code: def __init__(self, pretrained=True, layers=None):
      encoder = se_resnet152(
          pretrained="imagenet" if pretrained else None
      )
      super().__init__(
          encoder, [64, 256, 512, 1024, 2048], [2, 4, 8, 16, 32], layers
      )
  
imports: from typing import List
  import torch
  from torch import Tensor
  from .common import EncoderModule, _take, make_n_channel_input
  from ..backbone.senet import SENet, se_resnext50_32x4d, se_resnext101_32x4d, se_resnet50, se_resnet101, se_resnet152, senet154
label_desc: Use image node_id 1 to create a new SEResnet152Encoder object from inherited base classes: SEResnetEncoder with example: obj = SEResnet152Encoder(pretrained, layers)