code: def __init__(
      self,
      input_channels: int,
      output_channels: int,
      activation: str = ACT_RELU,
  ):
      super().__init__()
      self.conv_bn_relu_1 = make_conv_bn_act(
          input_channels, 8, stride=2, activation=activation
      )
      self.conv_bn_relu_2 = make_conv_bn_act(
          8, 64, activation=activation
      )
      self.conv_bn_relu_3 = make_conv_bn_act(
          64, output_channels, activation=activation
      )
  
imports: from collections import OrderedDict
  from typing import List, Union
  import torch
  from torch import nn
  from pytorch_toolbelt.modules import ACT_RELU, instantiate_activation_block, ChannelSpatialGate2d
  from pytorch_toolbelt.modules.encoders import EncoderModule, make_n_channel_input
label_desc: Use image node_id 1 to create a new StemBlock object from inherited base classes: nn with example: obj = StemBlock(input_channels, output_channels, activation)