Commit d2603183fb96948bdea2aef75d851c6423770e59
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test/test_model.py
... | ... | @@ -5,7 +5,7 @@ from sklearn import cross_validation |
5 | 5 | from ..common import * |
6 | 6 | from ..mdata import CV, ILSVRC, ILSVRC_S |
7 | 7 | from ..mmodel.svm import SVM |
8 | -from ..mmodel.theano import THEANO | |
8 | +from ..mmodel.theano import THEANO | |
9 | 9 | |
10 | 10 | import gzip |
11 | 11 | import cPickle |
... | ... | @@ -14,6 +14,7 @@ import cPickle |
14 | 14 | timer = Timer() |
15 | 15 | package_dir = os.path.dirname(os.path.abspath(__file__)) |
16 | 16 | |
17 | + | |
17 | 18 | def test_SVM_CV(): |
18 | 19 | timer.mark() |
19 | 20 | dcv = CV.DataCV() |
... | ... | @@ -89,7 +90,7 @@ def test_SVM_ILSVRC_HBASE(): |
89 | 90 | X1, Y1 = dil.load_data(mode='local') |
90 | 91 | |
91 | 92 | X_train, X_test, Y_train, Y_test = cross_validation.train_test_split(X, Y, test_size=0.4, random_state=0) |
92 | - print Y,np.sum(np.array(Y)==0),np.sum(np.array(Y)==1) | |
93 | + print Y, np.sum(np.array(Y) == 0), np.sum(np.array(Y) == 1) | |
93 | 94 | print np.array(Y).shape, np.array(X).shape |
94 | 95 | print np.array(X_train).shape, np.array(Y_train).shape |
95 | 96 | print np.array(X_test).shape, np.array(Y_test).shape |
... | ... | @@ -148,9 +149,7 @@ def test_SVM_ILSVRC_S(): |
148 | 149 | # test_SVM_ILSVRC_SPARK() |
149 | 150 | |
150 | 151 | |
151 | - | |
152 | 152 | def test_THEANO_crop(): |
153 | - | |
154 | 153 | timer.mark() |
155 | 154 | dilc = ILSVRC.DataILSVRC(base_dir='/data/hadoop/ImageNet/ILSVRC/ILSVRC2013_DET_val', category='Test_crop_pil') |
156 | 155 | X, Y = dilc.load_data(mode='local', feattype='coef') |
... | ... | @@ -158,11 +157,11 @@ def test_THEANO_crop(): |
158 | 157 | |
159 | 158 | # X_train, X_test, Y_train, Y_test = cross_validation.train_test_split(X, Y, test_size=0.2, random_state=0) |
160 | 159 | # with open(os.path.join(package_dir,'../res/','ils_crop.pkl'),'wb') as f: |
161 | - # cPickle.dump([(X_train,Y_train),(X_test,Y_test)], f) | |
160 | + # cPickle.dump([(X_train,Y_train),(X_test,Y_test)], f) | |
162 | 161 | |
163 | 162 | timer.mark() |
164 | 163 | mtheano = THEANO.ModelTHEANO(toolset='cnn') |
165 | - mtheano._train_cnn(dataset='/data/hadoop/ImageNet/ILSVRC/ILSVRC2013_DET_val/ils_crop.pkl') | |
164 | + mtheano._train_cnn(X, Y) | |
166 | 165 | timer.report() |
167 | 166 | |
168 | 167 | ... | ... |