class_docstr: A pytorch based classifier. Used to make sure we make maximum
  utilization of features provided by pytorch without reinventing the wheel.
code: def __init__(self, *args, **kwargs):
      self.transforms = [transforms.ToTensor()]
      nn.Module.__init__(self, *args, **kwargs)
      self.setup(*args, **kwargs)
  
imports: import numpy
  import pandas
  from numpy.typing import ArrayLike
  from evadb.functions.abstract.abstract_function import AbstractClassifierFunction, AbstractTransformationFunction
  from evadb.functions.gpu_compatible import GPUCompatible
  from evadb.utils.generic_utils import try_to_import_pillow, try_to_import_torch, try_to_import_torchvision
  from PIL import Image
  from torch import nn
  from torchvision.transforms import Compose, transforms
label_desc: Use image node_id 1 to create a new PytorchAbstractClassifierFunction object from inherited base classes: AbstractClassifierFunction, nn, GPUCompatible with example: obj = PytorchAbstractClassifierFunction()