File size: 2,732 Bytes
5b878c2 0507803 5b878c2 0507803 5b878c2 c2502f1 5b878c2 c2502f1 5b878c2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging
from transformers import GPT2Config
logger = logging.get_logger(__name__)
class LOLAConfig(PretrainedConfig):
"""
This is the configuration class is a modified copy of https://huggingface.co/openai-community/gpt2 with MoE support.
"""
model_type = "lola_v1"
keys_to_ignore_at_inference = ["past_key_values"]
attribute_map = {
"hidden_size": "n_embd",
"max_position_embeddings": "n_positions",
"num_attention_heads": "n_head",
"num_hidden_layers": "n_layer",
}
def __init__(
self,
vocab_size=100096, # Padded vocab size, actual size is 100000
n_positions=2048,
n_embd=2048,
n_layer=24,
n_head=16,
n_inner=8192,
activation_function="gelu_new",
resid_pdrop=0.1,
embd_pdrop=0.1,
attn_pdrop=0.1,
layer_norm_epsilon=1e-5,
initializer_range=0.02,
summary_type="cls_index",
summary_use_proj=True,
summary_activation=None,
summary_proj_to_labels=True,
summary_first_dropout=0.1,
scale_attn_weights=True,
use_cache=True,
bos_token_id=0,
eos_token_id=5,
scale_attn_by_inverse_layer_idx=False,
reorder_and_upcast_attn=False,
num_experts=16,
topk=1,
router_aux_loss_coef=0.01,
**kwargs,
):
self.vocab_size = vocab_size
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.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.summary_type = summary_type
self.summary_use_proj = summary_use_proj
self.summary_activation = summary_activation
self.summary_first_dropout = summary_first_dropout
self.summary_proj_to_labels = summary_proj_to_labels
self.scale_attn_weights = scale_attn_weights
self.use_cache = use_cache
self.scale_attn_by_inverse_layer_idx = scale_attn_by_inverse_layer_idx
self.reorder_and_upcast_attn = reorder_and_upcast_attn
self.num_experts = num_experts
self.topk = topk
self.bos_token_id = bos_token_id
self.eos_token_id = eos_token_id
self.router_aux_loss_coef = router_aux_loss_coef
super().__init__(bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
|