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# coding=utf-8
"""AudioCaps dataset."""
import os
import gzip
import shutil
import joblib
import pathlib
import logging
import datasets
import typing as tp
import pandas as pd
import urllib.request
from pathlib import Path
from copy import deepcopy
from tqdm.auto import tqdm
from rich.logging import RichHandler
logger = logging.getLogger(__name__)
logger.addHandler(RichHandler())
logger.setLevel(logging.INFO)
VERSION = "0.0.1"
# Cache location
DEFAULT_XDG_CACHE_HOME = "~/.cache"
XDG_CACHE_HOME = os.getenv("XDG_CACHE_HOME", DEFAULT_XDG_CACHE_HOME)
DEFAULT_HF_CACHE_HOME = os.path.join(XDG_CACHE_HOME, "huggingface")
HF_CACHE_HOME = os.path.expanduser(os.getenv("HF_HOME", DEFAULT_HF_CACHE_HOME))
DEFAULT_HF_DATASETS_CACHE = os.path.join(HF_CACHE_HOME, "datasets")
HF_DATASETS_CACHE = Path(os.getenv("HF_DATASETS_CACHE", DEFAULT_HF_DATASETS_CACHE))
class AudioCapsConfig(datasets.BuilderConfig):
"""BuilderConfig for AudioCaps."""
def __init__(self, features, **kwargs):
super(AudioCapsConfig, self).__init__(version=datasets.Version(VERSION, ""), **kwargs)
self.features = features
class AudioCaps(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
AudioCapsConfig(
features=datasets.Features(
{
"file": datasets.Value("string"),
"audio": datasets.Audio(sampling_rate=None),
"captions": atasets.Sequence(datasets.Value("string")),
}
),
name="audiocaps",
description="",
),
]
DEFAULT_CONFIG_NAME = "audiocaps"
def _info(self):
return datasets.DatasetInfo(
description="",
features=self.config.features,
supervised_keys=None,
homepage="",
citation="",
task_templates=None,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
extensions = ['.wav']
# Development sets
def _download_and_extract(filename):
DEV_URL = f'https://huggingface.co./datasets/confit/audiocaps/resolve/main/data/{filename}'
_dev_save_path = os.path.join(
HF_DATASETS_CACHE, 'confit___audiocaps/audiocaps', VERSION
)
download_file(
source=DEV_URL,
dest=os.path.join(_dev_save_path, filename),
unpack=True,
dest_unpack=os.path.join(_dev_save_path, 'extracted', 'train'),
)
joblib.Parallel(n_jobs=8, verbose=10)(
joblib.delayed(_download_and_extract)(
filename=_filename
) for _filename in tqdm([f'train{i}.zip' for i in range(1, 12+1)])
)
train_audio_paths = []
for _filename in [f'train{i}.zip' for i in range(1, 12+1)]:
DEV_URL = f'https://huggingface.co./datasets/confit/audiocaps/resolve/main/data/{_filename}'
_dev_save_path = os.path.join(
HF_DATASETS_CACHE, 'confit___audiocaps/audiocaps', VERSION
)
train_archive_path = os.path.join(_dev_save_path, 'extracted', 'train')
_, _walker = fast_scandir(train_archive_path, extensions, recursive=True)
train_audio_paths.extend(_walker)
# Validation set
VAL_URL = 'https://huggingface.co./datasets/confit/audiocaps/resolve/main/data/val.zip'
_val_save_path = os.path.join(
HF_DATASETS_CACHE, 'confit___audiocaps/audiocaps', VERSION
)
_filename = 'val.zip'
download_file(
source=VAL_URL,
dest=os.path.join(_val_save_path, _filename),
unpack=True,
dest_unpack=os.path.join(_val_save_path, 'extracted', 'validation'),
)
validation_archive_path = os.path.join(_val_save_path, 'extracted', 'validation')
_, validation_audio_paths = fast_scandir(validation_archive_path, extensions, recursive=True)
# Evaluation set
EVAL_URL = 'https://huggingface.co./datasets/confit/audiocaps/resolve/main/data/test.zip'
_eval_save_path = os.path.join(
HF_DATASETS_CACHE, 'confit___audiocaps/audiocaps', VERSION
)
_filename = 'test.zip'
download_file(
source=EVAL_URL,
dest=os.path.join(_eval_save_path, _filename),
unpack=True,
dest_unpack=os.path.join(_eval_save_path, 'extracted', 'test'),
)
test_archive_path = os.path.join(_eval_save_path, 'extracted', 'test')
_, test_audio_paths = fast_scandir(test_archive_path, extensions, recursive=True)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN, gen_kwargs={"audio_paths": train_audio_paths, "split": "train"}
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION, gen_kwargs={"audio_paths": validation_audio_paths, "split": "validation"}
),
datasets.SplitGenerator(
name=datasets.Split.TEST, gen_kwargs={"audio_paths": test_audio_paths, "split": "test"}
),
]
def _generate_examples(self, audio_paths, split=None):
if split == 'train':
metadata_df = pd.read_csv('https://huggingface.co./datasets/confit/audiocaps/raw/main/metadata/train.csv')
elif split == 'validation':
metadata_df = pd.read_csv('https://huggingface.co./datasets/confit/audiocaps/raw/main/metadata/val.csv')
elif split == 'test':
metadata_df = pd.read_csv('https://huggingface.co./datasets/confit/audiocaps/raw/main/metadata/test.csv')
fileid2caption = {}
for idx, row in metadata_df.iterrows():
fileid2caption[f"{row['audiocap_id']}.wav"] = row['caption'] # this filename doesn't have suffix
for guid, audio_path in enumerate(audio_paths):
fileid = Path(audio_path).name
caption = fileid2caption.get(fileid)
yield guid, {
"id": str(guid),
"file": audio_path,
"audio": audio_path,
"captions": [caption],
}
def fast_scandir(path: str, exts: tp.List[str], recursive: bool = False):
# Scan files recursively faster than glob
# From github.com/drscotthawley/aeiou/blob/main/aeiou/core.py
subfolders, files = [], []
try: # hope to avoid 'permission denied' by this try
for f in os.scandir(path):
try: # 'hope to avoid too many levels of symbolic links' error
if f.is_dir():
subfolders.append(f.path)
elif f.is_file():
if os.path.splitext(f.name)[1].lower() in exts:
files.append(f.path)
except Exception:
pass
except Exception:
pass
if recursive:
for path in list(subfolders):
sf, f = fast_scandir(path, exts, recursive=recursive)
subfolders.extend(sf)
files.extend(f) # type: ignore
return subfolders, files
def download_file(
source,
dest,
unpack=False,
dest_unpack=None,
replace_existing=False,
write_permissions=False,
):
"""Downloads the file from the given source and saves it in the given
destination path.
Arguments
---------
source : path or url
Path of the source file. If the source is an URL, it downloads it from
the web.
dest : path
Destination path.
unpack : bool
If True, it unpacks the data in the dest folder.
dest_unpack: path
Path where to store the unpacked dataset
replace_existing : bool
If True, replaces the existing files.
write_permissions: bool
When set to True, all the files in the dest_unpack directory will be granted write permissions.
This option is active only when unpack=True.
"""
class DownloadProgressBar(tqdm):
"""DownloadProgressBar class."""
def update_to(self, b=1, bsize=1, tsize=None):
"""Needed to support multigpu training."""
if tsize is not None:
self.total = tsize
self.update(b * bsize - self.n)
# Create the destination directory if it doesn't exist
dest_dir = pathlib.Path(dest).resolve().parent
dest_dir.mkdir(parents=True, exist_ok=True)
if "http" not in source:
shutil.copyfile(source, dest)
elif not os.path.isfile(dest) or (
os.path.isfile(dest) and replace_existing
):
logger.info(f"Downloading {source} to {dest}")
with DownloadProgressBar(
unit="B",
unit_scale=True,
miniters=1,
desc=source.split("/")[-1],
) as t:
urllib.request.urlretrieve(
source, filename=dest, reporthook=t.update_to
)
else:
logger.info(f"{dest} exists. Skipping download")
# Unpack if necessary
if unpack:
if dest_unpack is None:
dest_unpack = os.path.dirname(dest)
if os.path.exists(dest_unpack):
logger.info(f"{dest_unpack} already exists. Skipping extraction")
else:
logger.info(f"Extracting {dest} to {dest_unpack}")
# shutil unpack_archive does not work with tar.gz files
if (
source.endswith(".tar.gz")
or source.endswith(".tgz")
or source.endswith(".gz")
):
out = dest.replace(".gz", "")
with gzip.open(dest, "rb") as f_in:
with open(out, "wb") as f_out:
shutil.copyfileobj(f_in, f_out)
else:
shutil.unpack_archive(dest, dest_unpack)
if write_permissions:
set_writing_permissions(dest_unpack)
def set_writing_permissions(folder_path):
"""
This function sets user writing permissions to all the files in the given folder.
Arguments
---------
folder_path : folder
Folder whose files will be granted write permissions.
"""
for root, dirs, files in os.walk(folder_path):
for file_name in files:
file_path = os.path.join(root, file_name)
# Set writing permissions (mode 0o666) to the file
os.chmod(file_path, 0o666) |