class_docstr: X3D's 3D stem module.
  Performs a spatial followed by a depthwise temporal Convolution, BN, and Relu following by a
      spatiotemporal pooling.
class_docstr_tok: ["X3D","'s","3D","stem","module",".","Performs","a","spatial","followed","by","a","depthwise","temporal","Convolution",",","BN",",","and","Relu","following","by","a","spatiotemporal","pooling","."]
code: def forward(self, x):
      x = self.conv_xy(x)
      x = self.conv(x)
      x = self.bn(x)
      x = self.relu(x)
      return x
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 3 for calling the X3DStem obj's underlying member method code with example usage: obj.forward(x) and returns: x