)
    # Insert fake quant to simulate a QAT model.
    weight = array_ops.fake_quant_with_min_max_args(
        weight, min=-0.1, max=0.2, num_bits=8, narrow_range=False
    )

    # shape: (2, 2)
    output_tensor = math_ops.matmul(matmul_input, weight)
    # Insert fake quant to simulate a QAT model.
    output_tensor = array_ops.fake_quant_with_min_max_args(
        output_tensor, min=-0.2, max=0.2, num_bits=8, narrow_range=False

  // CHECK: return [[VAL8]] : tensor<1x8x2xf32>
  func.return %2 : tensor<1x8x2xf32>
}

func.func @fake_quant_with_min_max_args(%arg0 : tensor<?x?xf32>) -> tensor<?x?xf32> {
  // CHECK-DAG: [[VAL0:%.+]] = "tf.Const"() <{value = dense<1.275000e+02> : tensor<f32>}>
  // CHECK-DAG: [[VAL1:%.+]] = "tf.Const"() <{value = dense<1.00392163> : tensor<f32>}>