#
# 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.
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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
[docs]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)