}
    inputs_.push_back(t->output_);
    *output = tensorflow::down_cast<TracingTensorHandle*>(outputs[0]);
    return absl::OkStatus();
  }

  absl::Status Finalize(OutputList* outputs, AbstractFunction** f) override {
    std::vector<TF_Output> graph_outputs;
    graph_outputs.reserve(outputs->outputs.size());
    for (auto* abstract_output : outputs->outputs) {
      GraphTensor* output = dyn_cast<GraphTensor>(abstract_output);

        assertTrue(output1.contains("|"));

        // Test with less than 16 bytes
        baos.reset();
        byte[] data2 = { 0x41, 0x42, 0x43, 0x44 }; // "ABCD"
        Hexdump.hexdump(ps, data2, 0, 4);
        String output2 = baos.toString();

        assertNotNull(output2);
        assertTrue(output2.contains("00000:"));
        assertTrue(output2.contains(" 41 42 43 44"));

    private String[] newOutputs;

    /**
     * Constructs a new synonym item.
     *
     * @param id      The unique identifier of the item.
     * @param inputs  The input words.
     * @param outputs The output synonyms.
     */
    public SynonymItem(final long id, final String[] inputs, final String[] outputs) {
        this.id = id;
        this.inputs = inputs;
        this.outputs = outputs;

        Thread.sleep(50);

        String output1 = thread.getOutput();
        boolean contains1 = thread.contains("concurrent1");

        thread.join(1000);

        String output2 = thread.getOutput();
        boolean contains2 = thread.contains("concurrent1");

        assertNotNull(output1);
        assertNotNull(output2);
        assertTrue(contains2);
    }

    @Test

  }
  return outputs;
}

void TFOutputsFromOutputs(const std::vector<tensorflow::Output>& outputs,
                          TF_Output* tf_outputs) {
  for (int i = 0; i < outputs.size(); i++) {
    tf_outputs[i].oper = ToOperation(outputs[i].node());
    tf_outputs[i].index = outputs[i].index();
  }
}
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)

  VLOG(1) << "Running the dequeue op";
  TF_Output output{dequeue_op, 0};
  TF_Tensor* ret;
  TF_SessionRun(session, /*run_options*/ nullptr,
                // input related parameters
                /*inputs*/ nullptr, /*input_values*/ nullptr, /*ninputs*/ 0,
                // output related parameters
                /*outputs*/ &output, /*output_values*/ &ret,
                /*noutputs*/ 1,

                         const std::vector<IOSpec>& outputs) {
    const OpDef& signature = fdef.signature();
    ASSERT_EQ(outputs.size(), signature.output_arg_size());
    for (int i = 0; i < outputs.size(); ++i) {
      const OpDef::ArgDef& arg = signature.output_arg(i);
      const IOSpec& out = outputs[i];
      if (out.second != DT_INVALID) {
        ASSERT_EQ(arg.type(), out.second)

 *
 * Usage: java JvmConfigParser.java <jvm.config-path> <maven-project-basedir> [output-file]
 *
 * If output-file is provided, writes result to that file (avoids Windows file locking issues).
 * Otherwise, outputs to stdout.
 *
 * Outputs: Single line with space-separated quoted arguments (safe for batch scripts)
 */
public class JvmConfigParser {

      id: get_file_changes
      uses: trilom/file-changes-action@a6ca26c14274c33b15e6499323aac178af06ad4b # v1.2.4
      with:
        output: ' '
    - name: Report list of changed files
      run: |
        echo Changed files: ${{ steps.get_file_changes.outputs.files }}
    - name: Set up Python 3.9
      uses: actions/setup-python@83679a892e2d95755f2dac6acb0bfd1e9ac5d548 # v6.1.0
      with:

    // Convert back to a C++ Tensor and ensure we get expected output.
    Tensor output;
    ASSERT_EQ(absl::OkStatus(), TF_TensorToTensor(dst, &output)) << line;
    ASSERT_EQ(src.NumElements(), output.NumElements()) << line;
    for (int64_t i = 0; i < src.NumElements(); ++i) {
      ASSERT_EQ(data[i], output.flat<tstring>()(i)) << line;
    }

    TF_DeleteTensor(dst);
  }
}