mirror of
https://github.com/tensorflow/haskell.git
synced 2024-11-24 03:49:44 +01:00
882 lines
37 KiB
Text
882 lines
37 KiB
Text
-- Hoogle documentation, generated by Haddock
|
|
-- See Hoogle, http://www.haskell.org/hoogle/
|
|
|
|
|
|
-- | TensorFlow bindings.
|
|
--
|
|
-- Please see README.md
|
|
@package tensorflow
|
|
@version 0.1.0.0
|
|
|
|
|
|
-- | Originally taken from internal proto-lens code.
|
|
module TensorFlow.Internal.VarInt
|
|
|
|
-- | Decode an unsigned varint.
|
|
getVarInt :: Parser Word64
|
|
|
|
-- | Encode a Word64.
|
|
putVarInt :: Word64 -> Builder
|
|
|
|
module TensorFlow.Internal.FFI
|
|
data TensorFlowException
|
|
TensorFlowException :: Code -> Text -> TensorFlowException
|
|
data Session
|
|
|
|
-- | Runs the given action after creating a session with options populated
|
|
-- by the given optionSetter.
|
|
withSession :: (SessionOptions -> IO ()) -> ((IO () -> IO ()) -> Session -> IO a) -> IO a
|
|
extendGraph :: Session -> GraphDef -> IO ()
|
|
run :: Session -> [(ByteString, TensorData)] -> [ByteString] -> [ByteString] -> IO [TensorData]
|
|
|
|
-- | All of the data needed to represent a tensor.
|
|
data TensorData
|
|
TensorData :: [Int64] -> !DataType -> !(Vector Word8) -> TensorData
|
|
[tensorDataDimensions] :: TensorData -> [Int64]
|
|
[tensorDataType] :: TensorData -> !DataType
|
|
[tensorDataBytes] :: TensorData -> !(Vector Word8)
|
|
setSessionConfig :: ConfigProto -> SessionOptions -> IO ()
|
|
setSessionTarget :: ByteString -> SessionOptions -> IO ()
|
|
|
|
-- | Returns the serialized OpList of all OpDefs defined in this address
|
|
-- space.
|
|
getAllOpList :: IO ByteString
|
|
|
|
-- | Serializes the given msg and provides it as (ptr,len) argument to the
|
|
-- given action.
|
|
useProtoAsVoidPtrLen :: (Message msg, Integral c, Show c, Bits c) => msg -> (Ptr b -> c -> IO a) -> IO a
|
|
instance GHC.Classes.Eq TensorFlow.Internal.FFI.TensorData
|
|
instance GHC.Show.Show TensorFlow.Internal.FFI.TensorData
|
|
instance GHC.Classes.Eq TensorFlow.Internal.FFI.TensorFlowException
|
|
instance GHC.Show.Show TensorFlow.Internal.FFI.TensorFlowException
|
|
instance GHC.Exception.Exception TensorFlow.Internal.FFI.TensorFlowException
|
|
|
|
module TensorFlow.Types
|
|
|
|
-- | The class of scalar types supported by tensorflow.
|
|
class TensorType a
|
|
tensorType :: TensorType a => a -> DataType
|
|
tensorRefType :: TensorType a => a -> DataType
|
|
tensorVal :: TensorType a => Lens' TensorProto [a]
|
|
|
|
-- | Decode the bytes of a TensorData into a Vector.
|
|
decodeTensorData :: TensorType a => TensorData a -> Vector a
|
|
|
|
-- | Encode a Vector into a TensorData.
|
|
--
|
|
-- The values should be in row major order, e.g.,
|
|
--
|
|
-- element 0: index (0, ..., 0) element 1: index (0, ..., 1) ...
|
|
encodeTensorData :: TensorType a => Shape -> Vector a -> TensorData a
|
|
|
|
-- | Data about a tensor that is encoded for the TensorFlow APIs.
|
|
newtype TensorData a
|
|
TensorData :: TensorData -> TensorData a
|
|
[unTensorData] :: TensorData a -> TensorData
|
|
|
|
-- | Shape (dimensions) of a tensor.
|
|
newtype Shape
|
|
Shape :: [Int64] -> Shape
|
|
protoShape :: Lens' TensorShapeProto Shape
|
|
class Attribute a
|
|
attrLens :: Attribute a => Lens' AttrValue a
|
|
|
|
-- | A <a>Constraint</a> specifying the possible choices of a
|
|
-- <a>TensorType</a>.
|
|
--
|
|
-- We implement a <a>Constraint</a> like <tt>OneOf '[Double, Float]
|
|
-- a</tt> by turning the natural representation as a conjunction, i.e.,
|
|
--
|
|
-- <pre>
|
|
-- a == Double || a == Float
|
|
-- </pre>
|
|
--
|
|
-- into a disjunction like
|
|
--
|
|
-- <pre>
|
|
-- a /= Int32 && a /= Int64 && a /= ByteString && ...
|
|
-- </pre>
|
|
--
|
|
-- using an enumeration of all the possible <a>TensorType</a>s.
|
|
type OneOf ts a = (TensorType a, TensorTypes ts, NoneOf (AllTensorTypes \\ ts) a)
|
|
|
|
-- | A constraint checking that two types are different.
|
|
|
|
-- | Helper types to produce a reasonable type error message when the
|
|
-- Constraint "a /= a" fails. TODO(judahjacobson): Use ghc-8's
|
|
-- CustomTypeErrors for this.
|
|
data TypeError a
|
|
data ExcludedCase
|
|
|
|
-- | A <a>Constraint</a> checking that the input is a list of
|
|
-- <a>TensorType</a>s. Helps improve error messages when using
|
|
-- <a>OneOf</a>.
|
|
|
|
-- | A constraint that the type <tt>a</tt> doesn't appear in the type list
|
|
-- <tt>ts</tt>. Assumes that <tt>a</tt> and each of the elements of
|
|
-- <tt>ts</tt> are <a>TensorType</a>s.
|
|
|
|
-- | Takes the difference of two lists of types.
|
|
|
|
-- | Removes a type from the given list of types.
|
|
|
|
-- | An enumeration of all valid <a>TensorType</a>s.
|
|
type AllTensorTypes = '[Float, Double, Int8, Int16, Int32, Int64, Word8, Word16, ByteString, Bool]
|
|
instance GHC.Show.Show TensorFlow.Types.Shape
|
|
instance TensorFlow.Types.TensorType GHC.Types.Float
|
|
instance TensorFlow.Types.TensorType GHC.Types.Double
|
|
instance TensorFlow.Types.TensorType GHC.Int.Int32
|
|
instance TensorFlow.Types.TensorType GHC.Int.Int64
|
|
instance TensorFlow.Types.TensorType GHC.Word.Word8
|
|
instance TensorFlow.Types.TensorType GHC.Word.Word16
|
|
instance TensorFlow.Types.TensorType GHC.Int.Int16
|
|
instance TensorFlow.Types.TensorType GHC.Int.Int8
|
|
instance TensorFlow.Types.TensorType Data.ByteString.Internal.ByteString
|
|
instance TensorFlow.Types.TensorType GHC.Types.Bool
|
|
instance TensorFlow.Types.TensorType (Data.Complex.Complex GHC.Types.Float)
|
|
instance TensorFlow.Types.TensorType (Data.Complex.Complex GHC.Types.Double)
|
|
instance GHC.Exts.IsList TensorFlow.Types.Shape
|
|
instance TensorFlow.Types.Attribute GHC.Types.Float
|
|
instance TensorFlow.Types.Attribute Data.ByteString.Internal.ByteString
|
|
instance TensorFlow.Types.Attribute GHC.Int.Int64
|
|
instance TensorFlow.Types.Attribute Proto.Tensorflow.Core.Framework.Types.DataType
|
|
instance TensorFlow.Types.Attribute Proto.Tensorflow.Core.Framework.Tensor.TensorProto
|
|
instance TensorFlow.Types.Attribute GHC.Types.Bool
|
|
instance TensorFlow.Types.Attribute TensorFlow.Types.Shape
|
|
instance TensorFlow.Types.Attribute Proto.Tensorflow.Core.Framework.AttrValue.AttrValue'ListValue
|
|
instance TensorFlow.Types.Attribute [Proto.Tensorflow.Core.Framework.Types.DataType]
|
|
instance TensorFlow.Types.Attribute [GHC.Int.Int64]
|
|
|
|
module TensorFlow.Output
|
|
|
|
-- | A type of graph node which has no outputs. These nodes are valuable
|
|
-- for causing side effects when they are run.
|
|
newtype ControlNode
|
|
ControlNode :: Op -> ControlNode
|
|
[unControlNode] :: ControlNode -> Op
|
|
|
|
-- | A device that a node can be assigned to. There's a naming convention
|
|
-- where the device names are constructed from job and replica names.
|
|
newtype Device
|
|
Device :: Text -> Device
|
|
[deviceName] :: Device -> Text
|
|
|
|
-- | The name of a node in the graph. This corresponds to the proto field
|
|
-- NodeDef.name. Includes the scope prefix (if any) and a unique
|
|
-- identifier (if the node was implicitly named).
|
|
newtype NodeName
|
|
NodeName :: Text -> NodeName
|
|
[unNodeName] :: NodeName -> Text
|
|
|
|
-- | The representation of a node in a TensorFlow graph.
|
|
data Op
|
|
|
|
-- | Properties are fixed, including the device, name, and scope.
|
|
Rendered :: !NodeDef -> Op
|
|
|
|
-- | Properties are not fixed, and may change depending on which context
|
|
-- this op is rendered in.
|
|
Unrendered :: !OpDef -> Op
|
|
|
|
-- | Traverse on the <a>Unrendered</a> of an <a>Op</a>.
|
|
--
|
|
-- Same implementation as _Left.
|
|
opUnrendered :: Traversal' Op OpDef
|
|
|
|
-- | Op definition. This corresponds somewhat to the <a>NodeDef</a> proto.
|
|
data OpDef
|
|
OpDef :: !PendingNodeName -> !OpType -> !(Map Text AttrValue) -> [Output] -> [NodeName] -> OpDef
|
|
[_opName] :: OpDef -> !PendingNodeName
|
|
[_opType] :: OpDef -> !OpType
|
|
[_opAttrs] :: OpDef -> !(Map Text AttrValue)
|
|
[_opInputs] :: OpDef -> [Output]
|
|
[_opControlInputs] :: OpDef -> [NodeName]
|
|
opName :: Lens' OpDef PendingNodeName
|
|
opType :: Lens' OpDef OpType
|
|
opAttr :: Attribute a => Text -> Lens' OpDef a
|
|
opInputs :: Lens' OpDef [Output]
|
|
opControlInputs :: Lens' OpDef [NodeName]
|
|
|
|
-- | The type of op of a node in the graph. This corresponds to the proto
|
|
-- field NodeDef.op.
|
|
newtype OpType
|
|
OpType :: Text -> OpType
|
|
[unOpType] :: OpType -> Text
|
|
newtype OutputIx
|
|
OutputIx :: Int -> OutputIx
|
|
[unOutputIx] :: OutputIx -> Int
|
|
|
|
-- | An output of a TensorFlow node.
|
|
data Output
|
|
Output :: !OutputIx -> !Op -> Output
|
|
output :: OutputIx -> Op -> Output
|
|
outputIndex :: Lens' Output OutputIx
|
|
outputOp :: Lens' Output Op
|
|
|
|
-- | The name specified for an unrendered Op. If an Op has an ImplicitName,
|
|
-- it will be assigned based on the opType plus a unique identifier. Does
|
|
-- not contain the "scope" prefix.
|
|
data PendingNodeName
|
|
ExplicitName :: !Text -> PendingNodeName
|
|
ImplicitName :: PendingNodeName
|
|
|
|
-- | Opaque handle to a mutable resource in the graph. Typical such
|
|
-- resources are variables. The type parameter corresponds to the dtype
|
|
-- of the tensor held in the variable.
|
|
newtype ResourceHandle a
|
|
ResourceHandle :: Output -> ResourceHandle a
|
|
instance GHC.Classes.Ord TensorFlow.Output.Op
|
|
instance GHC.Classes.Eq TensorFlow.Output.Op
|
|
instance GHC.Show.Show TensorFlow.Output.Output
|
|
instance GHC.Classes.Ord TensorFlow.Output.Output
|
|
instance GHC.Classes.Eq TensorFlow.Output.Output
|
|
instance GHC.Classes.Ord TensorFlow.Output.OpDef
|
|
instance GHC.Classes.Eq TensorFlow.Output.OpDef
|
|
instance GHC.Show.Show TensorFlow.Output.NodeName
|
|
instance GHC.Classes.Ord TensorFlow.Output.NodeName
|
|
instance GHC.Classes.Eq TensorFlow.Output.NodeName
|
|
instance GHC.Show.Show TensorFlow.Output.PendingNodeName
|
|
instance GHC.Classes.Ord TensorFlow.Output.PendingNodeName
|
|
instance GHC.Classes.Eq TensorFlow.Output.PendingNodeName
|
|
instance Data.String.IsString TensorFlow.Output.Device
|
|
instance GHC.Classes.Ord TensorFlow.Output.Device
|
|
instance GHC.Classes.Eq TensorFlow.Output.Device
|
|
instance GHC.Show.Show TensorFlow.Output.OutputIx
|
|
instance GHC.Enum.Enum TensorFlow.Output.OutputIx
|
|
instance GHC.Num.Num TensorFlow.Output.OutputIx
|
|
instance GHC.Classes.Ord TensorFlow.Output.OutputIx
|
|
instance GHC.Classes.Eq TensorFlow.Output.OutputIx
|
|
instance GHC.Show.Show TensorFlow.Output.OpType
|
|
instance GHC.Classes.Ord TensorFlow.Output.OpType
|
|
instance GHC.Classes.Eq TensorFlow.Output.OpType
|
|
instance Data.String.IsString TensorFlow.Output.OpType
|
|
instance GHC.Show.Show TensorFlow.Output.Device
|
|
instance GHC.Show.Show TensorFlow.Output.Op
|
|
instance Data.String.IsString TensorFlow.Output.Output
|
|
|
|
module TensorFlow.Tensor
|
|
|
|
-- | A named output of a TensorFlow operation.
|
|
--
|
|
-- The type parameter <tt>a</tt> is the type of the elements in the
|
|
-- <a>Tensor</a>. The parameter <tt>v</tt> is either <a>Value</a> or
|
|
-- <a>Ref</a>, depending on whether the graph is treating this op output
|
|
-- as an immutable <a>Value</a> or a stateful <a>Ref</a> (e.g., a
|
|
-- variable). Note that a <tt>Tensor Ref</tt> can be casted into a
|
|
-- <tt>Tensor Value</tt> via <a>value</a>.
|
|
data Tensor v a
|
|
Tensor :: (TensorKind v) -> Output -> Tensor v a
|
|
data Value
|
|
data Ref
|
|
|
|
-- | This class provides a runtime switch on whether a <a>Tensor</a> should
|
|
-- be treated as a <a>Value</a> or as a <a>Ref</a>.
|
|
data TensorKind v
|
|
ValueKind :: TensorKind Value
|
|
RefKind :: TensorKind Ref
|
|
tensorKind :: Lens' (Tensor v a) (TensorKind v)
|
|
tensorOutput :: Lens' (Tensor v a) Output
|
|
|
|
-- | Lens for the attributes of a tensor.
|
|
--
|
|
-- Only valid if the tensor has not yet been rendered. If the tensor has
|
|
-- been rendered, the traversal will be over nothing (nothing can be read
|
|
-- or written).
|
|
tensorAttr :: Attribute attr => Text -> Traversal' (Tensor v a) attr
|
|
|
|
-- | Cast a 'Tensor *' into a 'Tensor Value'. Common usage is to cast a Ref
|
|
-- into Value. This behaves like a no-op.
|
|
value :: Tensor v a -> Tensor Value a
|
|
|
|
-- | A pair of a <a>Tensor</a> and some data that should be fed into that
|
|
-- <a>Tensor</a> when running the graph.
|
|
data Feed
|
|
Feed :: Output -> TensorData -> Feed
|
|
|
|
-- | Create a <a>Feed</a> for feeding the given data into a <a>Tensor</a>
|
|
-- when running the graph.
|
|
--
|
|
-- Note that if a <a>Tensor</a> is rendered, its identity may change; so
|
|
-- feeding the rendered <a>Tensor</a> may be different than feeding the
|
|
-- original <a>Tensor</a>.
|
|
feed :: Tensor v a -> TensorData a -> Feed
|
|
|
|
-- | Create a <a>Tensor</a> for a given name. This can be used to reference
|
|
-- nodes in a <tt>GraphDef</tt> that was loaded via <tt>addGraphDef</tt>.
|
|
-- TODO(judahjacobson): add more safety checks here.
|
|
tensorFromName :: TensorKind v -> Text -> Tensor v a
|
|
|
|
module TensorFlow.Build
|
|
|
|
-- | A type of graph node which has no outputs. These nodes are valuable
|
|
-- for causing side effects when they are run.
|
|
newtype ControlNode
|
|
ControlNode :: Op -> ControlNode
|
|
[unControlNode] :: ControlNode -> Op
|
|
data Unique
|
|
explicitName :: Text -> PendingNodeName
|
|
implicitName :: PendingNodeName
|
|
opDef :: OpType -> OpDef
|
|
opDefWithName :: PendingNodeName -> OpType -> OpDef
|
|
opName :: Lens' OpDef PendingNodeName
|
|
opType :: Lens' OpDef OpType
|
|
opAttr :: Attribute a => Text -> Lens' OpDef a
|
|
opInputs :: Lens' OpDef [Output]
|
|
opControlInputs :: Lens' OpDef [NodeName]
|
|
data GraphState
|
|
|
|
-- | Render a <a>Tensor</a>, fixing its name, scope, device and control
|
|
-- inputs from the <a>Build</a> context. Also renders any dependencies of
|
|
-- the <a>Tensor</a> that weren't already rendered.
|
|
--
|
|
-- This operation is idempotent; <tt>render >=> render ===
|
|
-- render</tt>. However, rendering a (previously un-rendered)
|
|
-- <a>Tensor</a> in two different contexts may result in two different
|
|
-- <a>Tensor</a>s.
|
|
render :: Tensor v a -> Build (Tensor v a)
|
|
|
|
-- | Render a <a>Tensor</a> and get its node's name.
|
|
renderNodeName :: Tensor v a -> Build NodeName
|
|
renderedNodeDefs :: Lens' GraphState (Map NodeName NodeDef)
|
|
|
|
-- | An action for building nodes in a TensorFlow graph. Used to manage
|
|
-- build state internally as part of the <tt>Session</tt> monad.
|
|
data BuildT m a
|
|
|
|
-- | An action for building nodes in a TensorFlow graph.
|
|
type Build = BuildT Identity
|
|
|
|
-- | Registers the given node to be executed before the next <a>run</a>.
|
|
addInitializer :: ControlNode -> Build ()
|
|
|
|
-- | This is Control.Monad.Morph.hoist sans the dependency.
|
|
hoistBuildT :: (forall a. m a -> n a) -> BuildT m b -> BuildT n b
|
|
evalBuildT :: Monad m => BuildT m a -> m a
|
|
runBuildT :: BuildT m a -> m (a, GraphState)
|
|
|
|
-- | Produce a GraphDef proto representation of the nodes that are rendered
|
|
-- in the given <a>Build</a> action.
|
|
asGraphDef :: Build a -> GraphDef
|
|
addGraphDef :: GraphDef -> Build ()
|
|
|
|
-- | Get all the initializers that have accumulated so far, and clear that
|
|
-- buffer.
|
|
flushInitializers :: Monad m => BuildT m [NodeName]
|
|
|
|
-- | Get all the NodeDefs that have accumulated so far, and clear that
|
|
-- buffer.
|
|
flushNodeBuffer :: Monad m => BuildT m [NodeDef]
|
|
|
|
-- | Render the given op if it hasn't been rendered already, and return its
|
|
-- name.
|
|
getOrAddOp :: Op -> Build NodeName
|
|
|
|
-- | Add a new node for a given <a>OpDef</a>. This is used for making
|
|
-- "stateful" ops which are not safe to dedup (e.g, "variable" and
|
|
-- "assign").
|
|
addNewOp :: OpDef -> Build NodeDef
|
|
|
|
-- | Render an <a>Output</a> and return a string representation for the
|
|
-- TensorFlow foreign APIs.
|
|
renderOutput :: Output -> Build Text
|
|
|
|
-- | Places all nodes rendered in the given <a>Build</a> action on the same
|
|
-- device as the given Tensor (see also <a>withDevice</a>). Make sure
|
|
-- that the action has side effects of rendering the desired tensors. A
|
|
-- pure return would not have the desired effect.
|
|
colocateWith :: Tensor v b -> Build a -> Build a
|
|
|
|
-- | Modify some part of the state, run an action, and restore the state
|
|
-- after that action is done.
|
|
withStateLens :: MonadState s m => Lens' s a -> (a -> a) -> m b -> m b
|
|
|
|
-- | Set a device for all nodes rendered in the given <a>Build</a> action
|
|
-- (unless further overridden by another use of withDevice).
|
|
withDevice :: Maybe Device -> Build a -> Build a
|
|
|
|
-- | Prepend a scope to all nodes rendered in the given <a>Build</a>
|
|
-- action.
|
|
withNameScope :: Text -> Build a -> Build a
|
|
|
|
-- | Add control inputs to all nodes rendered in the given <a>Build</a>
|
|
-- action.
|
|
withNodeDependencies :: Set NodeName -> Build a -> Build a
|
|
|
|
-- | Records the given summary action in Build for retrieval with
|
|
-- <a>collectAllSummaries</a>. The summary op is required to produce a
|
|
-- Summary protocol buffer in string form. For safety, use the
|
|
-- pre-composed functions: Logging.scalarSummary and
|
|
-- Logging.histogramSummary.
|
|
addSummary :: SummaryTensor -> Build ()
|
|
|
|
-- | Synonym for the tensors that return serialized Summary proto.
|
|
type SummaryTensor = Tensor Value ByteString
|
|
|
|
-- | Retrieves the summary ops collected thus far. Typically this only
|
|
-- happens once, but if <a>buildWithSummary</a> is used repeatedly, the
|
|
-- values accumulate.
|
|
collectAllSummaries :: Monad m => BuildT m [SummaryTensor]
|
|
instance GHC.Base.Monad m => Control.Monad.State.Class.MonadState TensorFlow.Build.GraphState (TensorFlow.Build.BuildT m)
|
|
instance Control.Monad.Trans.Class.MonadTrans TensorFlow.Build.BuildT
|
|
instance Control.Monad.IO.Class.MonadIO m => Control.Monad.IO.Class.MonadIO (TensorFlow.Build.BuildT m)
|
|
instance GHC.Base.Monad m => GHC.Base.Monad (TensorFlow.Build.BuildT m)
|
|
instance GHC.Base.Monad m => GHC.Base.Applicative (TensorFlow.Build.BuildT m)
|
|
instance GHC.Base.Functor m => GHC.Base.Functor (TensorFlow.Build.BuildT m)
|
|
instance GHC.Classes.Ord TensorFlow.Build.PendingNode
|
|
instance GHC.Classes.Eq TensorFlow.Build.PendingNode
|
|
instance Data.String.IsString TensorFlow.Build.Scope
|
|
instance GHC.Classes.Ord TensorFlow.Build.Scope
|
|
instance GHC.Classes.Eq TensorFlow.Build.Scope
|
|
instance GHC.Enum.Enum TensorFlow.Build.Unique
|
|
instance GHC.Classes.Ord TensorFlow.Build.Unique
|
|
instance GHC.Classes.Eq TensorFlow.Build.Unique
|
|
instance GHC.Show.Show TensorFlow.Build.Scope
|
|
|
|
module TensorFlow.BuildOp
|
|
|
|
-- | Class of types that can be used as op outputs.
|
|
class OpResult a
|
|
|
|
-- | Class of types that can be used as op functions.
|
|
class BuildOp f
|
|
|
|
-- | Starts an operation that returns a structured set of tensors
|
|
-- (singletons or tuples).
|
|
buildOp :: BuildOp f => OpDef -> f
|
|
|
|
-- | Starts an operation that returns a list of tensors.
|
|
buildListOp :: BuildOp f => [Int64] -> OpDef -> f
|
|
|
|
-- | Returns true if all the integers in each tuple are identical. Throws
|
|
-- an error with a descriptive message if not.
|
|
eqLengthGuard :: [(String, [(String, Int)])] -> Bool
|
|
instance GHC.Show.Show TensorFlow.BuildOp.ResultState
|
|
instance (TensorFlow.BuildOp.OpResult a1, TensorFlow.BuildOp.OpResult a2) => TensorFlow.BuildOp.OpResult (a1, a2)
|
|
instance (TensorFlow.BuildOp.OpResult a1, TensorFlow.BuildOp.OpResult a2, TensorFlow.BuildOp.OpResult a3) => TensorFlow.BuildOp.OpResult (a1, a2, a3)
|
|
instance (TensorFlow.BuildOp.OpResult a1, TensorFlow.BuildOp.OpResult a2, TensorFlow.BuildOp.OpResult a3, TensorFlow.BuildOp.OpResult a4) => TensorFlow.BuildOp.OpResult (a1, a2, a3, a4)
|
|
instance (TensorFlow.BuildOp.OpResult a1, TensorFlow.BuildOp.OpResult a2, TensorFlow.BuildOp.OpResult a3, TensorFlow.BuildOp.OpResult a4, TensorFlow.BuildOp.OpResult a5) => TensorFlow.BuildOp.OpResult (a1, a2, a3, a4, a5)
|
|
instance (TensorFlow.BuildOp.OpResult a1, TensorFlow.BuildOp.OpResult a2, TensorFlow.BuildOp.OpResult a3, TensorFlow.BuildOp.OpResult a4, TensorFlow.BuildOp.OpResult a5, TensorFlow.BuildOp.OpResult a6) => TensorFlow.BuildOp.OpResult (a1, a2, a3, a4, a5, a6)
|
|
instance TensorFlow.BuildOp.OpResult (TensorFlow.Output.ResourceHandle a)
|
|
instance TensorFlow.BuildOp.OpResult (TensorFlow.Tensor.Tensor TensorFlow.Tensor.Value a)
|
|
instance TensorFlow.BuildOp.OpResult (TensorFlow.Tensor.Tensor TensorFlow.Tensor.Ref a)
|
|
instance TensorFlow.BuildOp.OpResult TensorFlow.Output.ControlNode
|
|
instance TensorFlow.BuildOp.OpResult a => TensorFlow.BuildOp.OpResult [a]
|
|
instance TensorFlow.BuildOp.BuildOp TensorFlow.Output.ControlNode
|
|
instance TensorFlow.BuildOp.BuildOp (TensorFlow.Output.ResourceHandle a)
|
|
instance TensorFlow.BuildOp.BuildOp (TensorFlow.Tensor.Tensor TensorFlow.Tensor.Value a)
|
|
instance TensorFlow.BuildOp.BuildOp (TensorFlow.Tensor.Tensor TensorFlow.Tensor.Ref a)
|
|
instance TensorFlow.BuildOp.BuildOp [TensorFlow.Tensor.Tensor TensorFlow.Tensor.Value a]
|
|
instance (TensorFlow.BuildOp.OpResult t1, TensorFlow.BuildOp.OpResult t2) => TensorFlow.BuildOp.BuildOp (t1, t2)
|
|
instance (TensorFlow.BuildOp.OpResult t1, TensorFlow.BuildOp.OpResult t2, TensorFlow.BuildOp.OpResult t3) => TensorFlow.BuildOp.BuildOp (t1, t2, t3)
|
|
instance (TensorFlow.BuildOp.OpResult t1, TensorFlow.BuildOp.OpResult t2, TensorFlow.BuildOp.OpResult t3, TensorFlow.BuildOp.OpResult t4) => TensorFlow.BuildOp.BuildOp (t1, t2, t3, t4)
|
|
instance (TensorFlow.BuildOp.OpResult t1, TensorFlow.BuildOp.OpResult t2, TensorFlow.BuildOp.OpResult t3, TensorFlow.BuildOp.OpResult t4, TensorFlow.BuildOp.OpResult t5) => TensorFlow.BuildOp.BuildOp (t1, t2, t3, t4, t5)
|
|
instance (TensorFlow.BuildOp.OpResult t1, TensorFlow.BuildOp.OpResult t2, TensorFlow.BuildOp.OpResult t3, TensorFlow.BuildOp.OpResult t4, TensorFlow.BuildOp.OpResult t5, TensorFlow.BuildOp.OpResult t6) => TensorFlow.BuildOp.BuildOp (t1, t2, t3, t4, t5, t6)
|
|
instance TensorFlow.BuildOp.OpResult a => TensorFlow.BuildOp.BuildOp (TensorFlow.Build.Build a)
|
|
instance TensorFlow.BuildOp.BuildOp f => TensorFlow.BuildOp.BuildOp (TensorFlow.Output.ResourceHandle a -> f)
|
|
instance TensorFlow.BuildOp.BuildOp f => TensorFlow.BuildOp.BuildOp (TensorFlow.Tensor.Tensor v a -> f)
|
|
instance TensorFlow.BuildOp.BuildOp f => TensorFlow.BuildOp.BuildOp ([TensorFlow.Tensor.Tensor v a] -> f)
|
|
|
|
module TensorFlow.Nodes
|
|
|
|
-- | Types that contain ops which can be run.
|
|
class Nodes t
|
|
getNodes :: Nodes t => t -> Build (Set NodeName)
|
|
|
|
-- | Types that tensor representations (e.g. <a>Tensor</a>,
|
|
-- <a>ControlNode</a>) can be fetched into.
|
|
--
|
|
-- Includes collections of tensors (e.g. tuples).
|
|
class Nodes t => Fetchable t a
|
|
getFetch :: Fetchable t a => t -> Build (Fetch a)
|
|
|
|
-- | Fetch action. Keeps track of what needs to be fetched and how to
|
|
-- decode the fetched data.
|
|
data Fetch a
|
|
Fetch :: Set Text -> (Map Text TensorData -> a) -> Fetch a
|
|
|
|
-- | Nodes to fetch
|
|
[fetches] :: Fetch a -> Set Text
|
|
|
|
-- | Function to create an <tt>a</tt> from the fetched data.
|
|
[fetchRestore] :: Fetch a -> Map Text TensorData -> a
|
|
nodesUnion :: (Monoid b, Traversable t, Applicative f) => t (f b) -> f b
|
|
fetchTensorList :: TensorType a => Tensor v a -> Build (Fetch (Shape, [a]))
|
|
fetchTensorVector :: TensorType a => Tensor v a -> Build (Fetch (Shape, Vector a))
|
|
newtype Scalar a
|
|
Scalar :: a -> Scalar a
|
|
[unScalar] :: Scalar a -> a
|
|
instance Data.String.IsString a => Data.String.IsString (TensorFlow.Nodes.Scalar a)
|
|
instance GHC.Real.RealFrac a => GHC.Real.RealFrac (TensorFlow.Nodes.Scalar a)
|
|
instance GHC.Float.RealFloat a => GHC.Float.RealFloat (TensorFlow.Nodes.Scalar a)
|
|
instance GHC.Real.Real a => GHC.Real.Real (TensorFlow.Nodes.Scalar a)
|
|
instance GHC.Float.Floating a => GHC.Float.Floating (TensorFlow.Nodes.Scalar a)
|
|
instance GHC.Real.Fractional a => GHC.Real.Fractional (TensorFlow.Nodes.Scalar a)
|
|
instance GHC.Num.Num a => GHC.Num.Num (TensorFlow.Nodes.Scalar a)
|
|
instance GHC.Classes.Ord a => GHC.Classes.Ord (TensorFlow.Nodes.Scalar a)
|
|
instance GHC.Classes.Eq a => GHC.Classes.Eq (TensorFlow.Nodes.Scalar a)
|
|
instance GHC.Show.Show a => GHC.Show.Show (TensorFlow.Nodes.Scalar a)
|
|
instance GHC.Base.Functor TensorFlow.Nodes.Fetch
|
|
instance GHC.Base.Applicative TensorFlow.Nodes.Fetch
|
|
instance (TensorFlow.Nodes.Nodes t1, TensorFlow.Nodes.Nodes t2) => TensorFlow.Nodes.Nodes (t1, t2)
|
|
instance (TensorFlow.Nodes.Nodes t1, TensorFlow.Nodes.Nodes t2, TensorFlow.Nodes.Nodes t3) => TensorFlow.Nodes.Nodes (t1, t2, t3)
|
|
instance (TensorFlow.Nodes.Fetchable t1 a1, TensorFlow.Nodes.Fetchable t2 a2) => TensorFlow.Nodes.Fetchable (t1, t2) (a1, a2)
|
|
instance (TensorFlow.Nodes.Fetchable t1 a1, TensorFlow.Nodes.Fetchable t2 a2, TensorFlow.Nodes.Fetchable t3 a3) => TensorFlow.Nodes.Fetchable (t1, t2, t3) (a1, a2, a3)
|
|
instance TensorFlow.Nodes.Nodes t => TensorFlow.Nodes.Nodes [t]
|
|
instance TensorFlow.Nodes.Fetchable t a => TensorFlow.Nodes.Fetchable [t] [a]
|
|
instance TensorFlow.Nodes.Nodes TensorFlow.Output.ControlNode
|
|
instance (a ~ ()) => TensorFlow.Nodes.Fetchable TensorFlow.Output.ControlNode a
|
|
instance TensorFlow.Nodes.Nodes (TensorFlow.Tensor.Tensor v a)
|
|
instance (TensorFlow.Types.TensorType a, a ~ a') => TensorFlow.Nodes.Fetchable (TensorFlow.Tensor.Tensor v a) (Data.Vector.Vector a')
|
|
instance (TensorFlow.Types.TensorType a, a ~ a') => TensorFlow.Nodes.Fetchable (TensorFlow.Tensor.Tensor v a) (TensorFlow.Nodes.Scalar a')
|
|
|
|
module TensorFlow.ControlFlow
|
|
|
|
-- | Modify a <a>Build</a> action, such that all new ops rendered in it
|
|
-- will depend on the nodes in the first argument.
|
|
withControlDependencies :: Nodes t => t -> Build a -> Build a
|
|
|
|
-- | Create an op that groups multiple operations.
|
|
--
|
|
-- When this op finishes, all ops in the input <tt>n</tt> have finished.
|
|
-- This op has no output.
|
|
group :: Nodes t => t -> Build ControlNode
|
|
|
|
-- | Returns a <a>Tensor</a> with the same shape and contents as the input.
|
|
identity :: TensorType a => Tensor v a -> Tensor v a
|
|
|
|
-- | Does nothing. Only useful as a placeholder for control edges.
|
|
noOp :: ControlNode
|
|
|
|
-- | Returns a <a>Tensor</a> with a given name and the same shape and
|
|
-- contents as the input.
|
|
--
|
|
-- TODO(judahjacobson): This breaks when used with uninitialize
|
|
-- <tt>Tensor Ref</tt>s, since <tt>RefIdentity</tt> doesn't have
|
|
-- SetAllowsUninitializedInput(). Look into whether we can change that
|
|
-- op.
|
|
named :: TensorType a => Text -> Tensor v a -> Tensor v a
|
|
|
|
module TensorFlow.Session
|
|
data Session a
|
|
|
|
-- | Customization for session. Use the lenses to update:
|
|
-- <a>sessionTarget</a>, <a>sessionTracer</a>, <a>sessionConfig</a>.
|
|
data Options
|
|
|
|
-- | Uses the specified config for the created session.
|
|
sessionConfig :: Lens' Options ConfigProto
|
|
|
|
-- | Target can be: "local", ip:port, host:port. The set of supported
|
|
-- factories depends on the linked in libraries.
|
|
sessionTarget :: Lens' Options ByteString
|
|
|
|
-- | Uses the given logger to monitor session progress.
|
|
sessionTracer :: Lens' Options Tracer
|
|
|
|
-- | Run <a>Session</a> actions in a new TensorFlow session.
|
|
runSession :: Session a -> IO a
|
|
|
|
-- | Run <a>Session</a> actions in a new TensorFlow session created with
|
|
-- the given option setter actions (<a>sessionTarget</a>,
|
|
-- <a>sessionConfig</a>).
|
|
runSessionWithOptions :: Options -> Session a -> IO a
|
|
|
|
-- | Lift a <a>Build</a> action into a <a>Session</a>, including any
|
|
-- explicit op renderings.
|
|
build :: Build a -> Session a
|
|
|
|
-- | Helper combinator for doing something with the result of a
|
|
-- <a>Build</a> action. Example usage:
|
|
--
|
|
-- <pre>
|
|
-- buildAnd run :: Fetchable t a => Build t -> Session a
|
|
-- </pre>
|
|
buildAnd :: (a -> Session b) -> Build a -> Session b
|
|
|
|
-- | Lift a <a>Build</a> action into a <a>Session</a>, including any
|
|
-- explicit op renderings. Returns the merged summary ops which can be
|
|
-- used for logging, see <a>build</a> for a convenient wrapper.
|
|
buildWithSummary :: Build a -> Session (a, [SummaryTensor])
|
|
|
|
-- | Add all pending rendered nodes to the TensorFlow graph and runs any
|
|
-- pending initializers.
|
|
--
|
|
-- Note that run, runWithFeeds, etc. will all call this function
|
|
-- implicitly.
|
|
extend :: Session ()
|
|
addGraphDef :: GraphDef -> Build ()
|
|
|
|
-- | Run a subgraph <tt>t</tt>, rendering any dependent nodes that aren't
|
|
-- already rendered, and fetch the corresponding values for <tt>a</tt>.
|
|
run :: Fetchable t a => t -> Session a
|
|
|
|
-- | Run a subgraph <tt>t</tt>, rendering any dependent nodes that aren't
|
|
-- already rendered, feed the given input values, and fetch the
|
|
-- corresponding result values for <tt>a</tt>.
|
|
runWithFeeds :: Fetchable t a => [Feed] -> t -> Session a
|
|
|
|
-- | Run a subgraph <tt>t</tt>, rendering and extending any dependent nodes
|
|
-- that aren't already rendered. This behaves like <a>run</a> except that
|
|
-- it doesn't do any fetches.
|
|
run_ :: Nodes t => t -> Session ()
|
|
|
|
-- | Run a subgraph <tt>t</tt>, rendering any dependent nodes that aren't
|
|
-- already rendered, feed the given input values, and fetch the
|
|
-- corresponding result values for <tt>a</tt>. This behaves like
|
|
-- <a>runWithFeeds</a> except that it doesn't do any fetches.
|
|
runWithFeeds_ :: Nodes t => [Feed] -> t -> Session ()
|
|
|
|
-- | Starts a concurrent thread which evaluates the given Nodes forever
|
|
-- until runSession exits or an exception occurs. Graph extension happens
|
|
-- synchronously, but the resultant run proceeds as a separate thread.
|
|
asyncProdNodes :: Nodes t => t -> Session ()
|
|
instance Control.Monad.IO.Class.MonadIO TensorFlow.Session.Session
|
|
instance GHC.Base.Monad TensorFlow.Session.Session
|
|
instance GHC.Base.Applicative TensorFlow.Session.Session
|
|
instance GHC.Base.Functor TensorFlow.Session.Session
|
|
instance Data.Default.Class.Default TensorFlow.Session.Options
|
|
|
|
|
|
-- | The core functionality of TensorFlow.
|
|
--
|
|
-- Unless you are defining ops, you do not need to import other modules
|
|
-- from this package.
|
|
--
|
|
-- Basic ops are provided in the tensorflow-ops and tensorflow-core-ops
|
|
-- packages.
|
|
module TensorFlow.Core
|
|
data Session a
|
|
|
|
-- | Customization for session. Use the lenses to update:
|
|
-- <a>sessionTarget</a>, <a>sessionTracer</a>, <a>sessionConfig</a>.
|
|
data Options
|
|
|
|
-- | Uses the specified config for the created session.
|
|
sessionConfig :: Lens' Options ConfigProto
|
|
|
|
-- | Target can be: "local", ip:port, host:port. The set of supported
|
|
-- factories depends on the linked in libraries.
|
|
sessionTarget :: Lens' Options ByteString
|
|
|
|
-- | Uses the given logger to monitor session progress.
|
|
sessionTracer :: Lens' Options Tracer
|
|
|
|
-- | Run <a>Session</a> actions in a new TensorFlow session.
|
|
runSession :: Session a -> IO a
|
|
|
|
-- | Run <a>Session</a> actions in a new TensorFlow session created with
|
|
-- the given option setter actions (<a>sessionTarget</a>,
|
|
-- <a>sessionConfig</a>).
|
|
runSessionWithOptions :: Options -> Session a -> IO a
|
|
|
|
-- | Lift a <a>Build</a> action into a <a>Session</a>, including any
|
|
-- explicit op renderings.
|
|
build :: Build a -> Session a
|
|
|
|
-- | Helper combinator for doing something with the result of a
|
|
-- <a>Build</a> action. Example usage:
|
|
--
|
|
-- <pre>
|
|
-- buildAnd run :: Fetchable t a => Build t -> Session a
|
|
-- </pre>
|
|
buildAnd :: (a -> Session b) -> Build a -> Session b
|
|
|
|
-- | Lift a <a>Build</a> action into a <a>Session</a>, including any
|
|
-- explicit op renderings. Returns the merged summary ops which can be
|
|
-- used for logging, see <a>build</a> for a convenient wrapper.
|
|
buildWithSummary :: Build a -> Session (a, [SummaryTensor])
|
|
|
|
-- | Types that tensor representations (e.g. <a>Tensor</a>,
|
|
-- <a>ControlNode</a>) can be fetched into.
|
|
--
|
|
-- Includes collections of tensors (e.g. tuples).
|
|
class Nodes t => Fetchable t a
|
|
newtype Scalar a
|
|
Scalar :: a -> Scalar a
|
|
[unScalar] :: Scalar a -> a
|
|
|
|
-- | Types that contain ops which can be run.
|
|
class Nodes t
|
|
|
|
-- | Run a subgraph <tt>t</tt>, rendering any dependent nodes that aren't
|
|
-- already rendered, and fetch the corresponding values for <tt>a</tt>.
|
|
run :: Fetchable t a => t -> Session a
|
|
|
|
-- | Run a subgraph <tt>t</tt>, rendering and extending any dependent nodes
|
|
-- that aren't already rendered. This behaves like <a>run</a> except that
|
|
-- it doesn't do any fetches.
|
|
run_ :: Nodes t => t -> Session ()
|
|
|
|
-- | A pair of a <a>Tensor</a> and some data that should be fed into that
|
|
-- <a>Tensor</a> when running the graph.
|
|
data Feed
|
|
|
|
-- | Create a <a>Feed</a> for feeding the given data into a <a>Tensor</a>
|
|
-- when running the graph.
|
|
--
|
|
-- Note that if a <a>Tensor</a> is rendered, its identity may change; so
|
|
-- feeding the rendered <a>Tensor</a> may be different than feeding the
|
|
-- original <a>Tensor</a>.
|
|
feed :: Tensor v a -> TensorData a -> Feed
|
|
|
|
-- | Run a subgraph <tt>t</tt>, rendering any dependent nodes that aren't
|
|
-- already rendered, feed the given input values, and fetch the
|
|
-- corresponding result values for <tt>a</tt>.
|
|
runWithFeeds :: Fetchable t a => [Feed] -> t -> Session a
|
|
|
|
-- | Run a subgraph <tt>t</tt>, rendering any dependent nodes that aren't
|
|
-- already rendered, feed the given input values, and fetch the
|
|
-- corresponding result values for <tt>a</tt>. This behaves like
|
|
-- <a>runWithFeeds</a> except that it doesn't do any fetches.
|
|
runWithFeeds_ :: Nodes t => [Feed] -> t -> Session ()
|
|
|
|
-- | Starts a concurrent thread which evaluates the given Nodes forever
|
|
-- until runSession exits or an exception occurs. Graph extension happens
|
|
-- synchronously, but the resultant run proceeds as a separate thread.
|
|
asyncProdNodes :: Nodes t => t -> Session ()
|
|
|
|
-- | An action for building nodes in a TensorFlow graph.
|
|
type Build = BuildT Identity
|
|
|
|
-- | An action for building nodes in a TensorFlow graph. Used to manage
|
|
-- build state internally as part of the <tt>Session</tt> monad.
|
|
data BuildT m a
|
|
|
|
-- | Render a <a>Tensor</a>, fixing its name, scope, device and control
|
|
-- inputs from the <a>Build</a> context. Also renders any dependencies of
|
|
-- the <a>Tensor</a> that weren't already rendered.
|
|
--
|
|
-- This operation is idempotent; <tt>render >=> render ===
|
|
-- render</tt>. However, rendering a (previously un-rendered)
|
|
-- <a>Tensor</a> in two different contexts may result in two different
|
|
-- <a>Tensor</a>s.
|
|
render :: Tensor v a -> Build (Tensor v a)
|
|
|
|
-- | Produce a GraphDef proto representation of the nodes that are rendered
|
|
-- in the given <a>Build</a> action.
|
|
asGraphDef :: Build a -> GraphDef
|
|
addGraphDef :: GraphDef -> Build ()
|
|
|
|
-- | A type of graph node which has no outputs. These nodes are valuable
|
|
-- for causing side effects when they are run.
|
|
data ControlNode
|
|
|
|
-- | A named output of a TensorFlow operation.
|
|
--
|
|
-- The type parameter <tt>a</tt> is the type of the elements in the
|
|
-- <a>Tensor</a>. The parameter <tt>v</tt> is either <a>Value</a> or
|
|
-- <a>Ref</a>, depending on whether the graph is treating this op output
|
|
-- as an immutable <a>Value</a> or a stateful <a>Ref</a> (e.g., a
|
|
-- variable). Note that a <tt>Tensor Ref</tt> can be casted into a
|
|
-- <tt>Tensor Value</tt> via <a>value</a>.
|
|
data Tensor v a
|
|
data Value
|
|
data Ref
|
|
|
|
-- | This class provides a runtime switch on whether a <a>Tensor</a> should
|
|
-- be treated as a <a>Value</a> or as a <a>Ref</a>.
|
|
data TensorKind v
|
|
ValueKind :: TensorKind Value
|
|
RefKind :: TensorKind Ref
|
|
|
|
-- | Lens for the attributes of a tensor.
|
|
--
|
|
-- Only valid if the tensor has not yet been rendered. If the tensor has
|
|
-- been rendered, the traversal will be over nothing (nothing can be read
|
|
-- or written).
|
|
tensorAttr :: Attribute attr => Text -> Traversal' (Tensor v a) attr
|
|
|
|
-- | Cast a 'Tensor *' into a 'Tensor Value'. Common usage is to cast a Ref
|
|
-- into Value. This behaves like a no-op.
|
|
value :: Tensor v a -> Tensor Value a
|
|
|
|
-- | Create a <a>Tensor</a> for a given name. This can be used to reference
|
|
-- nodes in a <tt>GraphDef</tt> that was loaded via <tt>addGraphDef</tt>.
|
|
-- TODO(judahjacobson): add more safety checks here.
|
|
tensorFromName :: TensorKind v -> Text -> Tensor v a
|
|
|
|
-- | Data about a tensor that is encoded for the TensorFlow APIs.
|
|
data TensorData a
|
|
|
|
-- | The class of scalar types supported by tensorflow.
|
|
class TensorType a
|
|
|
|
-- | Decode the bytes of a TensorData into a Vector.
|
|
decodeTensorData :: TensorType a => TensorData a -> Vector a
|
|
|
|
-- | Encode a Vector into a TensorData.
|
|
--
|
|
-- The values should be in row major order, e.g.,
|
|
--
|
|
-- element 0: index (0, ..., 0) element 1: index (0, ..., 1) ...
|
|
encodeTensorData :: TensorType a => Shape -> Vector a -> TensorData a
|
|
|
|
-- | Shape (dimensions) of a tensor.
|
|
newtype Shape
|
|
Shape :: [Int64] -> Shape
|
|
|
|
-- | A <a>Constraint</a> specifying the possible choices of a
|
|
-- <a>TensorType</a>.
|
|
--
|
|
-- We implement a <a>Constraint</a> like <tt>OneOf '[Double, Float]
|
|
-- a</tt> by turning the natural representation as a conjunction, i.e.,
|
|
--
|
|
-- <pre>
|
|
-- a == Double || a == Float
|
|
-- </pre>
|
|
--
|
|
-- into a disjunction like
|
|
--
|
|
-- <pre>
|
|
-- a /= Int32 && a /= Int64 && a /= ByteString && ...
|
|
-- </pre>
|
|
--
|
|
-- using an enumeration of all the possible <a>TensorType</a>s.
|
|
type OneOf ts a = (TensorType a, TensorTypes ts, NoneOf (AllTensorTypes \\ ts) a)
|
|
|
|
-- | A constraint checking that two types are different.
|
|
|
|
-- | Places all nodes rendered in the given <a>Build</a> action on the same
|
|
-- device as the given Tensor (see also <a>withDevice</a>). Make sure
|
|
-- that the action has side effects of rendering the desired tensors. A
|
|
-- pure return would not have the desired effect.
|
|
colocateWith :: Tensor v b -> Build a -> Build a
|
|
|
|
-- | A device that a node can be assigned to. There's a naming convention
|
|
-- where the device names are constructed from job and replica names.
|
|
newtype Device
|
|
Device :: Text -> Device
|
|
[deviceName] :: Device -> Text
|
|
|
|
-- | Set a device for all nodes rendered in the given <a>Build</a> action
|
|
-- (unless further overridden by another use of withDevice).
|
|
withDevice :: Maybe Device -> Build a -> Build a
|
|
|
|
-- | Prepend a scope to all nodes rendered in the given <a>Build</a>
|
|
-- action.
|
|
withNameScope :: Text -> Build a -> Build a
|
|
|
|
-- | Returns a <a>Tensor</a> with a given name and the same shape and
|
|
-- contents as the input.
|
|
--
|
|
-- TODO(judahjacobson): This breaks when used with uninitialize
|
|
-- <tt>Tensor Ref</tt>s, since <tt>RefIdentity</tt> doesn't have
|
|
-- SetAllowsUninitializedInput(). Look into whether we can change that
|
|
-- op.
|
|
named :: TensorType a => Text -> Tensor v a -> Tensor v a
|
|
|
|
-- | Modify a <a>Build</a> action, such that all new ops rendered in it
|
|
-- will depend on the nodes in the first argument.
|
|
withControlDependencies :: Nodes t => t -> Build a -> Build a
|
|
|
|
-- | Create an op that groups multiple operations.
|
|
--
|
|
-- When this op finishes, all ops in the input <tt>n</tt> have finished.
|
|
-- This op has no output.
|
|
group :: Nodes t => t -> Build ControlNode
|
|
|
|
-- | Returns a <a>Tensor</a> with the same shape and contents as the input.
|
|
identity :: TensorType a => Tensor v a -> Tensor v a
|
|
|
|
-- | Does nothing. Only useful as a placeholder for control edges.
|
|
noOp :: ControlNode
|