# Copyright 2020-2021 Huawei Technologies Co., Ltd
#
# 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
import numpy as np
from akg.utils import kernel_exec as utils
from akg.ops.math_gpu.addn import addn
from tests.common.gen_random import random_gaussian
from tests.common.tensorio import compare_tensor


def gen_data(shape, shapes, dtype, n):
    support_list = {"float16": np.float16, "float32": np.float32}
    inputs = []
    for i in range(n):
        one_input = random_gaussian(shape, miu=1, sigma=0.1).astype(support_list[dtype])
        inputs.append(one_input)
        shapes.append(shape)
    expect = np.sum(inputs, axis=0)
    output = np.full(shape, np.nan, dtype)
    return expect, inputs, output


def test_ms_addn(shape, dtype, n, poly_sch=False):
    shapes = []
    for i in range(n):
        shapes.append(shape)
    if poly_sch:
        mod = utils.op_build_test(addn, [shapes], [dtype], attrs={"target": "cuda"}, kernel_name="addn")

    expect, inputs, output = gen_data(shape, shapes, dtype, n)
    output = utils.mod_launch(mod, (*inputs, output), expect=expect)
    res = compare_tensor(output, expect, rtol=5e-03, atol=1.e-8)
    print("Test {}".format("Pass" if res else "Fail"))
    if not res:
        print("Error cuda:========================")
        print(mod.imported_modules[0].get_source())
        raise AssertionError("Test fail")

    return True
