



'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


__lowerCAmelCase						      =       {
    '''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
    '''albert-large-v1''': '''https://huggingface.co/albert-large-v1/resolve/main/config.json''',
    '''albert-xlarge-v1''': '''https://huggingface.co/albert-xlarge-v1/resolve/main/config.json''',
    '''albert-xxlarge-v1''': '''https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json''',
    '''albert-base-v2''': '''https://huggingface.co/albert-base-v2/resolve/main/config.json''',
    '''albert-large-v2''': '''https://huggingface.co/albert-large-v2/resolve/main/config.json''',
    '''albert-xlarge-v2''': '''https://huggingface.co/albert-xlarge-v2/resolve/main/config.json''',
    '''albert-xxlarge-v2''': '''https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json''',
}

class      __magic_name__						(   _UpperCamelCase       ):
							lowerCAmelCase	:   Optional[Any]           = 'albert'







							def __init__(							self :	Tuple     ,_UpperCAmelCase :	List[str]=30000     ,_UpperCAmelCase :	Dict=128     ,_UpperCAmelCase :	Dict=4096     ,_UpperCAmelCase :	Tuple=12     ,_UpperCAmelCase :	List[Any]=1     ,_UpperCAmelCase :	Any=64     ,_UpperCAmelCase :	List[str]=16384     ,_UpperCAmelCase :	Any=1     ,_UpperCAmelCase :	str="gelu_new"     ,_UpperCAmelCase :	Any=0     ,_UpperCAmelCase :	Union[str, Any]=0     ,_UpperCAmelCase :	Optional[int]=512     ,_UpperCAmelCase :	Tuple=2     ,_UpperCAmelCase :	str=0.02     ,_UpperCAmelCase :	Tuple=1E-12     ,_UpperCAmelCase :	Optional[int]=0.1     ,_UpperCAmelCase :	int="absolute"     ,_UpperCAmelCase :	Optional[int]=0     ,_UpperCAmelCase :	Any=2     ,_UpperCAmelCase :	List[Any]=3     ,**_UpperCAmelCase :	int     ,):
									super().__init__(pad_token_id=_UpperCAmelCase     ,bos_token_id=_UpperCAmelCase     ,eos_token_id=_UpperCAmelCase     ,**_UpperCAmelCase		)

									_a					:				Optional[Any]				=							vocab_size
									_a					:				List[str]				=							embedding_size
									_a					:				Union[str, Any]				=							hidden_size
									_a					:				List[Any]				=							num_hidden_layers
									_a					:				List[Any]				=							num_hidden_groups
									_a					:				int				=							num_attention_heads
									_a					:				List[str]				=							inner_group_num
									_a					:				int				=							hidden_act
									_a					:				Optional[int]				=							intermediate_size
									_a					:				List[str]				=							hidden_dropout_prob
									_a					:				int				=							attention_probs_dropout_prob
									_a					:				Any				=							max_position_embeddings
									_a					:				str				=							type_vocab_size
									_a					:				str				=							initializer_range
									_a					:				Tuple				=							layer_norm_eps
									_a					:				List[str]				=							classifier_dropout_prob
									_a					:				str				=							position_embedding_type

class      __magic_name__						(   _UpperCamelCase       ):







							@property
							def 							__lowercase      (							self :	Union[str, Any]		):
									if self.task == "multiple-choice":
											_a					:				Optional[Any]				=							{0: 'batch', 1: 'choice', 2: 'sequence'}
									else:
											_a					:				Union[str, Any]				=							{0: 'batch', 1: 'sequence'}
									return OrderedDict(
									    [
									        ('input_ids', dynamic_axis),
									        ('attention_mask', dynamic_axis),
									        ('token_type_ids', dynamic_axis),
									    ]		)









'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


__lowerCAmelCase						      =       {
    '''configuration_data2vec_audio''': ['''DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Data2VecAudioConfig'''],
    '''configuration_data2vec_text''': [
        '''DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Data2VecTextConfig''',
        '''Data2VecTextOnnxConfig''',
    ],
    '''configuration_data2vec_vision''': [
        '''DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Data2VecVisionConfig''',
        '''Data2VecVisionOnnxConfig''',
    ],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase						      =       [
							    '''DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''Data2VecAudioForAudioFrameClassification''',
							    '''Data2VecAudioForCTC''',
							    '''Data2VecAudioForSequenceClassification''',
							    '''Data2VecAudioForXVector''',
							    '''Data2VecAudioModel''',
							    '''Data2VecAudioPreTrainedModel''',
							]
							__lowerCAmelCase						      =       [
							    '''DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''Data2VecTextForCausalLM''',
							    '''Data2VecTextForMaskedLM''',
							    '''Data2VecTextForMultipleChoice''',
							    '''Data2VecTextForQuestionAnswering''',
							    '''Data2VecTextForSequenceClassification''',
							    '''Data2VecTextForTokenClassification''',
							    '''Data2VecTextModel''',
							    '''Data2VecTextPreTrainedModel''',
							]
							__lowerCAmelCase						      =       [
							    '''DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''Data2VecVisionForImageClassification''',
							    '''Data2VecVisionForMaskedImageModeling''',
							    '''Data2VecVisionForSemanticSegmentation''',
							    '''Data2VecVisionModel''',
							    '''Data2VecVisionPreTrainedModel''',
							]

if is_tf_available():
							__lowerCAmelCase						      =       [
							    '''TFData2VecVisionForImageClassification''',
							    '''TFData2VecVisionForSemanticSegmentation''',
							    '''TFData2VecVisionModel''',
							    '''TFData2VecVisionPreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_dataavec_audio import DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP, DataaVecAudioConfig
							from .configuration_dataavec_text import (
							    DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    DataaVecTextConfig,
							    DataaVecTextOnnxConfig,
							)
							from .configuration_dataavec_vision import (
							    DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    DataaVecVisionConfig,
							    DataaVecVisionOnnxConfig,
							)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_dataavec_audio import (
														    DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DataaVecAudioForAudioFrameClassification,
														    DataaVecAudioForCTC,
														    DataaVecAudioForSequenceClassification,
														    DataaVecAudioForXVector,
														    DataaVecAudioModel,
														    DataaVecAudioPreTrainedModel,
														)
														from .modeling_dataavec_text import (
														    DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DataaVecTextForCausalLM,
														    DataaVecTextForMaskedLM,
														    DataaVecTextForMultipleChoice,
														    DataaVecTextForQuestionAnswering,
														    DataaVecTextForSequenceClassification,
														    DataaVecTextForTokenClassification,
														    DataaVecTextModel,
														    DataaVecTextPreTrainedModel,
														)
														from .modeling_dataavec_vision import (
														    DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DataaVecVisionForImageClassification,
														    DataaVecVisionForMaskedImageModeling,
														    DataaVecVisionForSemanticSegmentation,
														    DataaVecVisionModel,
														    DataaVecVisionPreTrainedModel,
														)
							if is_tf_available():
														from .modeling_tf_dataavec_vision import (
														    TFDataaVecVisionForImageClassification,
														    TFDataaVecVisionForSemanticSegmentation,
														    TFDataaVecVisionModel,
														    TFDataaVecVisionPreTrainedModel,
														)

else:
							import sys

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




