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大小: 10KB文件類型: .rar金幣: 2下載: 1 次發(fā)布日期: 2021-06-10
- 語言: Python
- 標(biāo)簽: 深度學(xué)習(xí)??
資源簡介
python寫的深度學(xué)習(xí)代碼,包括DBN,SDA等模型,一份不錯的學(xué)習(xí)深度神經(jīng)網(wǎng)絡(luò)以及python的代碼

代碼片段和文件信息
#!/usr/bin/env?python
#?-*-?coding:?utf-8?-*-
‘‘‘
?DBN??w/?continuous-valued?inputs?(Linear?Energy)
?References?:
???-?Y.?Bengio?P.?Lamblin?D.?Popovici?H.?Larochelle:?Greedy?layer-Wise
???Training?of?Deep?Networks?Advances?in?Neural?Information?Processing
???Systems?19?2007
‘‘‘
import?sys
import?numpy
from?Hiddenlayer?import?Hiddenlayer
from?LogisticRegression?import?LogisticRegression
from?RBM?import?RBM
from?CRBM?import?CRBM
from?DBN?import?DBN
from?utils?import?*
?
class?CDBN(DBN):
????def?__init__(self?input=None?label=None\
?????????????????n_ins=2?hidden_layer_sizes=[3?3]?n_outs=2\
?????????????????numpy_rng=None):
????????
????????self.x?=?input
????????self.y?=?label
????????self.sigmoid_layers?=?[]
????????self.rbm_layers?=?[]
????????self.n_layers?=?len(hidden_layer_sizes)??#?=?len(self.rbm_layers)
????????if?numpy_rng?is?None:
????????????numpy_rng?=?numpy.random.RandomState(1234)
????????
????????assert?self.n_layers?>?0
????????#?construct?multi-layer
????????for?i?in?xrange(self.n_layers):
????????????#?layer_size
????????????if?i?==?0:
????????????????input_size?=?n_ins
????????????else:
????????????????input_size?=?hidden_layer_sizes[i?-?1]
????????????#?layer_input
????????????if?i?==?0:
????????????????layer_input?=?self.x
????????????else:
????????????????layer_input?=?self.sigmoid_layers[-1].sample_h_given_v()
????????????????
????????????#?construct?sigmoid_layer
????????????sigmoid_layer?=?Hiddenlayer(input=layer_input
????????????????????????????????????????n_in=input_size
????????????????????????????????????????n_out=hidden_layer_sizes[i]
????????????????????????????????????????numpy_rng=numpy_rng
????????????????????????????????????????activation=sigmoid)
????????????self.sigmoid_layers.append(sigmoid_layer)
????????????#?construct?rbm_layer
????????????if?i?==?0:
????????????????rbm_layer?=?CRBM(input=layer_input?????#?continuous-valued?inputs
?????????????????????????????????n_visible=input_size
?????????????????????????????????n_hidden=hidden_layer_sizes[i]
?????????????????????????????????W=sigmoid_layer.W?????#?W?b?are?shared
?????????????????????????????????hbias=sigmoid_layer.b)
????????????else:
????????????????rbm_layer?=?RBM(input=layer_input
????????????????????????????????n_visible=input_size
????????????????????????????????n_hidden=hidden_layer_sizes[i]
????????????????????????????????W=sigmoid_layer.W?????#?W?b?are?shared
????????????????????????????????hbias=sigmoid_layer.b)
????????????????
????????????self.rbm_layers.append(rbm_layer)
????????#?layer?for?output?using?Logistic?Regression
????????self.log_layer?=?LogisticRegression(input=self.sigmoid_layers[-1].sample_h_given_v()
????????????????????????????????????????????label=self.y
????????????????????????????????????????????n_in=hidden_layer_sizes[-1]
????????????????????????????????????????????n_out=n_outs)
????????#?finetune?cost:?the?negative?log?likelihood?of?the?logistic?regression?layer
????????self.f
?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件???????4286??2013-03-27?08:13??python\CDBN.py
?????文件???????1853??2013-03-27?08:13??python\CRBM.py
?????文件???????4868??2013-03-27?08:13??python\dA.py
?????文件???????5882??2013-03-27?08:13??python\DBN.py
?????文件???????1558??2013-03-27?08:13??python\Hiddenla
?????文件???????2690??2013-03-27?08:13??python\LogisticRegression.py
?????文件???????5113??2013-03-27?08:13??python\RBM.py
?????文件???????5877??2013-03-27?08:13??python\SdA.py
?????文件????????545??2013-03-27?08:13??python\utils.py
?????目錄??????????0??2013-03-27?08:13??python
-----------?---------??----------?-----??----
????????????????32672????????????????????10
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