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- /**
- * 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_BITWISE_OPS_H_
- #define GE_OP_BITWISE_OPS_H_
-
- #include "graph/operator_reg.h"
-
- namespace ge {
-
- /**
- *@brief Elementwise computes the bitwise right-shift of x and y.
-
- *@par Inputs:
- *The input x can be k-dimensional tensor, num_lower and num_upper can be zero-dimensional scalar. Inputs include: \n
- * @li x:A Tensor. Must be one of the following types: int8, int16, int32, int64, uint8, uint16, uint32, uint64. \n
- * @li y:A Tensor. Must have the same type as x. \n
-
- *@par Outputs:
- *@li z:A Tensor. Has the same type as x. \n
-
- *@attention Constraints:\n
- *-The implementation for Unique on Ascend uses AI CPU, with bad performance. \n
-
- *@par Quantization supported or not
- *Not supported
- *@par Quantized inference supported or not
- *Supported
- *@par L2 convergence supported or not
- *@par Multiple batches supported or not
- */
-
- REG_OP(RightShift)
- .INPUT(x, TensorType({DT_INT8, DT_INT16, DT_INT32, DT_INT64, \
- DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64}))
- .INPUT(y, TensorType({DT_INT8, DT_INT16, DT_INT32, DT_INT64, \
- DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64}))
- .OUTPUT(z, TensorType({DT_INT8, DT_INT16, DT_INT32, DT_INT64, \
- DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64}))
- .OP_END_FACTORY_REG(RightShift)
-
- } // namespace ge
-
- #endif // GE_OP_BITWISE_OPS_H_
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