| 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) |
|
|
