text: """
  Copyright 2020 The OneFlow Authors. All rights reserved.
  
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at
  
      http://www.apache.org/licenses/LICENSE-2.0
  
  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License.
  """
  import unittest
  import numpy as np
  import oneflow as flow
  from collections import OrderedDict
  from oneflow.test_utils.automated_test_util import *
  from oneflow.nn.modules import min_max_observer
  from oneflow.test_utils.test_util import GenArgList
  from test_min_max_observer import _check_min_max_observer
  
  
  def _run_test_min_max_observer(
      test_case,
      placement,
      sbp,
      weight_shape,
      quantization_bit,
      quantization_scheme,
      quantization_formula,
      per_layer_quantization,
  ):
      weight = random_tensor(
          len(weight_shape), *weight_shape, low=-0.5, high=0.5
      ).to_global(placement, sbp)
      of_weight = weight.oneflow
      np_weight = of_weight.numpy()
  
      min_max_observer = flow.nn.MinMaxObserver(
          quantization_formula=quantization_formula,
          quantization_bit=quantization_bit,
          quantization_scheme=quantization_scheme,
          per_layer_quantization=per_layer_quantization,
      )
      scale, zero_point = min_max_observer(of_weight)
      _check_min_max_observer(
          test_case,
          np_weight,
          scale.numpy(),
          zero_point.numpy(),
          quantization_bit,
          quantization_scheme,
          quantization_formula,
          per_layer_quantization,
      )
  
  
  class TestMinMaxObserver(flow.unittest.TestCase):
      @globaltest
      def test_min_max_observer(test_case):
          arg_dict = OrderedDict()
          arg_dict["weight_shape"] = [(9, 48, 24, 10)]
          arg_dict["quantization_bit"] = [8, 2]
          arg_dict["quantization_scheme"] = ["symmetric", "affine"]
          arg_dict["quantization_formula"] = ["google"]
          arg_dict["per_layer_quantization"] = [True, False]
          for arg in GenArgList(arg_dict):
              for placement in all_placement():
                  for sbp in all_sbp(placement, valid_split_axis=[1, 2]):
                      _run_test_min_max_observer(test_case, placement, sbp, *arg)
  
  
  if __name__ == "__main__":
      unittest.main()
  