Update _URLS: add train.tsv and valid.tsv

mtg_jamendo.py

@@ -12,14 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import csv
-import json
-import os
 from pathlib import Path
 
 import pandas as pd
-
-import genres
 import datasets
 
 # Find for instance the citation on arxiv or on the dataset repo/website
@@ -48,10 +43,16 @@ _LICENSE = "Apache License 2.0"
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 _URLS = {
     "train": {
-        i: f"https://huggingface.co/datasets/rkstgr/mtg-jamendo/resolve/main/data/train/{i}.tar" for i in range(200)
+        "df": "https://huggingface.co/datasets/rkstgr/mtg-jamendo/resolve/main/data/train.tsv",
+        **{
+            i: f"https://huggingface.co/datasets/rkstgr/mtg-jamendo/resolve/main/data/train/{i}.tar" for i in range(200)
+        }
     },
     "val": {
-        i: f"https://huggingface.co/datasets/rkstgr/mtg-jamendo/resolve/main/data/val/{i}.tar" for i in range(22)
+        "df": "https://huggingface.co/datasets/rkstgr/mtg-jamendo/resolve/main/data/valid.tsv",
+        **{
+            i: f"https://huggingface.co/datasets/rkstgr/mtg-jamendo/resolve/main/data/val/{i}.tar" for i in range(22)
+        }
     }
 }
 
@@ -97,10 +98,10 @@ class MtgJamendo(datasets.GeneratorBasedBuilder):
             return {x["id"]: x for x in xs}
 
         train_tracks = to_dict(
-            pd.read_csv(Path(__file__).parent / "train.tsv", sep="\t").to_dict("records")
+            pd.read_csv(local_extracted_archive["train"]["df"], sep="\t").to_dict("records")
         )
         valid_tracks = to_dict(
-            pd.read_csv(Path(__file__).parent / "valid.tsv", sep="\t").to_dict("records")
+            pd.read_csv(local_extracted_archive["val"]["df"], sep="\t").to_dict("records")
         )
 
         train_splits = [