





'''simple docstring'''



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


_SCREAMING_SNAKE_CASE					=    logging.get_logger(__name__)

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






class 							__lowercase       (      lowerCAmelCase__						):







	'''simple docstring'''

	a    :				Dict											=       "timesformer"


	def __init__(self     ,_lowerCamelCase=224     ,_lowerCamelCase=16     ,_lowerCamelCase=3     ,_lowerCamelCase=8     ,_lowerCamelCase=768     ,_lowerCamelCase=12     ,_lowerCamelCase=12     ,_lowerCamelCase=3072     ,_lowerCamelCase="gelu"     ,_lowerCamelCase=0.0     ,_lowerCamelCase=0.0     ,_lowerCamelCase=0.0_2     ,_lowerCamelCase=1E-6     ,_lowerCamelCase=True     ,_lowerCamelCase="divided_space_time"     ,_lowerCamelCase=0     ,**_lowerCamelCase     ,)							->							List[str]:







				'''simple docstring'''





				super().__init__(**_lowerCamelCase )

				__lowercase										=							image_size
				__lowercase										=							patch_size
				__lowercase										=							num_channels
				__lowercase										=							num_frames

				__lowercase										=							hidden_size
				__lowercase										=							num_hidden_layers
				__lowercase										=							num_attention_heads
				__lowercase										=							intermediate_size
				__lowercase										=							hidden_act
				__lowercase										=							hidden_dropout_prob
				__lowercase										=							attention_probs_dropout_prob
				__lowercase										=							initializer_range
				__lowercase										=							layer_norm_eps
				__lowercase										=							qkv_bias

				__lowercase										=							attention_type
				__lowercase										=							drop_path_rate












'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_SCREAMING_SNAKE_CASE					=    {
    '''configuration_clipseg''': [
        '''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''CLIPSegConfig''',
        '''CLIPSegTextConfig''',
        '''CLIPSegVisionConfig''',
    ],
    '''processing_clipseg''': ['''CLIPSegProcessor'''],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE					=    [
	    '''CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''CLIPSegModel''',
	    '''CLIPSegPreTrainedModel''',
	    '''CLIPSegTextModel''',
	    '''CLIPSegVisionModel''',
	    '''CLIPSegForImageSegmentation''',
	]

if TYPE_CHECKING:
	from .configuration_clipseg import (
	    CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    CLIPSegConfig,
	    CLIPSegTextConfig,
	    CLIPSegVisionConfig,
	)
	from .processing_clipseg import CLIPSegProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_clipseg import (
		    CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
		    CLIPSegForImageSegmentation,
		    CLIPSegModel,
		    CLIPSegPreTrainedModel,
		    CLIPSegTextModel,
		    CLIPSegVisionModel,
		)

else:
	import sys

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





