code: def __init__(
      self, pretrained=True, layers=None, activation=ACT_RELU, **kwargs
  ):
      from timm.models.resnet import resnet152d
  
      act_layer = get_activation_block(activation)
      encoder = resnet152d(
          features_only=True,
          pretrained=pretrained,
          act_layer=act_layer,
          **kwargs,
      )
      super().__init__(encoder, layers)
  
imports: from collections import OrderedDict
  from typing import List
  import torch
  from torch import nn
  from .common import GenericTimmEncoder
  from ..common import EncoderModule, make_n_channel_input
  from ...None import ACT_RELU, get_activation_block
label_desc: Use image node_id 1 to create a new TimmResnet152D object from inherited base classes: GenericTimmEncoder with example: obj = TimmResnet152D(pretrained, layers, activation)