<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><link rel="stylesheet" type="text/css" href="style.css" /><script type="text/javascript" src="highlight.js"></script></head><body><pre><span class="hs-comment">-- Copyright 2016 TensorFlow authors.</span><span>
</span><span id="line-2"></span><span class="hs-comment">--</span><span>
</span><span id="line-3"></span><span class="hs-comment">-- Licensed under the Apache License, Version 2.0 (the "License");</span><span>
</span><span id="line-4"></span><span class="hs-comment">-- you may not use this file except in compliance with the License.</span><span>
</span><span id="line-5"></span><span class="hs-comment">-- You may obtain a copy of the License at</span><span>
</span><span id="line-6"></span><span class="hs-comment">--</span><span>
</span><span id="line-7"></span><span class="hs-comment">-- http://www.apache.org/licenses/LICENSE-2.0</span><span>
</span><span id="line-8"></span><span class="hs-comment">--</span><span>
</span><span id="line-9"></span><span class="hs-comment">-- Unless required by applicable law or agreed to in writing, software</span><span>
</span><span id="line-10"></span><span class="hs-comment">-- distributed under the License is distributed on an "AS IS" BASIS,</span><span>
</span><span id="line-11"></span><span class="hs-comment">-- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span><span>
</span><span id="line-12"></span><span class="hs-comment">-- See the License for the specific language governing permissions and</span><span>
</span><span id="line-13"></span><span class="hs-comment">-- limitations under the License.</span><span>
</span><span id="line-14"></span><span>
</span><span id="line-15"></span><span class="hs-pragma">{-# LANGUAGE DataKinds #-}</span><span>
</span><span id="line-16"></span><span class="hs-pragma">{-# LANGUAGE FlexibleContexts #-}</span><span>
</span><span id="line-17"></span><span class="hs-pragma">{-# LANGUAGE OverloadedStrings #-}</span><span>
</span><span id="line-18"></span><span>
</span><span id="line-19"></span><span class="hs-keyword">module</span><span> </span><span class="hs-identifier">TensorFlow.NN</span><span>
</span><span id="line-20"></span><span> </span><span class="hs-special">(</span><span> </span><span class="annot"><a href="TensorFlow.NN.html#sigmoidCrossEntropyWithLogits"><span class="hs-identifier">sigmoidCrossEntropyWithLogits</span></a></span><span>
</span><span id="line-21"></span><span> </span><span class="hs-special">)</span><span> </span><span class="hs-keyword">where</span><span>
</span><span id="line-22"></span><span>
</span><span id="line-23"></span><span class="hs-keyword">import</span><span> </span><span class="annot"><span class="hs-identifier">Prelude</span></span><span> </span><span class="hs-keyword">hiding</span><span> </span><span class="hs-special">(</span><span> </span><span class="annot"><span class="hs-identifier">log</span></span><span>
</span><span id="line-24"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">exp</span></span><span>
</span><span id="line-25"></span><span> </span><span class="hs-special">)</span><span>
</span><span id="line-26"></span><span class="hs-keyword">import</span><span> </span><span class="annot"><span class="hs-identifier">TensorFlow.Build</span></span><span> </span><span class="hs-special">(</span><span> </span><span class="annot"><span class="hs-identifier">MonadBuild</span></span><span>
</span><span id="line-27"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">withNameScope</span></span><span>
</span><span id="line-28"></span><span> </span><span class="hs-special">)</span><span>
</span><span id="line-29"></span><span class="hs-keyword">import</span><span> </span><span class="annot"><span class="hs-identifier">TensorFlow.GenOps.Core</span></span><span> </span><span class="hs-special">(</span><span> </span><span class="annot"><span class="hs-identifier">greaterEqual</span></span><span>
</span><span id="line-30"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">select</span></span><span>
</span><span id="line-31"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">log</span></span><span>
</span><span id="line-32"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">exp</span></span><span>
</span><span id="line-33"></span><span> </span><span class="hs-special">)</span><span>
</span><span id="line-34"></span><span class="hs-keyword">import</span><span> </span><span class="annot"><span class="hs-identifier">TensorFlow.Tensor</span></span><span> </span><span class="hs-special">(</span><span> </span><span class="annot"><span class="hs-identifier">Tensor</span></span><span class="hs-special">(</span><span class="hs-glyph">..</span><span class="hs-special">)</span><span>
</span><span id="line-35"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">render</span></span><span>
</span><span id="line-36"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">Value</span></span><span>
</span><span id="line-37"></span><span> </span><span class="hs-special">)</span><span>
</span><span id="line-38"></span><span class="hs-keyword">import</span><span> </span><span class="annot"><span class="hs-identifier">TensorFlow.Types</span></span><span> </span><span class="hs-special">(</span><span> </span><span class="annot"><span class="hs-identifier">TensorType</span></span><span class="hs-special">(</span><span class="hs-glyph">..</span><span class="hs-special">)</span><span>
</span><span id="line-39"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">OneOf</span></span><span>
</span><span id="line-40"></span><span> </span><span class="hs-special">)</span><span>
</span><span id="line-41"></span><span class="hs-keyword">import</span><span> </span><span class="annot"><a href="TensorFlow.Ops.html"><span class="hs-identifier">TensorFlow.Ops</span></a></span><span> </span><span class="hs-special">(</span><span> </span><span class="annot"><span class="hs-identifier">zerosLike</span></span><span>
</span><span id="line-42"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">add</span></span><span>
</span><span id="line-43"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">mul</span></span><span>
</span><span id="line-44"></span><span> </span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier">neg</span></span><span>
</span><span id="line-45"></span><span> </span><span class="hs-special">)</span><span>
</span><span id="line-46"></span><span>
</span><span id="line-47"></span><span class="hs-comment">-- | Computes sigmoid cross entropy given `logits`.</span><span>
</span><span id="line-48"></span><span class="hs-comment">--</span><span>
</span><span id="line-49"></span><span class="hs-comment">-- Measures the probability error in discrete classification tasks in which each</span><span>
</span><span id="line-50"></span><span class="hs-comment">-- class is independent and not mutually exclusive. For instance, one could</span><span>
</span><span id="line-51"></span><span class="hs-comment">-- perform multilabel classification where a picture can contain both an elephant</span><span>
</span><span id="line-52"></span><span class="hs-comment">-- and a dog at the same time.</span><span>
</span><span id="line-53"></span><span class="hs-comment">--</span><span>
</span><span id="line-54"></span><span class="hs-comment">-- For brevity, let `x = logits`, `z = targets`. The logistic loss is</span><span>
</span><span id="line-55"></span><span class="hs-comment">--</span><span>
</span><span id="line-56"></span><span class="hs-comment">-- z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))</span><span>
</span><span id="line-57"></span><span class="hs-comment">-- = z * -log(1 / (1 + exp(-x))) + (1 - z) * -log(exp(-x) / (1 + exp(-x)))</span><span>
</span><span id="line-58"></span><span class="hs-comment">-- = z * log(1 + exp(-x)) + (1 - z) * (-log(exp(-x)) + log(1 + exp(-x)))</span><span>
</span><span id="line-59"></span><span class="hs-comment">-- = z * log(1 + exp(-x)) + (1 - z) * (x + log(1 + exp(-x))</span><span>
</span><span id="line-60"></span><span class="hs-comment">-- = (1 - z) * x + log(1 + exp(-x))</span><span>
</span><span id="line-61"></span><span class="hs-comment">-- = x - x * z + log(1 + exp(-x))</span><span>
</span><span id="line-62"></span><span class="hs-comment">--</span><span>
</span><span id="line-63"></span><span class="hs-comment">-- For x < 0, to avoid overflow in exp(-x), we reformulate the above</span><span>
</span><span id="line-64"></span><span class="hs-comment">--</span><span>
</span><span id="line-65"></span><span class="hs-comment">-- x - x * z + log(1 + exp(-x))</span><span>
</span><span id="line-66"></span><span class="hs-comment">-- = log(exp(x)) - x * z + log(1 + exp(-x))</span><span>
</span><span id="line-67"></span><span class="hs-comment">-- = - x * z + log(1 + exp(x))</span><span>
</span><span id="line-68"></span><span class="hs-comment">--</span><span>
</span><span id="line-69"></span><span class="hs-comment">-- Hence, to ensure stability and avoid overflow, the implementation uses this</span><span>
</span><span id="line-70"></span><span class="hs-comment">-- equivalent formulation</span><span>
</span><span id="line-71"></span><span class="hs-comment">--</span><span>
</span><span id="line-72"></span><span class="hs-comment">-- max(x, 0) - x * z + log(1 + exp(-abs(x)))</span><span>
</span><span id="line-73"></span><span class="hs-comment">--</span><span>
</span><span id="line-74"></span><span class="hs-comment">-- `logits` and `targets` must have the same type and shape.</span><span>
</span><span id="line-75"></span><span id="local-6989586621679156356"><span id="local-6989586621679156357"><span class="annot"><a href="TensorFlow.NN.html#sigmoidCrossEntropyWithLogits"><span class="hs-identifier hs-type">sigmoidCrossEntropyWithLogits</span></a></span><span>
</span><span id="line-76"></span><span> </span><span class="hs-glyph">::</span><span> </span><span class="hs-special">(</span><span class="annot"><span class="hs-identifier hs-type">MonadBuild</span></span><span> </span><span class="annot"><a href="#local-6989586621679156357"><span class="hs-identifier hs-type">m</span></a></span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier hs-type">OneOf</span></span><span> </span><span class="hs-special">'</span><span class="hs-special">[</span><span class="annot"><span class="hs-identifier hs-type">Float</span></span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier hs-type">Double</span></span><span class="hs-special">]</span><span> </span><span class="annot"><a href="#local-6989586621679156356"><span class="hs-identifier hs-type">a</span></a></span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier hs-type">TensorType</span></span><span> </span><span class="annot"><a href="#local-6989586621679156356"><span class="hs-identifier hs-type">a</span></a></span><span class="hs-special">,</span><span> </span><span class="annot"><span class="hs-identifier hs-type">Num</span></span><span> </span><span class="annot"><a href="#local-6989586621679156356"><span class="hs-identifier hs-type">a</span></a></span><span class="hs-special">)</span><span>
</span><span id="line-77"></span><span> </span><span class="hs-glyph">=></span><span> </span><span class="annot"><span class="hs-identifier hs-type">Tensor</span></span><span> </span><span class="annot"><span class="hs-identifier hs-type">Value</span></span><span> </span><span class="annot"><a href="#local-6989586621679156356"><span class="hs-identifier hs-type">a</span></a></span><span> </span><span class="hs-comment">-- ^ __logits__</span><span>
</span><span id="line-78"></span><span> </span><span class="hs-glyph">-></span><span> </span><span class="annot"><span class="hs-identifier hs-type">Tensor</span></span><span> </span><span class="annot"><span class="hs-identifier hs-type">Value</span></span><span> </span><span class="annot"><a href="#local-6989586621679156356"><span class="hs-identifier hs-type">a</span></a></span><span> </span><span class="hs-comment">-- ^ __targets__</span><span>
</span><span id="line-79"></span><span> </span><span class="hs-glyph">-></span><span> </span><span class="annot"><a href="#local-6989586621679156357"><span class="hs-identifier hs-type">m</span></a></span><span> </span><span class="hs-special">(</span><span class="annot"><span class="hs-identifier hs-type">Tensor</span></span><span> </span><span class="annot"><span class="hs-identifier hs-type">Value</span></span><span> </span><span class="annot"><a href="#local-6989586621679156356"><span class="hs-identifier hs-type">a</span></a></span><span class="hs-special">)</span></span></span><span>
</span><span id="line-80"></span><span id="sigmoidCrossEntropyWithLogits"><span class="annot"><span class="annottext">sigmoidCrossEntropyWithLogits :: Tensor Value a -> Tensor Value a -> m (Tensor Value a)
</span><a href="TensorFlow.NN.html#sigmoidCrossEntropyWithLogits"><span class="hs-identifier hs-var hs-var">sigmoidCrossEntropyWithLogits</span></a></span></span><span> </span><span id="local-6989586621679156355"><span class="annot"><span class="annottext">logits :: Tensor Value a
</span><a href="#local-6989586621679156355"><span class="hs-identifier hs-var">logits</span></a></span></span><span> </span><span id="local-6989586621679156354"><span class="annot"><span class="annottext">targets :: Tensor Value a
</span><a href="#local-6989586621679156354"><span class="hs-identifier hs-var">targets</span></a></span></span><span> </span><span class="hs-glyph">=</span><span> </span><span class="hs-keyword">do</span><span>
</span><span id="line-81"></span><span> </span><span class="hs-keyword">let</span><span> </span><span id="local-6989586621679156353"><span class="annot"><span class="annottext">zeros :: Tensor Build a
</span><a href="#local-6989586621679156353"><span class="hs-identifier hs-var hs-var">zeros</span></a></span></span><span> </span><span class="hs-glyph">=</span><span> </span><span class="annot"><span class="annottext">Tensor Value a -> Tensor Build a
forall (v'1 :: * -> *) t.
TensorType t =>
Tensor v'1 t -> Tensor Build t
</span><span class="hs-identifier hs-var">zerosLike</span></span><span> </span><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156355"><span class="hs-identifier hs-var">logits</span></a></span><span>
</span><span id="line-82"></span><span> </span><span id="local-6989586621679156352"><span class="annot"><span class="annottext">cond :: Tensor Build Bool
</span><a href="#local-6989586621679156352"><span class="hs-identifier hs-var hs-var">cond</span></a></span></span><span> </span><span class="hs-glyph">=</span><span> </span><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156355"><span class="hs-identifier hs-var">logits</span></a></span><span> </span><span class="annot"><span class="annottext">Tensor Value a -> Tensor Build a -> Tensor Build Bool
forall (v'1 :: * -> *) (v'2 :: * -> *) t.
OneOf
'[Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8, Double,
Float]
t =>
Tensor v'1 t -> Tensor v'2 t -> Tensor Build Bool
</span><span class="hs-operator hs-var">`greaterEqual`</span></span><span> </span><span class="annot"><span class="annottext">Tensor Build a
</span><a href="#local-6989586621679156353"><span class="hs-identifier hs-var">zeros</span></a></span><span>
</span><span id="line-83"></span><span> </span><span id="local-6989586621679156351"><span class="annot"><span class="annottext">relu_logits :: Tensor Build a
</span><a href="#local-6989586621679156351"><span class="hs-identifier hs-var hs-var">relu_logits</span></a></span></span><span> </span><span class="hs-glyph">=</span><span> </span><span class="annot"><span class="annottext">Tensor Build Bool
-> Tensor Value a -> Tensor Build a -> Tensor Build a
forall (v'1 :: * -> *) (v'2 :: * -> *) (v'3 :: * -> *) t.
TensorType t =>
Tensor v'1 Bool -> Tensor v'2 t -> Tensor v'3 t -> Tensor Build t
</span><span class="hs-identifier hs-var">select</span></span><span> </span><span class="annot"><span class="annottext">Tensor Build Bool
</span><a href="#local-6989586621679156352"><span class="hs-identifier hs-var">cond</span></a></span><span> </span><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156355"><span class="hs-identifier hs-var">logits</span></a></span><span> </span><span class="annot"><span class="annottext">Tensor Build a
</span><a href="#local-6989586621679156353"><span class="hs-identifier hs-var">zeros</span></a></span><span>
</span><span id="line-84"></span><span> </span><span id="local-6989586621679156350"><span class="annot"><span class="annottext">neg_abs_logits :: Tensor Build a
</span><a href="#local-6989586621679156350"><span class="hs-identifier hs-var hs-var">neg_abs_logits</span></a></span></span><span> </span><span class="hs-glyph">=</span><span> </span><span class="annot"><span class="annottext">Tensor Build Bool
-> Tensor Build a -> Tensor Value a -> Tensor Build a
forall (v'1 :: * -> *) (v'2 :: * -> *) (v'3 :: * -> *) t.
TensorType t =>
Tensor v'1 Bool -> Tensor v'2 t -> Tensor v'3 t -> Tensor Build t
</span><span class="hs-identifier hs-var">select</span></span><span> </span><span class="annot"><span class="annottext">Tensor Build Bool
</span><a href="#local-6989586621679156352"><span class="hs-identifier hs-var">cond</span></a></span><span> </span><span class="hs-special">(</span><span class="annot"><span class="annottext">Tensor Value a -> Tensor Build a
forall (v'1 :: * -> *) t.
OneOf
'[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16,
Double, Float]
t =>
Tensor v'1 t -> Tensor Build t
</span><span class="hs-identifier hs-var">neg</span></span><span> </span><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156355"><span class="hs-identifier hs-var">logits</span></a></span><span class="hs-special">)</span><span> </span><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156355"><span class="hs-identifier hs-var">logits</span></a></span><span>
</span><span id="line-85"></span><span> </span><span class="annot"><span class="annottext">Text -> m (Tensor Value a) -> m (Tensor Value a)
forall (m :: * -> *) a. MonadBuild m => Text -> m a -> m a
</span><span class="hs-identifier hs-var">withNameScope</span></span><span> </span><span class="annot"><span class="hs-string">"logistic_loss"</span></span><span> </span><span class="annot"><span class="annottext">(m (Tensor Value a) -> m (Tensor Value a))
-> m (Tensor Value a) -> m (Tensor Value a)
forall a b. (a -> b) -> a -> b
</span><span class="hs-operator hs-var">$</span></span><span> </span><span class="hs-keyword">do</span><span>
</span><span id="line-86"></span><span> </span><span id="local-6989586621679156349"><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156349"><span class="hs-identifier hs-var">left</span></a></span></span><span> </span><span class="hs-glyph"><-</span><span> </span><span class="annot"><span class="annottext">Tensor Build a -> m (Tensor Value a)
forall (m :: * -> *) a.
MonadBuild m =>
Tensor Build a -> m (Tensor Value a)
</span><span class="hs-identifier hs-var">render</span></span><span> </span><span class="annot"><span class="annottext">(Tensor Build a -> m (Tensor Value a))
-> Tensor Build a -> m (Tensor Value a)
forall a b. (a -> b) -> a -> b
</span><span class="hs-operator hs-var">$</span></span><span> </span><span class="annot"><span class="annottext">Tensor Build a
</span><a href="#local-6989586621679156351"><span class="hs-identifier hs-var">relu_logits</span></a></span><span> </span><span class="annot"><span class="annottext">Tensor Build a -> Tensor Build a -> Tensor Build a
forall a. Num a => a -> a -> a
</span><span class="hs-glyph hs-var">-</span></span><span> </span><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156355"><span class="hs-identifier hs-var">logits</span></a></span><span> </span><span class="annot"><span class="annottext">Tensor Value a -> Tensor Value a -> Tensor Build a
forall (v'1 :: * -> *) (v'2 :: * -> *) t.
OneOf
'[Complex Double, Complex Float, Int16, Int32, Int64, Int8, Word16,
Word8, Double, Float]
t =>
Tensor v'1 t -> Tensor v'2 t -> Tensor Build t
</span><span class="hs-operator hs-var">`mul`</span></span><span> </span><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156354"><span class="hs-identifier hs-var">targets</span></a></span><span>
</span><span id="line-87"></span><span> </span><span id="local-6989586621679156348"><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156348"><span class="hs-identifier hs-var">right</span></a></span></span><span> </span><span class="hs-glyph"><-</span><span> </span><span class="annot"><span class="annottext">Tensor Build a -> m (Tensor Value a)
forall (m :: * -> *) a.
MonadBuild m =>
Tensor Build a -> m (Tensor Value a)
</span><span class="hs-identifier hs-var">render</span></span><span> </span><span class="annot"><span class="annottext">(Tensor Build a -> m (Tensor Value a))
-> Tensor Build a -> m (Tensor Value a)
forall a b. (a -> b) -> a -> b
</span><span class="hs-operator hs-var">$</span></span><span> </span><span class="annot"><span class="annottext">Tensor Build a -> Tensor Build a
forall (v'1 :: * -> *) t.
OneOf '[Complex Double, Complex Float, Word16, Double, Float] t =>
Tensor v'1 t -> Tensor Build t
</span><span class="hs-identifier hs-var">log</span></span><span> </span><span class="hs-special">(</span><span class="annot"><span class="hs-number">1</span></span><span> </span><span class="annot"><span class="annottext">Tensor Build a -> Tensor Build a -> Tensor Build a
forall a. Num a => a -> a -> a
</span><span class="hs-operator hs-var">+</span></span><span> </span><span class="annot"><span class="annottext">Tensor Build a -> Tensor Build a
forall (v'1 :: * -> *) t.
OneOf '[Complex Double, Complex Float, Word16, Double, Float] t =>
Tensor v'1 t -> Tensor Build t
</span><span class="hs-identifier hs-var">exp</span></span><span> </span><span class="annot"><span class="annottext">Tensor Build a
</span><a href="#local-6989586621679156350"><span class="hs-identifier hs-var">neg_abs_logits</span></a></span><span class="hs-special">)</span><span>
</span><span id="line-88"></span><span> </span><span class="annot"><span class="annottext">Text -> m (Tensor Value a) -> m (Tensor Value a)
forall (m :: * -> *) a. MonadBuild m => Text -> m a -> m a
</span><span class="hs-identifier hs-var">withNameScope</span></span><span> </span><span class="annot"><span class="hs-string">"sigmoid_add"</span></span><span> </span><span class="annot"><span class="annottext">(m (Tensor Value a) -> m (Tensor Value a))
-> m (Tensor Value a) -> m (Tensor Value a)
forall a b. (a -> b) -> a -> b
</span><span class="hs-operator hs-var">$</span></span><span> </span><span class="annot"><span class="annottext">Tensor Build a -> m (Tensor Value a)
forall (m :: * -> *) a.
MonadBuild m =>
Tensor Build a -> m (Tensor Value a)
</span><span class="hs-identifier hs-var">render</span></span><span> </span><span class="annot"><span class="annottext">(Tensor Build a -> m (Tensor Value a))
-> Tensor Build a -> m (Tensor Value a)
forall a b. (a -> b) -> a -> b
</span><span class="hs-operator hs-var">$</span></span><span> </span><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156349"><span class="hs-identifier hs-var">left</span></a></span><span> </span><span class="annot"><span class="annottext">Tensor Value a -> Tensor Value a -> Tensor Build a
forall (v'1 :: * -> *) (v'2 :: * -> *) t.
OneOf
'[Complex Double, Complex Float, ByteString, Int16, Int32, Int64,
Int8, Word16, Word8, Double, Float]
t =>
Tensor v'1 t -> Tensor v'2 t -> Tensor Build t
</span><span class="hs-operator hs-var">`add`</span></span><span> </span><span class="annot"><span class="annottext">Tensor Value a
</span><a href="#local-6989586621679156348"><span class="hs-identifier hs-var">right</span></a></span><span>
</span><span id="line-89"></span></pre></body></html>