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optimize internlm xcomposser performance again #11551

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Jul 10, 2024
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optimize internlm xcomposser performance again #11551

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1 change: 1 addition & 0 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 @@ -1261,6 +1261,7 @@ def _optimize_post(model, lightweight_bmm=False):
convert_forward(model, module.InternLM2Attention, internlm_xcomposser2_attention_forward)
from ipex_llm.transformers.models.internlm import internlm_xcomposser2_mlp_forward
convert_forward(model, module.InternLM2MLP, internlm_xcomposser2_mlp_forward)
convert_forward(model, module.InternLM2RMSNorm, llama_rms_norm_forward)
from ipex_llm.transformers.models.internlm import internlm_xcomposser2_chat
model.chat = MethodType(internlm_xcomposser2_chat, model)
elif model.config.model_type == "qwen":
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10 changes: 6 additions & 4 deletions python/llm/src/ipex_llm/transformers/models/internlm.py
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Expand Up @@ -359,12 +359,14 @@ def internlm_xcomposser2_attention_forward(
kv_seq_len += past_key_value[0].shape[-2]

# IPEX-LLM OPT: fuse rope
cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
if should_use_fuse_rope(hidden_states, position_ids, self.training):
query_states, key_states = apply_rotary_pos_emb_cache_freq_xpu(
query_states, key_states, sin, cos, "internlm", position_ids
)
# This fuse rope will get wrong result if context_length > max_position_embeddings (32768)
# we assume context_length <= 32768
import xe_addons
xe_addons.rotary_half_inplaced(self.rotary_emb.inv_freq, position_ids,
query_states, key_states)
else:
cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
query_states, key_states = apply_rotary_pos_emb(
query_states, key_states, cos, sin, position_ids, "internlm")

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