* 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 apply_momentum_proto.h
* \brief
*/
#ifndef OPS_NN_OPTIM_APPLY_MOMENTUM_PROTO_H
#define OPS_NN_OPTIM_APPLY_MOMENTUM_PROTO_H
#include "graph/operator_reg.h"
#include "graph/types.h"
namespace ge {
*@brief Updates "var" according to the momentum scheme. Set use_nesterov = True if you
* want to use Nesterov momentum. \n
* computing process:
*@code{.c}
* accum = accum * momentum + grad
* if use_nesterov {
* var -= grad * lr + accum * momentum * lr
* } else {
* var -= lr * accum
* }
*@endcode
*
*@par Inputs:
*@li var: A mutable tensor of ND. Must be of dtype float16, float32 or bfloat16.
* Specifying parameters to be updated.
* Should be from a Variable().
*@li accum: A mutable tensor of ND. Must be of the same shape and dtype as "var".
* Specifying gradient accumulation.
* Should be from a Variable().
*@li lr: A scalar. Must be of the same type as "var". Specifying the learning rate.
*@li grad: A tensor of ND. Must be of the same shape and type as "var". Specifying the gradient.
*@li momentum: A scalar. Must be of the same type as "var". Specifying the momentum.
*@par Attributes:
*@li use_nesterov: An optional bool. Defaults to "False".
* If "True", the tensor var will be updated as Nesterov momentum.
*
*@li use_locking: An optional bool. Defaults to "False".
* If "True", updating of the "var" and "accum" tensors is protected by a lock;
* otherwise the behavior is undefined, but may exhibit less contention.
*
*@par Outputs:
* var: A mutable tensor. Has the same shape, dtype and format as input "var".
*
*@par Third-party framework compatibility
*Compatible with the TensorFlow operator ApplyMomentum.
*
*/
REG_OP(ApplyMomentum)
.INPUT(var, TensorType::NumberType())
.INPUT(accum, TensorType::NumberType())
.INPUT(lr, TensorType::NumberType())
.INPUT(grad, TensorType::NumberType())
.INPUT(momentum, TensorType::NumberType())
.OUTPUT(var, TensorType::NumberType())
.ATTR(use_nesterov, Bool, false)
.ATTR(use_locking, Bool, false)
.OP_END_FACTORY_REG(ApplyMomentum)
}
#endif
