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fix crash in tiiuae/falcon-11B-vlm image-to-text generation (#34728)

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Signed-off-by: Wang, Yi <yi.a.wang@intel.com>
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Wang, Yi 2024-11-19 23:51:32 +08:00 committed by GitHub
parent 427b62ed1a
commit dc42330388
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1 changed files with 7 additions and 1 deletions
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8
src/transformers/models/falcon/modeling_falcon.py
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@ -1277,12 +1277,18 @@ class FalconForCausalLM(FalconPreTrainedModel, GenerationMixin):
output_hidden_states: Optional[bool] = None,
return_dict: Optional[bool] = None,
cache_position: Optional[torch.LongTensor] = None,
num_logits_to_keep: int = 0,
) -> Union[Tuple[torch.Tensor], CausalLMOutputWithCrossAttentions]:
r"""
labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
Labels for language modeling. Note that the labels **are shifted** inside the model, i.e. you can set
`labels = input_ids` Indices are selected in `[-100, 0, ..., config.vocab_size]` All labels set to `-100`
are ignored (masked), the loss is only computed for labels in `[0, ..., config.vocab_size]`
num_logits_to_keep (`int`, *optional*):
Calculate logits for the last `num_logits_to_keep` tokens. If `0`, calculate logits for all
`input_ids` (special case). Only last token logits are needed for generation, and calculating them only for that
token can save memory, which becomes pretty significant for long sequences or large vocabulary size.
"""
return_dict = return_dict if return_dict is not None else self.config.use_return_dict
@ -1302,7 +1308,7 @@ class FalconForCausalLM(FalconPreTrainedModel, GenerationMixin):
)
hidden_states = transformer_outputs[0]
lm_logits = self.lm_head(hidden_states)
lm_logits = self.lm_head(hidden_states[:, -num_logits_to_keep:, :])
loss = None
if labels is not None: