Fix stable diffusion ONNX export following diffusers breaking change #1116
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echarlaix
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Jun 16, 2023
| models_for_export["unet"] = (pipeline.unet, unet_onnx_config) | ||
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| # VAE Encoder https://github.com/huggingface/diffusers/blob/v0.11.1/src/diffusers/models/vae.py#L565 | ||
| vae_encoder = copy.deepcopy(pipeline.vae) | ||
| if hasattr(vae_encoder.encoder.mid_block.attentions[0], "_use_2_0_attn"): | ||
| vae_encoder.encoder.mid_block.attentions[0]._use_2_0_attn = False | ||
| if not packaging.version.parse(torch.__version__) >= packaging.version.parse("2.1.0"): |
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It could make sense to add a is_torch_version in the future (or check_if_torch_greater)
echarlaix
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Jun 16, 2023
…1116) fix stable diffusion export after breaking change in diffusers
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As per title and discussed on slack, slightly more minimal than #1108 given that SDPA ONNX export will be supported from PyTorch 2.1 onwards.
@echarlaix is it OK to have the requirement
diffusers>=0.17.0?