class_docstr: ResNe(X)t 3D stem module.
  Performs spatiotemporal Convolution, BN, and Relu following by a
      spatiotemporal pooling.
class_docstr_tok: ["ResNe","(","X",")","t","3D","stem","module",".","Performs","spatiotemporal","Convolution",",","BN",",","and","Relu","following","by","a","spatiotemporal","pooling","."]
code: def forward(self, x):
      x = self.conv(x)
      x = self.bn(x)
      x = self.relu(x)
      x = self.pool_layer(x)
      return x
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 3 for calling the ResNetBasicStem obj's underlying member method code with example usage: obj.forward(x) and returns: x