* Copyright (c) 2026 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 stateless_random_proto.h
* \brief
*/
#ifndef OPS_BUILT_IN_OP_PROTO_INC_STATELESS_RANDOM_H_
#define OPS_BUILT_IN_OP_PROTO_INC_STATELESS_RANDOM_H_
#include "graph/operator_reg.h"
#include "graph/operator.h"
namespace ge {
* @brief Outputs deterministic pseudorandom random integers from a uniform distribution. \n
* @par Inputs:
* @li shape: 1-D or empty tensor. The shape of the output tensor. Must be one of the following types: int64.
* @li seed: 0-D. seed for the counter-based RNG algorithm. Must be one of the following types: int64.
* @li offset: 0-D. offset for the counter-based RNG algorithm. Must be one of the following types: int64.
* @li from: 0-D scalar. Lower bound of the random range (inclusive). Must be one of the following types: int64.
* @li to: 0-D scalar. Upper bound of the random range (exclusive). Must be one of the following types: int64. \n
* @par Attributes:
* dtype:Output data type. Must be one of the following types: float16, bfloat16, float32, int64, int32,
* int16, int8, uint8, bool. Defaults to int32. \n
* @par Outputs:
* y: Returns Random values with specified shape.
* Must be one of the following types: float16, bfloat16, float32, int64, int32, int16, int8, uint8, bool. \n
* @par Third-party framework compatibility
* Compatible with TensorFlow StatelessRandom operator.
*/
REG_OP(StatelessRandom)
.INPUT(shape, TensorType({DT_INT64}))
.INPUT(seed, TensorType({DT_INT64}))
.INPUT(offset, TensorType({DT_INT64}))
.OPTIONAL_INPUT(from, TensorType({DT_INT64}))
.OPTIONAL_INPUT(to, TensorType({DT_INT64}))
.OUTPUT(y, TensorType({DT_FLOAT, DT_BF16, DT_FLOAT16, DT_INT64, DT_INT32, DT_INT16, DT_INT8, DT_UINT8, DT_BOOL}))
.ATTR(dtype, Type, DT_INT32)
.OP_END_FACTORY_REG(StatelessRandom)
}
#endif
