TF_Bool aggressive_shape_inference, TF_Bool include_input_tensor_values,
    TF_Bool include_output_tensor_values, TF_Status* s);

// Get the size of input OpInfo::TensorProperties given node name.
TF_CAPI_EXPORT extern void TF_GetInputPropertiesListSize(
    TF_GraphProperties* graph_properties, const char* name, int* num_values,
    TF_Status* status);

//
// The caller retains ownership of `input_values` (which can be deleted using
// TF_DeleteTensor). The caller also retains ownership of `run_options` and/or
// `run_metadata` (when not NULL) and should manually call TF_DeleteBuffer on
// them.
//
// On success, the tensors corresponding to outputs[0,noutputs-1] are placed in
// output_values[]. Ownership of the elements of output_values[] is transferred

                                                    const char* value,
                                                    TF_Status* status);

// Get configuration key and value using coordination service.
// The config key must be set before getting its value. Getting value of
// non-existing config keys will result in errors.
// If `timeout_in_ms=0`, this call will block until the key-value is set or the
// worker shuts down.

  /// found, call `compute_func`. If `compute_func` set `status` to `TF_OK`,
  /// store a copy of the output parameter in the cache, and another copy in
  /// `value`.
  void LookupOrCompute(const std::string& key, T* value,
                       const ComputeFunc& compute_func, TF_Status* status) {
    if (max_age_ == 0) {
      return compute_func(key, value, status);
    }

                                int num_values) = 0;
  virtual Status SetAttrTypeList(const char* attr_name, const DataType* values,
                                 int num_values) = 0;
  virtual Status SetAttrBoolList(const char* attr_name,
                                 const unsigned char* values,
                                 int num_values) = 0;
  virtual Status SetAttrShapeList(const char* attr_name, const int64_t** dims,

                         const void* const* values, const size_t* lengths,
                         int num_values, ForwardOperation*);
Status SetAttrFloatList(AbstractOperation*, const char* attr_name,
                        const float* values, int num_values, ForwardOperation*);
Status SetAttrIntList(AbstractOperation*, const char* attr_name,
                      const int64_t* values, int num_values, ForwardOperation*);

                                                  const float* values,
                                                  int num_values);
TF_CAPI_EXPORT extern void TFE_OpSetAttrBoolList(TFE_Op* op,
                                                 const char* attr_name,
                                                 const unsigned char* values,
                                                 int num_values);

  TF_Tensor* output_tensor(int i) { return output_values_[i]; }

  TF_Session* mutable_session() { return session_; }

 private:
  void DeleteInputValues();
  void ResetOutputValues();

  TF_Session* session_;
  std::vector<TF_Output> inputs_;
  std::vector<TF_Tensor*> input_values_;
  std::vector<TF_Output> outputs_;
  std::vector<TF_Tensor*> output_values_;
  std::vector<TF_Operation*> targets_;
};

    auto device_value = absl::make_unique<DataType>();
    *device_value = values[device_index];
    std::unique_ptr<TF_Tensor, decltype(&TF_DeleteTensor)> tensor(
        TF_NewTensor(
            datatype_enum, /*dims=*/nullptr, /*num_dims=*/0,
            device_value.release(), sizeof(DataType),
            [](void* data, size_t, void* arg) {
              delete reinterpret_cast<DataType*>(data);
            },

// read current values from streamz counters defined in other modules.
//
// The code under test will have created streamz counters like this:
// auto* streamz = tensorflow::monitoring::Counter<1>::New("name",
// "description", "label");
// and then incremented that counter for various values of label:
// streamz->GetCell("label-value")->IncrementBy(1);
//