#   Copyright (c) 2019 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
from paddle.fluid.tests.unittests.op_test import OpTest


class TestConcatOp(OpTest):
    def setUp(self):
        self.op_type = "concat"
        self.use_mkldnn = True
        self._cpu_only = True
        self.init_axis()
        self.init_shape()
        self.init_test_data()
        self.inputs = {'X': [('x0', self.x0), ('x1', self.x1), ('x2', self.x2)]}
        self.attrs = {'axis': self.axis, 'use_mkldnn': True}

        self.output = np.concatenate(
            (self.x0, self.x1, self.x2), axis=self.axis).astype('int')

        self.outputs = {'Out': self.output}

    def test_check_output(self):
        # TODO(wangzhongpu): support mkldnn op in dygraph mode
        self.check_output(check_dygraph=False)

#--------------------test concat s8 in with axis 0--------------------

    def init_test_data(self):
        self.x0 = (np.random.randint(0, 100, self.x0_shape) - 50).astype('int8')
        self.x1 = (np.random.randint(0, 80, self.x1_shape) - 30).astype('int8')
        self.x2 = (np.random.randint(0, 110, self.x2_shape) - 80).astype('int8')

    def init_axis(self):
        self.axis = 0

    def init_shape(self):
        self.x0_shape = [2, 2, 1, 2]
        self.x1_shape = [1, 2, 1, 2]
        self.x2_shape = [3, 2, 1, 2]


#--------------------test concat u8 in with axis 0--------------------


class TestConcatOp2(TestConcatOp):
    def init_test_data(self):
        self.x0 = (np.random.randint(0, 100, self.x0_shape)).astype('uint8')
        self.x1 = (np.random.randint(0, 50, self.x1_shape)).astype('uint8')
        self.x2 = (np.random.randint(0, 80, self.x2_shape)).astype('uint8')

    def init_axis(self):
        self.axis = 0

    def init_shape(self):
        self.x0_shape = [2, 1, 5, 5]
        self.x1_shape = [1, 1, 5, 5]
        self.x2_shape = [3, 1, 5, 5]


def create_test_int8_class(parent):

    #--------------------test concat s8/u8 in with axis 1--------------------

    class TestAxis1Case(parent):
        def init_axis(self):
            self.axis = 1

        def init_shape(self):
            self.x0_shape = [1, 1, 5, 5]
            self.x1_shape = [1, 2, 5, 5]
            self.x2_shape = [1, 3, 5, 5]

#--------------------test concat s8/u8 in with axis 2--------------------

    class TestAxis2Case(parent):
        def init_axis(self):
            self.axis = 2

        def init_shape(self):
            self.x0_shape = [2, 3, 4, 5]
            self.x1_shape = [2, 3, 5, 5]
            self.x2_shape = [2, 3, 6, 5]

#--------------------test concat s8/u8 in with axis 3--------------------

    class TestAxis3Case(parent):
        def init_axis(self):
            self.axis = 3

        def init_shape(self):
            self.x0_shape = [2, 3, 5, 5]
            self.x1_shape = [2, 3, 5, 6]
            self.x2_shape = [2, 3, 5, 7]

    cls_name_1 = "{0}_axis_{1}".format(parent.__name__, "1")
    cls_name_2 = "{0}_axis_{1}".format(parent.__name__, "2")
    cls_name_3 = "{0}_axis_{1}".format(parent.__name__, "3")
    TestAxis1Case.__name__ = cls_name_1
    TestAxis2Case.__name__ = cls_name_2
    TestAxis3Case.__name__ = cls_name_3
    globals()[cls_name_1] = TestAxis1Case
    globals()[cls_name_2] = TestAxis2Case
    globals()[cls_name_3] = TestAxis3Case

create_test_int8_class(TestConcatOp)
create_test_int8_class(TestConcatOp2)

if __name__ == '__main__':
    from paddle import enable_static
    enable_static()
    unittest.main()
