GitLab

* Fix bug of profiler for layernorm

* 1. Rename layernorm into normalization
2. Decouple softmax from normalization

* clang-format

* Add groupnorm example by layernorm
1.  Reference is not ready
2. shape of gamma and beta need to be fix

* Let shape of gamma and beta can be same as x

* Modify test, instance and client example

* [What] Fix bug of layernorm for greater than 2 dimension.
[Why] We need to get upper length from merge transform instead of embed transform.

* Add reference for groupnorm

* Fuse sigmoid after groupnorm

* [What] Rename original layernorm into layernorm2d
[Why] Prepare to add groupnorm using layernorm5d

* clang-format

* Add groupnorm test

* Refine error message

* Add groupnorm ckProfiler

* Test groupnorm kernel from device_instance

* update example

* upadte profiler

* Fix test naming

* Fix argc number

* Move descriptor and sweeponce to argument for quick debugging
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Implement layernorm kernel and deviceOp

* verify gpu kernel with host code

* 1. Separate gamma aand beta from affine
2. Check if argument is valid

* clean

* Sync the naming

* Support sweep once mode if we can put k dimension data inside one block

* [What] Get length from upper length.
[Why] if we get length directly, we may get length after padding.

* We only use one block in K dimension.
Hence, we can simplify the indexing of global R/W.

* Use 1d descriptor for gamma and beta

* Add accElementwiseOp

* Extract layernorm host code

* Support different YVectorDim in GridwiseLayernorm

* Rename XSrcVectorDim to XYSrcVectorDim. Because we use same parameter in deviceOp

* Gamma and beta can share the VGPR.

* Add test for fp32 and fp16

* Fix bug of concurrency and add test case which may fail orignally

* Propagate NaN for layernorm
Co-authored-by: Chao Liu <chao.liu2@amd.com>