🧹 Remove deprecated RotaryEmbedding parts in the Attention layers #34858
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ArthurZucker
reviewed
Dec 4, 2024
Comment on lines
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| kv_seq_len = key_states.shape[-2] | ||
| if past_key_value is not None: | ||
| kv_seq_len += cache_position[0] |
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Unwanted change I think
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Nop, this is actually doing nothing (never used, no purpose here) so I cleaned it up!
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Indeed not linked to the rotary though, but as I'm cleaning stuff, let's remove it as the same time
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@ArthurZucker should be good to go! |
ArthurZucker
reviewed
Dec 5, 2024
ArthurZucker
approved these changes
Dec 11, 2024
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Looks like there is a regression? |
Merged
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True! Aria relies on Llama and was merged in the meantime - #35208 correctly reapplies new Llama change to Aria |
BenjaminBossan
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Dec 12, 2024
This PR resolves the failing adoption prompt tests in the CI using transformers installed from source. In this transformers PR: huggingface/transformers#34858 the module.rotary_emb attribute has been removed, which adoption prompt so far assumed was present. Instead, the position_embeddings are now already computed and can be taken directly from the kwargs.
BenjaminBossan
added a commit
to BenjaminBossan/peft
that referenced
this pull request
Dec 12, 2024
This PR resolves the failing adoption prompt tests in the CI using transformers installed from source. In this transformers PR: huggingface/transformers#34858 the module.rotary_emb attribute has been removed, which adoption prompt so far assumed was present. Instead, the position_embeddings are now already computed and can be taken directly from the kwargs.
BenjaminBossan
added a commit
to huggingface/peft
that referenced
this pull request
Dec 13, 2024
This PR resolves the failing adoption prompt tests in the CI using transformers installed from source. In this transformers PR: huggingface/transformers#34858 the module.rotary_emb attribute has been removed, which adoption prompt so far assumed was present. Instead, the position_embeddings are now already computed and can be taken directly from the kwargs.
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What does this PR do?
This cleans-up the (expired) deprecated cycle for the rotary embeddings and fully move them to the Model instead of the Attention. Also removes deprecated EmbeddingClasses, and fix the tests accordingly.