Comments (1)
@anilmartha thank you for the report, this is unexpected. I did not add a full CI with bf16 but should probably add one with the most used models.
It appears that PyTorch 2.2.1 does not support scaled_dot_product_attention export in BF16, see https://github.com/pytorch/pytorch/blob/v2.2.1/torch/onnx/symbolic_opset14.py#L191-L199
This is fixed on main: https://github.com/pytorch/pytorch/blob/f4cf25bb24be735b2502ae13f290017992c2fac8/torch/onnx/symbolic_opset14.py#L194 & pytorch/pytorch#117878
So in PyTorch 2.3, this will be possible.
We could add an optional option in Optimum to choose that the export is done with the manual attention implementation, not torch.nn.functional.scaled_dot_product_attention
. Would that help you?
As an alternative, you could downgrade to torch==2.1.0
(for which SDPA is not picked in Transformers).
from optimum.
Related Issues (20)
- Trying to export a cohere model, that is a custom or unsupported architecture, but no custom onnx configuration was passed as `custom_onnx_configs`.
- RuntimeError: Expected all tensors to be on the same device, but found at least two devices HOT 2
- Support for `torch.export.export` HOT 2
- Lift upper version limit of transformers for habana HOT 4
- Add support for export SigLIP models HOT 8
- I had a problem mimicking this site: https://community.amd.com/t5/ai/developer-blog-build-a-chatbot-with-ryzen-ai-processors/ba-p/680693
- TypeError: QDQQuantizer.__init__() got an unexpected keyword argument 'static'
- [Bettertransformer] `Transformers 4.41.0 (torch.SDPA-Bert)` breaks bettertransformers Bert, but works in `Transformers 4.40.2` HOT 7
- Custom MT5 model ONNX export not able to run
- Add feature to export CLIPVisionModel from transformers to onnx
- Add feature to export CLIPVisionModel from transformers to onnx
- exporting ORTModelForVision2Seq doesn't work correctly on Pytorch 1.11 HOT 4
- Add ORT support for the StableDiffusionControlNetPipeline. HOT 1
- Could you provide the official onnx model of Qwen-VL-Chat(-Int4)?
- `merge_decoders` mixes up `decoder_model` and `decoder_model_with_past`
- ONNX export support for 4-bit quantized models HOT 1
- Support for phi3-v Vision Model HOT 1
- Quantization by optimum-cli ignores 'use_external_data_format' flag in ORTConfig and fails to quantize models >2GB
- Support for Florence 2 model HOT 1
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from optimum.