// CHECK-DAG: %[[INPUT_QINT:.*]] = "tf.Cast"(%arg0) <{Truncate = false}> : (tensor<1x2x2x1xi32>) -> tensor<1x2x2x1x!tf_type.qint32>
  // CHECK: "tf.UniformQuantizedClipByValue"(%[[INPUT_QINT]], %[[MIN_QINT]], %[[MIN_QINT]]
  %output = "tf.UniformQuantizedClipByValue"(%arg0, %q_min, %q_min, %scale, %zp)
    {quantization_axis = -1 : i64, quantization_max_val = 2147483647 : i64, quantization_min_val = -2147483648 : i64} :

        tensor<f32>, tensor<i32>) -> tensor<3x2x!tf_type.qint32>
  func.return %0 : tensor<3x2x!tf_type.qint32>
}

//===----------------------------------------------------------------------===//
// tf.UniformQuantizedClipByValue legalization
//===----------------------------------------------------------------------===//

// -----

// CHECK-LABEL: func @uniform_quantized_clip_by_value

        quantization_axis = -1 : i64, quantization_min_val = -2147483648 : i64, quantization_max_val = 2147483647 : i64
      } : (tensor<f32>, tensor<f32>, tensor<i32>) -> tensor<!tf_type.qint32>

      %1 = "tf.UniformQuantizedClipByValue"(%0, %qmin, %qmax, %scales, %zps) {
        quantization_axis = -1 : i64, quantization_min_val = -2147483648 : i64, quantization_max_val = 2147483647 : i64

    %qclip_max = "tf.Cast"(%i32_max_filled) {Truncate = false} : (tensor<*xi32>) -> tensor<*x!tf_type.qint32>
    %relu = "tf.UniformQuantizedClipByValue"(%input, %qclip_min, %qclip_max, %input_scale, %input_zp) {
      T = "tfdtype$DT_QINT32",
      quantization_axis = -1,
      quantization_min_val = -2147483648,
      quantization_max_val = 2147483647,

      "ToBool",
      "TridiagonalSolve",
      "TridiagonalMatMul",
      "TruncatedNormal",
      "UniformDequantize",
      "UniformQuantize",
      "UniformQuantizedAdd",
      "UniformQuantizedClipByValue",
      "UniformQuantizedConvolution",
      "UniformQuantizedDot",
      "UniformRequantize",
      "Unique",
      "UniqueV2",
      "UpperBound",
      "UnsortedSegmentMax",

    %scales: tensor<2xf32>, %zps: tensor<i32>) -> () {
  // expected-error @below {{'tf.UniformQuantizedClipByValue' op quantization_axis is -1, scales must have 0 rank.}}
  %0 = "tf.UniformQuantizedClipByValue"(%operand, %min, %max, %scales, %zps) {
    quantization_axis = -1 : i64,
    quantization_min_val = -2147483648 : i64,
    quantization_max_val = 2147483647 : i64

  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;

  let hasVerifier = 1;
}

def TF_UniformQuantizedClipByValueOp : TF_Op<"UniformQuantizedClipByValue", [Pure]> {
  let summary = "Perform clip by value on the quantized Tensor `operand`.";

  let description = [{