Enable Latent Consistency models ONNX export #1469
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echarlaix
commented
Oct 25, 2023
| @@ -435,7 +435,7 @@ def ordered_inputs(self, model: Union["PreTrainedModel", "TFPreTrainedModel"]) - | |||
| sig = inspect.signature(model.call) | |||
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| for param in sig.parameters: | |||
| param_regex = re.compile(rf"{param}(\.\d*)?") | |||
| param_regex = re.compile(rf"{param}(\..*)?$") | |||
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this modification comes from timestep matching both timestep and timestep_cond previously (behavior that we don't want), we still want past_key_value to match past_key_values.0.key though
fxmarty
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Oct 25, 2023
echarlaix
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michaelbenayoun
approved these changes
Oct 30, 2023
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| @parameterized.expand(SUPPORTED_ARCHITECTURES) | ||
| @require_diffusers | ||
| @unittest.skipIf(parse(_diffusers_version) <= Version("0.21.4"), "not supported with this diffusers version") |
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nit: I would specify the minimal diffusers version needed in the skip message.
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good point, will add it !
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Add Latent Consistency models (added in
diffusersin huggingface/diffusers#5438 and huggingface/diffusers#5448 ) ONNX export and pipeline to enable ONNX Runtime inference for text-to-imageAlso enable ONNX export using the CLI :
optimum-cli export onnx --model SimianLuo/LCM_Dreamshaper_v7 lcm_onnx/OpenVINO integration : huggingface/optimum-intel#463