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| from transformers.configuration_utils import PretrainedConfig |
| from transformers.utils import logging |
|
|
| logger = logging.get_logger(__name__) |
|
|
|
|
| class CodeGenConfig(PretrainedConfig): |
| model_type = "codegen" |
|
|
| def __init__( |
| self, |
| vocab_size=50400, |
| n_positions=2048, |
| n_ctx=2048, |
| n_embd=4096, |
| n_layer=28, |
| n_head=16, |
| rotary_dim=64, |
| n_inner=None, |
| activation_function="gelu_new", |
| resid_pdrop=0.0, |
| embd_pdrop=0.0, |
| attn_pdrop=0.0, |
| layer_norm_epsilon=1e-5, |
| initializer_range=0.02, |
| scale_attn_weights=True, |
| gradient_checkpointing=False, |
| use_cache=True, |
| bos_token_id=50256, |
| eos_token_id=50256, |
| **kwargs |
| ): |
| super().__init__(bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs) |
|
|
| self.vocab_size = vocab_size |
| self.n_ctx = n_ctx |
| self.n_positions = n_positions |
| self.n_embd = n_embd |
| self.n_layer = n_layer |
| self.n_head = n_head |
| self.n_inner = n_inner |
| self.rotary_dim = rotary_dim |
| self.activation_function = activation_function |
| self.resid_pdrop = resid_pdrop |
| self.embd_pdrop = embd_pdrop |
| self.attn_pdrop = attn_pdrop |
| self.layer_norm_epsilon = layer_norm_epsilon |
| self.initializer_range = initializer_range |
| self.gradient_checkpointing = gradient_checkpointing |
| self.scale_attn_weights = scale_attn_weights |
| self.use_cache = use_cache |
|
|
| self.bos_token_id = bos_token_id |
| self.eos_token_id = eos_token_id |
|
|
| @property |
| def max_position_embeddings(self): |
| return self.n_positions |
|
|
| @property |
| def hidden_size(self): |
| return self.n_embd |
|
|
| @property |
| def num_attention_heads(self): |
| return self.n_head |
|
|
| @property |
| def num_hidden_layers(self): |
| return self.n_layer |
|
|