onnxruntime

df8bf2df - [webgpu] Optimize InstanceNormalization by removing redundant transpose (#26626)

[webgpu] Optimize InstanceNormalization by removing redundant transpose (#26626) ### Description <!-- Describe your changes. --> This PR optimizes `InstanceNormalization` by removing redundant transpose. Given the implementation of `InstanceNormalization` for `NCHW` is more effiencient, we don't need to add wrapper `Transpose` to make it run in `NHWC`, which helps use to elide redundant transpose and improve performance. Testing on Lunar Lake shows about `~60%` performance improvement in `InstanceNormalization` operations. #### `InstanceNormalization` OP benchmark The input tensor shape: `(1,32,1048576)` The scale tensor shape: `(32)` The B tensor shape: `(32)` | time cost (ms) | baseline | opt | diff | | ---------------- | -------- | ---- | ---- | | Lunar Lake | 82.6 | 34.2 | 58% | #### Model benchmark | time cost (ms) | baseline | opt | diff | | ---------------- | -------- | ---- | ---- | | sd-turbo-vae-decoder-fp16-demo | 2437.6 | 1835.9 | 25% | ### 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. --> Please see above