code: def resize_dataset(x, IMG_SIZE):
      num_data = x.shape[0]
      dim = x.shape[1]
      X = np.zeros(
          shape=(num_data, dim, IMG_SIZE, IMG_SIZE), dtype=np.float32
      )
      for n in range(0, num_data):
          for d in range(0, dim):
              X[n, d, :, :] = np.array(
                  Image.fromarray(x[n, d, :, :]).resize(
                      (IMG_SIZE, IMG_SIZE), Image.BILINEAR
                  ),
                  dtype=np.float32,
              )
      return X
  
imports: from singa import singa_wrap
  from singa import autograd
  from singa import tensor
  from singa import device
  from singa import opt
  from PIL import Image
  import numpy
  import os
  import sys
  import time
label_desc: Use image node_id 6 for calling a global function with example usage: resize_dataset(x, IMG_SIZE) and returns: X