/**
 * 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 "log.h"
#include "aclnn_kernels/cast.h"
#include "aclnn_kernels/contiguous.h"
#include "aclnn/aclnn_base.h"
#include "opdev/common_types.h"
#include "opdev/data_type_utils.h"
#include "opdev/shape_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 <cmath>
#include "aclnn_kernels/common/op_error_check.h"
#include "op_api/level2_base.h"
#include "aclnn_log10.h"

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

constexpr float LOG_BASE = 10.0f;
constexpr float LOG_SCALE = 1.0f;
constexpr float LOG_SHIFT = 0.0f;

// 根据API定义，需要列出所能支持的所有dtype
static const std::initializer_list<op::DataType> DTYPE_SUPPORT_LIST = {
    op::DataType::DT_BOOL,  op::DataType::DT_UINT8,  op::DataType::DT_INT8,      op::DataType::DT_INT16,
    op::DataType::DT_INT32, op::DataType::DT_INT64,  op::DataType::DT_BF16,      op::DataType::DT_FLOAT16,
    op::DataType::DT_FLOAT, op::DataType::DT_DOUBLE, op::DataType::DT_COMPLEX64, op::DataType::DT_COMPLEX128};

static const std::initializer_list<op::DataType> UNCHANGED_DTYPE_LIST = {
    op::DataType::DT_BF16,   op::DataType::DT_FLOAT16,   op::DataType::DT_FLOAT,
    op::DataType::DT_DOUBLE, op::DataType::DT_COMPLEX64, op::DataType::DT_COMPLEX128};

static const std::initializer_list<op::DataType> ASCEND910_DTYPE_SELFREF_LIST = {
    op::DataType::DT_FLOAT16,   op::DataType::DT_FLOAT, op::DataType::DT_DOUBLE,
    op::DataType::DT_COMPLEX64, op::DataType::DT_COMPLEX128};

static bool CheckDtypeValid(const aclTensor* self, const aclTensor* out) {
  // 检查self的数据类型是否在log算子的支持列表内
  OP_CHECK_DTYPE_NOT_SUPPORT(self, DTYPE_SUPPORT_LIST, return false);
  // 检查out的数据类型是否符合要求
  if (CheckType(self->GetDataType(), UNCHANGED_DTYPE_LIST)) {
    OP_CHECK_DTYPE_NOT_SAME(self, out, return false);
  } else {
    OP_CHECK_DTYPE_NOT_MATCH(out, op::DataType::DT_FLOAT, return false);
  }
  return true;
}

static bool CheckInplaceDtypeValid(aclTensor *selfRef) {
  auto inplaceSupportList = GetDtypeSupportListV2(UNCHANGED_DTYPE_LIST, ASCEND910_DTYPE_SELFREF_LIST);
  // 检查selfRef的数据类型是否在inplace log10算子的支持列表内
  OP_CHECK_DTYPE_NOT_SUPPORT(selfRef, inplaceSupportList, return false);

  return true;
}

static void CheckFormat(const aclTensor* self) {
    ge::Format selfStorageFormat = self->GetStorageFormat();
    if (selfStorageFormat == ge::Format::FORMAT_FRACTAL_NZ) {
        OP_LOGW("aclnnLog10 doesn't support format NZ.");
    }
}

static aclnnStatus CheckParams(const aclTensor* self, const aclTensor* out) {
  // 1. 检查参数是否为空指针
  CHECK_RET(CheckNotNull2Tensor(self, out), ACLNN_ERR_PARAM_NULLPTR);

  // 2. 检查数据类型
  CHECK_RET(CheckDtypeValid(self, out), ACLNN_ERR_PARAM_INVALID);

  // 3. 检查shape
  CHECK_RET(CheckSameShape1In1Out(self, out), ACLNN_ERR_PARAM_INVALID);

  return ACLNN_SUCCESS;
}

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

  // 检查selfRef的数据类型是否在inplace log10算子的支持列表内
  CHECK_RET(CheckInplaceDtypeValid(selfRef), ACLNN_ERR_PARAM_INVALID);
  return ACLNN_SUCCESS;
}

aclnnStatus aclnnLog10GetWorkspaceSize(const aclTensor* self, aclTensor* out, uint64_t* workspaceSize,
                                       aclOpExecutor** executor) {
  L2_DFX_PHASE_1(aclnnLog10, DFX_IN(self), DFX_OUT(out));

  // 固定写法，创建OpExecutor
  auto uniqueExecutor = CREATE_EXECUTOR();
  CHECK_RET(uniqueExecutor.get() != nullptr, ACLNN_ERR_INNER_CREATE_EXECUTOR);

  // 固定写法，参数检查
  auto ret = CheckParams(self, out);
  CHECK_RET(ret == ACLNN_SUCCESS, ret);
  
  CheckFormat(self);

  // log算子的空tensor在kernel中支持，对标竞品根据算子实际情况补充
  if (self->IsEmpty()) {
    // 根据实际支持情况补充
    *workspaceSize = 0;
    uniqueExecutor.ReleaseTo(executor);
    return ACLNN_SUCCESS;
  }

  // 固定写法，将输入self转换成连续的tensor
  auto selfContiguous = l0op::Contiguous(self, uniqueExecutor.get());
  CHECK_RET(selfContiguous != nullptr, ACLNN_ERR_INNER_NULLPTR);

  auto logOut = l0op::Log(selfContiguous, LOG_BASE, LOG_SCALE, LOG_SHIFT, uniqueExecutor.get());
  CHECK_RET(logOut != nullptr, ACLNN_ERR_INNER_NULLPTR);

  auto viewCopyResult = l0op::ViewCopy(logOut, out, uniqueExecutor.get());
  CHECK_RET(viewCopyResult != nullptr, ACLNN_ERR_INNER_NULLPTR);

  *workspaceSize = uniqueExecutor->GetWorkspaceSize();
  uniqueExecutor.ReleaseTo(executor);  // 需要把 uniqueExecutor持有executor转移给executor
  return ACLNN_SUCCESS;
}

aclnnStatus aclnnInplaceLog10GetWorkspaceSize(aclTensor* selfRef, uint64_t* workspaceSize, aclOpExecutor** executor) {
  L2_DFX_PHASE_1(aclnnInplaceLog10, DFX_IN(selfRef), DFX_OUT(selfRef));

  auto out = const_cast<aclTensor*>(selfRef);
  auto ret = CheckInplaceParams(selfRef);
  CHECK_RET(ret == ACLNN_SUCCESS, ret);
  return aclnnLog10GetWorkspaceSize(selfRef, out, workspaceSize, executor);
}

aclnnStatus aclnnLog10(void* workspace, uint64_t workspaceSize, aclOpExecutor* executor, aclrtStream stream) {
  L2_DFX_PHASE_2(aclnnLog10);
  // 固定写法，调用框架能力，完成计算
  return CommonOpExecutorRun(workspace, workspaceSize, executor, stream);
}

aclnnStatus aclnnInplaceLog10(void* workspace, uint64_t workspaceSize, aclOpExecutor* executor, aclrtStream stream) {
  L2_DFX_PHASE_2(aclnnInplaceLog10);
  // 固定写法，调用框架能力，完成计算
  return CommonOpExecutorRun(workspace, workspaceSize, executor, stream);
}

#ifdef __cplusplus
}
#endif