diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go
index 615c386858e..ebe4a51116b 100644
--- a/tensorflow/go/op/wrappers.go
+++ b/tensorflow/go/op/wrappers.go
@@ -1904,10 +1904,10 @@ func DequantizeMode(value string) DequantizeAttr {
 // If the mode is 'MIN_FIRST', then this approach is used:
 //
 // ```c++
-// number_of_steps = 1 << (# of bits in T)
-// range_adjust = number_of_steps / (number_of_steps - 1)
+// num_discrete_values = 1 << (# of bits in T)
+// range_adjust = num_discrete_values / (num_discrete_values - 1)
 // range = (range_max - range_min) * range_adjust
-// range_scale = range / number_of_steps
+// range_scale = range / num_discrete_values
 // const double offset_input = static_cast<double>(input) - lowest_quantized;
 // result = range_min + ((input - numeric_limits<T>::min()) * range_scale)
 // ```
@@ -13766,10 +13766,10 @@ func QuantizeV2RoundMode(value string) QuantizeV2Attr {
 // If the mode is 'MIN_FIRST', then this approach is used:
 //
 // ```
-// number_of_steps = 1 << (# of bits in T)
-// range_adjust = number_of_steps / (number_of_steps - 1)
+// num_discrete_values = 1 << (# of bits in T)
+// range_adjust = num_discrete_values / (num_discrete_values - 1)
 // range = (range_max - range_min) * range_adjust
-// range_scale = number_of_steps / range
+// range_scale = num_discrete_values / range
 // quantized = round(input * range_scale) - round(range_min * range_scale) +
 //   numeric_limits<T>::min()
 // quantized = max(quantized, numeric_limits<T>::min())