text: /**
   * 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_
  