#!/usr/bin/python3
# coding=utf-8

# ----------------------------------------------------------------------------------------------------------
# Copyright (c) 2025 Huawei Technologies Co., Ltd.
# This program is free software, you can redistribute it and/or modify it under the terms and conditions of
# CANN Open Software License Agreement Version 2.0 (the "License").
# Please refer to the License for details. You may not use this file except in compliance with the License.
# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
# INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
# See LICENSE in the root of the software repository for the full text of the License.
# ----------------------------------------------------------------------------------------------------------


import os
import numpy as np


def gen_golden_data():
    m = 1024
    n = 640
    k = 256
    input_a = np.random.randint(1, 10, [m, k]).astype(np.float16)
    input_b = np.random.randint(1, 10, [k, n]).astype(np.float16)
    input_bias = np.random.randint(1, 10, [n]).astype(np.float32)
    alpha = 0.001
    golden = (np.matmul(input_a.astype(np.float32), input_b.astype(np.float32)) + input_bias).astype(np.float32)
    golden = np.where(golden >= 0, golden, golden * alpha)
    os.makedirs("input", exist_ok=True)
    os.makedirs("output", exist_ok=True)
    input_a.tofile("./input/x1_gm.bin")
    input_b.tofile("./input/x2_gm.bin")
    input_bias.tofile("./input/bias.bin")
    golden.tofile("./output/golden.bin")


if __name__ == "__main__":
    gen_golden_data()