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119 lines
3.4 KiB
119 lines
3.4 KiB
// 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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#pragma once
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#include <map>
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/details/var_handle.h"
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#include "paddle/fluid/framework/ir/node.h"
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#include "paddle/fluid/platform/device_context.h"
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#include "paddle/fluid/platform/macros.h"
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namespace paddle {
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namespace framework {
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namespace details {
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constexpr char kLocalExecScopeName[] = "@LCOAL_SCOPE@";
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// Wraps ir::Node and provide helper utilities.
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// It's responsible for populating necessary fields of ir::Node.
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class OpHandleBase {
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public:
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// Owned by `node`. No need to be deleted explicitly.
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explicit OpHandleBase(ir::Node *node) : node_(node) {
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node_->WrappedBy(this);
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}
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virtual ~OpHandleBase();
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std::string DebugString() const;
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virtual std::string Name() const = 0;
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void Run(bool use_cuda);
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virtual void RecordWaitEventOnCtx(platform::DeviceContext *waited_ctx);
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void AddInput(VarHandleBase *in);
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void AddOutput(VarHandleBase *out);
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// This method adds the wait events of all the input on all the device
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// context.
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// NODE: This Wait is asynchronous operation.
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virtual void WaitInputVarGenerated();
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// This method adds the wait events of all the input on the specified device
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// context.
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// NODE: This Wait is asynchronous operation.
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virtual void WaitInputVarGenerated(const platform::Place &place);
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virtual bool NeedWait(VarHandleBase *in_var);
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// If the Op involves data transfer of multiple devices that
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// will likely block other computations.
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virtual bool IsMultiDeviceTransfer() { return false; }
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const platform::DeviceContext *DeviceContext(platform::Place place) {
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auto it = dev_ctxes_.find(place);
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return it != dev_ctxes_.end() ? it->second : nullptr;
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}
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void SetDeviceContext(platform::Place place, platform::DeviceContext *ctx_) {
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dev_ctxes_[place] = ctx_;
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}
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const std::vector<VarHandleBase *> &Inputs() const { return inputs_; }
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size_t NoDupInputSize() const {
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std::unordered_set<VarHandleBase *> res;
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for (auto *var : inputs_) {
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res.emplace(var);
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}
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return res.size();
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}
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size_t NotReadyInputSize() const;
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const std::vector<VarHandleBase *> &Outputs() const { return outputs_; }
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size_t NoDummyInputSize() const;
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ir::Node *Node() { return node_; }
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protected:
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void RunAndRecordEvent(const std::function<void()> &callback);
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void RunAndRecordEvent(platform::Place p,
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const std::function<void()> &callback);
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virtual void RunImpl() = 0;
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ir::Node *node_;
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std::vector<VarHandleBase *> inputs_;
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std::vector<VarHandleBase *> outputs_;
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std::map<platform::Place, platform::DeviceContext *> dev_ctxes_;
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#ifdef PADDLE_WITH_CUDA
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std::unordered_map<int, cudaEvent_t> events_;
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#endif
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DISABLE_COPY_AND_ASSIGN(OpHandleBase);
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};
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} // namespace details
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} // namespace framework
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} // namespace paddle
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