code: def main(readcsv=read_csv):
      # input data file
      train_file = os.path.join(
          "..",
          "..",
          "..",
          "examples",
          "daal4py",
          "data",
          "batch",
          "svm_two_class_train_dense.csv",
      )
      predict_file = os.path.join(
          "..",
          "..",
          "..",
          "examples",
          "daal4py",
          "data",
          "batch",
          "svm_two_class_test_dense.csv",
      )
  
      nFeatures = 20
      train_data = readcsv(train_file, range(nFeatures), t=np.float32)
      train_labels = readcsv(
          train_file, range(nFeatures, nFeatures + 1), t=np.float32
      )
      predict_data = readcsv(
          predict_file, range(nFeatures), t=np.float32
      )
      predict_labels = readcsv(
          predict_file, range(nFeatures, nFeatures + 1), t=np.float32
      )
  
      predict_result_classic, decision_function_classic = compute(
          train_data, train_labels, predict_data, "boser"
      )
  
      train_data = to_numpy(train_data)
      train_labels = to_numpy(train_labels)
      predict_data = to_numpy(predict_data)
  
      # It is possible to specify to make the computations on GPU
      if gpu_available:
          with sycl_context("gpu"):
              sycl_train_data = sycl_buffer(train_data)
              sycl_train_labels = sycl_buffer(train_labels)
              sycl_predict_data = sycl_buffer(predict_data)
  
              predict_result_gpu, decision_function_gpu = compute(
                  sycl_train_data,
                  sycl_train_labels,
                  sycl_predict_data,
                  "thunder",
              )
              # assert np.allclose(predict_result_gpu, predict_result_classic)
  
      return (
          predict_labels,
          predict_result_classic,
          decision_function_classic,
      )
  
imports: import os
  import numpy
  import daal4py
  from daal4py.oneapi import sycl_buffer
label_desc: Use image node_id 3 for calling a global function with example usage: main(readcsv) and returns: predict_labels,  predict_result_classic,  decision_function_classic