%0 = "tf.Cast"(%arg0) : (tensor<1x3x2x2xi8>) -> tensor<1x3x2x2xi32>
    %1 = "tf.Sub"(%0, %arg2) : (tensor<1x3x2x2xi32>, tensor<i32>) -> tensor<1x3x2x2xi32>
    %2 = "tf.Cast"(%1) : (tensor<1x3x2x2xi32>) -> tensor<1x3x2x2xf32>
    %3 = "tf.Mul"(%2, %arg1) : (tensor<1x3x2x2xf32>, tensor<f32>) -> tensor<1x3x2x2xf32>
    return %3 : tensor<1x3x2x2xf32>
  }

        version = 5 : i64
      } : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>, tensor<1x1x1x2xf32>) -> tensor<1x3x4x2xf32>
    %2 = "quantfork.stats"(%1) {layerStats = dense<[5.00000000e-6, 7.00000000e-1]> : tensor<2xf32>} : (tensor<1x3x4x2xf32>) -> tensor<1x3x4x2xf32>
    return %2 : tensor<1x3x4x2xf32>
  }
// CHECK: func.func private @quantize_conv_with_bias_fn(%[[ARG_0:.+]]: tensor<1x3x4x3xf32>) -> tensor<1x3x4x2xf32> attributes {tf._original_func_name = "main_0"}

  %cst = arith.constant dense<[1, 3, 3, 2]> : tensor<4xi32>
  %cst_2 = arith.constant dense<[2, 3, 0, 1]> : tensor<4xi32>
  %2 = "tf.Transpose"(%arg, %cst_2) : (tensor<2x1x3x3xf32>, tensor<4xi32>) -> tensor<3x3x2x1xf32>
  %3 = "tf.Reshape"(%2, %cst) : (tensor<3x3x2x1xf32>, tensor<4xi32>) -> tensor<1x3x3x2xf32>
  return %3: tensor<1x3x3x2xf32>