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Mamba / FalconMamba: Fix mamba left padding #32677

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merged 10 commits into from
Aug 19, 2024
Merged

Mamba / FalconMamba: Fix mamba left padding #32677

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4e33582
fix mamba left padding
younesbelkada Aug 14, 2024
39dab5a
Apply suggestions from code review
younesbelkada Aug 14, 2024
97e9dfd
fix copies
younesbelkada Aug 14, 2024
8978e00
test with `inputs_embeds`
younesbelkada Aug 14, 2024
fcc05af
Update src/transformers/models/falcon_mamba/modeling_falcon_mamba.py
younesbelkada Aug 16, 2024
fe2725e
copies
younesbelkada Aug 16, 2024
6ea01ee
clairfy
younesbelkada Aug 16, 2024
f3339a7
Merge remote-tracking branch 'upstream/main' into fix-mamba-padding
younesbelkada Aug 16, 2024
9a09c89
fix last comments
younesbelkada Aug 16, 2024
6c16fc0
remove
younesbelkada Aug 16, 2024
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15 changes: 8 additions & 7 deletions src/transformers/models/falcon_mamba/modeling_falcon_mamba.py
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Original file line number Diff line number Diff line change
Expand Up @@ -619,14 +619,13 @@ def set_input_embeddings(self, new_embeddings):
def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.LongTensor] = None, # Ignored arg
inputs_embeds: Optional[torch.LongTensor] = None,
cache_params: Optional[MambaCache] = None,
use_cache: Optional[bool] = None,
output_hidden_states: Optional[bool] = None,
return_dict: Optional[bool] = None,
cache_position: Optional[torch.LongTensor] = None,
**kwargs, # `attention_mask` is passed by the tokenizer and we don't want it
attention_mask: Optional[torch.LongTensor] = None, # Ignored arg
) -> Union[Tuple, FalconMambaOutput]:
output_hidden_states = (
output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
Expand Down Expand Up @@ -735,6 +734,13 @@ def _update_model_kwargs_for_generation(
and model_kwargs["cache_position"] is not None
):
model_kwargs["cache_position"] = model_kwargs["cache_position"][-1:] + num_new_tokens

if "attention_mask" in model_kwargs:
attention_mask = model_kwargs["attention_mask"]
model_kwargs["attention_mask"] = torch.cat(
[attention_mask, attention_mask.new_ones((attention_mask.shape[0], 1))], dim=-1
)
Comment on lines +738 to +742
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good catch !


return model_kwargs

def prepare_inputs_for_generation(
Expand Down Expand Up @@ -773,11 +779,6 @@ def prepare_inputs_for_generation(
else:
model_inputs = {"input_ids": input_ids.contiguous()}

# In case cache is not used, manually update the attention mask
if not use_cache and attention_mask is not None and input_ids.shape != attention_mask.shape:
past_length = input_ids.shape[-1] - attention_mask.shape[-1]
attention_mask = torch.cat([attention_mask, torch.ones_like(input_ids[:, :past_length])], dim=-1)

model_inputs.update(
{
"cache_params": cache_params,
Expand Down
14 changes: 7 additions & 7 deletions src/transformers/models/mamba/modeling_mamba.py
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Original file line number Diff line number Diff line change
Expand Up @@ -574,14 +574,13 @@ def set_input_embeddings(self, new_embeddings):
def forward(
self,
input_ids: Optional[torch.LongTensor] = None,
attention_mask: Optional[torch.LongTensor] = None,
inputs_embeds: Optional[torch.LongTensor] = None,
cache_params: Optional[MambaCache] = None,
use_cache: Optional[bool] = None,
output_hidden_states: Optional[bool] = None,
return_dict: Optional[bool] = None,
cache_position: Optional[torch.LongTensor] = None,
**kwargs, # `attention_mask` is passed by the tokenizer and we don't want it
attention_mask: Optional[torch.LongTensor] = None, # Ignored arg
) -> Union[Tuple, MambaOutput]:
output_hidden_states = (
output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
Expand Down Expand Up @@ -691,6 +690,12 @@ def _update_model_kwargs_for_generation(
):
model_kwargs["cache_position"] = model_kwargs["cache_position"][-1:] + num_new_tokens

if "attention_mask" in model_kwargs:
attention_mask = model_kwargs["attention_mask"]
model_kwargs["attention_mask"] = torch.cat(
[attention_mask, attention_mask.new_ones((attention_mask.shape[0], 1))], dim=-1
)

return model_kwargs

def prepare_inputs_for_generation(
Expand Down Expand Up @@ -729,11 +734,6 @@ def prepare_inputs_for_generation(
else:
model_inputs = {"input_ids": input_ids.contiguous()}

# In case cache is not used, manually update the attention mask
if not use_cache and attention_mask is not None and input_ids.shape != attention_mask.shape:
past_length = input_ids.shape[-1] - attention_mask.shape[-1]
attention_mask = torch.cat([attention_mask, torch.ones_like(input_ids[:, :past_length])], dim=-1)

model_inputs.update(
{
"cache_params": cache_params,
Expand Down