Merge branch 'update' of https://github.com/openclimatefix/PVNet_summ…

…ation into update

README.md

@@ -20,7 +20,7 @@ pip install ".[dev]"
 
 ## Getting started with running PVNet summation
 
-In order to run PVNet summation, we assume that you are already set up with 
+In order to run PVNet summation, we assume that you are already set up with
 [PVNet](https://github.com/openclimatefix/PVNet) and have met all the requirements there.
 
 Before running any code, copy the example configuration to a
@@ -34,35 +34,35 @@ You will be making local amendments to these configs.
 
 ### Datasets
 
-The datasets required are the same as documented in 
-[PVNet](https://github.com/openclimatefix/PVNet). The only addition is that you will need PVLive 
+The datasets required are the same as documented in
+[PVNet](https://github.com/openclimatefix/PVNet). The only addition is that you will need PVLive
 data for the national sum i.e. GSP ID 0.
 
 
 ## Generating pre-made concurrent batches of data for PVNet
 
-It is required that you preprepare batches using the `save_concurrent_batches.py` script from 
-PVNet. This saves the batches as required by the PVNet model to make predictions for all GSPs for 
+It is required that you preprepare batches using the `save_concurrent_batches.py` script from
+PVNet. This saves the batches as required by the PVNet model to make predictions for all GSPs for
 a single forecast init time. Seen the PVNet package for more details on this.
 
 
 ### Set up and config example for batch creation
 
 
 The concurrent batches created in the step above will be augmented with a few additional pieces of
-data required for the summation model. Within your copy of `PVNet_summation/configs` make sure you 
+data required for the summation model. Within your copy of `PVNet_summation/configs` make sure you
 have replaced all of the items marked with `PLACEHOLDER`
 
 ### Training PVNet_summation
 
-How PVNet_summation is run is determined by the extensive configuration in the config files. The 
-configs stored in `PVNet/configs.example` should work with batches created using the steps and 
+How PVNet_summation is run is determined by the extensive configuration in the config files. The
+configs stored in `PVNet/configs.example` should work with batches created using the steps and
 batch creation config mentioned above.
 
 Make sure to update the following config files before training your model:
 
 1. In `configs/datamodule/default.yaml`:
-    - update `batch_dir` to point to the directory you stored your concurrent batches in during 
+    - update `batch_dir` to point to the directory you stored your concurrent batches in during
       batch creation.
     - update `gsp_zarr_path` to point to the PVLive data containing the national estimate
 2. In `configs/model/default.yaml`:
@@ -74,7 +74,7 @@ Make sure to update the following config files before training your model:
 4. In `configs.config.yaml`:
     - It is recommended that you set `presave_pvnet_outputs` to `True`. This means that the
       concurrent batches that you create will only be run through the PVNet model once before
-      training and their outputs saved, rather than being run on the fly on each batch throughout 
+      training and their outputs saved, rather than being run on the fly on each batch throughout
       training. This can speed up training significantly.
 
 

pvnet_summation/__init__.py

@@ -1,2 +1,2 @@
 """PVNet_summation"""
-__version__ = "0.1.4"
+__version__ = "0.1.4"

pvnet_summation/models/base_model.py

@@ -91,7 +91,7 @@ def __init__(
             )
         else:
             self.pvnet_output_shape = (317, self.pvnet_model.forecast_len)
-        
+
         self.use_weighted_loss = False
 
     def predict_pvnet_batch(self, batch):
@@ -186,7 +186,7 @@ def validation_step(self, batch: dict, batch_idx):
 
         losses = self._calculate_common_losses(y, y_hat)
         losses.update(self._calculate_val_losses(y, y_hat))
-        
+
         # Store these to make horizon accuracy plot
         self._horizon_maes.append(
             {i: losses[f"MAE_horizon/step_{i:03}"].cpu().numpy() for i in range(self.forecast_len)}

scripts/checkpoint_to_huggingface.py

@@ -1,5 +1,5 @@
 """Command line tool to push locally save model checkpoints to huggingface
-    
+
 use:
 python checkpoint_to_huggingface.py "path/to/model/checkpoints" \
     --local-path="~/tmp/this_model" \