feat(loader): updated last batch folder pointer in the index, added loading script

batch.py

@@ -0,0 +1,173 @@
+import os
+from pandas import read_csv
+
+from datasets import GeneratorBasedBuilder, Value, Version, BuilderConfig, Features, DatasetInfo, SplitGenerator, Split, Audio, Sequence
+
+_DESCRIPTION = '''
+The dataset contains threads parsed from the /b/ board of 2ch archive
+'''
+
+_HOMEPAGE = 'https://huggingface.co/datasets/zeio/batch'
+
+_LICENSE = 'Apache License Version 2.0'
+
+_CLUSTER = '{first_page:04d}-{last_page:04d}'
+_URLS = {
+    'written': 'https://huggingface.co/datasets/zeio/batch/resolve/main/threads-compressed/{cluster}.tar.xz',
+    'spoken': 'https://huggingface.co/datasets/zeio/batch-speech/raw/main/threads-compressed/{cluster}.tar.xz'
+}
+_INDEX = 'https://huggingface.co/datasets/zeio/batch/resolve/main/index.tsv'
+
+_N_ITEMS = 1750
+_N_BATCH = 20
+
+
+class Batch(GeneratorBasedBuilder):
+
+    VERSION = Version('06.11.2023')
+
+    BUILDER_CONFIGS = [
+        BuilderConfig(
+            name = 'written',
+            version = VERSION,
+            description = 'The base modification which contains only text representation of threads, which are divided into topics, which in turn are made of posts'
+        ),
+        BuilderConfig(
+            name = 'spoken',
+            version = VERSION,
+            description = (
+                'An extended configuration of the dataset in which besides text some threads have an associated audio data with speech '
+                'generated for text in the respective thread using an alternating speaker pattern'
+            )
+        )
+    ]
+
+    DEFAULT_CONFIG_NAME = 'written'
+
+    def _info(self):
+        if self.config.name == 'written':
+            features = Features({
+                'title': Value('string'),
+                'topics': Sequence({
+                    'posts': Sequence({
+                        'text': Value('string')
+                    })
+                })
+            })
+        elif self.config.name == 'spoken':
+            features = Features({
+                'title': Value('string'),
+                'speech': Audio(sampling_rate = 48_000),
+                'topics': Sequence({
+                    'posts': Sequence({
+                        'text': Value('string')
+                    })
+                })
+            })
+        else:
+            raise ValueError(f'Unknown config: {self.config.name}')
+
+        return DatasetInfo(
+            description=_DESCRIPTION,
+            features = features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE
+        )
+
+    def _split_generators(self, dl_manager):
+        name = self.config.name
+
+        url = _URLS['written']
+        spoken_url = _URLS['spoken'] if name == 'spoken' else None
+
+        offset = 0
+
+        written = {}
+        spoken = None if spoken_url is None else {}
+
+        while offset < _N_ITEMS:
+            cluster = _CLUSTER.format(first_page = offset, last_page = (offset := min(offset + _N_BATCH - 1, _N_ITEMS)))
+            written[f'threads/{cluster}'] = dl_manager.download_and_extract(url.format(cluster = cluster))
+            if spoken is not None:
+                try:
+                    spoken[f'threads/{cluster}'] = dl_manager.download_and_extract(spoken_url.format(cluster = cluster))
+                except:  # speech for some clusters may be missing
+                    pass
+
+        index = dl_manager.download_and_extract(_INDEX)
+
+        # print(clusters)
+        # print(index)
+
+        return [
+            SplitGenerator(
+                name = Split.TRAIN,
+                gen_kwargs = {
+                    'written': written,
+                    'spoken': spoken,
+                    'index': index
+                }
+            )
+        ]
+
+    def _generate_examples(self, written: dict, index: str, spoken: dict = None):
+        for i, row in read_csv(index, sep = '\t').iterrows():
+            # print(row)
+
+            path = os.path.join(written[row['path']], f'{row["thread"]}.txt')
+
+            topics = []
+            posts = []
+
+            # def append_topic():
+            #     nonlocal posts, topics
+
+            #     if len(posts) > 0:
+            #         topics.append({'posts': posts})
+            #         posts = []
+
+            with open(path, 'r', encoding = 'utf-8') as file:
+                for line in file.read().split('\n'):
+                    if line:
+                        posts.append({'text': line})
+                    # else:
+                    #     append_topic()
+                    elif len(posts) > 0:
+                        topics.append({'posts': posts})
+                        posts = []
+
+                # append_topic()
+
+            item = {
+                'title': row['title'],
+                'topics': topics
+            }
+
+            if spoken is not None:
+                speech_cluster_path = spoken.get(row['path'])
+
+                if speech_cluster_path is not None:
+                    speech_file_path = os.path.join(speech_cluster_path, f'{row["thread"]}.mp3')
+
+                    if os.path.isfile(speech_file_path):
+                        item['speech'] = speech_file_path
+
+            yield i, item
+
+            # if sound is None:
+            #     yield i, dict(row)
+            # else:
+            #     data = dict(row)
+
+            #     folder = data['folder']
+            #     filename = data['filename']
+
+            #     if folder == folder and filename == filename:  # if folder and filename are not nan
+            #         data['sound'] = os.path.join(sound, folder, f'{filename}.ogg')
+            #     else:
+            #         data['sound'] = NA
+
+            #     data.pop('folder')
+            #     data.pop('filename')
+
+            #     yield i, data

index.tsv

@@ -1,3 +1,3 @@
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