#   Copyright (c) 2021 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

import paddle
from paddle import fluid
from paddle.incubate.layers import _pull_gpups_sparse

paddle.enable_static()


class TestPullGpupsSparse(unittest.TestCase):
    """Test PullGpupsSparse op."""

    def test_static_graph(self):
        startup_program = fluid.Program()
        train_program = fluid.Program()
        slots = []
        with fluid.program_guard(train_program, startup_program):
            l = paddle.static.data(
                name='input', shape=[-1, 1], dtype="int64", lod_level=1
            )
            slots.append(l)
            output = _pull_gpups_sparse(
                slots, size=[11], is_distributed=True, is_sparse=True
            )
            cost = paddle.mean(output)
            sgd_optimizer = paddle.optimizer.SGD(learning_rate=0.001)
            sgd_optimizer.minimize(cost, train_program)
            block = train_program.global_block()
            place = fluid.CPUPlace()
            if fluid.core.is_compiled_with_cuda():
                place = fluid.CUDAPlace(0)
            exe = fluid.Executor(place)
            exe.run(startup_program)
            img = np.array([1]).astype(np.int64)
            res = exe.run(
                train_program, feed={'input': img}, fetch_list=[output]
            )


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