quant_specs.inference_type = tensorflow::DT_HALF;
  }

  const quant::QuantPassSpec quant_params = {
      {quant_specs.verify_numeric, error_tolerance_,
       quant_specs.whole_model_verify, enable_log_if_failed_},
      quant_specs};

  populateWithGenerated(patterns);

  if (quant_specs.weight_quantization || quant_specs.use_fake_quant_num_bits ||
      quant_specs.qdq_conversion_mode ==

      Option<"enable_whole_model_verify_", "whole-model-verify",
             "bool", "false",
             "Whether verify numericals layer by layer or whole model. Valid when `-numeric-verify` is set.">,
      Option<"enable_log_if_failed_", "log-if-failed",
             "bool", "false",
             "Whether verify numericals with thresholding tolerance. Valid when `-numeric-verify` is set.">,

  quant_specs_.weight_quantization = weight_quantization_;
  const QuantPassSpec quant_params = {
      {quant_specs_.verify_numeric, /*error_tolerance=*/5.0f,
       quant_specs_.whole_model_verify, /*enable_log_if_failed=*/false},
      quant_specs_};

  if (quant_specs_.weight_quantization) {
    patterns.add<TFDynamicRangeQuantization>(ctx, quant_params);
  } else {