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Update optimize qwen (#9943)

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* update for n tokens input

* fix dtype

* update
This commit is contained in:
Wang, Jian4 2024-01-19 16:54:59 +08:00 committed by GitHub
parent db8e90796a
commit bcaeb05272
1 changed files with 15 additions and 9 deletions
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18
python/llm/src/bigdl/llm/transformers/models/qwen.py
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@ -119,13 +119,12 @@ def qwen_attention_forward(
seq_end = kv_seq_len seq_end = kv_seq_len
logn_tensor = self.logn_tensor[:, seq_start:seq_end, :, :].type_as(query) logn_tensor = self.logn_tensor[:, seq_start:seq_end, :, :].type_as(query)
query = query * logn_tensor.expand_as(query) query = query * logn_tensor.expand_as(query)
if key_size == kv_seq_len:
causal_mask = torch.tril( causal_mask = torch.tril(
torch.ones((key_size, key_size), dtype=torch.bool, device=query.device) torch.ones((key_size, key_size), dtype=torch.bool, device=query.device)
).view(1, 1, key_size, key_size) ).view(1, 1, key_size, key_size)
else:
causal_mask = causal_mask[ causal_mask = None
:, :, key.size(1) - query.size(1): key.size(1), :key.size(1)
]
if quantize_kv_cache(self.c_attn, hidden_states): if quantize_kv_cache(self.c_attn, hidden_states):
query, key, value = query.transpose(1, 2), key.transpose(1, 2), value.transpose(1, 2) query, key, value = query.transpose(1, 2), key.transpose(1, 2), value.transpose(1, 2)
@ -207,9 +206,16 @@ def qwen_attention_forward(
value = new_value_states value = new_value_states
query = query.transpose(1, 2) query = query.transpose(1, 2)
# skip first init and only works for n tokens input
if causal_mask is None and query.size(2) > 1:
causal_mask = torch.tril(
torch.ones((key.size(2), key.size(2)), dtype=torch.bool, device=query.device)
).view(1, 1, key.size(2), key.size(2))
causal_mask = causal_mask[
:, :, key.size(2) - query.size(2): key.size(2), :key.size(2)
]
attn_output, attn_weight = self._attn( attn_output, attn_weight = self._attn(
query, key, value, causal_mask, attention_mask, head_mask query.to(key.dtype), key, value, causal_mask, attention_mask, head_mask
) )
context_layer = self._merge_heads( context_layer = self._merge_heads(