#include "tensorflow/core/platform/types.h"

namespace tensorflow {

// Represents the results of the execution of an operation.
struct OutputList {
  std::vector<AbstractTensorHandle*> outputs;
  int expected_num_outputs = -1;
};

namespace tracing {

// =============================================================================
// Implementation detail for the unified execution APIs for Eager and tracing

    abstract Provider<FileSystemLocation> getArtifact()

    @Override
    void transform(TransformOutputs outputs) {
        File artifactFile = artifact.get().asFile
        if (artifactFile.name == 'gradle-dependencies') {
            (artifactFile.listFiles() as List<File>).sort { it.name }.each {
                outputs.file(it)
            }
        }
    }

          context: ./tensorflow/tools/tf_sig_build_dockerfiles
          target: devel
          build-args: |
            PYTHON_VERSION=${{ matrix.python-version }}
            CACHEBUSTER=${{ steps.date.outputs.DATE }}
          tags: |
            gcr.io/tensorflow-sigs/build:${{ github.event.number }}-${{ matrix.python-version }}

        requestBody.put(KEY_PROPERTY, keyProp);
        requestBody.put("outputs", "output");
        return requestBody;
    }

    @Override
    protected Map<String, Object> getUpdateMap() {
        final Map<String, Object> updateMap = new HashMap<>();
        updateMap.put("outputs", "new_outputs");
        return updateMap;
    }

    @Test
    void crudTest() {

                                    <tr>
                                        <th><la:message key="labels.dict_synonym_target"/></th>
                                        <td>${f:br(f:h(outputs))}<la:hidden property="outputs"/></td>
                                    </tr>
                                    </tbody>
                                </table>
                            </div>

  std::vector<tensorflow::Output> outputs(n);
  for (int i = 0; i < n; ++i) {
    outputs[i] =
        tensorflow::Output(&tf_outputs[i].oper->node, tf_outputs[i].index);
  }
  return outputs;
}

void TFOutputsFromOutputs(const std::vector<tensorflow::Output>& outputs,
                          TF_Output* tf_outputs) {
  for (int i = 0; i < outputs.size(); i++) {

  explicit CSession(TF_Session* session);

  ~CSession();

  void SetInputs(std::vector<std::pair<TF_Operation*, TF_Tensor*>> inputs);
  void SetOutputs(std::initializer_list<TF_Operation*> outputs);
  void SetOutputs(const std::vector<TF_Output>& outputs);
  void SetTargets(std::initializer_list<TF_Operation*> targets);

  void Run(TF_Status* s);

  void CloseAndDelete(TF_Status* s);

    TF_Output inputs[2];
    TF_Output outputs[1];
    TF_Output grad_outputs[2];

    BuildSuccessGraph(inputs, outputs);

    AddGradients(false, prefix1, inputs, 2, outputs, 1, grad_outputs);
    if (prefix2 != nullptr) {
      AddGradients(false, prefix2, inputs, 2, outputs, 1, grad_outputs);
    }
  }

  TF_Status* s_;
  TF_Graph* graph_;

    public String dictId;

    @ValidateTypeFailure
    public Integer crudMode;

    @Required
    @Size(max = 1000)
    public String inputs;

    @Required
    @Size(max = 1000)
    public String outputs;

    public void initialize() {
        crudMode = CrudMode.CREATE;
    }

                return matchOutput;
            }

            pendingOutput = fst.outputs.add(pendingOutput, scratchArc.output());

            if (scratchArc.isFinal()) {
                matchOutput = fst.outputs.add(pendingOutput, scratchArc.nextFinalOutput());
                longestMatchEndOffset = start + index + Character.charCount(codePoint);
            }