wehub-resource-sync
108 lines
3.3 KiB
C++
108 lines
3.3 KiB
C++
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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#include <gtest/gtest.h>
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#include <memory>
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#include "paddle/phi/api/include/api.h"
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#include "paddle/phi/common/complex.h"
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#include "paddle/phi/common/place.h"
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#include "paddle/phi/core/compat/convert_utils.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/kernel_registry.h"
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PD_DECLARE_KERNEL(full, CPU, ALL_LAYOUT);
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PD_DECLARE_KERNEL(matmul, CPU, ALL_LAYOUT);
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#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
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PD_DECLARE_KERNEL(full, GPU, ALL_LAYOUT);
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PD_DECLARE_KERNEL(matmul, GPU, ALL_LAYOUT);
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#endif
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namespace paddle {
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namespace tests {
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// TODO(chenweihang): Remove this test after the API is used in the dygraph
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TEST(API, data_transform_same_place) {
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// 1. create tensor
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auto x =
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paddle::experimental::full({3, 3}, 1.0, DataType::COMPLEX128, CPUPlace());
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auto y =
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paddle::experimental::full({3, 3}, 2.0, DataType::FLOAT32, CPUPlace());
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std::vector<phi::dtype::complex<double>> sum(9, 6.0);
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// 2. test API
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auto out = paddle::experimental::matmul(x, y, false, false);
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// 3. check result
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ASSERT_EQ(out.dims().size(), 2);
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ASSERT_EQ(out.dims()[0], 3);
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ASSERT_EQ(out.dims()[1], 3);
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ASSERT_EQ(out.numel(), 9);
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ASSERT_EQ(out.type(), phi::DataType::COMPLEX128);
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ASSERT_EQ(out.layout(), phi::DataLayout::NCHW);
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ASSERT_EQ(out.initialized(), true);
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auto dense_out = std::dynamic_pointer_cast<phi::DenseTensor>(out.impl());
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for (size_t i = 0; i < 9; i++) {
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ASSERT_NEAR(sum[i].real,
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dense_out->data<phi::dtype::complex<double>>()[i].real,
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1e-6f);
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ASSERT_NEAR(sum[i].imag,
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dense_out->data<phi::dtype::complex<double>>()[i].imag,
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1e-6f);
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}
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}
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#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
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TEST(Tensor, data_transform_diff_place) {
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// 1. create tensor
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auto x = paddle::experimental::full(
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{3, 3}, 1.0, phi::DataType::FLOAT64, CPUPlace());
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auto y = paddle::experimental::full(
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{3, 3}, 2.0, phi::DataType::FLOAT64, GPUPlace());
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std::vector<float> sum(9, 6.0);
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// 2. test API
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auto out = paddle::experimental::matmul(x, y, false, false);
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// 3. check result
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ASSERT_EQ(out.dims().size(), 2);
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ASSERT_EQ(out.dims()[0], 3);
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ASSERT_EQ(out.dims()[1], 3);
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ASSERT_EQ(out.numel(), 9);
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ASSERT_EQ(out.dtype(), phi::DataType::FLOAT64);
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ASSERT_EQ(out.layout(), phi::DataLayout::NCHW);
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ASSERT_EQ(out.initialized(), true);
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ASSERT_EQ(out.impl()->place(), phi::TransToPhiPlace(phi::Backend::GPU));
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auto ref_out = experimental::copy_to(out, CPUPlace(), true);
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auto dense_out = std::dynamic_pointer_cast<phi::DenseTensor>(ref_out.impl());
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for (size_t i = 0; i < 9; i++) {
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ASSERT_NEAR(sum[i], dense_out->data<double>()[i], 1e-6f);
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}
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}
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#endif
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} // namespace tests
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} // namespace paddle
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