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@@ -20,6 +20,7 @@ build/ | |
| build_doc/ | ||
| *.user | ||
| *.tmp | ||
| *.pyc | ||
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| .vscode | ||
| .idea | ||
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| // Copyright (c) 2022 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. | ||
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| #include "paddle/fluid/distributed/collective/reducer.h" | ||
| #include "paddle/phi/common/data_type.h" | ||
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| namespace paddle { | ||
| namespace distributed { | ||
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| std::vector<std::vector<size_t>> Eager_AssignGroupBySize( | ||
| const std::vector<Tensor> tensors, | ||
| const std::vector<bool> &is_sparse_gradient, | ||
| const std::vector<size_t> &group_size_limits, | ||
| const std::vector<int64_t> &tensor_indices) { | ||
| PADDLE_ENFORCE_EQ( | ||
| tensors.size(), is_sparse_gradient.size(), | ||
| platform::errors::PreconditionNotMet( | ||
| "tensors len must be equal to is_sparse_gradient len, but " | ||
| "[%lu] != [%lu]", | ||
| tensors.size(), is_sparse_gradient.size())); | ||
| auto check_perm = [](const std::vector<int64_t> &x) -> bool { | ||
| size_t len = x.size(); | ||
| std::vector<size_t> cnt(len, 0); | ||
| for (size_t i = 0; i < len; ++i) { | ||
| if (x[i] >= static_cast<int64_t>(len) || x[i] < 0 || cnt[x[i]]) { | ||
| return false; | ||
| } | ||
| cnt[x[i]]++; | ||
| } | ||
| return true; | ||
| }; | ||
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| PADDLE_ENFORCE_EQ(true, check_perm(tensor_indices), | ||
| platform::errors::PreconditionNotMet( | ||
| "tensor_indices must be a permutation from 0 to %lu", | ||
| tensor_indices.size())); | ||
| // the return vector | ||
| std::vector<std::vector<size_t>> res; | ||
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| // Key: the var type | ||
| // Value: should use which index in group_size_limits for group size limit | ||
| std::map<experimental::DataType, size_t> group_limit_index; | ||
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| // Key: the var type | ||
| // Value: <the var index in input tensors, total numel in this group> | ||
| std::map<experimental::DataType, std::pair<std::vector<size_t>, size_t>> | ||
| next_group; | ||
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| for (size_t i = 0; i < tensors.size(); ++i) { | ||
| const auto &var = tensors[i]; | ||
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| size_t tensor_real_index = i; | ||
| if (!tensor_indices.empty()) { | ||
| tensor_real_index = tensor_indices[i]; | ||
| } | ||
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| if (is_sparse_gradient[tensor_real_index]) { | ||
| // we keep sparse var a single group | ||
| res.push_back({tensor_real_index}); | ||
| continue; | ||
| } | ||
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| const auto &var_dtype = var.dtype(); | ||
| VLOG(3) << "var[" << var.name() << "] 's type is " << var_dtype; | ||
| auto &group_info = next_group[var_dtype]; | ||
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| int64_t var_size = -1; | ||
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| if (var.is_dense_tensor()) { | ||
| var_size = | ||
| std::dynamic_pointer_cast<phi::DenseTensor>(var.impl())->numel(); | ||
| } else { | ||
| VLOG(3) << "var " << var.name() | ||
| << " is not tensor or selected_rows, so skip it"; | ||
| continue; | ||
| } | ||
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| group_info.first.push_back(tensor_real_index); | ||
| group_info.second += experimental::SizeOf(var_dtype) * var_size; | ||
| // group_info.second += framework::SizeOfType(var_dtype) * var_size; | ||
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| if (group_limit_index.find(var_dtype) == group_limit_index.end()) { | ||
| // means it is the first var of var_dtype | ||
| group_limit_index[var_dtype] = 0; | ||
| } | ||
| auto &cur_limit_index = group_limit_index[var_dtype]; | ||
| if (group_info.second >= group_size_limits[cur_limit_index]) { | ||
| // exceed group capacity and create a new group | ||
| res.emplace_back(std::move(group_info.first)); | ||
| group_info = std::pair<std::vector<size_t>, size_t>(); | ||
| cur_limit_index = | ||
| (std::min)(cur_limit_index + 1, group_size_limits.size() - 1); | ||
| } | ||
| } | ||
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| // add the final groups | ||
| for (auto &e : next_group) { | ||
| auto &group_info = e.second; | ||
| if (!group_info.first.empty()) { | ||
| res.emplace_back(std::move(group_info.first)); | ||
| } | ||
| } | ||
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| for (const auto &group_index : res) { | ||
| PADDLE_ENFORCE_NE( | ||
| group_index.empty(), true, | ||
| platform::errors::PreconditionNotMet( | ||
| "AssignGroupBySize construct empty group, please check.")); | ||
| } | ||
| if (tensor_indices.empty()) { | ||
| std::sort(res.begin(), res.end(), | ||
| [](const std::vector<size_t> &x, const std::vector<size_t> &y) { | ||
| return x.front() < y.front(); | ||
| }); | ||
| } | ||
| return res; | ||
| } | ||
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| } // namespace distributed | ||
| } // namespace paddle |
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| @@ -0,0 +1,32 @@ | ||
| // Copyright (c) 2022 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. | ||
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| #pragma once | ||
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| #include <map> | ||
| #include <vector> | ||
| #include "paddle/fluid/distributed/collective/ProcessGroup.h" | ||
| #include "paddle/fluid/eager/api/utils/tensor_utils.h" | ||
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| namespace paddle { | ||
| namespace distributed { | ||
| using Tensor = paddle::experimental::Tensor; | ||
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| std::vector<std::vector<size_t>> Eager_AssignGroupBySize( | ||
| const std::vector<Tensor>, const std::vector<bool>& is_sparse_gradient, | ||
| const std::vector<size_t>& group_size_limits, | ||
| const std::vector<int64_t>& tensor_indices = {}); | ||
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| } // namespace distributed | ||
| } // namespace paddle |
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✅Congratulation! Your pull request passed all required CI. You could ask reviewer(s) to approve and merge. 🎉