def test_dilation(self): self.m12 = DenseMatrix(np.mat([[3,1],[9,2]])) self.m22 = DenseMatrix(np.mat([[4,3],[2,1]])) self.ph2 = DenseMatrix(np.mat([[18,11],[24,7]])) self.row = ["a", "b"] self.ft = ["f1","f2"] self.space1 = Space(DenseMatrix(self.m12), self.row, self.ft) self.space2 = Space(DenseMatrix(self.ph2), ["a_a","a_b"], self.ft) m = Dilation() m.export(self.prefix + ".dil1") m.train([("a","b","a_b")], self.space1, self.space2) m.export(self.prefix + ".dil2")
def test_dilation(self): self.m12 = DenseMatrix(np.mat([[3, 1], [9, 2]])) self.m22 = DenseMatrix(np.mat([[4, 3], [2, 1]])) self.ph2 = DenseMatrix(np.mat([[18, 11], [24, 7]])) self.row = ["a", "b"] self.ft = ["f1", "f2"] self.space1 = Space(DenseMatrix(self.m12), self.row, self.ft) self.space2 = Space(DenseMatrix(self.ph2), ["a_a", "a_b"], self.ft) m = Dilation() m.export(self.prefix + ".dil1") m.train([("a", "b", "a_b")], self.space1, self.space2) m.export(self.prefix + ".dil2")
#------- from composes.utils import io_utils from composes.composition.dilation import Dilation #training data train_data = [("good", "car", "good_car"), ("good", "book", "good_book") ] #load an argument space arg_space = io_utils.load("./data/out/ex10.pkl") #load a phrase space phrase_space = io_utils.load("data/out/PHRASE_SS.ex10.pkl") print "Training phrase space" print phrase_space.id2row print phrase_space.cooccurrence_matrix #train a Dilation model on the data my_comp = Dilation() my_comp.train(train_data, arg_space, phrase_space) #print its parameters print "\nlambda:", my_comp._lambda #use the model to compose the train data composed_space = my_comp.compose([("good", "bike", "good_bike")], arg_space) print "\nComposed space:" print composed_space.id2row print composed_space.cooccurrence_matrix
#ex14.py #------- from composes.utils import io_utils from composes.composition.dilation import Dilation #training data train_data = [("good", "car", "good_car"), ("good", "book", "good_book")] #load an argument space arg_space = io_utils.load("./data/out/ex10.pkl") #load a phrase space phrase_space = io_utils.load("data/out/PHRASE_SS.ex10.pkl") print "Training phrase space" print phrase_space.id2row print phrase_space.cooccurrence_matrix #train a Dilation model on the data my_comp = Dilation() my_comp.train(train_data, arg_space, phrase_space) #print its parameters print "\nlambda:", my_comp._lambda #use the model to compose the train data composed_space = my_comp.compose([("good", "bike", "good_bike")], arg_space) print "\nComposed space:" print composed_space.id2row print composed_space.cooccurrence_matrix