





from typing import TYPE_CHECKING

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


__lowerCAmelCase :Any     =    {'''configuration_yolos''': ['''YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''YolosConfig''', '''YolosOnnxConfig''']}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase :Dict     =    ['''YolosFeatureExtractor''']
							__lowerCAmelCase :Optional[int]     =    ['''YolosImageProcessor''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase :Optional[int]     =    [
							    '''YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''YolosForObjectDetection''',
							    '''YolosModel''',
							    '''YolosPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_yolos import YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP, YolosConfig, YolosOnnxConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_yolos import YolosFeatureExtractor
														from .image_processing_yolos import YolosImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_yolos import (
														    YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST,
														    YolosForObjectDetection,
														    YolosModel,
														    YolosPreTrainedModel,
														)


else:
							import sys

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






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


__lowerCAmelCase :Tuple     =    logging.get_logger(__name__)

__lowerCAmelCase :int     =    {
    'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}






class        _a(    __A    ):
		lowerCamelCase__     :Optional[Any]   				=		'timesformer'







		def __init__(    self ,						__snake_case=2_2_4 ,						__snake_case=1_6 ,						__snake_case=3 ,						__snake_case=8 ,						__snake_case=7_6_8 ,						__snake_case=1_2 ,						__snake_case=1_2 ,						__snake_case=3_0_7_2 ,						__snake_case="gelu" ,						__snake_case=0.0 ,						__snake_case=0.0 ,						__snake_case=0.02 ,						__snake_case=1E-6 ,						__snake_case=True ,						__snake_case="divided_space_time" ,						__snake_case=0 ,						**__snake_case ,						)      ->      str:


							'''simple docstring'''

							super().__init__(**__snake_case				)

							_snake_case       :					Optional[Any]				       =   image_size
							_snake_case       :					Optional[int]				       =   patch_size
							_snake_case       :					str				       =   num_channels
							_snake_case       :					Tuple				       =   num_frames

							_snake_case       :					Union[str, Any]				       =   hidden_size
							_snake_case       :					Optional[int]				       =   num_hidden_layers
							_snake_case       :					List[Any]				       =   num_attention_heads
							_snake_case       :					Optional[int]				       =   intermediate_size
							_snake_case       :					List[str]				       =   hidden_act
							_snake_case       :					Optional[int]				       =   hidden_dropout_prob
							_snake_case       :					Optional[Any]				       =   attention_probs_dropout_prob
							_snake_case       :					Dict				       =   initializer_range
							_snake_case       :					Optional[int]				       =   layer_norm_eps
							_snake_case       :					str				       =   qkv_bias

							_snake_case       :					List[str]				       =   attention_type
							_snake_case       :					Optional[int]				       =   drop_path_rate