wehub-resource-sync
93 lines
2.6 KiB
Plaintext
93 lines
2.6 KiB
Plaintext
// Copyright (c) 2018 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 <stdio.h>
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#include "gtest/gtest.h"
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#include "paddle/fluid/framework/lod_tensor.h"
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#include "paddle/fluid/platform/init.h"
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#include "paddle/phi/common/place.h"
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__global__ void test(size_t* a, int size) {
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CUDA_KERNEL_LOOP(i, size) { a[i] *= 2; }
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}
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TEST(LoD, data) {
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paddle::framework::InitDevices();
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phi::LegacyLoD lod{{0, 1, 2}};
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lod.push_back({0, 2, 4, 5});
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lod.push_back(std::vector<size_t>({0, 1, 6, 8, 10, 11}));
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auto& v = lod[0];
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phi::MixVector<size_t> mix_vector_v(&v);
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phi::GPUPlace gpu(0);
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#ifdef PADDLE_WITH_HIP
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hipLaunchKernelGGL(test,
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dim3(1),
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dim3(1),
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0,
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0,
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mix_vector_v.CUDAMutableData(gpu),
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v.size());
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hipDeviceSynchronize();
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#else
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test<<<1, 1>>>(mix_vector_v.CUDAMutableData(gpu), v.size());
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cudaDeviceSynchronize();
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#endif
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mix_vector_v.CopyToCPU();
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for (size_t i = 0; i < v.size(); ++i) {
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EXPECT_EQ(v[i], i * 2);
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}
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}
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TEST(DenseTensor, LoDInGPU) {
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paddle::framework::InitDevices();
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phi::DenseTensor lod_tensor;
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phi::GPUPlace place(0);
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phi::LegacyLoD src_lod;
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src_lod.push_back(std::vector<size_t>{0, 2, 4, 6, 8, 10, 12, 14});
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lod_tensor.Resize({14, 16});
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lod_tensor.mutable_data<float>(place);
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lod_tensor.set_lod(src_lod);
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EXPECT_EQ(lod_tensor.lod_element(0, 2).first, 4UL);
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EXPECT_EQ(lod_tensor.lod_element(0, 4).first, 8UL);
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auto lod = lod_tensor.lod();
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phi::MixVector<size_t> mix_vector(&(lod[0]));
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#ifdef PADDLE_WITH_HIP
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hipLaunchKernelGGL(test,
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dim3(1),
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dim3(8),
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0,
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0,
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mix_vector.CUDAMutableData(place),
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lod[0].size());
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hipDeviceSynchronize();
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#else
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test<<<1, 8>>>(mix_vector.CUDAMutableData(place), lod[0].size());
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cudaDeviceSynchronize();
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#endif
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mix_vector.CopyToCPU();
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for (size_t i = 0; i < src_lod[0].size(); ++i) {
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EXPECT_EQ(lod[0].data()[i], src_lod[0].data()[i] * 2);
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}
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}
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