| | from transformers import PretrainedConfig |
| |
|
| |
|
| | class MELPEncoderConfig(PretrainedConfig): |
| | model_type = "melp" |
| |
|
| | def __init__( |
| | self, |
| | model_size: str = "small", |
| | shared_emb_dim: int = 256, |
| | embed_dim_caption: int = 768, |
| | use_attentional_pool_contrast: bool = True, |
| | use_attentional_pool_caption: bool = True, |
| | n_queries_contrast: int = 14, |
| | n_queries_caption: int = 128, |
| | attn_pooler_heads: int = 8, |
| | proj: str = "linear", |
| | drop: float = 0., |
| | proj_bias: bool = False, |
| | num_leads: int = 12, |
| | **kwargs |
| | ): |
| | self.model_size = model_size |
| | self.shared_emb_dim = shared_emb_dim |
| | self.embed_dim_caption = embed_dim_caption |
| | self.use_attentional_pool_contrast = use_attentional_pool_contrast |
| | self.use_attentional_pool_caption = use_attentional_pool_caption |
| | self.n_queries_contrast = n_queries_contrast |
| | self.n_queries_caption = n_queries_caption |
| | self.attn_pooler_heads = attn_pooler_heads |
| | self.proj = proj |
| | self.drop = drop |
| | self.proj_bias = proj_bias |
| | self.num_leads = num_leads |
| | super().__init__(**kwargs) |
| |
|
