class_docstr: Construct 3d max pool with same padding. PyTorch does not provide same padding.
  Same padding means the output size matches input size for stride=1.
class_docstr_tok: ["Construct","3d","max","pool","with","same","padding",".","PyTorch","does","not","provide","same","padding",".","Same","padding","means","the","output","size","matches","input","size","for","stride=1","."]
docstr: Get the zero padding number.
docstr_tok: ["Get","the","zero","padding","number","."]
code: def compute_pad(self, dim, s):
      """Get the zero padding number."""
  
      if s % self.stride[dim] == 0:
          return max(self.kernel_size[dim] - self.stride[dim], 0)
      else:
          return max(self.kernel_size[dim] - (s % self.stride[dim]), 0)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.hub import load_state_dict_from_url
label_desc: Use image node_id 1 for calling the MaxPool3dSamePadding obj's underlying member method code with example usage: obj.compute_pad(dim, s) and returns: max, max