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未验证 提交 1aa67778 编写于 作者: A Aurelius84 提交者： GitHub
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[Phi] Migrate unfold_op into phi (#39778) 

* [Phi] Migrate unfold_op into phi

* fix im2col CPUContext template instantial

* fix unfold_op.h header include problem

* fix unittest

* fix PT->PD
上级 60fc555e
隐藏空白更改
内联 并排
Showing with 558 addition and 275 deletion
paddle/fluid/imperative/prepared_operator.h
浏览文件 @ 1aa67778
......@@ -442,7 +442,9 @@ void BuildDygraphPtenKernelContext(
vector_int_attr.end());
kernel_ctx->EmplaceBackAttr(vector_int64_attr);
}
// TODO(YuanRisheng) Need support vector<int64_t> attr
} else if (attr_defs[i].type_index ==
std::type_index(typeid(std::vector<int>))) {
kernel_ctx->EmplaceBackAttr(BOOST_GET_CONST(std::vector<int>, attr));
} else {
PADDLE_THROW(platform::errors::Unimplemented(
"Unsupported cast op attribute `%s` when construct "
......
paddle/fluid/operators/fold_op.cc
浏览文件 @ 1aa67778
......@@ -13,7 +13,6 @@
* limitations under the License. */
#include "paddle/fluid/operators/fold_op.h"
#include "paddle/fluid/operators/unfold_op.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math/im2col.cc
浏览文件 @ 1aa67778
......@@ -22,6 +22,10 @@ class CPUDeviceContext;
} // namespace platform
} // namespace paddle
namespace phi {
class CPUContext;
} // namespace phi
namespace paddle {
namespace operators {
namespace math {
......@@ -31,12 +35,12 @@ namespace math {
* col =
* [input_channels, filter_height, filter_width, output_height, output_width]
*/
template <class T>
class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
platform::CPUDeviceContext, T> {
template <class T, typename DeviceContext>
class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO, DeviceContext,
T> {
public:
void operator()(const platform::CPUDeviceContext& context,
const framework::Tensor& im, const std::vector<int>& dilation,
void operator()(const DeviceContext& context, const framework::Tensor& im,
const std::vector<int>& dilation,
const std::vector<int>& stride,
const std::vector<int>& padding, framework::Tensor* col,
const DataLayout data_layout) {
......@@ -73,12 +77,11 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
* col =
* [input_channels, filter_height, filter_width, output_height, output_width]
*/
template <class T>
class Col2ImFunctor<paddle::operators::math::ColFormat::kCFO,
platform::CPUDeviceContext, T> {
template <class T, typename DeviceContext>
class Col2ImFunctor<paddle::operators::math::ColFormat::kCFO, DeviceContext,
T> {
public:
void operator()(const platform::CPUDeviceContext& context,
const framework::Tensor& col,
void operator()(const DeviceContext& context, const framework::Tensor& col,
const std::vector<int>& dilation,
const std::vector<int>& stride,
const std::vector<int>& padding, framework::Tensor* im,
......@@ -155,22 +158,30 @@ template class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
platform::CPUDeviceContext, float>;
template class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
platform::CPUDeviceContext, double>;
template class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
phi::CPUContext, float>;
template class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
phi::CPUContext, double>;
template class Col2ImFunctor<paddle::operators::math::ColFormat::kCFO,
platform::CPUDeviceContext, float>;
template class Col2ImFunctor<paddle::operators::math::ColFormat::kCFO,
platform::CPUDeviceContext, double>;
template class Col2ImFunctor<paddle::operators::math::ColFormat::kCFO,
phi::CPUContext, float>;
template class Col2ImFunctor<paddle::operators::math::ColFormat::kCFO,
phi::CPUContext, double>;
/*
* im = [input_channels, input_height, input_width]
* col =
* [output_height, output_width, input_channels, filter_height, filter_width]
*/
template <class T>
class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
platform::CPUDeviceContext, T> {
template <class T, typename DeviceContext>
class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF, DeviceContext,
T> {
public:
void operator()(const platform::CPUDeviceContext& context,
const framework::Tensor& im, const std::vector<int>& dilation,
void operator()(const DeviceContext& context, const framework::Tensor& im,
const std::vector<int>& dilation,
const std::vector<int>& stride,
const std::vector<int>& padding, framework::Tensor* col,
const DataLayout data_layout) {
......@@ -235,12 +246,11 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
* col =
* [output_height, output_width, input_channels, filter_height, filter_width]
*/
template <class T>
class Col2ImFunctor<paddle::operators::math::ColFormat::kOCF,
platform::CPUDeviceContext, T> {
template <class T, typename DeviceContext>
class Col2ImFunctor<paddle::operators::math::ColFormat::kOCF, DeviceContext,
T> {
public:
void operator()(const platform::CPUDeviceContext& context,
const framework::Tensor& col,
void operator()(const DeviceContext& context, const framework::Tensor& col,
const std::vector<int>& dilation,
const std::vector<int>& stride,
const std::vector<int>& padding, framework::Tensor* im,
......@@ -316,11 +326,18 @@ template class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
platform::CPUDeviceContext, float>;
template class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
platform::CPUDeviceContext, double>;
template class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
phi::CPUContext, float>;
template class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
phi::CPUContext, double>;
template class Col2ImFunctor<paddle::operators::math::ColFormat::kOCF,
platform::CPUDeviceContext, float>;
template class Col2ImFunctor<paddle::operators::math::ColFormat::kOCF,
platform::CPUDeviceContext, double>;
template class Col2ImFunctor<paddle::operators::math::ColFormat::kOCF,
phi::CPUContext, float>;
template class Col2ImFunctor<paddle::operators::math::ColFormat::kOCF,
phi::CPUContext, double>;
} // namespace math
} // namespace operators
} // namespace paddle
paddle/fluid/operators/unfold_op.cc
浏览文件 @ 1aa67778
......@@ -12,7 +12,9 @@
* See the License for the specific language governing permissions and
* limitations under the License. */
#include "paddle/fluid/operators/unfold_op.h"
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/phi/infermeta/unary.h"
namespace paddle {
namespace operators {
......@@ -60,126 +62,6 @@ feature map, a series of such columns will be formed.
class UnfoldOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE_EQ(
ctx->HasInput("X"), true,
platform::errors::NotFound("Input(X) of UnfoldOp should not be null"));
PADDLE_ENFORCE_EQ(
ctx->HasOutput("Y"), true,
platform::errors::NotFound("Output(Y) of UnfoldOp should not be null"));
auto in_dims = ctx->GetInputDim("X");
std::vector<int> kernel_sizes =
ctx->Attrs().Get<std::vector<int>>("kernel_sizes");
std::vector<int> strides = ctx->Attrs().Get<std::vector<int>>("strides");
std::vector<int> paddings = ctx->Attrs().Get<std::vector<int>>("paddings");
std::vector<int> dilations =
ctx->Attrs().Get<std::vector<int>>("dilations");
// Only [N, C, H, W] input supported now
PADDLE_ENFORCE_EQ(
in_dims.size(), 4,
platform::errors::InvalidArgument(
"Input should be 4-D tensor of format [N, C, H, W], but get %u",
in_dims.size()));
PADDLE_ENFORCE_EQ(
in_dims.size() - kernel_sizes.size(), 2U,
platform::errors::InvalidArgument(
"The dims of X should be larger than that of kernel_sizes "
"by a number of 2, due to the batch size and input channel dim. "
"But recieved dims(X:%u) - dims(kernel_sizes:%u) != 2",
in_dims.size(), kernel_sizes.size()));
PADDLE_ENFORCE_EQ(
strides.size(), kernel_sizes.size(),
platform::errors::InvalidArgument(
"The dims of strides should be the same with that of kernel_sizes. "
"But recieved dims(strides: %u) != dims(kernel_sizes: %u).",
strides.size(), kernel_sizes.size()));
PADDLE_ENFORCE_EQ(
paddings.size(), 2 * strides.size(),
platform::errors::InvalidArgument(
"The dims of paddings should be 2 times of that of strides. "
"But recieved dims(paddings: %u) != 2*dims(strides: %u).",
paddings.size(), strides.size()));
PADDLE_ENFORCE_EQ(
strides.size(), dilations.size(),
platform::errors::InvalidArgument(
"The dims of strides should be the same with that of dilations. "
"But recieved dims(strides: %u) != dims(dilations: %u).",
strides.size(), dilations.size()));
// check kernel_sizes
PADDLE_ENFORCE_GT(kernel_sizes[0], 0,
platform::errors::InvalidArgument(
"The `kernel_sizes` should be greater than zero, "
"but recieved kernel_height: %d kernel_width: %d.",
kernel_sizes[0], kernel_sizes[1]));
PADDLE_ENFORCE_GT(kernel_sizes[1], 0,
platform::errors::InvalidArgument(
"The `kernel_sizes` should be greater than zero, "
"but recieved kernel_height: %d kernel_width: %d.",
kernel_sizes[0], kernel_sizes[1]));
// check strides
PADDLE_ENFORCE_GT(strides[0], 0,
platform::errors::InvalidArgument(
"The `strides` should be greater than zero, "
"but recieved strides_height: %d strides_width: %d.",
strides[0], strides[1]));
PADDLE_ENFORCE_GT(strides[1], 0,
platform::errors::InvalidArgument(
"The `strides` should be greater than zero, "
"but recieved strides_height: %d strides_width: %d.",
strides[0], strides[1]));
// check dilations
PADDLE_ENFORCE_GT(
dilations[0], 0,
platform::errors::InvalidArgument(
"The `dilations` should be greater than zero, "
"but recieved dilations_height: %d dilations_width: %d.",
dilations[0], dilations[1]));
PADDLE_ENFORCE_GT(
dilations[1], 0,
platform::errors::InvalidArgument(
"The `dilations` should be greater than zero, "
"but recieved dilations_height: %d dilations_width: %d.",
dilations[0], dilations[1]));
std::vector<int> out_dims;
out_dims.push_back(in_dims[0]);
int output_channels = in_dims[1] * kernel_sizes[0] * kernel_sizes[1];
out_dims.push_back(output_channels);
int output_height =
CalcOutputSize(in_dims[2], kernel_sizes[0], dilations[0], paddings[0],
paddings[2], strides[0]);
int output_width = CalcOutputSize(in_dims[3], kernel_sizes[1], dilations[1],
paddings[1], paddings[3], strides[1]);
if (ctx->IsRuntime()) {
// only check output height and width in runtime
PADDLE_ENFORCE_GT(
output_height, 0,
platform::errors::InvalidArgument(
"The sliding blocks calculated from input spatial size "
"(%d, %d), kernel_sizes (%d, %d), strides (%d, %d), "
"dilations (%d, %d), is (%d, %d), which should be a "
"positive integer.",
in_dims[2], in_dims[3], kernel_sizes[0], kernel_sizes[1],
strides[0], strides[1], dilations[0], dilations[1], output_height,
output_width));
PADDLE_ENFORCE_GT(
output_width, 0,
platform::errors::InvalidArgument(
"The sliding blocks calculated from input spatial size "
"(%d, %d), kernel_sizes (%d, %d), strides (%d, %d), "
"dilations (%d, %d), is (%d, %d), which should be a "
"positive integer.",
in_dims[2], in_dims[3], kernel_sizes[0], kernel_sizes[1],
strides[0], strides[1], dilations[0], dilations[1], output_height,
output_width));
}
int output_col_length = output_height * output_width;
out_dims.push_back(output_col_length);
ctx->SetOutputDim("Y", phi::make_ddim(out_dims));
}
protected:
framework::OpKernelType GetExpectedKernelType(
......@@ -237,16 +119,11 @@ DECLARE_NO_NEED_BUFFER_VARS_INFERER(UnfoldGradOpNoNeedBufferVarsInferer, "X");
} // namespace paddle
namespace ops = paddle::operators;
DELCARE_INFER_SHAPE_FUNCTOR(unfold, UnfoldInferShapeFunctor,
PT_INFER_META(phi::UnfoldInferMeta));
REGISTER_OPERATOR(unfold, ops::UnfoldOp, ops::UnfoldOpMaker,
ops::UnfoldGradMaker<paddle::framework::OpDesc>,
ops::UnfoldGradMaker<paddle::imperative::OpBase>);
ops::UnfoldGradMaker<paddle::imperative::OpBase>,
UnfoldInferShapeFunctor);
REGISTER_OPERATOR(unfold_grad, ops::UnfoldGradOp,
ops::UnfoldGradOpNoNeedBufferVarsInferer);
REGISTER_OP_CPU_KERNEL(
unfold, ops::UnfoldOpKernel<paddle::platform::CPUDeviceContext, float>,
ops::UnfoldOpKernel<paddle::platform::CPUDeviceContext, double>);
REGISTER_OP_CPU_KERNEL(
unfold_grad,
ops::UnfoldGradOpKernel<paddle::platform::CPUDeviceContext, float>,
ops::UnfoldGradOpKernel<paddle::platform::CPUDeviceContext, double>);
paddle/fluid/operators/unfold_op.h 已删除 100644 → 0
浏览文件 @ 60fc555e
/* Copyright (c) 2019 PaddlePaddle 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. */
#pragma once
#include <memory>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math/im2col.h"
#include "paddle/phi/kernels/funcs/math_function.h"
namespace paddle {
namespace operators {
using Tensor = framework::Tensor;
inline int CalcOutputSize(int input_size, int filter_size, int dilation,
int padding1, int padding2, int stride) {
const int dkernel = dilation * (filter_size - 1) + 1;
int output_size = (input_size + padding1 + padding2 - dkernel) / stride + 1;
return output_size;
}
template <typename DeviceContext, typename T>
class UnfoldOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
const Tensor* input = ctx.Input<Tensor>("X");
const int batch_size = static_cast<int>(input->dims()[0]);
Tensor* output = ctx.Output<Tensor>("Y");
output->mutable_data<T>(ctx.GetPlace());
std::vector<int> kernel_sizes = ctx.Attr<std::vector<int>>("kernel_sizes");
std::vector<int> strides = ctx.Attr<std::vector<int>>("strides");
std::vector<int> paddings = ctx.Attr<std::vector<int>>("paddings");
std::vector<int> dilations = ctx.Attr<std::vector<int>>("dilations");
math::Im2ColFunctor<math::ColFormat::kCFO, DeviceContext, T> im2col;
auto& dev_ctx = ctx.template device_context<DeviceContext>();
auto input_dims = input->dims();
int output_height =
CalcOutputSize(input_dims[2], kernel_sizes[0], dilations[0],
paddings[0], paddings[2], strides[0]);
int output_width =
CalcOutputSize(input_dims[3], kernel_sizes[1], dilations[1],
paddings[1], paddings[3], strides[1]);
framework::DDim input_shape({input_dims[1], input_dims[2], input_dims[3]});
framework::DDim output_matrix_shape({input_dims[1], kernel_sizes[0],
kernel_sizes[1], output_height,
output_width});
for (int i = 0; i < batch_size; i++) {
Tensor in_batch = input->Slice(i, i + 1).Resize(input_shape);
Tensor out_batch = output->Slice(i, i + 1).Resize(output_matrix_shape);
im2col(dev_ctx, in_batch, dilations, strides, paddings, &out_batch);
}
}
};
template <typename DeviceContext, typename T>
class UnfoldGradOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
const Tensor* output_grad = ctx.Input<Tensor>(framework::GradVarName("Y"));
Tensor* input_grad = ctx.Output<Tensor>(framework::GradVarName("X"));
input_grad->mutable_data<T>(ctx.GetPlace());
if ((!output_grad) || (!input_grad)) return;
std::vector<int> kernel_sizes = ctx.Attr<std::vector<int>>("kernel_sizes");
std::vector<int> strides = ctx.Attr<std::vector<int>>("strides");
std::vector<int> paddings = ctx.Attr<std::vector<int>>("paddings");
std::vector<int> dilations = ctx.Attr<std::vector<int>>("dilations");
const int batch_size = static_cast<int>(input_grad->dims()[0]);
auto input_dims = input_grad->dims();
int output_height =
CalcOutputSize(input_dims[2], kernel_sizes[0], dilations[0],
paddings[0], paddings[2], strides[0]);
int output_width =
CalcOutputSize(input_dims[3], kernel_sizes[1], dilations[1],
paddings[1], paddings[3], strides[1]);
framework::DDim input_shape({input_dims[1], input_dims[2], input_dims[3]});
framework::DDim output_matrix_shape({input_dims[1], kernel_sizes[0],
kernel_sizes[1], output_height,
output_width});
math::Col2ImFunctor<math::ColFormat::kCFO, DeviceContext, T> col2im;
auto& dev_ctx = ctx.template device_context<DeviceContext>();
phi::funcs::SetConstant<DeviceContext, T> set_zero;
set_zero(dev_ctx, input_grad, static_cast<T>(0));
for (int i = 0; i < batch_size; i++) {
Tensor out_grad_batch =
output_grad->Slice(i, i + 1).Resize(output_matrix_shape);
Tensor in_grad_batch = input_grad->Slice(i, i + 1).Resize(input_shape);
col2im(dev_ctx, out_grad_batch, dilations, strides, paddings,
&in_grad_batch);
}
}
};
} // namespace operators
} // namespace paddle
paddle/phi/infermeta/unary.cc
浏览文件 @ 1aa67778
......@@ -18,6 +18,7 @@ limitations under the License. */
#include "paddle/phi/common/data_type.h"
#include "paddle/phi/core/enforce.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/kernels/funcs/unfold_functor.h"
namespace phi {
......@@ -537,6 +538,164 @@ void TraceInferMeta(
out->set_dims(phi::make_ddim(sizes));
}
void UnfoldInferMeta(const MetaTensor& x,
const std::vector<int>& kernel_sizes,
const std::vector<int>& strides,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
MetaTensor* out,
MetaConfig config) {
auto in_dims = x.dims();
// Only [N, C, H, W] input supported now
PADDLE_ENFORCE_EQ(
in_dims.size(),
4,
phi::errors::InvalidArgument(
"Input should be 4-D tensor of format [N, C, H, W], but get %u",
in_dims.size()));
PADDLE_ENFORCE_EQ(
in_dims.size() - kernel_sizes.size(),
2U,
phi::errors::InvalidArgument(
"The dims of X should be larger than that of kernel_sizes "
"by a number of 2, due to the batch size and input channel dim. "
"But recieved dims(X:%u) - dims(kernel_sizes:%u) != 2",
in_dims.size(),
kernel_sizes.size()));
PADDLE_ENFORCE_EQ(
strides.size(),
kernel_sizes.size(),
phi::errors::InvalidArgument(
"The dims of strides should be the same with that of kernel_sizes. "
"But recieved dims(strides: %u) != dims(kernel_sizes: %u).",
strides.size(),
kernel_sizes.size()));
PADDLE_ENFORCE_EQ(
paddings.size(),
2 * strides.size(),
phi::errors::InvalidArgument(
"The dims of paddings should be 2 times of that of strides. "
"But recieved dims(paddings: %u) != 2*dims(strides: %u).",
paddings.size(),
strides.size()));
PADDLE_ENFORCE_EQ(
strides.size(),
dilations.size(),
phi::errors::InvalidArgument(
"The dims of strides should be the same with that of dilations. "
"But recieved dims(strides: %u) != dims(dilations: %u).",
strides.size(),
dilations.size()));
// check kernel_sizes
PADDLE_ENFORCE_GT(kernel_sizes[0],
0,
phi::errors::InvalidArgument(
"The `kernel_sizes` should be greater than zero, "
"but recieved kernel_height: %d kernel_width: %d.",
kernel_sizes[0],
kernel_sizes[1]));
PADDLE_ENFORCE_GT(kernel_sizes[1],
0,
phi::errors::InvalidArgument(
"The `kernel_sizes` should be greater than zero, "
"but recieved kernel_height: %d kernel_width: %d.",
kernel_sizes[0],
kernel_sizes[1]));
// check strides
PADDLE_ENFORCE_GT(strides[0],
0,
phi::errors::InvalidArgument(
"The `strides` should be greater than zero, "
"but recieved strides_height: %d strides_width: %d.",
strides[0],
strides[1]));
PADDLE_ENFORCE_GT(strides[1],
0,
phi::errors::InvalidArgument(
"The `strides` should be greater than zero, "
"but recieved strides_height: %d strides_width: %d.",
strides[0],
strides[1]));
// check dilations
PADDLE_ENFORCE_GT(
dilations[0],
0,
phi::errors::InvalidArgument(
"The `dilations` should be greater than zero, "
"but recieved dilations_height: %d dilations_width: %d.",
dilations[0],
dilations[1]));
PADDLE_ENFORCE_GT(
dilations[1],
0,
phi::errors::InvalidArgument(
"The `dilations` should be greater than zero, "
"but recieved dilations_height: %d dilations_width: %d.",
dilations[0],
dilations[1]));
std::vector<int> out_dims;
out_dims.push_back(in_dims[0]);
int output_channels = in_dims[1] * kernel_sizes[0] * kernel_sizes[1];
out_dims.push_back(output_channels);
int output_height = phi::funcs::CalcOutputSize(in_dims[2],
kernel_sizes[0],
dilations[0],
paddings[0],
paddings[2],
strides[0]);
int output_width = phi::funcs::CalcOutputSize(in_dims[3],
kernel_sizes[1],
dilations[1],
paddings[1],
paddings[3],
strides[1]);
if (config.is_runtime) {
// only check output height and width in runtime
PADDLE_ENFORCE_GT(
output_height,
0,
phi::errors::InvalidArgument(
"The sliding blocks calculated from input spatial size "
"(%d, %d), kernel_sizes (%d, %d), strides (%d, %d), "
"dilations (%d, %d), is (%d, %d), which should be a "
"positive integer.",
in_dims[2],
in_dims[3],
kernel_sizes[0],
kernel_sizes[1],
strides[0],
strides[1],
dilations[0],
dilations[1],
output_height,
output_width));
PADDLE_ENFORCE_GT(
output_width,
0,
phi::errors::InvalidArgument(
"The sliding blocks calculated from input spatial size "
"(%d, %d), kernel_sizes (%d, %d), strides (%d, %d), "
"dilations (%d, %d), is (%d, %d), which should be a "
"positive integer.",
in_dims[2],
in_dims[3],
kernel_sizes[0],
kernel_sizes[1],
strides[0],
strides[1],
dilations[0],
dilations[1],
output_height,
output_width));
}
int output_col_length = output_height * output_width;
out_dims.push_back(output_col_length);
out->set_dims(phi::make_ddim(out_dims));
}
} // namespace phi
PD_REGISTER_INFER_META_FN(copy_to, phi::CopyToInferMeta);
......
paddle/phi/infermeta/unary.h
浏览文件 @ 1aa67778
......@@ -93,4 +93,11 @@ void SplitInferMeta(const MetaTensor& x_meta,
void TraceInferMeta(
const MetaTensor& x, int offset, int axis1, int axis2, MetaTensor* out);
void UnfoldInferMeta(const MetaTensor& x,
const std::vector<int>& kernel_sizes,
const std::vector<int>& strides,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
MetaTensor* out,
MetaConfig config = MetaConfig());
} // namespace phi
paddle/phi/kernels/CMakeLists.txt
浏览文件 @ 1aa67778
......@@ -10,7 +10,7 @@ add_subdirectory(funcs)
set_property(GLOBAL PROPERTY PTEN_KERNELS "")
set(COMMON_KERNEL_DEPS dense_tensor sparse_coo_tensor sparse_csr_tensor kernel_context kernel_factory arg_map_context convert_utils lod_utils)
set(COMMON_KERNEL_DEPS ${COMMON_KERNEL_DEPS} eigen_function blas math_function)
set(COMMON_KERNEL_DEPS ${COMMON_KERNEL_DEPS} eigen_function blas math_function im2col)
# remove this dep after removing fluid deps on tensor creation
set(COMMON_KERNEL_DEPS ${COMMON_KERNEL_DEPS} pten_api_utils)
set(COMMON_KERNEL_DEPS ${COMMON_KERNEL_DEPS} infermeta)
......
paddle/phi/kernels/cpu/unfold_grad_kernel.cc 0 → 100644
浏览文件 @ 1aa67778
// Copyright (c) 2022 PaddlePaddle 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 "paddle/phi/kernels/unfold_grad_kernel.h"
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/unfold_grad_kernel_impl.h"
PD_REGISTER_KERNEL(
unfold_grad, CPU, ALL_LAYOUT, phi::UnfoldGradKernel, float, double) {}
paddle/phi/kernels/cpu/unfold_kernel.cc 0 → 100644
浏览文件 @ 1aa67778
// Copyright (c) 2022 PaddlePaddle 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 "paddle/phi/kernels/unfold_kernel.h"
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/unfold_kernel_impl.h"
PD_REGISTER_KERNEL(unfold, CPU, ALL_LAYOUT, phi::UnfoldKernel, float, double) {}
paddle/phi/kernels/funcs/unfold_functor.h 0 → 100644
浏览文件 @ 1aa67778
// Copyright (c) 2022 PaddlePaddle 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.
#pragma once
namespace phi {
namespace funcs {
//////// CalcOutputSize Functor ///////
inline int CalcOutputSize(int input_size,
int filter_size,
int dilation,
int padding1,
int padding2,
int stride) {
const int dkernel = dilation * (filter_size - 1) + 1;
int output_size = (input_size + padding1 + padding2 - dkernel) / stride + 1;
return output_size;
}
} // namespace funcs
} // namespace phi
paddle/phi/kernels/gpu/unfold_grad_kernel.cu 0 → 100644
浏览文件 @ 1aa67778
// Copyright (c) 2022 PaddlePaddle 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 "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/unfold_grad_kernel_impl.h"
#include "paddle/phi/kernels/unfold_grad_kernel.h"
PD_REGISTER_KERNEL(
unfold_grad, GPU, ALL_LAYOUT, phi::UnfoldGradKernel, float, double) {}
paddle/phi/kernels/gpu/unfold_kernel.cu 0 → 100644
浏览文件 @ 1aa67778
// Copyright (c) 2022 PaddlePaddle 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 "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/unfold_kernel_impl.h"
#include "paddle/phi/kernels/unfold_kernel.h"
PD_REGISTER_KERNEL(unfold, GPU, ALL_LAYOUT, phi::UnfoldKernel, float, double) {}
paddle/phi/kernels/impl/unfold_grad_kernel_impl.h 0 → 100644
浏览文件 @ 1aa67778
// Copyright (c) 2022 PaddlePaddle 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.
#pragma once
#include <vector>
#include "paddle/fluid/operators/math/im2col.h"
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/kernels/funcs/math_function.h"
#include "paddle/phi/kernels/funcs/unfold_functor.h"
namespace phi {
template <typename T, typename Context>
void UnfoldGradKernel(const Context& ctx,
const DenseTensor& x,
const DenseTensor& out_grad,
const std::vector<int>& kernel_sizes,
const std::vector<int>& strides,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
DenseTensor* x_grad) {
ctx.template Alloc<T>(x_grad);
if (!x_grad) return;
auto x_dims = x_grad->dims();
const int batch_size = static_cast<int>(x_dims[0]);
int out_height = phi::funcs::CalcOutputSize(x_dims[2],
kernel_sizes[0],
dilations[0],
paddings[0],
paddings[2],
strides[0]);
int out_width = phi::funcs::CalcOutputSize(x_dims[3],
kernel_sizes[1],
dilations[1],
paddings[1],
paddings[3],
strides[1]);
DDim x_shape = make_ddim({x_dims[1], x_dims[2], x_dims[3]});
DDim out_matrix_shape = make_ddim(
{x_dims[1], kernel_sizes[0], kernel_sizes[1], out_height, out_width});
paddle::operators::math::
Col2ImFunctor<paddle::operators::math::ColFormat::kCFO, Context, T>
col2im;
phi::funcs::SetConstant<Context, T> set_zero;
set_zero(ctx, x_grad, static_cast<T>(0));
for (int i = 0; i < batch_size; i++) {
DenseTensor out_grad_batch =
out_grad.Slice(i, i + 1).Resize(out_matrix_shape);
DenseTensor x_grad_batch = x_grad->Slice(i, i + 1).Resize(x_shape);
col2im(ctx, out_grad_batch, dilations, strides, paddings, &x_grad_batch);
}
}
} // namespace phi
paddle/phi/kernels/impl/unfold_kernel_impl.h 0 → 100644
浏览文件 @ 1aa67778
// Copyright (c) 2022 PaddlePaddle 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.
#pragma once
#include <vector>
#include "paddle/fluid/operators/math/im2col.h"
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/kernels/funcs/math_function.h"
#include "paddle/phi/kernels/funcs/unfold_functor.h"
namespace phi {
template <typename T, typename Context>
void UnfoldKernel(const Context& ctx,
const DenseTensor& x,
const std::vector<int>& kernel_sizes,
const std::vector<int>& strides,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
DenseTensor* out) {
const int batch_size = static_cast<int>(x.dims()[0]);
ctx.template Alloc<T>(out);
paddle::operators::math::
Im2ColFunctor<paddle::operators::math::ColFormat::kCFO, Context, T>
im2col;
auto x_dims = x.dims();
int out_height = phi::funcs::CalcOutputSize(x_dims[2],
kernel_sizes[0],
dilations[0],
paddings[0],
paddings[2],
strides[0]);
int out_width = phi::funcs::CalcOutputSize(x_dims[3],
kernel_sizes[1],
dilations[1],
paddings[1],
paddings[3],
strides[1]);
DDim x_shape = make_ddim({x_dims[1], x_dims[2], x_dims[3]});
DDim out_matrix_shape = make_ddim(
{x_dims[1], kernel_sizes[0], kernel_sizes[1], out_height, out_width});
for (int i = 0; i < batch_size; i++) {
DenseTensor in_batch = x.Slice(i, i + 1).Resize(x_shape);
DenseTensor out_batch = out->Slice(i, i + 1).Resize(out_matrix_shape);
im2col(ctx, in_batch, dilations, strides, paddings, &out_batch);
}
}
} // namespace phi
paddle/phi/kernels/unfold_grad_kernel.h 0 → 100644
浏览文件 @ 1aa67778
// Copyright (c) 2022 PaddlePaddle 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.
#pragma once
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/device_context.h"
namespace phi {
template <typename T, typename Context>
void UnfoldGradKernel(const Context& ctx,
const DenseTensor& x,
const DenseTensor& out_grad,
const std::vector<int>& kernel_sizes,
const std::vector<int>& strides,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
DenseTensor* x_grad);
} // namespace phi
paddle/phi/kernels/unfold_kernel.h 0 → 100644
浏览文件 @ 1aa67778
// Copyright (c) 2022 PaddlePaddle 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.
#pragma once
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/device_context.h"
namespace phi {
template <typename T, typename Context>
void UnfoldKernel(const Context& ctx,
const DenseTensor& x,
const std::vector<int>& kernel_sizes,
const std::vector<int>& strides,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
DenseTensor* out);
} // namespace phi
paddle/fluid/operators/unfold_op.cu → paddle/phi/ops/compat/unfold_sig.cc
浏览文件 @ 1aa67778
/* Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
/* Copyright (c) 2022 PaddlePaddle 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.
Indicesou may obtain a copy of the License at
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
......@@ -12,15 +12,17 @@ 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 "paddle/fluid/operators/unfold_op.h"
#include "paddle/phi/core/compat/op_utils.h"
namespace ops = paddle::operators;
namespace phi {
REGISTER_OP_CUDA_KERNEL(
unfold, ops::UnfoldOpKernel<paddle::platform::CUDADeviceContext, float>,
ops::UnfoldOpKernel<paddle::platform::CUDADeviceContext, double>);
KernelSignature UnfoldGradOpArgumentMapping(const ArgumentMappingContext& ctx) {
return KernelSignature("unfold_grad",
{"X", GradVarName("Y")},
{"kernel_sizes", "strides", "paddings", "dilations"},
{GradVarName("X")});
}
REGISTER_OP_CUDA_KERNEL(
unfold_grad,
ops::UnfoldGradOpKernel<paddle::platform::CUDADeviceContext, float>,
ops::UnfoldGradOpKernel<paddle::platform::CUDADeviceContext, double>);
} // namespace phi
PD_REGISTER_ARG_MAPPING_FN(unfold_grad, phi::UnfoldGradOpArgumentMapping);
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