%12 = "quantfork.qcast"(%11) {volatile} : (tensor<2x3x1x3xf32>) -> tensor<2x3x1x3x!quant.uniform<i8:f32, 3.000000e-01:1>>
    %13 = "quantfork.dcast"(%12) : (tensor<2x3x1x3x!quant.uniform<i8:f32, 3.000000e-01:1>>) -> tensor<2x3x1x3xf32>
    return %13 : tensor<2x3x1x3xf32>
  }

  // CHECK: quantized_dot_general_fn_1

  %conv2 = "tfl.conv_2d"(%0, %w, %b2) {
    dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "RELU",
    padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32
  } : (tensor<1x5x5x2xf32>, tensor<3x1x1x2xf32>, tensor<3xf32>) -> tensor<1x5x5x3xf32>
  func.return %conv, %conv2 : tensor<1x5x5x3xf32>, tensor<1x5x5x3xf32>

func.func @CheckNumericVerifyMultipleUsers(%arg0: tensor<1x5x5x3xf32>) -> tensor<1x5x5x3xf32> {
  %0 = "tfl.quantize"(%arg0) {qtype = tensor<1x5x5x3x!quant.uniform<i8:f32, 0.1>>, volatile} : (tensor<1x5x5x3xf32>) -> tensor<1x5x5x3x!quant.uniform<i8:f32, 0.1>>
  %1 = "tfl.dequantize"(%0) : (tensor<1x5x5x3x!quant.uniform<i8:f32, 0.1>>) -> tensor<1x5x5x3xf32>