# Copyright (c) 2020 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_device_place, is_custom_device

import paddle
from paddle import base
from paddle.base.dygraph import guard


class TestImperativeUsingNonZeroGpu(unittest.TestCase):
    def run_main(self, np_arr, place):
        with guard(place):
            var = paddle.to_tensor(np_arr)
            np.testing.assert_array_equal(np_arr, var.numpy())

    def test_non_zero_gpu(self):
        if not (base.is_compiled_with_cuda() or is_custom_device()):
            return

        np_arr = np.random.random([11, 13]).astype('float32')
        if paddle.device.cuda.device_count() > 1:
            # should use non zero gpu if there are more than 1 gpu
            self.run_main(np_arr, get_device_place(1))
        else:
            self.run_main(np_arr, get_device_place(0))


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