code: def __init__(
      self, *, in_channels: int, out_channels: int, kernel_size: int
  ):
      super().__init__()
  
      self.kernel_size = kernel_size
      self.conv = nn.Conv1d(
          in_channels=in_channels,
          out_channels=out_channels,
          kernel_size=kernel_size,
      )
  
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 1 to create a new FrontPaddedConv1d object from inherited base classes: Module with example: obj = FrontPaddedConv1d()