fix(model.py): align_preciion_in_norm_layer #182
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KaiLv69
reviewed
May 26, 2024
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| def set_norm_precision_to_float32(self): | ||
| self.weight.data = self.weight.data.to(torch.float32) | ||
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llama里hidden_states和self.weight相乘之后是fp32，应该需要转回16位才能传给下一层，否则会报dtype不match的错。可以检查一下别的模型会不会有这个问题。
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在 Norm Layer 中添加 set_norm_precision_to_float32 函数，在 model 初始化后调用，将 Norm Layer 的权重转成 float32