# 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
from paddle.fluid.framework import _test_eager_guard


class TestSparseActivation(unittest.TestCase):
    def test_sparse_relu(self):
        with _test_eager_guard():
            x = [[0, -1, 0, 2], [0, 0, -3, 0], [4, 5, 0, 0]]
            dense_x = paddle.to_tensor(x, dtype='float32', stop_gradient=False)
            sparse_dim = 2
            sparse_x = dense_x.to_sparse_coo(sparse_dim)
            sparse_relu = paddle.sparse.ReLU()
            sparse_out = sparse_relu(sparse_x)
            dense_relu = paddle.nn.ReLU()
            #TODO: replace non_zero_elements() as values()
            dense_out = dense_relu(sparse_x.non_zero_elements())
            actual_result = sparse_out.non_zero_elements().numpy()
            assert np.array_equal(dense_out.numpy(), actual_result)
            dense_out.backward(dense_out)
            sparse_out.backward(sparse_out)


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