code: def __init__(
      self,
      input_channels: int,
      out_channels: Optional[int],
      num_layers: int,
  ) -> None:
      self.input_channels = input_channels
      self.out_channels = out_channels
      self.num_layers = num_layers
  
imports: from functools import partial
  from typing import Any, Callable, List, Optional, Sequence
  import torch
  from torch import nn, Tensor
  from torch.nn import functional
  from ..ops.misc import Conv2dNormActivation, Permute
  from ..ops.stochastic_depth import StochasticDepth
  from ..transforms._presets import ImageClassification
  from ..utils import _log_api_usage_once
  from ._api import register_model, Weights, WeightsEnum
  from ._meta import _IMAGENET_CATEGORIES
  from ._utils import _ovewrite_named_param, handle_legacy_interface
label_desc: Use image node_id 1 to create a new CNBlockConfig object  with example: obj = CNBlockConfig(input_channels, out_channels, num_layers)