class_docstr: single depth-wise separable TCN block as used in iNeuBe TCN.
  
  Args:
      in_chan: number of input feature channels.
      out_chan: number of output feature channels.
      ksz: kernel size.
      stride: stride in depth-wise convolution.
      dilation: dilation in depth-wise convolution.
      activation: activation function to use in the whole iNeuBe model,
          you can use any torch supported activation e.g. 'relu' or 'elu'.
code: def forward(self, inp):
      # [B, C, F] batch, channels, frames
      return self.layer(inp) + inp
  
imports: import torch
  from packaging.version import parse
  from torch_complex.tensor import ComplexTensor
  from espnet2.torch_utils.get_layer_from_string import get_layer
label_desc: Use image node_id 2 for calling the TCNResBlock obj's underlying member method code with example usage: obj.forward(inp) and returns: unknown