class_docstr: Block Decoder for readability,
  straight from the official TensorFlow repository.
class_docstr_tok: ["Block","Decoder","for","readability",",","straight","from","the","official","TensorFlow","repository","."]
docstr: Decode a list of string notations to specify blocks inside the network.
  
  Args:
      string_list (list[str]): A list of strings, each string is a notation of block.
  
  Returns:
      blocks_args: A list of BlockArgs namedtuples of block args.
docstr_tok: ["Decode","a","list","of","string","notations","to","specify","blocks","inside","the","network",".","Args",":","string_list","(","list","[","str","]",")",":","A","list","of","strings",",","each","string","is","a","notation","of","block",".","Returns",":","blocks_args",":","A","list","of","BlockArgs","namedtuples","of","block","args","."]
code: def decode(string_list):
      """Decode a list of string notations to specify blocks inside the network.
  
      Args:
          string_list (list[str]): A list of strings, each string is a notation of block.
  
      Returns:
          blocks_args: A list of BlockArgs namedtuples of block args.
      """
      assert isinstance(string_list, list)
      blocks_args = []
      for block_string in string_list:
          blocks_args.append(
              BlockDecoder._decode_block_string(block_string)
          )
      return blocks_args
  
imports: import re
  import math
  import collections
  from functools import partial
  import torch
  from torch import nn
  from torch.nn import functional
  from torch.utils import model_zoo
label_desc: Use image node_id 3 for calling the BlockDecoder obj's underlying member method code with example usage: obj.decode(string_list) and returns: blocks_args