class_docstr: Kernel predictor for the location-variable convolutions
class_docstr_tok: ["Kernel","predictor","for","the","location-variable","convolutions"]
code: def remove_weight_norm(self):
      parametrize.remove_parametrizations(self.input_conv[0], "weight")
      parametrize.remove_parametrizations(self.kernel_conv, "weight")
      parametrize.remove_parametrizations(self.bias_conv)
      for block in self.residual_convs:
          parametrize.remove_parametrizations(block[1], "weight")
          parametrize.remove_parametrizations(block[3], "weight")
  
imports: from dataclasses import dataclass
  from enum import Enum
  from typing import Callable, Optional
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.nn.utils.parametrize
label_desc: Use image node_id 3 for calling the KernelPredictor obj's underlying member method code with example usage: obj.remove_weight_norm() without return types