class_docstr: Standard residual block
docstr: Standard residual block
  
  Args:
      filters: conv filters, int
      kernel_size: kernel size, int
docstr_tok: ["Standard","residual","block","Args",":","filters",":","conv","filters",",","int","kernel_size",":","kernel","size",",","int"]
code: def __init__(self, filters: int, kernel_size: int) -> None:
      """Standard residual block
  
      Args:
          filters: conv filters, int
          kernel_size: kernel size, int
      """
      super().__init__()
      self.conv1 = nn.Conv2d(filters, filters, kernel_size, padding=1)
      self.activation = nn.LeakyReLU(
          negative_slope=0.01
      )  # default value
      self.conv2 = nn.Conv2d(filters, filters, kernel_size, padding=1)
  
imports: import itertools
  import math
  from typing import Generator, List, NamedTuple, Optional, Sequence, Tuple, Union
  import torch
  import torch.nn
  import utils.memoize
  from datamodules.video_data_api import Scenes, VideoData
  from neural.entropy_model import PreviousLatent, VCTEntropyModel
  from torch import Tensor
label_desc: Use image node_id 1 to create a new ResidualBlock object from inherited base classes: nn with example: obj = ResidualBlock(filters, kernel_size)