EXPECT_EQ("Tensor<type: float shape: [2,3] values: [1 2 3][4 5 6]>",
            output->DebugString(100));
}

REGISTER_OP("DoNothingOp")
    .Input("input1: float")
    .Input("input2: float")
    .Attr("NumInput3: int >= 0")
    .Input("input3: NumInput3 * float")
    .Output("output1: float")
    .Attr("SomeDataTypeAttr: type");

TEST_F(DeviceKernelOpTest, TestGetKernelInfo) {

// RUN: tac-translate -input-mlir -output-mlir -device-specs=GPU %s -o - 2>&1 | FileCheck %s

module {
func.func @main(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>, %arg2: tensor<1xf32>, %arg3: tensor<1xf32>) -> tensor<2x1xf32> attributes {tf.entry_function = {inputs = "input0,input1,input2,input3", outputs = "output"}} {
  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function = "RELU6"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>

  std::vector<TFE_TensorHandle*> compute_fn_inputs;
  TFE_TensorHandle* input_a = TestScalarTensorHandle(ctx, 2.0f);
  TFE_TensorHandle* input_b = TestScalarTensorHandle(ctx, 1.0f);
  compute_fn_inputs.push_back(input_a);
  compute_fn_inputs.push_back(input_b);

  TFE_Op* compute_fn_op = TF_ConcreteFunctionMakeCallOp(

  }

  // Builds a SignatureDef with the provided `inputs` and `outputs`.
  SignatureDef BuildSignatureDef(const std::unordered_set<string>& inputs,
                                 const std::unordered_set<string>& outputs) {
    SignatureDef signature_def;
    for (const string& input : inputs) {
      (*signature_def.mutable_inputs())[input].set_name(input);
    }
    for (const string& output : outputs) {

        file("input.txt").createNewFile()
        file("input-nested.txt").createNewFile()
        file("input1.txt").createNewFile()
        file("input2.txt").createNewFile()
        file("inputs").createDir()
        file("inputs/inputA.txt").createNewFile()
        file("inputs/inputB.txt").createNewFile()
        file("inputs1").createDir()
        file("inputs2").createDir()

        buildFile """

// CHECK: func @add(
// CHECK-SAME: {tf_saved_model.index_path = ["input1"]}
// CHECK-SAME: {tf_saved_model.index_path = ["input2"]}
// CHECK-SAME: {tf_saved_model.index_path = ["result"]}
// CHECK-SAME: tf.entry_function = {inputs = "input1:0,input2:0", outputs = "result:0"}
// CHECK-SAME: tf_saved_model.exported_names = ["add"]

// CHECK: func @sub(
// CHECK-SAME: {tf_saved_model.index_path = ["input2"]}
// CHECK-SAME: {tf_saved_model.index_path = ["input1"]}

  func.func @add(%arg0: tensor<?xf32> {tf_saved_model.index_path = ["input1"]}, %arg1: tensor<?xf32> {tf_saved_model.index_path = ["input2"]}) -> (tensor<?xf32> {tf_saved_model.index_path = ["result"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "input1:0,input2:0", outputs = "result:0"}, tf_saved_model.exported_names = ["add"]} {

        
        input2 = getResourceFile("2.txt")
        output2 = signing.signatureType.fileFor(input2)
        input2Artifact = new DefaultPublishArtifact(input2.name, "Text File", "txt", null, null, input2)
        
        [output1, output2].each { output ->
            assert !output.exists() || output.delete()
        }
        
        assert input1.text && input2.text  // don't care what it is, just need some
    }
    

package hash_test

import (
	"bytes"
	"crypto/sha256"
	"encoding"
	"fmt"
	"log"
)

func Example_binaryMarshaler() {
	const (
		input1 = "The tunneling gopher digs downwards, "
		input2 = "unaware of what he will find."
	)

	first := sha256.New()
	first.Write([]byte(input1))

	marshaler, ok := first.(encoding.BinaryMarshaler)
	if !ok {
		log.Fatal("first does not implement encoding.BinaryMarshaler")
	}

        connection.queueIncoming(input1)
        connection.queueIncoming(input2)
        connection.queueIncoming(closeInput)
        received.await()
        daemonConnection.stop()

        then:
        1 * handler.onInput(input1)
        1 * handler.onInput(input2)
        1 * handler.onEndOfInput() >> { received.countDown() }
        0 * handler._
    }