bert.py

from omegaconf import DictConfig
from libai.config import LazyCall
from libai.models import BertModel, BertForPreTraining


cfg = dict(
    vocab_size=30522,
    hidden_size=768,
    hidden_layers=24,
    num_attention_heads=12,
    intermediate_size=4096,
    hidden_dropout_prob=0.1,
    attention_probs_dropout_prob=0.1,
    max_position_embeddings=512,
    num_tokentypes=2,
    add_pooling_layer=True,
    initializer_range=0.02,
    layernorm_eps=1e-5,
    bias_gelu_fusion=True,
    bias_dropout_fusion=True,
    scale_mask_softmax_fusion=True,
    apply_query_key_layer_scaling=True,
    apply_residual_post_layernorm=False,
    add_binary_head=True,
    amp_enabled=False,
)

cfg = DictConfig(cfg)

bert_model = LazyCall(BertModel)(cfg=cfg)

pretrain_model = LazyCall(BertForPreTraining)(cfg=cfg)