code: def test_onnx_save_load_digest(self):
      warnings.filterwarnings("ignore")
      max_depth = 10
      num_classes = 2
      model = GradientBoostingClassifier(
          n_estimators=10, max_depth=max_depth
      )
      np.random.seed(0)
      X = np.random.rand(100, 200)
      X = np.array(X, dtype=np.float32)
      y = np.random.randint(num_classes, size=100)
  
      model.fit(X, y)
  
      hb_model = hummingbird.ml.convert(model, "onnx", X)
      self.assertIsNotNone(hb_model)
      my_digest = hb_model.save("onnx-tmp")
  
      hb_model_loaded = hummingbird.ml.ONNXContainer.load(
          "onnx-tmp", digest=my_digest
      )
      np.testing.assert_allclose(
          hb_model_loaded.predict_proba(X),
          hb_model.predict_proba(X),
          rtol=1e-06,
          atol=1e-06,
      )
  
      # Now try to load with a different digest
      self.assertRaises(
          RuntimeError,
          hummingbird.ml.ONNXContainer.load,
          "onnx-tmp",
          digest="BAD_DIGEST",
      )
  
      os.remove("onnx-tmp.zip")
  
imports: import unittest
  import warnings
  import os
  import sys
  import numpy
  from typing import Iterator
  from packaging.version import Version, parse
  import shutil
  from sklearn.ensemble import GradientBoostingClassifier
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
  from sklearn.datasets import load_iris
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import make_pipeline
  from onnxconverter_common.data_types import FloatTensorType, DoubleTensorType, Int64TensorType, Int32TensorType, StringTensorType
  import hummingbird.ml
  from hummingbird.ml._utils import onnx_ml_tools_installed, onnx_runtime_installed, tvm_installed, sparkml_installed, pandas_installed, prophet_installed
  from hummingbird.ml.exceptions import MissingBackend
label_desc: Use image node_id 34 for calling the TestBackends obj's underlying member method code with example usage: obj.test_onnx_save_load_digest() without return types