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neilisaac / torch   python

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Version: 1.8.0 

/ include / caffe2 / core / net_simple.h

#ifndef CAFFE2_CORE_NET_SIMPLE_H_
#define CAFFE2_CORE_NET_SIMPLE_H_

#include <vector>

#include "c10/util/Registry.h"
#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/net.h"
#include "caffe2/core/tensor.h"
#include "caffe2/core/workspace.h"
#include "caffe2/proto/caffe2_pb.h"

namespace caffe2 {

// This is the very basic structure you need to run a network - all it
// does is simply to run everything in sequence. If you want more fancy control
// such as a DAG-like execution, check out other better net implementations.
class TORCH_API SimpleNet : public NetBase {
 public:
  SimpleNet(const std::shared_ptr<const NetDef>& net_def, Workspace* ws);
  bool SupportsAsync() override {
    return false;
  }

  vector<float> TEST_Benchmark(
      const int warmup_runs,
      const int main_runs,
      const bool run_individual) override;

  /*
   * This returns a list of pointers to objects stored in unique_ptrs.
   * Used by Observers.
   *
   * Think carefully before using.
   */
  vector<OperatorBase*> GetOperators() const override {
    vector<OperatorBase*> op_list;
    for (auto& op : operators_) {
      op_list.push_back(op.get());
    }
    return op_list;
  }

 protected:
  bool Run() override;
  bool RunAsync() override;

  vector<unique_ptr<OperatorBase>> operators_;

  C10_DISABLE_COPY_AND_ASSIGN(SimpleNet);
};

} // namespace caffe2

#endif // CAFFE2_CORE_NET_SIMPLE_H_