Standalone layernorm (#315)

* 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>

example/23_softmax/softmax_blockwise.cpp

@@ -212,6 +212,8 @@ int main(int argc, char* argv[])
 
     auto device_instance = DeviceInstance{};
 
+    std::cout << i_inLengths.size() << ", " << i_inStrides.size() << std::endl;
+
     auto argument_ptr = device_instance.MakeArgumentPointer(i_inLengths,
                                                             i_inStrides,
                                                             reduceDims,