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


A		:   List[str]         =    logging.get_logger(__name__)

A		:   List[Any]         =    {
    '''facebook/regnet-y-040''': '''https://huggingface.co/facebook/regnet-y-040/blob/main/config.json''',
}



class       a_   ( _a						):
			a  : List[Any]				      =       '''regnet'''
			a  : List[Any]				      =       ['''x''', '''y''']






			def __init__(			self							, __UpperCamelCase=3							, __UpperCamelCase=32							, __UpperCamelCase=[128, 192, 512, 1_088]							, __UpperCamelCase=[2, 6, 12, 2]							, __UpperCamelCase=64							, __UpperCamelCase="y"							, __UpperCamelCase="relu"							, **__UpperCamelCase							, ):
									super().__init__(**__UpperCamelCase     )
									if layer_type not in self.layer_types:
															raise ValueError(f"""layer_type={layer_type} is not one of {",".join(self.layer_types     )}"""     )
									_lowercase									=				num_channels
									_lowercase									=				embedding_size
									_lowercase									=				hidden_sizes
									_lowercase									=				depths
									_lowercase									=				groups_width
									_lowercase									=				layer_type
									_lowercase									=				hidden_act
									# always downsample in the first stage
									_lowercase									=				True

from typing import TYPE_CHECKING

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


A		:   Any         =    {'''configuration_bit''': ['''BIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BitConfig''', '''BitOnnxConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A		:   Any         =    [
		    '''BIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''BitForImageClassification''',
		    '''BitModel''',
		    '''BitPreTrainedModel''',
		    '''BitBackbone''',
		]


try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A		:   Tuple         =    ['''BitImageProcessor''']


if TYPE_CHECKING:
		from .configuration_bit import BIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BitConfig, BitOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_bit import (
				    BIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BitBackbone,
				    BitForImageClassification,
				    BitModel,
				    BitPreTrainedModel,
				)

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .image_processing_bit import BitImageProcessor

else:
		import sys

		A		:   int         =    _LazyModule(__name__, globals()['''__file__'''], _import_structure)