cleaning

P3.py

@@ -78,7 +78,7 @@ _DATA_PATH = "data"
 #     )
 #     return ds
 
-def load_cached_task(features_file, tfrecord, split):
+def load_cached_task(features_file, tfrecord):
     # # TODO(Victor): this info.*.json is actually done twice... -> factorize
     # with tf.io.gfile.GFile(os.path.join(cache_dir, f"info.{split}.json")) as f:
     with tf.io.gfile.GFile(features_file) as f:
@@ -100,9 +100,6 @@ def load_cached_task(features_file, tfrecord, split):
         feat: _feature_config(**desc) for feat, desc in features.items()
     }
 
-    # tfrecords = os.path.join(
-    #     cache_dir, f"{split}.tfrecord-*-of-*{split_info['num_shards']}"
-    # )
     ds = tf.data.TFRecordDataset(tf.io.gfile.glob([tfrecord]))
     ds = ds.map(
         lambda pb: tf.io.parse_single_example(pb, feature_description),
@@ -116,6 +113,7 @@ def load_cached_task(features_file, tfrecord, split):
     )
     return ds
 
+
 def find_task_splits_and_features():
     """Find the available tasks under ./data and their available splits and features."""
     task_and_their_splits = defaultdict(dict)
@@ -239,7 +237,6 @@ class P3(datasets.GeneratorBasedBuilder):
                     gen_kwargs={
                         "features_file": data_dir[task_name][split_name]["features_file"],
                         "tfrecord": data_dir[task_name][split_name]["tfrecord"],
-                        "split": split_name,
                     }
                 )
             )
@@ -251,7 +248,6 @@ class P3(datasets.GeneratorBasedBuilder):
                     gen_kwargs={
                         "features_file": data_dir[task_name][split_name]["features_file"],
                         "tfrecord": data_dir[task_name][split_name]["tfrecord"],
-                        "split": split_name,
                     }
                 )
             )
@@ -263,7 +259,6 @@ class P3(datasets.GeneratorBasedBuilder):
                     gen_kwargs={
                         "features_file": data_dir[task_name][split_name]["features_file"],
                         "tfrecord": data_dir[task_name][split_name]["tfrecord"],
-                        "split": split_name,
                     }
                 )
             )
@@ -276,14 +271,13 @@ class P3(datasets.GeneratorBasedBuilder):
                     gen_kwargs={
                         "features_file": data_dir[task_name][special_split_name]["features_file"],
                         "tfrecord": data_dir[task_name][special_split_name]["tfrecord"],
-                        "split": special_split_name,
                     }
                 )
             )
         return split_generators
 
 
-    def _generate_examples(self, features_file, tfrecord, split):
+    def _generate_examples(self, features_file, tfrecord):
         """This function returns the examples in the raw (text) form."""
         _FEAT_MAPPING_FUNCTIONS = {
             "answer_choices": lambda x: [choice.decode("utf-8") for choice in x],
@@ -297,7 +291,7 @@ class P3(datasets.GeneratorBasedBuilder):
         }
 
         key = 0
-        ds = load_cached_task(features_file, tfrecord, split)
+        ds = load_cached_task(features_file, tfrecord)
         for ex in ds.as_numpy_iterator():
             ex_dict = {}
             for feat_name, feat_value in ex.items():