def test_list_invalid_key(self): lc = LearningCurve(self.fpath) lc.parse() assert_raises(KeyError, lc.list, 'wrong-key', phase=Phase.TRAIN) assert_raises(KeyError, lc.list, 'wrong-key', phase=Phase.TEST) assert_raises(KeyError, lc.list, 'accuracy', phase=Phase.TRAIN)
def test_list_num_iters(self): lc = LearningCurve(self.fpath) lc.parse() x = lc.list('NumIters') dx = np.diff(x) assert_true(np.all(dx > 0))
def test_list_loss_acc(self): lc = LearningCurve(self.fpath) lc.parse() loss = lc.list('loss') acc = lc.list('accuracy') assert_equal(loss.shape, acc.shape) assert_false(np.all(loss == acc))
def test_list(self): lc = LearningCurve(self.fpath) lc.parse() x = lc.list('NumIters') assert_greater(x.size, 0) loss = lc.list('loss') assert_equal(x.shape, loss.shape) acc = lc.list('accuracy') assert_equal(x.shape, acc.shape)
def test_keys_parsed(self): lc = LearningCurve(self.fpath) train_keys, test_keys = lc.parse() assert_list_equal(train_keys, ['NumIters', 'Seconds', 'LearningRate', 'loss']) assert_list_equal( test_keys, ['NumIters', 'Seconds', 'LearningRate', 'accuracy', 'loss'])
def test_keys_parsed(self): lc = LearningCurve(self.fpath) train_keys, test_keys = lc.parse() assert_list_equal(train_keys, ['NumIters', 'Seconds', 'LearningRate', 'loss']) assert_list_equal(test_keys, ['NumIters', 'Seconds', 'LearningRate', 'accuracy', 'loss'])