code: def generate_data(par, size, seed=777):
      ns, nf = par["ns"], par["nf"]
  
      data_blocks, weight_blocks = [], []
      rng = np.random.default_rng(seed)
  
      for b in range(size):
          data = rng.uniform(b, (b + 1) * (b + 1), size=(ns, nf))
          weights = rng.uniform(1, (b + 1), size=ns)
          weight_blocks.append(weights)
          data_blocks.append(data)
  
      data = np.concatenate(data_blocks, axis=0)
      weights = np.concatenate(weight_blocks)
  
      return (data, weights)
  
imports: import dpctl.tensor
  import numpy
  from dpctl import SyclQueue
  from mpi4py import MPI
  from sklearnex.spmd.basic_statistics import BasicStatistics
label_desc: Use image node_id 1 for calling a global function with example usage: generate_data(par, size, seed) and returns: data,  weights