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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_PAD_OPS_H
- #define GE_OP_PAD_OPS_H
-
- #include "graph/operator_reg.h"
- namespace ge {
-
- /**
- *@brief Creates a tensor filled with a scalar value.
- * This operation creates a tensor of shape "dims" and fills it with "value".
- *
- *@par Inputs:
- *@li dims: A 1D tensor of types int32 or int64. Represents the shape of the output tensor.
-
- *@li value: A 0D scalar. Specifies the value to fill the returned tensor.
- * Must be one of the following types:
- * float16, float32, double, int32, uint8, int16, int8, complex64, int64,
- * qint8, quint8, qint32, uint16, complex128, uint32, uint64.
- *
- *@par Outputs:
- * y: A tensor. Has the same type as "value".
- *
- *@par Third-party framework compatibility
- *@li Compatible with the TensorFlow operator Fill.
- *@li Compatible with the Caffe operator Filler.
- *
- */
- REG_OP(Fill)
- .INPUT(dims, TensorType::IndexNumberType())
- .INPUT(value, TensorType::BasicType())
- .OUTPUT(y, TensorType::BasicType())
- .OP_END_FACTORY_REG(Fill)
-
- /**
- *@brief Creates a tensor filled with a scalar value.
- * This operation creates a tensor of shape "dims" and fills it with "value".
- *
- *@par Inputs:
- * value: A 0D scalar for the value to fill the returned tensor. Must be one of
- * the following types:
- * float16, float32, uint8, int8, int16, int32, int64, quint8, qint8, qint32
- *
- *@par Attributes:
- * dims: A tensor. Must be one of the following types:"int32"
- * 1-D. Represents the shape of the output tensor.
- *
- *@par Outputs:
- * y: A tensor. Has the same type as "value".
- *
- */
- REG_OP(FillD)
- .INPUT(value, 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}))
- .REQUIRED_ATTR(dims, ListInt)
- .OP_END_FACTORY_REG(FillD)
-
- /**
- *@brief Broadcasts an array for a compatible shape.
- * Broadcasting is the process of making arrays to have compatible shapes
- * for arithmetic operations. Two shapes are compatible if for each
- * dimension pair they are either equal or one of them is one. When trying
- * to broadcast a Tensor to a shape, it starts with the trailing dimensions,
- * and works its way forward.
- *
- *@par Inputs:
- *@li x: A tensor.
- *@li shape: A tensor of type int32.
- * A 1D tensor of type int32, for the shape of the desired output.
- *
- *@par Outputs:
- * y: A tensor. Has the same type as "x".
- *
- *@par Third-party framework compatibility
- *Compatible with the TensorFlow operator BroadcastTo.
- *
- */
- REG_OP(BroadcastTo)
- .INPUT(x, TensorType::BasicType())
- .INPUT(shape, TensorType({DT_INT32}))
- .OUTPUT(y, TensorType::BasicType())
- .OP_END_FACTORY_REG(BroadcastTo)
-
- /**
- *@brief Broadcasts an array for a compatible shape.
- * Broadcasting is the process of making arrays to have compatible shapes
- * for arithmetic operations. Two shapes are compatible if for each
- * dimension pair they are either equal or one of them is one. When trying
- * to broadcast a Tensor to a shape, it starts with the trailing dimensions,
- * and works its way forward.
- *
- *@par Inputs:
- * x: A tensor. A tensor to broadcast.
- *
- *@par Attributes:
- * shape: A tensor of type int32.
- * A 1D tensor of type int32, for the shape of the desired output.
- *
- *@par Outputs:
- * y: A tensor. Has the same type as "x".
- *
- *@par Third-party framework compatibility
- *Compatible with the TensorFlow operator BroadcastTo.
- *
- */
- REG_OP(BroadcastToD)
- .INPUT(x, TensorType::BasicType())
- .OUTPUT(y, TensorType::BasicType())
- .REQUIRED_ATTR(shape, ListInt)
- .OP_END_FACTORY_REG(BroadcastToD)
-
- /**
- *@brief Pads a tensor.
-
- *@par Inputs:
- *Two inputs, including:
- * @li x: A Tensor. Must be one of the following types: float16, float32, double, int32,
- * uint8, int16, int8, complex64, int64, qint8, quint8, qint32, qint16, quint16, uint16,
- * complex128, uint32, uint64.
- * @li paddings: A Tensor of type int32 or int64.
-
- *@par Outputs:
- *y: A Tensor of the same type as "x".
-
- *@par Third-party framework compatibility:
- * Compatible with TensorFlow operator Pad.
- */
- REG_OP(Pad)
- .INPUT(x, TensorType::BasicType())
- .INPUT(paddings, TensorType::IndexNumberType())
- .OUTPUT(y, TensorType::BasicType())
- .OP_END_FACTORY_REG(Pad)
-
- /**
- *@brief Pads a tensor.
-
- *@par Inputs:
- *x: A Tensor. Must be one of the following types: float16, float32, int8, uint8, int32.
-
- *@par Attributes:
- *paddings: An optional "vector<vector<int>>". Defaults to "{}".
- * For each dimension D of input, paddings[D, 0] indicates how many
- * values to add before the contents of tensor in that dimension,
- * and paddings[D, 1] indicates how many values to add after the
- * contents of tensor in that dimension.
-
- *@par Outputs:
- *y: A Tensor of the same type as "x".
-
- *@par Third-party framework compatibility:
- * Compatible with TensorFlow operator Pad.
- */
- REG_OP(PadD)
- .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_INT8, DT_UINT8, DT_FLOAT}))
- .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_INT8, DT_UINT8, DT_FLOAT}))
- .REQUIRED_ATTR(paddings, ListListInt)
- .OP_END_FACTORY_REG(PadD)
-
- /**
- *@brief Create a diagonal tensor
-
- *@par Inputs:
- *Two inputs, including:
- * @li x: A mutable Tensor. Must be one of the following types:
- * float16, float32, int32.
-
- * @li assist: A mutable Tensor with rank k is at most 1,
- * Has the same type as "x".
-
- *@par Outputs:
- *y: A mutable Tensor. Has the same type as "x".
-
- *@see Diag()
- *@par Third-party framework compatibility
- * Compatible with the TensorFlow operator Diag.
- */
- REG_OP(DiagD)
- .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_INT32}))
- .INPUT(assist, TensorType({DT_FLOAT16, DT_FLOAT, DT_INT32}))
- .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_INT32}))
- .OP_END_FACTORY_REG(DiagD)
-
- /**
- *@brief Create a diagonal tensor
-
- *@par Inputs:
- *One input, include:
- * x: A mutable Tensor with rank k, where k is at most 1. Must be one of the
- * following types:
- * float16, float32, double, int32, int64, complex64, complex128.
-
- *@par Outputs:
- *y: A mutable Tensor. Has the same type as "x".
-
- *@see DiagD()
- *@par Third-party framework compatibility
- * Compatible with the TensorFlow operator Diag.
- */
- REG_OP(Diag)
- .INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32,
- DT_INT64, DT_COMPLEX64, DT_COMPLEX128}))
- .OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32,
- DT_INT64, DT_COMPLEX64, DT_COMPLEX128}))
- .OP_END_FACTORY_REG(Diag)
-
- /**
- *@brief Ascend Padding, pad the last dimension of input
-
- *@par Inputs:
- *One input, include:
- *x: Tensor which last dimension must be 1. For example: [624000, 1].
-
- *@par Outputs:
- *y: Padding the last dimension of x to padDimSize, [624000, padDimSize].
-
- *@par Third-party framework compatibility
- * Compatible with the TensorFlow operator Diag.
- */
- REG_OP(AscendPadding)
- .INPUT(x, TensorType::BasicType())
- .OUTPUT(y, TensorType::BasicType())
- .ATTR(pad_dim_size, Int, 8)
- .OP_END_FACTORY_REG(AscendPadding)
-
- } // namespace ge
-
- #endif //GE_OP_PAD_OPS_H
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