update config and submit (derecho queue)

config/inference.yml

@@ -1,17 +1,18 @@
 model: "hrrr"
-ML_model_path: "/glade/p/cisl/aiml/ai2es/winter_ptypes/models/classifier_weighted_smallmodel"
+evidential: True
+ML_model_path: "/glade/p/cisl/aiml/ai2es/winter_ptypes/models/evidential_weighted"
 input_scaler_file: "input.json"
-output_scaler_file: "output_label.json"
-out_path: "/glade/scratch/username/ptype_case_studies_vaisala/20221205/"
+out_path: "/glade/work/username/ptype_real_time/2023-11-17/"
 drop_input_data: False
 add_interp_data: True
-n_processors: 1      # Only used if use_dask=False (dask has its own parameters at bottom of config)
-use_dask: True
+n_processors: 20      # Only used if use_dask=False (dask has its own parameters at bottom of config)
+use_dask: False
 save_format: "netcdf"   # Supports "zarr" and "netcdf"
-extent: [-120, -110, 32, 35]  # [min_lon, max_lon, min_lat, max_lat] or "full"
+extent: [-115, -110, 32, 35]  # [min_lon, max_lon, min_lat, max_lat] or "full"
 dates:
-  start: "2022-02-03 00:00"
-  end: "2022-02-04 23:00"
+  most_recent: True
+  start: "2022-02-03 00:00" # ignore if most_recent is True
+  end: "2022-02-03 05:00"   # ignore if most_recent is True
   frequency: "1H"
 
 forecast_range:

scripts/submit_inference.sh

@@ -1,13 +1,13 @@
 #!/bin/bash -l
 #PBS -N ptype_inf
 #PBS -A NAML0001
-#PBS -l walltime=12:00:00
+#PBS -l walltime=00:30:00
 #PBS -o ptype_inference.out
 #PBS -e ptype_inference.out
-#PBS -q casper
-#PBS -l select=1:ncpus=24:mem=256GB
+#PBS -q main
+#PBS -l select=1:ncpus=20:ngpus=4:mem=128GB -l gpu_type=a100
 #PBS -m a
-#PBS -M dgagne@ucar.edu
+#PBS -M cbceker@ucar.edu
 conda activate ptype
-cd /glade/work/dgagne/ptype-physical/
-python -u ./scripts/run_inference.py  -c ./config/inference_vaisala_NE.yml
+cd /glade/work/cbecker/ptype-physical/
+python -u ./scripts/run_inference.py  -c ./config/inference.yml