# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
import numpy as np
from helpers import opr_test

import megengine.functional as F


def common_test_reduce(opr, ref_opr):
    data1_shape = (5, 6, 7)
    data2_shape = (2, 9, 12)
    data1 = np.random.random(data1_shape).astype(np.float32)
    data2 = np.random.random(data2_shape).astype(np.float32)
    cases = [{"input": data1}, {"input": data2}]

    if opr not in (F.argmin, F.argmax):
        opr_test(cases, opr, ref_fn=ref_opr)

        axis = 2
        opr_test(cases, opr, ref_fn=lambda x: ref_opr(x, axis=axis), axis=axis)

        axis = 2
        keepdims = True
        opr_test(
            cases,
            opr,
            ref_fn=lambda x: ref_opr(x, axis=axis, keepdims=keepdims),
            axis=axis,
            keepdims=keepdims,
        )
    else:
        opr_test(cases, opr, ref_fn=lambda x: ref_opr(x).astype(np.int32))

        axis = 2
        opr_test(
            cases,
            opr,
            ref_fn=lambda x: ref_opr(x, axis=axis).astype(np.int32),
            axis=axis,
        )


def test_sum():
    common_test_reduce(opr=F.sum, ref_opr=np.sum)


def test_prod():
    common_test_reduce(opr=F.prod, ref_opr=np.prod)


def test_mean():
    common_test_reduce(opr=F.mean, ref_opr=np.mean)


def test_min():
    common_test_reduce(opr=F.min, ref_opr=np.min)


def test_max():
    common_test_reduce(opr=F.max, ref_opr=np.max)


def test_argmin():
    common_test_reduce(opr=F.argmin, ref_opr=np.argmin)


def test_argmax():
    common_test_reduce(opr=F.argmax, ref_opr=np.argmax)


def test_sqrt():
    d1_shape = (15,)
    d2_shape = (25,)
    d1 = np.random.random(d1_shape).astype(np.float32)
    d2 = np.random.random(d2_shape).astype(np.float32)

    cases = [{"input": d1}, {"input": d2}]
    opr_test(cases, F.sqrt, ref_fn=np.sqrt)