Onednn

This is a patch release containing following changes to v0.21.4:

* Fixed s8 reorders that did not compute compensation correctly (d446661de2865741b1ad5f35a913feb6953b2592, 7a497726bfaf009eeb92ca62f873b20d53b7a3d9)
* Fixed potential buffer overflow in int8 convolution scratchpad (8c5c7cf34e1e36a4c47afa506ab3af510423e28e)
* Fixed segfault for s8 reorders on blocked formats (9497accb06f3d0e4f53ac8719d0f9c6721e5df38, 6f1d0c93bf461be9adcbf25201a8905bd055e478)
* Fixed correctness in fp32 convolution weight gradient with dilation and padding (503bf57e447b458dd26af03189b21603395c89aa, d00afabbdd8fb67eb07e65b8eb8445934789dfa6)
* Fixed correctness inssue in 1D bfloat16 dilated convolution (481dd391bee2442994db7589e00ddba3044ca682)

This is a patch release containing following changes to v0.21.3:

* Fixed large padding handling in input tensor transposition in bfloat16 weights gradient convolution (6df67fe)
* Fixed performance of reference convolution (2e1d048)
* Fixed "code is too big" error in case of extreme large spatial size (ed0be61, 4dee389, 59759ba)

This is a patch release containing following changes to v0.21.2:
* Reduced the upper-bound of memory requirement for gemm-based convolution to reduce the probability of OOM error (cd99749c97e1cb6a7ec96f3ffa9e225a445b8a24)
* Significantly reduced the size required for 1x1 convolution (564344566ad5cd8e1f9e6bdb5defc77b88a19b64)
* Added new dummy stream (cba5823ad881b837957c89d388241bbdc245a0bf)

This is a patch release containing following changes to v0.21.1:
* Fixed performance regression in GEMM (95346214b9cbd689b750ab093910e439f0f83d9b)
* Fixed int8 dilated convolution for some shapes with input heights <= dilation over the heights dimension (e68f1514061e4f58cc67a9669985ea3c4563acaf)
* Addressed static initialization order issue in bf16 converters (ae8efdeebf1b576e9d25a8601301b4791219cde9)
* Fixed fast reference backward convolution dispatching for 3D-spatial case (5994d63ffeec9830c280b5d6fb38ab6d6d97da4e)

This is a patch release containing following changes to Intel MKL-DNN v0.21:
* Fixed output channel blocking logic in forward AVX2 convolution that could lead to incorrect result or segfault (6accb47c4588ab6f0c350117faf7f26e850446d2)
* Fixed int8 grouped convolution for some shapes with the number of input or output channels not being a multiple of 8 on Intel AVX512 systems (878ac2d4b2d561b44a9c2dc19f6988a7da0a71a6)

Performance optimizations
* Improved int8 and fp32 GEMM and inner product performance.
* Improved reorder performance for certain shapes.
* Improved RNN, LSTM, GRU and LBR-GRU training performance.

New functionality
* Added GELU activation support.

Thanks to the contributors
This release contains contributions from many Intel Performance Libraries developers. We would also like to thank everyone who asked questions and reported issues.