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| # data file | ||
| alpaca_data/ | ||
| libai/version.py | ||
| sft_result |
| example = tokenizer.tokenize( | ||
| full_prompt_and_response, add_bos=True, add_eos=True, device="cpu" | ||
| full_prompt_and_response, add_bos=True, add_eos=True, device=None, | ||
| # device="cpu" |
xiezipeng-ML
reviewed
Nov 2, 2024
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| self.scale_mask_softmax_fusion = scale_mask_softmax_fusion | ||
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| self.query_key_value = Linear( |
Contributor
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这个实现有问题导致的之后的k，v相关计算对不上，GQA里k，v的num_head数量和q不一样，参考chatglm的方式实现：
libai/projects/ChatGLM/chatglm.py
Lines 245 to 259 in 9dcbe3b
xiezipeng-ML
reviewed
Nov 2, 2024
| query_key_value = query_key_value.permute( | ||
| 0, 2, 1, 3 | ||
| ) # [bsz, num_heads, src_len, 3 * head_size] | ||
| query, key, value = flow.chunk(query_key_value, chunks=3, dim=-1) |
Contributor
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这里的k和v的num_head排列顺序有问题，GQA里是多个q_head对应单个k_head,v_head，
举个例子
# k的h1对应q的h1，h2
q: [h1, h2, h3, h4]
k: [ h1, h2]
v: [ h1, h2]
repeat k,v的head后：
# k的h1对应q的h1，h2
q: [h1, h2, h3, h4]
k: [h1, h1, h2, h2]
v: [h1, h1, h2, h2]
但是这里的实现结果k,v head排列顺序有问题，所以之后计算是有问题的
# k的h1对应q的h1，h2
q: [h1, h2, h3, h4]
k: [h1, h2, h1, h2]
v: [h1, h2, h1, h2]
参考chaglm的实现：
libai/projects/ChatGLM/chatglm.py
Lines 332 to 356 in 9dcbe3b
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