class_docstr: This class defines the `EfficientNet architecture <https://arxiv.org/abs/1905.11946>`_
class_docstr_tok: ["This","class","defines","the","`","EfficientNet","architecture","<","https",":","\/\/arxiv.org\/abs\/1905.11946",">","`","_"]
code: def add_arguments(
      cls, parser: argparse.ArgumentParser
  ) -> argparse.ArgumentParser:
      group = parser.add_argument_group(title=cls.__name__)
      group.add_argument(
          "--model.classification.efficientnet.mode",
          type=str,
          choices=[f"b{i}" for i in range(8)],
      )
      group.add_argument(
          "--model.classification.efficientnet.stochastic-depth-prob",
          type=float,
          default=0.0,
      )
      return parser
  
file_path: ml-cvnets/cvnets/models/classification/efficientnet.py
imports: import argparse
  from typing import Any, Optional, Tuple
  from torch import nn
  from cvnets.layers import ConvLayer2d, Dropout, GlobalPool, LinearLayer
  from cvnets.models import MODEL_REGISTRY
  from cvnets.models.classification.base_image_encoder import BaseImageEncoder
  from cvnets.models.classification.config.efficientnet import EfficientNetBlockConfig, get_configuration
  from cvnets.modules import EfficientNetBlock
label_desc: Use image node_id 3 for calling the EfficientNet obj's underlying member method code with example usage: obj.add_arguments(cls, parser) and returns: parser