[pre-commit.ci] auto fixes from pre-commit.com hooks

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pvnet/models/base_model.py

@@ -42,7 +42,7 @@
 
 def make_clean_data_config(input_path, output_path, placeholder="PLACEHOLDER"):
     """Resave the data config and replace the filepaths with a placeholder.
-    
+
     Args:
         input_path: Path to input datapipes configuration file
         output_path: Location to save the output configuration file
@@ -77,26 +77,25 @@ def make_clean_data_config(input_path, output_path, placeholder="PLACEHOLDER"):
 
     with open(output_path, "w") as outfile:
         yaml.dump(config, outfile, default_flow_style=False)
-
-
+
 
 def minimize_data_config(input_path, output_path, model):
     """Strip out parts of the data config which aren't used by the model
-    
+
     Args:
         input_path: Path to input datapipes configuration file
         output_path: Location to save the output configuration file
     """
     with open(input_path) as cfg:
         config = yaml.load(cfg, Loader=yaml.FullLoader)
-    
+
     if "nwp" in config["input_data"]:
         if not model.include_nwp:
             del config["input_data"]["nwp"]
         else:
             for nwp_source in config["input_data"]["nwp"].keys():
                 nwp_config = config["input_data"]["nwp"][nwp_source]
-                
+
                 if nwp_source not in model.nwp_encoders_dict:
                     # If not used, delete this source from the config
                     del config["input_data"]["nwp"][nwp_source]
@@ -105,43 +104,42 @@ def minimize_data_config(input_path, output_path, model):
                     nwp_pixel_size = model.nwp_encoders_dict[nwp_source].image_size_pixels
                     nwp_config["nwp_image_size_pixels_height"] = nwp_pixel_size
                     nwp_config["nwp_image_size_pixels_width"] = nwp_pixel_size
-                    
+
                     # Replace the forecast minutes
                     nwp_config["forecast_minutes"] = (
-                        model.nwp_encoders_dict[nwp_source].sequence_length - 
-                        nwp_config["history_minutes"]/nwp_config["time_resolution_minutes"] - 1
-                    )*nwp_config["time_resolution_minutes"]
-
-                    
+                        model.nwp_encoders_dict[nwp_source].sequence_length
+                        - nwp_config["history_minutes"] / nwp_config["time_resolution_minutes"]
+                        - 1
+                    ) * nwp_config["time_resolution_minutes"]
+
     if "satellite" in config["input_data"]:
         if not model.include_sat:
             del config["input_data"]["satellite"]
         else:
             sat_config = config["input_data"]["satellite"]
-            
+
             # Replace the image size
             sat_pixel_size = model.sat_encoder.image_size_pixels
             sat_config["satellite_image_size_pixels_height"] = sat_pixel_size
             sat_config["satellite_image_size_pixels_width"] = sat_pixel_size
-            
+
             # Replace the satellite delay
             sat_config["live_delay_minutes"] = model.min_sat_delay_minutes
 
     if "pv" in config["input_data"]:
         if not model.include_pv:
             del config["input_data"]["pv"]
-            
+
     if "gsp" in config["input_data"]:
         gsp_config = config["input_data"]["gsp"]
-        
+
         # Replace the forecast minutes
         gsp_config["forecast_minutes"] = model.forecast_minutes
 
     with open(output_path, "w") as outfile:
         yaml.dump(config, outfile, default_flow_style=False)
 
 
-
 class PVNetModelHubMixin(PyTorchModelHubMixin):
     """
     Implementation of [`PyTorchModelHubMixin`] to provide model Hub upload/download capabilities.
@@ -271,10 +269,10 @@ def save_pretrained(
         # Save cleaned datapipes configuration file
         if data_config is not None:
             new_data_config_path = save_directory / DATA_CONFIG_NAME
-            
+
             # Replace the input filenames with place holders
             make_clean_data_config(data_config, new_data_config_path)
-            
+
             # Taylor the data config to the model being saved
             minimize_data_config(new_data_config_path, new_data_config_path, self)
 
@@ -649,7 +647,7 @@ def on_validation_epoch_end(self):
         """Run on epoch end"""
 
         horizon_maes_dict = self._horizon_maes.flush()
-        
+
         # Create the horizon accuracy curve
         if isinstance(self.logger, pl.loggers.WandbLogger):
             per_step_losses = [[i, horizon_maes_dict[i]] for i in range(self.forecast_len)]