* 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.
*/
* \file div_no_nan_proto.h
* \brief
*/
#ifndef OPS_OP_PROTO_INC_DIV_NO_NAN_H_
#define OPS_OP_PROTO_INC_DIV_NO_NAN_H_
#include "graph/operator_reg.h"
#include "graph/types.h"
namespace ge {
*@brief Returns 0 if the denominator is zero, else, like Div. Support broadcasting operations.
*@par Inputs:
* Two inputs, including:
*@li x1: A ND Tensor. Must be one of the following types:float16, float32, int32,
* int8, uint8, double, bfloat16.
*@li x2: A ND Tensor which has the same dtype as "x1". The shapes of "x1", "x2",
* and "y" must comply with the broadcast rule. \n
*@par Outputs:
*y: A ND Tensor which has the same dtype as "x1".The shapes of "x1", "x2",
*and "y" must comply with the broadcast rule. \n
*@par Third-party framework compatibility
* Compatible with the TensorFlow operator DivNoNan.
*/
REG_OP(DivNoNan)
.INPUT(x1, TensorType({DT_FLOAT, DT_UINT8, DT_INT8, DT_INT32, DT_FLOAT16, DT_DOUBLE, DT_BF16}))
.INPUT(x2, TensorType({DT_FLOAT, DT_UINT8, DT_INT8, DT_INT32, DT_FLOAT16, DT_DOUBLE, DT_BF16}))
.OUTPUT(y, TensorType({DT_FLOAT, DT_UINT8, DT_INT8, DT_INT32, DT_FLOAT16, DT_DOUBLE, DT_BF16}))
.OP_END_FACTORY_REG(DivNoNan)
}
#endif
