fix(*): decrease the row group size for audio datasets
Browse filesBy default, the row group size is set to 100 rows, which is too large
for the Hugging Face Dataset Viewer. This change reduces that number
to 20 rows. See this issue for more details:
https://github.com/google-deepmind/librispeech-long/issues/1
README.md
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@@ -17,19 +17,19 @@ dataset_info:
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dtype: float64
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splits:
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- name: dev_clean
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num_bytes:
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num_examples: 295
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- name: dev_other
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num_bytes:
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num_examples: 188
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- name: test_clean
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num_examples: 270
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- name: test_other
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num_examples: 207
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download_size:
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dataset_size:
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configs:
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- config_name: librispeech_long
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data_files:
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dtype: float64
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splits:
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- name: dev_clean
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num_bytes: 1809224578.0
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num_examples: 295
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- name: dev_other
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num_bytes: 1070577217.0
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num_examples: 188
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- name: test_clean
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num_bytes: 1677717130.0
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num_examples: 270
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- name: test_other
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num_bytes: 1195726954.0
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num_examples: 207
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download_size: 5753245879
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dataset_size: 5753245879
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configs:
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- config_name: librispeech_long
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data_files:
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librispeech_long/dev_clean-00000-of-00001.parquet
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oid sha256:a41961898641a1fde675bd71f0e30accc17ec43c5d77120323f0554867c63681
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size 1809224578
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librispeech_long/dev_other-00000-of-00001.parquet
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oid sha256:ce5c1aa12e33ace577e7ca8456d4aafa37dd3b6ff8b9098e676cf59caa49fe36
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size 1070577217
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librispeech_long/test_clean-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:8f16e89e3a3b69d644ee4844b8a66df4edffd119fd565a2629d3466d6f3d0348
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size 1677717130
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librispeech_long/test_other-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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size 1195726954
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process.py
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@@ -28,11 +28,14 @@ from dataclasses import dataclass
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from pathlib import Path
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from typing import Dict, List, Optional, Tuple
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from datasets import Audio, Dataset, Features, Value
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from tqdm import tqdm
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# --- Configuration ---
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# Config name on the Hub.
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CONFIG_NAME = "librispeech_long"
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@@ -217,6 +220,7 @@ def build_parquet_dataset(rows: List[Row]) -> Dataset:
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}
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for r in rows
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]
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return Dataset.from_list(data_list, features=features)
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from pathlib import Path
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from typing import Dict, List, Optional, Tuple
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import datasets
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from datasets import Audio, Dataset, Features, Value
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from tqdm import tqdm
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# --- Configuration ---
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datasets.config.PARQUET_ROW_GROUP_SIZE_FOR_AUDIO_DATASETS = 20
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# Config name on the Hub.
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CONFIG_NAME = "librispeech_long"
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}
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for r in rows
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]
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return Dataset.from_list(data_list, features=features)
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