tensor_util_test.cc 6.6 KB
Newer Older
D
dzhwinter 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228
/*
  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/framework/tensor_util.h"
#include <gtest/gtest.h>
#include <string>

namespace paddle {
namespace framework {
TEST(CopyFrom, Tensor) {
  Tensor src_tensor;
  Tensor dst_tensor;
  platform::CPUDeviceContext cpu_ctx((platform::CPUPlace()));

  int* src_ptr =
      src_tensor.mutable_data<int>(make_ddim({3, 3}), platform::CPUPlace());

  int arr[9] = {1, 2, 3, 4, 5, 6, 7, 8, 9};
  memcpy(src_ptr, arr, 9 * sizeof(int));

  auto cpu_place = new platform::CPUPlace();
  CopyFrom(src_tensor, *cpu_place, cpu_ctx, &dst_tensor);

  const int* dst_ptr = dst_tensor.data<int>();
  ASSERT_NE(src_ptr, dst_ptr);
  for (size_t i = 0; i < 9; ++i) {
    EXPECT_EQ(src_ptr[i], dst_ptr[i]);
  }

  Tensor slice_tensor = src_tensor.Slice(1, 2);
  CopyFrom(slice_tensor, *cpu_place, cpu_ctx, &dst_tensor);
  const int* slice_ptr = slice_tensor.data<int>();
  dst_ptr = dst_tensor.data<int>();
  ASSERT_NE(dst_ptr, slice_ptr);
  for (size_t i = 0; i < 3; ++i) {
    EXPECT_EQ(dst_ptr[i], slice_ptr[i]);
  }
#ifdef PADDLE_WITH_CUDA
  {
    Tensor src_tensor;
    Tensor gpu_tensor;
    Tensor dst_tensor;

    int* src_ptr =
        src_tensor.mutable_data<int>(make_ddim({3, 3}), platform::CPUPlace());

    int arr[9] = {1, 2, 3, 4, 5, 6, 7, 8, 9};
    memcpy(src_ptr, arr, 9 * sizeof(int));

    // CPU Tensor to GPU Tensor
    auto gpu_place = new platform::GPUPlace(0);
    platform::CUDADeviceContext gpu_ctx(*gpu_place);
    CopyFrom(src_tensor, *gpu_place, gpu_ctx, &gpu_tensor);

    // GPU Tensor to CPU Tensor
    auto cpu_place = new platform::CPUPlace();
    CopyFrom(gpu_tensor, *cpu_place, gpu_ctx, &dst_tensor);

    // Sync before Compare Tensors
    gpu_ctx.Wait();
    const int* dst_ptr = dst_tensor.data<int>();
    ASSERT_NE(src_ptr, dst_ptr);
    for (size_t i = 0; i < 9; ++i) {
      EXPECT_EQ(src_ptr[i], dst_ptr[i]);
    }

    Tensor slice_tensor = src_tensor.Slice(1, 2);

    // CPU Slice Tensor to GPU Tensor
    CopyFrom(slice_tensor, *gpu_place, gpu_ctx, &gpu_tensor);

    // GPU Tensor to CPU Tensor
    CopyFrom(gpu_tensor, *cpu_place, gpu_ctx, &dst_tensor);

    // Sync before Compare Slice Tensors
    gpu_ctx.Wait();
    const int* slice_ptr = slice_tensor.data<int>();
    dst_ptr = dst_tensor.data<int>();
    ASSERT_NE(dst_ptr, slice_ptr);
    for (size_t i = 0; i < 3; ++i) {
      EXPECT_EQ(dst_ptr[i], slice_ptr[i]);
    }
  }
#endif
}

TEST(CopyFromVector, Tensor) {
  using namespace paddle::framework;
  using namespace paddle::platform;
  {
    std::vector<int> src_vec = {1, 2, 3, 4, 5, 6, 7, 8, 9};
    Tensor cpu_tensor;

    // Copy to CPU Tensor
    cpu_tensor.Resize(make_ddim({3, 3}));
    auto cpu_place = new paddle::platform::CPUPlace();
    CPUDeviceContext cpu_ctx(*cpu_place);
    CopyFromVector<int>(src_vec, cpu_ctx, &cpu_tensor);

    // Compare Tensors
    const int* cpu_ptr = cpu_tensor.data<int>();
    const int* src_ptr = src_vec.data();
    ASSERT_NE(src_ptr, cpu_ptr);
    for (size_t i = 0; i < 9; ++i) {
      EXPECT_EQ(src_ptr[i], cpu_ptr[i]);
    }

    src_vec.erase(src_vec.begin(), src_vec.begin() + 5);
    cpu_tensor.Resize(make_ddim({2, 2}));
    CopyFromVector<int>(src_vec, cpu_ctx, &cpu_tensor);
    cpu_ptr = cpu_tensor.data<int>();
    src_ptr = src_vec.data();
    ASSERT_NE(src_ptr, cpu_ptr);
    for (size_t i = 0; i < 5; ++i) {
      EXPECT_EQ(src_ptr[i], cpu_ptr[i]);
    }

    delete cpu_place;
  }

#ifdef PADDLE_WITH_CUDA
  {
    std::vector<int> src_vec = {1, 2, 3, 4, 5, 6, 7, 8, 9};
    Tensor cpu_tensor;
    Tensor gpu_tensor;
    Tensor dst_tensor;

    // Copy to CPU Tensor
    cpu_tensor.Resize(make_ddim({3, 3}));
    auto cpu_place = new paddle::platform::CPUPlace();
    CPUDeviceContext cpu_ctx(*cpu_place);
    CopyFromVector<int>(src_vec, cpu_ctx, &cpu_tensor);

    // Copy to GPUTensor
    gpu_tensor.Resize(make_ddim({3, 3}));
    auto gpu_place = new paddle::platform::GPUPlace();
    CUDADeviceContext gpu_ctx(*gpu_place);
    CopyFromVector<int>(src_vec, gpu_ctx, &gpu_tensor);
    // Copy from GPU to CPU tensor for comparison
    CopyFrom(gpu_tensor, *cpu_place, gpu_ctx, &dst_tensor);

    // Sync before Compare Tensors
    gpu_ctx.Wait();
    const int* src_ptr = src_vec.data();
    const int* cpu_ptr = cpu_tensor.data<int>();
    const int* dst_ptr = dst_tensor.data<int>();
    ASSERT_NE(src_ptr, cpu_ptr);
    ASSERT_NE(src_ptr, dst_ptr);
    for (size_t i = 0; i < 9; ++i) {
      EXPECT_EQ(src_ptr[i], cpu_ptr[i]);
      EXPECT_EQ(src_ptr[i], dst_ptr[i]);
    }

    src_vec.erase(src_vec.begin(), src_vec.begin() + 5);

    cpu_tensor.Resize(make_ddim({2, 2}));
    CopyFromVector<int>(src_vec, cpu_ctx, &cpu_tensor);
    gpu_tensor.Resize(make_ddim({2, 2}));
    CopyFromVector<int>(src_vec, gpu_ctx, &gpu_tensor);
    CopyFrom(gpu_tensor, *cpu_place, gpu_ctx, &dst_tensor);

    // Sync before Compare Tensors
    gpu_ctx.Wait();
    src_ptr = src_vec.data();
    cpu_ptr = cpu_tensor.data<int>();
    dst_ptr = dst_tensor.data<int>();
    ASSERT_NE(src_ptr, cpu_ptr);
    ASSERT_NE(src_ptr, dst_ptr);
    for (size_t i = 0; i < 5; ++i) {
      EXPECT_EQ(src_ptr[i], cpu_ptr[i]);
      EXPECT_EQ(src_ptr[i], dst_ptr[i]);
    }

    delete cpu_place;
    delete gpu_place;
  }
#endif
}

TEST(CopyToVector, Tensor) {
  using namespace paddle::framework;
  using namespace paddle::platform;
  {
    Tensor src;
    int* src_ptr = src.mutable_data<int>({3, 3}, CPUPlace());
    for (int i = 0; i < 3 * 3; ++i) {
      src_ptr[i] = i;
    }

    CPUPlace place;
    CPUDeviceContext cpu_ctx(place);
    std::vector<int> dst;
    CopyToVector<int>(src, cpu_ctx, &dst);

    for (int i = 0; i < 3 * 3; ++i) {
      EXPECT_EQ(src_ptr[i], dst[i]);
    }
  }
#ifdef PADDLE_WITH_CUDA
  {
    std::vector<int> src_vec = {1, 2, 3, 4, 5, 6, 7, 8, 9};
    Tensor gpu_tensor;
    GPUPlace place;
    CUDADeviceContext gpu_ctx(place);
    CopyFromVector<int>(src_vec, gpu_ctx, &gpu_tensor);

    std::vector<int> dst;
    CopyToVector<int>(gpu_tensor, gpu_ctx, &dst);

    for (int i = 0; i < 3 * 3; ++i) {
      EXPECT_EQ(src_vec[i], dst[i]);
    }
  }
#endif
}

}  // namespace framework
}  // namespace paddle