#   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 numpy as np
import unittest

import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.layers as layers
from paddle.fluid.framework import Program, program_guard
from functools import partial


class TestAPISwitchCase(unittest.TestCase):
    def test_return_single_var(self):
        def fn_1():
            return layers.fill_constant(shape=[4, 2], dtype='int32', value=1)

        def fn_2():
            return layers.fill_constant(shape=[4, 2], dtype='int32', value=2)

        def fn_3():
            return layers.fill_constant(shape=[4, 3], dtype='int32', value=3)

        main_program = Program()
        startup_program = Program()
        with program_guard(main_program, startup_program):
            index_1 = layers.fill_constant(shape=[1], dtype='int32', value=1)
            index_2 = layers.fill_constant(shape=[1], dtype='int32', value=2)
            index_5 = layers.fill_constant(shape=[1], dtype='int32', value=5)

            # call fn_1
            out_0 = layers.switch_case(
                branch_index=index_1, branch_fns={1: fn_1,
                                                  2: fn_2,
                                                  3: fn_3})

            # call fn_2 : branch_fns={0: fn_1, 1:fn_2, 2:fn_3}
            out_1 = layers.switch_case(
                branch_index=index_1, branch_fns=(fn_1, fn_2, fn_3))

            # call default fn_3
            out_2 = layers.switch_case(
                branch_index=index_5,
                branch_fns=((1, fn_1), (2, fn_2)),
                default=fn_3)

            # no default, call fn_2
            out_3 = layers.switch_case(
                branch_index=index_2, branch_fns=[(1, fn_1), (2, fn_2)])

            # no default, call fn_2 but branch_index is 5
            out_4 = layers.switch_case(
                branch_index=index_5,
                branch_fns=[(1, fn_1), (3, fn_2), (2, fn_3)])

            place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
            ) else fluid.CPUPlace()
            exe = fluid.Executor(place)

            res = exe.run(main_program,
                          fetch_list=[out_0, out_1, out_2, out_3, out_4])

            self.assertTrue(
                np.allclose(res[0], 1),
                "result is {} but answer is {}".format(res[0], 1))
            self.assertTrue(
                np.allclose(res[1], 2),
                "result is {} but answer is {}".format(res[0], 2))
            self.assertTrue(
                np.allclose(res[2], 3),
                "result is {} but answer is {}".format(res[0], 3))
            self.assertTrue(
                np.allclose(res[3], 2),
                "result is {} but answer is {}".format(res[0], 2))
            self.assertTrue(
                np.allclose(res[4], 2),
                "result is {} but answer is {}".format(res[0], 2))

    def test_return_var_tuple(self):
        def fn_1():
            return layers.fill_constant(
                shape=[1, 2], dtype='int32', value=1), layers.fill_constant(
                    shape=[2, 3], dtype='float32', value=2)

        def fn_2():
            return layers.fill_constant(
                shape=[3, 4], dtype='int32', value=3), layers.fill_constant(
                    shape=[4, 5], dtype='float32', value=4)

        def fn_3():
            return layers.fill_constant(
                shape=[5], dtype='int32', value=5), layers.fill_constant(
                    shape=[5, 6], dtype='float32', value=6)

        main_program = Program()
        startup_program = Program()
        with program_guard(main_program, startup_program):
            index_1 = layers.fill_constant(shape=[1], dtype='int32', value=1)

            out = layers.switch_case(index_1, ((1, fn_1), (2, fn_2)), fn_3)

            place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
            ) else fluid.CPUPlace()
            exe = fluid.Executor(place)
            ret = exe.run(main_program, fetch_list=out)

            self.assertTrue(
                np.allclose(np.asarray(ret[0]), np.full((1, 2), 1, np.int32)))
            self.assertTrue(
                np.allclose(
                    np.asarray(ret[1]), np.full((2, 3), 2, np.float32)))


class TestAPISwitchCase_Nested(unittest.TestCase):
    def test_nested_switch_case(self):
        def fn_1(x=1):
            out = layers.switch_case(
                branch_index=layers.fill_constant(
                    shape=[1], dtype='int32', value=x),
                branch_fns={
                    1: partial(
                        layers.fill_constant, shape=[1], dtype='int32',
                        value=1),
                    x: partial(
                        layers.fill_constant, shape=[2], dtype='int32', value=x)
                })
            return out

        def fn_2(x=2):
            out = layers.switch_case(
                branch_index=layers.fill_constant(
                    shape=[1], dtype='int32', value=2),
                branch_fns={
                    1: partial(
                        layers.fill_constant,
                        shape=[4, 3],
                        dtype='int32',
                        value=1),
                    2: partial(
                        fn_1, x=x)
                })
            return out

        def fn_3():
            out = layers.switch_case(
                branch_index=layers.fill_constant(
                    shape=[1], dtype='int32', value=3),
                branch_fns={
                    1: partial(
                        layers.fill_constant,
                        shape=[4, 3],
                        dtype='int32',
                        value=1),
                    3: partial(
                        fn_2, x=3)
                })
            return out

        main_program = Program()
        startup_program = Program()
        with program_guard(main_program, startup_program):
            index_1 = fluid.data(name="index_1", shape=[1], dtype='uint8')
            index_2 = layers.fill_constant(shape=[1], dtype='int32', value=2)
            index_3 = layers.fill_constant(shape=[1], dtype='int64', value=3)

            out_1 = layers.switch_case(
                branch_index=index_1, branch_fns={1: fn_1,
                                                  2: fn_2,
                                                  3: fn_3})
            out_2 = layers.switch_case(
                branch_index=index_2, branch_fns={1: fn_1,
                                                  2: fn_2,
                                                  3: fn_3})

            out_3 = layers.switch_case(
                branch_index=index_3, branch_fns={1: fn_1,
                                                  2: fn_2,
                                                  3: fn_3})

            place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
            ) else fluid.CPUPlace()
            exe = fluid.Executor(place)

            res = exe.run(main_program,
                          feed={"index_1": np.array(
                              [1], dtype="uint8")},
                          fetch_list=[out_1, out_2, out_3])

            self.assertTrue(
                np.allclose(res[0], 1),
                "result is {} but answer is {}".format(res[0], 1))
            self.assertTrue(
                np.allclose(res[1], 2),
                "result is {} but answer is {}".format(res[1], 2))
            self.assertTrue(
                np.allclose(res[2], 3),
                "result is {} but answer is {}".format(res[2], 3))


# test TypeError and ValueError of api switch_case
class TestAPISwitchCase_Error(unittest.TestCase):
    def test_error(self):
        def fn_1():
            return layers.fill_constant(shape=[4, 2], dtype='int32', value=1)

        def fn_2():
            return layers.fill_constant(shape=[4, 2], dtype='int32', value=2)

        def fn_3():
            return layers.fill_constant(shape=[4, 3], dtype='int32', value=3)

        main_program = Program()
        startup_program = Program()
        with program_guard(main_program, startup_program):
            key_float32 = layers.fill_constant(
                shape=[1], dtype='float32', value=0.23)
            key_int32 = layers.fill_constant(
                shape=[1], dtype='int32', value=0.23)

            # The type of 'branch_index' in Op(switch_case) must be Variable
            def type_error_branch_index():
                layers.switch_case(
                    branch_index=1, branch_fns=[(1, fn_1)], default=fn_3)

            self.assertRaises(TypeError, type_error_branch_index)

            # The data type of 'branch_index' in Op(switch_case) must be int32, int64 or uint8
            def dtype_error_branch_index():
                layers.switch_case(
                    branch_index=key_float32,
                    branch_fns=[(1, fn_1)],
                    default=fn_3)

            self.assertRaises(TypeError, dtype_error_branch_index)

            # The type of 'branch_fns' in Op(switch_case) must be list, tuple or dict
            def type_error_branch_fns():
                layers.switch_case(
                    branch_index=key_int32, branch_fns=1, default=fn_3)

            self.assertRaises(TypeError, type_error_branch_fns)

            # The elements' type of 'branch_fns' in Op(switch_case) must be tuple
            def type_error_index_fn_pair_1():
                layers.switch_case(
                    branch_index=key_int32, branch_fns=[1], default=fn_3)

            self.assertRaises(TypeError, type_error_index_fn_pair_1)

            # The tuple's size of 'branch_fns' in Op(switch_case) must be 2
            def type_error_index_fn_pair_2():
                layers.switch_case(
                    branch_index=key_int32,
                    branch_fns=[(1, 2, 3)],
                    default=fn_3)

            self.assertRaises(TypeError, type_error_index_fn_pair_2)

            # The key's type of 'branch_fns' in Op(switch_case) must be int
            def type_error_key():
                layers.switch_case(
                    branch_index=key_int32, branch_fns=[(2.3, 2)], default=fn_3)

            self.assertRaises(TypeError, type_error_key)

            # The key in 'branch_fns' must be unique
            def value_error_key():
                layers.switch_case(
                    branch_index=key_int32,
                    branch_fns=[(2, fn_1), (2, fn_2)],
                    default=fn_3)

            self.assertRaises(ValueError, value_error_key)

            # The type of function in 'branch_fns' must be callable
            def type_error_fn():
                layers.switch_case(
                    branch_index=key_int32,
                    branch_fns=[(1, 1), (2, fn_2)],
                    default=fn_3)

            self.assertRaises(TypeError, type_error_fn)

            # The default in Op(case) must be callable
            def type_error_default():
                layers.switch_case(
                    branch_index=key_int32,
                    branch_fns=[(1, fn_1), (2, fn_2)],
                    default=1)

            self.assertRaises(TypeError, type_error_default)


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