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// See docs in ../ops/array_ops.cc
#define EIGEN_USE_THREADS
#include <memory>
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/kernels/reverse_op.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/public/status.h"
#include "tensorflow/core/public/tensor.h"
#include "tensorflow/core/public/tensor_shape.h"
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
namespace tensorflow {
typedef Eigen::ThreadPoolDevice CPUDevice;
typedef Eigen::GpuDevice GPUDevice;
template <typename Device, typename T>
class ReverseOp : public OpKernel {
public:
explicit ReverseOp(OpKernelConstruction* context) : OpKernel(context) {}
void Compute(OpKernelContext* context) override {
const Tensor& input = context->input(0);
const Tensor& dims = context->input(1);
if (TensorShapeUtils::IsScalar(input.shape())) {
Tensor* output = nullptr;
OP_REQUIRES_OK(context,
context->allocate_output(0, input.shape(), &output));
output->scalar<T>() = input.scalar<T>();
} else {
const int input_dims = input.dims();
OP_REQUIRES(context, TensorShapeUtils::IsVector(dims.shape()),
errors::InvalidArgument("'dims' must be 1-dimension, not ",
dims.dims()));
OP_REQUIRES(context, input_dims == dims.dim_size(0),
errors::InvalidArgument(
"'dims' must have the same number of values as 'input' has "
"dimensions. 'input' has ", input_dims, "'dims' has ",
dims.dim_size(0), " values"));
OP_REQUIRES(context, input_dims <= 8, errors::Unimplemented(
"reverse is not implemented for tensors of rank > 8."));
Tensor* output = nullptr;
OP_REQUIRES_OK(context,
context->allocate_output(0, input.shape(), &output));
#define HANDLE_REVERSE(NDIMS) \
case NDIMS: \
functor::Reverse<Device, T, NDIMS>()( \
context->eigen_device<Device>(), input.tensor<T, NDIMS>(), \
dims.vec<bool>(), output->tensor<T, NDIMS>()); \
return;
switch (input_dims) {
HANDLE_REVERSE(0);
HANDLE_REVERSE(1);
HANDLE_REVERSE(2);
HANDLE_REVERSE(3);
HANDLE_REVERSE(4);
HANDLE_REVERSE(5);
HANDLE_REVERSE(6);
HANDLE_REVERSE(7);
HANDLE_REVERSE(8);
}
#undef HANDLE_REVERSE
}
}
};
#define REGISTER_KERNEL(T) \
REGISTER_KERNEL_BUILDER(Name("Reverse") \
.Device(DEVICE_CPU) \
.TypeConstraint<T>("T") \
.HostMemory("dims"), \
ReverseOp<CPUDevice, T>)
REGISTER_KERNEL(uint8);
REGISTER_KERNEL(int8);
REGISTER_KERNEL(int32);
REGISTER_KERNEL(bool);
REGISTER_KERNEL(float);
REGISTER_KERNEL(double);
#undef REGISTER_KERNEL
#if GOOGLE_CUDA
// Forward declarations of the function specializations for GPU (to prevent
// building the GPU versions here, they will be built compiling _gpu.cu.cc).
namespace functor {
#define DECLARE_GPU_SPEC_DIM(T, DIM) \
template <> \
void Reverse<GPUDevice, T, DIM>::operator()( \
const GPUDevice& d, typename TTypes<T, DIM>::ConstTensor input, \
typename TTypes<bool, 1>::ConstTensor dims, \
typename TTypes<T, DIM>::Tensor output); \
extern template struct Reverse<GPUDevice, T, DIM>;
#define DECLARE_GPU_SPEC(T) \
DECLARE_GPU_SPEC_DIM(T, 0) \
DECLARE_GPU_SPEC_DIM(T, 1) \
DECLARE_GPU_SPEC_DIM(T, 2) \
DECLARE_GPU_SPEC_DIM(T, 3) \
DECLARE_GPU_SPEC_DIM(T, 4) \
DECLARE_GPU_SPEC_DIM(T, 5) \
DECLARE_GPU_SPEC_DIM(T, 6) \
DECLARE_GPU_SPEC_DIM(T, 7) \
DECLARE_GPU_SPEC_DIM(T, 8)
DECLARE_GPU_SPEC(uint8);
DECLARE_GPU_SPEC(int8);
DECLARE_GPU_SPEC(int32);
DECLARE_GPU_SPEC(bool);
DECLARE_GPU_SPEC(float);
DECLARE_GPU_SPEC(double);
#undef DECLARE_GPU_SPEC
#undef DECLARE_GPU_SPEC_DIM
} // namespace functor
// Registration of the GPU implementations.
#define REGISTER_GPU_KERNEL(T) \
REGISTER_KERNEL_BUILDER(Name("Reverse") \
.Device(DEVICE_GPU) \
.TypeConstraint<T>("T") \
.HostMemory("dims"), \
ReverseOp<GPUDevice, T>)
REGISTER_GPU_KERNEL(uint8);
REGISTER_GPU_KERNEL(int8);
REGISTER_GPU_KERNEL(float);
REGISTER_GPU_KERNEL(double);
#undef REGISTER_GPU_KERNEL
#endif // GOOGLE_CUDA
} // namespace tensorflow
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