def do1DTest(self, trainable, train_X, train_y, test_X, test_y):
#Test for 1-D array as input to the transformers
train_X = train_X[:,0]
test_X = test_X[:,0]
trainable_pipeline = (trainable & NoOp()) >> ConcatFeatures() >> float32_transform() >> LR()
trained_pipeline = trainable_pipeline.fit(train_X, train_y)
trained_pipeline.predict(test_X)
hyperopt = Hyperopt(estimator=trainable_pipeline, max_evals=1)
trained_hyperopt = hyperopt.fit(train_X, train_y)
trained_hyperopt.predict(test_X)
def doTest(self, trainable, train_X, train_y, test_X, test_y):
trained = trainable.fit(train_X, train_y)
transformed = trained.transform(test_X)
with self.assertWarns(DeprecationWarning):
trainable.transform(train_X)
trainable.to_json()
trainable_pipeline = trainable >> float32_transform() >> LR()
trained_pipeline = trainable_pipeline.fit(train_X, train_y)
trained_pipeline.predict(test_X)
hyperopt = Hyperopt(estimator=trainable_pipeline, max_evals=1)
trained_hyperopt = hyperopt.fit(train_X, train_y)
trained_hyperopt.predict(test_X)
