Delete configuration.py

configuration.py

@@ -1,68 +0,0 @@
-from transformers.configuration_utils import PretrainedConfig
-
-class STLConfig(PretrainedConfig):
-
-    model_type = "stldec"
-    keys_to_ignore_at_inference = ["past_key_values"]
-    attribute_map = {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}
-
-    def __init__(
-        self,
-        vocab_size=35,
-        decoder_vocab_size=None, # unused
-        max_position_embeddings=1024,
-        encoder_layers=12,
-        encoder_ffn_dim=4096,
-        encoder_attention_heads=16,
-        decoder_layers=12,
-        decoder_ffn_dim=4096,
-        decoder_attention_heads=16,
-        encoder_layerdrop=0.0,
-        decoder_layerdrop=0.0,
-        use_cache=True,
-        is_encoder_decoder=True,
-        activation_function="gelu",
-        d_model=1024,
-        dropout=0.1,
-        attention_dropout=0.0,
-        activation_dropout=0.0,
-        init_std=0.02,
-        decoder_start_token_id=3,
-        scale_embedding=False,
-        pad_token_id=1,
-        eos_token_id=3,
-        bos_token_id=2,
-        forced_eos_token_id=3,
-        share_encoder_decoder_embeddings=True,
-        **kwargs,
-    ):
-        self.vocab_size = vocab_size
-        self.decoder_vocab_size = decoder_vocab_size or vocab_size
-        self.max_position_embeddings = max_position_embeddings
-        self.d_model = d_model
-        self.encoder_ffn_dim = encoder_ffn_dim
-        self.encoder_layers = encoder_layers
-        self.encoder_attention_heads = encoder_attention_heads
-        self.decoder_ffn_dim = decoder_ffn_dim
-        self.decoder_layers = decoder_layers
-        self.decoder_attention_heads = decoder_attention_heads
-        self.dropout = dropout
-        self.attention_dropout = attention_dropout
-        self.activation_dropout = activation_dropout
-        self.activation_function = activation_function
-        self.init_std = init_std
-        self.encoder_layerdrop = encoder_layerdrop
-        self.decoder_layerdrop = decoder_layerdrop
-        self.use_cache = use_cache
-        self.num_hidden_layers = encoder_layers
-        self.scale_embedding = scale_embedding  # scale factor will be sqrt(d_model) if True
-        self.share_encoder_decoder_embeddings = share_encoder_decoder_embeddings
-        super().__init__(
-            bos_token_id=bos_token_id,
-            pad_token_id=pad_token_id,
-            eos_token_id=eos_token_id,
-            is_encoder_decoder=is_encoder_decoder,
-            decoder_start_token_id=decoder_start_token_id,
-            forced_eos_token_id=forced_eos_token_id,
-            **kwargs,
-        )