class_docstr: The basic class for cell operation search, which contains a preprocessing operation and a mixed cell operation.
  Each cell is defined on a `path` in the topology search space.
  Args:
      c_prev: number of input channels
      c: number of output channels
      rate: resolution change rate. It represents the preprocessing operation before the mixed cell operation.
          ``-1`` for 2x downsample, ``1`` for 2x upsample, ``0`` for no change of resolution.
      arch_code_c: cell operation code
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docstr: Args:
      x: input tensor
      weight: weights for different operations.
docstr_tok: ["Args",":","x",":","input","tensor","weight",":","weights","for","different","operations","."]
code: def forward(
      self, x: torch.Tensor, weight: Optional[torch.Tensor]
  ) -> torch.Tensor:
      """
      Args:
          x: input tensor
          weight: weights for different operations.
      """
      x = self.preprocess(x)
      x = self.op(x, weight)
      return x
  
imports: from __future__ import annotations
  import datetime
  import warnings
  from typing import Optional
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from monai.networks.blocks.dints_block import ActiConvNormBlock, FactorizedIncreaseBlock, FactorizedReduceBlock, P3DActiConvNormBlock
  from monai.networks.layers.factories import Conv
  from monai.networks.layers.utils import get_act_layer, get_norm_layer
  from monai.utils import optional_import
label_desc: Use image node_id 2 for calling the Cell obj's underlying member method code with example usage: obj.forward(x, weight) and returns: x