|
|
|
|
|
|
|
|
|
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) |
|
|
