case tensorflow::DT_QINT32:
        return 32;
      default:
        return 0;
    }
  }

  // Whether to add the NumericVerify ops to verify numbers before and after
  // quantization.
  bool verify_numeric = false;
  // Whether to add verification for layer by layer, or on whole model. When
  // disabled (per-layer) float and quantized ops will be run from same input

    // fixed_point = clamp(clamp_min, clamp_max, (
    //   roundHalfToEven(expressed / scale) + zero_point))
    APFloat scaled = (expressed_value / scale_);
    scaled.roundToIntegral(round_mode_);
    scaled.add(zero_point_, round_mode_);
    APFloat fixed_point = llvm::minimum(scaled, clamp_max_);
    fixed_point = llvm::maximum(fixed_point, clamp_min_);

    llvm::APSInt result(storage_bit_width_, !is_signed_);

      for (const auto& enumerated_result :
           llvm::enumerate(candidate_op->getResults())) {
        Value result = enumerated_result.value();
        Type result_type = result.getType();
        // Add this to the test coverage once we create test ops with none type
        // results.
        if (mlir::isa<NoneType>(result_type)) {
          outputs_replaced.insert({result, enumerated_result.index()});

// Monitoring Sampler APIs.
// These APIs de-templated monitoring Sampler for swig.

typedef struct TFE_MonitoringSamplerCell TFE_MonitoringSamplerCell;

// Atomically add the value of the cell.
TF_CAPI_EXPORT extern void TFE_MonitoringSamplerCellAdd(
    TFE_MonitoringSamplerCell* cell, double value);

// Retrieves the current value of the cell. The return value is a HistogramProto