wehub-resource-sync
80 lines
2.6 KiB
C++
80 lines
2.6 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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/lib/utils/allocator.h"
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#include "paddle/phi/backends/context_pool.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/common/place.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/device_context.h"
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#include "paddle/phi/kernels/memcpy_kernel.h"
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namespace phi {
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namespace tests {
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using DDim = phi::DDim;
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#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
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TEST(DEV_API, memcpy_d2h) {
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// 1. create tensor
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const auto cpu_alloc =
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std::make_unique<paddle::experimental::DefaultAllocator>(phi::CPUPlace());
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phi::DenseTensor x_cpu(cpu_alloc.get(),
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phi::DenseTensorMeta(phi::DataType::FLOAT32,
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common::make_ddim({3, 2, 2, 3}),
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phi::DataLayout::NCHW));
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auto& pool = phi::DeviceContextPool::Instance();
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auto* cpu_ctx = pool.GetByPlace(phi::CPUPlace());
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auto* x_cpu_data = cpu_ctx->template Alloc<float>(&x_cpu);
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for (int i = 0; i < x_cpu.numel(); i++) {
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x_cpu_data[i] = static_cast<float>(i);
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}
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const auto alloc =
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std::make_unique<paddle::experimental::DefaultAllocator>(phi::GPUPlace());
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phi::DenseTensor x;
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// 2. test API
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auto* dev_ctx = pool.GetByPlace(phi::GPUPlace());
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phi::MemcpyH2DKernel<phi::GPUContext>(*dev_ctx, x_cpu, 1, &x);
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phi::DenseTensor out;
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phi::MemcpyD2HKernel<phi::GPUContext>(*dev_ctx, x, 1, &out);
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// 3. check result
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std::vector<int64_t> expect_shape = {12, 3};
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ASSERT_EQ(out.dims(), x.dims());
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ASSERT_EQ(out.meta().dtype, phi::DataType::FLOAT32);
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ASSERT_EQ(out.meta().layout, phi::DataLayout::NCHW);
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bool value_equal = true;
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auto* dense_out_data = out.data<float>();
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for (int i = 0; i < x_cpu.numel(); i++) {
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if (x_cpu_data[i] != dense_out_data[i]) {
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value_equal = false;
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break;
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}
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}
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ASSERT_EQ(value_equal, true);
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}
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#endif
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} // namespace tests
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} // namespace phi
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