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Paddle/python/paddle/v2/topology.py

125 lines
3.5 KiB

8 years ago
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
# 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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import collections
from paddle.proto.ModelConfig_pb2 import ModelConfig
import layer as v2_layer
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__all__ = ['Topology']
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def __flatten__(lis):
"""
Given a list, possibly nested to any level, return it flattened.
"""
new_lis = []
for item in lis:
if isinstance(item, collections.Sequence):
new_lis.extend(__flatten__(item))
else:
new_lis.append(item)
return new_lis
def __bfs_travel__(callback, *layers):
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layers = __flatten__(layers)
for each_layer in layers:
__break__ = callback(each_layer)
if __break__:
return
__layers__ = each_layer.__parent_layers__.values() + \
each_layer.extra_parent()
__bfs_travel__(callback, *__layers__)
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class Topology(object):
"""
Topology is used to store the information about all layers
and network configs.
"""
def __init__(self, layers, extra_layers=None):
def __check__(layers):
if not isinstance(layers, collections.Sequence):
__check_layer_type__(layers)
layers = [layers]
for layer in layers:
__check_layer_type__(layer)
return layers
layers = __check__(layers)
self.layers = layers
if extra_layers is not None:
extra_layers = __check__(extra_layers)
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:
self.layers.extend(extra_layers)
assert isinstance(self.__model_config__, ModelConfig)
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def proto(self):
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return self.__model_config__
def get_layer(self, name):
"""
get v2.Layer Class instance by layer name
:param name:
:return:
"""
result_layer = [None]
def __impl__(l):
if l.name == name:
result_layer[0] = l
return True # break
return False
__bfs_travel__(__impl__, *self.layers)
if result_layer[0] is None:
raise ValueError("No such layer %s" % name)
return result_layer[0]
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def data_layers(self):
"""
get all data layer
:return:
"""
data_layers = dict()
def __impl__(l):
if isinstance(l, v2_layer.DataLayerV2):
data_layers[l.name] = l
__bfs_travel__(__impl__, *self.layers)
return data_layers
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def data_type(self):
"""
get data_type from proto, such as:
[('image', dense_vector(768)), ('label', integer_value(10))]
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"""
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data_layers = self.data_layers()
return [(nm, data_layers[nm].type)
for nm in self.proto().input_layer_names]
def __check_layer_type__(layer):
if not isinstance(layer, v2_layer.LayerV2):
raise ValueError('layer should have type paddle.layer.Layer')