/** * 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. */ /*! * \file control_flow_ops.h * \brief */ #ifndef OPS_BUILT_IN_OP_PROTO_INC_CONTROL_FLOW_OPS_H_ #define OPS_BUILT_IN_OP_PROTO_INC_CONTROL_FLOW_OPS_H_ #include "graph/operator_reg.h" #include "graph/operator.h" namespace ge { /** *@brief Forwards the value of an available tensor from input "x" to output "y". * Merge waits for at least one of the input tensors to become available. * It is usually combined with Switch to implement branching. * Merge forwards the first tensor to become available to output "y", * and sets "value_index" the index of the tensor in inputs . \n *@par Inputs: *x: The input tensors, one of which will become available. * Must be one of the following types: float16, float32, float64, int8, * int16, int32, int64, uint8, uint16, uint32, uint64, bool . It's a dynamic input. \n *@par Outputs: *@li y: The available tensor. Has the same type as "x". *@li value_index: A scalar of type int32, for the index of the chosen input * tensor . \n *@see Switch() *@par Third-party framework compatibility *@Compatible with the TensorFlow operator Merge. */ 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) /** *@brief Forwards the value of an available tensor from input "x" to output "y". * Merge waits for at least one of the input tensors to become available. * It is usually combined with Switch to implement branching. * Merge forwards the first tensor to become available to output "y", * and sets "value_index" the index of the tensor in inputs . \n *@par Inputs: *x: The input tensors, one of which will become available. * Must be one of the following types: float16, float32, float64, int8, * int16, int32, int64, uint8, uint16, uint32, uint64, bool . It's a dynamic input. \n *@par Outputs: *@li y: The available tensor. Has the same type as "x". *@li value_index: A scalar of type int32, for the index of the chosen input * tensor . \n *@see Switch() | Merge() *@par Third-party framework compatibility *@Compatible with the TensorFlow operator RefMerge. */ 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) /** *@brief Forwards "data" to the output port determined by "pred". * If "pred" is "true", the data input is forwarded to "output_true". * Otherwise, the data is forwarded to "output_false" . \n *@par Inputs: *@li data: The tensor to be forwarded. \ n * Must be one of the following types: float16, float32, float64, * int8, int16, int32, int64, uint8, uint16, uint32, uint64, bool. *@li pred: A boolean scalar. The output port that will receive data . \n *@par Outputs: *@li output_false: If "pred" is "false", data will be forwarded to this output. * Has the same type as "data". *@li output_true: If "pred" is "true", data will be forwarded to this output. * Has the same type as "data" . \n *@see Merge() *@par Third-party framework compatibility *@Compatible with the TensorFlow operator Switch. */ 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) /** *@brief Forwards "data" to the output port determined by "pred". * If "pred" is "true", the data input is forwarded to "output_true". * Otherwise, the data is forwarded to "output_false" . \n *@par Inputs: *@li data: The ref tensor to be forwarded. * Must be one of the following types: float16, float32, float64, * int8, int16, int32, int64, uint8, uint16, uint32, uint64, bool. *@li pred: A boolean scalar. The output port that will receive data . \n *@par Outputs: *@li output_false: If "pred" is "false", data will be forwarded to this output. * Has the same type as "data". *@li output_true: If "pred" is "true", data will be forwarded to this output. * Has the same type as "data" . \n *@see Merge() | Switch() *@par Third-party framework compatibility *@Compatible with the TensorFlow operator RefSwitch. */ 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) /** *@brief Forwards "data" to the output port determined by "pred_value" . \n *@par Inputs: *@li data: The tensor to be forwarded. \ n * Must be one of the following types: float16, float32, float64, * int8, int16, int32, int64, uint8, uint16, uint32, uint64, bool. *@li pred_value: A int64 tensor which determines the output port that will receive data . \n *@par Outputs: *output: The output tensors, one of which will become available. * Has the same type as "data". */ 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) /** *@brief Creates or finds a child frame, and makes "x" available to the child * frame. This op is used together with Exit to create loops in the graph. * The Executor uses the unique "frame_name" to identify frames. * If "is_constant" is "true", output "y" is a constant in the child * frame; otherwise it may be changed in the child frame . \n *@par Inputs: *x: The tensor to be made available to the child frame. * Must be one of the following types: float16, float32, float64, int8, * int16, int32, int64, uint8, uint16, uint32, uint64, bool . \n *@par Attributes: *@li frame_name: A required string. The name of the child frame. *@li is_constant: A required bool. If true, the output is constant in * the child frame . \n *@par Outputs: *y: A Tensor. Has the same type as "x" . \n *@see Exit() *@par Third-party framework compatibility *@Compatible with the TensorFlow operator Enter. */ 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})) .REQUIRED_ATTR(frame_name, String) .REQUIRED_ATTR(is_constant, Bool) .OP_END_FACTORY_REG(Enter) /** *@brief Creates or finds a child frame, and makes "x" available to the child * frame. This op is used together with Exit to create loops in the graph. * The Executor uses the unique "frame_name" to identify frames. * If "is_constant" is "true", output "y" is a constant in the child * frame; otherwise it may be changed in the child frame . \n *@par Inputs: *x: The tensor to be made available to the child frame. * Must be one of the following types: float16, float32, float64, int8, * int16, int32, int64, uint8, uint16, uint32, uint64, bool . \n *@par Attributes: *@li frame_name: A required string. The name of the child frame. *@li is_constant: A required bool. If true, the output is constant in * the child frame . \n *@par Outputs: *y: A tensor. Has the same type as "x" . \n *@see Exit() | Enter() *@par Third-party framework compatibility *@Compatible with the TensorFlow operator RefEnter. */ 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})) .REQUIRED_ATTR(frame_name, String) .REQUIRED_ATTR(is_constant, Bool) .OP_END_FACTORY_REG(RefEnter) /** *@brief Forwards the input to the output. This op represents the loop * termination condition . \n *@par Inputs: *x: A boolean scalar. The condition of the Switch op . \n *@par Outputs: *y: The tensor "x" . \n *@see Switch() *@par Third-party framework compatibility *@Compatible with the TensorFlow operator LoopCond. */ REG_OP(LoopCond) .INPUT(x, TensorType({DT_BOOL})) .OUTPUT(y, TensorType({DT_BOOL})) .OP_END_FACTORY_REG(LoopCond) /** *@brief Makes the input available to the next iteration . \n *@par Inputs: *x: The tensor to be made available to the next iteration. * Must be one of the following types: float16, float32, float64, int8, * int16, int32, int64, uint8, uint16, uint32, uint64, bool . \n *@par Outputs: *y: A Tensor. Has the same type as "x" . \n *@par Third-party framework compatibility *@Compatible with the TensorFlow operator NextIteration. */ 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) /** *@brief Makes the input available to the next iteration . \n *@par Inputs: *x: The tensor to be made available to the next iteration. * Must be one of the following types: float16, float32, float64, int8, * int16, int32, int64, uint8, uint16, uint32, uint64, bool . \n *@par Outputs: *y: A tensor. Has the same type as "x" . \n *@par Third-party framework compatibility *@Compatible with the TensorFlow operator RefNextIteration. */ 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) /** *@brief Exits the current frame to its parent frame . \n *@par Inputs: *x: The tensor to be made available to the parent frame. * Must be one of the following types: float16, float32, float64, int8, * int16, int32, int64, uint8, uint16, uint32, uint64, bool . \n *@par Outputs: *y: A Tensor. Has the same type as "x" . \n *@see Enter() *@par Third-party framework compatibility *@Compatible with the TensorFlow operator Exit. */ 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) /** *@brief Exits the current frame to its parent frame . \n *@par Inputs: *x: The tensor to be made available to the parent frame. * Must be one of the following types: float16, float32, float64, int8, * int16, int32, int64, uint8, uint16, uint32, uint64, bool . \n *@par Outputs: *y: A tensor. Has the same type as "x" . \n *@see Enter() | Exit() *@par Third-party framework compatibility *@Compatible with the TensorFlow operator RefExit. */ 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) /** *@brief Only useful as a placeholder for control edges. * It is similar to a no-op that always produces a live control output * even when some control inputs are dead . \n *@par Third-party framework compatibility *@Compatible with the TensorFlow operator ControlTrigger. */ REG_OP(ControlTrigger) .OP_END_FACTORY_REG(ControlTrigger) /** *@brief Returns index of shape in the map. *@par Inputs: * Three inputs, including: *@li x: One dimensional tensore of type int32, specifying queried shape, max size is 8. *@li data_seq: One dimensional tensore of type int32, specifying the mapped table is queried. *@li level_index: One dimensional tensore of type int32, specifying secondary index. \n *@par Outputs: *@li y: A Tensor with shape [batch, 8], of type int32, specifying index of shape in the map. *@par Third-party framework compatibility * It is a custom operator. It has no corresponding operator in Caffe. */ REG_OP(MapIndex) .INPUT(x, TensorType({DT_INT32})) .INPUT(data_seq, TensorType({DT_INT32})) .OPTIONAL_INPUT(level_index, TensorType({DT_INT32})) .OUTPUT(y, TensorType({DT_INT32})) .OP_END_FACTORY_REG(MapIndex) } // namespace ge #endif // OPS_BUILT_IN_OP_PROTO_INC_CONTROL_FLOW_OPS_H_