code: def setup(ds):
      """
      Load the datasets to use. Nothing interesting to see.
      """
      global x_train, y_train
      if ds == "imagenet":
          import torchvision
  
          transform = torchvision.transforms.Compose(
              [
                  torchvision.transforms.Resize(256),
                  torchvision.transforms.CenterCrop(256),
                  torchvision.transforms.ToTensor(),
              ]
          )
          imagenet_data = torchvision.datasets.ImageNet(
              "/mnt/data/datasets/unpacked_imagenet_pytorch/",
              split="val",
              transform=transform,
          )
          data_loader = torch.utils.data.DataLoader(
              imagenet_data, batch_size=100, shuffle=True, num_workers=8
          )
          r = []
          for x, _ in data_loader:
              if len(r) > 1000:
                  break
              print(x.shape)
              r.extend(x.numpy())
          x_train = np.array(r)
          print(x_train.shape)
      elif ds == "xray":
          import torchvision
  
          transform = torchvision.transforms.Compose(
              [
                  torchvision.transforms.Resize(256),
                  torchvision.transforms.CenterCrop(256),
                  torchvision.transforms.ToTensor(),
              ]
          )
          imagenet_data = torchvision.datasets.ImageFolder(
              "CheXpert-v1.0/train", transform=transform
          )
          data_loader = torch.utils.data.DataLoader(
              imagenet_data, batch_size=100, shuffle=True, num_workers=8
          )
          r = []
          for x, _ in data_loader:
              if len(r) > 1000:
                  break
              print(x.shape)
              r.extend(x.numpy())
          x_train = np.array(r)
          print(x_train.shape)
      elif ds == "challenge":
          x_train = np.load("orig-7.npy")
          print(np.min(x_train), np.max(x_train), x_train.shape)
      else:
          raise
  
imports: import collections
  import hashlib
  import time
  import multiprocessing
  import torch
  import numpy
  import torch.nn
  import scipy.stats
  import matplotlib.pyplot
  from PIL import Image
  import jax
  import jax.numpy
  import objax
  import scipy.optimize
  import numpy
  import multiprocessing
label_desc: Use image node_id 1 for calling a global function with example usage: setup(ds) without return types