text: #
  # Copyright 2018 Analytics Zoo Authors.
  #
  # 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.
  #
  from zoo.pipeline.api.onnx.mapper.operator_mapper import OperatorMapper
  import zoo.pipeline.api.keras.layers as zlayers
  import zoo.pipeline.api.autograd as zautograd
  import bigdl.nn.layer as blayer
  
  
  class GatherMapper(OperatorMapper):
      def __init__(self, node, initializer, _all_tensors):
          super(GatherMapper, self).__init__(node, initializer, _all_tensors)
  
      def _extract_model_inputs(self):
          return [self._to_zoo_input(i) for i in self._input_list]
  
      def _to_tensor(self):
          data = self.model_inputs[0].zvalue
          indices = self.model_inputs[1].zvalue
  
          if self._initializer and isinstance(data, zautograd.Parameter):
              embedding = zlayers.Embedding(input_dim=data.shape[0],
                                            output_dim=data.shape[1],
                                            weights=data.get_weight(),
                                            input_length=indices.shape[1])
              return embedding(indices)
          else:
              dim = int(self.onnx_attr['axis'])
              assert dim >= 1, "Currently only dim>=1 is supported."
              assert indices.shape == (1,), "Currently only one index is supported."
              index = int(indices.get_weight().max())
              return zautograd.expand_dims(data.index_select(dim=dim, index=index), axis=dim)
  