add loading bar with tqdm

nst_sv.py

@@ -22,11 +22,10 @@ TODO:
 * add train-validation-test split option
 """
 
-import csv
 import json
 import os
-import logging
 
+from tqdm import tqdm
 import datasets
 
 
@@ -59,13 +58,6 @@ _URLS = {
 
 _ANNOTATIONS_URL = "https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/se_2020/ADB_SWE_0467.tar.gz"
 
-# _BAD_ANNOTATIONS = [
-#     'se14x012-07071999-1342_r4670012.json',
-#     'se14x600-21022000-1038_r4670002.json',
-#     'se12x387-05071999-1018_r4670387.json',
-#     'se13x379-06081999-1429_r4670380.json',
-#     'se12x048-21071999-1158_r4670048.json'
-# ]
 
 class NstSV(datasets.GeneratorBasedBuilder):
     """Audio dataset for Swedish ASR provided by National Library of Norawy.
@@ -138,7 +130,11 @@ class NstSV(datasets.GeneratorBasedBuilder):
             "frequency": datasets.Value("string"),
             "memo": datasets.Value("string"),
             "script": datasets.Value("string"),
-            "version": datasets.Value("string"), 
+            "version": datasets.Value("string"),
+            # real sampling rate is 16000
+            # it is set to 48000 to allow concatenation
+            # with common voice dataset using
+            # datasets.concatenate_datasets([dataset_a, dataset_b])
             "audio": datasets.features.Audio(sampling_rate=48000),
             'client_id': datasets.Value("string"),
             'path': datasets.Value("string"),
@@ -177,8 +173,7 @@ class NstSV(datasets.GeneratorBasedBuilder):
         urls = _URLS[self.config.name]
         data_dir = dl_manager.download_and_extract(urls)
         annotations_dir = dl_manager.download_and_extract(_ANNOTATIONS_URL)
-        # print(f"data_dir: {data_dir}")
-        # print(f"annotations_dir: {annotations_dir}")
+
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
@@ -217,8 +212,6 @@ class NstSV(datasets.GeneratorBasedBuilder):
 
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, data_dir, annotations_dir):
-        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
 
         files_failed_loading = []
         if self.config.name == "close_channel":
@@ -227,7 +220,7 @@ class NstSV(datasets.GeneratorBasedBuilder):
             channel_ext = "-2"
 
         annotations_files = os.listdir(annotations_dir)
-        for i, annotation_filename in enumerate(annotations_files):
+        for annotation_filename in tqdm(annotations_files):
             print(f"Loading from annotation file: {i+1}/{len(annotations_files)}")
             # if annotation_filename not in _BAD_ANNOTATIONS:
             annotations_filepath = os.path.join(annotations_dir, annotation_filename)