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improve the eval perf with kv cache #3732

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improve the eval perf with kv cache #3732

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13 changes: 7 additions & 6 deletions examples/models/llama2/eval_llama_lib.py
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Original file line number Diff line number Diff line change
Expand Up @@ -88,12 +88,13 @@ def tok_decode(self, tokens):

def _model_call(self, inps):
if self._use_kv_cache:
result_logits = []
for pos in range(self._max_seq_length):
pos_tensor = torch.tensor([pos], dtype=torch.int64)
logits = self._model(inps[:, pos : pos + 1], pos_tensor)
result_logits.append(logits)
return torch.cat(result_logits, dim=1)
pos_tensor = torch.arange(
self._max_seq_length, dtype=torch.int64, device=self.device
)

# Batch process the whole sequence.
logits = self._model(inps[:, : self._max_seq_length], pos_tensor)
return logits
else:
return self._model(inps)

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