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Update local_chat.py

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修复config.architectures[0] == "DeepseekV2ForCausalLM" or "DeepseekV3ForCausalLM" 永远为真
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宁鹏涛 2025-03-01 21:52:48 +08:00 • committed by GitHub
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ktransformers/local_chat.py
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@ -169,7 +169,7 @@ def local_chat(
assert Config().long_context_config['max_seq_len'] > input_tensor.shape[1] + max_new_tokens, \ assert Config().long_context_config['max_seq_len'] > input_tensor.shape[1] + max_new_tokens, \
"please change max_seq_len in ~/.ktransformers/config.yaml" "please change max_seq_len in ~/.ktransformers/config.yaml"
if system != "Windows" and (config.architectures[0] == "DeepseekV2ForCausalLM" or "DeepseekV3ForCausalLM") and flashinfer_enabled and get_compute_capability() >= 8: if system != "Windows" and (config.architectures[0] == "DeepseekV2ForCausalLM" or config.architectures[0] == "DeepseekV3ForCausalLM") and flashinfer_enabled and get_compute_capability() >= 8:
generated = prefill_and_generate( generated = prefill_and_generate(
model, tokenizer, input_tensor.cuda(), max_new_tokens, use_cuda_graph, mode = mode, force_think = force_think, chunk_prefill_size = chunk_prefill_size, model, tokenizer, input_tensor.cuda(), max_new_tokens, use_cuda_graph, mode = mode, force_think = force_think, chunk_prefill_size = chunk_prefill_size,
use_flashinfer_mla = True, num_heads = config.num_attention_heads, head_dim_ckv = config.kv_lora_rank, head_dim_kpe = config.qk_rope_head_dim, q_head_dim = config.qk_rope_head_dim + config.qk_nope_head_dim use_flashinfer_mla = True, num_heads = config.num_attention_heads, head_dim_ckv = config.kv_lora_rank, head_dim_kpe = config.qk_rope_head_dim, q_head_dim = config.qk_rope_head_dim + config.qk_nope_head_dim