code: def drop_blocks(drop_prob=0.0):
      return [
          None,
          None,
          partial(
              DropBlock2d,
              drop_prob=drop_prob,
              block_size=5,
              gamma_scale=0.25,
          )
          if drop_prob
          else None,
          partial(
              DropBlock2d,
              drop_prob=drop_prob,
              block_size=3,
              gamma_scale=1.00,
          )
          if drop_prob
          else None,
      ]
  
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 5 for calling a global function with example usage: drop_blocks(drop_prob) and returns: list