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      with Licensor regarding such Contributions.

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      with Licensor regarding such Contributions.

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      the terms of any separate license agreement you may have executed
      with Licensor regarding such Contributions.

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      names, trademarks, service marks, or product names of the Licensor,
      except as required for reasonable and customary use in describing the
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      the terms of any separate license agreement you may have executed
      with Licensor regarding such Contributions.

   6. Trademarks. This License does not grant permission to use the trade
      names, trademarks, service marks, or product names of the Licensor,
      except as required for reasonable and customary use in describing the
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      the terms of any separate license agreement you may have executed
      with Licensor regarding such Contributions.

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                c_outputs, target_oper_names, run_metadata, status);
}

void TF_PRunSetup(TF_DeprecatedSession* s,
                  // Input names
                  const char** c_input_names, int ninputs,
                  // Output names
                  const char** c_output_names, int noutputs,
                  // Target nodes
                  const char** c_target_oper_names, int ntargets,

  // but is not limited to get, list, watch, create, update, patch,
  // delete, deletecollection, and proxy).
  // +listType=set
  repeated string verbs = 5;

  // shortNames is a list of suggested short names of the resource.
  // +listType=set
  repeated string shortNames = 6;

  // categories is a list of the grouped resources this resource belongs to (e.g. 'all').

// graph_def.library().gradient()
std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def);

// Returns a sorted vector of names contained in `grad_def`
std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def);

class CSession {
 public:
  CSession(TF_Graph* graph, TF_Status* s, bool use_XLA = false);