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src/p/y/pylearn2-HEAD/pylearn2/scripts/datasets/make_downsampled_stl10.py   pylearn2(Download)
unlabeled.enable_compression()
unlabeled.use_design_loc(downsampled_dir + '/unlabeled.npy')
serial.save(downsampled_dir+'/unlabeled.pkl',unlabeled)
 
del unlabeled
test.enable_compression()
test.use_design_loc(downsampled_dir + '/test.npy')
serial.save(downsampled_dir+'/test.pkl',test)
del test
 
train.enable_compression()
train.use_design_loc(downsampled_dir + '/train.npy')
serial.save(downsampled_dir+'/train.pkl',train)
 
del train

src/p/y/pylearn2-HEAD/pylearn2/train_extensions/best_params.py   pylearn2(Download)
        if new_cost < self.best_cost:
            self.best_cost = new_cost
            serial.save(self.save_path, model, on_overwrite = 'backup')
 

src/p/y/pylearn2-HEAD/pylearn2/cross_validation/__init__.py   pylearn2(Download)
                if not self.allow_overwrite and os.path.exists(self.save_path):
                    raise IOError("Trying to overwrite file when not allowed.")
                serial.save(self.save_path, models, on_overwrite='backup')
        finally:
            for trainer in self.trainers:

src/p/y/pylearn2-HEAD/pylearn2/train.py   pylearn2(Download)
                    # Make sure that saving does not serialize the dataset
                    self.dataset._serialization_guard = SerializationGuard()
                    serial.save(self.save_path, self.model,
                                on_overwrite='backup')
                finally:

src/p/y/pylearn2-HEAD/pylearn2/scripts/datasets/make_stl10_whitened.py   pylearn2(Download)
print 'Saving the unsupervised data'
data.use_design_loc(output_dir+'/unsupervised.npy')
serial.save(output_dir + '/unsupervised.pkl', data)
 
X = data.X
data.X = unlabeled
data.use_design_loc(output_dir + '/unlabeled.npy')
serial.save(output_dir + '/unlabeled.pkl',data)
del data
del unlabeled
 
print "Saving the labeled train data"
supplement.X = labeled
supplement.use_design_loc(output_dir+'/train.npy')
serial.save(output_dir+'/train.pkl', supplement)
print "Saving the test data"
test.use_design_loc(output_dir+'/test.npy')
serial.save(output_dir+'/test.pkl', test)
 
serial.save(output_dir + '/preprocessor.pkl',preprocessor)

src/p/y/pylearn2-HEAD/pylearn2/scripts/datasets/make_cifar10_whitened.py   pylearn2(Download)
print 'Saving the unsupervised data'
train.use_design_loc(output_dir+'/train.npy')
serial.save(output_dir + '/train.pkl', train)
 
print "Loading the test data"
print "Saving the test data"
test.use_design_loc(output_dir+'/test.npy')
serial.save(output_dir+'/test.pkl', test)
 
serial.save(output_dir + '/preprocessor.pkl',preprocessor)

src/p/y/pylearn2-HEAD/pylearn2/scripts/datasets/make_cifar10_gcn_whitened.py   pylearn2(Download)
print 'Saving the unsupervised data'
train.use_design_loc(output_dir+'/train.npy')
serial.save(output_dir + '/train.pkl', train)
 
print "Loading the test data"
print "Saving the test data"
test.use_design_loc(output_dir+'/test.npy')
serial.save(output_dir+'/test.pkl', test)
 
serial.save(output_dir + '/preprocessor.pkl',preprocessor)

src/p/y/pylearn2-HEAD/pylearn2/scripts/datasets/make_cifar100_whitened.py   pylearn2(Download)
print 'Saving the unsupervised data'
train.use_design_loc(output_dir+'/train.npy')
serial.save(output_dir + '/train.pkl', train)
 
print "Loading the test data"
print "Saving the test data"
test.use_design_loc(output_dir+'/test.npy')
serial.save(output_dir+'/test.pkl', test)
 
serial.save(output_dir + '/preprocessor.pkl',preprocessor)

src/p/y/pylearn2-HEAD/pylearn2/scripts/datasets/make_cifar100_gcn_whitened.py   pylearn2(Download)
print 'Saving the training data'
train.use_design_loc(output_dir+'/train.npy')
serial.save(output_dir + '/train.pkl', train)
 
print "Loading the test data"
print "Saving the test data"
test.use_design_loc(output_dir+'/test.npy')
serial.save(output_dir+'/test.pkl', test)
 
serial.save(output_dir + '/preprocessor.pkl',preprocessor)

src/p/y/pylearn2-HEAD/pylearn2/scripts/datasets/make_stl10_patches_8x8.py   pylearn2(Download)
data.use_design_loc(patch_dir + '/data.npy')
 
serial.save(patch_dir + '/data.pkl',data)
 
serial.save(patch_dir + '/preprocessor.pkl',pipeline)

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