class_docstr: TLU layer from 'Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep
  Neural Networks, see :cite:`FRN2019` for more details. :math:`{\tau}` is learnable per channel.
  
  .. math::
      y = \max(x, {\tau})
  
  Args:
      num_features: number of channels
  
  Returns:
      torch.Tensor
  
  Shape:
      - Input: :math:`(B, \text{num_features}, H, W)`
      - Output: :math:`(B, \text{num_features}, H, W)`
class_docstr_tok: ["TLU","layer","from","'Filter","Response","Normalization","Layer",":","Eliminating","Batch","Dependence","in","the","Training","of","Deep","Neural","Networks",",","see",":","cite",":","`","FRN2019","`","for","more","details",".",":","math",":","`","{","\\tau","}","`","is","learnable","per","channel",".","..","math",":",":","y","=","\\max","(","x",",","{","\\tau","}",")","Args",":","num_features",":","number","of","channels","Returns",":","torch.Tensor","Shape",":","-","Input",":",":","math",":","`","(","B",",","\\text","{","num_features","}",",","H",",","W",")","`","-","Output",":",":","math",":","`","(","B",",","\\text","{","num_features","}",",","H",",","W",")","`"]
code: def forward(self, x: Tensor) -> Tensor:
      return torch.max(x, self.tau)
  
imports: from typing import Dict
  import torch
  from torch import nn
  from kornia.core import Module, Parameter, Tensor, tensor, zeros
  from kornia.utils.helpers import map_location_to_cpu
label_desc: Use image node_id 4 for calling the TLU obj's underlying member method code with example usage: obj.forward(x) and returns: torch