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

149 lines
5.9 KiB

5 years ago
/**
* 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_