defined forcings to be 0, meaningless for stats_calc in MEPS

mllam · Nov 13, 2024 · f97719b · f97719b
1 parent bcc3e51
commit f97719b
Showing 1 changed file with 4 additions and 3 deletions.
diff --git a/neural_lam/datastore/npyfilesmeps/compute_standardization_stats.py b/neural_lam/datastore/npyfilesmeps/compute_standardization_stats.py
@@ -167,15 +167,14 @@ def main(
         )
         torch.cuda.set_device(device) if torch.cuda.is_available() else None
 
-    # XXX ([email protected]): I don't quite understand why, but below fails with the
-    # MEPS example dataset if I just use `datastore._num_timesteps - 2` which
-    # would assume would be ok
     ar_steps = datastore._num_timesteps - 10
     ds = WeatherDataset(
         datastore=datastore,
         split="train",
         ar_steps=ar_steps,
         standardize=False,
+        num_past_forcing_steps=0,
+        num_future_forcing_steps=0,
     )
     if distributed:
         ds = PaddedWeatherDataset(
@@ -277,6 +276,8 @@ def main(
         split="train",
         ar_steps=ar_steps,
         standardize=True,
+        num_past_forcing_steps=0,
+        num_future_forcing_steps=0,
     )  # Re-load with standardization
     if distributed:
         ds_standard = PaddedWeatherDataset(