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""" |
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================================================ |
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@author: Jaron |
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@time: 2024/07/10 19:43:31 |
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@email: [email protected] |
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@description: Causal Cross-Attention Mask (CCAM) |
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================================================ |
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""" |
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from transformers import PretrainedConfig |
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class CCAMConfig(PretrainedConfig): |
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model_type = 'ccam' |
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_auto_class = 'AutoConfig' |
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def __init__( |
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self, |
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num_query: int = 1024, |
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num_heads: int = 16, |
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hidden_size: int = 1024, |
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intermediate_size: int = 4096, |
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num_key_value_heads: int = 16, |
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dropout: float = 0.1, |
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mlp_bias: bool = True, |
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hidden_act: str = 'swiglu', |
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output_size: int = None, |
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attention_bias: bool = True, |
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layer_norm_eps: float = 1e-5, |
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cross_hidden_size: int = None, |
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attention_dropout: float = 0.1, |
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_attn_implementation: str = 'sdpa', |
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**kwargs |
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): |
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super().__init__(**kwargs) |
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self.dropout = dropout |
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self.mlp_bias = mlp_bias |
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self.num_query = num_query |
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self.num_heads = num_heads |
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self.hidden_act = hidden_act |
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self.hidden_size = hidden_size |
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self.output_size = output_size |
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self.layer_norm_eps = layer_norm_eps |
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self.attention_bias = attention_bias |
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self.intermediate_size = intermediate_size |
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self.cross_hidden_size = cross_hidden_size |
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self.attention_dropout = attention_dropout |
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self.num_key_value_heads = num_key_value_heads |
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self._attn_implementation = _attn_implementation |
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