class_docstr: Base class for any neural network
class_docstr_tok: ["Base","class","for","any","neural","network"]
code: def __init__(self, opts, *args, **kwargs) -> None:
      super().__init__()
      self.opts = opts
  
imports: from __future__ import annotations
  import argparse
  import traceback
  from typing import Any, Dict, List, Mapping, Optional, Tuple
  import torch
  from torch import nn
  from cvnets.layers import norm_layers_tuple
  from cvnets.misc.common import get_tensor_sizes, parameter_list
  from cvnets.misc.init_utils import initialize_weights
  from options.parse_args import JsonValidator
  from utils import logger
  from utils.common_utils import check_frozen_norm_layer
  from utils.ddp_utils import is_master
label_desc: Use image node_id 1 to create a new BaseAnyNNModel object from inherited base classes: nn with example: obj = BaseAnyNNModel(opts)