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 as np
  import paddle
  import paddle.fluid as fluid
  from paddle import zeros_like
  from paddle.fluid import core, Program, program_guard
  from paddle.fluid.framework import _test_eager_guard
  
  
  class TestZerosLikeAPIError(unittest.TestCase):
  
      def test_errors(self):
          with program_guard(Program(), Program()):
              x = paddle.fluid.data('x', [3, 4])
              self.assertRaises(TypeError, zeros_like, x, 'int8')
  
      def test_eager(self):
          with _test_eager_guard():
              self.test_errors()
  
  
  class TestZerosLikeAPI(unittest.TestCase):
  
      def test_api(self):
          shape = [3, 4]
          startup_program = Program()
          train_program = Program()
          with program_guard(train_program, startup_program):
              x = paddle.fluid.data('X', shape)
              out1 = zeros_like(x)
              out2 = zeros_like(x, np.bool)
              out3 = zeros_like(x, 'float64')
              out4 = zeros_like(x, 'int32')
              out5 = zeros_like(x, 'int64')
          place = (fluid.CUDAPlace(0)
                   if core.is_compiled_with_cuda() else fluid.CPUPlace())
          exe = fluid.Executor(place)
          outs = exe.run(train_program,
                         feed={'X': np.ones(shape).astype('float32')},
                         fetch_list=[out1, out2, out3, out4, out5])
          for (i, dtype) in enumerate(
              [np.float32, np.bool, np.float64, np.int32, np.int64]):
              self.assertEqual(outs[i].dtype, dtype)
              self.assertEqual((outs[i] == np.zeros(shape, dtype)).all(), True)
  
      def test_eager(self):
          with _test_eager_guard():
              self.test_api()
  
  
  class TestZerosLikeImpeartive(unittest.TestCase):
  
      def test_out(self):
          shape = [3, 4]
          place = (fluid.CUDAPlace(0)
                   if core.is_compiled_with_cuda() else fluid.CPUPlace())
          paddle.disable_static(place)
          x = paddle.to_tensor(np.ones(shape))
          for dtype in [np.bool, np.float32, np.float64, np.int32, np.int64]:
              out = zeros_like(x, dtype)
              self.assertEqual((out.numpy() == np.zeros(shape, dtype)).all(),
                               True)
          out = paddle.tensor.zeros_like(x)
          self.assertEqual((out.numpy() == np.zeros(shape, dtype)).all(), True)
          out = paddle.tensor.creation.zeros_like(x)
          self.assertEqual((out.numpy() == np.zeros(shape, dtype)).all(), True)
          paddle.enable_static()
  
      def test_eager(self):
          with _test_eager_guard():
              self.test_out()
  
  
  if (__name__ == '__main__'):
      unittest.main()
  