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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/10946 ``` codemod -d . --extensions cc,cpp,cu,cuh,h caffe2/proto/caffe2.pb.h caffe2/proto/caffe2_pb.h ``` Reviewed By: houseroad Differential Revision: D9539945 fbshipit-source-id: 497d04720e8e7e61c05ffe1b23733d0cb774de7e
52 lines
1.3 KiB
C++
52 lines
1.3 KiB
C++
#ifndef CAFFE2_CORE_NET_SIMPLE_ASYNC_H_
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#define CAFFE2_CORE_NET_SIMPLE_ASYNC_H_
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#include <vector>
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#include "caffe2/core/common.h"
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#include "caffe2/core/logging.h"
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#include "caffe2/core/net.h"
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#include "caffe2/core/registry.h"
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#include "caffe2/core/tensor.h"
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#include "caffe2/core/workspace.h"
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#include "caffe2/proto/caffe2_pb.h"
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namespace caffe2 {
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// This is the very basic structure you need to run a network - all it
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// does is simply to run everything in sequence. If you want more fancy control
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// such as a DAG-like execution, check out other better net implementations.
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class AsyncSimpleNet : public NetBase {
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public:
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AsyncSimpleNet(const std::shared_ptr<const NetDef>& net_def, Workspace* ws);
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bool SupportsAsync() override {
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return true;
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}
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/*
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* This returns a list of pointers to objects stored in unique_ptrs.
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* Used by Observers.
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*
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* Think carefully before using.
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*/
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vector<OperatorBase*> GetOperators() const override {
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vector<OperatorBase*> op_list;
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for (auto& op : operators_) {
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op_list.push_back(op.get());
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}
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return op_list;
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}
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protected:
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bool DoRunAsync() override;
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vector<unique_ptr<OperatorBase>> operators_;
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AT_DISABLE_COPY_AND_ASSIGN(AsyncSimpleNet);
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};
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} // namespace caffe2
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#endif // CAFFE2_CORE_NET_SIMPLE_ASYNC_H_
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