class_docstr: Base class for different image classification models
class_docstr_tok: ["Base","class","for","different","image","classification","models"]
docstr: Check to see if model is adhering to the image encoder structure. Sub-classes
  are not required to adhere to this structure. This is only required for easy
  integration with downstream tasks.
docstr_tok: ["Check","to","see","if","model","is","adhering","to","the","image","encoder","structure",".","Sub-classes","are","not","required","to","adhere","to","this","structure",".","This","is","only","required","for","easy","integration","with","downstream","tasks","."]
code: def check_model(self) -> None:
      """Check to see if model is adhering to the image encoder structure. Sub-classes
      are not required to adhere to this structure. This is only required for easy
      integration with downstream tasks."""
      assert (
          self.model_conf_dict
      ), "Model configuration dictionary should not be empty"
      assert self.conv_1 is not None, "Please implement self.conv_1"
      assert self.layer_1 is not None, "Please implement self.layer_1"
      assert self.layer_2 is not None, "Please implement self.layer_2"
      assert self.layer_3 is not None, "Please implement self.layer_3"
      assert self.layer_4 is not None, "Please implement self.layer_4"
      assert self.layer_5 is not None, "Please implement self.layer_5"
      assert (
          self.conv_1x1_exp is not None
      ), "Please implement self.conv_1x1_exp"
      assert (
          self.classifier is not None
      ), "Please implement self.classifier"
  
imports: import argparse
  from typing import Any, Dict, List, Mapping, Optional, Tuple
  import torch
  from torch import Tensor, nn
  from torch.utils.checkpoint import checkpoint
  from common import is_test_env
  from cvnets.layers import LinearLayer
  from cvnets.misc.init_utils import initialize_fc_layer
  from cvnets.models import MODEL_REGISTRY, BaseAnyNNModel
  from cvnets.neural_augmentor import build_neural_augmentor
  from utils import logger
label_desc: Use image node_id 3 for calling the BaseImageEncoder obj's underlying member method code with example usage: obj.check_model() without return types