#  Copyright (c) 2024 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, get_places

import paddle
from paddle import base


class TestIndexSelectStrided(unittest.TestCase):
    def setUp(self):
        self.shape = [3, 3]
        self.typelist = ['float32', 'float64', 'int32', 'int64', 'float16']
        self.places = get_places()
        if base.core.is_compiled_with_cuda():
            self.places.append(base.CUDAPinnedPlace())

    def test_index_select_strided_forward(self):
        for idx, p in enumerate(self.places):
            if idx == 0:
                paddle.set_device('cpu')
            else:
                paddle.set_device(get_device())
            for dtype in self.typelist:
                x_np = np.random.random(self.shape).astype(dtype)
                x = paddle.to_tensor(x_np, place=p)
                row0 = paddle._C_ops.index_select_strided(x, 0, 0)
                row1 = paddle._C_ops.index_select_strided(x, 1, 0)
                row2 = paddle._C_ops.index_select_strided(x, 2, 0)
                col0 = paddle._C_ops.index_select_strided(x, 0, 1)
                col1 = paddle._C_ops.index_select_strided(x, 1, 1)
                col2 = paddle._C_ops.index_select_strided(x, 2, 1)
                # check inplace
                row0[0] = 0
                x_np[0][0] = 0
                np.testing.assert_allclose(x.numpy(), x_np)
                np.testing.assert_allclose(row0.numpy(), x_np[0])
                np.testing.assert_allclose(row1.numpy(), x_np[1])
                np.testing.assert_allclose(row2.numpy(), x_np[2])
                np.testing.assert_allclose(col0.numpy(), x_np[:, 0])
                np.testing.assert_allclose(col1.numpy(), x_np[:, 1])
                np.testing.assert_allclose(col2.numpy(), x_np[:, 2])

    def test_index_select_strided_backward(self):
        for idx, p in enumerate(self.places):
            if idx == 0:
                paddle.set_device('cpu')
            else:
                paddle.set_device(get_device())
            for dtype in self.typelist:
                x_np = np.random.random(self.shape).astype(dtype)
                x = paddle.to_tensor(x_np, place=p)
                x.stop_gradient = False
                a = paddle._C_ops.index_select_strided(x, 1, 0)
                b = a * 2
                b.retain_grads()
                loss = b.sum()
                loss.backward()
                self.assertEqual((b.grad.numpy() == 1).all().item(), True)


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