tensor_util_test.cc 6.7 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
/*
  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 {
D
dzhwinter 已提交
20

D
dzhwinter 已提交
21 22 23 24 25 26 27 28 29 30
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));
D
dzhwinter 已提交
31
  src_tensor.set_layout(DataLayout::kAnyLayout);
D
dzhwinter 已提交
32 33

  auto cpu_place = new platform::CPUPlace();
D
dzhwinter 已提交
34
  CopyFrom(src_tensor, *cpu_place, &dst_tensor);
D
dzhwinter 已提交
35 36 37 38 39 40 41

  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]);
  }

D
dzhwinter 已提交
42 43
  EXPECT_TRUE(dst_tensor.layout() == src_tensor.layout());

D
dzhwinter 已提交
44
  Tensor slice_tensor = src_tensor.Slice(1, 2);
D
dzhwinter 已提交
45
  CopyFrom(slice_tensor, *cpu_place, &dst_tensor);
D
dzhwinter 已提交
46 47 48 49 50 51
  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]);
  }
D
dzhwinter 已提交
52 53
  EXPECT_TRUE(dst_tensor.layout() == src_tensor.layout());

D
dzhwinter 已提交
54 55 56 57 58 59 60 61 62 63 64 65 66
#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
D
dzhwinter 已提交
67
    auto gpu_place = new platform::CUDAPlace(0);
D
dzhwinter 已提交
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
    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]);
    }
D
dzhwinter 已提交
99 100

    EXPECT_TRUE(dst_tensor.layout() == src_tensor.layout());
D
dzhwinter 已提交
101 102 103 104 105 106 107 108 109 110 111 112 113 114
  }
#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();
D
dzhwinter 已提交
115
    CopyFromVector<int>(src_vec, &cpu_tensor);
D
dzhwinter 已提交
116 117 118 119 120 121 122 123 124 125 126

    // 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}));
D
dzhwinter 已提交
127
    CopyFromVector<int>(src_vec, &cpu_tensor);
D
dzhwinter 已提交
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
    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}));
D
dzhwinter 已提交
153
    auto gpu_place = new paddle::platform::CUDAPlace();
D
dzhwinter 已提交
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
    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;
    std::vector<int> dst;
D
dzhwinter 已提交
209
    CopyToVector<int>(src, &dst);
D
dzhwinter 已提交
210 211 212 213 214 215 216 217 218

    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;
D
dzhwinter 已提交
219
    CUDAPlace place;
D
dzhwinter 已提交
220 221 222 223 224 225 226 227 228 229 230 231 232 233 234
    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