"tf.Const"() {device = "", dtype = !tf_type.string, value = dense<""> : tensor<2x!tf_type.string>} : () -> tensor<2x!tf_type.string>

      %outputs_10:8, %control_11 = tf_executor.island wraps "tf.ParseExampleV2"(%arg0, %outputs_4, %outputs_8, %outputs_2, %outputs_6, %outputs, %outputs_0) {Tdense = ["tfdtype$DT_FLOAT", "tfdtype$DT_FLOAT"], dense_shapes = [#tf_type.shape<>, #tf_type.shape<>], device = "", num_sparse = 2 : i64, ragged_split_types = [], ragged_value_types = [], resultSegmentSizes =...

    %0:6 = tf_executor.graph {
      %outputs, %control = tf_executor.island wraps "tf.ReadVariableOp"(%arg2) {device = ""} : (tensor<*x!tf_type.resource>) -> tensor<*xf32>

                                &outputs));
  std::unordered_set<string> expected_inputs = {"input1:0", "input2:0"};
  std::unordered_set<string> expected_outputs = {"output1:0", "output2:0"};
  EXPECT_EQ(expected_inputs, inputs);
  EXPECT_EQ(expected_outputs, outputs);
}

TEST_F(FreezeTest, InputsAndOutputsSparseCooSignatureDef) {
  // Test that inputs and outputs get correctly populated for a

overlapping-outputs-timeline.png...

    }

    /**
     * The way the outputs have been produced.
     */
    enum ExecutionOutcome {
        /**
         * The outputs haven't been changed, because the work is already up-to-date
         * (i.e. its inputs and outputs match that of the previous execution in the
         * same workspace).
         */
        UP_TO_DATE,

        /**
         * The outputs of the work have been loaded from the build cache.

REGISTER_OP("TestThreeInputsOp")
    .Input("x: T")
    .Input("y: T")
    .Input("z: T")
    .Output("output: T")
    .Attr("T: numbertype")
    .Attr("act: {'x', 'y', 'z'} = 'z'");

REGISTER_OP("TestTwoOutputsOp")
    .Input("input: T")
    .Output("output1: T")
    .Output("output2: T")
    .Attr("T: numbertype");

                @InputFiles def inputFiles = project.layout.files()

                @OutputDirectory File outputs1
                @OutputDirectory File outputs2

                @TaskAction void action() {
                    new File(outputs1, "output1.txt").text = "output1"
                    new File(outputs2, "output2.txt").text = "output2"
                }
            }
        """

        buildFile << """

namespace tensorflow {
namespace experimental {
namespace cc {

// SignatureDefFunctionMetadata stores additional information on each input
// and output's names, dtypes, and shape.
class SignatureDefFunctionMetadata final {
  // TODO(bmzhao): Add getters here as necessary.
 private:
  friend class SignatureDefFunction;
  static SignatureDefFunctionMetadata* wrap(

apiVersion: release-notes/v2
kind: feature
area: istioctl
releaseNotes:
  - |

# RUN: not tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -tf-input-arrays=input -tf-input-data-types=DT_FLOAT -tf-input-shapes='' -tf-output-arrays=input:1 -o - 2>&1 | FileCheck %s

# CHECK: Invalid output index 1 specified for node: input

node {
  name: "input"
  op: "Placeholder"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }