


from collections import OrderedDict
from typing import Mapping

from packaging import version

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


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

SCREAMING_SNAKE_CASE			:			int        =     {
    "microsoft/beit-base-patch16-224-pt22k": (
        "https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json"
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}





class        snake_case__	(			SCREAMING_SNAKE_CASE_							):
	UpperCAmelCase :				List[Any]       =			"""beit"""





	def __init__(	self					,     UpperCamelCase_=8192					,     UpperCamelCase_=768					,     UpperCamelCase_=12					,     UpperCamelCase_=12					,     UpperCamelCase_=3072					,     UpperCamelCase_="gelu"					,     UpperCamelCase_=0.0					,     UpperCamelCase_=0.0					,     UpperCamelCase_=0.02					,     UpperCamelCase_=1e-12					,     UpperCamelCase_=224					,     UpperCamelCase_=16					,     UpperCamelCase_=3					,     UpperCamelCase_=False					,     UpperCamelCase_=False					,     UpperCamelCase_=False					,     UpperCamelCase_=False					,     UpperCamelCase_=0.1					,     UpperCamelCase_=0.1					,     UpperCamelCase_=True					,     UpperCamelCase_=[3, 5, 7, 11]					,     UpperCamelCase_=[1, 2, 3, 6]					,     UpperCamelCase_=True					,     UpperCamelCase_=0.4					,     UpperCamelCase_=256					,     UpperCamelCase_=1					,     UpperCamelCase_=False					,     UpperCamelCase_=255					,     **UpperCamelCase_					,     )		->      str:
								"""simple docstring"""






								super().__init__(**__SCREAMING_SNAKE_CASE				)

								a_							: Dict								=						vocab_size
								a_							: Tuple								=						hidden_size
								a_							: Any								=						num_hidden_layers
								a_							: Dict								=						num_attention_heads
								a_							: Union[str, Any]								=						intermediate_size
								a_							: Union[str, Any]								=						hidden_act
								a_							: Union[str, Any]								=						hidden_dropout_prob
								a_							: Optional[Any]								=						attention_probs_dropout_prob
								a_							: Dict								=						initializer_range
								a_							: Optional[int]								=						layer_norm_eps

								a_							: Any								=						image_size
								a_							: List[str]								=						patch_size
								a_							: List[Any]								=						num_channels
								a_							: Optional[Any]								=						use_mask_token
								a_							: List[Any]								=						use_absolute_position_embeddings
								a_							: Dict								=						use_relative_position_bias
								a_							: Any								=						use_shared_relative_position_bias
								a_							: int								=						layer_scale_init_value
								a_							: List[Any]								=						drop_path_rate
								a_							: List[Any]								=						use_mean_pooling
								# decode head attributes (semantic segmentation)
								a_							: Union[str, Any]								=						out_indices
								a_							: Dict								=						pool_scales
								# auxiliary head attributes (semantic segmentation)
								a_							: Union[str, Any]								=						use_auxiliary_head
								a_							: Optional[Any]								=						auxiliary_loss_weight
								a_							: Optional[int]								=						auxiliary_channels
								a_							: int								=						auxiliary_num_convs
								a_							: str								=						auxiliary_concat_input
								a_							: str								=						semantic_loss_ignore_index





class        snake_case__	(			SCREAMING_SNAKE_CASE_							):
	UpperCAmelCase :				Optional[int]       =			version.parse("""1.11"""							)





	@property
	def      A					(	self				)		->      Mapping[str, Mapping[int, str]]:
								"""simple docstring"""






								return OrderedDict(
								    [
								        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
								    ]				)





	@property
	def      A					(	self				)		->      float:
								"""simple docstring"""






								return 1e-4










'''simple docstring'''







import os
import time

import pytest

from datasets.utils.filelock import FileLock, Timeout





def 		_UpperCAmelCase (				__A				: int   ):
				a_		:	Optional[Any]									=   FileLock(str(tmpdir / '''foo.lock'''   )   )
				a_		:	Union[str, Any]									=   FileLock(str(tmpdir / '''foo.lock'''   )   )
				a_		:	List[Any]									=   0.01
				with locka.acquire():
								with pytest.raises(__A   ):
												a_		:	List[Any]									=   time.time()
												locka.acquire(__A   )
												assert time.time() - _start > timeout





def 		_UpperCAmelCase (				__A				: Tuple   ):
				a_		:	Tuple									=   '''a''' * 10_00 + '''.lock'''
				a_		:	List[Any]									=   FileLock(str(tmpdir / filename   )   )
				assert locka._lock_file.endswith('''.lock'''   )
				assert not locka._lock_file.endswith(__A   )
				assert len(os.path.basename(locka._lock_file   )   ) <= 2_55
				a_		:	Optional[int]									=   FileLock(tmpdir / filename   )
				with locka.acquire():
								with pytest.raises(__A   ):
												locka.acquire(0   )




