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Fix qwen's position_ids no enough #10572

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merged 2 commits into from
Mar 28, 2024
Merged

Fix qwen's position_ids no enough #10572

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5943798
fix position_ids
qiuxin2012 Mar 28, 2024
93d9f44
fix position_ids
qiuxin2012 Mar 28, 2024
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2 changes: 0 additions & 2 deletions python/llm/src/ipex_llm/transformers/convert.py
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Original file line number Diff line number Diff line change
Expand Up @@ -595,7 +595,6 @@ def merge_qk_proj_func(module):
from ipex_llm.transformers.models.bert import merge_qkv
model.apply(merge_qkv)
if model.config.model_type == "qwen":
position_ids = torch.arange(0, model.config.max_position_embeddings)
rope_base = model.config.rotary_emb_base
from accelerate.big_modeling import init_empty_weights

Expand Down Expand Up @@ -625,7 +624,6 @@ def split_qkv_proj_func(module):
module.q_proj = q_proj
module.k_proj = k_proj
module.v_proj = v_proj
module.position_ids = position_ids
module.rope_base = rope_base
del module.c_attn
model.apply(split_qkv_proj_func)
Expand Down
13 changes: 7 additions & 6 deletions python/llm/src/ipex_llm/transformers/models/qwen.py
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Original file line number Diff line number Diff line change
Expand Up @@ -136,6 +136,8 @@ def qwen_attention_forward_original(
device = hidden_states.device
# for flash attention
original_dtype = hidden_states.dtype
position_ids = rotary_pos_emb_list[-1] # the last one is posisiton_ids
rotary_pos_emb_list = rotary_pos_emb_list[:-1]

use_fuse_rope = should_use_fuse_rope(self, hidden_states)
qtype_check = decoding_fast_path_qtype_check(self.q_proj)
Expand All @@ -147,8 +149,6 @@ def qwen_attention_forward_original(
cache_v = cache_v.transpose(1, 2)

kv_seq_len = cache_k.shape[-2]
self.position_ids = self.position_ids.to(device)
position_ids = self.position_ids[kv_seq_len]
base = self.rope_base
if is_enough_kv_cache_room(layer_past, kv_seq_len):
new_cache_k, new_cache_v = extend_kv_cache(bsz,
Expand Down Expand Up @@ -182,7 +182,7 @@ def qwen_attention_forward_original(
# query = self._split_heads(query, self.num_heads, self.head_dim)
# key = self._split_heads(key, self.num_heads, self.head_dim)
# value = self._split_heads(value, self.num_heads, self.head_dim)
if rotary_pos_emb_list is not None:
if len(rotary_pos_emb_list) != 0:
cur_len = query.shape[1]
if len(rotary_pos_emb_list) == 1:
rotary_pos_emb = rotary_pos_emb_list[0]
Expand Down Expand Up @@ -332,6 +332,8 @@ def qwen_attention_forward_quantized(

bsz, q_len, _ = hidden_states.size()
device = hidden_states.device
position_ids = rotary_pos_emb_list[-1] # the last one is posisiton_ids
rotary_pos_emb_list = rotary_pos_emb_list[:-1]

use_fuse_rope = should_use_fuse_rope(self, hidden_states)
# qtype_check = decoding_fast_path_qtype_check(self.q_proj)
Expand All @@ -349,7 +351,6 @@ def qwen_attention_forward_quantized(
device=device
)

position_ids = self.position_ids[self.kv_seq_len].to(device)
base = self.rope_base

args = [hidden_states, self.q_proj.weight.data, self.k_proj.weight.data,
Expand Down Expand Up @@ -599,7 +600,7 @@ def qwen_model_forward(
if self.use_cache_quantization:
past_length = past_key_values[0][0][0].size(2)
else:
past_length = past_key_values[0][0].size(-2)
past_length = past_key_values[0][0].size(1)
if position_ids is None:
position_ids = torch.arange(
past_length,
Expand Down Expand Up @@ -651,7 +652,7 @@ def qwen_model_forward(
self.rotary_emb._ntk_alpha_cached_list = ntk_alpha_list
rotary_pos_emb_list = [
self.rotary_emb(kv_seq_len, ntk_alpha=ntk_alpha) for ntk_alpha in ntk_alpha_list
]
] + [position_ids]

hidden_states = self.drop(hidden_states)
output_shape = input_shape + (hidden_states.size(-1),)
Expand Down
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