akarbown commented on a change in pull request #19896:
URL: https://github.com/apache/incubator-mxnet/pull/19896#discussion_r643227365
##########
File path: src/operator/contrib/adaptive_avg_pooling-inl.h
##########
@@ -43,6 +43,9 @@
#include "../operator_common.h"
#include "../mxnet_op.h"
#include "../mshadow_op.h"
+#if MXNET_USE_MKLDNN == 1
Review comment:
Please change it to MXNET_USE_ONEDNN.
##########
File path: src/operator/contrib/adaptive_avg_pooling.cc
##########
@@ -197,6 +198,81 @@
num_threads(engine::OpenMP::Get()->GetRecommendedOMPThreadCount())
}
}
+#if MXNET_USE_MKLDNN == 1
Review comment:
Please change it to MXNET_USE_ONEDNN.
##########
File path: src/operator/contrib/adaptive_avg_pooling.cc
##########
@@ -197,6 +198,81 @@
num_threads(engine::OpenMP::Get()->GetRecommendedOMPThreadCount())
}
}
+#if MXNET_USE_MKLDNN == 1
+bool SupportMKLDNNAveragePooling(const NDArray &in_data,
+ const NDArray &out_data) {
+ for (int64_t idx = 2; idx < in_data.shape().ndim(); ++idx) {
+ const int s1 = in_data.shape()[idx];
+ const int s2 = out_data.shape()[idx];
+ if (s2 == 0) {
+ return false;
+ }
+ if (s1 % s2 != 0) {
+ return false;
+ }
+ }
+ const int IH = in_data.shape()[2];
+ const int IW = in_data.shape()[3];
+ const int OH = out_data.shape()[2];
+ const int OW = out_data.shape()[3];
+
+ const int strides_1 = floor((IH << 1) / OH) - floor(IH / OH);
+ const int strides_2 = floor((IW << 1) / OW) - floor(IW / OW);
Review comment:
Maybe worth considering to rename 'strides_1, strides_2' to
'strides_H/strides_W'?
##########
File path: src/operator/contrib/adaptive_avg_pooling.cc
##########
@@ -197,6 +198,81 @@
num_threads(engine::OpenMP::Get()->GetRecommendedOMPThreadCount())
}
}
+#if MXNET_USE_MKLDNN == 1
+bool SupportMKLDNNAveragePooling(const NDArray &in_data,
+ const NDArray &out_data) {
+ for (int64_t idx = 2; idx < in_data.shape().ndim(); ++idx) {
+ const int s1 = in_data.shape()[idx];
+ const int s2 = out_data.shape()[idx];
+ if (s2 == 0) {
+ return false;
+ }
+ if (s1 % s2 != 0) {
+ return false;
+ }
+ }
+ const int IH = in_data.shape()[2];
+ const int IW = in_data.shape()[3];
+ const int OH = out_data.shape()[2];
+ const int OW = out_data.shape()[3];
+
+ const int strides_1 = floor((IH << 1) / OH) - floor(IH / OH);
+ const int strides_2 = floor((IW << 1) / OW) - floor(IW / OW);
+ const int kernel_1 = ceil((IH << 1) / OH) - floor(IH / OH);
+ const int kernel_2 = ceil((IW << 1) / OW) - floor(IW / OW);
Review comment:
The same as the comment above but connected with 'kernel_1/kernel2'?
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