graphengine/third_party/fwkacllib/inc/ops/math_ops.h

/**
 * Copyright 2019-2020 Huawei Technologies Co., Ltd
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#ifndef GE_OP_MATH_OPS_H_
#define GE_OP_MATH_OPS_H_

#include "graph/operator_reg.h"
#include "graph/operator.h"

namespace ge {

REG_OP(Igamma)
    .INPUT(a, TensorType({DT_FLOAT, DT_DOUBLE}))
    .INPUT(x, TensorType({DT_FLOAT, DT_DOUBLE}))
    .OUTPUT(z, TensorType({DT_FLOAT, DT_DOUBLE}))
    .OP_END_FACTORY_REG(Igamma)

REG_OP(Igammac)
    .INPUT(a, TensorType({DT_FLOAT, DT_DOUBLE}))
    .INPUT(x, TensorType({DT_FLOAT, DT_DOUBLE}))
    .OUTPUT(z, TensorType({DT_FLOAT, DT_DOUBLE}))
    .OP_END_FACTORY_REG(Igammac)

REG_OP(CompareAndBitpack)
    .INPUT(x, TensorType({ DT_FLOAT, DT_FLOAT16, DT_DOUBLE, DT_INT8, \
        DT_INT16, DT_INT32, DT_INT64, DT_BOOL }))
    .INPUT(threshold, TensorType({ DT_FLOAT, DT_FLOAT16, DT_DOUBLE, \
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_BOOL }))
    .OUTPUT(y, TensorType(DT_UINT8))
    .OP_END_FACTORY_REG(CompareAndBitpack)

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)

REG_OP(Betainc)
    .INPUT(a, TensorType({DT_DOUBLE, DT_FLOAT}))
    .INPUT(b, TensorType({DT_DOUBLE, DT_FLOAT}))
    .INPUT(x, TensorType({DT_DOUBLE, DT_FLOAT}))
    .OUTPUT(z, TensorType({DT_DOUBLE, DT_FLOAT}))
    .OP_END_FACTORY_REG(Betainc)

REG_OP(Zeta)
    .INPUT(x, TensorType({DT_DOUBLE, DT_FLOAT}))
    .INPUT(q, TensorType({DT_DOUBLE, DT_FLOAT}))
    .OUTPUT(z, TensorType({DT_DOUBLE, DT_FLOAT}))
    .OP_END_FACTORY_REG(Zeta)

REG_OP(Bucketize)
    .INPUT(x, TensorType({DT_INT32, DT_INT64, DT_DOUBLE, DT_FLOAT}))
    .OUTPUT(y, TensorType({DT_INT32}))
    .REQUIRED_ATTR(boundaries, ListFloat)
    .OP_END_FACTORY_REG(Bucketize)

REG_OP(SparseSegmentSum)
    .INPUT(x, TensorType({DT_INT8, DT_UINT8, DT_INT16, DT_UINT16,
        DT_INT32, DT_INT64, DT_DOUBLE, DT_FLOAT, DT_FLOAT16}))
    .INPUT(indices, TensorType({DT_INT32}))
    .INPUT(segment_ids, TensorType({DT_INT32}))
    .OUTPUT(y, TensorType({DT_INT8, DT_UINT8, DT_INT16, DT_UINT16,
        DT_INT32, DT_INT64, DT_DOUBLE, DT_FLOAT, DT_FLOAT16}))
    .OP_END_FACTORY_REG(SparseSegmentSum)

REG_OP(SparseSegmentMean)
    .INPUT(x, TensorType({DT_FLOAT, DT_DOUBLE}))
    .INPUT(indices, TensorType({DT_INT32}))
    .INPUT(segment_ids, TensorType({DT_INT32}))
    .OUTPUT(y, TensorType({DT_FLOAT, DT_DOUBLE}))
    .OP_END_FACTORY_REG(SparseSegmentMean)

REG_OP(SparseSegmentMeanGrad)
    .INPUT(x, TensorType({DT_FLOAT, DT_DOUBLE}))
    .INPUT(indices, TensorType({DT_INT32}))
    .INPUT(segment_ids, TensorType({DT_INT32}))
    .INPUT(output_dim0, TensorType({DT_INT32}))
    .OUTPUT(y, TensorType({DT_FLOAT, DT_DOUBLE}))
    .OP_END_FACTORY_REG(SparseSegmentMeanGrad)

REG_OP(IgammaGradA)
    .INPUT(a, TensorType({DT_FLOAT, DT_DOUBLE}))
    .INPUT(x, TensorType({DT_FLOAT, DT_DOUBLE}))
    .OUTPUT(z, TensorType({DT_FLOAT, DT_DOUBLE}))
    .OP_END_FACTORY_REG(IgammaGradA)

REG_OP(InitData)
    .ATTR(channel_name, String, "")
    .OP_END_FACTORY_REG(InitData)

REG_OP(GetNext)
    .DYNAMIC_OUTPUT(y, TensorType({DT_INT8, DT_UINT8, DT_INT16, DT_UINT16, DT_INT32, DT_INT64, DT_UINT32, DT_UINT64,
                                        DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_BOOL}))
    .ATTR(output_types, ListInt, {})
    .ATTR(output_shapes, ListListInt, {})
    .ATTR(output_num, Int, 1)
    .ATTR(channel_name, String, "")
    .OP_END_FACTORY_REG(GetNext)
}  // namespace ge

#endif  // GE_OP_MATH_OPS_H_