code: def change_input_channels(
      self, input_channels: int, mode="auto", **kwargs
  ):
      from timm.models.layers import Conv2dSame
  
      if isinstance(self.encoder.conv_stem, Conv2dSame):
          self.encoder.conv_stem = make_n_channel_input_conv2d_same(
              self.encoder.conv_stem, input_channels, mode, **kwargs
          )
      else:
          self.encoder.conv_stem = make_n_channel_input(
              self.encoder.conv_stem, input_channels, mode, **kwargs
          )
      return self
  
file_path: pytorch-toolbelt/pytorch_toolbelt/modules/encoders/timm/efficient_net_v2.py
imports: import copy
  import math
  import warnings
  import torch
  from torch import nn
  from .common import GenericTimmEncoder
  from ..common import make_n_channel_input
  from ...activations import ACT_SILU, get_activation_block
label_desc: Use image node_id 2 for calling the TimmEfficientNetV2 obj's underlying member method code with example usage: obj.change_input_channels(input_channels, mode) and returns: self