c.Env = append(os.Environ(), "CGO_ENABLED=0")
	if output, err := c.CombinedOutput(); err != nil {
		t.Logf("go build -o %s read3.go\n%s", exe, output)
		t.Fatalf("go build failed: %v", err)
	}

	// Use a deadline to try to get some output even if the program hangs.
	ctx := context.Background()
	if deadline, ok := t.Deadline(); ok {
		// Leave a 20% grace period to flush output, which may be large on the

        Args:
          input_tensor: Input tensor to matmul with the filter.

        Returns:
          A 'output' -> output tensor mapping
        """
        out = math_ops.matmul(input_tensor, random_tensor_gen_fn((2, 3)))
        out = math_ops.matmul(out, random_tensor_gen_fn((3, 4)))
        return {'output': out}

    model = TwoMatmulModel()
    input_shape = (1, 2)

    save.save(
        model,

      )

      inputs = {'input_vocabs': input_vocabs_placeholder}
      outputs = {
          'lookup': lookup_tensor,
          'output': output_tensor,
      }

      self._save_tf1_model(
          sess,
          output_path,
          signature_def_key,
          tags,
          inputs=inputs,
          outputs=outputs,
          init_op=lookup_ops.tables_initializer(),

	cmd.Flags().StringVarP(pf.OutputFormat, "output", "o", *pf.OutputFormat, fmt.Sprintf("Output format. One of: %s.", strings.Join(pf.AllowedFormats(), "|")))
	cmd.Flags().StringVarP(pf.OutputFormat, "experimental-output", "", *pf.OutputFormat, fmt.Sprintf("Output format. One of: %s.", strings.Join(pf.AllowedFormats(), "|")))
	_ = cmd.Flags().MarkDeprecated("experimental-output", "please use --output instead.")
}

John Howard <******@****.***> 1717524306 -0700

          inputs={'x1': in_placeholder_1}, outputs={'output1': output_tensor_1}
      )

      in_placeholder_2, output_tensor_2 = self._create_simple_tf1_conv_model()
      sig_def_2 = signature_def_utils_impl.predict_signature_def(
          inputs={'x2': in_placeholder_2}, outputs={'output2': output_tensor_2}
      )

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

  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);

        "same location"        | null           | "file"     | "output.txt"               | "output.txt"
        "consuming ancestor"   | null           | "file"     | "build/dir/sub/output.txt" | "build/dir"
        "consuming descendant" | 'build/dir'    | "dir"      | "build/dir/sub/output.txt" | "build/dir/sub/output.txt"
    }

  func.func @main() {
// CHECK: arith.constant
// CHECK: TPUCompile
// CHECK: TPUExecute
// CHECK-NOT: func @_func
    tf_executor.graph {
      %outputs, %control = tf_executor.island wraps "arith.constant"() {value = dense<2.000000e+00> : tensor<f32>} : () -> tensor<f32>

            "max": [0.5]
          }
        }
      ],
      "inputs": [0],
      "outputs": [24],
      "operators": [
        {
          "inputs": [
            0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
          ],
          "outputs": [24],
          "intermediates": [
            25, 26, 27, 28, 29
          ],