code: def __init__(self, sk_ratio, width_multiplier):
      ops = []
      channels = 64 * width_multiplier // 2
      if sk_ratio > 0:
          ops.append(conv(3, channels, stride=2))
          ops.append(BatchNormRelu(channels))
          ops.append(conv(channels, channels))
          ops.append(BatchNormRelu(channels))
          ops.append(conv(channels, channels * 2))
      else:
          ops.append(conv(3, channels * 2, kernel_size=7, stride=2))
      ops.append(BatchNormRelu(channels * 2))
      ops.append(nn.MaxPool2d(kernel_size=3, stride=2, padding=1))
      super().__init__(*ops)
  
imports: import logging
  from enum import Enum
  import torch
  import torch.nn
  import torch.nn.functional
  from vissl.config import AttrDict
  from vissl.models.trunks import register_model_trunk
label_desc: Use image node_id 1 to create a new Stem object from inherited base classes: nn with example: obj = Stem(sk_ratio, width_multiplier)