def save(self, model_name):
load_datasets.print_debug()
print 'Saving the model file '
output = open('LogistRegression' + model_name, 'wb')
pickle.dump(self.W.get_value(borrow=True).T, output, -1)
pickle.dump(self.b.get_value(borrow=True).T, output, -1)
pickle.dump(self.n_in, output, -1)
#pickle.dump(self.n_out,output,-1);
pickle.dump(self.n_classes, output, -1)
output.close()
def save(self,model_name):
load_datasets.print_debug();
print 'Saving the model file ';
output = open('LogistRegression'+model_name, 'wb')
pickle.dump(self.W.get_value(borrow=True).T, output,-1)
pickle.dump(self.b.get_value(borrow=True).T, output,-1)
pickle.dump(self.n_in,output,-1);
#pickle.dump(self.n_out,output,-1);
pickle.dump(self.n_classes,output,-1);
output.close()
def load(self, model_name):
load_datasets.print_debug()
print 'Loading the model file '
pkl_file = open('LogistRegression' + model_name, 'rb')
aa = pickle.load(pkl_file)
self.W.set_value(aa.T, borrow=True)
bb = pickle.load(pkl_file)
self.b.set_value(bb.T, borrow=True)
self.n_out = pickle.load(pkl_file)
self.n_classes = pickle.load(pkl_file)
self.n_out = self.n_classes
self.n_in = np.shape(aa)[1]
def load(self,model_name):
load_datasets.print_debug();
print 'Loading the model file ';
pkl_file = open('LogistRegression'+model_name,'rb')
aa=pickle.load(pkl_file)
self.W.set_value(aa.T,borrow=True);
bb=pickle.load(pkl_file);
self.b.set_value(bb.T,borrow=True);
self.n_out=pickle.load(pkl_file);
self.n_classes=pickle.load(pkl_file);
self.n_out=self.n_classes;
self.n_in=np.shape(aa)[1]
