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HF forward labels #128

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HF forward labels #128

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460c239
hf forward labels
sedrick-keh-tri Dec 1, 2023
bdc42f0
black reformat
sedrick-keh-tri Dec 12, 2023
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17 changes: 16 additions & 1 deletion open_lm/utils/transformers/hf_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,6 +52,7 @@ def forward(
position_ids: Optional[torch.LongTensor] = None,
past_key_values: Optional[List[torch.FloatTensor]] = None,
inputs_embeds: Optional[torch.FloatTensor] = None,
labels: Optional[torch.LongTensor] = None,
use_cache: Optional[bool] = None,
output_attentions: Optional[bool] = None,
output_hidden_states: Optional[bool] = None,
Expand All @@ -78,7 +79,21 @@ def forward(
```"""
# decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)
logits, _ = self.model(input_ids)
output = CausalLMOutputWithPast(logits=logits)

if labels is not None:
# Shift so that tokens < n predict n
shift_logits = logits[..., :-1, :].contiguous()
shift_labels = labels[..., 1:].contiguous()
# Flatten the tokens
loss_fct = CrossEntropyLoss()
shift_logits = shift_logits.view(-1, self.config.vocab_size)
shift_labels = shift_labels.view(-1)
# Enable model parallelism
shift_labels = shift_labels.to(shift_logits.device)
loss = loss_fct(shift_logits, shift_labels)
output = CausalLMOutputWithPast(loss=loss, logits=logits)
else:
output = CausalLMOutputWithPast(logits=logits)
return output

def prepare_inputs_for_generation(
Expand Down