mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-06-09 00:30:53 +00:00
d0519a7603
### Description Two contrib kernels that supposed to speed-up StableDiffusion according to this doc https://github.com/microsoft/onnxruntime/blob/main/onnxruntime/python/tools/transformers/models/stable_diffusion/README.md However, there is no noticable effect in speed or memory consumption. So i guess the only way to make it faster is to implement MultiHeadAttention but i'm not capable of doing that right now. So i'll focus on existing PRs and finding the JSEP kernel that produces incorrect results. It should be one of the old ones (i suspect Conv or ConvTranspose), as SD was not generating images correctly on webgpu since i started working on it. I hoped someone else would fix that by the time i finish with kernels/optimizations 😅 --------- Co-authored-by: Guenther Schmuelling <guschmue@microsoft.com> Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com> |
||
|---|---|---|
| .. | ||
| 3rd-party | ||
| argminmax.ts | ||
| bias-add.ts | ||
| bias-split-gelu.ts | ||
| binary-op.ts | ||
| common.ts | ||
| concat.ts | ||
| conv-grouped.ts | ||
| conv-transpose.ts | ||
| conv.ts | ||
| conv2d-mm.ts | ||
| conv2dtranspose-mm.ts | ||
| einsum.ts | ||
| expand.ts | ||
| fuse-utils.ts | ||
| gather-elements.ts | ||
| gather.ts | ||
| gemm.ts | ||
| instance-norm.ts | ||
| layer-norm.ts | ||
| matmul.ts | ||
| pad.ts | ||
| pool.ts | ||
| range.ts | ||
| reduce.ts | ||
| resize.ts | ||
| skip-layer-norm.ts | ||
| slice.ts | ||
| softmax.ts | ||
| split.ts | ||
| tile.ts | ||
| transpose.ts | ||
| unary-op.ts | ||