1/* Copyright 2015 The TensorFlow Authors. All Rights Reserved.
2
3Licensed under the Apache License, Version 2.0 (the "License");
4you may not use this file except in compliance with the License.
5You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9Unless required by applicable law or agreed to in writing, software
10distributed under the License is distributed on an "AS IS" BASIS,
11WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12See the License for the specific language governing permissions and
13limitations under the License.
14==============================================================================*/
15
16// See docs in ../ops/nn_ops.cc.
17
18#include "tensorflow/core/lib/strings/str_util.h"
19#define EIGEN_USE_THREADS
20
21#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
22#include "tensorflow/core/framework/op_kernel.h"
23#include "tensorflow/core/framework/register_types.h"
24#include "tensorflow/core/framework/tensor.h"
25#include "tensorflow/core/framework/tensor_shape.h"
26#include "tensorflow/core/kernels/softmax_op_functor.h"
27
28namespace tensorflow {
29
30typedef Eigen::ThreadPoolDevice CPUDevice;
31typedef Eigen::GpuDevice GPUDevice;
32
33// Partial specialization for a CPUDevice, that uses the Eigen implementation
34// from SoftmaxEigenImpl.
35namespace functor {
36template <typename Device, typename T>
37struct SoftmaxFunctorBase {
38 void operator()(const Device& d, typename TTypes<T>::ConstMatrix logits,
39 typename TTypes<T>::Matrix softmax, const bool log) {
40 SoftmaxEigenImpl<Device, T>::Compute(d, logits, softmax, log);
41 }
42};
43template <typename T>
44struct SoftmaxFunctor<CPUDevice, T> : SoftmaxFunctorBase<CPUDevice, T> {};
45
46} // namespace functor
47
48template <typename Device, typename T>
49class SoftmaxOp : public OpKernel {
50 public:
51 explicit SoftmaxOp(OpKernelConstruction* context) : OpKernel(context) {
52 log_ = absl::StartsWith(type_string(), "Log");
53 }
54
55 void Compute(OpKernelContext* context) override {
56 const Tensor& logits_in = context->input(0);
57 OP_REQUIRES(context, TensorShapeUtils::IsVectorOrHigher(logits_in.shape()),
58 errors::InvalidArgument("logits must have >= 1 dimension, got ",
59 logits_in.shape().DebugString()));
60 Tensor* softmax_out = nullptr;
61 OP_REQUIRES_OK(context, context->forward_input_or_allocate_output(
62 {0}, 0, logits_in.shape(), &softmax_out));
63 if (logits_in.NumElements() > 0) {
64 functor::SoftmaxFunctor<Device, T> functor;
65 functor(context->eigen_device<Device>(), logits_in.flat_inner_dims<T>(),
66 softmax_out->flat_inner_dims<T>(), log_);
67 }
68 }
69
70 private:
71 bool log_;
72};
73
74#define REGISTER_CPU(T) \
75 REGISTER_KERNEL_BUILDER( \
76 Name("Softmax").Device(DEVICE_CPU).TypeConstraint<T>("T"), \
77 SoftmaxOp<CPUDevice, T>);
78TF_CALL_FLOAT_TYPES(REGISTER_CPU);
79
80#undef REGISTER_CPU
81#define REGISTER_CPU(T) \
82 REGISTER_KERNEL_BUILDER( \
83 Name("LogSoftmax").Device(DEVICE_CPU).TypeConstraint<T>("T"), \
84 SoftmaxOp<CPUDevice, T>);
85TF_CALL_FLOAT_TYPES(REGISTER_CPU);
86
87#undef REGISTER_CPU
88
89} // namespace tensorflow
90