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278 lines
8.9 KiB
278 lines
8.9 KiB
/*
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Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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#include "paddle/framework/tensor.h"
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#include <gtest/gtest.h>
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#include <string>
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TEST(Tensor, Dims) {
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using namespace paddle::framework;
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using namespace paddle::platform;
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Tensor tt;
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tt.Resize({2, 3, 4});
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DDim dims = tt.dims();
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ASSERT_EQ(arity(dims), 3);
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for (int i = 0; i < 3; ++i) {
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EXPECT_EQ(i + 2, dims[i]);
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}
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}
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TEST(Tensor, DataAssert) {
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paddle::framework::Tensor src_tensor;
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bool caught = false;
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try {
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src_tensor.data<double>();
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} catch (paddle::platform::EnforceNotMet err) {
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caught = true;
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std::string msg =
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"holder_ should not be null\nTensor holds no memory. Call "
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"Tensor::mutable_data first.";
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const char* what = err.what();
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for (size_t i = 0; i < msg.length(); ++i) {
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ASSERT_EQ(what[i], msg[i]);
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}
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}
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ASSERT_TRUE(caught);
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}
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/* following tests are not available at present
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because Memory::Alloc() and Memory::Free() have not been ready.
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*/
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TEST(Tensor, MutableData) {
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using namespace paddle::framework;
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using namespace paddle::platform;
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{
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Tensor src_tensor;
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float* p1 = nullptr;
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float* p2 = nullptr;
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// initialization
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p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
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EXPECT_NE(p1, nullptr);
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// set src_tensor a new dim with large size
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// momery is supposed to be re-allocated
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p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), CPUPlace());
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EXPECT_NE(p2, nullptr);
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EXPECT_NE(p1, p2);
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// set src_tensor a new dim with same size
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// momery block is supposed to be unchanged
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p1 = src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), CPUPlace());
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EXPECT_EQ(p1, p2);
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// set src_tensor a new dim with smaller size
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// momery block is supposed to be unchanged
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p2 = src_tensor.mutable_data<float>(make_ddim({2, 2}), CPUPlace());
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EXPECT_EQ(p1, p2);
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}
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#ifdef PADDLE_WITH_CUDA
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{
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Tensor src_tensor;
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float* p1 = nullptr;
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float* p2 = nullptr;
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// initialization
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p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), GPUPlace());
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EXPECT_NE(p1, nullptr);
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// set src_tensor a new dim with large size
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// momery is supposed to be re-allocated
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p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), GPUPlace());
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EXPECT_NE(p2, nullptr);
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EXPECT_NE(p1, p2);
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// set src_tensor a new dim with same size
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// momery block is supposed to be unchanged
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p1 = src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), GPUPlace());
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EXPECT_EQ(p1, p2);
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// set src_tensor a new dim with smaller size
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// momery block is supposed to be unchanged
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p2 = src_tensor.mutable_data<float>(make_ddim({2, 2}), GPUPlace());
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EXPECT_EQ(p1, p2);
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}
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#endif
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}
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TEST(Tensor, ShareDataWith) {
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using namespace paddle::framework;
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using namespace paddle::platform;
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{
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Tensor src_tensor;
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Tensor dst_tensor;
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// Try to share data form uninitialized tensor
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bool caught = false;
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try {
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dst_tensor.ShareDataWith<float>(src_tensor);
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} catch (paddle::platform::EnforceNotMet err) {
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caught = true;
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std::string msg =
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"holder_ should not be null\nTensor holds no memory. Call "
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"Tensor::mutable_data first.";
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const char* what = err.what();
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for (size_t i = 0; i < msg.length(); ++i) {
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ASSERT_EQ(what[i], msg[i]);
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}
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}
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ASSERT_TRUE(caught);
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src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), CPUPlace());
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dst_tensor.ShareDataWith<int>(src_tensor);
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ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
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}
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#ifdef PADDLE_WITH_CUDA
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{
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Tensor src_tensor;
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Tensor dst_tensor;
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src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), GPUPlace());
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dst_tensor.ShareDataWith<int>(src_tensor);
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ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
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}
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#endif
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}
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TEST(Tensor, Slice) {
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using namespace paddle::framework;
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using namespace paddle::platform;
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{
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Tensor src_tensor;
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src_tensor.mutable_data<int>(make_ddim({5, 3, 4}), CPUPlace());
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Tensor slice_tensor = src_tensor.Slice<int>(1, 3);
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DDim slice_dims = slice_tensor.dims();
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ASSERT_EQ(arity(slice_dims), 3);
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EXPECT_EQ(slice_dims[0], 2);
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EXPECT_EQ(slice_dims[1], 3);
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EXPECT_EQ(slice_dims[2], 4);
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uintptr_t src_data_address =
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reinterpret_cast<uintptr_t>(src_tensor.data<int>());
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uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
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src_tensor.mutable_data<int>(src_tensor.dims(), CPUPlace()));
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uintptr_t slice_data_address =
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reinterpret_cast<uintptr_t>(slice_tensor.data<int>());
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uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
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slice_tensor.mutable_data<int>(slice_tensor.dims(), CPUPlace()));
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EXPECT_EQ(src_data_address, src_mutable_data_address);
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EXPECT_EQ(slice_data_address, slice_mutable_data_address);
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EXPECT_EQ(src_data_address + 3 * 4 * 1 * sizeof(int), slice_data_address);
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}
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#ifdef PADDLE_WITH_CUDA
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{
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Tensor src_tensor;
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src_tensor.mutable_data<double>(make_ddim({6, 9}), GPUPlace());
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Tensor slice_tensor = src_tensor.Slice<double>(2, 6);
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DDim slice_dims = slice_tensor.dims();
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ASSERT_EQ(arity(slice_dims), 2);
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EXPECT_EQ(slice_dims[0], 4);
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EXPECT_EQ(slice_dims[1], 9);
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uintptr_t src_data_address =
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reinterpret_cast<uintptr_t>(src_tensor.data<double>());
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uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
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src_tensor.mutable_data<double>(src_tensor.dims(), GPUPlace()));
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uintptr_t slice_data_address =
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reinterpret_cast<uintptr_t>(slice_tensor.data<double>());
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uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
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slice_tensor.mutable_data<double>(slice_tensor.dims(), GPUPlace()));
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EXPECT_EQ(src_data_address, src_mutable_data_address);
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EXPECT_EQ(slice_data_address, slice_mutable_data_address);
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EXPECT_EQ(src_data_address + 9 * 2 * sizeof(double), slice_data_address);
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}
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#endif
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}
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TEST(Tensor, CopyFrom) {
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using namespace paddle::framework;
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using namespace paddle::platform;
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{
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Tensor src_tensor;
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Tensor dst_tensor;
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int* src_ptr = src_tensor.mutable_data<int>(make_ddim({3, 3}), CPUPlace());
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int arr[9] = {1, 2, 3, 4, 5, 6, 7, 8, 9};
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memcpy(src_ptr, arr, 9 * sizeof(int));
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auto cpu_place = new paddle::platform::CPUPlace();
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dst_tensor.CopyFrom<int>(src_tensor, *cpu_place);
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const int* dst_ptr = dst_tensor.data<int>();
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ASSERT_NE(src_ptr, dst_ptr);
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for (size_t i = 0; i < 9; ++i) {
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EXPECT_EQ(src_ptr[i], dst_ptr[i]);
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}
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Tensor slice_tensor = src_tensor.Slice<int>(1, 2);
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dst_tensor.CopyFrom<int>(slice_tensor, *cpu_place);
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const int* slice_ptr = slice_tensor.data<int>();
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dst_ptr = dst_tensor.data<int>();
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ASSERT_NE(dst_ptr, slice_ptr);
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for (size_t i = 0; i < 3; ++i) {
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EXPECT_EQ(dst_ptr[i], slice_ptr[i]);
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}
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}
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#ifdef PADDLE_WITH_CUDA
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{
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Tensor src_tensor;
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Tensor gpu_tensor;
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Tensor dst_tensor;
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int* src_ptr = src_tensor.mutable_data<int>(make_ddim({3, 3}), CPUPlace());
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int arr[9] = {1, 2, 3, 4, 5, 6, 7, 8, 9};
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memcpy(src_ptr, arr, 9 * sizeof(int));
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// CPU Tensor to GPU Tensor
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auto gpu_place = new paddle::platform::GPUPlace(0);
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gpu_tensor.CopyFrom<int>(src_tensor, *gpu_place);
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// GPU Tensor to CPU Tensor
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auto cpu_place = new paddle::platform::CPUPlace();
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dst_tensor.CopyFrom<int>(gpu_tensor, *cpu_place);
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// Compare Tensors
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const int* dst_ptr = dst_tensor.data<int>();
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ASSERT_NE(src_ptr, dst_ptr);
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for (size_t i = 0; i < 9; ++i) {
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EXPECT_EQ(src_ptr[i], dst_ptr[i]);
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}
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Tensor slice_tensor = src_tensor.Slice<int>(1, 2);
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// CPU Slice Tensor to GPU Tensor
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gpu_tensor.CopyFrom<int>(slice_tensor, *gpu_place);
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// GPU Tensor to CPU Tensor
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dst_tensor.CopyFrom<int>(gpu_tensor, *cpu_place);
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// Compare Slice Tensors
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const int* slice_ptr = slice_tensor.data<int>();
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dst_ptr = dst_tensor.data<int>();
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ASSERT_NE(dst_ptr, slice_ptr);
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for (size_t i = 0; i < 3; ++i) {
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EXPECT_EQ(dst_ptr[i], slice_ptr[i]);
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}
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}
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#endif
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}
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TEST(Tensor, ReshapeToMatrix) {
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using namespace paddle::framework;
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using namespace paddle::platform;
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Tensor src;
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int* src_ptr = src.mutable_data<int>({2, 3, 4, 9}, CPUPlace());
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for (int i = 0; i < 2 * 3 * 4 * 9; ++i) {
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src_ptr[i] = i;
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}
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Tensor res = ReshapeToMatrix<int>(src, 2);
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ASSERT_EQ(res.dims()[0], 2 * 3);
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ASSERT_EQ(res.dims()[1], 4 * 9);
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}
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