🤖 Lint code

ivy_models/bart/config_bart.py

@@ -216,33 +216,33 @@ class BartConfig(BaseSpec):
         "num_attention_heads": "encoder_attention_heads",
         "hidden_size": "d_model",
     }
-    
-    vocab_size: int = 50265,
-    max_position_embeddings: int = 1024,
-    encoder_layers: int = 12,
-    encoder_ffn_dim: int = 4096,
-    encoder_attention_heads: int = 16,
-    decoder_layers: int = 12,
-    decoder_ffn_dim: int = 4096,
-    decoder_attention_heads: int = 16,
-    encoder_layerdrop: float = 0.0,
-    decoder_layerdrop: float = 0.0,
-    activation_function: str = "gelu",
-    d_model: int = 1024,
-    dropout: float = 0.1,
-    attention_dropout: float = 0.0,
-    activation_dropout: float = 0.0,
-    init_std: float = 0.02,
-    classifier_dropout: float = 0.0,
-    scale_embedding: bool = False,
-    use_cache: bool = True,
-    num_labels: int = 3,
-    pad_token_id: int = 1,
-    bos_token_id: int = 0,
-    eos_token_id: int = 2,
-    is_encoder_decoder: bool = True,
-    decoder_start_token_id: int = 2,
-    forced_eos_token_id: int = 2,
+
+    vocab_size: int = (50265,)
+    max_position_embeddings: int = (1024,)
+    encoder_layers: int = (12,)
+    encoder_ffn_dim: int = (4096,)
+    encoder_attention_heads: int = (16,)
+    decoder_layers: int = (12,)
+    decoder_ffn_dim: int = (4096,)
+    decoder_attention_heads: int = (16,)
+    encoder_layerdrop: float = (0.0,)
+    decoder_layerdrop: float = (0.0,)
+    activation_function: str = ("gelu",)
+    d_model: int = (1024,)
+    dropout: float = (0.1,)
+    attention_dropout: float = (0.0,)
+    activation_dropout: float = (0.0,)
+    init_std: float = (0.02,)
+    classifier_dropout: float = (0.0,)
+    scale_embedding: bool = (False,)
+    use_cache: bool = (True,)
+    num_labels: int = (3,)
+    pad_token_id: int = (1,)
+    bos_token_id: int = (0,)
+    eos_token_id: int = (2,)
+    is_encoder_decoder: bool = (True,)
+    decoder_start_token_id: int = (2,)
+    forced_eos_token_id: int = (2,)
 
     def get(self, *attr_names):
         new_dict = {}