* 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 concat_d_proto.h
* \brief
*/
#ifndef OPS_OP_PROTO_INC_CONCAT_D_PROTO_H_
#define OPS_OP_PROTO_INC_CONCAT_D_PROTO_H_
#include "graph/operator_reg.h"
namespace ge {
* @brief Concatenates tensors along one dimension .
* @par Inputs:
* One input:
* x: Dynamic input. A ND Tensor.
* Must be one of the following types: bfloat16, float16, float32, int32,
* int8, int16, int64, uint8, uint16, uint32, uint64, bool, double, complex64,
HIFLOAT8, FLOAT8_E5M2, FLOAT8_E4M3FN, FLOAT8_E8M0. \n
* @par Attributes:
* @li concat_dim: A required int8, int16, int32, or int64.
Specifies the dimension along which to concatenate.
No default value.
* @li N: An optional int8, int16, int32, or int64.
Specifies the number of elements in "x". Defaults to "1". \n
* @par Outputs:
* y: A Tensor. Has the same type and format as "x" . \n
* @attention Constraints:
* @li "x" is a list of at least 2 "tensor" objects of the same type.
* @li "concat_dim" is in the range [-len(x.shape), len(x.shape)] . \n
* @par Third-party framework compatibility
* Compatible with the TensorFlow operator Concat.
* @par Restrictions:
* Warning: THIS FUNCTION IS DEPRECATED. Please use Concat instead.
*/
REG_OP(ConcatD)
.DYNAMIC_INPUT(x, TensorType({DT_BF16, DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_BOOL, DT_INT32, DT_INT64,
DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64, DT_DOUBLE, DT_COMPLEX64, DT_FLOAT8_E4M3FN,
DT_FLOAT8_E5M2, DT_HIFLOAT8, DT_FLOAT8_E8M0}))
.OUTPUT(y, TensorType({DT_BF16, DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_BOOL, DT_INT32, DT_INT64,
DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64, DT_DOUBLE, DT_COMPLEX64, DT_FLOAT8_E4M3FN,
DT_FLOAT8_E5M2, DT_HIFLOAT8, DT_FLOAT8_E8M0}))
.REQUIRED_ATTR(concat_dim, Int)
.ATTR(N, Int, 1)
.OP_END_FACTORY_REG(ConcatD)
}
#endif
