^bb0(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>):
  %0 = "tf.SquaredDifference"(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
  %1 = "tf.Relu6"(%0) : (tensor<1xf32>) -> tensor<1xf32>
  func.return %1: tensor<1xf32>

// CHECK-LABEL: squaredDifferenceRelu
// CHECK:  tfl.squared_difference %arg0, %arg1 : tensor<1xf32>
// CHECK:  %1 = "tfl.relu6"(%0) : (tensor<1xf32>) -> tensor<1xf32>

    }
    void $cppClass::print(OpAsmPrinter &p) {
      return printOneResultOp(getOperation(), p);
    }
  }];

  let hasOptions = 1;
}

def TFL_SquaredDifferenceOp : TFL_Op<"squared_difference", [
    TFL_OperandsHaveSameShapesOrBroadcastableShape<[0, 1], 4>,
    BinaryOpSameElementTypeConstraint,
    TFL_SameFirstOperandAndFirstResultElementType,
    ResultsBroadcastableShape,

  %0 = "tfl.squared_difference"(%arg0, %arg1) : (tensor<1x80x128x!quant.uniform<i8:f32, 0.089839041233062744:10>>, tensor<1x80x128x!quant.uniform<i8:f32, 0.0019308560295030475:-6>>) -> tensor<1x80x128x!quant.uniform<i8:f32, 0.60070550441741943:-128>>

        `tf.math.segment_min`, `tf.math.segment_prod`, `tf.math.segment_sum`,
        `tf.math.sin`, `tf.math.sinh`, `tf.math.softplus`, `tf.math.softsign`,
        `tf.math.squared_difference`, `tf.math.tan`,
        `tf.math.unsorted_segment_max`, `tf.math.unsorted_segment_min`,
        `tf.math.unsorted_segment_prod`, `tf.math.unsorted_segment_sum`,
        `tf.math.zeta`.

    }
  }];
}

def TF_SquaredDifferenceOp : TF_Op<"SquaredDifference", [Commutative, Pure, ResultsBroadcastableShape]>,
                             WithBroadcastableBinOpBuilder {
  let summary = "Returns conj(x - y)(x - y) element-wise.";

  let description = [{
*NOTE*: `SquaredDifference` supports broadcasting. More about broadcasting