


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


_snake_case					=					logging.get_logger(__name__)

_snake_case					=					{
    '''facebook/regnet-y-040''': '''https://huggingface.co/facebook/regnet-y-040/blob/main/config.json''',
}
class      UpperCAmelCase_ ( UpperCamelCase   ):

   '''simple docstring'''




   __A			:				List[str]							=		"regnet"
   __A			:				List[str]							=		["x", "y"]






   def __init__(		self						,    __A=3						,    __A=32						,    __A=[128, 192, 512, 1088]						,    __A=[2, 6, 12, 2]						,    __A=64						,    __A="y"						,    __A="relu"						,    **__A						,    ):






     """simple docstring"""





     super().__init__(**__A			)
     if layer_type not in self.layer_types:
       raise ValueError(F"""layer_type={layer_type} is not one of {','.join(self.layer_types			)}"""			)
     lowerCamelCase			: List[str]   =    num_channels
     lowerCamelCase			: Optional[Any]   =    embedding_size
     lowerCamelCase			: Optional[Any]   =    hidden_sizes
     lowerCamelCase			: List[Any]   =    depths
     lowerCamelCase			: Optional[Any]   =    groups_width
     lowerCamelCase			: Optional[Any]   =    layer_type
     lowerCamelCase			: Optional[Any]   =    hidden_act
     # always downsample in the first stage
     lowerCamelCase			: Optional[Any]   =    True







from typing import TYPE_CHECKING

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


_snake_case					=					{'''configuration_hubert''': ['''HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''HubertConfig''']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case					=					[
       '''HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''HubertForCTC''',
       '''HubertForSequenceClassification''',
       '''HubertModel''',
       '''HubertPreTrainedModel''',
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case					=					[
       '''TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFHubertForCTC''',
       '''TFHubertModel''',
       '''TFHubertPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_hubert import (
          HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          HubertForCTC,
          HubertForSequenceClassification,
          HubertModel,
          HubertPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_hubert import (
          TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFHubertForCTC,
          TFHubertModel,
          TFHubertPreTrainedModel,
      )


else:
   import sys

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



