human
2. Register Model for deployment"
Please write code following the instructions in jupyter notebook style.
assistant
#Here is code to 2.

registered_model = client.get_or_create_registered_model(
    name="census", labels=["xgboost", "sklearn"])

hpw_model = model

from verta.registry import VertaModelBase

class CensusTwoStep(VertaModelBase):
    def __init__(self, artifacts):
        import cloudpickle
        self.hpw_model = cloudpickle.load(
            open(artifacts["hpw_model"], "rb"))
        self.income_model = cloudpickle.load(
            open(artifacts["income_model"], "rb"))
        
    def predict(self, batch_input):
        import numpy as np
        results = []
        for one_input in batch_input:
            output = self.hpw_model.predict(one_input)
            output = np.concatenate((np.array(one_input), np.reshape(output, (-1,1))), axis=1)
            output = self.income_model.predict(output)
            results.append(output)
        return results

import cloudpickle
cloudpickle.dump(income_model, open("income_model.pkl", "wb"))
cloudpickle.dump(hpw_model, open("hpw_model.pkl", "wb"))

my_model = CensusTwoStep(
    {
        "hpw_model" : "hpw_model.pkl", 
        "income_model" : "income_model.pkl"
    })

my_model.predict([X_train_hpw.values.tolist()[:5]])

from verta.environment import Python
model_version = registered_model.create_standard_model(
    model_cls=CensusTwoStep,
    environment=Python(requirements=["sklearn", "xgboost"]),
    artifacts={
        "hpw_model" : hpw_model,
        "income_model" : income_model
    },
    name="v6"
)

model_version