Revert "fixing the code"

This reverts commit b5e9c8d.

flood_forecast/evaluator.py

@@ -157,7 +157,7 @@ def evaluate_model(
                 df_train_and_test["pred_" + target_col[0]] = 0
                 df_train_and_test.loc[df_train_and_test.index[history_length:],
                                       "pred_" + target_col[0]] = end_tensor_list
-        print("Current historical dataframe:")
+        print("Current historical dataframe ")
         print(df_train_and_test)
         eval_log = run_evaluation(model, df_train_and_test, forecast_history, target_col, end_tensor, g_loss, eval_log,
                                   end_tensor_0)

flood_forecast/explain_model_output.py

@@ -21,7 +21,7 @@ def handle_dl_output(dl, dl_class: str, datetime_start: datetime, device: str) -
     """
     :param dl: The test data-loader. Should be passed directly
     :type dl: Union[CSVTestLoader, TemporalTestLoader]
-    :param dl_class: A string that is the name of DL passef from the params file.
+    :param dl_class: A string that is the name of DL passef from the params file
     :type dl_class: str
     :param datetime_start: The start datetime for the forecast
     :type datetime_start: datetime

flood_forecast/transformer_xl/data_embedding.py

@@ -87,10 +87,10 @@ def forward(self, x):
 
 
 class TemporalEmbedding(nn.Module):
-    def __init__(self, d_model: int, embed_type='fixed', lowest_level=4):
+    def __init__(self, d_model, embed_type='fixed', lowest_level=4):
         """A class to create
 
-        :param d_model: The model embedding dimension.
+        :param d_model: The model embedding dimension
         :type d_model: int
         :param embed_tsype: [description], defaults to 'fixed'
         :type embed_type: str, optional

requirements.txt

@@ -12,7 +12,7 @@ google-cloud-storage
 plotly~=5.20.0
 pytz>=2022.1
 setuptools~=69.5.1
-numpy==1.26.4
+numpy>=1.21
 requests
 torchvision>=0.6.0
 mpld3>=0.5