class_docstr: Base class for any neural network
class_docstr_tok: ["Base","class","for","any","neural","network"]
docstr: Create dummy input and labels for CI/CD purposes. Child classes should implement it.
docstr_tok: ["Create","dummy","input","and","labels","for","CI\/CD","purposes",".","Child","classes","should","implement","it","."]
code: def dummy_input_and_label(self, batch_size: int) -> Dict:
      """Create dummy input and labels for CI/CD purposes. Child classes should implement it."""
      raise NotImplementedError(
          f"Please implement dummy_input_and_label function for {self.__name__}"
      )
  
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 7 for calling the BaseAnyNNModel obj's underlying member method code with example usage: obj.dummy_input_and_label(batch_size) without return types