Fitting pmdarima auto_arima to time series with missing values

I have some time series data at weekly granularity, but some weeks have NaN values.

The pmdarima auto_arima documentation says that the input time series data should not contain any np.nan or np.inf values.

It looks like the R ARIMA package allows you to fit time series with missing values: https://stats.stackexchange.com/questions/346225/fitting-arima-to-time-series-with-missing-values

So, without having to use imputed values in my training data, what are my options if I want to use auto_arima on my time series data?

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