// CHECK-LABEL: CheckNumerics
  // CHECK:  return %arg0 : tensor<3xf32>
}

func.func @placeholder_with_default(%arg0: tensor<3xf32>) -> tensor<3xf32> {
  %0 = "tf.PlaceholderWithDefault"(%arg0): (tensor<3xf32>) -> tensor<3xf32>
  func.return %0 : tensor<3xf32>
  // Should be converted to Identity and then from Identity to value
  // CHECK-LABEL: placeholder_with_default

  let arguments = (ins
  );

  let results = (outs
    TF_Tensor:$output
  );

  TF_DerivedResultTypeAttr dtype = TF_DerivedResultTypeAttr<0>;
}

def TF_PlaceholderWithDefaultOp : TF_Op<"PlaceholderWithDefault", [Pure]> {
  let summary = "Placeholder op";

  let description = [{
    A placeholder op that passes through input when its output is not fed.
  }];

  let arguments = (ins
    TF_Tensor:$input

            "_UnaryOpsComposition", "CollectiveReduceV2",
            "CollectiveAssignGroupV2",
            // The following 5 operations are converted to identity
            "PlaceholderWithDefault", "PreventGradient", "StopGradient",
            "Snapshot", "_EagerConst"}},
          // clang-format off
    {"RED",
     {"All", "Any", "Min", "Max", "Mean", "Prod", "Sum"}},
          // clang-format on

  // control dependencies are not to be executed. For single output nodes,
  // Placeholders can be converted to a NoOp if there are no uses, and
  // PlaceholderWithDefault can be converted to an Identity.
  for (const auto* edge : control_edges) {
    graph_->AddControlEdge(placeholder_node, edge->dst());
    graph_->RemoveControlEdge(edge);
  }

  if (update_inplace) {