code: def __call__(self, x: torch.Tensor):
      if self.kernel_size > 1:
          pad = x.new_zeros(*x.shape[:-1], self.kernel_size - 1)
          x = torch.cat([pad, x], dim=-1)
      return self.conv(x)
  
file_path: labml/samples/stocks/model.py
imports: from typing import List, Tuple
  import torch
  from labml_helpers.module import Module
  from torch import nn
  from stocks import CandleIdx
label_desc: Use image node_id 2 for calling the FrontPaddedConv1d obj's underlying member method code with example usage: obj.__call__(x) and returns: self