class_docstr: Base class for any neural network
class_docstr_tok: ["Base","class","for","any","neural","network"]
docstr: Implement the model-specific forward function in sub-classes.
docstr_tok: ["Implement","the","model-specific","forward","function","in","sub-classes","."]
code: def forward(self, x: Any, *args, **kwargs) -> Any:
      """Implement the model-specific forward function in sub-classes."""
      raise NotImplementedError
  
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 4 for calling the BaseAnyNNModel obj's underlying member method code with example usage: obj.forward(x) without return types