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Correct llava mask & fix missing setter for vocab_size #29389

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merged 8 commits into from
Mar 22, 2024
Merged

Correct llava mask & fix missing setter for vocab_size #29389

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4252a21
correct llava mask
fxmarty Mar 1, 2024
1203982
fix vipllava as wlel
fxmarty Mar 1, 2024
beb7946
mask out embedding for padding tokens
fxmarty Mar 18, 2024
6aad22f
add test
fxmarty Mar 18, 2024
b993bad
Merge branch 'main' into fix-llava-mask
fxmarty Mar 22, 2024
eff874c
fix style
fxmarty Mar 22, 2024
e967bc0
add setter
fxmarty Mar 22, 2024
38b2929
fix test on suggestion
fxmarty Mar 22, 2024
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8 changes: 4 additions & 4 deletions src/transformers/models/llava/modeling_llava.py
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Original file line number Diff line number Diff line change
Expand Up @@ -444,11 +444,11 @@ def forward(
# Sum all dimensions of head_dim (-2) to avoid random errors such as: https://github.com/huggingface/transformers/pull/28032#issuecomment-1863691941
batch_index, non_attended_tokens = torch.where(first_layer_past_key_value.float().sum(-2) == 0)

# Get the target length
target_seqlen = first_layer_past_key_value.shape[-1] + 1
target_length = input_ids.shape[1]
past_length = first_layer_past_key_value.shape[-1]

extended_attention_mask = torch.ones(
(attention_mask.shape[0], target_seqlen - attention_mask.shape[1]),
(attention_mask.shape[0], past_length),
dtype=attention_mask.dtype,
device=attention_mask.device,
)
Expand All @@ -463,7 +463,7 @@ def forward(
# Zero-out the places where we don't need to attend
extended_attention_mask[new_batch_index, new_non_attended_tokens] = 0

attention_mask = torch.cat((attention_mask, extended_attention_mask), dim=1)
attention_mask = torch.cat((extended_attention_mask, attention_mask[:, -target_length:]), dim=1)
position_ids = torch.sum(attention_mask, dim=1).unsqueeze(-1) - 1

outputs = self.language_model(
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8 changes: 4 additions & 4 deletions src/transformers/models/vipllava/modeling_vipllava.py
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Original file line number Diff line number Diff line change
Expand Up @@ -443,11 +443,11 @@ def forward(
# Sum all dimensions of head_dim (-1) to avoid random errors such as: https://github.com/huggingface/transformers/pull/28032#issuecomment-1863691941
batch_index, non_attended_tokens = torch.where(first_layer_past_key_value.float().sum(-1) == 0)

# Get the target length
target_seqlen = first_layer_past_key_value.shape[-2] + 1
target_length = input_ids.shape[1]
past_length = first_layer_past_key_value.shape[-1]

extended_attention_mask = torch.ones(
(attention_mask.shape[0], target_seqlen - attention_mask.shape[1]),
(attention_mask.shape[0], past_length),
dtype=attention_mask.dtype,
device=attention_mask.device,
)
Expand All @@ -462,7 +462,7 @@ def forward(
# Zero-out the places where we don't need to attend
extended_attention_mask[new_batch_index, new_non_attended_tokens] = 0

attention_mask = torch.cat((attention_mask, extended_attention_mask), dim=1)
attention_mask = torch.cat((extended_attention_mask, attention_mask[:, -target_length:]), dim=1)
position_ids = torch.sum(attention_mask, dim=1).unsqueeze(-1) - 1

outputs = self.language_model(
Expand Down
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