fix: paths to dataset with partition not equal to one

Created by: dilyararimovna

hot fix: train file name for case of several train files

deeppavlov/models/evolution/evolution_param_generator.py

@@ -243,8 +243,8 @@ class ParamsEvolution:
             # if several train files:
             if self.train_partition != 1:
                 file_ext = str(Path(next_population[i]["dataset_reader"]["train"]).suffix)
-                next_population[i]["dataset_reader"]["train"] = "_".join(str(Path(next_population[i]["dataset_reader"][
-                                                                                      "train"]).stem.split("_")[:-1])) \
+                next_population[i]["dataset_reader"]["train"] = "_".join(
+                    [str(p) for p in Path(next_population[i]["dataset_reader"]["train"]).stem.split("_")[:-1]])\
                                                                 + "_" + str(iteration % self.train_partition) + file_ext
             try:
                 # re-init learning rate with the final one (works for KerasModel)
@@ -305,9 +305,9 @@ class ParamsEvolution:
             # if several train files
             if self.train_partition != 1:
                 file_ext = str(Path(next_population[i]["dataset_reader"]["train"]).suffix)
-                next_population[i]["dataset_reader"]["train"] = "_".join(str(Path(next_population[i]["dataset_reader"][
-                                                                                  "train"]).stem.split("_")[:-1])) \
-                                                            + "_" + str(iteration % self.train_partition) + file_ext
+                next_population[i]["dataset_reader"]["train"] = "_".join(
+                    [str(p) for p in Path(next_population[i]["dataset_reader"]["train"]).stem.split("_")[:-1]])\
+                                                                + "_" + str(iteration % self.train_partition) + file_ext
             for which_path in ["save_path", "load_path"]:
                 next_population[i] = self.insert_value_or_dict_into_config(
                     next_population[i],