



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


lowerCamelCase__      =			logging.get_logger(__name__)

lowerCamelCase__      =			{
    # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}






class  SCREAMING_SNAKE_CASE      (				_lowerCamelCase       ):
							__lowerCamelCase						:						List[Any]     ='''megatron-bert'''





							def __init__( self		:		Optional[Any]   ,					__lowercase		:		str=29056   ,					__lowercase		:		Any=1024   ,					__lowercase		:		Optional[Any]=24   ,					__lowercase		:		Optional[Any]=16   ,					__lowercase		:		Dict=4096   ,					__lowercase		:		Union[str, Any]="gelu"   ,					__lowercase		:		List[str]=0.1   ,					__lowercase		:		Any=0.1   ,					__lowercase		:		str=512   ,					__lowercase		:		List[Any]=2   ,					__lowercase		:		Optional[int]=0.02   ,					__lowercase		:		Tuple=1E-12   ,					__lowercase		:		List[str]=0   ,					__lowercase		:		List[str]="absolute"   ,					__lowercase		:		int=True   ,					**__lowercase		:		Dict   ,					):

											'''simple docstring'''
											super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE   ,					**_SCREAMING_SNAKE_CASE						)

											__a	  =		vocab_size
											__a	  =		hidden_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	  =		position_embedding_type
											__a	  =		use_cache





"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


A_						:    str				=      {'configuration_unispeech': ['UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechConfig']}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    Optional[int]				=      [
							    'UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'UniSpeechForCTC',
							    'UniSpeechForPreTraining',
							    'UniSpeechForSequenceClassification',
							    'UniSpeechModel',
							    'UniSpeechPreTrainedModel',
							]

if TYPE_CHECKING:
							from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_unispeech import (
														    UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
														    UniSpeechForCTC,
														    UniSpeechForPreTraining,
														    UniSpeechForSequenceClassification,
														    UniSpeechModel,
														    UniSpeechPreTrainedModel,
														)

else:
							import sys

							A_						:    int				=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





