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178 lines
6.8 KiB
178 lines
6.8 KiB
/**
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* Copyright 2019-2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef GE_OP_SET_OPS_H_
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#define GE_OP_SET_OPS_H_
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#include "graph/operator.h"
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#include "graph/operator_reg.h"
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namespace ge {
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/**
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*@brief Applies set operation along last dimension of 2 Tensor inputs.
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*@par Inputs:
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*Inputs include: \n
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* @li x1: A Tensor. Must be one of the following types: int8, int16, int32, int64, uint8, uint16, string.
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* @li x2: A Tensor. Must have the same type as x1.
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*@par Attributes:
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*@li set_operation: A string.
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*@li validate_indices: An optional bool. Defaults to True.
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*@par Outputs:
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*@li y_indices: A Tensor of type int64.
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*@li y_values: A Tensor. Has the same type as x1.
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*@li y_shape: A Tensor of type int64.
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*@attention Constraints:\n
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*-The implementation for DenseToDenseSetOperation on Ascend uses AICPU, with bad performance.\n
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*@par Third-party framework compatibility
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*@li compatible with tensorflow DenseToDenseSetOperation operator.
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*/
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REG_OP(DenseToDenseSetOperation)
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.INPUT(x1, TensorType({DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, \
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DT_INT32, DT_INT64, DT_STRING}))
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.INPUT(x2, TensorType({DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, \
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DT_INT32, DT_INT64, DT_STRING}))
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.OUTPUT(y_indices, TensorType({DT_INT64}))
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.OUTPUT(y_values, TensorType({DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, \
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DT_INT32, DT_INT64, DT_STRING}))
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.OUTPUT(y_shape, TensorType({DT_INT64}))
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.ATTR(set_operation, String, "")
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.ATTR(validate_indices, Bool, true)
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.OP_END_FACTORY_REG(DenseToDenseSetOperation)
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/**
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*@brief Applies set operation along last dimension of Tensor and SparseTensor.
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*@par Inputs:
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*Inputs include: \n
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* @li x1: A Tensor. Must be one of the following types: int8, int16, int32, int64, uint8, uint16, string.
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* @li x2_indices: A Tensor of type int64. 2D Tensor, indices of a SparseTensor.
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* @li x2_values: A Tensor. Must have the same type as set1. 1D Tensor, values of a SparseTensor.
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* @li x2_shape: A Tensor of type int64. 1D Tensor, shape of a SparseTensor.
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*@par Attributes:
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*@li set_operation: A string.
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*@li validate_indices: An optional bool. Defaults to True.
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*@par Outputs:
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*@li y_indices: A Tensor of type int64.
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*@li y_values: A Tensor. Has the same type as x1.
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*@li y_shape: A Tensor of type int64.
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*@attention Constraints:\n
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*-The implementation for DenseToSparseSetOperation on Ascend uses AICPU, with bad performance.\n
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*@par Third-party framework compatibility
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*@li compatible with tensorflow DenseToSparseSetOperation operator.
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*/
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REG_OP(DenseToSparseSetOperation)
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.INPUT(x1, TensorType({DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, \
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DT_INT32, DT_INT64, DT_STRING}))
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.INPUT(x2_indices, TensorType({DT_INT64}))
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.INPUT(x2_values, TensorType({DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, \
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DT_INT32, DT_INT64, DT_STRING}))
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.INPUT(x2_shape, TensorType({DT_INT64}))
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.OUTPUT(y_indices, TensorType({DT_INT64}))
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.OUTPUT(y_values, TensorType({DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, \
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DT_INT32, DT_INT64, DT_STRING}))
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.OUTPUT(y_shape, TensorType({DT_INT64}))
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.ATTR(set_operation, String, "")
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.ATTR(validate_indices, Bool, true)
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.OP_END_FACTORY_REG(DenseToSparseSetOperation)
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/**
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*@brief Applies set operation along last dimension of 2 SparseTensor inputs.
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*@par Inputs:
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*Inputs include: \n
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* @li x1_indices: A Tensor of type int64. 2D Tensor, indices of a SparseTensor.
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* @li x1_values: A Tensor. Must be one of the following types: int8, int16, \n
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int32, int64, uint8, uint16, string. 1D Tensor, values of a SparseTensor.
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* @li x1_shape: A Tensor of type int64. 1D Tensor, shape of a SparseTensor.
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* @li x2_indices: A Tensor of type int64. 2D Tensor, indices of a SparseTensor.
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* @li x2_values: A Tensor. Must have the same type as set1_values. 1D Tensor, values of a SparseTensor.
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* @li x2_shape: A Tensor of type int64. 1D Tensor, shape of a SparseTensor.
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*@par Attributes:
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*@li set_operation: A string.
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*@li validate_indices: An optional bool. Defaults to True.
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*@par Outputs:
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*@li y_indices: A Tensor of type int64.
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*@li y_values: A Tensor. Has the same type as x1_values.
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*@li y_shape: A Tensor of type int64.
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*@attention Constraints:\n
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*-The implementation for SparseToSparseSetOperation on Ascend uses AICPU, with bad performance.\n
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*@par Third-party framework compatibility
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*@li compatible with tensorflow SparseToSparseSetOperation operator.
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*/
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REG_OP(SparseToSparseSetOperation)
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.INPUT(x1_indices, TensorType({DT_INT64}))
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.INPUT(x1_values, TensorType({DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, \
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DT_INT32, DT_INT64, DT_STRING}))
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.INPUT(x1_shape, TensorType({DT_INT64}))
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.INPUT(x2_indices, TensorType({DT_INT64}))
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.INPUT(x2_values, TensorType({DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, \
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DT_INT32, DT_INT64, DT_STRING}))
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.INPUT(x2_shape, TensorType({DT_INT64}))
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.OUTPUT(y_indices, TensorType({DT_INT64}))
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.OUTPUT(y_values, TensorType({DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, \
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DT_INT32, DT_INT64, DT_STRING}))
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.OUTPUT(y_shape, TensorType({DT_INT64}))
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.ATTR(set_operation, String, "")
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.ATTR(validate_indices, Bool, true)
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.OP_END_FACTORY_REG(SparseToSparseSetOperation)
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/**
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*@brief Number of unique elements along last dimension of input set.
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*@par Inputs:
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*Inputs include: \n
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* @li set_indices: A Tensor of type int64. 2D Tensor, indices of a SparseTensor.
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* @li set_values: A Tensor. Must be one of the following types: int8, int16, int32, int64, uint8, uint16.
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* @li set_shape: A Tensor of type int64. 1D Tensor, shape of a SparseTensor.
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*@par Attributes:
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*validate_indices: An optional bool. Defaults to True.
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*@par Outputs:
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*size: A Tensor of type int32.
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*@attention Constraints:\n
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*-The implementation for SetSize on Ascend uses AICPU, with bad performance.\n
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*@par Third-party framework compatibility
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*@li compatible with tensorflow SetSize operator.
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*/
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REG_OP(SetSize)
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.INPUT(set_indices, TensorType({DT_INT64}))
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.INPUT(set_values, TensorType({DT_INT8, DT_INT16, \
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DT_UINT8, DT_UINT16, DT_INT32, DT_INT64, DT_STRING}))
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.INPUT(set_shape, TensorType({DT_INT64}))
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.OUTPUT(size, TensorType({DT_INT32}))
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.ATTR(validate_indices, Bool, true)
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.OP_END_FACTORY_REG(SetSize)
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} // namespace ge
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#endif // GE_OP_SET_OPS_H_
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