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@ -131,9 +131,7 @@ class URLModelSource(StringLikeSource):
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return str(self.url)
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ModelSource = Annotated[
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Union[LocalModelSource, HFModelSource, URLModelSource], Field(discriminator="type")
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]
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ModelSource = Annotated[Union[LocalModelSource, HFModelSource, URLModelSource], Field(discriminator="type")]
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MODEL_SOURCE_TO_TYPE_MAP = {
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URLModelSource: ModelSourceType.Url,
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@ -17,7 +17,8 @@ class MigrateCallback(Protocol):
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See :class:`Migration` for an example.
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"""
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def __call__(self, cursor: sqlite3.Cursor) -> None: ...
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def __call__(self, cursor: sqlite3.Cursor) -> None:
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...
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class MigrationError(RuntimeError):
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@ -858,9 +858,9 @@ def do_textual_inversion_training(
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# Let's make sure we don't update any embedding weights besides the newly added token
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index_no_updates = torch.arange(len(tokenizer)) != placeholder_token_id
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with torch.no_grad():
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accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[index_no_updates] = (
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orig_embeds_params[index_no_updates]
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)
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accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[
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index_no_updates
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] = orig_embeds_params[index_no_updates]
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# Checks if the accelerator has performed an optimization step behind the scenes
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if accelerator.sync_gradients:
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