}
	}
}

// check that getmac exists as a powershell command, and that it
// speaks English.
func checkGetmac(t *testing.T) {
	out, err := runCmd("getmac", "/?")
	if err != nil {
		if strings.Contains(err.Error(), "term 'getmac' is not recognized as the name of a cmdlet") {
			t.Skipf("getmac not available")
		}
		t.Fatal(err)
	}

    SmallVector<double, 4> min, max;
    min.reserve(fqOp.getMin().size());
    max.reserve(fqOp.getMax().size());
    for (auto m : fqOp.getMin())
      min.push_back(cast<FloatAttr>(m).getValueAsDouble());
    for (auto m : fqOp.getMax())
      max.push_back(cast<FloatAttr>(m).getValueAsDouble());

    return fakeQuantAttrsToType(fqOp.getLoc(), fqOp.getNumBits(),

    // a special case that there are tf.Identity ops between the min/max
    // constants and the tf.FakeQuantWithMinMaxVarsOp.
    Value min = tf_op.getMin(), max = tf_op.getMax();
    DenseFPElementsAttr min_value, max_value;
    if (auto id1 = dyn_cast_or_null<TF::IdentityOp>(min.getDefiningOp())) {
      id1.replaceAllUsesWith(id1.getInput());
      min = tf_op.getMin();

        return average;
    }

    public Amount<Q> getMedian() {
        return median;
    }

    public Amount<Q> getMin() {
        return min;
    }

    public Amount<Q> getMax() {
        return max;
    }

    public Amount<Q> getStandardError() {
        return standardError;
    }

    public static double confidenceInDifference(DataSeries first, DataSeries second) {

              quant::DownCastScale(qtype, calibrated_type.getMin(),
                                   calibrated_type.getMax(), op.getLoc()));
        }
      } else if (tensor_property.number_of_bits == 16) {
        double max = std::max(std::abs(calibrated_type.getMin()),
                              std::abs(calibrated_type.getMax()));
        qtype = quantfork::fakeQuantAttrsToType(

    ids.push_back(op.getId());
    calibration_methods.push_back(op.getCalibrationMethod());
    statistics_outputs.push_back(op.getMin());
    statistics_outputs.push_back(op.getMax());
    statistics_outputs.push_back(op.getHistogram());
  }
}

// Inserts a `CalibrationStatisticsSaverOp` to the end of the region.
LogicalResult InsertCalibrationStatisticsSaverOp(

		return nil, entry, &entryNotFoundError{Err: errors.New("bad checksum")}
	}
	return data, entry, nil
}

// GetMmap looks up the action ID in the cache and returns
// the corresponding output bytes.
// GetMmap should only be used for data that can be expected to fit in memory.
func GetMmap(c Cache, id ActionID) ([]byte, Entry, error) {
	entry, err := c.Get(id)
	if err != nil {
		return nil, entry, err
	}

struct FetchConstantMinMaxInputs {
  using AttrType = DenseFPElementsAttr;
  bool operator()(TFFakeQuantOp tf_op, AttrType &min_value,
                  AttrType &max_value) const {
    Value min = tf_op.getMin(), max = tf_op.getMax();
    if (auto min_id = min.getDefiningOp<TF::IdentityOp>()) {
      min = min_id.getInput();
    }
    if (auto max_id = max.getDefiningOp<TF::IdentityOp>()) {
      max = max_id.getInput();
    }

struct FetchConstantMinMaxInputs {
  using AttrType = DenseFPElementsAttr;
  bool operator()(TFFakeQuantOp tf_op, AttrType &min_value,
                  AttrType &max_value) const {
    Value min = tf_op.getMin(), max = tf_op.getMax();
    if (!matchPattern(min, m_Constant(&min_value))) {
      return false;
    }
    if (!matchPattern(max, m_Constant(&max_value))) {
      return false;
    }
    return true;  // Successfully matched and fetched.

                    }
                    td()
                        .classAttr(classAttr)
                        .title("median: " + value + ", min: " + data.getMin() + ", max: " + data.getMax() + ", se: " + se + ", values: " + data)
                        .text(value.format())
                        .end();
                    td()
                        .classAttr("numeric more-detail")