wehub-resource-sync
110 lines
3.5 KiB
C++
110 lines
3.5 KiB
C++
// Copyright (c) 2024 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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#pragma once
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#include <algorithm>
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#include <chrono>
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#include <memory>
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#include <numeric>
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#include <optional>
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#include <string>
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#include <unordered_map>
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#include <vector>
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#include "paddle/common/errors.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/core/distributed/collective/process_group.h"
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#include "paddle/phi/core/distributed/types.h"
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#include "paddle/phi/core/distributed/utils.h"
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#include "paddle/phi/core/enforce.h"
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namespace paddle {
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namespace distributed {
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using phi::distributed::AllreduceOptions;
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using phi::distributed::BarrierOptions;
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using phi::distributed::BroadcastOptions;
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using phi::distributed::CommType;
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using phi::distributed::GatherOptions;
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using phi::distributed::GetPartialTensor;
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using phi::distributed::ReduceOp;
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using phi::distributed::ReduceOptions;
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using phi::distributed::ReduceScatterOptions;
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using phi::distributed::ScatterOptions;
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constexpr int kIgnoreId = -1;
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using phi::distributed::ProcessGroup;
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using phi::distributed::ProcessGroupIdMap;
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using phi::distributed::ProcessGroupMapFromGid;
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static void CheckTensorContiguous(const DenseTensor& tensor) {
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if (!tensor.meta().is_contiguous()) {
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PADDLE_THROW(
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common::errors::InvalidArgument("The tensor must be contiguous"));
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}
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}
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static void CheckTensorContiguous(const std::vector<DenseTensor>& inputs) {
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for (const auto& tensor : inputs) {
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if (!tensor.meta().is_contiguous()) {
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PADDLE_THROW(
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common::errors::InvalidArgument("The tensor must be contiguous"));
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}
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}
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}
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static void CheckTensorSamePlace(const std::vector<DenseTensor>& tensors) {
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for (const auto& tensor : tensors) {
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if (tensor.place() != tensors[0].place()) {
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PADDLE_THROW(
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common::errors::InvalidArgument("The tensors must be in the same "
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"place"));
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}
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}
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}
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static std::vector<int64_t> GetAllToAllSplitSizes(
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const std::vector<DenseTensor>& tensors) {
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std::vector<int64_t> split_sizes(tensors.size());
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std::transform(tensors.begin(),
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tensors.end(),
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split_sizes.begin(),
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[](const DenseTensor& tensor) { return tensor.numel(); });
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return split_sizes;
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}
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static std::vector<const void*> GetTensorPtrs(
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const std::vector<DenseTensor>& tensors) {
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std::vector<const void*> tensor_ptrs(tensors.size());
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std::transform(tensors.begin(),
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tensors.end(),
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tensor_ptrs.begin(),
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[](const DenseTensor& tensor) { return tensor.data(); });
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return tensor_ptrs;
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}
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static int64_t GetTensorNumel(const std::vector<DenseTensor>& tensors) {
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return std::accumulate(tensors.begin(),
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tensors.end(),
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int64_t(0),
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[](int64_t sum, const DenseTensor& tensor) {
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return sum + tensor.numel();
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});
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}
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} // namespace distributed
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} // namespace paddle
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