code: def __init__(self):
      super().__init__()
      self.backbone = nn.Sequential(
          nn.Flatten(), nn.Linear(28 * 28, 10)
      )
      self.head = nn.LogSoftmax()
  
imports: from argparse import ArgumentParser
  from typing import Any, Tuple, Union
  import pytest
  import torch
  from flash import Trainer
  from flash.core.classification import ClassificationTask
  from flash.core.utilities.imports import _TOPIC_CORE_AVAILABLE
  from pytorch_lightning.callbacks.early_stopping import EarlyStopping
  from pytorch_lightning.callbacks.finetuning import BaseFinetuning
  from pytorch_lightning.core.lightning import LightningModule
  from torch import nn
  from torch.nn import functional
  from torch.optim.optimizer import Optimizer
  from torch.utils.data import DataLoader
label_desc: Use image node_id 1 to create a new DummyClassifier object from inherited base classes: nn with example: obj = DummyClassifier()