code: def resnet34d(pretrained=False, **kwargs):
      """Constructs a ResNet-34-D model."""
      model_args = dict(
          block=BasicBlock,
          layers=[3, 4, 6, 3],
          stem_width=32,
          stem_type="deep",
          avg_down=True,
          **kwargs,
      )
      return ResNet(**model_args)
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.models.helpers import build_model_with_cfg
  from timm.models.layers import DropBlock2d, DropPath, AvgPool2dSame, BlurPool2d, GroupNorm, create_attn, get_attn, create_classifier
label_desc: Use image node_id 7 for calling a global function with example usage: resnet34d(pretrained) and returns: ResNet