class_docstr: Code for "UniFormer: Unified Transformer for Efficient Spatiotemporal Representation Learning"
  arXiv:2201.04676
  Kunchang Li, Yali Wang, Peng Gao, Guanglu Song, Yu Liu, Hongsheng Li, Yu Qiao
  
  Args:
      depth (`tuple[int]`)
          Depth. Default: (5, 8, 20, 7).
      num_classes (`int`):
          dimension of head. Default: 400.
      img_size (`int`):
          The spatial crop size for training. Default: 224.
      in_chans (`int`):
          Image input channels num. Default: 3.
      embed_dim (`tuple[int]`)
          Embedding dimension. Default: (64, 128, 320, 512).
      head_dim (`int`):
          Dimension of head. Default: 64.
      mlp_ratio (`int`):
          Ratio of mlp hidden dim to embedding dim. Default: 4.
      qkv_bias (`bool`):
          Enable bias for qkv if True. Default: True.
      qk_scale (`float`):
          Override default qk scale of head_dim ** -0.5 if set. Default: None.
      representation_size (`int`):
          Enable and set representation layer (pre-logits) to this value if set. Default: None.
      drop_rate (`float`):
          Dropout rate. Default: 0.
      attn_drop_rate (`float`):
          Attention dropout rate. Default: 0.
      drop_path_rate (`float`):
          Stochastic depth rate. Default: 0.1.
      split (`bool`):
          Whether use split attention. Default: False.
      std (`bool`):
          Spatial-temporal downsample. Default: False.
      use_checkpoint (`bool`):
          Whether use checkpoint. Default: False.
      checkpoint_num (`tuple[int]`)
          Checkpoint num. Default: (0, 0, 0, 0).
      pretrain_name (`string`):
          Pretrained name. Default: None.
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code: def get_classifier(self):
      return self.head
  
imports: from collections import OrderedDict
  import torch
  from torch import nn
  from torch.utils import checkpoint
  from functools import partial
  from towhee.models.utils.general_utils import to_2tuple
  from towhee.models.utils.weight_init import trunc_normal_
  from towhee.models.layers.droppath import DropPath
  from towhee.models.layers.mlp import Mlp
  from towhee.models.layers.attention import MultiHeadAttention
  from towhee.models.uniformer.config import _C
  import os
label_desc: Use image node_id 4 for calling the Uniformer obj's underlying member method code with example usage: obj.get_classifier() and returns: self