You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
graphengine/third_party/fwkacllib/inc/ops/state_ops.h

164 lines
5.4 KiB

/**
* 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_STATE_OPS_H_
#define GE_OP_STATE_OPS_H_
#include "graph/operator_reg.h"
namespace ge {
/**
*@brief Creates a variable tensor.
*@par Inputs:
*x: A tensor, used to assign a value to the variable tensor internally. \n
The caller does not need to pass the value of the variable tensor.
*@par Attributes:
*@li index: An integer. Index of the input tensor.
*@li value: A tensor, used to pass and record the value of the variable tensor.
*@li container: A string. The container of the variable tensor.
*@li shared_name: A string. The shared name of the variable tensor.
*@par Outputs:
*y: The created variable tensor.
*@par Third-party framework compatibility
*Compatible with the TensorFlow operator Variable.
*/
REG_OP(Variable)
.INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT16, \
DT_UINT8, DT_INT32, DT_INT64, DT_UINT32, DT_UINT64, DT_BOOL, DT_DOUBLE}))
.OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT16, \
DT_UINT8, DT_INT32, DT_INT64, DT_UINT32, DT_UINT64, DT_BOOL, DT_DOUBLE}))
.ATTR(index, Int, 0)
.ATTR(value, Tensor, Tensor())
.ATTR(container, String, "")
.ATTR(shared_name, String, "")
.OP_END_FACTORY_REG(Variable)
/**
*@brief Returns a temporary variable tensor. After the use of TemporaryVariable, \n
pass the reference to the variable tensor to the matching DestroyTemporaryVariable op for destruction.
*@par Attributes:
*@li shape: A required list of int32 or int64. The shape of the variable tensor.
*@li dtype: Required. The type of elements in the variable tensor.
*@li var_name: An optional string. The name of the variable to be created.
*@par Outputs:
*y: The created variable tensor.
*@par Third-party framework compatibility
*Compatible with the TensorFlow operator TemporaryVariable.
*/
REG_OP(TemporaryVariable)
.OUTPUT(y, TensorType::ALL())
.REQUIRED_ATTR(shape, ListInt)
.REQUIRED_ATTR(dtype, Int)
.ATTR(var_name, String, "")
.OP_END_FACTORY_REG(TemporaryVariable)
/**
*@brief Destroys the temporary variable and returns its final value. \n
All other uses of the temporary variable must have been executed before this op.
*@par Inputs:
*x: A reference to the temporary variable tensor.
*@par Attributes:
*var_name: A required string. Name of the temporary variable. \n
Must be the same as the "var_name" attribute of the reference to the temporary variable tensor.
*@par Outputs:
*y: Final value of the reference to the temporary variable tensor.
*@par Third-party framework compatibility
*Compatible with the TensorFlow operator DestroyTemporaryVariable.
*/
REG_OP(DestroyTemporaryVariable)
.INPUT(x, TensorType::ALL())
.OUTPUT(y, TensorType::ALL())
.ATTR(var_name, String, "")
.OP_END_FACTORY_REG(DestroyTemporaryVariable)
/**
*@brief Checks whether a tensor has been initialized. Outputs boolean scalar indicating whether the tensor has been initialized.
*@par Inputs:
*x: A tensor.
*@par Outputs:
*y: A tensor, indicating whether "x" has been initialized.
*@par Third-party framework compatibility
*Compatible with the TensorFlow operator IsVariableInitialized.
*/
REG_OP(IsVariableInitialized)
.INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT16, DT_UINT8,
DT_INT32, DT_INT64, DT_UINT32, DT_UINT64, DT_BOOL, DT_DOUBLE}))
.OUTPUT(y, TensorType({DT_BOOL}))
.OP_END_FACTORY_REG(IsVariableInitialized)
/**
*@brief Checks whether a tensor has been initialized. Outputs boolean scalar indicating whether the tensor has been initialized.
*@par Inputs:
*x: A tensor.
*@par Outputs:
*y: A tensor, indicating whether "x" has been initialized, and the data type is boolean.
*@par Third-party framework compatibility
*Compatible with the TensorFlow operator VarIsInitializedOp.
*/
REG_OP(VarIsInitializedOp)
.INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT16, DT_UINT8,
DT_INT32, DT_INT64, DT_UINT32, DT_UINT64, DT_BOOL, DT_DOUBLE}))
.OUTPUT(y, TensorType({DT_BOOL}))
.OP_END_FACTORY_REG(VarIsInitializedOp)
/**
*@brief Increments 'ref' until it reaches 'limit'.
*@par Inputs:
*Inputs include: \n
*ref: A mutable Tensor. Must be one of the following types: int32, int64.
*@par Attributes:
*limit: An int. If incrementing ref would bring it above limit, instead \n
generates an 'OutOfRange' error.
*@par Outputs:
*y: A Tensor. Has the same type as ref.
*@attention Constraints:\n
*-The implementation for CountUpTo on Ascend uses AICPU, with bad performance.\n
*@par Third-party framework compatibility
*@li compatible with tensorflow CountUpTo operator.
*/
REG_OP(CountUpTo)
.INPUT(ref, TensorType({DT_INT32, DT_INT64}))
.OUTPUT(y, TensorType({DT_INT32, DT_INT64}))
.ATTR(limit, Int, 0)
.OP_END_FACTORY_REG(CountUpTo)
} // namespace ge
#endif // GE_OP_STATE_OPS_H_