minor

onnxruntime/core/providers/qnn/builder/qnn_node_group/conv_activation_fusion.cc

@@ -27,10 +27,10 @@ namespace {
 // removal is valid or not.
 // 4. Due to rounding effect, we can be get the upperbound and lowerbound of min or max
 // - Which one to use?
-// - upperbound of min and lowerbound of max
+// upperbound of min and lowerbound of max
 // - Why?
-// - We want the codomain to be unchanged.
-
+// We want the codomain to be unchanged, so as long as the domain genreate a codomain that fill the integer value
+// range will be fine.
 
 // The quantization formula is y = saturate((x / y_scale) + y_zero_point)
 // For (x / y_scale), it rounds to the nearest even. So the allowed quantize limits before saturate need to be taken
@@ -43,7 +43,7 @@ struct quantize_domain {
  int64_t codomain_min = std::numeric_limits<T>::lowest();
  int64_t biased = codomain_min - zp;
  float before_round = float(biased) + 0.5; // move to upperbound
- if (biased % 2 == 1) { // cannot be exact ?.5 because of rounding to even
+ if (biased % 2 == 1) {  // cannot be exact ?.5 because of rounding to even
  before_round = std::nextafterf(before_round, float(biased));
  }
  return before_round * scale;
@@ -53,14 +53,14 @@ struct quantize_domain {
  int64_t codomain_max = std::numeric_limits<T>::max();
  int64_t biased = codomain_max - zp;
  float before_round = float(biased) - 0.5; // move to lowerbound
- if (biased % 2 == 1) { // cannot be exact ?.5 because of rounding to even
+ if (biased % 2 == 1) {  // cannot be exact ?.5 because of rounding to even
  before_round = std::nextafterf(before_round, float(biased));
  }
  return before_round * scale;
  }
 };
 
-}
+} // namespace
 
 // Gets the scale, zero-point, and zero-point type for a QuantizeLinear node that uses per-tensor quantization.
 static bool GetQScalarScaleZeroPoint(const QnnModelWrapper& qnn_model_wrapper,
@@ -100,9 +100,9 @@ static bool GetQScalarScaleZeroPoint(const QnnModelWrapper& qnn_model_wrapper,
 
 // Computes the floating point domain (min_, max_) from a QuantizeLinear node's scale/zero-point.
 static bool GetQDomain(const QnnModelWrapper& qnn_model_wrapper,
-  const NodeUnit& q_node_unit,
-  /*out*/ float& min_,
-  /*out*/ float& max_) {
+ const NodeUnit& q_node_unit,
+ /*out*/ float& min_,
+ /*out*/ float& max_) {
  int32_t zp_data_type = ONNX_NAMESPACE::TensorProto::DataType::TensorProto_DataType_UNDEFINED;
  int32_t zero_point = 0;
  float scale = 0.0f;