/**
 * 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.
 */

#include "aclnn_atan.h"
#include "atan.h"
#include "aclnn_kernels/cast.h"
#include "aclnn_kernels/contiguous.h"
#include "aclnn_kernels/common/op_error_check.h"
#include "opdev/common_types.h"
#include "opdev/data_type_utils.h"
#include "opdev/format_utils.h"
#include "opdev/op_dfx.h"
#include "opdev/op_executor.h"
#include "opdev/op_log.h"
#include "opdev/tensor_view_utils.h"
#include "opdev/platform.h"
#include "op_api/level2_base.h"
#include "op_api/aclnn_check.h"

using namespace op;
#ifdef __cplusplus
extern "C" {
#endif

// 根据API定义，需要列出所能支持的所有dtype
static const std::initializer_list<DataType> ASCEND910_DTYPE_DTYPE_SUPPORT_LIST = {
    DataType::DT_FLOAT, DataType::DT_FLOAT16, DataType::DT_DOUBLE, DataType::DT_INT8, DataType::DT_INT16,
    DataType::DT_INT32, DataType::DT_INT64,   DataType::DT_BOOL,   DataType::DT_UINT8};

static const std::initializer_list<DataType> ASCEND910B_DTYPE_DTYPE_SUPPORT_LIST = {
    DataType::DT_FLOAT, DataType::DT_FLOAT16, DataType::DT_DOUBLE, DataType::DT_INT8,  DataType::DT_INT16,
    DataType::DT_INT32, DataType::DT_INT64,   DataType::DT_BOOL,   DataType::DT_UINT8, DataType::DT_BF16};

static const std::initializer_list<DataType> OUTPUT_DTYPE_SUPPORT_LIST = {
    DataType::DT_FLOAT, DataType::DT_FLOAT16, DataType::DT_DOUBLE, DataType::DT_BF16};

static const std::initializer_list<DataType> ASCEND910_DTYPE_SELFREF_LIST = {
    DataType::DT_FLOAT, DataType::DT_FLOAT16, DataType::DT_DOUBLE};

static const std::initializer_list<DataType> ASCEND950_DTYPE_SELFREF_LIST = {
    DataType::DT_FLOAT, DataType::DT_FLOAT16, DataType::DT_BF16};

static bool CheckInplaceDtypeValid(aclTensor* selfRef)
{
    auto inplaceSupportList = GetDtypeSupportListV2(OUTPUT_DTYPE_SUPPORT_LIST, ASCEND910_DTYPE_SELFREF_LIST);
    if (IsRegBase()) {
        inplaceSupportList = ASCEND950_DTYPE_SELFREF_LIST;
    }
    // 检查selfRef的数据类型是否在inplace atan算子的支持列表内
    OP_CHECK_DTYPE_NOT_SUPPORT(selfRef, inplaceSupportList, return false);

    return true;
}

static aclnnStatus CheckParamsAtan(const aclTensor* input, const aclTensor* out)
{
    // 检查输入的数据类型是否在API支持的数据类型范围之内，需要根据api定义校验
    auto supportList = GetDtypeSupportListV1(ASCEND910B_DTYPE_DTYPE_SUPPORT_LIST, ASCEND910_DTYPE_DTYPE_SUPPORT_LIST);
    CHECK_RET(CheckDtypeValid1In1Out(input, out, supportList, OUTPUT_DTYPE_SUPPORT_LIST), ACLNN_ERR_PARAM_INVALID);
    // 检查输入的数据的值是否合理
    CHECK_RET(CheckSameShape1In1Out(input, out), ACLNN_ERR_PARAM_INVALID);
    return ACLNN_SUCCESS;
}

static aclnnStatus CheckInplaceParamsAtan(aclTensor* selfRef)
{
    OP_CHECK_NULL(selfRef, return ACLNN_ERR_PARAM_NULLPTR);

    // 检查selfRef的数据类型是否在inplace atan算子的支持列表内
    CHECK_RET(CheckInplaceDtypeValid(selfRef), ACLNN_ERR_PARAM_INVALID);
    return ACLNN_SUCCESS;
}

static aclnnStatus ExecAtanGetWorkspaceSize(
    const aclTensor* input, aclTensor* out, uint64_t* workspaceSize, aclOpExecutor** executor)
{
    CHECK_NOT_NULL(input, out);
    // 创建OpExecutor
    auto uniqueExecutor = CREATE_EXECUTOR();
    CHECK_RET(uniqueExecutor.get() != nullptr, ACLNN_ERR_INNER_CREATE_EXECUTOR);

    // 参数检查
    auto ret = CheckParamsAtan(input, out);
    CHECK_RET(ret == ACLNN_SUCCESS, ret);

    if (input->IsEmpty()) {
        // 根据实际支持情况补充
        *workspaceSize = 0;
        uniqueExecutor.ReleaseTo(executor);
        return ACLNN_SUCCESS;
    }

    auto inputContiguous = l0op::Contiguous(input, uniqueExecutor.get());
    CHECK_RET(inputContiguous != nullptr, ACLNN_ERR_INNER_NULLPTR);

    const aclTensor* inputCast = nullptr;
    if (!CheckType(inputContiguous->GetDataType(), OUTPUT_DTYPE_SUPPORT_LIST)) {
        inputCast = l0op::Cast(inputContiguous, DataType::DT_FLOAT, uniqueExecutor.get());
        CHECK_RET(inputCast != nullptr, ACLNN_ERR_INNER_NULLPTR);
    } else {
        inputCast = inputContiguous;
    }
    // 执行L0算子
    auto atanOutRet = l0op::Atan(inputCast, uniqueExecutor.get());
    CHECK_RET(atanOutRet != nullptr, ACLNN_ERR_INNER_NULLPTR);

    auto castOut = l0op::Cast(atanOutRet, out->GetDataType(), uniqueExecutor.get());
    CHECK_RET(castOut != nullptr, ACLNN_ERR_INNER_NULLPTR);

    // 将计算结果拷贝到输出out上，out可能是非连续的tensor
    auto viewCopyResult = l0op::ViewCopy(castOut, out, uniqueExecutor.get());
    CHECK_RET(viewCopyResult != nullptr, ACLNN_ERR_INNER_NULLPTR);

    // 获取计算过程中需要使用的workspace大小
    *workspaceSize = uniqueExecutor->GetWorkspaceSize();
    // 需要把 uniqueExecutor持有executor转移给executor
    uniqueExecutor.ReleaseTo(executor);
    return ACLNN_SUCCESS;
}

aclnnStatus aclnnAtanGetWorkspaceSize(
    const aclTensor* input, aclTensor* out, uint64_t* workspaceSize, aclOpExecutor** executor)
{
    L2_DFX_PHASE_1(aclnnAtan, DFX_IN(input), DFX_OUT(out));
    return ExecAtanGetWorkspaceSize(input, out, workspaceSize, executor);
}

aclnnStatus aclnnInplaceAtanGetWorkspaceSize(aclTensor* inputRef, uint64_t* workspaceSize, aclOpExecutor** executor)
{
    L2_DFX_PHASE_1(aclnnInplaceAtan, DFX_IN(inputRef), DFX_OUT(inputRef));
    auto out = const_cast<aclTensor*>(inputRef);
    auto ret = CheckInplaceParamsAtan(inputRef);
    CHECK_RET(ret == ACLNN_SUCCESS, ret);
    return ExecAtanGetWorkspaceSize(inputRef, out, workspaceSize, executor);
}

aclnnStatus aclnnAtan(void* workspace, uint64_t workspaceSize, aclOpExecutor* executor, const aclrtStream stream)
{
    // 固定写法，调用框架能力，完成计算
    L2_DFX_PHASE_2(aclnnAtan);
    return CommonOpExecutorRun(workspace, workspaceSize, executor, stream);
}

aclnnStatus aclnnInplaceAtan(void* workspace, uint64_t workspaceSize, aclOpExecutor* executor, const aclrtStream stream)
{
    // 固定写法，调用框架能力，完成计算
    L2_DFX_PHASE_2(aclnnInplaceAtan);
    return CommonOpExecutorRun(workspace, workspaceSize, executor, stream);
}

#ifdef __cplusplus
}
#endif