code: def __init__(
      self,
      num_channels=3,
      embedding_size=32,
      hidden_sizes=[128, 192, 512, 1088],
      depths=[2, 6, 12, 2],
      groups_width=64,
      layer_type="y",
      hidden_act="relu",
      **kwargs,
  ):
      super().__init__(**kwargs)
      if layer_type not in self.layer_types:
          raise ValueError(
              f"layer_type={layer_type} is not one of {','.join(self.layer_types)}"
          )
      self.num_channels = num_channels
      self.embedding_size = embedding_size
      self.hidden_sizes = hidden_sizes
      self.depths = depths
      self.groups_width = groups_width
      self.layer_type = layer_type
      self.hidden_act = hidden_act
      # always downsample in the first stage
      self.downsample_in_first_stage = True
  
imports: from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 1 to create a new RegNetConfig object from inherited base classes: PretrainedConfig with example: obj = RegNetConfig(num_channels, embedding_size, hidden_sizes, depths, groups_width, layer_type, hidden_act)