
"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import _LazyModule


__magic_name__									=					{'''tokenization_byt5''': ['''ByT5Tokenizer''']}


if TYPE_CHECKING:
			from .tokenization_byta import ByTaTokenizer
else:
			import sys

			__magic_name__									=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE							    =							logging.get_logger(__name__)

SCREAMING_SNAKE_CASE							    =							{
    'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
    'studio-ousia/luke-large': 'https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json',
}


class     __UpperCAmelCase							(       __A							):


     """simple docstring"""
     _lowerCamelCase   =      """luke"""


     def __init__(	self  ,       __A=50267  ,       __A=500000  ,       __A=768  ,       __A=256  ,       __A=12  ,       __A=12  ,       __A=3072  ,       __A="gelu"  ,       __A=0.1  ,       __A=0.1  ,       __A=512  ,       __A=2  ,       __A=0.02  ,       __A=1E-12  ,       __A=True  ,       __A=None  ,       __A=1  ,       __A=0  ,       __A=2  ,       **__A  ,       ):
        super().__init__(pad_token_id=__A  ,       bos_token_id=__A  ,       eos_token_id=__A  ,       **__A    )

        __a					=  vocab_size
        __a					=  entity_vocab_size
        __a					=  hidden_size
        __a					=  entity_emb_size
        __a					=  num_hidden_layers
        __a					=  num_attention_heads
        __a					=  hidden_act
        __a					=  intermediate_size
        __a					=  hidden_dropout_prob
        __a					=  attention_probs_dropout_prob
        __a					=  max_position_embeddings
        __a					=  type_vocab_size
        __a					=  initializer_range
        __a					=  layer_norm_eps
        __a					=  use_entity_aware_attention
        __a					=  classifier_dropout



