wuxun-zhang commented on a change in pull request #17884: [MKL-DNN] Integrate
Conv3d and Pool3d/1d
URL: https://github.com/apache/incubator-mxnet/pull/17884#discussion_r397620385
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File path: src/operator/nn/mkldnn/mkldnn_base-inl.h
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@@ -324,20 +323,27 @@ inline static mkldnn::memory::desc GetWeightDesc(const
NDArray &arr,
if (num_groups == 1) {
return GetMemDesc(arr, dtype);
} else {
- auto ndim = arr.shape().ndim();
- CHECK((ndim == 3) || (ndim == 4))
- << "MKL-DNN weight currectly supports 3d and 4d layout";
+ const auto ndim = arr.shape().ndim();
+ CHECK((ndim == 3) || (ndim == 4) || (ndim == 5))
+ << "MKL-DNN weight currently supports 3d or 4d or 5d layout";
auto tz = mkldnn::memory::dims{0};
- const int N = 0, H = 2, W = 3, C = 1;
- if (ndim == 3) {
- tz = mkldnn::memory::dims{
- num_groups, static_cast<int>(arr.shape()[N] / num_groups),
- static_cast<int>(arr.shape()[C]), static_cast<int>(arr.shape()[H])};
- } else {
- tz = mkldnn::memory::dims{
- num_groups, static_cast<int>(arr.shape()[N] / num_groups),
- static_cast<int>(arr.shape()[C]), static_cast<int>(arr.shape()[H]),
- static_cast<int>(arr.shape()[W])};
+ const int D = (ndim == 5) ? 2 : 1;
+ const int N = 0, C = 1, H = D + 1, W = D + 2;
Review comment:
Thanks. Done.
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