# Copyright (c) 2019 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.

import unittest

import numpy as np
from op_test import get_places, is_custom_device

from paddle import base


class TensorToNumpyTest(unittest.TestCase):
    def setUp(self):
        self.shape = [11, 25, 32, 43]

    def test_main(self):
        dtypes = [
            'float32',
            'float64',
            'int32',
            'int64',
            'uint8',
            'int8',
            'bool',
        ]

        places = get_places()
        if base.core.is_compiled_with_cuda() or is_custom_device():
            places.append(base.CUDAPinnedPlace())

        for p in places:
            for dtype in dtypes:
                np_arr = np.reshape(
                    np.array(range(np.prod(self.shape))).astype(dtype),
                    self.shape,
                )

                t = base.DenseTensor()
                t.set(np_arr, p)

                ret_np_arr = np.array(t)
                self.assertEqual(np_arr.shape, ret_np_arr.shape)
                self.assertEqual(np_arr.dtype, ret_np_arr.dtype)

                all_equal = np.all(np_arr == ret_np_arr)
                self.assertTrue(all_equal)


if __name__ == '__main__':
    unittest.main()