#   Copyright (c) 2018 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.fluid.core as core
from op_test import OpTest


class TestSliceOp(OpTest):
    def setUp(self):
        self.op_type = "slice"
        self.config()
        self.inputs = {'Input': self.input}
        self.outputs = {'Out': self.out}
        self.attrs = {
            'axes': self.axes,
            'starts': self.starts,
            'ends': self.ends
        }

    def config(self):
        self.input = np.random.random([3, 4, 5, 6]).astype("float32")
        self.starts = [1, 0, 2]
        self.ends = [3, 3, 4]
        self.axes = [0, 1, 2]
        self.out = self.input[1:3, 0:3, 2:4, :]

    def test_check_output(self):
        self.check_output()

    def test_check_grad_normal(self):
        self.check_grad(['Input'], 'Out', max_relative_error=0.006)


class TestCase1(TestSliceOp):
    def config(self):
        self.input = np.random.random([3, 4, 5, 6]).astype("float32")
        self.starts = [-3, 0, 2]
        self.ends = [3, 100, -1]
        self.axes = [0, 1, 2]
        self.out = self.input[-3:3, 0:100, 2:-1, :]


class TestCase2(TestSliceOp):
    def config(self):
        self.input = np.random.random([3, 4, 5, 6]).astype("float32")
        self.starts = [-3, 0, 2]
        self.ends = [3, 100, -1]
        self.axes = [0, 1, 3]
        self.out = self.input[-3:3, 0:100, :, 2:-1]


@unittest.skipIf(not core.is_compiled_with_cuda(),
                 "core is not compiled with CUDA")
class TestFP16(TestSliceOp):
    def config(self):
        self.dtype = "float16"
        self.input = np.random.random([3, 4, 5, 6]).astype(self.dtype)
        self.starts = [-3, 0, 2]
        self.ends = [3, 100, -1]
        self.axes = [0, 1, 3]
        self.out = self.input[-3:3, 0:100, :, 2:-1]

    def test_check_output(self):
        place = core.CUDAPlace(0)
        if core.is_float16_supported(place):
            self.check_output_with_place(place, atol=1e-5)

    def test_check_grad_normal(self):
        place = core.CUDAPlace(0)
        if core.is_float16_supported(place):
            self.check_grad_with_place(
                place, ['Input'], 'Out', max_relative_error=0.006)


@unittest.skipIf(not core.is_compiled_with_cuda(),
                 "core is not compiled with CUDA")
class TestFP16_2(TestSliceOp):
    def config(self):
        self.dtype = "float16"
        self.input = np.random.random([3, 4, 5]).astype(self.dtype)
        self.starts = [0]
        self.ends = [1]
        self.axes = [1]
        self.out = self.input[:, 0:1, :]

    def test_check_output(self):
        place = core.CUDAPlace(0)
        if core.is_float16_supported(place):
            self.check_output_with_place(place, atol=1e-5)

    def test_check_grad_normal(self):
        place = core.CUDAPlace(0)
        if core.is_float16_supported(place):
            self.check_grad_with_place(
                place, ['Input'],
                'Out',
                max_relative_error=0.006,
                numeric_grad_delta=0.5)


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