const std::string dir = testing::TmpDir();
  const std::string output_file_path = io::JoinPath(dir, "statistics.pbtxt");

  TF_CHECK_OK(NodeDefBuilder("op", "CalibrationStatisticsSaver")
                  .Input(inputs)
                  .Attr("ids", ids)
                  .Attr("calibration_methods", calibration_methods)
                  .Attr("output_file_path", output_file_path)
                  .Finalize(node_def()));

      absl::Nonnull<OpKernelConstruction*> context)
      : OpKernel(context) {
    std::string output_file_path;
    OP_REQUIRES_OK(context,
                   context->GetAttr("output_file_path", &output_file_path));
    OP_REQUIRES_OK(context, context->env()->NewWritableFile(output_file_path,
                                                            &output_file_));

  // CHECK-SAME: is_stateless = false

  // CHECK: "tf.CalibrationStatisticsSaver"
  // CHECK-SAME: output_file_path = "serving_default_0.pb"

  // CHECK: "tf.CalibrationStatisticsSaver"
  // CHECK-SAME: output_file_path = "serving_default_1.pb"

  // CHECK: "tf.CalibrationStatisticsSaver"
  // CHECK-SAME: output_file_path = "serving_default_2.pb"

  }
}

// Inserts a `CalibrationStatisticsSaverOp` to the end of the region.
LogicalResult InsertCalibrationStatisticsSaverOp(
    Region& region, MLIRContext& ctx, absl::string_view output_file_path,
    const std::unordered_set<std::string>& aggregator_ops_to_ignore) {
  SmallVector<Value> statistics_outputs;
  SmallVector<StringRef> ids;
  SmallVector<int32_t> calibration_methods;

// CHECK: "tf.CalibrationStatisticsSaver"(%[[MIN_1]], %[[MAX_1]], %[[HISTOGRAM_1]])
// CHECK-SAME: <{calibration_methods = [5 : i32], ids = ["keeping_id"], output_file_path = "serving_default_0.pb"}>  : (tensor<f32>, tensor<f32>, tensor<512xi64>) -> ()
// CHECK: return

// -----

  let summary = "Aggregates and saves calibration statistics.";

  let arguments = (ins
    Variadic<TensorOf<[TF_Float32, TF_Int64]>>:$inputs,

    StrAttr:$output_file_path,
    StrArrayAttr:$ids,
    I32ArrayAttr:$calibration_methods
  );

  TF_DerivedOperandTypeListAttr Tin = TF_DerivedOperandTypeListAttr<0>;
}

def TF_DumpTensorOp : TF_Op<"DumpTensor", []> {

    DSYMUTIL("dsymutil", Lists.<String>newArrayList("-f"), ".dwarf") {
        @Override
        public List<String> getInputOutputFileArguments(String inputFilePath, String outputFilePath) {
            return Lists.newArrayList("-o", outputFilePath, inputFilePath);
        }
    };

    private static final OperatingSystem OS = OperatingSystem.current();

    private final String executable;

		return "", err
	}

	templateFile := GetEffectiveTemplatePath(i.Metadata.ProxyConfig)

	outputFilePath := configFile(i.Metadata.ProxyConfig.ConfigPath, templateFile)
	outputFile, err := os.Create(outputFilePath)
	if err != nil {
		return "", err
	}
	defer func() { _ = outputFile.Close() }()

	// Write the content of the file.

		// Fall back to the "real" path if PrintPath is not set
		outputFilePath := file.PrintPath
		if len(outputFilePath) == 0 {
			outputFilePath = file.RealPath
		}

		fmt.Fprintf(w, "[dryrun] Would write file %q with content:\n", outputFilePath)
		apiclient.PrintBytesWithLinePrefix(w, fileBytes, "\t")
	}
	return errorsutil.NewAggregate(errs)
}

                }
            }

            tasks.register<MyTask>("myTask") {
                input = "Hello world"
                output = File("$outputFilePath")
            }
            """.trimIndent()
        )
        return File(outputFilePath)
    }

    private
    fun withSettingsWithAssignment() {
        withSettings("""
            import org.gradle.kotlin.dsl.support.serviceOf