]

dense_features

-> Tensor v'5 Float

example_weights

-> Tensor v'6 Float

example_labels

-> [Tensor v'7 Int64]

sparse_indices

-> [Tensor v'8 Float]

sparse_weights

-> [Tensor v'9 Float]

dense_weights

-> Tensor v'10 Float

example_state_data

-> (Tensor Build Float, [Tensor Build Float], [Tensor Build Float])

(out_example_state_data, out_delta_sparse_weights, out_delta_dense_weights)

  • out_example_state_data
  • out_delta_sparse_weights
  • out_delta_dense_weights

sdcaOptimizer' Source #

Arguments

:: OpParams 
-> Float

l1

-> Float

l2

-> Int64

num_inner_iterations

-> Int64

num_loss_partitions

-> [Tensor v'1 Int64]

sparse_example_indices

-> [Tensor v'2 Int64]

sparse_feature_indices

-> [Tensor v'3 Float]

sparse_feature_values

-> [Tensor v'4 Float]

dense_features

-> Tensor v'5 Float

example_weights

-> Tensor v'6 Float

example_labels

-> [Tensor v'7 Int64]

sparse_indices

-> [Tensor v'8 Float]

sparse_weights

-> [Tensor v'9 Float]

dense_weights

-> Tensor v'10 Float

example_state_data

-> (Tensor Build Float, [Tensor Build Float], [Tensor Build Float])

(out_example_state_data, out_delta_sparse_weights, out_delta_dense_weights)

  • out_example_state_data
  • out_delta_sparse_weights
  • out_delta_dense_weights

sdcaShrinkL1 Source #

Arguments

:: MonadBuild m' 
=> Float

l1

-> Float

l2

-> [Tensor Ref Float]

weights

-> m' ControlNode 

sdcaShrinkL1' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Float

l1

-> Float

l2

-> [Tensor Ref Float]

weights

-> m' ControlNode 

segmentMax Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor Build t

output

segmentMax' Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor Build t

output

segmentMean Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor Build t

output

segmentMean' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor Build t

output

segmentMin Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor Build t

output

segmentMin' Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor Build t

output

segmentProd Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor Build t

output

segmentProd' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor Build t

output

segmentSum Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor Build t

output

segmentSum' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor Build t

output

select Source #

Arguments

:: TensorType t 
=> Tensor v'1 Bool

condition

-> Tensor v'2 t

t

-> Tensor v'3 t

e

-> Tensor Build t

output

select' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 Bool

condition

-> Tensor v'2 t

t

-> Tensor v'3 t

e

-> Tensor Build t

output

selfAdjointEig Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

input

-> Tensor Build t

output

selfAdjointEig' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

selfAdjointEigV2 Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t)

(e, v)

  • e
  • v

selfAdjointEigV2' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t)

(e, v)

  • e
  • v

selu Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

features

-> Tensor Build t

activations

selu' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

features

-> Tensor Build t

activations

seluGrad Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

gradients

-> Tensor v'2 t

outputs

-> Tensor Build t

backprops

seluGrad' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

gradients

-> Tensor v'2 t

outputs

-> Tensor Build t

backprops

serializeIterator Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

resource_handle

-> m' (Tensor Value Variant)

serialized

serializeIterator' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource_handle

-> m' (Tensor Value Variant)

serialized

serializeManySparse Source #

Arguments

:: (TensorType t, OneOf '[ByteString, Variant] out_type) 
=> Tensor v'1 Int64

sparse_indices

-> Tensor v'2 t

sparse_values

-> Tensor v'3 Int64

sparse_shape

-> Tensor Build out_type

serialized_sparse

serializeManySparse' Source #

Arguments

:: (TensorType t, OneOf '[ByteString, Variant] out_type) 
=> OpParams 
-> Tensor v'1 Int64

sparse_indices

-> Tensor v'2 t

sparse_values

-> Tensor v'3 Int64

sparse_shape

-> Tensor Build out_type

serialized_sparse

serializeSparse Source #

Arguments

:: (TensorType t, OneOf '[ByteString, Variant] out_type) 
=> Tensor v'1 Int64

sparse_indices

-> Tensor v'2 t

sparse_values

-> Tensor v'3 Int64

sparse_shape

-> Tensor Build out_type

serialized_sparse

serializeSparse' Source #

Arguments

:: (TensorType t, OneOf '[ByteString, Variant] out_type) 
=> OpParams 
-> Tensor v'1 Int64

sparse_indices

-> Tensor v'2 t

sparse_values

-> Tensor v'3 Int64

sparse_shape

-> Tensor Build out_type

serialized_sparse

serializeTensor Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

tensor

-> Tensor Build ByteString

serialized

serializeTensor' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

tensor

-> Tensor Build ByteString

serialized

setSize Source #

Arguments

:: OneOf '[ByteString, Int16, Int32, Int64, Int8, Word16, Word8] t 
=> Tensor v'1 Int64

set_indices

-> Tensor v'2 t

set_values

-> Tensor v'3 Int64

set_shape

-> Tensor Build Int32

size

setSize' Source #

Arguments

:: OneOf '[ByteString, Int16, Int32, Int64, Int8, Word16, Word8] t 
=> OpParams 
-> Tensor v'1 Int64

set_indices

-> Tensor v'2 t

set_values

-> Tensor v'3 Int64

set_shape

-> Tensor Build Int32

size

setStatsAggregatorDataset Source #

Arguments

:: MonadBuild m' 
=> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 ResourceHandle

stats_aggregator

-> m' (Tensor Value Variant)

handle

setStatsAggregatorDataset' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 ResourceHandle

stats_aggregator

-> m' (Tensor Value Variant)

handle

shape Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_type) 
=> Tensor v'1 t

input

-> Tensor Build out_type

output

shape' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_type) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build out_type

output

shapeN Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_type) 
=> [Tensor v'1 t]

input

-> [Tensor Build out_type]

output

shapeN' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_type) 
=> OpParams 
-> [Tensor v'1 t]

input

-> [Tensor Build out_type]

output

shardedFilename Source #

Arguments

:: Tensor v'1 ByteString

basename

-> Tensor v'2 Int32

shard

-> Tensor v'3 Int32

num_shards

-> Tensor Build ByteString

filename

shardedFilename' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

basename

-> Tensor v'2 Int32

shard

-> Tensor v'3 Int32

num_shards

-> Tensor Build ByteString

filename

shardedFilespec Source #

Arguments

:: Tensor v'1 ByteString

basename

-> Tensor v'2 Int32

num_shards

-> Tensor Build ByteString

filename

shardedFilespec' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

basename

-> Tensor v'2 Int32

num_shards

-> Tensor Build ByteString

filename

shuffleAndRepeatDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

buffer_size

-> Tensor v'3 Int64

seed

-> Tensor v'4 Int64

seed2

-> Tensor v'5 Int64

count

-> Tensor Build Variant

handle

shuffleAndRepeatDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

buffer_size

-> Tensor v'3 Int64

seed

-> Tensor v'4 Int64

seed2

-> Tensor v'5 Int64

count

-> Tensor Build Variant

handle

shuffleDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

buffer_size

-> Tensor v'3 Int64

seed

-> Tensor v'4 Int64

seed2

-> Tensor Build Variant

handle

shuffleDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

buffer_size

-> Tensor v'3 Int64

seed

-> Tensor v'4 Int64

seed2

-> Tensor Build Variant

handle

shutdownDistributedTPU :: forall m'. MonadBuild m' => m' ControlNode Source #

An op that shuts down a running distributed TPU system. The Op returns

an error if no system is running.

sigmoidGrad Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Word16, Double, Float] t 
=> Tensor v'1 t

y

-> Tensor v'2 t

dy

-> Tensor Build t

z

sigmoidGrad' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

y

-> Tensor v'2 t

dy

-> Tensor Build t

z

size Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_type) 
=> Tensor v'1 t

input

-> Tensor Build out_type

output

size' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_type) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build out_type

output

skipDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

count

-> Tensor Build Variant

handle

skipDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

count

-> Tensor Build Variant

handle

skipgram Source #

Arguments

:: MonadBuild m' 
=> Int64

batch_size

-> m' (Tensor Value ByteString, Tensor Value Int32, Tensor Value Int64, Tensor Value Int32, Tensor Value Int64, Tensor Value Int32, Tensor Value Int32)

(vocab_word, vocab_freq, words_per_epoch, current_epoch, total_words_processed, examples, labels)

  • vocab_word
  • vocab_freq
  • words_per_epoch
  • current_epoch
  • total_words_processed
  • examples
  • labels

skipgram' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

batch_size

-> m' (Tensor Value ByteString, Tensor Value Int32, Tensor Value Int64, Tensor Value Int32, Tensor Value Int64, Tensor Value Int32, Tensor Value Int32)

(vocab_word, vocab_freq, words_per_epoch, current_epoch, total_words_processed, examples, labels)

  • vocab_word
  • vocab_freq
  • words_per_epoch
  • current_epoch
  • total_words_processed
  • examples
  • labels

slice Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] index) 
=> Tensor v'1 t

input

-> Tensor v'2 index

begin

-> Tensor v'3 index

size

-> Tensor Build t

output

slice' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] index) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 index

begin

-> Tensor v'3 index

size

-> Tensor Build t

output

slideDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

window_size

-> Tensor v'3 Int64

stride

-> Tensor Build Variant

handle

slideDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

window_size

-> Tensor v'3 Int64

stride

-> Tensor Build Variant

handle

snapshot Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor Build t

output

snapshot' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

softmax Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

logits

-> Tensor Build t

softmax

softmax' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

logits

-> Tensor Build t

softmax

softmaxCrossEntropyWithLogits Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> Tensor v'1 t

features

-> Tensor v'2 t

labels

-> (Tensor Build t, Tensor Build t)

(loss, backprop)

  • loss
  • backprop

softmaxCrossEntropyWithLogits' Source #

Arguments

:: OneOf '[Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

features

-> Tensor v'2 t

labels

-> (Tensor Build t, Tensor Build t)

(loss, backprop)

  • loss
  • backprop

softplus Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

features

-> Tensor Build t

activations

softplus' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

features

-> Tensor Build t

activations

softplusGrad Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

gradients

-> Tensor v'2 t

features

-> Tensor Build t

backprops

softplusGrad' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

gradients

-> Tensor v'2 t

features

-> Tensor Build t

backprops

softsign Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

features

-> Tensor Build t

activations

softsign' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

features

-> Tensor Build t

activations

softsignGrad Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

gradients

-> Tensor v'2 t

features

-> Tensor Build t

backprops

softsignGrad' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

gradients

-> Tensor v'2 t

features

-> Tensor Build t

backprops

spaceToBatch Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tpaddings) 
=> Int64

block_size

-> Tensor v'1 t

input

-> Tensor v'2 tpaddings

paddings

-> Tensor Build t

output

spaceToBatch' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tpaddings) 
=> OpParams 
-> Int64

block_size

-> Tensor v'1 t

input

-> Tensor v'2 tpaddings

paddings

-> Tensor Build t

output

spaceToBatchND Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tblock_shape, OneOf '[Int32, Int64] tpaddings) 
=> Tensor v'1 t

input

-> Tensor v'2 tblock_shape

block_shape

-> Tensor v'3 tpaddings

paddings

-> Tensor Build t

output

spaceToBatchND' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tblock_shape, OneOf '[Int32, Int64] tpaddings) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tblock_shape

block_shape

-> Tensor v'3 tpaddings

paddings

-> Tensor Build t

output

spaceToDepth Source #

Arguments

:: TensorType t 
=> Int64

block_size

-> Tensor v'1 t

input

-> Tensor Build t

output

spaceToDepth' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Int64

block_size

-> Tensor v'1 t

input

-> Tensor Build t

output

sparseAccumulatorApplyGradient Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype) 
=> Bool

has_known_shape

-> Tensor Ref ByteString

handle

-> Tensor v'2 Int64

local_step

-> Tensor v'3 Int64

gradient_indices

-> Tensor v'4 dtype

gradient_values

-> Tensor v'5 Int64

gradient_shape

-> m' ControlNode 

sparseAccumulatorApplyGradient' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype) 
=> OpParams 
-> Bool

has_known_shape

-> Tensor Ref ByteString

handle

-> Tensor v'2 Int64

local_step

-> Tensor v'3 Int64

gradient_indices

-> Tensor v'4 dtype

gradient_values

-> Tensor v'5 Int64

gradient_shape

-> m' ControlNode 

sparseAccumulatorTakeGradient Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

num_required

-> m' (Tensor Value Int64, Tensor Value dtype, Tensor Value Int64)

(indices, values, shape)

  • indices
  • values
  • shape

sparseAccumulatorTakeGradient' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] dtype) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

num_required

-> m' (Tensor Value Int64, Tensor Value dtype, Tensor Value Int64)

(indices, values, shape)

  • indices
  • values
  • shape

sparseAdd Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] treal) 
=> Tensor v'1 Int64

a_indices

-> Tensor v'2 t

a_values

-> Tensor v'3 Int64

a_shape

-> Tensor v'4 Int64

b_indices

-> Tensor v'5 t

b_values

-> Tensor v'6 Int64

b_shape

-> Tensor v'7 treal

thresh

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(sum_indices, sum_values, sum_shape)

  • sum_indices
  • sum_values
  • sum_shape

sparseAdd' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] treal) 
=> OpParams 
-> Tensor v'1 Int64

a_indices

-> Tensor v'2 t

a_values

-> Tensor v'3 Int64

a_shape

-> Tensor v'4 Int64

b_indices

-> Tensor v'5 t

b_values

-> Tensor v'6 Int64

b_shape

-> Tensor v'7 treal

thresh

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(sum_indices, sum_values, sum_shape)

  • sum_indices
  • sum_values
  • sum_shape

sparseAddGrad Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

backprop_val_grad

-> Tensor v'2 Int64

a_indices

-> Tensor v'3 Int64

b_indices

-> Tensor v'4 Int64

sum_indices

-> (Tensor Build t, Tensor Build t)

(a_val_grad, b_val_grad)

  • a_val_grad
  • b_val_grad

sparseAddGrad' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

backprop_val_grad

-> Tensor v'2 Int64

a_indices

-> Tensor v'3 Int64

b_indices

-> Tensor v'4 Int64

sum_indices

-> (Tensor Build t, Tensor Build t)

(a_val_grad, b_val_grad)

  • a_val_grad
  • b_val_grad

sparseApplyAdadelta Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

accum_update

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

epsilon

-> Tensor v'7 t

grad

-> Tensor v'8 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyAdadelta' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

accum_update

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

epsilon

-> Tensor v'7 t

grad

-> Tensor v'8 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyAdagrad Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyAdagrad' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyAdagradDA Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

var

-> Tensor Ref t

gradient_accumulator

-> Tensor Ref t

gradient_squared_accumulator

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 Int64

global_step

-> m' (Tensor Ref t)

out

sparseApplyAdagradDA' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

gradient_accumulator

-> Tensor Ref t

gradient_squared_accumulator

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 Int64

global_step

-> m' (Tensor Ref t)

out

sparseApplyCenteredRMSProp Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

var

-> Tensor Ref t

mg

-> Tensor Ref t

ms

-> Tensor Ref t

mom

-> Tensor v'5 t

lr

-> Tensor v'6 t

rho

-> Tensor v'7 t

momentum

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> Tensor v'10 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyCenteredRMSProp' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

mg

-> Tensor Ref t

ms

-> Tensor Ref t

mom

-> Tensor v'5 t

lr

-> Tensor v'6 t

rho

-> Tensor v'7 t

momentum

-> Tensor v'8 t

epsilon

-> Tensor v'9 t

grad

-> Tensor v'10 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyFtrl Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

linear

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 t

lr_power

-> m' (Tensor Ref t)

out

sparseApplyFtrl' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

linear

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 t

lr_power

-> m' (Tensor Ref t)

out

sparseApplyFtrlV2 Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

linear

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 t

l2_shrinkage

-> Tensor v'10 t

lr_power

-> m' (Tensor Ref t)

out

sparseApplyFtrlV2' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor Ref t

linear

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

lr

-> Tensor v'7 t

l1

-> Tensor v'8 t

l2

-> Tensor v'9 t

l2_shrinkage

-> Tensor v'10 t

lr_power

-> m' (Tensor Ref t)

out

sparseApplyMomentum Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

momentum

-> m' (Tensor Ref t)

out

sparseApplyMomentum' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

grad

-> Tensor v'5 tindices

indices

-> Tensor v'6 t

momentum

-> m' (Tensor Ref t)

out

sparseApplyProximalAdagrad Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

l1

-> Tensor v'5 t

l2

-> Tensor v'6 t

grad

-> Tensor v'7 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyProximalAdagrad' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

accum

-> Tensor v'3 t

lr

-> Tensor v'4 t

l1

-> Tensor v'5 t

l2

-> Tensor v'6 t

grad

-> Tensor v'7 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyProximalGradientDescent Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

var

-> Tensor v'2 t

alpha

-> Tensor v'3 t

l1

-> Tensor v'4 t

l2

-> Tensor v'5 t

grad

-> Tensor v'6 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyProximalGradientDescent' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor v'2 t

alpha

-> Tensor v'3 t

l1

-> Tensor v'4 t

l2

-> Tensor v'5 t

grad

-> Tensor v'6 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyRMSProp Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor Ref t

var

-> Tensor Ref t

ms

-> Tensor Ref t

mom

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

momentum

-> Tensor v'7 t

epsilon

-> Tensor v'8 t

grad

-> Tensor v'9 tindices

indices

-> m' (Tensor Ref t)

out

sparseApplyRMSProp' Source #

Arguments

:: (MonadBuild m', OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor Ref t

var

-> Tensor Ref t

ms

-> Tensor Ref t

mom

-> Tensor v'4 t

lr

-> Tensor v'5 t

rho

-> Tensor v'6 t

momentum

-> Tensor v'7 t

epsilon

-> Tensor v'8 t

grad

-> Tensor v'9 tindices

indices

-> m' (Tensor Ref t)

out

sparseConcat Source #

Arguments

:: TensorType t 
=> Int64

concat_dim

-> [Tensor v'1 Int64]

indices

-> [Tensor v'2 t]

values

-> [Tensor v'3 Int64]

shapes

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseConcat' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Int64

concat_dim

-> [Tensor v'1 Int64]

indices

-> [Tensor v'2 t]

values

-> [Tensor v'3 Int64]

shapes

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseCross Source #

Arguments

:: (OneOfs '[ByteString, Int64] sparse_types, OneOfs '[ByteString, Int64] dense_types, OneOf '[ByteString, Int64] out_type) 
=> Int64

hash_key

-> Bool

hashed_output

-> DataType

internal_type

-> Int64

num_buckets

-> [Tensor v'1 Int64]

indices

-> TensorList v'2 sparse_types

values

-> [Tensor v'3 Int64]

shapes

-> TensorList v'4 dense_types

dense_inputs

-> (Tensor Build Int64, Tensor Build out_type, Tensor Build Int64)

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseCross' Source #

Arguments

:: (OneOfs '[ByteString, Int64] sparse_types, OneOfs '[ByteString, Int64] dense_types, OneOf '[ByteString, Int64] out_type) 
=> OpParams 
-> Int64

hash_key

-> Bool

hashed_output

-> DataType

internal_type

-> Int64

num_buckets

-> [Tensor v'1 Int64]

indices

-> TensorList v'2 sparse_types

values

-> [Tensor v'3 Int64]

shapes

-> TensorList v'4 dense_types

dense_inputs

-> (Tensor Build Int64, Tensor Build out_type, Tensor Build Int64)

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseDenseCwiseAdd Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 Int64

sp_indices

-> Tensor v'2 t

sp_values

-> Tensor v'3 Int64

sp_shape

-> Tensor v'4 t

dense

-> Tensor Build t

output

sparseDenseCwiseAdd' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

sp_indices

-> Tensor v'2 t

sp_values

-> Tensor v'3 Int64

sp_shape

-> Tensor v'4 t

dense

-> Tensor Build t

output

sparseDenseCwiseDiv Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 Int64

sp_indices

-> Tensor v'2 t

sp_values

-> Tensor v'3 Int64

sp_shape

-> Tensor v'4 t

dense

-> Tensor Build t

output

sparseDenseCwiseDiv' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

sp_indices

-> Tensor v'2 t

sp_values

-> Tensor v'3 Int64

sp_shape

-> Tensor v'4 t

dense

-> Tensor Build t

output

sparseDenseCwiseMul Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 Int64

sp_indices

-> Tensor v'2 t

sp_values

-> Tensor v'3 Int64

sp_shape

-> Tensor v'4 t

dense

-> Tensor Build t

output

sparseDenseCwiseMul' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

sp_indices

-> Tensor v'2 t

sp_values

-> Tensor v'3 Int64

sp_shape

-> Tensor v'4 t

dense

-> Tensor Build t

output

sparseFillEmptyRows Source #

Arguments

:: TensorType t 
=> Tensor v'1 Int64

indices

-> Tensor v'2 t

values

-> Tensor v'3 Int64

dense_shape

-> Tensor v'4 t

default_value

-> (Tensor Build Int64, Tensor Build t, Tensor Build Bool, Tensor Build Int64)

(output_indices, output_values, empty_row_indicator, reverse_index_map)

  • output_indices
  • output_values
  • empty_row_indicator
  • reverse_index_map

sparseFillEmptyRows' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 Int64

indices

-> Tensor v'2 t

values

-> Tensor v'3 Int64

dense_shape

-> Tensor v'4 t

default_value

-> (Tensor Build Int64, Tensor Build t, Tensor Build Bool, Tensor Build Int64)

(output_indices, output_values, empty_row_indicator, reverse_index_map)

  • output_indices
  • output_values
  • empty_row_indicator
  • reverse_index_map

sparseFillEmptyRowsGrad Source #

Arguments

:: TensorType t 
=> Tensor v'1 Int64

reverse_index_map

-> Tensor v'2 t

grad_values

-> (Tensor Build t, Tensor Build t)

(d_values, d_default_value)

  • d_values
  • d_default_value

sparseFillEmptyRowsGrad' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 Int64

reverse_index_map

-> Tensor v'2 t

grad_values

-> (Tensor Build t, Tensor Build t)

(d_values, d_default_value)

  • d_values
  • d_default_value

sparseMatMul Source #

Arguments

:: (OneOf '[Word16, Float] ta, OneOf '[Word16, Float] tb) 
=> Tensor v'1 ta

a

-> Tensor v'2 tb

b

-> Tensor Build Float

product

sparseMatMul' Source #

Arguments

:: (OneOf '[Word16, Float] ta, OneOf '[Word16, Float] tb) 
=> OpParams 
-> Tensor v'1 ta

a

-> Tensor v'2 tb

b

-> Tensor Build Float

product

sparseReduceMax Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 Int64

input_indices

-> Tensor v'2 t

input_values

-> Tensor v'3 Int64

input_shape

-> Tensor v'4 Int32

reduction_axes

-> Tensor Build t

output

sparseReduceMax' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

input_indices

-> Tensor v'2 t

input_values

-> Tensor v'3 Int64

input_shape

-> Tensor v'4 Int32

reduction_axes

-> Tensor Build t

output

sparseReduceMaxSparse Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 Int64

input_indices

-> Tensor v'2 t

input_values

-> Tensor v'3 Int64

input_shape

-> Tensor v'4 Int32

reduction_axes

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseReduceMaxSparse' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

input_indices

-> Tensor v'2 t

input_values

-> Tensor v'3 Int64

input_shape

-> Tensor v'4 Int32

reduction_axes

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseReduceSum Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 Int64

input_indices

-> Tensor v'2 t

input_values

-> Tensor v'3 Int64

input_shape

-> Tensor v'4 Int32

reduction_axes

-> Tensor Build t

output

sparseReduceSum' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

input_indices

-> Tensor v'2 t

input_values

-> Tensor v'3 Int64

input_shape

-> Tensor v'4 Int32

reduction_axes

-> Tensor Build t

output

sparseReduceSumSparse Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 Int64

input_indices

-> Tensor v'2 t

input_values

-> Tensor v'3 Int64

input_shape

-> Tensor v'4 Int32

reduction_axes

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseReduceSumSparse' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

input_indices

-> Tensor v'2 t

input_values

-> Tensor v'3 Int64

input_shape

-> Tensor v'4 Int32

reduction_axes

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseReorder Source #

Arguments

:: TensorType t 
=> Tensor v'1 Int64

input_indices

-> Tensor v'2 t

input_values

-> Tensor v'3 Int64

input_shape

-> (Tensor Build Int64, Tensor Build t)

(output_indices, output_values)

  • output_indices
  • output_values

sparseReorder' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 Int64

input_indices

-> Tensor v'2 t

input_values

-> Tensor v'3 Int64

input_shape

-> (Tensor Build Int64, Tensor Build t)

(output_indices, output_values)

  • output_indices
  • output_values

sparseReshape Source #

Arguments

:: Tensor v'1 Int64

input_indices

-> Tensor v'2 Int64

input_shape

-> Tensor v'3 Int64

new_shape

-> (Tensor Build Int64, Tensor Build Int64)

(output_indices, output_shape)

  • output_indices
  • output_shape

sparseReshape' Source #

Arguments

:: OpParams 
-> Tensor v'1 Int64

input_indices

-> Tensor v'2 Int64

input_shape

-> Tensor v'3 Int64

new_shape

-> (Tensor Build Int64, Tensor Build Int64)

(output_indices, output_shape)

  • output_indices
  • output_shape

sparseSegmentMean Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor Build t

output

sparseSegmentMean' Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor Build t

output

sparseSegmentMeanGrad Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

grad

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor v'4 Int32

output_dim0

-> Tensor Build t

output

sparseSegmentMeanGrad' Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

grad

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor v'4 Int32

output_dim0

-> Tensor Build t

output

sparseSegmentMeanWithNumSegments Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx, OneOf '[Int32, Int64] tnumsegments) 
=> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor v'4 tnumsegments

num_segments

-> Tensor Build t

output

sparseSegmentMeanWithNumSegments' Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx, OneOf '[Int32, Int64] tnumsegments) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor v'4 tnumsegments

num_segments

-> Tensor Build t

output

sparseSegmentSqrtN Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor Build t

output

sparseSegmentSqrtN' Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor Build t

output

sparseSegmentSqrtNGrad Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

grad

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor v'4 Int32

output_dim0

-> Tensor Build t

output

sparseSegmentSqrtNGrad' Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

grad

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor v'4 Int32

output_dim0

-> Tensor Build t

output

sparseSegmentSqrtNWithNumSegments Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx, OneOf '[Int32, Int64] tnumsegments) 
=> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor v'4 tnumsegments

num_segments

-> Tensor Build t

output

sparseSegmentSqrtNWithNumSegments' Source #

Arguments

:: (OneOf '[Double, Float] t, OneOf '[Int32, Int64] tidx, OneOf '[Int32, Int64] tnumsegments) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor v'4 tnumsegments

num_segments

-> Tensor Build t

output

sparseSegmentSum Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor Build t

output

sparseSegmentSum' Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor Build t

output

sparseSegmentSumWithNumSegments Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx, OneOf '[Int32, Int64] tnumsegments) 
=> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor v'4 tnumsegments

num_segments

-> Tensor Build t

output

sparseSegmentSumWithNumSegments' Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx, OneOf '[Int32, Int64] tnumsegments) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tidx

indices

-> Tensor v'3 Int32

segment_ids

-> Tensor v'4 tnumsegments

num_segments

-> Tensor Build t

output

sparseSlice Source #

Arguments

:: TensorType t 
=> Tensor v'1 Int64

indices

-> Tensor v'2 t

values

-> Tensor v'3 Int64

shape

-> Tensor v'4 Int64

start

-> Tensor v'5 Int64

size

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseSlice' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 Int64

indices

-> Tensor v'2 t

values

-> Tensor v'3 Int64

shape

-> Tensor v'4 Int64

start

-> Tensor v'5 Int64

size

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseSoftmax Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 Int64

sp_indices

-> Tensor v'2 t

sp_values

-> Tensor v'3 Int64

sp_shape

-> Tensor Build t

output

sparseSoftmax' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

sp_indices

-> Tensor v'2 t

sp_values

-> Tensor v'3 Int64

sp_shape

-> Tensor Build t

output

sparseSoftmaxCrossEntropyWithLogits Source #

Arguments

:: (OneOf '[Word16, Double, Float] t, OneOf '[Int32, Int64] tlabels) 
=> Tensor v'1 t

features

-> Tensor v'2 tlabels

labels

-> (Tensor Build t, Tensor Build t)

(loss, backprop)

  • loss
  • backprop

sparseSoftmaxCrossEntropyWithLogits' Source #

Arguments

:: (OneOf '[Word16, Double, Float] t, OneOf '[Int32, Int64] tlabels) 
=> OpParams 
-> Tensor v'1 t

features

-> Tensor v'2 tlabels

labels

-> (Tensor Build t, Tensor Build t)

(loss, backprop)

  • loss
  • backprop

sparseSparseMaximum Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 Int64

a_indices

-> Tensor v'2 t

a_values

-> Tensor v'3 Int64

a_shape

-> Tensor v'4 Int64

b_indices

-> Tensor v'5 t

b_values

-> Tensor v'6 Int64

b_shape

-> (Tensor Build Int64, Tensor Build t)

(output_indices, output_values)

  • output_indices
  • output_values

sparseSparseMaximum' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

a_indices

-> Tensor v'2 t

a_values

-> Tensor v'3 Int64

a_shape

-> Tensor v'4 Int64

b_indices

-> Tensor v'5 t

b_values

-> Tensor v'6 Int64

b_shape

-> (Tensor Build Int64, Tensor Build t)

(output_indices, output_values)

  • output_indices
  • output_values

sparseSparseMinimum Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 Int64

a_indices

-> Tensor v'2 t

a_values

-> Tensor v'3 Int64

a_shape

-> Tensor v'4 Int64

b_indices

-> Tensor v'5 t

b_values

-> Tensor v'6 Int64

b_shape

-> (Tensor Build Int64, Tensor Build t)

(output_indices, output_values)

  • output_indices
  • output_values

sparseSparseMinimum' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 Int64

a_indices

-> Tensor v'2 t

a_values

-> Tensor v'3 Int64

a_shape

-> Tensor v'4 Int64

b_indices

-> Tensor v'5 t

b_values

-> Tensor v'6 Int64

b_shape

-> (Tensor Build Int64, Tensor Build t)

(output_indices, output_values)

  • output_indices
  • output_values

sparseSplit Source #

Arguments

:: TensorType t 
=> Int64

num_split

-> Tensor v'1 Int64

split_dim

-> Tensor v'2 Int64

indices

-> Tensor v'3 t

values

-> Tensor v'4 Int64

shape

-> ([Tensor Build Int64], [Tensor Build t], [Tensor Build Int64])

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseSplit' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Int64

num_split

-> Tensor v'1 Int64

split_dim

-> Tensor v'2 Int64

indices

-> Tensor v'3 t

values

-> Tensor v'4 Int64

shape

-> ([Tensor Build Int64], [Tensor Build t], [Tensor Build Int64])

(output_indices, output_values, output_shape)

  • output_indices
  • output_values
  • output_shape

sparseTensorDenseAdd Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 tindices

a_indices

-> Tensor v'2 t

a_values

-> Tensor v'3 tindices

a_shape

-> Tensor v'4 t

b

-> Tensor Build t

output

sparseTensorDenseAdd' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 tindices

a_indices

-> Tensor v'2 t

a_values

-> Tensor v'3 tindices

a_shape

-> Tensor v'4 t

b

-> Tensor Build t

output

sparseTensorDenseMatMul Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 tindices

a_indices

-> Tensor v'2 t

a_values

-> Tensor v'3 Int64

a_shape

-> Tensor v'4 t

b

-> Tensor Build t

product

sparseTensorDenseMatMul' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 tindices

a_indices

-> Tensor v'2 t

a_values

-> Tensor v'3 Int64

a_shape

-> Tensor v'4 t

b

-> Tensor Build t

product

sparseTensorSliceDataset Source #

Arguments

:: (MonadBuild m', TensorType tvalues) 
=> Tensor v'1 Int64

indices

-> Tensor v'2 tvalues

values

-> Tensor v'3 Int64

dense_shape

-> m' (Tensor Value Variant)

handle

sparseTensorSliceDataset' Source #

Arguments

:: (MonadBuild m', TensorType tvalues) 
=> OpParams 
-> Tensor v'1 Int64

indices

-> Tensor v'2 tvalues

values

-> Tensor v'3 Int64

dense_shape

-> m' (Tensor Value Variant)

handle

sparseToDense Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tindices) 
=> Tensor v'1 tindices

sparse_indices

-> Tensor v'2 tindices

output_shape

-> Tensor v'3 t

sparse_values

-> Tensor v'4 t

default_value

-> Tensor Build t

dense

sparseToDense' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tindices) 
=> OpParams 
-> Tensor v'1 tindices

sparse_indices

-> Tensor v'2 tindices

output_shape

-> Tensor v'3 t

sparse_values

-> Tensor v'4 t

default_value

-> Tensor Build t

dense

sparseToSparseSetOperation Source #

Arguments

:: OneOf '[ByteString, Int16, Int32, Int64, Int8, Word16, Word8] t 
=> Tensor v'1 Int64

set1_indices

-> Tensor v'2 t

set1_values

-> Tensor v'3 Int64

set1_shape

-> Tensor v'4 Int64

set2_indices

-> Tensor v'5 t

set2_values

-> Tensor v'6 Int64

set2_shape

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(result_indices, result_values, result_shape)

  • result_indices
  • result_values
  • result_shape

sparseToSparseSetOperation' Source #

Arguments

:: OneOf '[ByteString, Int16, Int32, Int64, Int8, Word16, Word8] t 
=> OpParams 
-> Tensor v'1 Int64

set1_indices

-> Tensor v'2 t

set1_values

-> Tensor v'3 Int64

set1_shape

-> Tensor v'4 Int64

set2_indices

-> Tensor v'5 t

set2_values

-> Tensor v'6 Int64

set2_shape

-> (Tensor Build Int64, Tensor Build t, Tensor Build Int64)

(result_indices, result_values, result_shape)

  • result_indices
  • result_values
  • result_shape

split Source #

Arguments

:: TensorType t 
=> Int64

num_split

-> Tensor v'1 Int32

split_dim

-> Tensor v'2 t

value

-> [Tensor Build t]

output

split' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Int64

num_split

-> Tensor v'1 Int32

split_dim

-> Tensor v'2 t

value

-> [Tensor Build t]

output

splitV Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tlen) 
=> Int64

num_split

-> Tensor v'1 t

value

-> Tensor v'2 tlen

size_splits

-> Tensor v'3 Int32

split_dim

-> [Tensor Build t]

output

splitV' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tlen) 
=> OpParams 
-> Int64

num_split

-> Tensor v'1 t

value

-> Tensor v'2 tlen

size_splits

-> Tensor v'3 Int32

split_dim

-> [Tensor Build t]

output

sqlDataset Source #

Arguments

:: MonadBuild m' 
=> [DataType]

output_types

-> Tensor v'1 ByteString

driver_name

-> Tensor v'2 ByteString

data_source_name

-> Tensor v'3 ByteString

query

-> m' (Tensor Value Variant)

handle

sqlDataset' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

output_types

-> Tensor v'1 ByteString

driver_name

-> Tensor v'2 ByteString

data_source_name

-> Tensor v'3 ByteString

query

-> m' (Tensor Value Variant)

handle

sqrtGrad Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Word16, Double, Float] t 
=> Tensor v'1 t

y

-> Tensor v'2 t

dy

-> Tensor Build t

z

sqrtGrad' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

y

-> Tensor v'2 t

dy

-> Tensor Build t

z

squeeze Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor Build t

output

squeeze' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

stack Source #

Arguments

:: MonadBuild m' 
=> DataType

elem_type

-> m' (Tensor Ref ByteString)

handle

stack' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

elem_type

-> m' (Tensor Ref ByteString)

handle

stackClose Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

handle

-> m' ControlNode 

stackCloseV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

handle

-> m' ControlNode 

stackCloseV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> m' ControlNode 

stackPop Source #

Arguments

:: (MonadBuild m', TensorType elem_type) 
=> Tensor Ref ByteString

handle

-> m' (Tensor Value elem_type)

elem

stackPop' Source #

Arguments

:: (MonadBuild m', TensorType elem_type) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> m' (Tensor Value elem_type)

elem

stackPopV2 Source #

Arguments

:: (MonadBuild m', TensorType elem_type) 
=> Tensor v'1 ResourceHandle

handle

-> m' (Tensor Value elem_type)

elem

stackPopV2' Source #

Arguments

:: (MonadBuild m', TensorType elem_type) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> m' (Tensor Value elem_type)

elem

stackPush Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 t

elem

-> m' (Tensor Value t)

output

stackPush' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 t

elem

-> m' (Tensor Value t)

output

stackPushV2 Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 t

elem

-> m' (Tensor Value t)

output

stackPushV2' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 t

elem

-> m' (Tensor Value t)

output

stackV2 Source #

Arguments

:: MonadBuild m' 
=> DataType

elem_type

-> Tensor v'1 Int32

max_size

-> m' (Tensor Value ResourceHandle)

handle

stackV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

elem_type

-> Tensor v'1 Int32

max_size

-> m' (Tensor Value ResourceHandle)

handle

stage Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> TensorList v'1 dtypes

values

-> m' ControlNode 

stage' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> TensorList v'1 dtypes

values

-> m' ControlNode 

stageClear Source #

Arguments

:: MonadBuild m' 
=> [DataType]

dtypes

-> m' ControlNode 

stageClear' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

dtypes

-> m' ControlNode 

stagePeek Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> Tensor v'1 Int32

index

-> m' (TensorList Value dtypes)

values

stagePeek' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> Tensor v'1 Int32

index

-> m' (TensorList Value dtypes)

values

stageSize Source #

Arguments

:: MonadBuild m' 
=> [DataType]

dtypes

-> m' (Tensor Value Int32)

size

stageSize' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [DataType]

dtypes

-> m' (Tensor Value Int32)

size

statelessMultinomial Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tseed, OneOf '[Int32, Int64] output_dtype) 
=> Tensor v'1 t

logits

-> Tensor v'2 Int32

num_samples

-> Tensor v'3 tseed

seed

-> Tensor Build output_dtype

output

statelessMultinomial' Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tseed, OneOf '[Int32, Int64] output_dtype) 
=> OpParams 
-> Tensor v'1 t

logits

-> Tensor v'2 Int32

num_samples

-> Tensor v'3 tseed

seed

-> Tensor Build output_dtype

output

statelessRandomNormal Source #

Arguments

:: (OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t, OneOf '[Int32, Int64] tseed) 
=> Tensor v'1 t

shape

-> Tensor v'2 tseed

seed

-> Tensor Build dtype

output

statelessRandomNormal' Source #

Arguments

:: (OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t, OneOf '[Int32, Int64] tseed) 
=> OpParams 
-> Tensor v'1 t

shape

-> Tensor v'2 tseed

seed

-> Tensor Build dtype

output

statelessRandomUniform Source #

Arguments

:: (OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t, OneOf '[Int32, Int64] tseed) 
=> Tensor v'1 t

shape

-> Tensor v'2 tseed

seed

-> Tensor Build dtype

output

statelessRandomUniform' Source #

Arguments

:: (OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t, OneOf '[Int32, Int64] tseed) 
=> OpParams 
-> Tensor v'1 t

shape

-> Tensor v'2 tseed

seed

-> Tensor Build dtype

output

statelessTruncatedNormal Source #

Arguments

:: (OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t, OneOf '[Int32, Int64] tseed) 
=> Tensor v'1 t

shape

-> Tensor v'2 tseed

seed

-> Tensor Build dtype

output

statelessTruncatedNormal' Source #

Arguments

:: (OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t, OneOf '[Int32, Int64] tseed) 
=> OpParams 
-> Tensor v'1 t

shape

-> Tensor v'2 tseed

seed

-> Tensor Build dtype

output

stopGradient Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor Build t

output

stopGradient' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor Build t

output

stridedSlice Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] index) 
=> Tensor v'1 t

input

-> Tensor v'2 index

begin

-> Tensor v'3 index

end

-> Tensor v'4 index

strides

-> Tensor Build t

output

stridedSlice' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] index) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 index

begin

-> Tensor v'3 index

end

-> Tensor v'4 index

strides

-> Tensor Build t

output

stridedSliceAssign Source #

Arguments

:: (MonadBuild m', TensorType t, OneOf '[Int32, Int64] index) 
=> Tensor Ref t

ref

-> Tensor v'2 index

begin

-> Tensor v'3 index

end

-> Tensor v'4 index

strides

-> Tensor v'5 t

value

-> m' (Tensor Ref t)

output_ref

stridedSliceAssign' Source #

Arguments

:: (MonadBuild m', TensorType t, OneOf '[Int32, Int64] index) 
=> OpParams 
-> Tensor Ref t

ref

-> Tensor v'2 index

begin

-> Tensor v'3 index

end

-> Tensor v'4 index

strides

-> Tensor v'5 t

value

-> m' (Tensor Ref t)

output_ref

stridedSliceGrad Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] index) 
=> Tensor v'1 index

shape

-> Tensor v'2 index

begin

-> Tensor v'3 index

end

-> Tensor v'4 index

strides

-> Tensor v'5 t

dy

-> Tensor Build t

output

stridedSliceGrad' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] index) 
=> OpParams 
-> Tensor v'1 index

shape

-> Tensor v'2 index

begin

-> Tensor v'3 index

end

-> Tensor v'4 index

strides

-> Tensor v'5 t

dy

-> Tensor Build t

output

stringJoin Source #

Arguments

:: [Tensor v'1 ByteString]

inputs

-> Tensor Build ByteString

output

stringJoin' Source #

Arguments

:: OpParams 
-> [Tensor v'1 ByteString]

inputs

-> Tensor Build ByteString

output

stringSplit Source #

Arguments

:: Tensor v'1 ByteString

input

-> Tensor v'2 ByteString

delimiter

-> (Tensor Build Int64, Tensor Build ByteString, Tensor Build Int64)

(indices, values, shape)

  • indices
  • values
  • shape

stringSplit' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

input

-> Tensor v'2 ByteString

delimiter

-> (Tensor Build Int64, Tensor Build ByteString, Tensor Build Int64)

(indices, values, shape)

  • indices
  • values
  • shape

stringToHashBucket Source #

Arguments

:: Int64

num_buckets

-> Tensor v'1 ByteString

string_tensor

-> Tensor Build Int64

output

stringToHashBucket' Source #

Arguments

:: OpParams 
-> Int64

num_buckets

-> Tensor v'1 ByteString

string_tensor

-> Tensor Build Int64

output

stringToHashBucketFast Source #

Arguments

:: Int64

num_buckets

-> Tensor v'1 ByteString

input

-> Tensor Build Int64

output

stringToHashBucketFast' Source #

Arguments

:: OpParams 
-> Int64

num_buckets

-> Tensor v'1 ByteString

input

-> Tensor Build Int64

output

stringToHashBucketStrong Source #

Arguments

:: Int64

num_buckets

-> Tensor v'1 ByteString

input

-> Tensor Build Int64

output

stringToHashBucketStrong' Source #

Arguments

:: OpParams 
-> Int64

num_buckets

-> Tensor v'1 ByteString

input

-> Tensor Build Int64

output

stringToNumber Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] out_type 
=> Tensor v'1 ByteString

string_tensor

-> Tensor Build out_type

output

stringToNumber' Source #

Arguments

:: OneOf '[Int32, Int64, Double, Float] out_type 
=> OpParams 
-> Tensor v'1 ByteString

string_tensor

-> Tensor Build out_type

output

substr Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> Tensor v'1 ByteString

input

-> Tensor v'2 t

pos

-> Tensor v'3 t

len

-> Tensor Build ByteString

output

substr' Source #

Arguments

:: OneOf '[Int32, Int64] t 
=> OpParams 
-> Tensor v'1 ByteString

input

-> Tensor v'2 t

pos

-> Tensor v'3 t

len

-> Tensor Build ByteString

output

sum Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> Tensor v'1 t

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build t

output

sum' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tidx) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tidx

reduction_indices

-> Tensor Build t

output

svd Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t, Tensor Build t)

(s, u, v)

  • s
  • u
  • v

svd' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build t, Tensor Build t)

(s, u, v)

  • s
  • u
  • v

switch Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

data

-> Tensor v'2 Bool

pred

-> (Tensor Build t, Tensor Build t)

(output_false, output_true)

  • output_false
  • output_true

switch' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 Bool

pred

-> (Tensor Build t, Tensor Build t)

(output_false, output_true)

  • output_false
  • output_true

tFRecordDataset Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

filenames

-> Tensor v'2 ByteString

compression_type

-> Tensor v'3 Int64

buffer_size

-> m' (Tensor Value Variant)

handle

tFRecordDataset' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

filenames

-> Tensor v'2 ByteString

compression_type

-> Tensor v'3 Int64

buffer_size

-> m' (Tensor Value Variant)

handle

tFRecordReader Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Ref ByteString)

reader_handle

tFRecordReader' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Ref ByteString)

reader_handle

tFRecordReaderV2 Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Value ResourceHandle)

reader_handle

tFRecordReaderV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Value ResourceHandle)

reader_handle

tPUEmbeddingActivations Source #

Arguments

:: Int64

lookup_id: Identifier of the set of embedding indices which produced these activations.

-> Int64

table_id: The id of the table in the embedding layer configuration from which these activations were computed.

-> Tensor v'1 Float

embedding_variable: A trainable variable, enabling optimizers to find this op.

-> Tensor v'2 Float

sliced_activations: The embedding activations Tensor to return.

-> Tensor Build Float

output

An op enabling differentiation of TPU Embeddings.

This op simply returns its first input, which is assumed to have been sliced from the Tensors returned by TPUEmbeddingDequeueActivations. The presence of this op, and its first argument being a trainable Variable, enables automatic differentiation of graphs containing embeddings via the TPU Embedding Python libraries.

tPUEmbeddingActivations' Source #

Arguments

:: OpParams 
-> Int64

lookup_id: Identifier of the set of embedding indices which produced these activations.

-> Int64

table_id: The id of the table in the embedding layer configuration from which these activations were computed.

-> Tensor v'1 Float

embedding_variable: A trainable variable, enabling optimizers to find this op.

-> Tensor v'2 Float

sliced_activations: The embedding activations Tensor to return.

-> Tensor Build Float

output

tPUEmbeddingEnqueueSparseBatch Source #

Arguments

:: MonadBuild m' 
=> [Tensor v'1 Int32]

sample_indices: A list of rank 1 Tensors specifying row indices of the COO sparse matrix representing the embedding lookups for each table.

-> [Tensor v'2 Int32]

embedding_indices: A list of rank 1 Tensors specifying column indices of the COO sparse matrix representing the embedding lookups for each table.

-> [Tensor v'3 Float]

aggregation_weights: A list of rank 1 Tensors specifying the nonzero values of the COO sparse matrix representing the embedding lookups for each table.

-> m' ControlNode 

An op that feeds a batch of embedding indices and weights to the TPU.

Embedding lookups are equivalent to sparse-dense matrix multiplications: the sparse matrix contains nonzeros in column j in order to retrieve row j from the embedding table.

The three Tensor list arguments (sample_indices, embedding_indices, and aggregation_weights) represent these sparse matrices in COO format. The Tensor lists each have one entry for each embedding table specified in the model. For the kth embedding table, the three Tensors at position k in the list specify a COO-format sparse matrix. For the kth table, the row indices, column indices, and nonzero values of the COO sparse matrix are specified by sample_indices[k], embedding_indices[k], and aggregation_weights[k], respectively. Entries must be sorted by row index, then by column index.

There should be at most one TPUEmbeddingEnqueueSparseBatch op in a signle training step per TPU shard.

tPUEmbeddingEnqueueSparseBatch' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [Tensor v'1 Int32]

sample_indices: A list of rank 1 Tensors specifying row indices of the COO sparse matrix representing the embedding lookups for each table.

-> [Tensor v'2 Int32]

embedding_indices: A list of rank 1 Tensors specifying column indices of the COO sparse matrix representing the embedding lookups for each table.

-> [Tensor v'3 Float]

aggregation_weights: A list of rank 1 Tensors specifying the nonzero values of the COO sparse matrix representing the embedding lookups for each table.

-> m' ControlNode 

tPUEmbeddingLoadAdagradParameters Source #

Arguments

:: MonadBuild m' 
=> Int64

host_id: Which CPU host in the distributed training job will execute this op.

-> Int64

num_hosts: The number of CPU hosts in the distributed training job.

-> Int64

table_id: The id of the table specified in the embedding_config.

-> Tensor v'1 Float

parameters: The shard of the embedding table resident on the host executing this op. For single-TPU models, this is the entire embedding table.

-> Tensor v'2 Float

accumulators: Shard of the Adagrad accumulators resident on the host executing this op.

-> m' ControlNode 

Load an embedding table shard into TensorNode memories for use with Adagrad.

TPU embeddings use dedicated per-optimizer Ops for loading and retrieving trainable variables and optimizer state from TPU memory. This op enables functionality equivalent to AdagradOptimizer.

tPUEmbeddingLoadAdagradParameters' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

host_id: Which CPU host in the distributed training job will execute this op.

-> Int64

num_hosts: The number of CPU hosts in the distributed training job.

-> Int64

table_id: The id of the table specified in the embedding_config.

-> Tensor v'1 Float

parameters: The shard of the embedding table resident on the host executing this op. For single-TPU models, this is the entire embedding table.

-> Tensor v'2 Float

accumulators: Shard of the Adagrad accumulators resident on the host executing this op.

-> m' ControlNode 

tPUEmbeddingLoadGradientDescentParameters Source #

Arguments

:: MonadBuild m' 
=> Int64

host_id: Which CPU host in the distributed training job will execute this op.

-> Int64

num_hosts: The number of CPU hosts in the distributed training job.

-> Int64

table_id: The id of the table specified in the tpu_embedding_config.

-> Tensor v'1 Float

parameters: The shard of the embedding table resident on the host executing this op. For single-TPU models, this is the entire embedding table.

-> m' ControlNode 

Load an embedding table shard into TPU memory for use with GradientDescent.

TPU embeddings use dedicated per-optimizer Ops for loading and retrieving trainable variables and optimizer state from TPU memory. This op enables functionality equivalent to GradientDescentOptimizer.

tPUEmbeddingLoadGradientDescentParameters' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

host_id: Which CPU host in the distributed training job will execute this op.

-> Int64

num_hosts: The number of CPU hosts in the distributed training job.

-> Int64

table_id: The id of the table specified in the tpu_embedding_config.

-> Tensor v'1 Float

parameters: The shard of the embedding table resident on the host executing this op. For single-TPU models, this is the entire embedding table.

-> m' ControlNode 

tPUEmbeddingReceiveActivations Source #

Arguments

:: MonadBuild m' 
=> Int64

num_tables: The number of output activation tensors, equal to the number of embedding tables in the model.

-> m' [Tensor Value Float]

outputs: A TensorList of embedding activations containing one Tensor per embedding table in the model.

An op that receives embedding activations on the TPU.

The TPU system performs the embedding lookups and aggregations specified by the arguments to TPUEmbeddingEnqueueSparseBatch. The results of these aggregations are visible to the Tensorflow Graph as the outputs of a TPUEmbeddingDequeueActivations Op. This op returns a list containing one Tensor of activations per table specified in the model. There can be at most one ReceieveActivations op in the TPU graph.

tPUEmbeddingReceiveActivations' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

num_tables: The number of output activation tensors, equal to the number of embedding tables in the model.

-> m' [Tensor Value Float]

outputs: A TensorList of embedding activations containing one Tensor per embedding table in the model.

tPUEmbeddingRetrieveAdagradParameters Source #

Arguments

:: MonadBuild m' 
=> Int64

host_id: Which CPU host in the distributed training job will execute this op.

-> Int64

num_hosts: The number of CPU hosts in the distributed training job.

-> Int64

table_id: The id of the table specified in the embedding_config_json.

-> m' (Tensor Value Float, Tensor Value Float)

(parameters, accumulators)

  • parameters
  • accumulators

Retrieve an embedding table shard from TPU memory.

TPU embeddings use dedicated per-optimizer Ops for loading and retrieving trainable variables and optimizer state from TPU memory. This op enables functionality equivalent to AdagradOptimizer.

tPUEmbeddingRetrieveAdagradParameters' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

host_id: Which CPU host in the distributed training job will execute this op.

-> Int64

num_hosts: The number of CPU hosts in the distributed training job.

-> Int64

table_id: The id of the table specified in the embedding_config_json.

-> m' (Tensor Value Float, Tensor Value Float)

(parameters, accumulators)

  • parameters
  • accumulators

tPUEmbeddingRetrieveGradientDescentParameters Source #

Arguments

:: MonadBuild m' 
=> Int64

host_id: Which CPU host in the distributed training job will execute this op.

-> Int64

num_hosts: The number of CPU hosts in the distributed training job.

-> Int64

table_id: The id of the table specified in tpu_embedding_config.

-> m' (Tensor Value Float)

parameters

Retrieve an embedding table shard from TPU memory.

TPU embeddings use dedicated per-optimizer Ops for loading and retrieving trainable variables and optimizer state from TPU memory. This op enables functionality equivalent to GradientDescentOptimizer.

tPUEmbeddingRetrieveGradientDescentParameters' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

host_id: Which CPU host in the distributed training job will execute this op.

-> Int64

num_hosts: The number of CPU hosts in the distributed training job.

-> Int64

table_id: The id of the table specified in tpu_embedding_config.

-> m' (Tensor Value Float)

parameters

tPUEmbeddingSendGradients Source #

Arguments

:: MonadBuild m' 
=> [Tensor v'1 Float]

gradients: A TensorList of gradients with which to update embedding tables.

-> m' ControlNode 

An op that performs gradient updates of embedding tables.

The TensorList argument has the same length and shapes as the return value of TPUEmbeddingReceiveActivations, but contains gradients of the model's loss with respect to the embedding activations. The embedding tables are updated from these gradients via the optimizer specified in the configuration given to tpu.initialize_system.

tPUEmbeddingSendGradients' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [Tensor v'1 Float]

gradients: A TensorList of gradients with which to update embedding tables.

-> m' ControlNode 

tPUReplicateMetadata Source #

Arguments

:: MonadBuild m' 
=> Int64

num_replicas

-> m' ControlNode 

tPUReplicateMetadata' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

num_replicas

-> m' ControlNode 

tPUReplicatedInput Source #

Arguments

:: TensorType t 
=> [Tensor v'1 t]

inputs

-> Tensor Build t

output

Operator that connects N unreplicated inputs to an N-way replicated TPU computation.

tPUReplicatedInput' Source #

Arguments

:: TensorType t 
=> OpParams 
-> [Tensor v'1 t]

inputs

-> Tensor Build t

output

tPUReplicatedOutput Source #

Arguments

:: TensorType t 
=> Int64

num_replicas

-> Tensor v'1 t

input

-> [Tensor Build t]

outputs

Operator that connects the output of an N-way replicated TPU computation to N separate outputs.

tPUReplicatedOutput' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Int64

num_replicas

-> Tensor v'1 t

input

-> [Tensor Build t]

outputs

takeDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

count

-> Tensor Build Variant

handle

takeDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor v'2 Int64

count

-> Tensor Build Variant

handle

takeManySparseFromTensorsMap Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 Int64

sparse_handles

-> m' (Tensor Value Int64, Tensor Value dtype, Tensor Value Int64)

(sparse_indices, sparse_values, sparse_shape)

  • sparse_indices
  • sparse_values
  • sparse_shape

takeManySparseFromTensorsMap' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 Int64

sparse_handles

-> m' (Tensor Value Int64, Tensor Value dtype, Tensor Value Int64)

(sparse_indices, sparse_values, sparse_shape)

  • sparse_indices
  • sparse_values
  • sparse_shape

tanhGrad Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Word16, Double, Float] t 
=> Tensor v'1 t

y

-> Tensor v'2 t

dy

-> Tensor Build t

z

tanhGrad' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

y

-> Tensor v'2 t

dy

-> Tensor Build t

z

temporaryVariable Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Shape

shape

-> m' (Tensor Ref dtype)

ref

temporaryVariable' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Shape

shape

-> m' (Tensor Ref dtype)

ref

tensorArray Source #

Arguments

:: MonadBuild m' 
=> DataType

dtype

-> Tensor v'1 Int32

size

-> m' (Tensor Ref ByteString)

handle

tensorArray' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

dtype

-> Tensor v'1 Int32

size

-> m' (Tensor Ref ByteString)

handle

tensorArrayConcat Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value dtype, Tensor Value Int64)

(value, lengths)

  • value
  • lengths

tensorArrayConcat' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value dtype, Tensor Value Int64)

(value, lengths)

  • value
  • lengths

tensorArrayConcatV2 Source #

Arguments

:: TensorType dtype 
=> Tensor v'1 ByteString

handle

-> Tensor v'2 Float

flow_in

-> (Tensor Build dtype, Tensor Build Int64)

(value, lengths)

  • value
  • lengths

tensorArrayConcatV2' Source #

Arguments

:: TensorType dtype 
=> OpParams 
-> Tensor v'1 ByteString

handle

-> Tensor v'2 Float

flow_in

-> (Tensor Build dtype, Tensor Build Int64)

(value, lengths)

  • value
  • lengths

tensorArrayConcatV3 Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value dtype, Tensor Value Int64)

(value, lengths)

  • value
  • lengths

tensorArrayConcatV3' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value dtype, Tensor Value Int64)

(value, lengths)

  • value
  • lengths

tensorArrayGather Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 Float

flow_in

-> m' (Tensor Value dtype)

value

tensorArrayGather' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 Float

flow_in

-> m' (Tensor Value dtype)

value

tensorArrayGatherV2 Source #

Arguments

:: TensorType dtype 
=> Tensor v'1 ByteString

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 Float

flow_in

-> Tensor Build dtype

value

tensorArrayGatherV2' Source #

Arguments

:: TensorType dtype 
=> OpParams 
-> Tensor v'1 ByteString

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 Float

flow_in

-> Tensor Build dtype

value

tensorArrayGatherV3 Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 Float

flow_in

-> m' (Tensor Value dtype)

value

tensorArrayGatherV3' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 Float

flow_in

-> m' (Tensor Value dtype)

value

tensorArrayGrad Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Ref ByteString)

grad_handle

tensorArrayGrad' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Ref ByteString)

grad_handle

tensorArrayGradV2 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value ByteString)

grad_handle

tensorArrayGradV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value ByteString)

grad_handle

tensorArrayGradV3 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value ResourceHandle, Tensor Value Float)

(grad_handle, flow_out)

  • grad_handle
  • flow_out

tensorArrayGradV3' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value ResourceHandle, Tensor Value Float)

(grad_handle, flow_out)

  • grad_handle
  • flow_out

tensorArrayPack Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value dtype)

value

tensorArrayPack' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value dtype)

value

tensorArrayRead Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 Float

flow_in

-> m' (Tensor Value dtype)

value

tensorArrayRead' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 Float

flow_in

-> m' (Tensor Value dtype)

value

tensorArrayReadV2 Source #

Arguments

:: TensorType dtype 
=> Tensor v'1 ByteString

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 Float

flow_in

-> Tensor Build dtype

value

tensorArrayReadV2' Source #

Arguments

:: TensorType dtype 
=> OpParams 
-> Tensor v'1 ByteString

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 Float

flow_in

-> Tensor Build dtype

value

tensorArrayReadV3 Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 Float

flow_in

-> m' (Tensor Value dtype)

value

tensorArrayReadV3' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 Float

flow_in

-> m' (Tensor Value dtype)

value

tensorArrayScatter Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArrayScatter' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArrayScatterV2 Source #

Arguments

:: TensorType t 
=> Tensor v'1 ByteString

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> Tensor Build Float

flow_out

tensorArrayScatterV2' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 ByteString

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> Tensor Build Float

flow_out

tensorArrayScatterV3 Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArrayScatterV3' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

indices

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArraySize Source #

Arguments

:: MonadBuild m' 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value Int32)

size

tensorArraySize' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value Int32)

size

tensorArraySizeV2 Source #

Arguments

:: Tensor v'1 ByteString

handle

-> Tensor v'2 Float

flow_in

-> Tensor Build Int32

size

tensorArraySizeV2' Source #

Arguments

:: OpParams 
-> Tensor v'1 ByteString

handle

-> Tensor v'2 Float

flow_in

-> Tensor Build Int32

size

tensorArraySizeV3 Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value Int32)

size

tensorArraySizeV3' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Float

flow_in

-> m' (Tensor Value Int32)

size

tensorArraySplit Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 t

value

-> Tensor v'3 Int64

lengths

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArraySplit' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 t

value

-> Tensor v'3 Int64

lengths

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArraySplitV2 Source #

Arguments

:: TensorType t 
=> Tensor v'1 ByteString

handle

-> Tensor v'2 t

value

-> Tensor v'3 Int64

lengths

-> Tensor v'4 Float

flow_in

-> Tensor Build Float

flow_out

tensorArraySplitV2' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 ByteString

handle

-> Tensor v'2 t

value

-> Tensor v'3 Int64

lengths

-> Tensor v'4 Float

flow_in

-> Tensor Build Float

flow_out

tensorArraySplitV3 Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 t

value

-> Tensor v'3 Int64

lengths

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArraySplitV3' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 t

value

-> Tensor v'3 Int64

lengths

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArrayUnpack Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 t

value

-> Tensor v'3 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArrayUnpack' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 t

value

-> Tensor v'3 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArrayV2 Source #

Arguments

:: MonadBuild m' 
=> DataType

dtype

-> Tensor v'1 Int32

size

-> m' (Tensor Value ByteString)

handle

tensorArrayV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

dtype

-> Tensor v'1 Int32

size

-> m' (Tensor Value ByteString)

handle

tensorArrayV3 Source #

Arguments

:: MonadBuild m' 
=> DataType

dtype

-> Tensor v'1 Int32

size

-> m' (Tensor Value ResourceHandle, Tensor Value Float)

(handle, flow)

  • handle
  • flow

tensorArrayV3' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

dtype

-> Tensor v'1 Int32

size

-> m' (Tensor Value ResourceHandle, Tensor Value Float)

(handle, flow)

  • handle
  • flow

tensorArrayWrite Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArrayWrite' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor Ref ByteString

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArrayWriteV2 Source #

Arguments

:: TensorType t 
=> Tensor v'1 ByteString

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> Tensor Build Float

flow_out

tensorArrayWriteV2' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 ByteString

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> Tensor Build Float

flow_out

tensorArrayWriteV3 Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorArrayWriteV3' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

handle

-> Tensor v'2 Int32

index

-> Tensor v'3 t

value

-> Tensor v'4 Float

flow_in

-> m' (Tensor Value Float)

flow_out

tensorDataset Source #

Arguments

:: (MonadBuild m', TensorTypes toutput_types) 
=> TensorList v'1 toutput_types

components

-> m' (Tensor Value Variant)

handle

tensorDataset' Source #

Arguments

:: (MonadBuild m', TensorTypes toutput_types) 
=> OpParams 
-> TensorList v'1 toutput_types

components

-> m' (Tensor Value Variant)

handle

tensorListConcatLists Source #

Arguments

:: DataType

element_dtype

-> Tensor v'1 Variant

input_a

-> Tensor v'2 Variant

input_b

-> Tensor Build Variant

output

tensorListConcatLists' Source #

Arguments

:: OpParams 
-> DataType

element_dtype

-> Tensor v'1 Variant

input_a

-> Tensor v'2 Variant

input_b

-> Tensor Build Variant

output

tensorListElementShape Source #

Arguments

:: OneOf '[Int32, Int64] shape_type 
=> Tensor v'1 Variant

input_handle

-> Tensor Build shape_type

element_shape

tensorListElementShape' Source #

Arguments

:: OneOf '[Int32, Int64] shape_type 
=> OpParams 
-> Tensor v'1 Variant

input_handle

-> Tensor Build shape_type

element_shape

tensorListFromTensor Source #

Arguments

:: (TensorType element_dtype, OneOf '[Int32, Int64] shape_type) 
=> Tensor v'1 element_dtype

tensor

-> Tensor v'2 shape_type

element_shape

-> Tensor Build Variant

output_handle

tensorListFromTensor' Source #

Arguments

:: (TensorType element_dtype, OneOf '[Int32, Int64] shape_type) 
=> OpParams 
-> Tensor v'1 element_dtype

tensor

-> Tensor v'2 shape_type

element_shape

-> Tensor Build Variant

output_handle

tensorListGetItem Source #

Arguments

:: TensorType element_dtype 
=> Tensor v'1 Variant

input_handle

-> Tensor v'2 Int32

index

-> Tensor Build element_dtype

item

tensorListGetItem' Source #

Arguments

:: TensorType element_dtype 
=> OpParams 
-> Tensor v'1 Variant

input_handle

-> Tensor v'2 Int32

index

-> Tensor Build element_dtype

item

tensorListLength Source #

Arguments

:: Tensor v'1 Variant

input_handle

-> Tensor Build Int32

length

tensorListLength' Source #

Arguments

:: OpParams 
-> Tensor v'1 Variant

input_handle

-> Tensor Build Int32

length

tensorListPopBack Source #

Arguments

:: TensorType element_dtype 
=> Tensor v'1 Variant

input_handle

-> (Tensor Build Variant, Tensor Build element_dtype)

(output_handle, tensor)

  • output_handle
  • tensor

tensorListPopBack' Source #

Arguments

:: TensorType element_dtype 
=> OpParams 
-> Tensor v'1 Variant

input_handle

-> (Tensor Build Variant, Tensor Build element_dtype)

(output_handle, tensor)

  • output_handle
  • tensor

tensorListPushBack Source #

Arguments

:: TensorType element_dtype 
=> Tensor v'1 Variant

input_handle

-> Tensor v'2 element_dtype

tensor

-> Tensor Build Variant

output_handle

tensorListPushBack' Source #

Arguments

:: TensorType element_dtype 
=> OpParams 
-> Tensor v'1 Variant

input_handle

-> Tensor v'2 element_dtype

tensor

-> Tensor Build Variant

output_handle

tensorListPushBackBatch Source #

Arguments

:: TensorType element_dtype 
=> Tensor v'1 Variant

input_handles

-> Tensor v'2 element_dtype

tensor

-> Tensor Build Variant

output_handles

tensorListPushBackBatch' Source #

Arguments

:: TensorType element_dtype 
=> OpParams 
-> Tensor v'1 Variant

input_handles

-> Tensor v'2 element_dtype

tensor

-> Tensor Build Variant

output_handles

tensorListReserve Source #

Arguments

:: OneOf '[Int32, Int64] shape_type 
=> DataType

element_dtype

-> Tensor v'1 shape_type

element_shape

-> Tensor v'2 Int32

num_elements

-> Tensor Build Variant

handle

tensorListReserve' Source #

Arguments

:: OneOf '[Int32, Int64] shape_type 
=> OpParams 
-> DataType

element_dtype

-> Tensor v'1 shape_type

element_shape

-> Tensor v'2 Int32

num_elements

-> Tensor Build Variant

handle

tensorListSetItem Source #

Arguments

:: TensorType element_dtype 
=> Tensor v'1 Variant

input_handle

-> Tensor v'2 Int32

index

-> Tensor v'3 element_dtype

item

-> Tensor Build Variant

output_handle

tensorListSetItem' Source #

Arguments

:: TensorType element_dtype 
=> OpParams 
-> Tensor v'1 Variant

input_handle

-> Tensor v'2 Int32

index

-> Tensor v'3 element_dtype

item

-> Tensor Build Variant

output_handle

tensorListStack Source #

Arguments

:: TensorType element_dtype 
=> Tensor v'1 Variant

input_handle

-> Tensor Build element_dtype

tensor

tensorListStack' Source #

Arguments

:: TensorType element_dtype 
=> OpParams 
-> Tensor v'1 Variant

input_handle

-> Tensor Build element_dtype

tensor

tensorSliceDataset Source #

Arguments

:: (MonadBuild m', TensorTypes toutput_types) 
=> TensorList v'1 toutput_types

components

-> m' (Tensor Value Variant)

handle

tensorSliceDataset' Source #

Arguments

:: (MonadBuild m', TensorTypes toutput_types) 
=> OpParams 
-> TensorList v'1 toutput_types

components

-> m' (Tensor Value Variant)

handle

tensorSummary Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

tensor

-> Tensor Build ByteString

summary

tensorSummary' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

tensor

-> Tensor Build ByteString

summary

tensorSummaryV2 Source #

Arguments

:: TensorType t 
=> Tensor v'1 ByteString

tag

-> Tensor v'2 t

tensor

-> Tensor v'3 ByteString

serialized_summary_metadata

-> Tensor Build ByteString

summary

tensorSummaryV2' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 ByteString

tag

-> Tensor v'2 t

tensor

-> Tensor v'3 ByteString

serialized_summary_metadata

-> Tensor Build ByteString

summary

textLineDataset Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

filenames

-> Tensor v'2 ByteString

compression_type

-> Tensor v'3 Int64

buffer_size

-> m' (Tensor Value Variant)

handle

textLineDataset' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

filenames

-> Tensor v'2 ByteString

compression_type

-> Tensor v'3 Int64

buffer_size

-> m' (Tensor Value Variant)

handle

textLineReader Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Ref ByteString)

reader_handle

textLineReader' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Ref ByteString)

reader_handle

textLineReaderV2 Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Value ResourceHandle)

reader_handle

textLineReaderV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Value ResourceHandle)

reader_handle

threadUnsafeUnigramCandidateSampler Source #

Arguments

:: MonadBuild m' 
=> Int64

num_sampled

-> Int64

num_true

-> Int64

range_max

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

threadUnsafeUnigramCandidateSampler' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

num_sampled

-> Int64

num_true

-> Int64

range_max

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

tile Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tmultiples) 
=> Tensor v'1 t

input

-> Tensor v'2 tmultiples

multiples

-> Tensor Build t

output

tile' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tmultiples) 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 tmultiples

multiples

-> Tensor Build t

output

tileGrad Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

input

-> Tensor v'2 Int32

multiples

-> Tensor Build t

output

tileGrad' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Int32

multiples

-> Tensor Build t

output

timestamp Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Value Double)

ts

timestamp' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Value Double)

ts

topK Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Int64

k

-> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build Int32)

(values, indices)

  • values
  • indices

topK' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Int64

k

-> Tensor v'1 t

input

-> (Tensor Build t, Tensor Build Int32)

(values, indices)

  • values
  • indices

topKV2 Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> Tensor v'1 t

input

-> Tensor v'2 Int32

k

-> (Tensor Build t, Tensor Build Int32)

(values, indices)

  • values
  • indices

topKV2' Source #

Arguments

:: OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

input

-> Tensor v'2 Int32

k

-> (Tensor Build t, Tensor Build Int32)

(values, indices)

  • values
  • indices

transpose Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tperm) 
=> Tensor v'1 t

x

-> Tensor v'2 tperm

perm

-> Tensor Build t

y

transpose' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] tperm) 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 tperm

perm

-> Tensor Build t

y

truncateMod Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

truncateMod' Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor Build t

z

truncatedNormal Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t) 
=> Tensor v'1 t

shape

-> m' (Tensor Value dtype)

output

truncatedNormal' Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Double, Float] dtype, OneOf '[Int32, Int64] t) 
=> OpParams 
-> Tensor v'1 t

shape

-> m' (Tensor Value dtype)

output

tryRpc Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

address

-> Tensor v'2 ByteString

method

-> Tensor v'3 ByteString

request

-> m' (Tensor Value ByteString, Tensor Value Int32, Tensor Value ByteString)

(response, status_code, status_message)

  • response
  • status_code
  • status_message

tryRpc' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

address

-> Tensor v'2 ByteString

method

-> Tensor v'3 ByteString

request

-> m' (Tensor Value ByteString, Tensor Value Int32, Tensor Value ByteString)

(response, status_code, status_message)

  • response
  • status_code
  • status_message

unbatch Source #

Arguments

:: TensorType t 
=> Int64

timeout_micros

-> Tensor v'1 t

batched_tensor

-> Tensor v'2 Int64

batch_index

-> Tensor v'3 Int64

id

-> Tensor Build t

unbatched_tensor

unbatch' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Int64

timeout_micros

-> Tensor v'1 t

batched_tensor

-> Tensor v'2 Int64

batch_index

-> Tensor v'3 Int64

id

-> Tensor Build t

unbatched_tensor

unbatchDataset Source #

Arguments

:: [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor Build Variant

handle

unbatchDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> Tensor v'1 Variant

input_dataset

-> Tensor Build Variant

handle

unbatchGrad Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

original_input

-> Tensor v'2 Int64

batch_index

-> Tensor v'3 t

grad

-> Tensor v'4 Int64

id

-> Tensor Build t

batched_grad

unbatchGrad' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

original_input

-> Tensor v'2 Int64

batch_index

-> Tensor v'3 t

grad

-> Tensor v'4 Int64

id

-> Tensor Build t

batched_grad

uniformCandidateSampler Source #

Arguments

:: MonadBuild m' 
=> Int64

num_sampled

-> Int64

num_true

-> Int64

range_max

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

uniformCandidateSampler' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Int64

num_sampled

-> Int64

num_true

-> Int64

range_max

-> Bool

unique

-> Tensor v'1 Int64

true_classes

-> m' (Tensor Value Int64, Tensor Value Float, Tensor Value Float)

(sampled_candidates, true_expected_count, sampled_expected_count)

  • sampled_candidates
  • true_expected_count
  • sampled_expected_count

unique Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_idx) 
=> Tensor v'1 t

x

-> (Tensor Build t, Tensor Build out_idx)

(y, idx)

  • y
  • idx

unique' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_idx) 
=> OpParams 
-> Tensor v'1 t

x

-> (Tensor Build t, Tensor Build out_idx)

(y, idx)

  • y
  • idx

uniqueV2 Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] taxis, OneOf '[Int32, Int64] out_idx) 
=> Tensor v'1 t

x

-> Tensor v'2 taxis

axis

-> (Tensor Build t, Tensor Build out_idx)

(y, idx)

  • y
  • idx

uniqueV2' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] taxis, OneOf '[Int32, Int64] out_idx) 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 taxis

axis

-> (Tensor Build t, Tensor Build out_idx)

(y, idx)

  • y
  • idx

uniqueWithCounts Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_idx) 
=> Tensor v'1 t

x

-> (Tensor Build t, Tensor Build out_idx, Tensor Build out_idx)

(y, idx, count)

  • y
  • idx
  • count

uniqueWithCounts' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] out_idx) 
=> OpParams 
-> Tensor v'1 t

x

-> (Tensor Build t, Tensor Build out_idx, Tensor Build out_idx)

(y, idx, count)

  • y
  • idx
  • count

uniqueWithCountsV2 Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] taxis, OneOf '[Int32, Int64] out_idx) 
=> Tensor v'1 t

x

-> Tensor v'2 taxis

axis

-> (Tensor Build t, Tensor Build out_idx, Tensor Build out_idx)

(y, idx, count)

  • y
  • idx
  • count

uniqueWithCountsV2' Source #

Arguments

:: (TensorType t, OneOf '[Int32, Int64] taxis, OneOf '[Int32, Int64] out_idx) 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 taxis

axis

-> (Tensor Build t, Tensor Build out_idx, Tensor Build out_idx)

(y, idx, count)

  • y
  • idx
  • count

unpack Source #

Arguments

:: TensorType t 
=> Int64

num

-> Tensor v'1 t

value

-> [Tensor Build t]

output

unpack' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Int64

num

-> Tensor v'1 t

value

-> [Tensor Build t]

output

unravelIndex Source #

Arguments

:: OneOf '[Int32, Int64] tidx 
=> Tensor v'1 tidx

indices

-> Tensor v'2 tidx

dims

-> Tensor Build tidx

output

unravelIndex' Source #

Arguments

:: OneOf '[Int32, Int64] tidx 
=> OpParams 
-> Tensor v'1 tidx

indices

-> Tensor v'2 tidx

dims

-> Tensor Build tidx

output

unsortedSegmentMax Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices, OneOf '[Int32, Int64] tnumsegments) 
=> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor v'3 tnumsegments

num_segments

-> Tensor Build t

output

unsortedSegmentMax' Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices, OneOf '[Int32, Int64] tnumsegments) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor v'3 tnumsegments

num_segments

-> Tensor Build t

output

unsortedSegmentMin Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices, OneOf '[Int32, Int64] tnumsegments) 
=> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor v'3 tnumsegments

num_segments

-> Tensor Build t

output

unsortedSegmentMin' Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices, OneOf '[Int32, Int64] tnumsegments) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor v'3 tnumsegments

num_segments

-> Tensor Build t

output

unsortedSegmentProd Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices, OneOf '[Int32, Int64] tnumsegments) 
=> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor v'3 tnumsegments

num_segments

-> Tensor Build t

output

unsortedSegmentProd' Source #

Arguments

:: (OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices, OneOf '[Int32, Int64] tnumsegments) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor v'3 tnumsegments

num_segments

-> Tensor Build t

output

unsortedSegmentSum Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices, OneOf '[Int32, Int64] tnumsegments) 
=> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor v'3 tnumsegments

num_segments

-> Tensor Build t

output

unsortedSegmentSum' Source #

Arguments

:: (OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t, OneOf '[Int32, Int64] tindices, OneOf '[Int32, Int64] tnumsegments) 
=> OpParams 
-> Tensor v'1 t

data

-> Tensor v'2 tindices

segment_ids

-> Tensor v'3 tnumsegments

num_segments

-> Tensor Build t

output

unstage Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> m' (TensorList Value dtypes)

values

unstage' Source #

Arguments

:: (MonadBuild m', TensorTypes dtypes) 
=> OpParams 
-> m' (TensorList Value dtypes)

values

varHandleOp Source #

Arguments

:: MonadBuild m' 
=> DataType

dtype

-> Shape

shape

-> m' (Tensor Value ResourceHandle)

resource

varHandleOp' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> DataType

dtype

-> Shape

shape

-> m' (Tensor Value ResourceHandle)

resource

varIsInitializedOp Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

resource

-> m' (Tensor Value Bool)

is_initialized

varIsInitializedOp' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

resource

-> m' (Tensor Value Bool)

is_initialized

variable Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Shape

shape

-> m' (Tensor Ref dtype)

ref

variable' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Shape

shape

-> m' (Tensor Ref dtype)

ref

variableShape Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] out_type) 
=> Tensor v'1 ResourceHandle

input

-> m' (Tensor Value out_type)

output

variableShape' Source #

Arguments

:: (MonadBuild m', OneOf '[Int32, Int64] out_type) 
=> OpParams 
-> Tensor v'1 ResourceHandle

input

-> m' (Tensor Value out_type)

output

variableV2 Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Shape

shape

-> m' (Tensor Ref dtype)

ref

variableV2' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Shape

shape

-> m' (Tensor Ref dtype)

ref

wholeFileReader Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Ref ByteString)

reader_handle

wholeFileReader' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Ref ByteString)

reader_handle

wholeFileReaderV2 Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Value ResourceHandle)

reader_handle

wholeFileReaderV2' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Value ResourceHandle)

reader_handle

workerHeartbeat Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

request: A string tensor containing a serialized WorkerHeartbeatRequest

-> m' (Tensor Value ByteString)

response: A string tensor containing a serialized WorkerHeartbeatResponse

Worker heartbeat op.

Heartbeats may be sent periodically to indicate the coordinator is still active, to retrieve the current worker status and to expedite shutdown when necessary.

workerHeartbeat' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

request: A string tensor containing a serialized WorkerHeartbeatRequest

-> m' (Tensor Value ByteString)

response: A string tensor containing a serialized WorkerHeartbeatResponse

writeAudioSummary Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 ByteString

tag

-> Tensor v'4 Float

tensor

-> Tensor v'5 Float

sample_rate

-> m' ControlNode 

writeAudioSummary' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 ByteString

tag

-> Tensor v'4 Float

tensor

-> Tensor v'5 Float

sample_rate

-> m' ControlNode 

writeFile Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

filename

-> Tensor v'2 ByteString

contents

-> m' ControlNode 

writeFile' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

filename

-> Tensor v'2 ByteString

contents

-> m' ControlNode 

writeGraphSummary Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 ByteString

tensor

-> m' ControlNode 

writeGraphSummary' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 ByteString

tensor

-> m' ControlNode 

writeHistogramSummary Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 ByteString

tag

-> Tensor v'4 t

values

-> m' ControlNode 

writeImageSummary Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Word8, Float] t) 
=> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 ByteString

tag

-> Tensor v'4 t

tensor

-> Tensor v'5 Word8

bad_color

-> m' ControlNode 

writeImageSummary' Source #

Arguments

:: (MonadBuild m', OneOf '[Word16, Word8, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 ByteString

tag

-> Tensor v'4 t

tensor

-> Tensor v'5 Word8

bad_color

-> m' ControlNode 

writeScalarSummary Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 ByteString

tag

-> Tensor v'4 t

value

-> m' ControlNode 

writeScalarSummary' Source #

Arguments

:: (MonadBuild m', OneOf '[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double, Float] t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 ByteString

tag

-> Tensor v'4 t

value

-> m' ControlNode 

writeSummary Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 t

tensor

-> Tensor v'4 ByteString

tag

-> Tensor v'5 ByteString

summary_metadata

-> m' ControlNode 

writeSummary' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Tensor v'1 ResourceHandle

writer

-> Tensor v'2 Int64

step

-> Tensor v'3 t

tensor

-> Tensor v'4 ByteString

tag

-> Tensor v'5 ByteString

summary_metadata

-> m' ControlNode 

zerosLike Source #

Arguments

:: TensorType t 
=> Tensor v'1 t

x

-> Tensor Build t

y

zerosLike' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor Build t

y

zeta Source #

Arguments

:: OneOf '[Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

q

-> Tensor Build t

z

zeta' Source #

Arguments

:: OneOf '[Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

q

-> Tensor Build t

z

zipDataset Source #

Arguments

:: [DataType]

output_types

-> [Tensor v'1 Variant]

input_datasets

-> Tensor Build Variant

handle

zipDataset' Source #

Arguments

:: OpParams 
-> [DataType]

output_types

-> [Tensor v'1 Variant]

input_datasets

-> Tensor Build Variant

handle

_Arg Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Int64

index: This argument is the index-th argument of the function.

-> m' (Tensor Value t)

output: The argument.

A graph node which represents an argument to a function.

_Arg' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Int64

index: This argument is the index-th argument of the function.

-> m' (Tensor Value t)

output: The argument.

_ArrayToList Source #

Arguments

:: (TensorType t, TensorTypes out_types) 
=> [Tensor v'1 t]

input

-> TensorList Build out_types

output

Converts an array of tensors to a list of tensors.

_ArrayToList' Source #

Arguments

:: (TensorType t, TensorTypes out_types) 
=> OpParams 
-> [Tensor v'1 t]

input

-> TensorList Build out_types

output

_ConfigureDistributedTPU Source #

Arguments

:: MonadBuild m' 
=> [Tensor v'1 Int32]

inputs: A scalar tensor for each host indicating how many TPU chips there are on the host.

-> m' (Tensor Value ByteString)

output: A tensor containing a TPUHostConfiguration proto serialized to a string, containing the information necessary to initialize the chips in a host.

An op that sets up the centralized structures for a distributed TPU

system.

_ConfigureDistributedTPU' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [Tensor v'1 Int32]

inputs: A scalar tensor for each host indicating how many TPU chips there are on the host.

-> m' (Tensor Value ByteString)

output: A tensor containing a TPUHostConfiguration proto serialized to a string, containing the information necessary to initialize the chips in a host.

_DisconnectHostFromDistributedTPUSystem Source #

Arguments

:: MonadBuild m' 
=> m' (Tensor Value Int32)

number_of_tpu_chips: A scalar tensor containing the number of TPU chips on the host.

An op that disconnects the TPUs on a host from a running distributed

TPU system.

_DisconnectHostFromDistributedTPUSystem' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> m' (Tensor Value Int32)

number_of_tpu_chips: A scalar tensor containing the number of TPU chips on the host.

_HostCast Source #

Arguments

:: (TensorType srcT, TensorType dstT) 
=> Tensor v'1 srcT

x

-> Tensor Build dstT

y

Cast x of type SrcT to y of DstT.

_HostCast requires its input and produces its output in host memory.

_HostCast' Source #

Arguments

:: (TensorType srcT, TensorType dstT) 
=> OpParams 
-> Tensor v'1 srcT

x

-> Tensor Build dstT

y

_HostRecv Source #

Arguments

:: (MonadBuild m', TensorType tensor_type) 
=> Int64

send_device_incarnation: The current incarnation of send_device.

-> m' (Tensor Value tensor_type)

tensor: The tensor to receive.

Receives the named tensor from send_device on recv_device.

_HostRecv requires its input on host memory whereas _Recv requires its input on device memory.

_HostRecv' Source #

Arguments

:: (MonadBuild m', TensorType tensor_type) 
=> OpParams 
-> Int64

send_device_incarnation: The current incarnation of send_device.

-> m' (Tensor Value tensor_type)

tensor: The tensor to receive.

_HostSend Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Int64

send_device_incarnation: The current incarnation of send_device.

-> Tensor v'1 t

tensor: The tensor to send.

-> m' ControlNode 

Sends the named tensor from send_device to recv_device.

_HostSend requires its input on host memory whereas _Send requires its input on device memory.

_HostSend' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Int64

send_device_incarnation: The current incarnation of send_device.

-> Tensor v'1 t

tensor: The tensor to send.

-> m' ControlNode 

_InitializeHostForDistributedTPU Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

input: A string containing the address of the UberDriver to connect to.

-> m' (Tensor Value Int32)

tpu_ids: A vector containing the global TPU id of each TPU on the host.

An op that connects each chip on the host to a centralized UberDriver to allow

them to operate as a distributed system with chips in other hosts.

_InitializeHostForDistributedTPU' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

input: A string containing the address of the UberDriver to connect to.

-> m' (Tensor Value Int32)

tpu_ids: A vector containing the global TPU id of each TPU on the host.

_ListToArray Source #

Arguments

:: (TensorTypes tin, TensorType t) 
=> Int64

N

-> TensorList v'1 tin

input

-> [Tensor Build t]

output

Converts a list of tensors to an array of tensors.

_ListToArray' Source #

Arguments

:: (TensorTypes tin, TensorType t) 
=> OpParams 
-> Int64

N

-> TensorList v'1 tin

input

-> [Tensor Build t]

output

_MklAdd Source #

Arguments

:: OneOf '[Complex Double, Complex Float, ByteString, Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor v'3 Word8

mkl_x

-> Tensor v'4 Word8

mkl_y

-> (Tensor Build t, Tensor Build Word8)

(z, mkl_z)

  • z
  • mkl_z

Returns x + y element-wise.

  • NOTE*: Add supports broadcasting. AddN does not. More about broadcasting here

_MklAdd' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, ByteString, Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor v'3 Word8

mkl_x

-> Tensor v'4 Word8

mkl_y

-> (Tensor Build t, Tensor Build Word8)

(z, mkl_z)

  • z
  • mkl_z

_MklMaximum Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor v'3 Word8

mkl_x

-> Tensor v'4 Word8

mkl_y

-> (Tensor Build t, Tensor Build Word8)

(z, mkl_z)

  • z
  • mkl_z

Returns the max of x and y (i.e. x > y ? x : y) element-wise.

  • NOTE*: Maximum supports broadcasting. More about broadcasting here

_MklMaximum' Source #

Arguments

:: OneOf '[Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor v'3 Word8

mkl_x

-> Tensor v'4 Word8

mkl_y

-> (Tensor Build t, Tensor Build Word8)

(z, mkl_z)

  • z
  • mkl_z

_MklMul Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor v'3 Word8

mkl_x

-> Tensor v'4 Word8

mkl_y

-> (Tensor Build t, Tensor Build Word8)

(z, mkl_z)

  • z
  • mkl_z

Returns x * y element-wise.

  • NOTE*: Mul supports broadcasting. More about broadcasting here

_MklMul' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16, Word8, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor v'3 Word8

mkl_x

-> Tensor v'4 Word8

mkl_y

-> (Tensor Build t, Tensor Build Word8)

(z, mkl_z)

  • z
  • mkl_z

_MklSquaredDifference Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor v'3 Word8

mkl_x

-> Tensor v'4 Word8

mkl_y

-> (Tensor Build t, Tensor Build Word8)

(z, mkl_z)

  • z
  • mkl_z

Returns (x - y)(x - y) element-wise.

  • NOTE*: SquaredDifference supports broadcasting. More about broadcasting here

_MklSquaredDifference' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor v'3 Word8

mkl_x

-> Tensor v'4 Word8

mkl_y

-> (Tensor Build t, Tensor Build Word8)

(z, mkl_z)

  • z
  • mkl_z

_MklSub Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Int64, Word16, Double, Float] t 
=> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor v'3 Word8

mkl_x

-> Tensor v'4 Word8

mkl_y

-> (Tensor Build t, Tensor Build Word8)

(z, mkl_z)

  • z
  • mkl_z

Returns x - y element-wise.

  • NOTE*: Sub supports broadcasting. More about broadcasting here

_MklSub' Source #

Arguments

:: OneOf '[Complex Double, Complex Float, Int32, Int64, Word16, Double, Float] t 
=> OpParams 
-> Tensor v'1 t

x

-> Tensor v'2 t

y

-> Tensor v'3 Word8

mkl_x

-> Tensor v'4 Word8

mkl_y

-> (Tensor Build t, Tensor Build Word8)

(z, mkl_z)

  • z
  • mkl_z

_ParallelConcatStart Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> Shape

shape: 1-D Tensor indicating the shape of the output.

-> m' (Tensor Value dtype)

output: An empty Tensor of the specified type.

Creates an empty Tensor with shape shape and type dtype.

The memory can optionally be initialized. This is usually useful in conjunction with inplace operations.

_ParallelConcatStart' Source #

Arguments

:: (MonadBuild m', TensorType dtype) 
=> OpParams 
-> Shape

shape: 1-D Tensor indicating the shape of the output.

-> m' (Tensor Value dtype)

output: An empty Tensor of the specified type.

_ParallelConcatUpdate Source #

Arguments

:: TensorType t 
=> Int64

loc: A scalar indicating the index of the first dimension such that value[loc, :] is updated.

-> Tensor v'1 t

value: A Tensor object that will be updated in-place.

-> Tensor v'2 t

update: A Tensor of rank one less than value if loc is a scalar, otherwise of rank equal to value that contains the new values for value.

-> Tensor Build t

output: value that has been updated accordingly.

Updates input value at loc with update.

If you use this function you will almost certainly want to add a control dependency as done in the implementation of parallel_stack to avoid race conditions.

_ParallelConcatUpdate' Source #

Arguments

:: TensorType t 
=> OpParams 
-> Int64

loc: A scalar indicating the index of the first dimension such that value[loc, :] is updated.

-> Tensor v'1 t

value: A Tensor object that will be updated in-place.

-> Tensor v'2 t

update: A Tensor of rank one less than value if loc is a scalar, otherwise of rank equal to value that contains the new values for value.

-> Tensor Build t

output: value that has been updated accordingly.

_Recv Source #

Arguments

:: (MonadBuild m', TensorType tensor_type) 
=> Int64

send_device_incarnation: The current incarnation of send_device.

-> m' (Tensor Value tensor_type)

tensor: The tensor to receive.

Receives the named tensor from send_device on recv_device.

_Recv' Source #

Arguments

:: (MonadBuild m', TensorType tensor_type) 
=> OpParams 
-> Int64

send_device_incarnation: The current incarnation of send_device.

-> m' (Tensor Value tensor_type)

tensor: The tensor to receive.

_Retval Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Int64

index: This return value is the index-th return value of the function.

-> Tensor v'1 t

input: The return value.

-> m' ControlNode 

A graph node which represents a return value of a function.

_Retval' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Int64

index: This return value is the index-th return value of the function.

-> Tensor v'1 t

input: The return value.

-> m' ControlNode 

_ScopedAllocator Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Int64

expected_call_count

-> Int64

id

-> Shape

shape

-> m' (Tensor Value t)

output

Allocates a mutable tensor that becomes available to appropriately annotated

downstream Ops as backing store for their output tensor allocations via the ScopedAllocatorMgr. Returns a reference to this value.

This is an experimental op for internal use only. It is possible to use this op in unsafe ways.

shapes is a list of the shapes of the tensors that are to be allocated by this ScopedAllocator. shape is the shape of the output of this Op, i.e. the 1D backing tensor from which the individual allocated tensors are aliased. sa_name is the name assigned to the Node, for connectivity specification and debugging. id is a non-negative integer scope_id handled by the ScopedAllocatorMgr. expected_call_count is the number of individual tensors expected to be allocated from the backing tensor.

_ScopedAllocator' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Int64

expected_call_count

-> Int64

id

-> Shape

shape

-> m' (Tensor Value t)

output

_ScopedAllocatorConcat Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Int64

id

-> Shape

shape

-> Tensor v'1 t

backing

-> [Tensor v'2 t]

inputs

-> m' (Tensor Value t)

output

Acts like a Concat Op that merges multple tensors into one, however it must

only be used in conjunction with a ScopedAllocator which is backing the memory of all of its input tensors so that actually it just outputs a read-only reference to that ScopedAllocator's backing tensor.

This is an experimental op for internal use only. It is possible to use this op in unsafe ways.

backing is the backing tensor, i.e. the output of an upstream ScopedAllocator. inputs is a list of nominal input tensors, all of which must be aliases to regions of the backing tensor. These will be outputs of upstream nodes that allocate their outputs from the same ScopedAllocator. shape is the shape of the output, which will usually be the same shape as the input backing tensor. reshape is true iff the output shape is to be different from that of the input backing tensor. sa_name is the Node name of the upstream ScopedAllocator. id is the scope_id identifying the upstream ScopedAllocator. N is the number of nominal inputs to be concatenated.

_ScopedAllocatorConcat' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Int64

id

-> Shape

shape

-> Tensor v'1 t

backing

-> [Tensor v'2 t]

inputs

-> m' (Tensor Value t)

output

_ScopedAllocatorSplit Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Int64

id

-> Tensor v'1 t

concat

-> [Tensor v'2 t]

split

-> m' [Tensor Value t]

output

Acts roughly like a SplitV Op that splits one tensor into multiple tensors

but must only be used in conjunction with corresponding ScopedAllocator and ScopedAllocatorConcat instances. In practice it is provided as inputs the backing tensor as first input, which contains the concatenated values, and a list of alias tensors as its other input and it simply outputs that second list.

This is an experimental op for internal use only. It is possible to use this op in unsafe ways.

concat is the single output produced by an upstream ScopedAllocatorConcat node. This is actually the backing tensor from a ScopedAllocator node upstream of the ScopedAllocatorConcat. split is a list of tensors aliased from the backing tensor. It will become the output of this ScopedAllocatorSplit node. 'type' is the common DataType of all of the input and output tensors. sa_name is the Node name of the upstream ScopedAllocator. id is the scope_id identifying the upstream ScopedAllocator. N is the number of split tensors. shapes is a list of the split tensor shapes.

_ScopedAllocatorSplit' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Int64

id

-> Tensor v'1 t

concat

-> [Tensor v'2 t]

split

-> m' [Tensor Value t]

output

_Send Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> Int64

send_device_incarnation: The current incarnation of send_device.

-> Tensor v'1 t

tensor: The tensor to send.

-> m' ControlNode 

Sends the named tensor from send_device to recv_device.

_Send' Source #

Arguments

:: (MonadBuild m', TensorType t) 
=> OpParams 
-> Int64

send_device_incarnation: The current incarnation of send_device.

-> Tensor v'1 t

tensor: The tensor to send.

-> m' ControlNode 

_SetGlobalTPUArray Source #

Arguments

:: MonadBuild m' 
=> Tensor v'1 ByteString

topology: A serialized tensorflow.tpu.TopologyProto that describes the TPU topology.

-> m' ControlNode 

An op that informs a host of the global ids of all the of TPUs in the

system.

_SetGlobalTPUArray' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> Tensor v'1 ByteString

topology: A serialized tensorflow.tpu.TopologyProto that describes the TPU topology.

-> m' ControlNode 

_ShutdownDistributedTPU :: forall m'. MonadBuild m' => m' ControlNode Source #

An op that shuts down a running distributed TPU system. The Op returns

an error if no system is running. This Op must be run on the same TPU_SYSTEM device as the corresponding _ConfigureDistributedTPU was run to start the system, and must be run only after _DisconnectHostFromDistributedTPUSystem has completed on every host in the system.

_WaitForDistributedTPU Source #

Arguments

:: MonadBuild m' 
=> [Tensor v'1 Int32]

inputs: For each initialized host, a vector giving the global TPU id of each TPU on the host.

-> m' (Tensor Value ByteString)

topology: A serialized tensorflow.tpu.TopologyProto that describes the TPU topology.

An op that blocks execution until a distributed TPU system has

started up. This Op must be run on the same TPU_SYSTEM device as _ConfigureDistributedTPU, and takes an inputs the outputs from the _InitializeHostForDistributedTPU Ops.

_WaitForDistributedTPU' Source #

Arguments

:: MonadBuild m' 
=> OpParams 
-> [Tensor v'1 Int32]

inputs: For each initialized host, a vector giving the global TPU id of each TPU on the host.

-> m' (Tensor Value ByteString)

topology: A serialized tensorflow.tpu.TopologyProto that describes the TPU topology.

_XlaRecvAtHost Source #

Arguments

:: (MonadBuild m', TensorTypes toutputs) 
=> Int64

device_ordinal: The device to use.

-> Tensor v'1 ByteString

dynamic_key: The key sent at runtime by the compile node to identify which execution the transfer corresponds to.

-> m' (TensorList Value toutputs)

outputs: A list of tensors that will be received from the XLA computation.

A placeholder op for multiple values that will be sent to TensorFlow from a

running XLA computation.

_XlaRecvAtHost' Source #

Arguments

:: (MonadBuild m', TensorTypes toutputs) 
=> OpParams 
-> Int64

device_ordinal: The device to use.

-> Tensor v'1 ByteString

dynamic_key: The key sent at runtime by the compile node to identify which execution the transfer corresponds to.

-> m' (TensorList Value toutputs)

outputs: A list of tensors that will be received from the XLA computation.

_XlaSendFromHost Source #

Arguments

:: (MonadBuild m', TensorTypes tinputs) 
=> Int64

device_ordinal: The device to use.

-> TensorList v'1 tinputs

inputs: A list of tensors that will be sent to the XLA computation.

-> Tensor v'2 ByteString

dynamic_key: The key sent at runtime by the compile node to identify which execution the transfer corresponds to.

-> m' ControlNode 

A placeholder op for multiple values that will be sent from TensorFlow to a

running XLA computation.

_XlaSendFromHost' Source #

Arguments

:: (MonadBuild m', TensorTypes tinputs) 
=> OpParams 
-> Int64

device_ordinal: The device to use.

-> TensorList v'1 tinputs

inputs: A list of tensors that will be sent to the XLA computation.

-> Tensor v'2 ByteString

dynamic_key: The key sent at runtime by the compile node to identify which execution the transfer corresponds to.

-> m' ControlNode