


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


snake_case__			     =						logging.get_logger(__name__)

snake_case__			     =						{
    'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json',
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}


class 					lowerCAmelCase_ (       _a):
						lowerCamelCase_         =     '''vit_mae'''




						def __init__(	self						:   Any   ,     __A						:   Dict=768   ,     __A						:   Optional[int]=12   ,     __A						:   Any=12   ,     __A						:   Any=3072   ,     __A						:   List[str]="gelu"   ,     __A						:   int=0.0   ,     __A						:   Dict=0.0   ,     __A						:   Optional[Any]=0.02   ,     __A						:   Any=1E-12   ,     __A						:   Optional[Any]=224   ,     __A						:   Any=16   ,     __A						:   Any=3   ,     __A						:   Optional[Any]=True   ,     __A						:   Any=16   ,     __A						:   int=512   ,     __A						:   Tuple=8   ,     __A						:   Optional[Any]=2048   ,     __A						:   Tuple=0.75   ,     __A						:   Optional[Any]=False   ,     **__A						:   Optional[Any]   ,     )      ->Dict:






									"""simple docstring"""






									super().__init__(**A__						)

									a__ :Dict						  =    hidden_size
									a__ :Optional[Any]						  =    num_hidden_layers
									a__ :List[str]						  =    num_attention_heads
									a__ :Any						  =    intermediate_size
									a__ :Union[str, Any]						  =    hidden_act
									a__ :List[str]						  =    hidden_dropout_prob
									a__ :Union[str, Any]						  =    attention_probs_dropout_prob
									a__ :Optional[int]						  =    initializer_range
									a__ :Optional[Any]						  =    layer_norm_eps
									a__ :Tuple						  =    image_size
									a__ :Dict						  =    patch_size
									a__ :Optional[int]						  =    num_channels
									a__ :List[str]						  =    qkv_bias
									a__ :Tuple						  =    decoder_num_attention_heads
									a__ :Any						  =    decoder_hidden_size
									a__ :Optional[int]						  =    decoder_num_hidden_layers
									a__ :Tuple						  =    decoder_intermediate_size
									a__ :int						  =    mask_ratio
									a__ :Union[str, Any]						  =    norm_pix_loss






# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case__			 =						{
    '''configuration_mgp_str''': ['''MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MgpstrConfig'''],
    '''processing_mgp_str''': ['''MgpstrProcessor'''],
    '''tokenization_mgp_str''': ['''MgpstrTokenizer'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		snake_case__			 =						[
		    '''MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''MgpstrModel''',
		    '''MgpstrPreTrainedModel''',
		    '''MgpstrForSceneTextRecognition''',
		]

if TYPE_CHECKING:
		from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
		from .processing_mgp_str import MgpstrProcessor
		from .tokenization_mgp_str import MgpstrTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mgp_str import (
				    MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MgpstrForSceneTextRecognition,
				    MgpstrModel,
				    MgpstrPreTrainedModel,
				)
else:
		import sys

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


