code: def test_one(self):
      train_dataset = MyDataset(
          batchsize_per_replica=32,
          shuffle=False,
          transform=GenericImageTransform(
              transform=transforms.Compose(
                  [
                      transforms.RandomResizedCrop(224),
                      transforms.RandomHorizontalFlip(),
                      transforms.ToTensor(),
                      transforms.Normalize(
                          mean=[0.485, 0.456, 0.406],
                          std=[0.229, 0.224, 0.225],
                      ),
                  ]
              )
          ),
          num_samples=100,
          crop_size=224,
          class_ratio=0.5,
          seed=0,
      )
  
      test_dataset = MyDataset(
          batchsize_per_replica=32,
          shuffle=False,
          transform=GenericImageTransform(
              transform=transforms.Compose(
                  [
                      transforms.Resize(256),
                      transforms.CenterCrop(224),
                      transforms.ToTensor(),
                      transforms.Normalize(
                          mean=[0.485, 0.456, 0.406],
                          std=[0.229, 0.224, 0.225],
                      ),
                  ]
              )
          ),
          num_samples=100,
          crop_size=224,
          class_ratio=0.5,
          seed=0,
      )
  
      model = MyModel()
      loss = MyLoss()
  
      optimizer = SGD(momentum=0.9, weight_decay=1e-4, nesterov=True)
  
      task = (
          ClassificationTask()
          .set_model(model)
          .set_dataset(train_dataset, "train")
          .set_dataset(test_dataset, "test")
          .set_loss(loss)
          .set_optimizer(optimizer)
          .set_optimizer_schedulers(
              {
                  "lr": LinearParamScheduler(
                      start_value=0.01, end_value=0.009
                  )
              }
          )
          .set_num_epochs(1)
      )
  
      trainer = LocalTrainer()
      trainer.train(task)
  
file_path: ClassyVision/test/api_test.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import pathlib
  import sys
  import unittest
  import classy_vision
  from classy_vision.dataset.transforms import GenericImageTransform
  from classy_vision.optim import SGD
  from classy_vision.optim.param_scheduler import LinearParamScheduler
  from classy_vision.tasks import ClassificationTask
  from classy_vision.trainer import LocalTrainer
  from torchvision import transforms
  from datasets.my_dataset import MyDataset
  from losses.my_loss import MyLoss
  from models.my_model import MyModel
label_desc: Use image node_id 1 for calling the APITest obj's underlying member method code with example usage: obj.test_one() without return types