# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 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
import pytest

from megengine import tensor
from megengine.module import Conv1d, Conv2d, Conv3d, Linear
from megengine.module.init import calculate_fan_in_and_fan_out, fill_


def test_fill_():
    x = tensor(np.zeros((2, 3, 4)), dtype=np.float32)
    fill_(x, 5.0)

    np.testing.assert_array_equal(
        x.numpy(), np.full(shape=(2, 3, 4), fill_value=5.0, dtype=np.float32)
    )


def test_calculate_fan_in_and_fan_out():
    l = Linear(in_features=3, out_features=8)
    fanin, fanout = calculate_fan_in_and_fan_out(l.weight)
    assert fanin == 3
    assert fanout == 8

    with pytest.raises(ValueError):
        calculate_fan_in_and_fan_out(l.bias)

    l = Conv1d(in_channels=2, out_channels=3, kernel_size=5)
    fanin, fanout = 
calculate_fan_in_and_fan_out(l.weight)