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fix vocab_size path for gemma3 #774

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fix vocab_size path for gemma3 #774

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c20106e
fix vocab_size path for gemma3
winglian Jun 25, 2025
6e04ee7
fix pad_token_id also
winglian Jun 25, 2025
1bcd24d
more fixes
winglian Jun 25, 2025
8bce236
Merge branch 'main' into gemma3-mm-vocab-size-attr
lancerts Jul 2, 2025
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45 changes: 30 additions & 15 deletions .idea/workspace.xml
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@shimizust shimizust Jun 28, 2025 •
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can you remove and add .idea to the .gitignore

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12 changes: 6 additions & 6 deletions src/liger_kernel/transformers/model/gemma3.py
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Original file line number Diff line number Diff line change
Expand Up @@ -208,7 +208,7 @@ def multimodal_forward(
is_training = token_type_ids is not None and labels is not None

# Replace image id woth PAD if the image token if OOV, to avoid index-errors
if input_ids is not None and self.config.image_token_index >= self.vocab_size:
if input_ids is not None and self.config.image_token_index >= self.config.text_config.vocab_size:
special_image_mask = input_ids == self.config.image_token_index
llm_input_ids = input_ids.clone()
llm_input_ids[special_image_mask] = 0
Expand Down Expand Up @@ -250,17 +250,17 @@ def multimodal_forward(
inputs_embeds = inputs_embeds.masked_scatter(special_image_mask, image_features)

# mask out pad-token-ids in labels for BC
if labels is not None and self.pad_token_id in labels:
if labels is not None and self.config.pad_token_id in labels:
logger.warning_once(
"`labels` contains `pad_token_id` which will be masked with `config.ignore_index`. "
"You have to mask out `pad_token_id` when preparing `labels`, this behavior will be removed in v.4.46.",
)
labels = torch.where(input_ids == self.pad_token_id, self.config.ignore_index, labels)

causal_mask = self._update_causal_mask(
causal_mask = self.model._update_causal_mask(
attention_mask, token_type_ids, past_key_values, cache_position, inputs_embeds, is_training
)
outputs = self.language_model.model(
outputs = self.language_model(
attention_mask=causal_mask,
position_ids=position_ids,
past_key_values=past_key_values,
Expand Down Expand Up @@ -304,9 +304,9 @@ def multimodal_forward(
shift_labels = shift_labels.view(-1).to(hidden_device)

lce = LigerFusedLinearCrossEntropyLoss()
loss = lce(self.language_model.lm_head.weight, shift_hidden_states, shift_labels)
loss = lce(self.lm_head.weight, shift_hidden_states, shift_labels)
else:
logits = self.language_model.lm_head(hidden_states)
logits = self.lm_head(hidden_states)
if labels is not None:
# Upcast to float if we need to compute the loss to avoid potential precision issues
logits = logits.float()
Expand Down
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