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# coding=utf-8
""" MetaLA configuration"""
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging
logger = logging.get_logger(__name__)
LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP = {}
class MetaLAConfig(PretrainedConfig):
model_type = "metala"
keys_to_ignore_at_inference = ["past_key_values"]
def __init__(
self,
pad_token_id=1,
bos_token_id=0,
eos_token_id=2,
vocab_size=50272,
use_cache=True,
init_std=0.02,
# model config
decoder_embed_dim=1024,
decoder_layers=24,
decoder_attention_heads=8,
add_bos_token=False,
causal=True,
glu_act="none",
glu_dim=5632,
bias=False,
norm_type="simplermsnorm",
no_scale_embedding=True,
use_gk=True,
use_gv=False,
**kwargs,
):
super().__init__(
pad_token_id=pad_token_id,
bos_token_id=bos_token_id,
eos_token_id=eos_token_id,
**kwargs,
)
# hf origin
self.vocab_size = vocab_size
self.use_cache = use_cache
self.init_std = init_std
# add
self.decoder_embed_dim = decoder_embed_dim
self.decoder_layers = decoder_layers
self.decoder_attention_heads = decoder_attention_heads
self.add_bos_token = add_bos_token
self.causal = causal
self.glu_act = glu_act
self.glu_dim = glu_dim
self.bias = bias
self.norm_type = norm_type
self.no_scale_embedding = no_scale_embedding
self.use_gk = use_gk
self.use_gv = use_gv |