* 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_proto.h
* \brief
*/
#ifndef OPS_OP_PROTO_INC_DIV_H_
#define OPS_OP_PROTO_INC_DIV_H_
#include "graph/operator_reg.h"
#include "graph/types.h"
namespace ge {
* @brief Returns x1/x2 element-wise. 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, float64, int64, uint16, int16,
* complex32, complex64, complex128, bfloat16, the format can be [NCHW,NHWC,ND].
* @li x2: A ND Tensor. Has the same dtype and format as input "x1". \n
* @par Outputs:
* y: A ND Tensor. Has the same dtype and format as input "x1". \n
* @par Third-party framework compatibility
* Compatible with the TensorFlow operator Div.
*/
REG_OP(Div)
.INPUT(
x1, TensorType(
{DT_FLOAT, DT_FLOAT16, DT_INT8, DT_UINT8, DT_INT32, DT_DOUBLE, DT_INT64, DT_UINT16, DT_INT16,
DT_COMPLEX64, DT_COMPLEX128, DT_BF16, DT_COMPLEX32}))
.INPUT(
x2, TensorType(
{DT_FLOAT, DT_FLOAT16, DT_INT8, DT_UINT8, DT_INT32, DT_DOUBLE, DT_INT64, DT_UINT16, DT_INT16,
DT_COMPLEX64, DT_COMPLEX128, DT_BF16, DT_COMPLEX32}))
.OUTPUT(
y, TensorType(
{DT_FLOAT, DT_FLOAT16, DT_INT8, DT_UINT8, DT_INT32, DT_DOUBLE, DT_INT64, DT_UINT16, DT_INT16,
DT_COMPLEX64, DT_COMPLEX128, DT_BF16, DT_COMPLEX32}))
.OP_END_FACTORY_REG(Div)
}
#endif
