class_docstr: BasicHead. No pool.
class_docstr_tok: ["BasicHead",".","No","pool","."]
code: def forward(self, x):
      if hasattr(self, "dropout"):
          x = self.dropout(x)
      if self.detach_final_fc:
          x = x.detach()
      x = self.projection(x)
  
      if not self.training:
          if self.act is not None:
              x = self.act(x)
          # Performs fully convlutional inference.
          if x.ndim == 5 and x.shape[1:4] > torch.Size([1, 1, 1]):
              x = x.mean([1, 2, 3])
  
      x = x.view(x.shape[0], -1)
  
      return x
  
imports: from functools import partial
  import torch
  import torch.nn
  from detectron2.layers import ROIAlign
  import slowfast.utils.logging
  from slowfast.models.attention import MultiScaleBlock
  from slowfast.models.batchnorm_helper import NaiveSyncBatchNorm1d
  from slowfast.models.nonlocal_helper import Nonlocal
label_desc: Use image node_id 2 for calling the TransformerBasicHead obj's underlying member method code with example usage: obj.forward(x) and returns: x