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import json |
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import os |
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import tarfile |
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import zipfile |
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import gzip |
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import subprocess |
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from os.path import join as p_join |
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from tqdm import tqdm |
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from multiprocessing import Pool |
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from typing import Optional |
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import pandas as pd |
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url_metadata_dict = { |
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"enA-jaA": "https://dl.fbaipublicfiles.com/seamless/data/seamless_align_nov2023_extension/seamless.dataset.metadata.public.enA-jaA.tsv.gz", |
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"enA-jpn": "https://dl.fbaipublicfiles.com/seamless/data/seamless.dataset.metadata.public.enA-jpn.withduration.tsv.gz" |
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} |
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direction = os.getenv("DIRECTION", "enA-jaA") |
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sides = set(direction.split("-")) |
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cache_dir_audio = p_join("download", "audio", direction) |
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cache_dir_feature = p_join("download", "feature", direction) |
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os.makedirs(cache_dir_feature, exist_ok=True) |
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for s in sides: |
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os.makedirs(p_join(cache_dir_audio, s), exist_ok=True) |
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n_pool = int(os.getenv("N_POOL", 8)) |
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wget_max_retry = os.getenv("MAX_RETRY", "1") |
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wget_timeout = os.getenv("TIMEOUT", "20") |
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line_no_start = int(os.getenv("LINE_NO_START", 0)) |
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line_no_end = int(os.getenv("LINE_NO_END", 10000)) |
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def wget(url: str, output_file: Optional[str] = None): |
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os.makedirs(os.path.dirname(output_file), exist_ok=True) |
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subprocess.run(["wget", url, "-O", output_file, "--tries", wget_max_retry, "--timeout", wget_timeout]) |
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if not os.path.exists(output_file): |
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return False |
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if output_file.endswith('.tar.gz') or output_file.endswith('.tgz') or output_file.endswith('.tar'): |
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if output_file.endswith('.tar'): |
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tar = tarfile.open(output_file) |
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else: |
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tar = tarfile.open(output_file, "r:gz") |
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tar.extractall(os.path.dirname(output_file)) |
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tar.close() |
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os.remove(output_file) |
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elif output_file.endswith('.gz'): |
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with gzip.open(output_file, 'rb') as f: |
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with open(output_file.replace('.gz', ''), 'wb') as f_write: |
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f_write.write(f.read()) |
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os.remove(output_file) |
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elif output_file.endswith('.zip'): |
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with zipfile.ZipFile(output_file, 'r') as zip_ref: |
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zip_ref.extractall() |
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os.remove(output_file) |
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return True |
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def get_metadata(): |
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url_metadata = url_metadata_dict[direction] |
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meta_data_filename = os.path.basename(url_metadata) |
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meta_data_path = p_join("download", "meta", meta_data_filename) |
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if not os.path.exists(meta_data_path.replace(".gz", "")): |
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assert wget(url_metadata, output_file=meta_data_path) |
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df = pd.read_csv(meta_data_path.replace(".gz", ""), sep=r'[\t\s]', header=None) |
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df = df[[0, 2, 3, 4, 9, 10, 11, 12]] |
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df.columns = ["id", "url", "duration_start", "duration_end", "laser_score", "direction", "side", "line_no"] |
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if direction == "enA-jpn": |
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df = df[df["side"] == "enA"] |
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assert len(df["direction"].unique()) == 1 |
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df.pop("direction") |
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return df.sort_values(by=["line_no", "side"]) |
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def to_json_serializable(val): |
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if "float" in str(type(val)): |
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return float(val) |
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if "int" in str(type(val)): |
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return int(val) |
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return str(val) |
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def get_audio(dataframe: pd.DataFrame): |
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features = {"line_no": int(dataframe.pop('line_no').values[0])} |
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for side, df in dataframe.groupby("side"): |
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df.pop("side") |
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features.update({f"{side}.{k}": to_json_serializable(v) for k, v in df.iloc[0].to_dict().items()}) |
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identifier = os.path.basename(features[f"{side}.url"]).split(".")[-1] |
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features[f"{side}.path"] = str(p_join(cache_dir_audio, side, f"{features['line_no']}.{identifier}")) |
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if not os.path.exists(features[f"{side}.path"]): |
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flag = wget(features[f"{side}.url"], output_file=features[f"{side}.path"]) |
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if not flag: |
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return False |
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with open(p_join(cache_dir_feature, f'{features["line_no"]}.json'), "w") as f: |
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json.dump(features, f) |
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return True |
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def process_dataset(): |
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df_metadata = get_metadata() |
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print(f"metadata: {len(df_metadata)}, {line_no_start} --> {line_no_end}") |
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inputs = [ |
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g for line_no, g in df_metadata.groupby("line_no") |
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if line_no_start <= line_no < line_no_end and not os.path.exists( |
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p_join(cache_dir_feature, f'{int(line_no)}.json') |
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) |
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] |
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print(f"filtered unique lines: {len(inputs)}") |
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if direction == "enA-jaA": |
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inputs = [g for g in inputs if len(g["side"].unique()) == 2 and set(g["side"].unique()) == sides] |
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print(f"removed side != 2: {len(inputs)}") |
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if n_pool == 1: |
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for g in tqdm(inputs, total=len(inputs)): |
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flag = get_audio(g) |
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if not flag: |
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print(f"failed:\n{g['url']}") |
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else: |
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with Pool(n_pool) as pool: |
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pool.map(get_audio, tqdm(inputs, total=len(inputs))) |
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if __name__ == '__main__': |
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process_dataset() |
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