[LLM] Support gpt3 fine grained dybatch v1 #7080
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@@ Coverage Diff @@
## develop #7080 +/- ##
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- Coverage 59.91% 59.78% -0.13%
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Files 556 558 +2
Lines 82037 82217 +180
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+ Hits 49149 49152 +3
- Misses 32888 33065 +177
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| def set_state_dict(self, state_dict): | ||
| dtype = paddle.get_default_dtype() | ||
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| for k, v in state_dict.items(): |
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这里的if代码有点多啊？能改的和llama里的一样吗？
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建议先这样写，因为gpt的模型来源比较复杂，参数名比较乱，这种if写法已经尽可能多的兼容各种命名的模型了
wj-Mcat
requested changes
Sep 20, 2023
| cls, pretrained_model_name_or_path, from_hf_hub: bool = False, subfolder: str | None = None, *args, **kwargs | ||
| ): | ||
| # TODO: Support safetensors loading. | ||
| kwargs["use_safetensors"] = False |
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| kwargs["use_safetensors"] = False | |
| kwargs["use_safetensors"] = kwargs.get("use_safetensors", False) |
建议使用这个，因为单分片 safetensors 是可以支持 inferencemodel 加载的。
| position_ids = tgt_pos | ||
| attention_mask = (tgt_generation_mask - 1) * 1e4 | ||
| else: | ||
| attention_mask = (attention_mask - 1) * 1e4 |
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这里建议使用：paddle.finfo(attention_mask.dtype).min 的方式来转化 attention_mask 的值。
在 bf16 和 fp16 下面不同值域不一样，建议用这个来得到该 dtype 下的最小值。
上面的 tgt_attention_mask 也是需要调整一下。
可以的，我想补充单测和comment指出的问题 放在下个PR一块做吧，这个PR先合一版？ |
wj-Mcat
approved these changes
Sep 20, 2023
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Description
Support gpt3 fine grained dybatch v1.