// information to the abstract model and/or elevating k8s
// representation to first-class type to avoid extra conversions.

func parseInputsImpl(inputs string, withValidate bool) ([]config.Config, []IstioKind, error) {
	var varr []config.Config
	var others []IstioKind
	reader := bytes.NewReader([]byte(inputs))
	empty := IstioKind{}

	// We store configs as a YaML stream; there may be more than one decoder.

  func.func @gather_with_float_output(%arg0: tensor<1x3x2x1024xf32> {tf_saved_model.index_path = ["input1"]}, %arg1: tensor<1xi32> {tf_saved_model.index_path = ["input2"]}) -> (tensor<1x3x1x1xf32> {tf_saved_model.index_path = ["output"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_input:0", outputs = "PartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {

  func.return %r : tensor<i32>
}

// -----

// Test inputs to the child streams are merged to the parent streams

// CHECK-LABEL: func private @main_stream_1
// CHECK-SAME: ([[INPUT0:%.*]]: tensor<i32>, [[INPUT1:%.*]]: tensor<i32>
// CHECK: tf.Sub
// CHECK: tf.Sub
// CHECK: mlrt.async({{%.*}}, [[INPUT1]]

// CHECK-LABEL: func @main

      (BinaryOp (TFL_ReshapeOp:$lhs $input1, (Arith_ConstantOp:$shape1 $s1)),
                (TFL_ReshapeOp:$rhs $input2, (Arith_ConstantOp:$shape2 $s2))),
      (TFL_ReshapeOp (BinaryOp $input1, $input2), $shape1),
      [(IsTailOfShape $rhs, $lhs),
       (IsTailOfShape $lhs, $rhs),
       (IsTailOfShape $input1, $input2),
       (IsTailOfShape $input2, $input1),
       (SameElementType $input1, $input2)]>;

    // expected-error @+1 {{'tf.TPUReplicatedInput' op TF2XLA TPU bridge input check: number of inputs inconsistent. num_replicas=2 no. of inputs=3}}
    %ri, %c0 = tf_executor.island wraps "tf.TPUReplicatedInput"(%arg0, %arg1, %arg1) {index = 1 : i64, is_mirrored_variable = false, is_packed = false} : (tensor<i32>, tensor<i32>, tensor<i32>) -> tensor<i32>

  auto loc =
      mlir::FileLineColLoc::get(context, input->getBufferIdentifier(), 0, 0);
  std::vector<std::string> inputs;
  std::vector<std::string> outputs;
  return tflite::FlatBufferToMlir(
      absl::string_view(input->getBufferStart(), input->getBufferSize()),
      context, loc, false, inputs, outputs, false);
}

}  // namespace

std::string FlatBufferFileToMlir(const std::string& model_file_or_buffer,

  props.set_assigned_device(std::move(assigned_device));
  return props;
}

impl::NodeMatcherProperties impl::Inputs(
    absl::Span<const ::testing::Matcher<OutEdge>> inputs) {
  std::vector<::testing::Matcher<OutEdge>> inputs_vector;
  absl::c_copy(inputs, std::back_inserter(inputs_vector));

  impl::NodeMatcherProperties props;
  props.set_inputs(std::move(inputs_vector));
  return props;
}

	meta := analysis.Metadata{
		Name:        "webhook.Analyzer",
		Description: "Checks the validity of Istio webhooks",
		Inputs: []config.GroupVersionKind{
			gvk.MutatingWebhookConfiguration,
		},
	}
	if !a.SkipServiceCheck {
		meta.Inputs = append(meta.Inputs, gvk.Service)
	}
	return meta
}

func getNamespaceLabels() []klabels.Set {
	return []klabels.Set{
		{},

func.func private @tensor_list_type_array_like() -> !tfr.tensor_list<[N, T]>

// -----

// CHECK-LABEL: tensor_list_type_tuple_like
func.func private @tensor_list_type_tuple_like() -> !tfr.tensor_list<input_T>

// -----

// expected-error@+1 {{unbalanced '[' character in pretty dialect name}}
func.func private @tensor_invalid_1() -> !tfr.tensor<[N, T>

// -----

// expected-error@+1 {{unbalanced}}

name: Comment Docs Preview in PR
description: Comment with the docs URL preview in the PR
author: Sebastián Ramírez <******@****.***>
inputs:
  token:
    description: Token for the repo. Can be passed in using {{ secrets.GITHUB_TOKEN }}
    required: true
  deploy_url:
    description: The deployment URL to comment in the PR
    required: true
runs:
  using: docker