onnxruntime

Stable Diffusion CUDA Optimizations (#14428)

### Description

Add stable diffusion CUDA kernel optimizations.

The following are included:
(1) GroupNorm operator. This kernel is from TensorRT 8.5.
(2) BiasSplitGelu operator. This kernel is modified from SplitGelu of
TensorRT 8.5. We added bias to the SplitGelu.
(3) NhwcConv operator. This adds support of NHWC format (ONNX Conv
operator uses NCHW format).
(3) Update MultiHeadAttention (packed kv and no bias) for cross
attention. This could avoid transpose of kv for TRT fused cross
attention kernel.
(4) Optimization and benchmark script

Not included:
(1) Script to convert Conv to NhwcConv in onnx graph.
(2) Update symbolic shape inference for NhwcConv.
(3) Add SeqLen2Spatial operator
(4) Documents

Limitations: GroupNorm, BiasSplitGelu and NhwcConv kernels are
implemented based on stable diffusion usage. They might not be
applicable to any input size or dimensions. For example, BiasSplitGelu
requires hidden size to be 2560 | 5120 | 10240, and NhwcConv assumes 4D
input/weight.

There is minor increasement of binary size. For SM=75 only, python
package wheel size adds (33757K - 33640K) = 117 KB. It is possible to
move NHWC from template parameter to constructor to reduce binary size
(with slight cost of performance).

Note: for RTX 4090/4080/4070 Ti, need build with CUDA 11.8 and latest
cuDNN to get best performance.