You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
110 lines
3.7 KiB
110 lines
3.7 KiB
# 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.
|
|
|
|
import collections
|
|
|
|
from paddle.trainer_config_helpers.default_decorators import wrap_name_default
|
|
import paddle.trainer_config_helpers as conf_helps
|
|
|
|
|
|
class Layer(object):
|
|
def __init__(self, name=None, parent_layers=None):
|
|
assert isinstance(parent_layers, dict)
|
|
self.name = name
|
|
self.__contex__ = {}
|
|
self.__parent_layers__ = parent_layers
|
|
|
|
def to_proto(self, context):
|
|
"""
|
|
function to set proto attribute
|
|
"""
|
|
kwargs = dict()
|
|
for layer_name in self.__parent_layers__:
|
|
if not isinstance(self.__parent_layers__[layer_name],
|
|
collections.Sequence):
|
|
v1_layer = self.__parent_layers__[layer_name].to_proto(
|
|
context=context)
|
|
else:
|
|
v1_layer = map(lambda x: x.to_proto(context=context),
|
|
self.__parent_layers__[layer_name])
|
|
kwargs[layer_name] = v1_layer
|
|
|
|
if self.context_name() is None:
|
|
return self.to_proto_impl(**kwargs)
|
|
elif self.context_name() not in context:
|
|
context[self.context_name()] = self.to_proto_impl(**kwargs)
|
|
self.__contex__ = context
|
|
if self.use_context_name():
|
|
return context[self.context_name()]
|
|
else:
|
|
return context[self.name]
|
|
|
|
def to_proto_impl(self, **kwargs):
|
|
raise NotImplementedError()
|
|
|
|
def context_name(self):
|
|
"""
|
|
Context name means the context which stores `to_proto_impl` result.
|
|
If multiple layer share same context_name, the `to_proto_impl` of them
|
|
will be invoked only once.
|
|
"""
|
|
return self.name
|
|
|
|
def use_context_name(self):
|
|
return False
|
|
|
|
def calculate_size(self):
|
|
"""
|
|
lazy calculate size of the layer, should be called when to_proto_impl of
|
|
this layer is called.
|
|
:return:
|
|
"""
|
|
return self.__contex__[self.context_name()].size
|
|
|
|
|
|
def __convert_to_v2__(method_name, parent_names, is_default_name=True):
|
|
if is_default_name:
|
|
wrapper = wrap_name_default(name_prefix=method_name)
|
|
else:
|
|
wrapper = None
|
|
|
|
class V2LayerImpl(Layer):
|
|
def __init__(self, **kwargs):
|
|
parent_layers = dict()
|
|
other_kwargs = dict()
|
|
for pname in parent_names:
|
|
if kwargs.has_key(pname):
|
|
parent_layers[pname] = kwargs[pname]
|
|
|
|
for key in kwargs.keys():
|
|
if key not in parent_names:
|
|
other_kwargs[key] = kwargs[key]
|
|
|
|
name = kwargs.get('name', None)
|
|
super(V2LayerImpl, self).__init__(name, parent_layers)
|
|
self.__other_kwargs__ = other_kwargs
|
|
|
|
if wrapper is not None:
|
|
__init__ = wrapper(__init__)
|
|
|
|
def to_proto_impl(self, **kwargs):
|
|
args = dict()
|
|
for each in kwargs:
|
|
args[each] = kwargs[each]
|
|
for each in self.__other_kwargs__:
|
|
args[each] = self.__other_kwargs__[each]
|
|
return getattr(conf_helps, method_name)(**args)
|
|
|
|
return V2LayerImpl
|