class_docstr: The basic class for cells used in NAS-FPN and NAS-FCOS.
  
  BaseMergeCell takes 2 inputs. After applying convolution
  on them, they are resized to the target size. Then,
  they go through binary_op, which depends on the type of cell.
  If with_out_conv is True, the result of output will go through
  another convolution layer.
  
  Args:
      in_channels (int): number of input channels in out_conv layer.
      out_channels (int): number of output channels in out_conv layer.
      with_out_conv (bool): Whether to use out_conv layer
      out_conv_cfg (dict): Config dict for convolution layer, which should
          contain "groups", "kernel_size", "padding", "bias" to build
          out_conv layer.
      out_norm_cfg (dict): Config dict for normalization layer in out_conv.
      out_conv_order (tuple): The order of conv/norm/activation layers in
          out_conv.
      with_input1_conv (bool): Whether to use convolution on input1.
      with_input2_conv (bool): Whether to use convolution on input2.
      input_conv_cfg (dict): Config dict for building input1_conv layer and
          input2_conv layer, which is expected to contain the type of
          convolution.
          Default: None, which means using conv2d.
      input_norm_cfg (dict): Config dict for normalization layer in
          input1_conv and input2_conv layer. Default: None.
      upsample_mode (str): Interpolation method used to resize the output
          of input1_conv and input2_conv to target size. Currently, we
          support ['nearest', 'bilinear']. Default: 'nearest'.
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code: def _build_input_conv(self, channel, conv_cfg, norm_cfg):
      return ConvModule(
          channel,
          channel,
          3,
          padding=1,
          conv_cfg=conv_cfg,
          norm_cfg=norm_cfg,
          bias=True,
      )
  
imports: from abc import abstractmethod
  import torch
  import torch.nn
  import torch.nn.functional
  from ..cnn import ConvModule
label_desc: Use image node_id 2 for calling the BaseMergeCell obj's underlying member method code with example usage: obj._build_input_conv(channel, conv_cfg, norm_cfg) and returns: ConvModule