* 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 bincount_proto.h
* \brief
*/
#ifndef OPS_OP_PROTO_INC_BINCOUNT_H_
#define OPS_OP_PROTO_INC_BINCOUNT_H_
#include "graph/operator_reg.h"
#include "graph/types.h"
namespace ge {
*@brief Counts the number of occurrences of each value in an integer array.
Outputs a vector with length size and the same dtype as weights. If weights
are empty, then index i stores the number of times the value i is counted in
arr. If weights are non-empty, then index i stores the sum of the value in
weights at each index.
*@par Inputs:
*The input size must be a non-negative int32 scalar Tensor. Inputs include:
*@li array:1D Tensor for each value in the range [0, 2147483647).
*@li size:non-negative int32 scalar Tensor.
*@li weights: is an int32, int64, float32, or double Tensor with the same
shape as arr, or a length-0 Tensor, in which case it acts as all weights
equal to 1. \n
*@par Outputs:
*bins:1D Tensor with length equal to size. The counts or summed weights for
each value in the range [0, size). \n
*@par Third-party framework compatibility
*Compatible with tensorflow Bincount operator.
*/
REG_OP(Bincount)
.INPUT(array, TensorType(DT_INT32))
.INPUT(size, TensorType(DT_INT32))
.INPUT(weights, TensorType({DT_FLOAT, DT_INT32, DT_INT64, DT_DOUBLE}))
.OUTPUT(bins, TensorType({DT_FLOAT, DT_INT32, DT_INT64, DT_DOUBLE}))
.OP_END_FACTORY_REG(Bincount)
}
#endif
