experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Splitting out common_shape_fns.cc:

Browse Source 
* Shape functions under shape_inference:: namespace stay in common_shape_fns.cc.
* Other functions are moved to kernel_shape_util.h.
Also, I removed common_shape_fns.h include in ops_util.h since it is not used in ops_util and only by files that include ops_util.h.

PiperOrigin-RevId: 298692539
Change-Id: I79df418a377d4eaed67aeec6f3736acb9d5b111d
This commit is contained in:
Anna R 2020-03-03 14:17:57 -08:00 committed by TensorFlower Gardener
parent ddabed4285
commit 8f7e34982d
34 changed files with 341 additions and 253 deletions

2
tensorflow/compiler/mlir/xla/transforms/legalize_tf.cc
View File

@ -46,7 +46,7 @@ limitations under the License.
#include "tensorflow/compiler/mlir/xla/transforms/passes.h"
#include "tensorflow/compiler/xla/client/padding.h"
#include "tensorflow/compiler/xla/xla_data.pb.h"
#include "tensorflow/core/framework/common_shape_fns.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/kernels/conv_grad_shape_utils.h"
#include "tensorflow/core/util/padding.h"
#include "tensorflow/core/util/tensor_format.h"

2
tensorflow/compiler/tf2xla/kernels/conv_op_helpers.cc
View File

@ -29,10 +29,10 @@ limitations under the License.
#include "tensorflow/compiler/xla/literal_util.h"
#include "tensorflow/compiler/xla/util.h"
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/ops_util.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/tensor_slice.h"

1
tensorflow/compiler/tf2xla/kernels/extract_image_patches_op.cc
View File

@ -23,6 +23,7 @@ limitations under the License.
#include "tensorflow/compiler/xla/client/xla_builder.h"
#include "tensorflow/compiler/xla/shape_util.h"
#include "tensorflow/compiler/xla/util.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/util/tensor_format.h"

2
tensorflow/core/BUILD
View File

@ -469,6 +469,7 @@ tf_cuda_library(
"//tensorflow/core/framework:graph_to_functiondef.h",
"//tensorflow/core/framework:kernel_def_builder.h",
"//tensorflow/core/framework:kernel_def_util.h",
"//tensorflow/core/framework:kernel_shape_util.h",
"//tensorflow/core/framework:log_memory.h",
"//tensorflow/core/framework:logging.h",
"//tensorflow/core/framework:lookup_interface.h",
@ -2351,6 +2352,7 @@ tf_cuda_library(
"//tensorflow/core/framework:attr_value_util",
"//tensorflow/core/framework:bfloat16",
"//tensorflow/core/framework:common_shape_fns",
"//tensorflow/core/framework:kernel_shape_util",
"//tensorflow/core/framework:node_def_util",
"//tensorflow/core/framework:node_properties",
"//tensorflow/core/framework:numeric_types",

17
tensorflow/core/framework/BUILD
View File

@ -129,6 +129,7 @@ exports_files(
[
"attr_value_util.h",
"common_shape_fns.h",
"kernel_shape_util.h",
"node_def_util.h",
"node_properties.h",
"op.h",
@ -166,6 +167,7 @@ filegroup(
"graph_to_functiondef.h",
"kernel_def_builder.h",
"kernel_def_util.h",
"kernel_shape_util.h",
"local_rendezvous.h",
"log_memory.h",
"logging.h",
@ -269,6 +271,8 @@ filegroup(
"bfloat16.h",
"bounds_check.h",
"cpu_allocator_impl.cc",
"kernel_shape_util.cc",
"kernel_shape_util.h",
"log_memory.cc",
"log_memory.h",
"numeric_types.h",
@ -775,6 +779,19 @@ cc_library(
],
)
cc_library(
name = "kernel_shape_util",
srcs = ["kernel_shape_util.cc"],
hdrs = ["kernel_shape_util.h"],
deps = [
":tensor",
":tensor_shape",
"//tensorflow/core/lib/core:errors",
"//tensorflow/core/platform:status",
"//tensorflow/core/util:padding",
],
)
cc_library(
name = "common_shape_fns",
srcs = ["common_shape_fns.cc"],

112
tensorflow/core/framework/common_shape_fns.cc
View File

@ -27,118 +27,6 @@ limitations under the License.
namespace tensorflow {
Status GetWindowedOutputSizeVerboseV2(int64 input_size, int64 filter_size,
int64 dilation_rate, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_before,
int64* padding_after) {
if (stride <= 0) {
return errors::InvalidArgument("Stride must be > 0, but got ", stride);
}
if (dilation_rate < 1) {
return errors::InvalidArgument("Dilation rate must be >= 1, but got ",
dilation_rate);
}
// See also the parallel implementation in GetWindowedOutputSizeFromDimsV2.
int64 effective_filter_size = (filter_size - 1) * dilation_rate + 1;
switch (padding_type) {
case Padding::VALID:
*output_size = (input_size - effective_filter_size + stride) / stride;
*padding_before = *padding_after = 0;
break;
case Padding::EXPLICIT:
*output_size = (input_size + *padding_before + *padding_after -
effective_filter_size + stride) /
stride;
break;
case Padding::SAME:
*output_size = (input_size + stride - 1) / stride;
const int64 padding_needed =
std::max(int64{0}, (*output_size - 1) * stride +
effective_filter_size - input_size);
// For odd values of total padding, add more padding at the 'right'
// side of the given dimension.
*padding_before = padding_needed / 2;
*padding_after = padding_needed - *padding_before;
break;
}
if (*output_size < 0) {
return errors::InvalidArgument(
"Computed output size would be negative: ", *output_size,
" [input_size: ", input_size,
", effective_filter_size: ", effective_filter_size,
", stride: ", stride, "]");
}
return Status::OK();
}
Status GetWindowedOutputSizeVerbose(int64 input_size, int64 filter_size,
int64 stride, Padding padding_type,
int64* output_size, int64* padding_before,
int64* padding_after) {
return GetWindowedOutputSizeVerboseV2(input_size, filter_size,
/*dilation_rate=*/1, stride,
padding_type, output_size,
padding_before, padding_after);
}
Status GetWindowedOutputSize(int64 input_size, int64 filter_size, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_size) {
if (padding_type == Padding::EXPLICIT) {
return errors::Internal(
"GetWindowedOutputSize does not handle EXPLICIT padding; call "
"GetWindowedOutputSizeVerbose instead");
}
int64 padding_after_unused;
return GetWindowedOutputSizeVerbose(input_size, filter_size, stride,
padding_type, output_size, padding_size,
&padding_after_unused);
}
Status GetWindowedOutputSizeV2(int64 input_size, int64 filter_size,
int64 dilation_rate, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_size) {
if (padding_type == Padding::EXPLICIT) {
return errors::Internal(
"GetWindowedOutputSizeV2 does not handle EXPLICIT padding; call "
"GetWindowedOutputSizeVerboseV2 instead");
}
int64 padding_after_unused;
return GetWindowedOutputSizeVerboseV2(input_size, filter_size, dilation_rate,
stride, padding_type, output_size,
padding_size, &padding_after_unused);
}
Status Get3dOutputSize(const std::array<int64, 3>& input,
const std::array<int64, 3>& window,
const std::array<int64, 3>& strides,
Padding padding_type, std::array<int64, 3>* output_ptr,
std::array<int64, 3>* padding_ptr) {
for (size_t i = 0; i < input.size(); ++i) {
TF_RETURN_IF_ERROR(GetWindowedOutputSize(input[i], window[i], strides[i],
padding_type, &(*output_ptr)[i],
&(*padding_ptr)[i]));
}
return Status::OK();
}
Status Get3dOutputSizeV2(const std::array<int64, 3>& input,
const std::array<int64, 3>& window,
const std::array<int64, 3>& dilations,
const std::array<int64, 3>& strides,
Padding padding_type, std::array<int64, 3>* output_ptr,
std::array<int64, 3>* padding_ptr) {
for (size_t i = 0; i < input.size(); ++i) {
TF_RETURN_IF_ERROR(GetWindowedOutputSizeV2(
input[i], window[i], dilations[i], strides[i], padding_type,
&(*output_ptr)[i], &(*padding_ptr)[i]));
}
return Status::OK();
}
namespace shape_inference {
// The V2 version computes windowed output size with arbitrary dilation_rate,

123
tensorflow/core/framework/common_shape_fns.h
View File

@ -23,129 +23,6 @@ limitations under the License.
namespace tensorflow {
// GetWindowedOutputSize(): Given an input tensor, kernel, stride and padding
// type, the function computes the output and padding dimensions.
//
// For example, ignoring batches or multiple features, a 1D convolution
// takes as input a 1D tensor of shape (H), and convolves it with a filter of
// shape (K).
//
// It also takes in a few additional parameters:
//
// Stride (S): the stride with which we apply the filters. This is the offset
// between locations where we apply the filters. A larger stride
// means that the output will be spatially smaller.
//
// Padding (P): the padding we apply to the input tensor along each
// dimension. This is usually used to make sure that the spatial dimensions
// do not shrink when we progress with convolutions. This function supports two
// types of padding.
// SAME: the pad value is computed so that the output will have size H/S.
// VALID: no padding is carried out.
// If you want to use EXPLICIT padding, GetWindowedOutputSizeVerbose must be
// called instead. Note the padded area is zero-filled.
//
// The output dimensions for convolution and many other operations, when given
// all the parameters above, are as follows:
// - When Padding = SAME: the output size is (H'), where
// H' = ceil(float(H) / float(S))
// where ceil is the ceiling function. The number of padded cells
// is computed as:
// Pc = ((H' - 1) * S + K - H) / 2
// When the stride is 1, the expression simplifies to
// H' = H, Pc = (K-1)/2.
// This is where SAME comes from - the output has the same size as the input
// has.
//
// - When Padding = VALID: the output size is computed as
// H' = ceil(float(H - K + 1) / float(S))
// and the number of padded cells is always zero.
// When the stride is 1, the expression simplifies to
// H' = H-K+1.
//
// For convolution, mathematically, the output value at location (r')
// is the inner product of two vectors: the chunk of input at
// ((r'*S-Pr) : (r'*S-Pr+K)),
// and the filter.
//
// For 2D and 3D convolutions, the spatial dimensions are orthogonal, so the
// size and padding of each spatial dimension can be computed by calling
// GetWindowedOutputSize separately for each dimension.
//
Status GetWindowedOutputSize(int64 input_size, int64 filter_size, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_size);
// The V2 version computes the same outputs with arbitrary dilation_rate.
// The output dimensions are computed as follows:
// - When adding dilation_rate (D), we compute an effective filter size (K'):
// K' = (K - 1) * D + 1
// - When Padding = SAME: the output size is (H'), where
// H' = ceil(float(H) / float(S))
// where ceil is the ceiling function. The number of padded cells
// is computed as:
// Pc = ((H' - 1) * S + K' - H) / 2
// When the stride is 1, the expression simplifies to
// H' = H, Pc = (K'-1)/2.
// This is where SAME comes from - the output has the same size as the input
// has.
//
// - When Padding = VALID: the output size is computed as
// H' = ceil(float(H - K' + 1) / float(S))
// and the number of padded cells is always zero.
// When the stride is 1, the expression simplifies to
// H' = H-K'+1.
//
// If you want to use EXPLICIT padding, GetWindowedOutputSizeVerboseV2 must be
// called instead
//
// TODO(b/67112639): Merge V2 versions and the original versions eventually.
Status GetWindowedOutputSizeV2(int64 input_size, int64 filter_size,
int64 dilation_rate, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_size);
// Returns the same output dimensions as in GetWindowedOutputSize, but returns
// verbose padding dimensions (before/after), and EXPLICIT padding is supported.
// When padding_type is EXPLICIT, *padding_before and *padding_after must
// already point to initialized integers with the padding amounts. Otherwise,
// *padding_before and *padding_after are set by this function, and any
// excess padding (caused by an odd padding size value) is added to the
// 'padding_after' dimension.
Status GetWindowedOutputSizeVerbose(int64 input_size, int64 filter_size,
int64 stride, Padding padding_type,
int64* output_size, int64* padding_before,
int64* padding_after);
// The V2 version computes the same outputs with arbitrary dilation_rate. For
// detailed equations, refer to the comments for GetWindowedOutputSizeV2().
Status GetWindowedOutputSizeVerboseV2(int64 input_size, int64 filter_size,
int64 dilation_rate, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_before,
int64* padding_after);
// Given an input tensor, kernel, stride and padding type, populates the 3D size
// of the output tensor and padding to be applied to the input tensor at the
// lower end of every dimension. Use for 3D convolutions, where the input data
// is padded with zeros, as well as for 3D avg/max pooling, where the input data
// is padded with invalid values that are not considered for pooling. EXPLICIT
// padding is not supported.
Status Get3dOutputSize(const std::array<int64, 3>& input,
const std::array<int64, 3>& window,
const std::array<int64, 3>& strides,
Padding padding_type, std::array<int64, 3>* output_ptr,
std::array<int64, 3>* padding_ptr);
// The V2 version computes the same outputs with arbitrary dilation_rate. For
// detailed equations, refer to the comments for GetWindowedOutputSizeV2().
Status Get3dOutputSizeV2(const std::array<int64, 3>& input,
const std::array<int64, 3>& window,
const std::array<int64, 3>& dilations,
const std::array<int64, 3>& strides,
Padding padding_type, std::array<int64, 3>* output_ptr,
std::array<int64, 3>* padding_ptr);
namespace shape_inference {
// Like GetWindowedOutputSize, but deals with DimensionHandles. Does not support

131
tensorflow/core/framework/kernel_shape_util.cc Normal file
View File

@ -0,0 +1,131 @@
/* Copyright 2020 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.
==============================================================================*/
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/lib/core/errors.h"
namespace tensorflow {
Status GetWindowedOutputSizeVerboseV2(int64 input_size, int64 filter_size,
int64 dilation_rate, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_before,
int64* padding_after) {
if (stride <= 0) {
return errors::InvalidArgument("Stride must be > 0, but got ", stride);
}
if (dilation_rate < 1) {
return errors::InvalidArgument("Dilation rate must be >= 1, but got ",
dilation_rate);
}
// See also the parallel implementation in GetWindowedOutputSizeFromDimsV2.
int64 effective_filter_size = (filter_size - 1) * dilation_rate + 1;
switch (padding_type) {
case Padding::VALID:
*output_size = (input_size - effective_filter_size + stride) / stride;
*padding_before = *padding_after = 0;
break;
case Padding::EXPLICIT:
*output_size = (input_size + *padding_before + *padding_after -
effective_filter_size + stride) /
stride;
break;
case Padding::SAME:
*output_size = (input_size + stride - 1) / stride;
const int64 padding_needed =
std::max(int64{0}, (*output_size - 1) * stride +
effective_filter_size - input_size);
// For odd values of total padding, add more padding at the 'right'
// side of the given dimension.
*padding_before = padding_needed / 2;
*padding_after = padding_needed - *padding_before;
break;
}
if (*output_size < 0) {
return errors::InvalidArgument(
"Computed output size would be negative: ", *output_size,
" [input_size: ", input_size,
", effective_filter_size: ", effective_filter_size,
", stride: ", stride, "]");
}
return Status::OK();
}
Status GetWindowedOutputSizeVerbose(int64 input_size, int64 filter_size,
int64 stride, Padding padding_type,
int64* output_size, int64* padding_before,
int64* padding_after) {
return GetWindowedOutputSizeVerboseV2(input_size, filter_size,
/*dilation_rate=*/1, stride,
padding_type, output_size,
padding_before, padding_after);
}
Status GetWindowedOutputSize(int64 input_size, int64 filter_size, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_size) {
if (padding_type == Padding::EXPLICIT) {
return errors::Internal(
"GetWindowedOutputSize does not handle EXPLICIT padding; call "
"GetWindowedOutputSizeVerbose instead");
}
int64 padding_after_unused;
return GetWindowedOutputSizeVerbose(input_size, filter_size, stride,
padding_type, output_size, padding_size,
&padding_after_unused);
}
Status GetWindowedOutputSizeV2(int64 input_size, int64 filter_size,
int64 dilation_rate, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_size) {
if (padding_type == Padding::EXPLICIT) {
return errors::Internal(
"GetWindowedOutputSizeV2 does not handle EXPLICIT padding; call "
"GetWindowedOutputSizeVerboseV2 instead");
}
int64 padding_after_unused;
return GetWindowedOutputSizeVerboseV2(input_size, filter_size, dilation_rate,
stride, padding_type, output_size,
padding_size, &padding_after_unused);
}
Status Get3dOutputSize(const std::array<int64, 3>& input,
const std::array<int64, 3>& window,
const std::array<int64, 3>& strides,
Padding padding_type, std::array<int64, 3>* output_ptr,
std::array<int64, 3>* padding_ptr) {
for (size_t i = 0; i < input.size(); ++i) {
TF_RETURN_IF_ERROR(GetWindowedOutputSize(input[i], window[i], strides[i],
padding_type, &(*output_ptr)[i],
&(*padding_ptr)[i]));
}
return Status::OK();
}
Status Get3dOutputSizeV2(const std::array<int64, 3>& input,
const std::array<int64, 3>& window,
const std::array<int64, 3>& dilations,
const std::array<int64, 3>& strides,
Padding padding_type, std::array<int64, 3>* output_ptr,
std::array<int64, 3>* padding_ptr) {
for (size_t i = 0; i < input.size(); ++i) {
TF_RETURN_IF_ERROR(GetWindowedOutputSizeV2(
input[i], window[i], dilations[i], strides[i], padding_type,
&(*output_ptr)[i], &(*padding_ptr)[i]));
}
return Status::OK();
}
} // namespace tensorflow

149
tensorflow/core/framework/kernel_shape_util.h Normal file
View File

@ -0,0 +1,149 @@
/* Copyright 2020 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.
==============================================================================*/
#ifndef TENSORFLOW_CORE_FRAMEWORK_KERNEL_SHAPE_UTIL_H_
#define TENSORFLOW_CORE_FRAMEWORK_KERNEL_SHAPE_UTIL_H_
#include <array>
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/util/padding.h"
namespace tensorflow {
// GetWindowedOutputSize(): Given an input tensor, kernel, stride and padding
// type, the function computes the output and padding dimensions.
//
// For example, ignoring batches or multiple features, a 1D convolution
// takes as input a 1D tensor of shape (H), and convolves it with a filter of
// shape (K).
//
// It also takes in a few additional parameters:
//
// Stride (S): the stride with which we apply the filters. This is the offset
// between locations where we apply the filters. A larger stride
// means that the output will be spatially smaller.
//
// Padding (P): the padding we apply to the input tensor along each
// dimension. This is usually used to make sure that the spatial dimensions
// do not shrink when we progress with convolutions. This function supports two
// types of padding.
// SAME: the pad value is computed so that the output will have size H/S.
// VALID: no padding is carried out.
// If you want to use EXPLICIT padding, GetWindowedOutputSizeVerbose must be
// called instead. Note the padded area is zero-filled.
//
// The output dimensions for convolution and many other operations, when given
// all the parameters above, are as follows:
// - When Padding = SAME: the output size is (H'), where
// H' = ceil(float(H) / float(S))
// where ceil is the ceiling function. The number of padded cells
// is computed as:
// Pc = ((H' - 1) * S + K - H) / 2
// When the stride is 1, the expression simplifies to
// H' = H, Pc = (K-1)/2.
// This is where SAME comes from - the output has the same size as the input
// has.
//
// - When Padding = VALID: the output size is computed as
// H' = ceil(float(H - K + 1) / float(S))
// and the number of padded cells is always zero.
// When the stride is 1, the expression simplifies to
// H' = H-K+1.
//
// For convolution, mathematically, the output value at location (r')
// is the inner product of two vectors: the chunk of input at
// ((r'*S-Pr) : (r'*S-Pr+K)),
// and the filter.
//
// For 2D and 3D convolutions, the spatial dimensions are orthogonal, so the
// size and padding of each spatial dimension can be computed by calling
// GetWindowedOutputSize separately for each dimension.
//
Status GetWindowedOutputSize(int64 input_size, int64 filter_size, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_size);
// The V2 version computes the same outputs with arbitrary dilation_rate.
// The output dimensions are computed as follows:
// - When adding dilation_rate (D), we compute an effective filter size (K'):
// K' = (K - 1) * D + 1
// - When Padding = SAME: the output size is (H'), where
// H' = ceil(float(H) / float(S))
// where ceil is the ceiling function. The number of padded cells
// is computed as:
// Pc = ((H' - 1) * S + K' - H) / 2
// When the stride is 1, the expression simplifies to
// H' = H, Pc = (K'-1)/2.
// This is where SAME comes from - the output has the same size as the input
// has.
//
// - When Padding = VALID: the output size is computed as
// H' = ceil(float(H - K' + 1) / float(S))
// and the number of padded cells is always zero.
// When the stride is 1, the expression simplifies to
// H' = H-K'+1.
//
// If you want to use EXPLICIT padding, GetWindowedOutputSizeVerboseV2 must be
// called instead
//
// TODO(b/67112639): Merge V2 versions and the original versions eventually.
Status GetWindowedOutputSizeV2(int64 input_size, int64 filter_size,
int64 dilation_rate, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_size);
// Returns the same output dimensions as in GetWindowedOutputSize, but returns
// verbose padding dimensions (before/after), and EXPLICIT padding is supported.
// When padding_type is EXPLICIT, *padding_before and *padding_after must
// already point to initialized integers with the padding amounts. Otherwise,
// *padding_before and *padding_after are set by this function, and any
// excess padding (caused by an odd padding size value) is added to the
// 'padding_after' dimension.
Status GetWindowedOutputSizeVerbose(int64 input_size, int64 filter_size,
int64 stride, Padding padding_type,
int64* output_size, int64* padding_before,
int64* padding_after);
// The V2 version computes the same outputs with arbitrary dilation_rate. For
// detailed equations, refer to the comments for GetWindowedOutputSizeV2().
Status GetWindowedOutputSizeVerboseV2(int64 input_size, int64 filter_size,
int64 dilation_rate, int64 stride,
Padding padding_type, int64* output_size,
int64* padding_before,
int64* padding_after);
// Given an input tensor, kernel, stride and padding type, populates the 3D size
// of the output tensor and padding to be applied to the input tensor at the
// lower end of every dimension. Use for 3D convolutions, where the input data
// is padded with zeros, as well as for 3D avg/max pooling, where the input data
// is padded with invalid values that are not considered for pooling. EXPLICIT
// padding is not supported.
Status Get3dOutputSize(const std::array<int64, 3>& input,
const std::array<int64, 3>& window,
const std::array<int64, 3>& strides,
Padding padding_type, std::array<int64, 3>* output_ptr,
std::array<int64, 3>* padding_ptr);
// The V2 version computes the same outputs with arbitrary dilation_rate. For
// detailed equations, refer to the comments for GetWindowedOutputSizeV2().
Status Get3dOutputSizeV2(const std::array<int64, 3>& input,
const std::array<int64, 3>& window,
const std::array<int64, 3>& dilations,
const std::array<int64, 3>& strides,
Padding padding_type, std::array<int64, 3>* output_ptr,
std::array<int64, 3>* padding_ptr);
} // namespace tensorflow
#endif // TENSORFLOW_CORE_FRAMEWORK_KERNEL_SHAPE_UTIL_H_

1
tensorflow/core/framework/ops_util.h
View File

@ -21,7 +21,6 @@ limitations under the License.
#include <array>
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/framework/common_shape_fns.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/tensor_types.h"
#include "tensorflow/core/lib/core/status.h"

2
tensorflow/core/grappler/optimizers/layout_optimizer_test.cc
View File

@ -14,8 +14,10 @@ limitations under the License.
==============================================================================*/
#include "tensorflow/core/grappler/optimizers/layout_optimizer.h"
#include "tensorflow/cc/ops/standard_ops.h"
#include "tensorflow/core/framework/common_shape_fns.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/tensor_testutil.h"
#include "tensorflow/core/grappler/clusters/single_machine.h"

2
tensorflow/core/kernels/avgpooling_op.cc
View File

@ -20,7 +20,9 @@ limitations under the License.
#include "tensorflow/core/kernels/avgpooling_op.h"
#include <vector>
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"

2
tensorflow/core/kernels/conv_grad_filter_ops.cc
View File

@ -21,6 +21,7 @@ limitations under the License.
#include <algorithm>
#include <vector>
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"
@ -34,7 +35,6 @@ limitations under the License.
#ifdef TENSORFLOW_USE_LIBXSMM_CONVOLUTIONS
#include "tensorflow/core/kernels/xsmm_conv2d.h"
#endif
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/gtl/array_slice.h"
#include "tensorflow/core/platform/logging.h"

2
tensorflow/core/kernels/conv_grad_input_ops.cc
View File

@ -24,6 +24,7 @@ limitations under the License.
#include "absl/base/dynamic_annotations.h"
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"
@ -36,7 +37,6 @@ limitations under the License.
#ifdef TENSORFLOW_USE_LIBXSMM_CONVOLUTIONS
#include "tensorflow/core/kernels/xsmm_conv2d.h"
#endif
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/gtl/array_slice.h"
#include "tensorflow/core/platform/logging.h"

2
tensorflow/core/kernels/conv_grad_ops_3d.cc
View File

@ -16,6 +16,7 @@ limitations under the License.
#define USE_EIGEN_TENSOR
#define EIGEN_USE_THREADS
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"
@ -28,7 +29,6 @@ limitations under the License.
#include "tensorflow/core/kernels/conv_grad_ops.h"
#include "tensorflow/core/kernels/conv_grad_shape_utils.h"
#include "tensorflow/core/kernels/conv_ops_gpu.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/gtl/inlined_vector.h"
#include "tensorflow/core/util/padding.h"

1
tensorflow/core/kernels/conv_grad_shape_utils.cc
View File

@ -24,6 +24,7 @@ limitations under the License.
#include <vector>
#include "tensorflow/core/framework/common_shape_fns.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/register_types.h"
#include "tensorflow/core/framework/tensor.h"

1
tensorflow/core/kernels/conv_ops.cc
View File

@ -32,6 +32,7 @@ limitations under the License.
#include "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"

1
tensorflow/core/kernels/conv_ops_3d.cc
View File

@ -16,6 +16,7 @@ limitations under the License.
#define USE_EIGEN_TENSOR
#define EIGEN_USE_THREADS
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"

3
tensorflow/core/kernels/conv_ops_fused_image_transform.cc
View File

@ -21,8 +21,9 @@ limitations under the License.
#include <string>
#include <vector>
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/common_shape_fns.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"

4
tensorflow/core/kernels/conv_ops_using_gemm.cc
View File

@ -47,10 +47,12 @@ limitations under the License.
#define EIGEN_USE_THREADS
#include <string.h>
#include <map>
#include <vector>
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/common_shape_fns.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"

2
tensorflow/core/kernels/depthwise_conv_grad_op.cc
View File

@ -19,6 +19,7 @@ limitations under the License.
#include <cmath>
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"
@ -28,7 +29,6 @@ limitations under the License.
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/kernels/conv_grad_ops.h"
#include "tensorflow/core/kernels/depthwise_conv_op.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/types.h"

5
tensorflow/core/kernels/depthwise_conv_op.cc
View File

@ -15,11 +15,14 @@ limitations under the License.
#define EIGEN_USE_THREADS
#include "tensorflow/core/kernels/depthwise_conv_op.h"
#include <algorithm>
#include <cmath>
#include <type_traits>
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"
@ -28,8 +31,6 @@ limitations under the License.
#include "tensorflow/core/framework/tensor_types.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/kernels/conv_ops.h"
#include "tensorflow/core/kernels/depthwise_conv_op.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/types.h"

6
tensorflow/core/kernels/dilation_ops.cc
View File

@ -17,20 +17,20 @@ limitations under the License.
#define EIGEN_USE_THREADS
#include "tensorflow/core/kernels/dilation_ops.h"
#include <cfloat>
#include <vector>
#include "tensorflow/core/kernels/dilation_ops.h"
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/common_runtime/device.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#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/framework/tensor_slice.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/gtl/array_slice.h"
#include "tensorflow/core/util/padding.h"

3
tensorflow/core/kernels/extract_image_patches_op.cc
View File

@ -19,8 +19,11 @@ limitations under the License.
#define EIGEN_USE_THREADS
#include "tensorflow/core/kernels/extract_image_patches_op.h"
#include <vector>
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"

3
tensorflow/core/kernels/extract_volume_patches_op.cc
View File

@ -25,8 +25,11 @@ when rates are to be added.
#define EIGEN_USE_THREADS
#include "tensorflow/core/kernels/extract_volume_patches_op.h"
#include <vector>
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"

2
tensorflow/core/kernels/mkl_pooling_ops_common.cc
View File

@ -22,7 +22,7 @@ limitations under the License.
#include "tensorflow/core/common_runtime/device.h"
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/common_shape_fns.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
namespace tensorflow {
using mkldnn::prop_kind;

2
tensorflow/core/kernels/neon/neon_depthwise_conv_op.cc
View File

@ -20,6 +20,7 @@ limitations under the License.
#define GEMMLOWP_ALLOW_SLOW_SCALAR_FALLBACK
#include "public/gemmlowp.h"
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"
@ -28,7 +29,6 @@ limitations under the License.
#include "tensorflow/core/framework/tensor_types.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/kernels/neon/depthwiseconv_float.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/mem.h"

2
tensorflow/core/kernels/nn_ops_test.cc
View File

@ -35,6 +35,7 @@ limitations under the License.
#include "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/fake_input.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/node_def_builder.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/tensor.h"
@ -44,7 +45,6 @@ limitations under the License.
#include "tensorflow/core/graph/graph_constructor.h"
#include "tensorflow/core/graph/graph_def_builder.h"
#include "tensorflow/core/kernels/ops_testutil.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/lib/core/threadpool.h"
#include "tensorflow/core/platform/logging.h"

2
tensorflow/core/kernels/ops_util_test.cc
View File

@ -14,7 +14,9 @@ limitations under the License.
==============================================================================*/
#include "tensorflow/core/kernels/ops_util.h"
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/platform/test.h"

1
tensorflow/core/kernels/pooling_ops_3d.cc
View File

@ -20,6 +20,7 @@ limitations under the License.
#include "third_party/eigen3/Eigen/Core"
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/register_types.h"

1
tensorflow/core/kernels/pooling_ops_common.cc
View File

@ -18,6 +18,7 @@ limitations under the License.
#include <vector>
#include "tensorflow/core/common_runtime/device.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/register_types.h"
#include "tensorflow/core/framework/tensor.h"

2
tensorflow/core/kernels/quantized_conv_ops.cc
View File

@ -22,11 +22,11 @@ limitations under the License.
#define GEMMLOWP_ALLOW_SLOW_SCALAR_FALLBACK
#include "public/gemmlowp.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/kernels/conv_ops.h"
#include "tensorflow/core/kernels/meta_support.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/kernels/quantization_utils.h"
#include "tensorflow/core/kernels/reference_gemm.h"
#include "tensorflow/core/lib/core/errors.h"

1
tensorflow/core/ops/array_ops.cc
View File

@ -17,6 +17,7 @@ limitations under the License.
#include <ostream>
#include "tensorflow/core/framework/common_shape_fns.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/tensor.pb.h"

2
tensorflow/core/ops/nn_ops.cc
View File

@ -14,7 +14,9 @@ limitations under the License.
==============================================================================*/
#include <cmath>
#include "tensorflow/core/framework/common_shape_fns.h"
#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/framework/numeric_op.h"
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/shape_inference.h"