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Fix Gradient Checkpointing for Deberta & Deberta-V2 using PEFT / Adapters #35898

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Fix Gradient Checkpointing for Deberta & Deberta-V2 using PEFT / Adapters #35898

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4 changes: 2 additions & 2 deletions src/transformers/models/deberta/modeling_deberta.py
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Original file line number Diff line number Diff line change
Expand Up @@ -418,10 +418,10 @@ def forward(self, input_ids=None, token_type_ids=None, position_ids=None, mask=N

embeddings = inputs_embeds
if self.position_biased_input:
embeddings += position_embeddings
embeddings = embeddings + position_embeddings
if self.token_type_embeddings is not None:
token_type_embeddings = self.token_type_embeddings(token_type_ids)
embeddings += token_type_embeddings
embeddings = embeddings + token_type_embeddings

if self.embed_proj is not None:
embeddings = self.embed_proj(embeddings)
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4 changes: 2 additions & 2 deletions src/transformers/models/deberta_v2/modeling_deberta_v2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -551,10 +551,10 @@ def forward(self, input_ids=None, token_type_ids=None, position_ids=None, mask=N

embeddings = inputs_embeds
if self.position_biased_input:
embeddings += position_embeddings
embeddings = embeddings + position_embeddings
if self.token_type_embeddings is not None:
token_type_embeddings = self.token_type_embeddings(token_type_ids)
embeddings += token_type_embeddings
embeddings = embeddings + token_type_embeddings

if self.embed_proj is not None:
embeddings = self.embed_proj(embeddings)
Expand Down