class_docstr: Video 3D stem module. Provides stem operations of Conv, BN, ReLU, MaxPool
  on input data tensor for one or multiple pathways.
class_docstr_tok: ["Video","3D","stem","module",".","Provides","stem","operations","of","Conv",",","BN",",","ReLU",",","MaxPool","on","input","data","tensor","for","one","or","multiple","pathways","."]
code: def forward(self, x):
      assert (
          len(x) == self.num_pathways
      ), "Input tensor does not contain {} pathway".format(
          self.num_pathways
      )
      # use a new list, don't modify in-place the x list, which is bad for activation checkpointing.
      y = []
      for pathway in range(len(x)):
          m = getattr(self, "pathway{}_stem".format(pathway))
          y.append(m(x[pathway]))
      return y
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 3 for calling the VideoModelStem obj's underlying member method code with example usage: obj.forward(x) and returns: y