strided_memcpy_test.cc

/* Copyright (c) 2016 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/fluid/operators/strided_memcpy.h"

#include "gtest/gtest.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]);
  }
}

#ifdef PADDLE_WITH_CUDA
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::CUDAPlace gpu0(0);
  platform::CPUPlace cpu;

  platform::CUDADeviceContext ctx(gpu0);

  auto src_allocation = memory::Alloc(gpu0, sizeof(src));

  int* gpu_src = reinterpret_cast<int*>(src_allocation->ptr());
  memory::Copy(gpu0, gpu_src, cpu, src, sizeof(src), ctx.stream());

  framework::DDim src_stride({5, 1});

  int dst[4];
  auto dst_allocation = memory::Alloc(gpu0, sizeof(dst));
  int* gpu_dst = reinterpret_cast<int*>(dst_allocation->ptr());

  framework::DDim dst_dim({2, 2});
  framework::DDim dst_stride({2, 1});

  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]);
}

TEST(StridedMemcpy, GPUConcat) {
  // clang-format off
  int src[] = {
      1, 2,
      3, 4
  };
  // clang-format on

  platform::CUDAPlace gpu0(0);
  platform::CPUPlace cpu;
  platform::CUDADeviceContext ctx(gpu0);
  auto gpu_src_allocation = memory::Alloc(gpu0, sizeof(src));
  int* gpu_src = reinterpret_cast<int*>(gpu_src_allocation->ptr());
  memory::Copy(gpu0, gpu_src, cpu, src, sizeof(src), ctx.stream());

  int dst[8];
  auto gpu_dst_allocation = memory::Alloc(gpu0, sizeof(dst));
  int* gpu_dst = reinterpret_cast<int*>(gpu_dst_allocation->ptr());

  framework::DDim src_stride({2, 1});
  framework::DDim dst_dim({2, 2});
  framework::DDim dst_stride({4, 1});

  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]);
  }
}

#endif
}  // namespace operators
}  // namespace paddle