class_docstr: P = ((S-1)*W-S+F)/2, with F = filter size, S = stride
code: def forward(self, x):
      out = self.conv(x)
      if self.norm is not None:
          out = self.norm(out)
      if self.activation is not None:
          out = self.activation(out)
      return out
  
file_path: ARKitScenes/depth_upsampling/models/mspf/blocks/multi_scale_depth.py
imports: import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 2 for calling the Conv2D obj's underlying member method code with example usage: obj.forward(x) and returns: out