init

download_audio.py

@@ -93,7 +93,6 @@ def to_json_serializable(val):
 
 
 def cleanup(features, feature_file):
-    os.remove(features[f"{side}.path"])
     if os.path.exists(feature_file):
         os.remove(feature_file)
     for _side in sides:
@@ -101,7 +100,7 @@ def cleanup(features, feature_file):
             os.remove(features[f"{_side}.path"])
     # create a dummy so that we can skip from next run
     with open(feature_file, "w") as f:
-        json.dump({"dummy": "dummy"})
+        json.dump({"dummy": "dummy"}, f)
 
 
 def get_audio(dataframe: pd.DataFrame):

main.sh

@@ -3,6 +3,7 @@ rm -rf download/audio
 rm -rf download/feature
 python -c 'n=41; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/feature/enA-jaA/*.json")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
 python -c 'n=41; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/enA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
+python -c 'n=41; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/jaA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
 python -c 'file_name="download/audio/enA-jaA/jaA/100020.mp3"; from datasets import Audio; a=Audio(); wav=a.decode_example({"path": file_name, "bytes": None}): print(wav)'
 ####################
 # enA-jaA: 718_606 #
@@ -59,7 +60,7 @@ done
 # kotoba-4
 for i in $(seq 41 50);
 do
-  export N_POOL=40
+  export N_POOL=10
   export DATASET_ID=${i}
   export DIRECTION="enA-jaA"
   export LINE_NO_START=$(((DATASET_ID-1) * 2500))