Onednn

This is a release candidate for oneDNN v1.7. Please provide feedback and report bugs in [Github issues](https://github.com/oneapi-src/oneDNN/issues).

This is a patch release containing the following changes to v1.6.4:
* Fixed issue with memory descriptor size computations (fc836a38713d5a8fd8915f56c16f63b81e3973e2)
* Reduced required scratchpad size for RNNs (c7e165a541b903c4e3c38dc27b3e7fcc0c1e1294)
* Improved performance of fp16 convolution with bias on GPUs (943760e66e19dcbdb58ac8d24c0862a289d2c947)
* Fixed segmentation fault for convolution weight gradient on systems with Intel AVX512 support (85e92b326ef7109ed68a7e9bdaf6113d6f59276d)

This is a patch release containing the following changes to v1.6.3:
* Fixed performance regression in `dnnl_sgemm` with `N=1` (379a216b94393f17a37d5f042323fc923a7553af, f35e9917608925b57bb4e1486f77720f36970aef)
* Extended matmul to support multiple demensions and broadcast (0728f265f18448a3375574e622bdd6fcad0d2787)
* Fixed performance regression for convolution weight gradient implementation for Intel AVX2(9ab050b0f4a3d434cbb14b7ddb7056736564b9dc, 6cd0c352f9949191dac1938b8f16b53b5967c1ea)
* Fixed `unknown primitive kind` assertion on GPU (c95a01cea1bd43445497eae4f1323947bd56c977)
* Fixed build issue on Windows for the case when oneDNN is built as submodule (2fceddf2f564b729550b288eb2e7bba5523c223e)
* Fixed issues with `NaN` results produced by `dnnl_sgemm` in some scenarios (5ce95efe6f5e86cddbf704b637063cd8dc914125)
* Improved performance for convolution backpropagation with 1x1 filter and NHWC activations on systems with Intel AVX2 support (74bfc74ccb089c32829ffb1711842f880a1fb99b)
* Fixed correctness issue for convolution with 3D spatial (bf6ee840bef680223ccdb0c358bfce460f10d371)
* Fixed potential segmentation fault when destroying RNN primitive (0d9839b085263c0f4f6dcaf95e1bc2618a684297)
* Fixed performance regression for fp32 convolutions Intel AVX512 implementation (668e28289ccf17dad541238155c03a42e99802ba)

This is a patch release containing the following changes to v1.6.2:
* Implemented workaround for [GCC internal compiler error with -std=c++14](https://gcc.gnu.org/bugzilla/show_bug.cgi?id=83204) (5ef631a030a6f73131c77892041042805a06064f)

This is a patch release containing the following changes to v1.6.1:
* Implemented workaround for running examples using cmake on macOS (089a877733899fc1ac3d0b9028afe0ca2e1675ca)
* Implemented workaround for internal compiler error when building oneDNN with Microsoft Visual Studio 2019 (c6f9b7a3e5833bfe06580be6c70c7a4e019e3a43)
* Fixed segfault for grouped convolutions (77e5d5744d522cad984443e92bd1b95a9f55ae85)
* Fixed segfault for convolutions with 1x1 filter on Intel AVX2 systems (09c18e65a2061bec659d073b8b0dc5f96e9d7312)
* Fixed segfault for convolutions with 1x1 filter on Intel AVX-512 system (2c4ad3806e344251d9555eaa02e9a803a652200f)
* Fixed issue with zero padding in bfloat16 convolutions with NHWC activations (4c05c181b40cf7132f8943411fb3fab1786df0f7)

This is a patch release containing following changes to v1.6:
* Fixed performance regression for convolutions with 1x1 filter on Intel AVX2 (8186817fa59b97c602944f4ff46ce9b5b63d217c)
* Fixed invalid memory access issue for bfloat16 1D grouped convolutions (9ebda6517eb5a28d991d126da8d8babaa3d3c4dd)
* Fixed `RuntimeError: label is redefined` for convolutions with large filter size on Intel AVX512 (f974b50ea37571826662f3d1fed7ced8642d6f43)
* Suppressed MSBuild warning MSB8065 (f91e641b87c625d83b329164b2471a655a880447)
* Restricted support for shared virtual memory (SVM) to OpenCL 2.0 and later (fa6bbf40f7aba32a9593d3703bfcaa4abd3dd379)