control_flow_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_CONTROL_FLOW_OPS_H_
#define GE_CONTROL_FLOW_OPS_H_

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

namespace ge {

REG_OP(Merge)
    .DYNAMIC_INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(value_index, TensorType({DT_INT32}))
    .OP_END_FACTORY_REG(Merge)

REG_OP(RefMerge)
    .DYNAMIC_INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(value_index, TensorType({DT_INT32}))
    .OP_END_FACTORY_REG(RefMerge)

REG_OP(Switch)
    .INPUT(data, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .INPUT(pred, TensorType({DT_BOOL}))
    .OUTPUT(output_false, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(output_true, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OP_END_FACTORY_REG(Switch)

REG_OP(RefSwitch)
    .INPUT(data, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .INPUT(pred, TensorType({DT_BOOL}))
    .OUTPUT(output_false, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(output_true, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OP_END_FACTORY_REG(RefSwitch)

REG_OP(SwitchN)
    .INPUT(data, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .INPUT(pred_value, TensorType({DT_INT64}))
    .DYNAMIC_OUTPUT(output, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OP_END_FACTORY_REG(SwitchN)

REG_OP(Enter)
    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .ATTR(frame_name, String, "")
    .ATTR(is_constant, Bool, false)
    .OP_END_FACTORY_REG(Enter)

REG_OP(RefEnter)
    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .ATTR(frame_name, String, "")
    .ATTR(is_constant, Bool, false)
    .OP_END_FACTORY_REG(RefEnter)

REG_OP(LoopCond)
    .INPUT(x, TensorType({DT_BOOL}))
    .OUTPUT(y, TensorType({DT_BOOL}))
    .OP_END_FACTORY_REG(LoopCond)

REG_OP(NextIteration)
    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OP_END_FACTORY_REG(NextIteration)

REG_OP(RefNextIteration)
    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OP_END_FACTORY_REG(RefNextIteration)

REG_OP(Exit)
    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OP_END_FACTORY_REG(Exit)

REG_OP(RefExit)
    .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE,
        DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32,
        DT_UINT64, DT_BOOL}))
    .OP_END_FACTORY_REG(RefExit)

REG_OP(ControlTrigger)
    .OP_END_FACTORY_REG(ControlTrigger)
}  // namespace ge

#endif  // GE_CONTROL_FLOW_OPS_H_