

'''simple docstring'''





from typing import TYPE_CHECKING

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


lowerCAmelCase__								=		{
    """configuration_distilbert""": [
        """DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """DistilBertConfig""",
        """DistilBertOnnxConfig""",
    ],
    """tokenization_distilbert""": ["""DistilBertTokenizer"""],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__								=		["""DistilBertTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__								=		[
							    """DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """DistilBertForMaskedLM""",
							    """DistilBertForMultipleChoice""",
							    """DistilBertForQuestionAnswering""",
							    """DistilBertForSequenceClassification""",
							    """DistilBertForTokenClassification""",
							    """DistilBertModel""",
							    """DistilBertPreTrainedModel""",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__								=		[
							    """TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFDistilBertForMaskedLM""",
							    """TFDistilBertForMultipleChoice""",
							    """TFDistilBertForQuestionAnswering""",
							    """TFDistilBertForSequenceClassification""",
							    """TFDistilBertForTokenClassification""",
							    """TFDistilBertMainLayer""",
							    """TFDistilBertModel""",
							    """TFDistilBertPreTrainedModel""",
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__								=		[
							    """FlaxDistilBertForMaskedLM""",
							    """FlaxDistilBertForMultipleChoice""",
							    """FlaxDistilBertForQuestionAnswering""",
							    """FlaxDistilBertForSequenceClassification""",
							    """FlaxDistilBertForTokenClassification""",
							    """FlaxDistilBertModel""",
							    """FlaxDistilBertPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_distilbert import (
							    DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    DistilBertConfig,
							    DistilBertOnnxConfig,
							)
							from .tokenization_distilbert import DistilBertTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_distilbert_fast import DistilBertTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_distilbert import (
														    DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DistilBertForMaskedLM,
														    DistilBertForMultipleChoice,
														    DistilBertForQuestionAnswering,
														    DistilBertForSequenceClassification,
														    DistilBertForTokenClassification,
														    DistilBertModel,
														    DistilBertPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_distilbert import (
														    TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFDistilBertForMaskedLM,
														    TFDistilBertForMultipleChoice,
														    TFDistilBertForQuestionAnswering,
														    TFDistilBertForSequenceClassification,
														    TFDistilBertForTokenClassification,
														    TFDistilBertMainLayer,
														    TFDistilBertModel,
														    TFDistilBertPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_distilbert import (
														    FlaxDistilBertForMaskedLM,
														    FlaxDistilBertForMultipleChoice,
														    FlaxDistilBertForQuestionAnswering,
														    FlaxDistilBertForSequenceClassification,
														    FlaxDistilBertForTokenClassification,
														    FlaxDistilBertModel,
														    FlaxDistilBertPreTrainedModel,
														)

else:
							import sys

							lowerCAmelCase__								=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)







import logging

from transformers.configuration_utils import PretrainedConfig


lowerCAmelCase__								=		logging.getLogger(__name__)







class 	lowercase    (				_lowercase							):


		"""simple docstring"""




		a__					       =  "masked_bert"


		def __init__(				self	,       __snake_case=3_05_22	,       __snake_case=7_68	,       __snake_case=12	,       __snake_case=12	,       __snake_case=30_72	,       __snake_case="gelu"	,       __snake_case=0.1	,       __snake_case=0.1	,       __snake_case=5_12	,       __snake_case=2	,       __snake_case=0.0_2	,       __snake_case=1e-12	,       __snake_case=0	,       __snake_case="topK"	,       __snake_case="constant"	,       __snake_case=0.0	,       **__snake_case	,       ):
			super().__init__(pad_token_id=__snake_case	,       **__snake_case)

			_UpperCamelCase   :		List[Any]			=						vocab_size
			_UpperCamelCase   :		Union[str, Any]			=						hidden_size
			_UpperCamelCase   :		Optional[int]			=						num_hidden_layers
			_UpperCamelCase   :		Any			=						num_attention_heads
			_UpperCamelCase   :		int			=						hidden_act
			_UpperCamelCase   :		str			=						intermediate_size
			_UpperCamelCase   :		str			=						hidden_dropout_prob
			_UpperCamelCase   :		Any			=						attention_probs_dropout_prob
			_UpperCamelCase   :		Tuple			=						max_position_embeddings
			_UpperCamelCase   :		Dict			=						type_vocab_size
			_UpperCamelCase   :		str			=						initializer_range
			_UpperCamelCase   :		List[Any]			=						layer_norm_eps
			_UpperCamelCase   :		Tuple			=						pruning_method
			_UpperCamelCase   :		Tuple			=						mask_init
			_UpperCamelCase   :		Dict			=						mask_scale




