func.func @tfInplaceUpdate(%arg0: tensor<2x1x2xf32>) -> tensor<2x1x2xf32> {
  %1 = arith.constant dense<1> : tensor<1xi32>
  %2 = arith.constant dense<2.0> : tensor<1x1x2xf32>
  %3 = "tf.InplaceUpdate"(%arg0, %1, %2) {device = ""}
    : (tensor<2x1x2xf32>, tensor<1xi32>, tensor<1x1x2xf32>) -> tensor<2x1x2xf32>
  func.return %3 : tensor<2x1x2xf32>
}

}

// CHECK-LABEL: @tfInplaceUpdate

module {
func.func @tfInplaceUpdate(%arg0: tensor<2x1x2xf32>) -> tensor<2x1x2xf32> {
  %1 = arith.constant dense<1> : tensor<1xi32>
  %2 = arith.constant dense<2.0> : tensor<1x1x2xf32>
  %3 = "tf.InplaceUpdate"(%arg0, %1, %2) {device = ""}
    : (tensor<2x1x2xf32>, tensor<1xi32>, tensor<1x1x2xf32>) -> tensor<2x1x2xf32>
  func.return %3 : tensor<2x1x2xf32>
}
}

//CHECK: module attributes

module {
func.func @tfInplaceUpdate(%arg0: tensor<2x1x2xf32>) -> tensor<2x1x2xf32> {
  %1 = arith.constant dense<1> : tensor<1xi32>
  %2 = arith.constant dense<2.0> : tensor<1x1x2xf32>
  %3 = "tf.InplaceUpdate"(%arg0, %1, %2) {device = ""}
    : (tensor<2x1x2xf32>, tensor<1xi32>, tensor<1x1x2xf32>) -> tensor<2x1x2xf32>
  func.return %3 : tensor<2x1x2xf32>
}
}

//CHECK: module {

    "FakeQuantWithMinMaxVarsPerChannelGradient",
    "Fill",
    "Fingerprint",
    "Gather",
    "GuaranteeConst",
    "Identity",
    "IdentityN",
    "InplaceAdd",
    "InplaceSub",
    "InplaceUpdate",
    "InvertPermutation",
    "ListDiff",
    "MatrixBandPart",
    "MatrixDiag",
    "MatrixDiagPart",
    "MatrixDiagPartV2",
    "MatrixDiagPartV3",
    "MatrixDiagV2",
    "MatrixDiagV3",

absl::StatusOr<bool> IsSmallConstant(Node* n) {
  if (!n->IsConstant()) {
    return false;
  }

  return IsConstantSmall(n);
}

bool IsInPlaceOp(absl::string_view op_name) {
  return op_name == "InplaceUpdate" || op_name == "InplaceAdd" ||
         op_name == "InplaceSub";
}
}  // namespace

Status CloneConstantsForBetterClusteringPassImpl::CloneSmallConstantInputs(