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clang-format

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This commit is contained in:
Hoeseong Kim 2018-09-15 12:46:58 +09:00
parent b3ec2caeee
commit 33f57bd131
4 changed files with 44 additions and 36 deletions
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50
tensorflow/core/kernels/extract_volume_patches_op.cc
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@ -13,8 +13,8 @@ See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
/*
See extract_image_patches_op* files and docs for extract_image_patches in
/*
See extract_image_patches_op* files and docs for extract_image_patches in
../ops/image_ops.cc.
Rates are not supported as of now, but the comments hint how to edit the code
@ -60,7 +60,7 @@ class ExtractVolumePatchesOp : public UnaryOp<T> {
: UnaryOp<T>(context) {
ParseAttributeVec5(context, "ksizes", &ksizes_);
ParseAttributeVec5(context, "strides", &strides_);
//ParseAttributeVec5(context, "rates", &rates_);
// ParseAttributeVec5(context, "rates", &rates_);
OP_REQUIRES_OK(context, context->GetAttr("padding", &padding_));
}
@ -88,18 +88,20 @@ class ExtractVolumePatchesOp : public UnaryOp<T> {
/*
// TODO(hsgkim): enable rates
// Rates are disabled as of now due to Eigen's definitions of extract_volume_patch
// functions; none of them accept rates as its argument and rates are fixed to
// (1, 1, 1, 1, 1). A workaround has to be found for this.
// Rates are disabled as of now due to Eigen's definitions of
// `extract_volume_patch` functions; none of them accept rates
// as its argument and rates are fixed to (1, 1, 1, 1, 1). A
// workaround has to be found for this.
// In order to enable rates, uncomment the following lines and use
// ksize_*_eff instead of ksize_* for the second argument of GetWindowedOutputSize
// calls.
// ksize_*_eff instead of ksize_* for the second argument of
// GetWindowedOutputSize calls.
const int rate_planes = rates_[1];
const int rate_rows = rates_[2];
const int rate_cols = rates_[3];
const int ksize_planes_eff = ksize_planes + (ksize_planes - 1) * (rate_planes - 1);
const int ksize_planes_eff = ksize_planes +
(ksize_planes - 1) * (rate_planes - 1);
const int ksize_rows_eff = ksize_rows + (ksize_rows - 1) * (rate_rows - 1);
const int ksize_cols_eff = ksize_cols + (ksize_cols - 1) * (rate_cols - 1);
*/
@ -116,8 +118,9 @@ class ExtractVolumePatchesOp : public UnaryOp<T> {
GetWindowedOutputSize(in_cols, ksize_cols, stride_cols,
padding_, &out_cols, &pad_cols));
const std::vector<int64> out_sizes = {batch, out_planes, out_rows, out_cols,
ksize_planes * ksize_rows * ksize_cols * depth};
const std::vector<int64> out_sizes = {
batch, out_planes, out_rows, out_cols,
ksize_planes * ksize_rows * ksize_cols * depth};
TensorShape out_shape(out_sizes);
Tensor* output = nullptr;
@ -129,9 +132,8 @@ class ExtractVolumePatchesOp : public UnaryOp<T> {
}
functor::ExtractVolumePatchesForward<Device, T>()(
context->eigen_device<Device>(), input.tensor<T, 5>(),
ksize_planes, ksize_rows, ksize_cols,
stride_planes, stride_rows, stride_cols,
context->eigen_device<Device>(), input.tensor<T, 5>(), ksize_planes,
ksize_rows, ksize_cols, stride_planes, stride_rows, stride_cols,
/* rate_planes, rate_rows, rate_cols, */
BrainPadding2EigenPadding(padding_), output->tensor<T, 5>());
}
@ -161,16 +163,18 @@ TF_CALL_REAL_NUMBER_TYPES(REGISTER);
// Forward declarations of the functor specializations for GPU.
namespace functor {
#define DECLARE_GPU_SPEC(T) \
template <> \
void ExtractVolumePatchesForward<GPUDevice, T>::operator()( \
const GPUDevice& d, typename TTypes<T, 5>::ConstTensor input, \
int patch_planes, int patch_rows, int patch_cols, \
int stride_planes, int stride_rows, int stride_cols, \
/* int rate_planes, int rate_rows, int rate_cols, */ \
const Eigen::PaddingType& padding, \
typename TTypes<T, 5>::Tensor output); \
// clang-format off
#define DECLARE_GPU_SPEC(T) \
template <> \
void ExtractVolumePatchesForward<GPUDevice, T>::operator()( \
const GPUDevice& d, typename TTypes<T, 5>::ConstTensor input, \
int patch_planes, int patch_rows, int patch_cols, \
int stride_planes, int stride_rows, int stride_cols, \
/* int rate_planes, int rate_rows, int rate_cols, */ \
const Eigen::PaddingType& padding, \
typename TTypes<T, 5>::Tensor output); \
extern template struct ExtractVolumePatchesForward<GPUDevice, T>;
// clang-format on
TF_CALL_GPU_NUMBER_TYPES(DECLARE_GPU_SPEC);

12
tensorflow/core/kernels/extract_volume_patches_op.h
View File

@ -16,10 +16,10 @@ limitations under the License.
#ifndef TENSORFLOW_KERNELS_EXTRACT_VOLUME_PATCHES_OP_H_
#define TENSORFLOW_KERNELS_EXTRACT_VOLUME_PATCHES_OP_H_
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/tensor_types.h"
#include "tensorflow/core/kernels/eigen_volume_patch.h"
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
namespace tensorflow {
namespace functor {
@ -27,7 +27,7 @@ namespace functor {
template <typename Device, typename T>
struct ExtractVolumePatchesForward {
void operator()(const Device& d, typename TTypes<T, 5>::ConstTensor input,
int patch_planes, int patch_rows, int patch_cols,
int patch_planes, int patch_rows, int patch_cols,
int stride_planes, int stride_rows, int stride_cols,
/* int rate_planes, int rate_rows, int rate_cols, */
const Eigen::PaddingType& padding,
@ -38,15 +38,15 @@ struct ExtractVolumePatchesForward {
output_32bit.device(d) =
To32Bit(input)
.extract_volume_patches(patch_cols, patch_rows, patch_planes,
stride_cols, stride_rows, stride_planes,
padding)
stride_cols, stride_rows, stride_planes,
padding)
.reshape(output_32bit.dimensions());
} else {
output.device(d) =
input
.extract_volume_patches(patch_cols, patch_rows, patch_planes,
stride_cols, stride_rows, stride_planes,
padding)
stride_cols, stride_rows, stride_planes,
padding)
.reshape(output.dimensions());
}
}

2
tensorflow/core/kernels/extract_volume_patches_op_gpu.cu.cc
View File

@ -17,8 +17,8 @@ limitations under the License.
#define EIGEN_USE_GPU
#include "tensorflow/core/framework/register_types.h"
#include "tensorflow/core/kernels/extract_volume_patches_op.h"
#include "tensorflow/core/framework/register_types.h"
namespace tensorflow {

16
tensorflow/core/ops/array_ops.cc
View File

@ -2609,7 +2609,8 @@ REGISTER_OP("ExtractVolumePatches")
int32 rate_rows = rates[2];
int32 rate_cols = rates[3];
int32 ksize_planes_eff = ksize_planes + (ksize_planes - 1) * (rate_planes - 1);
int32 ksize_planes_eff = ksize_planes +
(ksize_planes - 1) * (rate_planes - 1);
int32 ksize_rows_eff = ksize_rows + (ksize_rows - 1) * (rate_rows - 1);
int32 ksize_cols_eff = ksize_cols + (ksize_cols - 1) * (rate_cols - 1);
*/
@ -2619,10 +2620,12 @@ REGISTER_OP("ExtractVolumePatches")
DimensionHandle in_rows_dim = c->Dim(input_shape, 2);
DimensionHandle in_cols_dim = c->Dim(input_shape, 3);
DimensionHandle output_depth_dim;
TF_RETURN_IF_ERROR(c->Multiply(
c->Dim(input_shape, 4), ksize_planes * ksize_rows * ksize_cols, &output_depth_dim));
TF_RETURN_IF_ERROR(c->Multiply(c->Dim(input_shape, 4),
ksize_planes * ksize_rows * ksize_cols,
&output_depth_dim));
if (!c->ValueKnown(in_planes_dim) || !c->ValueKnown(in_rows_dim) || !c->ValueKnown(in_cols_dim)) {
if (!c->ValueKnown(in_planes_dim) || !c->ValueKnown(in_rows_dim) ||
!c->ValueKnown(in_cols_dim)) {
ShapeHandle output_shape =
c->MakeShape({batch_size_dim, InferenceContext::kUnknownDim,
InferenceContext::kUnknownDim, output_depth_dim});
@ -2647,8 +2650,9 @@ REGISTER_OP("ExtractVolumePatches")
TF_RETURN_IF_ERROR(GetWindowedOutputSizeVerbose(
in_cols, ksize_cols, stride_cols, padding, &output_cols,
&padding_before, &padding_after));
ShapeHandle output_shape = c->MakeShape(
{batch_size_dim, output_planes, output_rows, output_cols, output_depth_dim});
ShapeHandle output_shape =
c->MakeShape({batch_size_dim, output_planes, output_rows, output_cols,
output_depth_dim});
c->set_output(0, output_shape);
return Status::OK();
});