anko-intel commented on code in PR #21002:
URL: https://github.com/apache/incubator-mxnet/pull/21002#discussion_r918884081
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src/operator/nn/dnnl/dnnl_fully_connected-inl.h:
##########
@@ -100,7 +94,7 @@ class FCInputIndex {
const bool has_bias = !full_param.default_param.no_bias;
const bool quantized = dnnl_param.quantized;
const bool sum_input_quantized =
- quantized && dnnl_param.with_sum && !dnnl_param.enable_float_output;
+ quantized && dnnl_param.with_sum &&
!dnnl_param.enabled_float_output.has_value();
Review Comment:
is it enough ? shoud it be ?
( dnnl_param.enabled_float_output.has_value() &&
dnnl_param.enabled_float_output.value == mshadow::kFloat32)
##########
3rdparty/mshadow/mshadow/base.h:
##########
@@ -769,6 +769,10 @@ namespace isnan_typed {
MSHADOW_XINLINE bool IsNan(volatile mshadow::half::half_t val) {
return (val.half_ & (~MSHADOW_HALF_SIGN_BIT)) > MSHADOW_HALF_EXPONENT_BITS;
}
+ template <>
+ MSHADOW_XINLINE bool IsNan(volatile mshadow::bfloat::bf16_t val) {
+ return (val.bf16_ & (~MSHADOW_BF16_SIGN_BIT)) > MSHADOW_BF16_EXPONENT_BITS;
Review Comment:
I am wonder if conversion to float and using isnan() could be faster?
probably no, as I am not awere of ony CPU instruction checkin against NaN
##########
3rdparty/mshadow/mshadow/base.h:
##########
@@ -409,7 +409,7 @@ struct DataType<half::half_t> {
#endif
#endif
};
-template<>
+template <>
Review Comment:
we can add space between "template" and <> in a whole file to be consistent
##########
src/common/utils.h:
##########
@@ -929,11 +929,8 @@ inline mxnet::TShape CanonicalizeAxes(const mxnet::TShape&
src) {
}
inline bool is_float(const int dtype) {
Review Comment:
maybe we can chang the name to is_floating to emphase that it not aswer for
particular type like float but common floating point group of data
representation
```suggestion
inline bool is_floating(const int dtype) {
```
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