renamed arguments

infer.py

@@ -36,10 +36,11 @@ def main(args):
         doc_ids=ids,
         dataset_name=dataset.get_name(),
         targets=None,
-        category_mapper="models/category_mappers/rai-mapping.csv"
+        category_mapper=args.category_map,
+        outdir=args.outdir,
     )
 
-def save_inference_preds(preds, dataset_name, doc_ids, targets=None, category_mapper=None, output_dir="results/inference-preds"):
+def save_inference_preds(preds, dataset_name, doc_ids, targets=None, category_mapper=None, outdir="results/inference-preds"):
     """
     Parameters
     ----------
@@ -61,7 +62,7 @@ def save_inference_preds(preds, dataset_name, doc_ids, targets=None, category_ma
                 Dir where to store output csv file.
                 (default = results/inference-preds)
     """
-    os.makedirs(output_dir, exist_ok=True)
+    os.makedirs(outdir, exist_ok=True)
     df = pd.DataFrame()
     langs = sorted(preds.keys())
     _ids = []
@@ -86,18 +87,23 @@ def save_inference_preds(preds, dataset_name, doc_ids, targets=None, category_ma
         mapper = pd.read_csv(category_mapper).to_dict()["category"]
         df["gfun_string_prediction"] = [mapper[p] for p in _preds]
 
-    output_file = f"{output_dir}/{dataset_name}.csv"
+    output_file = f"{outdir}/{dataset_name}.csv"
     print(f"Storing predicitons in: {output_file}")
     df.to_csv(output_file, index=False)
 
+    return
+        
 
 if __name__ == "__main__":
     from argparse import ArgumentParser
     parser = ArgumentParser()
-    parser.add_argument("--datapath", type=str, default="~/datasets/rai/csv", help="Path to csv file containing the documents to be classified")
+    parser.add_argument("--datapath", required=True, type=str, help="path to csv file containing the documents to be classified")
+    parser.add_argument("--outdir", type=str, default="results/inference-preds", help="path to store csv file containing gfun predictions")
+    parser.add_argument("--category_map", type=str, default="models/category_mappers/rai-mapping.csv", help="path to csv file containing the mapping from label name to label id [str: id]")
     parser.add_argument("--nlabels", type=int, default=28)
-    parser.add_argument("--muse_dir", type=str, default="~/resources/muse_embeddings", help="Path to muse embeddings")
+    parser.add_argument("--muse_dir", type=str, default="embeddings", help="path to muse embeddings")
     parser.add_argument("--trained_gfun", type=str, default="rai_pmt_mean_231029", help="name of the trained gfun instance")
+
     args = parser.parse_args()
     main(args)
 

run-rai.sh

@@ -1,25 +0,0 @@
-#!bin/bash
-
-njobs=-1
-clf=singlelabel
-patience=5
-eval_every=5
-text_len=512
-text_lr=1e-4
-bsize=2
-txt_model=mbert
-dataset=rai
-
-config="-pmt"
-echo "[Running gFun config: $config]"
-python main.py $config \
-    -d $dataset\
-    --nosave \
-    --n_jobs $njobs \
-    --clf_type $clf \
-    --patience $patience \
-    --evaluate_step $eval_every \
-    --batch_size $bsize \
-    --max_length $text_len \
-    --textual_lr $text_lr \
-    --textual_trf_name $txt_model \