<commit_before>/* Copyright 2015 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

// See docs in ../ops/nn_ops.cc.

#define EIGEN_USE_THREADS

#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"

#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/kernels/xent_op.h"
#include "tensorflow/core/util/bcast.h"

namespace tensorflow {

typedef Eigen::ThreadPoolDevice CPUDevice;
typedef Eigen::GpuDevice GPUDevice;
#ifdef TENSORFLOW_USE_SYCL
typedef Eigen::SyclDevice SYCLDevice;
#endif  // TENSORFLOW_USE_SYCL

template <typename Device, typename T>
class SoftmaxXentWithLogitsOp : public OpKernel {
 public:
  explicit SoftmaxXentWithLogitsOp(OpKernelConstruction* context)
      : OpKernel(context) {}

  void Compute(OpKernelContext* context) override {
    const Tensor& logits_in = context->input(0);
    const Tensor& labels_in = context->input(1);

    TensorShape shape_in = logits_in.shape();

    BCast bcast(BCast::FromShape(logits_in.shape()),
                BCast::FromShape(labels_in.shape()));
    if (!logits_in.IsSameSize(labels_in)) {
      OP_REQUIRES(context, bcast.IsValid(),
                  errors::InvalidArgument(
                      "logits and labels must be broadcastable: logits_size=",
                      logits_in.shape().DebugString(),
                      " labels_size=", labels_in.shape().DebugString()));
      shape_in = BCast::ToShape(bcast.output_shape());
    }
    OP_REQUIRES(context, TensorShapeUtils::IsMatrix(shape_in),
                errors::InvalidArgument("logits and labels must be beither "
                                        "2-dimensional, or roadcasted to "
                                        "2-dimensional"));
<commit_msg>Fix typo in `SoftmaxXentWithLogitsOp`.<commit_after>/* Copyright 2015 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

// See docs in ../ops/nn_ops.cc.

#define EIGEN_USE_THREADS

#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"

#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/kernels/xent_op.h"
#include "tensorflow/core/util/bcast.h"

namespace tensorflow {

typedef Eigen::ThreadPoolDevice CPUDevice;
typedef Eigen::GpuDevice GPUDevice;
#ifdef TENSORFLOW_USE_SYCL
typedef Eigen::SyclDevice SYCLDevice;
#endif  // TENSORFLOW_USE_SYCL

template <typename Device, typename T>
class SoftmaxXentWithLogitsOp : public OpKernel {
 public:
  explicit SoftmaxXentWithLogitsOp(OpKernelConstruction* context)
      : OpKernel(context) {}

  void Compute(OpKernelContext* context) override {
    const Tensor& logits_in = context->input(0);
    const Tensor& labels_in = context->input(1);

    TensorShape shape_in = logits_in.shape();

    BCast bcast(BCast::FromShape(logits_in.shape()),
                BCast::FromShape(labels_in.shape()));
    if (!logits_in.IsSameSize(labels_in)) {
      OP_REQUIRES(context, bcast.IsValid(),
                  errors::InvalidArgument(
                      "logits and labels must be broadcastable: logits_size=",
                      logits_in.shape().DebugString(),
                      " labels_size=", labels_in.shape().DebugString()));
      shape_in = BCast::ToShape(bcast.output_shape());
    }
    OP_REQUIRES(context, TensorShapeUtils::IsMatrix(shape_in),
                errors::InvalidArgument("logits and labels must be either "
                                        "2-dimensional, or broadcasted to be "
                                        "2-dimensional"));

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