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125 lines
3.5 KiB
125 lines
3.5 KiB
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import collections
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from paddle.proto.ModelConfig_pb2 import ModelConfig
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import layer as v2_layer
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__all__ = ['Topology']
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def __flatten__(lis):
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"""
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Given a list, possibly nested to any level, return it flattened.
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"""
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new_lis = []
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for item in lis:
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if isinstance(item, collections.Sequence):
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new_lis.extend(__flatten__(item))
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else:
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new_lis.append(item)
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return new_lis
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def __bfs_travel__(callback, *layers):
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layers = __flatten__(layers)
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for each_layer in layers:
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__break__ = callback(each_layer)
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if __break__:
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return
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__layers__ = each_layer.__parent_layers__.values() + \
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each_layer.extra_parent()
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__bfs_travel__(callback, *__layers__)
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class Topology(object):
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"""
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Topology is used to store the information about all layers
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and network configs.
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"""
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def __init__(self, layers, extra_layers=None):
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def __check__(layers):
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if not isinstance(layers, collections.Sequence):
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__check_layer_type__(layers)
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layers = [layers]
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for layer in layers:
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__check_layer_type__(layer)
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return layers
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layers = __check__(layers)
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self.layers = layers
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if extra_layers is not None:
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extra_layers = __check__(extra_layers)
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self.__model_config__ = v2_layer.parse_network(
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layers, extra_layers=extra_layers)
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if extra_layers is not None:
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self.layers.extend(extra_layers)
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assert isinstance(self.__model_config__, ModelConfig)
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def proto(self):
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return self.__model_config__
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def get_layer(self, name):
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"""
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get v2.Layer Class instance by layer name
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:param name:
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:return:
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"""
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result_layer = [None]
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def __impl__(l):
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if l.name == name:
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result_layer[0] = l
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return True # break
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return False
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__bfs_travel__(__impl__, *self.layers)
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if result_layer[0] is None:
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raise ValueError("No such layer %s" % name)
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return result_layer[0]
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def data_layers(self):
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"""
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get all data layer
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:return:
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"""
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data_layers = dict()
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def __impl__(l):
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if isinstance(l, v2_layer.DataLayerV2):
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data_layers[l.name] = l
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__bfs_travel__(__impl__, *self.layers)
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return data_layers
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def data_type(self):
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"""
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get data_type from proto, such as:
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[('image', dense_vector(768)), ('label', integer_value(10))]
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"""
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data_layers = self.data_layers()
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return [(nm, data_layers[nm].type)
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for nm in self.proto().input_layer_names]
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def __check_layer_type__(layer):
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if not isinstance(layer, v2_layer.LayerV2):
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raise ValueError('layer should have type paddle.layer.Layer')
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