提交 2e38044f 编写于 作者: Y Yu Yang 提交者: GitHub

Merge pull request #4205 from reyoung/feature/tensor_copy

Add StridedCopy method
...@@ -96,3 +96,4 @@ set(GLOB_OP_LIB ${OP_LIBRARY} CACHE INTERNAL "Global OP library") ...@@ -96,3 +96,4 @@ set(GLOB_OP_LIB ${OP_LIBRARY} CACHE INTERNAL "Global OP library")
cc_test(gather_test SRCS gather_test.cc DEPS tensor) cc_test(gather_test SRCS gather_test.cc DEPS tensor)
cc_test(net_op_test SRCS net_op_test.cc DEPS net_op) cc_test(net_op_test SRCS net_op_test.cc DEPS net_op)
cc_test(scatter_test SRCS scatter_test.cc DEPS tensor) cc_test(scatter_test SRCS scatter_test.cc DEPS tensor)
cc_test(strided_memcpy_test SRCS strided_memcpy_test.cc DEPS tensor paddle_memory)
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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/framework/ddim.h"
#include "paddle/memory/memcpy.h"
#include "paddle/platform/device_context.h"
namespace paddle {
namespace operators {
namespace detail {
template <typename T, int Rank>
struct StridedMemcpyFunctor;
template <typename T>
struct StridedMemcpyFunctor<T, 1> {
void operator()(const platform::DeviceContext& dev_ctx, const T* src,
framework::Dim<1> src_stride, framework::Dim<1> dst_dim,
framework::Dim<1> dst_stride, T* dst) const {
auto place = dev_ctx.GetPlace();
if (platform::is_cpu_place(place)) {
auto& cpu_place = boost::get<platform::CPUPlace>(place);
memory::Copy(cpu_place, dst, cpu_place, src, sizeof(T) * dst_dim.head);
} else {
#ifndef PADDLE_ONLY_CPU
auto& gpu_place = boost::get<platform::GPUPlace>(place);
auto& cuda_ctx =
reinterpret_cast<const platform::CUDADeviceContext&>(dev_ctx);
memory::Copy(gpu_place, dst, gpu_place, src, sizeof(T) * dst_dim.head,
cuda_ctx.stream());
#else
PADDLE_THROW("Paddle is not compiled with GPU");
#endif
}
}
};
template <typename T, int Rank>
struct StridedMemcpyFunctor {
void operator()(const platform::DeviceContext& dev_ctx, const T* src,
framework::Dim<Rank> src_stride, framework::Dim<Rank> dst_dim,
framework::Dim<Rank> dst_stride, T* dst) const {
for (int64_t i = 0; i < dst_dim.head; ++i) {
StridedMemcpyFunctor<T, Rank - 1> func;
func(dev_ctx, src, src_stride.tail, dst_dim.tail, dst_stride.tail, dst);
src += src_stride.head;
dst += dst_stride.head;
}
}
};
template <typename T>
struct StridedCopyDimVisitor : public boost::static_visitor<void> {
StridedCopyDimVisitor(const platform::DeviceContext& dev_ctx, const T* src,
const framework::DDim& src_stride,
const framework::DDim& dst_stride, T* dst)
: dev_ctx_(dev_ctx),
src_(src),
src_stride_(src_stride),
dst_stride_(dst_stride),
dst_(dst) {}
template <typename Dim>
void operator()(Dim dst_dim) const {
Dim src_stride = boost::get<Dim>(src_stride_);
Dim dst_stride = boost::get<Dim>(dst_stride_);
constexpr int dim = Dim::dimensions;
StridedMemcpyFunctor<T, dim> functor;
functor(dev_ctx_, src_, src_stride, dst_dim, dst_stride, dst_);
}
const platform::DeviceContext& dev_ctx_;
const T* src_;
const framework::DDim& src_stride_;
const framework::DDim& dst_stride_;
T* dst_;
};
} // namespace detail
} // namespace operators
} // namespace paddle
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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/operators/detail/strided_memcpy.h"
namespace paddle {
namespace operators {
// Strided memory copy from src to dst.
//
// The src and dst should be both on dev_ctx.GetPlace(), otherwise, there will
// be a segment fault.
//
// The stride of an array (also referred to as increment, pitch or step size) is
// the number of locations in memory between beginnings of successive array
// elements
//
// For example, for tensor like [1, 3, 300, 300]. If there is no padding, the
// stride is [270000, 90000, 300, 1].
//
// NOTE: When use GPU, the memcpy is async. To sync memcpy, please invoke
// `dev_ctx.Wait()`.
template <typename T>
inline void StridedMemcpy(const platform::DeviceContext& dev_ctx, const T* src,
const framework::DDim& src_stride,
const framework::DDim& dst_dim,
const framework::DDim& dst_stride, T* dst) {
using namespace detail;
StridedCopyDimVisitor<T> func(dev_ctx, src, src_stride, dst_stride, dst);
boost::apply_visitor(func, dst_dim);
}
} // namespace operators
} // namespace paddle
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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/operators/strided_memcpy.h"
#include "gtest/gtest.h"
#include "paddle/memory/memory.h"
namespace paddle {
namespace operators {
TEST(StridedMemcpy, CPUCrop) {
// clang-format off
int src[] = {
0, 1, 2, 0, 0,
0, 3, 4, 0, 0,
0, 0, 0, 0, 0,
};
// clang-format on
framework::DDim src_stride({5, 1});
int dst[4];
framework::DDim dst_dim({2, 2});
framework::DDim dst_stride({2, 1});
platform::CPUDeviceContext ctx;
StridedMemcpy<int>(ctx, src + 1, src_stride, dst_dim, dst_stride, dst);
ASSERT_EQ(1, dst[0]);
ASSERT_EQ(2, dst[1]);
ASSERT_EQ(3, dst[2]);
ASSERT_EQ(4, dst[3]);
}
TEST(StridedMemcpy, CPUConcat) {
// clang-format off
int src[] = {
1, 2,
3, 4
};
// clang-format on
int dst[8];
framework::DDim src_stride({2, 1});
framework::DDim dst_dim({2, 2});
framework::DDim dst_stride({4, 1});
platform::CPUDeviceContext ctx;
StridedMemcpy<int>(ctx, src, src_stride, dst_dim, dst_stride, dst);
StridedMemcpy<int>(ctx, src, src_stride, dst_dim, dst_stride, dst + 2);
// clang-format off
int expect_dst[] = {
1, 2, 1, 2,
3, 4, 3, 4
};
// clang-format on
for (size_t i = 0; i < sizeof(expect_dst) / sizeof(int); ++i) {
ASSERT_EQ(expect_dst[i], dst[i]);
}
}
#ifndef PADDLE_ONLY_CPU
TEST(StridedMemcpy, GPUCrop) {
// clang-format off
int src[] = {
0, 1, 2, 0, 0,
0, 3, 4, 0, 0,
0, 0, 0, 0, 0,
};
// clang-format on
platform::GPUPlace gpu0(0);
platform::CPUPlace cpu;
int* gpu_src = reinterpret_cast<int*>(memory::Alloc(gpu0, sizeof(src)));
memory::Copy(gpu0, gpu_src, cpu, src, sizeof(src));
framework::DDim src_stride({5, 1});
int dst[4];
int* gpu_dst = reinterpret_cast<int*>(memory::Alloc(gpu0, sizeof(dst)));
framework::DDim dst_dim({2, 2});
framework::DDim dst_stride({2, 1});
platform::CUDADeviceContext ctx(gpu0);
StridedMemcpy<int>(ctx, gpu_src + 1, src_stride, dst_dim, dst_stride,
gpu_dst);
memory::Copy(cpu, dst, gpu0, gpu_dst, sizeof(dst), ctx.stream());
ctx.Wait();
ASSERT_EQ(1, dst[0]);
ASSERT_EQ(2, dst[1]);
ASSERT_EQ(3, dst[2]);
ASSERT_EQ(4, dst[3]);
memory::Free(gpu0, gpu_dst);
memory::Free(gpu0, gpu_src);
}
TEST(StridedMemcpy, GPUConcat) {
// clang-format off
int src[] = {
1, 2,
3, 4
};
// clang-format on
platform::GPUPlace gpu0(0);
platform::CPUPlace cpu;
int* gpu_src = reinterpret_cast<int*>(memory::Alloc(gpu0, sizeof(src)));
memory::Copy(gpu0, gpu_src, cpu, src, sizeof(src));
int dst[8];
int* gpu_dst = reinterpret_cast<int*>(memory::Alloc(gpu0, sizeof(dst)));
framework::DDim src_stride({2, 1});
framework::DDim dst_dim({2, 2});
framework::DDim dst_stride({4, 1});
platform::CUDADeviceContext ctx(gpu0);
StridedMemcpy<int>(ctx, gpu_src, src_stride, dst_dim, dst_stride, gpu_dst);
StridedMemcpy<int>(ctx, gpu_src, src_stride, dst_dim, dst_stride,
gpu_dst + 2);
memory::Copy(cpu, dst, gpu0, gpu_dst, sizeof(dst), ctx.stream());
ctx.Wait();
// clang-format off
int expect_dst[] = {
1, 2, 1, 2,
3, 4, 3, 4
};
// clang-format on
for (size_t i = 0; i < sizeof(expect_dst) / sizeof(int); ++i) {
ASSERT_EQ(expect_dst[i], dst[i]);
}
memory::Free(gpu0, gpu_dst);
memory::Free(gpu0, gpu_src);
}
#endif
} // namespace operators
} // namespace paddle
\ No newline at end of file
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册