huggingface / huggingface/diffusers
pipeline does not work with conversion to fp16 in the to cuda call
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説明
Hi,
i was using and doing some fine-tuning with the Pixart model.
and i found a problem that i could pin it down to:
this code works:
```
pipe2 = PixArtAlphaPipeline.from_pretrained("PixArt-alpha/PixArt-XL-2-512x512", torch_dtype=torch.float16)
pipe2.to("cuda")
image = pipe2(prompt, num_inference_steps=20).images[0]
```
while this does not, it gives out just noise images :
```
pipe1 = PixArtAlphaPipeline.from_pretrained("PixArt-alpha/PixArt-XL-2-512x512")
pipe1.to("cuda", dtype=torch.float16)
image = pipe1(prompt, num_inference_steps=20).images[0]
```
i have looked through the code, and i cannot find any issues so far.
has anyone encountered a similar problem or has tips where to look further?
i am on WSL Ubuntu, diffusers==0.27.2, torch==2.2.2
コントリビューションガイド
調査の方向性
Start by reproducing the two PixArtAlphaPipeline snippets with diffusers 0.27.2 and torch 2.2.2 on WSL Ubuntu, comparing the pipeline state and generated outputs after each CUDA conversion. Done means identifying why the two conversion paths differ and making the dtype conversion produce valid, non-noise images.
索引モデルが issue の本文から書いたものです。
評価
- 技術スタック
- python, pytorch
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- machine-learning
- issue の種類
- バグ
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- 4/5
- 見積もり時間
- 3〜5日
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- 25/100