class_docstr: Bottleneck transformation: Tx1x1, 1x3x3, 1x1x1, where T is the size of
      temporal kernel.
class_docstr_tok: ["Bottleneck","transformation",":","Tx1x1",",","1x3x3",",","1x1x1",",","where","T","is","the","size","of","temporal","kernel","."]
code: def forward(self, x):
      # Explicitly forward every layer.
      # Branch2a.
      x = self.a(x)
      x = self.a_bn(x)
      x = self.a_relu(x)
  
      # Branch2b.
      x = self.b(x)
      x = self.b_bn(x)
      x = self.b_relu(x)
  
      # Branch2c
      x = self.c(x)
      x = self.c_bn(x)
      return x
  
imports: import torch
  import torch.nn
  from slowfast.models.common import drop_path
  from slowfast.models.nonlocal_helper import Nonlocal
  from slowfast.models.operators import SE, Swish
label_desc: Use image node_id 3 for calling the BottleneckTransform obj's underlying member method code with example usage: obj.forward(x) and returns: x