Provisory suggestion to generate reproducible seeds for each fold in …

…ModelTrainer.hyperparametrizable
NNPDF · Oct 31, 2023 · 3ce533e · 3ce533e
1 parent 5ef7787
commit 3ce533e
Showing 1 changed file with 2 additions and 1 deletion.
diff --git a/n3fit/src/n3fit/model_trainer.py b/n3fit/src/n3fit/model_trainer.py
@@ -852,7 +852,8 @@ def hyperparametrizable(self, params):
             if k > 0:
                 # seeds = [np.random.randint(0, pow(2, 31)) for _ in seeds]
                 # generate seeds for each k-fold from the input `nnseeds`
-                seeds = [seed * k for seed in seeds]
+                seeds_gerator = [np.random.default_rng(seed=seed) for seed in seeds]
+                seeds = [generator.random() for generator in seeds_gerator]
 
             # Generate the pdf model
             pdf_models = self._generate_pdf(