


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCamelCase :				Union[str, Any]						    =       logging.get_logger(__name__)

UpperCamelCase :				Any						    =       {
    '''squeezebert/squeezebert-uncased''': (
        '''https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json'''
    ),
    '''squeezebert/squeezebert-mnli''': '''https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json''',
    '''squeezebert/squeezebert-mnli-headless''': (
        '''https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json'''
    ),
}

class     __snake_case							(      _UpperCAmelCase):
     SCREAMING_SNAKE_CASE_		:					Dict 				= SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
     SCREAMING_SNAKE_CASE_		:					Optional[int] 				= "squeezebert"
     def __init__(	self					:	Any  ,			_lowerCAmelCase					:	Optional[int]=3_0_5_2_2  ,			_lowerCAmelCase					:	Optional[int]=7_6_8  ,			_lowerCAmelCase					:	Optional[int]=1_2  ,			_lowerCAmelCase					:	str=1_2  ,			_lowerCAmelCase					:	int=3_0_7_2  ,			_lowerCAmelCase					:	int="gelu"  ,			_lowerCAmelCase					:	List[Any]=0.1  ,			_lowerCAmelCase					:	Optional[Any]=0.1  ,			_lowerCAmelCase					:	Optional[Any]=5_1_2  ,			_lowerCAmelCase					:	Any=2  ,			_lowerCAmelCase					:	Optional[int]=0.02  ,			_lowerCAmelCase					:	str=1E-1_2  ,			_lowerCAmelCase					:	str=0  ,			_lowerCAmelCase					:	int=7_6_8  ,			_lowerCAmelCase					:	List[Any]=4  ,			_lowerCAmelCase					:	Optional[int]=4  ,			_lowerCAmelCase					:	List[str]=4  ,			_lowerCAmelCase					:	Any=1  ,			_lowerCAmelCase					:	Dict=4  ,			_lowerCAmelCase					:	Tuple=4  ,			**_lowerCAmelCase					:	List[Any]  ,			)       ->				List[str]:



           '''simple docstring'''





           super().__init__(pad_token_id=_lowerCAmelCase  ,			**_lowerCAmelCase     )

           __magic_name__ 		=			vocab_size
           __magic_name__ 		=			hidden_size
           __magic_name__ 		=			num_hidden_layers
           __magic_name__ 		=			num_attention_heads
           __magic_name__ 		=			hidden_act
           __magic_name__ 		=			intermediate_size
           __magic_name__ 		=			hidden_dropout_prob
           __magic_name__ 		=			attention_probs_dropout_prob
           __magic_name__ 		=			max_position_embeddings
           __magic_name__ 		=			type_vocab_size
           __magic_name__ 		=			initializer_range
           __magic_name__ 		=			layer_norm_eps
           __magic_name__ 		=			embedding_size
           __magic_name__ 		=			q_groups
           __magic_name__ 		=			k_groups
           __magic_name__ 		=			v_groups
           __magic_name__ 		=			post_attention_groups
           __magic_name__ 		=			intermediate_groups
           __magic_name__ 		=			output_groups







class     __snake_case							(      _UpperCAmelCase):
     @property
     def   a (	self					:	Dict     )       ->				Mapping[str, Mapping[int, str]]:



           '''simple docstring'''





           if self.task == "multiple-choice":
                 __magic_name__ 		=			{0: 'batch', 1: 'choice', 2: 'sequence'}
           else:
                 __magic_name__ 		=			{0: 'batch', 1: 'sequence'}
           return OrderedDict(
               [
                   ('input_ids', dynamic_axis),
                   ('attention_mask', dynamic_axis),
                   ('token_type_ids', dynamic_axis),
               ]     )





from typing import TYPE_CHECKING

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


UpperCamelCase :				str						    =       {
    '''configuration_bart''': ['''BART_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BartConfig''', '''BartOnnxConfig'''],
    '''tokenization_bart''': ['''BartTokenizer'''],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase :				Optional[int]						    =       ['''BartTokenizerFast''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase :				Any						    =       [
					    '''BART_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''BartForCausalLM''',
					    '''BartForConditionalGeneration''',
					    '''BartForQuestionAnswering''',
					    '''BartForSequenceClassification''',
					    '''BartModel''',
					    '''BartPretrainedModel''',
					    '''PretrainedBartModel''',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase :				Tuple						    =       [
					    '''TFBartForConditionalGeneration''',
					    '''TFBartForSequenceClassification''',
					    '''TFBartModel''',
					    '''TFBartPretrainedModel''',
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase :				List[Any]						    =       [
					    '''FlaxBartDecoderPreTrainedModel''',
					    '''FlaxBartForCausalLM''',
					    '''FlaxBartForConditionalGeneration''',
					    '''FlaxBartForQuestionAnswering''',
					    '''FlaxBartForSequenceClassification''',
					    '''FlaxBartModel''',
					    '''FlaxBartPreTrainedModel''',
					]

if TYPE_CHECKING:
					from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
					from .tokenization_bart import BartTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_bart_fast import BartTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_bart import (
										    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
										    BartForCausalLM,
										    BartForConditionalGeneration,
										    BartForQuestionAnswering,
										    BartForSequenceClassification,
										    BartModel,
										    BartPretrainedModel,
										    PretrainedBartModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_bart import (
										    TFBartForConditionalGeneration,
										    TFBartForSequenceClassification,
										    TFBartModel,
										    TFBartPretrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_bart import (
										    FlaxBartDecoderPreTrainedModel,
										    FlaxBartForCausalLM,
										    FlaxBartForConditionalGeneration,
										    FlaxBartForQuestionAnswering,
										    FlaxBartForSequenceClassification,
										    FlaxBartModel,
										    FlaxBartPreTrainedModel,
										)

else:
					import sys

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

