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|
|
| from transformers.configuration_utils import PretrainedConfig |
|
|
| CODESAGE_PRETRAINED_CONFIG_ARCHIVE_MAP = { |
| "codesage/codesage-small": "https://huggingface.co/codesage/codesage-small/resolve/main/config.json", |
| "codesage/codesage-base": "https://huggingface.co/codesage/codesage-base/resolve/main/config.json", |
| "codesage/codesage-large": "https://huggingface.co/codesage/codesage-large/resolve/main/config.json", |
| } |
|
|
|
|
| class CodeSageConfig(PretrainedConfig): |
| model_type = "codesage" |
|
|
| def __init__( |
| self, |
| vocab_size=50257, |
| max_position_embeddings=1024, |
| hidden_size=768, |
| num_hidden_layers=12, |
| num_attention_heads=12, |
| intermediate_size=3072, |
| activation_function="gelu_new", |
| residual_dropout_prob=0.1, |
| embedding_dropout_prob=0.1, |
| attention_dropout_prob=0.1, |
| layer_norm_epsilon=1e-5, |
| initializer_range=0.02, |
| position_embedding_type='absolute', |
| bos_token_id=0, |
| eos_token_id=0, |
| pad_token_id=49153, |
| **kwargs |
| ): |
| self.vocab_size = vocab_size |
| self.max_position_embeddings = max_position_embeddings |
| self.hidden_size = hidden_size |
| self.num_hidden_layers = num_hidden_layers |
| self.num_attention_heads = num_attention_heads |
| self.intermediate_size = intermediate_size |
| assert 'gelu' in activation_function |
| self.activation_function = activation_function |
| self.residual_dropout_prob = residual_dropout_prob |
| self.embedding_dropout_prob = embedding_dropout_prob |
| self.attention_dropout_prob = attention_dropout_prob |
| self.layer_norm_epsilon = layer_norm_epsilon |
| self.initializer_range = initializer_range |
| self.position_embedding_type = position_embedding_type |
|
|
| super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs) |
|
|
