|
- /**
- * 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_NN_OPS_H_
- #define GE_OP_NN_OPS_H_
-
- #include "graph/operator_reg.h"
- #include "graph/operator.h"
-
- namespace ge {
-
- REG_OP(FractionalMaxPoolGrad)
- .INPUT(orig_input, TensorType({DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64}))
- .INPUT(orig_output, TensorType({DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64}))
- .INPUT(out_backprop, TensorType({DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64}))
- .INPUT(row_pooling_sequence, TensorType({ DT_INT64 }))
- .INPUT(col_pooling_sequence, TensorType({ DT_INT64 }))
- .OUTPUT(y, TensorType({ DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64 }))
- .ATTR(overlapping, Bool, false)
- .OP_END_FACTORY_REG(FractionalMaxPoolGrad)
-
- REG_OP(FractionalAvgPool)
- .INPUT(x, TensorType({DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64}))
- .OUTPUT(y, TensorType({DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64}))
- .OUTPUT(row_pooling_sequence, TensorType({DT_INT64}))
- .OUTPUT(col_pooling_sequence, TensorType({DT_INT64}))
- .ATTR(pooling_ratio, ListFloat, {})
- .ATTR(pseudo_random, Bool, false)
- .ATTR(overlapping, Bool, false)
- .ATTR(deterministic, Bool, false)
- .ATTR(seed, Int, 0)
- .ATTR(seed2, Int, 0)
- .OP_END_FACTORY_REG(FractionalAvgPool)
-
- REG_OP(FractionalMaxPool)
- .INPUT(x, TensorType({DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64}))
- .OUTPUT(y, TensorType({DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64}))
- .OUTPUT(row_pooling_sequence, TensorType({DT_INT64}))
- .OUTPUT(col_pooling_sequence, TensorType({DT_INT64}))
- .ATTR(pooling_ratio, ListFloat, {})
- .ATTR(pseudo_random, Bool, false)
- .ATTR(overlapping, Bool, false)
- .ATTR(deterministic, Bool, false)
- .ATTR(seed, Int, 0)
- .ATTR(seed2, Int, 0)
- .OP_END_FACTORY_REG(FractionalMaxPool)
-
- REG_OP(NthElement)
- .INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16,
- DT_UINT16, DT_UINT8, DT_INT32, DT_INT64, DT_DOUBLE}))
- .INPUT(n, TensorType({DT_INT32}))
- .OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16,
- DT_UINT16, DT_UINT8, DT_INT32, DT_INT64, DT_DOUBLE}))
- .ATTR(reverse, Bool, false)
- .OP_END_FACTORY_REG(NthElement)
-
- REG_OP(FractionalAvgPoolGrad)
- .INPUT(orig_input_tensor_shape, TensorType({DT_INT64}))
- .INPUT(out_backprop, TensorType({DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64}))
- .INPUT(row_pooling_sequence, TensorType({DT_INT64}))
- .INPUT(col_pooling_sequence, TensorType({DT_INT64}))
- .OUTPUT(y, TensorType({DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64}))
- .ATTR(overlapping, Bool, false)
- .OP_END_FACTORY_REG(FractionalAvgPoolGrad)
-
- REG_OP(DataFormatVecPermute)
- .INPUT(x, TensorType({ DT_INT32, DT_INT64 }))
- .OUTPUT(y, TensorType({ DT_INT32, DT_INT64 }))
- .ATTR(src_format, String, "NHWC")
- .ATTR(dst_format, String, "NCHW")
- .OP_END_FACTORY_REG(DataFormatVecPermute)
-
- } // namespace ge
-
- #endif // GE_OP_NN_OPS_H_
|