/**
 * 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 "greater_equal.h"
#include "opdev/aicpu/aicpu_task.h"
#include "opdev/make_op_executor.h"
#include "opdev/op_def.h"
#include "opdev/op_dfx.h"
#include "opdev/op_executor.h"
#include "opdev/op_log.h"
#include "opdev/shape_utils.h"
#include "op_api/aclnn_check.h"

using namespace op;

namespace l0op {

OP_TYPE_REGISTER(GreaterEqual);

// 仅1971支持DT_BF16
static const std::initializer_list<op::DataType> AICORE_DTYPE_SUPPORT_LIST = {
    op::DataType::DT_FLOAT, op::DataType::DT_INT32,
    op::DataType::DT_FLOAT16, op::DataType::DT_INT8,
    op::DataType::DT_UINT8, op::DataType::DT_BF16,
    op::DataType::DT_INT64};

// 610lite支持类型
static const std::initializer_list<op::DataType> ASCEND610LITE_DTYPE_SUPPORT_LIST = {
    DataType::DT_FLOAT, DataType::DT_FLOAT16, DataType::DT_INT32, op::DataType::DT_INT8,
    op::DataType::DT_UINT8};

// 950支持类型
static const std::initializer_list<op::DataType> REGBASE_DTYPE_SUPPORT_LIST = {
  op::DataType::DT_FLOAT, op::DataType::DT_INT32, op::DataType::DT_FLOAT16, op::DataType::DT_INT8,
  op::DataType::DT_UINT8, op::DataType::DT_BF16, op::DataType::DT_INT64,
  op::DataType::DT_UINT64, op::DataType::DT_BOOL};

// 根据芯片类型、dtype判断算子是否支持走aicore
static inline bool IsAiCoreSupport(const aclTensor *self) {
  auto npuArch = op::GetCurrentPlatformInfo().GetCurNpuArch();
  if (IsRegBase(npuArch)) {
    return CheckType(self->GetDataType(), REGBASE_DTYPE_SUPPORT_LIST);
  }
  if (npuArch == NpuArch::DAV_3102) {
    return CheckType(self->GetDataType(), ASCEND610LITE_DTYPE_SUPPORT_LIST);
  }
  // 只需要判断dtype
  return op::CheckType(self->GetDataType(), AICORE_DTYPE_SUPPORT_LIST);
}

// 判断tensor是否支持非连续
bool IsGreaterEqualSupportNonContiguous(const aclTensor* self) {
  bool isSupportNonContiguous = IsRegBase();
  return isSupportNonContiguous && IsAiCoreSupport(self);
}

const aclTensor *GreaterEqual(const aclTensor *self, const aclTensor *other, aclOpExecutor *executor) {
  L0_DFX(GreaterEqual, self, other);

  op::Shape outShape;
  if (!BroadcastInferShape(self->GetViewShape(), other->GetViewShape(), outShape)) {
    OP_LOGE(ACLNN_ERR_PARAM_INVALID, "InferShape %s and %s failed.", op::ToString(self->GetViewShape()).GetString(),
            op::ToString(other->GetViewShape()).GetString());
    return nullptr;
  }

  auto out = executor->AllocTensor(outShape, op::DataType::DT_BOOL);
  auto ret = ACL_SUCCESS;

  if (IsAiCoreSupport(self)) {
    ret = ADD_TO_LAUNCHER_LIST_AICORE(GreaterEqual, OP_INPUT(self, other), OP_OUTPUT(out));
    OP_CHECK(ret == ACLNN_SUCCESS, OP_LOGE(ACLNN_ERR_INNER_NULLPTR, "GreaterEqual AiCore ADD_TO_LAUNCHER_LIST_AICORE failed."), return nullptr);
  } else {
    static internal::AicpuTaskSpace space("GreaterEqual");
    ret = ADD_TO_LAUNCHER_LIST_AICPU(GreaterEqual, OP_ATTR_NAMES(), OP_INPUT(self, other), OP_OUTPUT(out));
    OP_CHECK(ret == ACLNN_SUCCESS, OP_LOGE(ACLNN_ERR_INNER_NULLPTR, "GreaterEqual AiCPU ADD_TO_LAUNCHER_LIST_AICPU failed."), return nullptr);
  }
  return out;
}
} // l0op