graph_evaluator.h

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#pragma once
#include "computation_graph/raw_memory_object.h"
#include "library_defines.h"
#include "ml_core/callbacks.h"
#include "public_ops.h"
#ifdef BLACE_AI_TORCH_INTERFACE
#include <ATen/core/TensorBody.h>
#endif
#include <filesystem>
#include <memory>
#ifdef BLACE_AI_OPENCV_INTERFACE
#include <opencv2/core/mat.hpp>
#endif
 
namespace blace {
class NodeOp;
}
 
namespace blace {
namespace computation_graph {
struct GraphEvaluatorImpl;
 
class EXPORT_OR_IMPORT GraphEvaluator {
public:
  GraphEvaluator(blace::ops::OpP node, bool is_in_worker = false);
 
  void to_dot_file(const std::filesystem::path &filename);
 
  std::string to_dot_string();
 
#ifdef BLACE_AI_OPENCV_INTERFACE
  std::pair<ml_core::ReturnCode, cv::Mat> evaluateToCVMat();
#endif
 
  std::pair<ml_core::ReturnCode, std::string> evaluateToString();
 
  std::pair<ml_core::ReturnCode, std::vector<int64_t>> evaluateToIntList();
 
  std::pair<ml_core::ReturnCode, std::shared_ptr<RawMemoryObject>>
  evaluateToRawMemory(
      std::shared_ptr<ml_core::ProgressCallback> progress_callback = nullptr);
 
#ifdef BLACE_AI_TORCH_INTERFACE
  bool has_all_required_data();
 
  std::vector<int64_t> missing_data_frames();
 
  // at::Tensor evaluateToTorchTensor(
  //     std::shared_ptr<ml_core::ProgressCallback> progress_callback =
  //     nullptr);
  std::pair<ml_core::ReturnCode, at::Tensor> evaluateToTorchTensor(
      std::shared_ptr<ml_core::ProgressCallback> progress_callback = nullptr);
#endif
 
  ~GraphEvaluator();
 
private:
  std::unique_ptr<GraphEvaluatorImpl> _impl;
  bool is_in_worker;
};
} // namespace computation_graph
} // namespace blace