op_handle_base.h 3.3 KB
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//   Copyright (c) 2018 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.

#pragma once
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#include <map>
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#include <string>
#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 {
namespace framework {
namespace details {

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constexpr char kLocalExecScopeName[] = "@LCOAL_SCOPE@";

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// Wraps ir::Node and provide helper utilities.
// It's responsible for populating necessary fields of ir::Node.
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class OpHandleBase {
 public:
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  explicit OpHandleBase(ir::Node *node) : node_(node) {
    node_->WrappedBy(this);
  }
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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);

  void AddOutput(VarHandleBase *out);

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  // This method adds the wait events of all the input on all the device
  // context.
  // 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
  // context.
  // NODE: This Wait is asynchronous operation.
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  virtual void WaitInputVarGenerated(const platform::Place &place);

  virtual bool NeedWait(VarHandleBase *in_var);

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  // If the Op involves data transfer of multiple devices that
  // will likely block other computations.
  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);
    return it != dev_ctxes_.end() ? it->second : nullptr;
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  }

  void SetDeviceContext(platform::Place place, platform::DeviceContext *ctx_) {
    dev_ctxes_[place] = ctx_;
  }

  const std::vector<VarHandleBase *> &Inputs() const { return inputs_; }

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  size_t NoDupInputSize() const {
    std::unordered_set<VarHandleBase *> res;
    for (auto *var : inputs_) {
      res.emplace(var);
    }
    return res.size();
  }

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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,
                         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_;
  std::vector<VarHandleBase *> outputs_;
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  std::map<platform::Place, platform::DeviceContext *> dev_ctxes_;
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#ifdef PADDLE_WITH_CUDA
  std::unordered_map<int, cudaEvent_t> events_;
#endif

  DISABLE_COPY_AND_ASSIGN(OpHandleBase);
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};

}  // namespace details
}  // namespace framework
}  // namespace paddle