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Paddle/paddle/fluid/imperative/tests/test_group.cc

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// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include <sstream>
#include <string>
#include "gtest/gtest.h"
#include "paddle/fluid/imperative/reducer.h"
namespace paddle {
namespace imperative {
TEST(TestGroup, TestPrintGroupMessage) {
Group group;
std::stringstream stream1, stream2;
stream1 << group;
ASSERT_STREQ(stream1.str().c_str(),
"numel: 0 ;is_sparse: 0 ;var number: 0\n[]\n");
std::vector<size_t> vars;
size_t vars_num = 102;
for (size_t i = 0; i < vars_num; ++i) {
vars.push_back(i);
}
group.variable_indices_ = vars;
group.all_length_ = 102;
group.is_sparse_ = false;
std::string head = "numel: 102 ;is_sparse: 0 ;var number: 102\n";
head = head + "[";
auto begin = vars.begin();
auto end = vars.end();
for (int i = 0; begin != end && i < 100; ++i, ++begin) {
if (i > 0) head += ' ';
head += std::to_string(*begin);
}
if (begin != end) {
head += " ...";
}
head += "]\n";
stream2 << group;
ASSERT_STREQ(stream2.str().c_str(), head.c_str());
}
template <typename T, typename Place>
void GroupConcatSplit(Place place, size_t size) {
platform::CPUPlace cpu_place;
Group group;
// [[0.0], [0.0, 1.0], [0.0, 1.0, 2.0] .. ]
std::vector<framework::Variable> vars;
vars.resize(size);
for (size_t i = 0; i < size; ++i) {
auto len = i + 1;
auto* tensor = vars[i].GetMutable<framework::LoDTensor>();
tensor->Resize({static_cast<int64_t>(len)});
auto* data = tensor->mutable_data<T>(place);
std::vector<T> value;
for (size_t j = 0; j < len; ++j) {
value.push_back(static_cast<T>(1.0 * j));
}
if (std::is_same<Place, platform::CUDAPlace>::value) {
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
paddle::memory::Copy(place, data, cpu_place, value.data(),
sizeof(T) * value.size(), 0);
#endif
} else {
paddle::memory::Copy(place, data, cpu_place, value.data(),
sizeof(T) * value.size());
}
framework::Tensor tmp;
tmp.ShareDataWith(*tensor).Resize({static_cast<int64_t>(len)});
group.dense_tensors_.push_back(std::move(tmp));
group.all_length_ += len;
group.dtype_ = tensor->type();
}
paddle::platform::DeviceContextPool& pool =
paddle::platform::DeviceContextPool::Instance();
auto* dev_ctx = pool.Get(place);
{ // concat
auto* tensor = group.dense_contents_.GetMutable<framework::LoDTensor>();
tensor->Resize(framework::make_ddim({group.all_length_}))
.mutable_data(place, group.dtype_);
group.ConcatTensors(*dev_ctx);
group.DivNRanks(*dev_ctx, 1);
framework::Tensor tmp;
framework::TensorCopySync(*tensor, cpu_place, &tmp);
auto* data = tmp.data<T>();
size_t offset = 0;
for (size_t i = 0; i < size; ++i) {
auto len = i + 1;
for (size_t j = 0; j < len; ++j) {
EXPECT_EQ(data[offset + j], static_cast<T>(1.0 * j));
// [[-0.0], [-0.0, -1.0], [-0.0, -1.0, -2.0] .. ]
data[offset + j] = -data[offset + j];
}
offset += len;
}
framework::TensorCopySync(tmp, place, tensor);
}
{ // split
group.SplitTensors(*dev_ctx);
for (size_t i = 0; i < size; ++i) {
auto len = i + 1;
auto& tensor = group.dense_tensors_[i];
framework::Tensor tmp;
framework::TensorCopySync(tensor, cpu_place, &tmp);
auto* data = tmp.data<T>();
for (size_t j = 0; j < len; ++j) {
EXPECT_EQ(data[j], static_cast<T>(-1.0 * j));
}
}
}
}
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
TEST(TestGroup, TestConcatSplit) {
platform::CUDAPlace cuda_place(0);
platform::CPUPlace cpu_place;
int size = 3;
GroupConcatSplit<float>(cpu_place, size);
GroupConcatSplit<double>(cpu_place, size);
GroupConcatSplit<platform::float16>(cpu_place, size);
GroupConcatSplit<float>(cuda_place, size);
GroupConcatSplit<double>(cuda_place, size);
GroupConcatSplit<platform::float16>(cuda_place, size);
size = 15;
GroupConcatSplit<float>(cpu_place, size);
GroupConcatSplit<double>(cpu_place, size);
GroupConcatSplit<platform::float16>(cpu_place, size);
GroupConcatSplit<float>(cuda_place, size);
GroupConcatSplit<double>(cuda_place, size);
GroupConcatSplit<platform::float16>(cuda_place, size);
}
TEST(TestGroup, TestConcatSplitException) {
platform::CUDAPinnedPlace place;
int size = 3;
ASSERT_ANY_THROW(GroupConcatSplit<float>(place, size));
}
#endif
#if defined(PADDLE_WITH_XPU_BKCL)
TEST(TestGroup, TestXPUConcatSplit) {
platform::XPUPlace xpu_place(0);
platform::CPUPlace cpu_place;
int size = 3;
GroupConcatSplit<float>(cpu_place, size);
GroupConcatSplit<float>(xpu_place, size);
size = 15;
GroupConcatSplit<float>(cpu_place, size);
GroupConcatSplit<float>(xpu_place, size);
}
#endif
} // namespace imperative
} // namespace paddle