private final ImmutableMap<E, Integer> inputSet;
    private final int mask;

    SubSet(ImmutableMap<E, Integer> inputSet, int mask) {
      this.inputSet = inputSet;
      this.mask = mask;
    }

    @Override
    public Iterator<E> iterator() {
      return new UnmodifiableIterator<E>() {
        final ImmutableList<E> elements = inputSet.keySet().asList();
        int remainingSetBits = mask;

  %result:4 = tf_device.replicate([%arg0, %arg1] as %input0: tensor<*xf32>) {n = 2 : i32} {
    tf_device.return %input0, %arg2 : tensor<*xf32>, tensor<*xi32>
  }
  func.return

// CHECK:      tf_device.replicate
// CHECK-SAME: ([%[[ARG_0]], %[[ARG_1]]] as %[[INPUT_0:[a-z0-9]*]]: tensor<*xf32>)
// CHECK-SAME: n = 2
// CHECK-NEXT:   tf_device.return %[[INPUT_0]], %[[ARG_2]]
}

// -----

    private final ImmutableMap<E, Integer> inputSet;
    private final int mask;

    SubSet(ImmutableMap<E, Integer> inputSet, int mask) {
      this.inputSet = inputSet;
      this.mask = mask;
    }

    @Override
    public Iterator<E> iterator() {
      return new UnmodifiableIterator<E>() {
        final ImmutableList<E> elements = inputSet.keySet().asList();
        int remainingSetBits = mask;

  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteStatus(s);
}

void CSession::SetInputs(
    std::vector<std::pair<TF_Operation*, TF_Tensor*>> inputs) {
  DeleteInputValues();
  inputs_.clear();
  for (const auto& p : inputs) {
    inputs_.emplace_back(TF_Output{p.first, 0});
    input_values_.emplace_back(p.second);
  }
}

void CSession::SetOutputs(std::initializer_list<TF_Operation*> outputs) {

  std::unordered_set<string> inputs;
  std::unordered_set<string> outputs;
  TF_ASSERT_OK(FreezeSavedModel(saved_model_bundle, &frozen_graph_def, &inputs,
                                &outputs));
  EXPECT_EQ(expected_inputs, inputs);
  EXPECT_EQ(expected_outputs, outputs);
}

TEST_F(FreezeTest, InputsAndOutputsMultipleSignatureDefs) {
  // Test that inputs and outputs get correctly merged and populated when

FIELD com.google.common.collect.ImmutableRangeSet.ranges
FIELD com.google.common.collect.ImmutableSet.asList
FIELD com.google.common.collect.Maps.FilteredMapValues.unfiltered
FIELD com.google.common.collect.Sets.SubSet.inputSet
FIELD com.google.common.collect.SingletonImmutableBiMap.inverse
FIELD com.google.common.collect.TreeTraverser.PostOrderNode.childIterator
FIELD com.google.common.collect.TreeTraverser.PreOrderIterator.stack

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>

# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -tf-input-arrays=input -tf-input-shapes='' -tf-output-arrays=input -tf-convert-legacy-fed-inputs -o - | FileCheck --check-prefix=NODATATYPE %s

# Verify that invalid LegacyFedInput ops without any inputs are replaced with
# Placeholder ops.

  TF_Session* mutable_session() { return session_; }

 private:
  void DeleteInputValues();
  void ResetOutputValues();

  TF_Session* session_;
  std::vector<TF_Output> inputs_;
  std::vector<TF_Tensor*> input_values_;
  std::vector<TF_Output> outputs_;
  std::vector<TF_Tensor*> output_values_;
  std::vector<TF_Operation*> targets_;
};

// RUN: tf-opt -split-input-file -verify-diagnostics -tf-tpu-annotate-dynamic-shape-inputs %s | FileCheck %s

// Test that annotate the inputs of the cluster func to be dynamic shaped.

module attributes {tf.devices = ["/job:worker/replica:0/task:0/device:CPU:0", "/job:worker/replica:0/task:0/device:TPU_SYSTEM:0", "/job:worker/replica:0/task:0/device:TPU:0"]} {
   func.func @main(
      %arg0: tensor<2048xi64> {tf.device = "/job:localhost/replica:0/task:0/device:CPU:0"},