remove wandb.login() calls, seems enough to do it once when initially running on new machine

fix voronoi_featurize_dataset.py df to wandb.Table conversion error due to structure column

Author: janosh

models/bowsr/test_bowsr.py

@@ -98,8 +98,6 @@
     task_type=task_type,
     slurm_vars=slurm_vars,
 )
-if wandb.run is None:
-    wandb.login()
 
 wandb.init(project="matbench-discovery", name=job_name, config=run_params)
 

models/cgcnn/test_cgcnn.py

@@ -69,7 +69,6 @@
     "created_at": {"$gt": "2022-11-22", "$lt": "2022-11-23"},
     "display_name": {"$regex": "^cgcnn-robust"},
 }
-wandb.login()
 runs = wandb.Api().runs("janosh/matbench-discovery", filters=filters)
 
 assert len(runs) == 10, f"Expected 10 runs, got {len(runs)} for {filters=}"

models/m3gnet/test_m3gnet.py

@@ -75,8 +75,6 @@
     df=dict(shape=str(df_this_job.shape), columns=", ".join(df_this_job)),
     slurm_vars=slurm_vars,
 )
-if wandb.run is None:
-    wandb.login()
 
 run_name = f"{job_name}-{slurm_array_task_id}"
 wandb.init(project="matbench-discovery", name=run_name, config=run_params)

models/megnet/test_megnet.py

@@ -67,8 +67,6 @@
     df=dict(shape=str(df_wbm_structs.shape), columns=", ".join(df_wbm_structs)),
     slurm_vars=slurm_vars,
 )
-if wandb.run is None:
-    wandb.login()
 
 wandb.init(project="matbench-discovery", name=job_name, config=run_params)
 

models/voronoi/voronoi_featurize_dataset.py

@@ -13,20 +13,19 @@
 from matbench_discovery.slurm import slurm_submit
 from models.voronoi import featurizer
 
-module_dir = os.path.dirname(__file__)
-
 data_name = "mp"  # "mp"
 if data_name == "wbm":
     data_path = f"{ROOT}/data/wbm/2022-10-19-wbm-init-structs.json.bz2"
     input_col = "initial_structure"
 elif data_name == "mp":
     data_path = f"{ROOT}/data/mp/2022-09-16-mp-computed-structure-entries.json.gz"
-    input_col = "structure"
+    input_col = "relaxed_structure"
 
-slurm_array_task_count = 30
 debug = "slurm-submit" in sys.argv
 job_name = f"voronoi-features-{data_name}{'-debug' if DEBUG else ''}"
+module_dir = os.path.dirname(__file__)
 out_dir = os.environ.get("SBATCH_OUTPUT", f"{module_dir}/{today}-{job_name}")
+slurm_array_task_count = 50
 
 
 slurm_vars = slurm_submit(
@@ -70,9 +69,8 @@
     df=dict(shape=str(df_this_job.shape), columns=", ".join(df_this_job)),
     input_col=input_col,
     slurm_vars=slurm_vars,
+    out_path=out_path,
 )
-if wandb.run is None:
-    wandb.login()
 
 wandb.init(project="matbench-discovery", name=run_name, config=run_params)
 
@@ -82,11 +80,11 @@
 warnings.filterwarnings(action="ignore", category=UserWarning, module="pymatgen")
 
 df_features = featurizer.featurize_dataframe(
-    df_this_job, input_col, ignore_errors=True, pbar=dict(position=0, leave=True)
-)
+    df_this_job, input_col, ignore_errors=True
+)[featurizer.feature_labels()].round(6)
 
 
 # %%
-df_features[featurizer.feature_labels()].to_csv(out_path)
+df_features.to_csv(out_path)
 
 wandb.log({"voronoi_features": wandb.Table(dataframe=df_features)})

models/wrenformer/test_wrenformer.py

@@ -51,8 +51,6 @@
 
 
 # %%
-wandb.login()
-
 filters = {
     "created_at": {"$gt": "2022-11-15", "$lt": "2022-11-16"},
     "display_name": {"$regex": "wrenformer-robust"},