code: def generate_sparse_data_non_seq(batch_size, feature_size):
      data = np.zeros((batch_size, feature_size)).astype(np.float32)
      np.random.seed(0)
      for i in range(0, batch_size):
          one_hot_index = np.random.random_integers(0, feature_size - 1)
          data[i][one_hot_index] = 1.0
      sparse_data = scipy.sparse.csr_matrix(data)
      return sparse_data
  
file_path: CNTK/bindings/python/cntk/tests/onnx_verify_helper.py
imports: from __future__ import print_function
  import os, re, sys, subprocess, scipy, pytest, numpy
  import cntk
label_desc: Use image node_id 9 for calling a global function with example usage: generate_sparse_data_non_seq(batch_size, feature_size) and returns: sparse_data