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from transformers import PretrainedConfig |
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class QformerConfig(PretrainedConfig): |
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model_type = 'qformer' |
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_auto_class = 'AutoConfig' |
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def __init__( |
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self, |
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num_query_token=32, |
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visual_hidden_size=4096, |
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llm_hidden_size=768, |
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cross_attention_freq=2, |
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bert="bert-base-uncased", |
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bias=True, |
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qformer_pth=None, |
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**kwargs, |
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): |
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self.num_query_token=num_query_token |
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self.visual_hidden_size = visual_hidden_size |
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self.llm_hidden_size = llm_hidden_size |
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self.bias = bias |
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self.bert = bert |
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self.cross_attention_freq = cross_attention_freq |
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self.qformer_pth = qformer_pth |
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super().__init__(**kwargs) |
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