Stable Diffusion CUDA optimizations Part 2 (#14597)
### Description
This is a follow-up of
https://github.com/microsoft/onnxruntime/pull/14428 for Stable Diffusion
CUDA optimizations:
(1) use NchwConv to replace Conv in onnx graph and add Tranpose nodes
accordingly
(2) reduce sequential Transpose nodes to at most one.
(3) symbolic shape infer of NchwConv
(4) fix add bias transpose which causes CUDA error (launching more than
1024 threads per block) in inferencing fp32 model.
(5) add models (bert, bart, stable_diffusion subdirectories) to package;
(6) remove option --disable_channels_last
Note that
(1) We can add a few graph transformations to reduce Transpose nodes
further. It is not done in this PR due to time limit.
(2) Stable diffusion 2.1 model outputs black images. It seems that
forcing Attention to float32 could avoid the issue. However it is much
slow to use float32 Attention.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
