text: #   Copyright (c) 2022 PaddlePaddle 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.
  
  from __future__ import print_function
  
  import unittest
  import numpy
  import sys
  
  sys.path.append("..")
  
  import op_test
  import paddle
  import paddle.fluid as fluid
  import paddle.fluid.framework as framework
  import paddle.fluid.layers as layers
  
  paddle.enable_static()
  numpy.random.seed(2022)
  
  
  class TestAssignValueMLUOp(op_test.OpTest):
  
      def setUp(self):
          self.set_mlu()
          self.op_type = "assign_value"
          self.inputs = {}
          self.attrs = {}
          self.init_data()
  
          self.attrs["shape"] = self.value.shape
          self.attrs["dtype"] = framework.convert_np_dtype_to_dtype_(
              self.value.dtype)
          self.outputs = {"Out": self.value}
  
      def set_mlu(self):
          self.__class__.use_mlu = True
          self.place = paddle.device.MLUPlace(0)
  
      def init_data(self):
          self.value = numpy.random.random(size=(2, 5)).astype(numpy.float32)
          self.attrs["fp32_values"] = [float(v) for v in self.value.flat]
  
      def test_check_output(self):
          self.check_output_with_place(self.place)
  
  
  class TestAssignValueMLUOp2(TestAssignValueMLUOp):
  
      def init_data(self):
          self.value = numpy.random.random(size=(2, 5)).astype(numpy.int32)
          self.attrs["int32_values"] = [int(v) for v in self.value.flat]
  
  
  class TestAssignValueMLUOp3(TestAssignValueMLUOp):
  
      def init_data(self):
          self.value = numpy.random.random(size=(2, 5)).astype(numpy.int64)
          self.attrs["int64_values"] = [int(v) for v in self.value.flat]
  
  
  class TestAssignValueMLUOp4(TestAssignValueMLUOp):
  
      def init_data(self):
          self.value = numpy.random.choice(a=[False, True],
                                           size=(2, 5)).astype(numpy.bool)
          self.attrs["bool_values"] = [int(v) for v in self.value.flat]
  
  
  if __name__ == '__main__':
      unittest.main()
  