"istio.io/istio/pkg/config/schema/collections"
	"istio.io/istio/pkg/config/schema/resource"
)

func ConvertInputsToSchemas(inputs []config.GroupVersionKind) collection.Schemas {
	resultBuilder := collection.NewSchemasBuilder()
	for _, gv := range inputs {
		s, f := collections.All.FindByGroupVersionKind(gv)
		if !f {
			continue
		}
		_ = resultBuilder.Add(s)
	}

	return resultBuilder.Build()
}

// 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.

      (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,

	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{
		{},

                def output = file("build/task-a/output.txt")
                inputs.file input
                outputs.file output
                outputs.cacheIf { true }
                doFirst action
            }

            task taskB {
                def output = file("build/task-b/output.txt")
                inputs.file input
                outputs.file output
                outputs.cacheIf { true }

    private final boolean allMustSucceed;
    protected final ImmutableList<ClosingFuture<?>> inputs;

    private Combiner(boolean allMustSucceed, Iterable<? extends ClosingFuture<?>> inputs) {
      this.allMustSucceed = allMustSucceed;
      this.inputs = ImmutableList.copyOf(inputs);
      for (ClosingFuture<?> input : inputs) {
        input.becomeSubsumedInto(closeables);
      }
    }

    /**

                                             const char* prefix2 = nullptr) {
    TF_Output inputs[2];
    TF_Output outputs[1];
    TF_Output grad_outputs[2];

    BuildSuccessGraph(inputs, outputs);

    AddGradients(false, prefix1, inputs, 2, outputs, 1, grad_outputs);
    if (prefix2 != nullptr) {
      AddGradients(false, prefix2, inputs, 2, outputs, 1, grad_outputs);
    }
  }

  TF_Status* s_;

  func.func @serving_default(%arg0: tensor<1x20x20x28xf32> {tf_saved_model.index_path = ["a"]}) -> (tensor<1x40x40x28xf32> {tf_saved_model.index_path = ["b"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "c:0", outputs = "d:0"}, tf_saved_model.exported_names = ["serving_default"]} {
      %c = stablehlo.constant dense<40> : tensor<2xi32>