adapt prophet calls with vectorized=True (#1208)

Author: hrzn

darts/models/forecasting/prophet_model.py

@@ -155,7 +155,7 @@ def _predict(
         predict_df = self._generate_predict_df(n=n, future_covariates=future_covariates)
 
         if num_samples == 1:
-            forecast = self.model.predict(predict_df)["yhat"].values
+            forecast = self.model.predict(predict_df, vectorized=True)["yhat"].values
         else:
             forecast = np.expand_dims(
                 self._stochastic_samples(predict_df, n_samples=num_samples), axis=1
@@ -203,7 +203,7 @@ def _stochastic_samples(self, predict_df, n_samples) -> np.ndarray:
 
         predict_df["trend"] = self.model.predict_trend(predict_df)
 
-        forecast = self.model.sample_posterior_predictive(predict_df)
+        forecast = self.model.sample_posterior_predictive(predict_df, vectorized=True)
 
         # reset default number of uncertainty_samples
         self.model.uncertainty_samples = n_samples_default
@@ -221,7 +221,7 @@ def predict_raw(
 
         predict_df = self._generate_predict_df(n=n, future_covariates=future_covariates)
 
-        return self.model.predict(predict_df)
+        return self.model.predict(predict_df, vectorized=True)
 
     def add_seasonality(
         self,

requirements/core.txt

@@ -8,7 +8,7 @@ nfoursid>=1.0.0
 numpy>=1.19.0
 pandas>=1.0.5
 pmdarima>=1.8.0
-prophet>=1.1
+prophet>=1.1.1
 requests>=2.22.0
 scikit-learn>=1.0.1
 scipy>=1.3.2