// CHECK-LABEL: depthwiseConv2D
// CHECK-DAG:  %[[CONSTANT:.*]] = arith.constant dense<0.000000e+00> : tensor<12xf32>
// CHECK-DAG:  %[[CONSTANT0:.*]] = arith.constant dense<[1, 3, 3, 12]> : tensor<4xi32>
// CHECK:  %0 = "tf.Reshape"(%arg1, %[[CONSTANT0]]) : (tensor<3x3x3x4xf32>, tensor<4xi32>) -> tensor<1x3x3x12xf32>

  %4 = "tfl.dequantize"(%3) : (tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>) -> tensor<32x3x3x3xf32>

                                     Type result_type, Value input,
                                     Value filter, Value bias) const {
    // Compared to tfl.conv_2d, tfl.depthwise_conv_2d has an additional
    // 'depth_multiplier' attribute. However, tf.DepthwiseConv2dNative does not
    // have a corresponding 'depth_multiplier' attribute; the multiplier is the

    if (!function_name.starts_with("quantized_") &&
        !function_name.starts_with("composite_")) {
      return failure();
    }

    if (function_name.contains("depthwise_conv2d")) {
      return addReshapeOpToDepthwiseWeight(call_op, rewriter);
    }

    return failure();
  }
};

// Prints a summary about the quantization results.
class QuantizationSummary {