



"""simple docstring"""






from typing import TYPE_CHECKING

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


__snake_case							:   Dict      =    {'configuration_deit': ['DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DeiTConfig', 'DeiTOnnxConfig']}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case							:   List[str]      =    ['DeiTFeatureExtractor']
	__snake_case							:   Any      =    ['DeiTImageProcessor']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case							:   List[Any]      =    [
	    'DEIT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'DeiTForImageClassification',
	    'DeiTForImageClassificationWithTeacher',
	    'DeiTForMaskedImageModeling',
	    'DeiTModel',
	    'DeiTPreTrainedModel',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case							:   Dict      =    [
	    'TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TFDeiTForImageClassification',
	    'TFDeiTForImageClassificationWithTeacher',
	    'TFDeiTForMaskedImageModeling',
	    'TFDeiTModel',
	    'TFDeiTPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_deit import DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, DeiTConfig, DeiTOnnxConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_deit import DeiTFeatureExtractor
		from .image_processing_deit import DeiTImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_deit import (
		    DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DeiTForImageClassification,
		    DeiTForImageClassificationWithTeacher,
		    DeiTForMaskedImageModeling,
		    DeiTModel,
		    DeiTPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_deit import (
		    TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFDeiTForImageClassification,
		    TFDeiTForImageClassificationWithTeacher,
		    TFDeiTForMaskedImageModeling,
		    TFDeiTModel,
		    TFDeiTPreTrainedModel,
		)


else:
	import sys

	__snake_case							:   List[str]      =    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






from collections import OrderedDict
from typing import Mapping

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


_a 						=      logging.get_logger(__name__)

_a 						=      {
    "camembert-base": "https://huggingface.co/camembert-base/resolve/main/config.json",
    "umberto-commoncrawl-cased-v1": (
        "https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"
    ),
    "umberto-wikipedia-uncased-v1": (
        "https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"
    ),
}






class 					__A    (    lowerCAmelCase ):

			'''simple docstring'''







			lowerCAmelCase_							     =						"""camembert"""





			def __init__(    self       ,  __lowerCAmelCase=3_0_5_2_2       ,  __lowerCAmelCase=7_6_8       ,  __lowerCAmelCase=1_2       ,  __lowerCAmelCase=1_2       ,  __lowerCAmelCase=3_0_7_2       ,  __lowerCAmelCase="gelu"       ,  __lowerCAmelCase=0.1       ,  __lowerCAmelCase=0.1       ,  __lowerCAmelCase=5_1_2       ,  __lowerCAmelCase=2       ,  __lowerCAmelCase=0.02       ,  __lowerCAmelCase=1E-12       ,  __lowerCAmelCase=1       ,  __lowerCAmelCase=0       ,  __lowerCAmelCase=2       ,  __lowerCAmelCase="absolute"       ,  __lowerCAmelCase=True       ,  __lowerCAmelCase=None       ,  **__lowerCAmelCase       ,  ):



				'''simple docstring'''







				super().__init__(pad_token_id=__lowerCAmelCase       ,  bos_token_id=__lowerCAmelCase       ,  eos_token_id=__lowerCAmelCase       ,  **__lowerCAmelCase							)

				lowerCamelCase__								=		vocab_size
				lowerCamelCase__								=		hidden_size
				lowerCamelCase__								=		num_hidden_layers
				lowerCamelCase__								=		num_attention_heads
				lowerCamelCase__								=		hidden_act
				lowerCamelCase__								=		intermediate_size
				lowerCamelCase__								=		hidden_dropout_prob
				lowerCamelCase__								=		attention_probs_dropout_prob
				lowerCamelCase__								=		max_position_embeddings
				lowerCamelCase__								=		type_vocab_size
				lowerCamelCase__								=		initializer_range
				lowerCamelCase__								=		layer_norm_eps
				lowerCamelCase__								=		position_embedding_type
				lowerCamelCase__								=		use_cache
				lowerCamelCase__								=		classifier_dropout






class 					__A    (    lowerCAmelCase ):

			'''simple docstring'''







			@property
			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







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



