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185 lines
5.3 KiB
185 lines
5.3 KiB
// Copyright (c) 2020 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 <sstream>
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#include <string>
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#include "gtest/gtest.h"
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#include "paddle/fluid/imperative/reducer.h"
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namespace paddle {
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namespace imperative {
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TEST(TestGroup, TestPrintGroupMessage) {
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Group group;
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std::stringstream stream1, stream2;
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stream1 << group;
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ASSERT_STREQ(stream1.str().c_str(),
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"numel: 0 ;is_sparse: 0 ;var number: 0\n[]\n");
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std::vector<size_t> vars;
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size_t vars_num = 102;
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for (size_t i = 0; i < vars_num; ++i) {
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vars.push_back(i);
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}
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group.variable_indices_ = vars;
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group.all_length_ = 102;
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group.is_sparse_ = false;
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std::string head = "numel: 102 ;is_sparse: 0 ;var number: 102\n";
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head = head + "[";
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auto begin = vars.begin();
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auto end = vars.end();
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for (int i = 0; begin != end && i < 100; ++i, ++begin) {
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if (i > 0) head += ' ';
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head += std::to_string(*begin);
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}
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if (begin != end) {
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head += " ...";
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}
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head += "]\n";
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stream2 << group;
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ASSERT_STREQ(stream2.str().c_str(), head.c_str());
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}
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template <typename T, typename Place>
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void GroupConcatSplit(Place place, size_t size) {
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platform::CPUPlace cpu_place;
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Group group;
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// [[0.0], [0.0, 1.0], [0.0, 1.0, 2.0] .. ]
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std::vector<framework::Variable> vars;
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vars.resize(size);
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for (size_t i = 0; i < size; ++i) {
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auto len = i + 1;
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auto* tensor = vars[i].GetMutable<framework::LoDTensor>();
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tensor->Resize({static_cast<int64_t>(len)});
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auto* data = tensor->mutable_data<T>(place);
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std::vector<T> value;
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for (size_t j = 0; j < len; ++j) {
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value.push_back(static_cast<T>(1.0 * j));
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}
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if (std::is_same<Place, platform::CUDAPlace>::value) {
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#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
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paddle::memory::Copy(place, data, cpu_place, value.data(),
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sizeof(T) * value.size(), 0);
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#endif
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} else {
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paddle::memory::Copy(place, data, cpu_place, value.data(),
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sizeof(T) * value.size());
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}
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framework::Tensor tmp;
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tmp.ShareDataWith(*tensor).Resize({static_cast<int64_t>(len)});
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group.dense_tensors_.push_back(std::move(tmp));
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group.all_length_ += len;
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group.dtype_ = tensor->type();
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}
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paddle::platform::DeviceContextPool& pool =
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paddle::platform::DeviceContextPool::Instance();
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auto* dev_ctx = pool.Get(place);
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{ // concat
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auto* tensor = group.dense_contents_.GetMutable<framework::LoDTensor>();
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tensor->Resize(framework::make_ddim({group.all_length_}))
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.mutable_data(place, group.dtype_);
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group.ConcatTensors(*dev_ctx);
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group.DivNRanks(*dev_ctx, 1);
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framework::Tensor tmp;
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framework::TensorCopySync(*tensor, cpu_place, &tmp);
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auto* data = tmp.data<T>();
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size_t offset = 0;
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for (size_t i = 0; i < size; ++i) {
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auto len = i + 1;
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for (size_t j = 0; j < len; ++j) {
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EXPECT_EQ(data[offset + j], static_cast<T>(1.0 * j));
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// [[-0.0], [-0.0, -1.0], [-0.0, -1.0, -2.0] .. ]
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data[offset + j] = -data[offset + j];
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}
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offset += len;
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}
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framework::TensorCopySync(tmp, place, tensor);
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}
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{ // split
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group.SplitTensors(*dev_ctx);
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for (size_t i = 0; i < size; ++i) {
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auto len = i + 1;
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auto& tensor = group.dense_tensors_[i];
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framework::Tensor tmp;
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framework::TensorCopySync(tensor, cpu_place, &tmp);
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auto* data = tmp.data<T>();
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for (size_t j = 0; j < len; ++j) {
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EXPECT_EQ(data[j], static_cast<T>(-1.0 * j));
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}
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}
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}
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}
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#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
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TEST(TestGroup, TestConcatSplit) {
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platform::CUDAPlace cuda_place(0);
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platform::CPUPlace cpu_place;
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int size = 3;
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GroupConcatSplit<float>(cpu_place, size);
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GroupConcatSplit<double>(cpu_place, size);
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GroupConcatSplit<platform::float16>(cpu_place, size);
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GroupConcatSplit<float>(cuda_place, size);
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GroupConcatSplit<double>(cuda_place, size);
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GroupConcatSplit<platform::float16>(cuda_place, size);
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size = 15;
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GroupConcatSplit<float>(cpu_place, size);
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GroupConcatSplit<double>(cpu_place, size);
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GroupConcatSplit<platform::float16>(cpu_place, size);
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GroupConcatSplit<float>(cuda_place, size);
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GroupConcatSplit<double>(cuda_place, size);
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GroupConcatSplit<platform::float16>(cuda_place, size);
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}
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TEST(TestGroup, TestConcatSplitException) {
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platform::CUDAPinnedPlace place;
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int size = 3;
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ASSERT_ANY_THROW(GroupConcatSplit<float>(place, size));
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}
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#endif
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#if defined(PADDLE_WITH_XPU_BKCL)
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TEST(TestGroup, TestXPUConcatSplit) {
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platform::XPUPlace xpu_place(0);
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platform::CPUPlace cpu_place;
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int size = 3;
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GroupConcatSplit<float>(cpu_place, size);
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GroupConcatSplit<float>(xpu_place, size);
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size = 15;
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GroupConcatSplit<float>(cpu_place, size);
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GroupConcatSplit<float>(xpu_place, size);
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}
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#endif
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} // namespace imperative
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} // namespace paddle
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