%cst = stablehlo.constant dense<0.000000e+00>: tensor<10x1024x3xf32>

        output.contains 'Output: nested.outputFiles$2 [output-nested-2.txt]'
        output.contains 'Output: outputDirectories$1 [outputs1]'
        output.contains 'Output: outputDirectories$2 [outputs2]'
        output.contains "Output: outputDirectory [outputs]"
        output.contains "Output: outputFile [output.txt]"
        output.contains 'Output: outputFiles$1 [output1.txt]'

                            const std::vector<Output>& outputs,
                            const std::vector<Output>& inputs,
                            std::vector<Output>* grad_outputs) {
  std::vector<Output> grad_inputs;
  grad_inputs.reserve(outputs.size());
  for (const Output& output : outputs) {
    grad_inputs.emplace_back(ops::OnesLike(scope, output));
  }

                }
                outputs.files files(fileList) withPropertyName("out")
                def output1 = project.file("build/output1.txt")
                def output2 = project.file("build/output2.txt")
                doLast {
                    output1.parentFile.mkdirs()
                    output1 << "data"
                    if (!System.getProperty("changedCardinality")) {

// WholeModel-DAG: "tf.DumpTensor"(%[[output1]]) <{enabled = true, file_name = "unquantized_tensor_data.pb", func_name = "conv", log_dir_path = "/tmp/dumps/composite_conv2d_with_bias_and_relu6_fn_1", node_name = "Conv2D_1"}> : (tensor<*xf32>) -> ()
// WholeModel-DAG: return %[[output0]], %[[output1]]

// IntPerLayer-LABEL: func @conv
// IntPerLayer-DAG: %[[w:.*]] = "tf.Const"() <{value = dense<{{\[\[\[\[}}1.600000e-01, 1.000000e-01

  %output_1 = "tf.TensorArrayGatherV3"(%handle_3, %indices, %res_1#3) {device = "/job:localhost/replica:0/task:0/device:CPU:0", element_shape = #tf_type.shape<?x512>} : (tensor<2x!tf_type.resource<tensor<?x512xf32>>>, tensor<?xi32>, tensor<f32>) -> tensor<?x?x512xf32>
  func.return %output_0, %output_1 : tensor<?x?x512xf32>, tensor<?x?x512xf32>
}

  TF_OpDefinitionBuilderAddInput(builder, "input1: uint8");
  TF_OpDefinitionBuilderAddInput(builder, "input2: uint32");
  TF_OpDefinitionBuilderAddOutput(builder, "output1: uint8");
  TF_OpDefinitionBuilderAddOutput(builder, "output2: uint8");
  TF_OpDefinitionBuilderSetShapeInferenceFunction(
      builder, &TF_ShapeInferenceContextSetUnknownShape);
  TF_Status* status = TF_NewStatus();

        %0 = tf_executor.graph {
          %output_0, %control_0 = tf_executor.island wraps "tf.Const"() <{value = dense<1.0> : tensor<1x2xf32>}> : () -> tensor<1x2xf32>

type ActionID [HashSize]byte

// An OutputID is a cache output key, the hash of an output of a computation.
type OutputID [HashSize]byte

// Cache is the interface as used by the cmd/go.
type Cache interface {
	// Get returns the cache entry for the provided ActionID.
	// On miss, the error type should be of type *entryNotFoundError.
	//
	// After a success call to Get, OutputFile(Entry.OutputID) must

	}
	if copy(e.OutputID[:], res.OutputID) != len(res.OutputID) {
		return Entry{}, &entryNotFoundError{errors.New("incomplete ProgResponse OutputID")}
	}
	c.noteOutputFile(e.OutputID, res.DiskPath)
	return e, nil
}

func (c *ProgCache) noteOutputFile(o OutputID, diskPath string) {
	c.mu.Lock()
	defer c.mu.Unlock()
	c.outputFile[o] = diskPath
}