Update fsdkaggle2019-script.py
Browse files- fsdkaggle2019-script.py +82 -3
fsdkaggle2019-script.py
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@@ -4,6 +4,7 @@
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import os
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import textwrap
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import datasets
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import itertools
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import typing as tp
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from pathlib import Path
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from copy import deepcopy
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from ._fsd2019 import CLASSES
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SAMPLE_RATE = 44_100
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_TRAIN_CURATED_URL = "https://zenodo.org/records/3612637/files/FSDKaggle2019.audio_train_curated.zip"
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@@ -29,12 +33,20 @@ _TRAIN_NOISY_URLS = [
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_TEST_URL = "https://zenodo.org/records/3612637/files/FSDKaggle2019.audio_test.zip"
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_METADATA_URL = "https://zenodo.org/records/3612637/files/FSDKaggle2019.meta.zip"
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class FSDKaggle2019Config(datasets.BuilderConfig):
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"""BuilderConfig for FSDKaggle2019."""
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def __init__(self, features, **kwargs):
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super(FSDKaggle2019Config, self).__init__(version=datasets.Version(
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self.features = features
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@@ -82,8 +94,16 @@ class FSDKaggle2019(datasets.GeneratorBasedBuilder):
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if self.config.name == 'curated':
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train_archive_path = dl_manager.download_and_extract(_TRAIN_CURATED_URL)
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elif self.config.name == 'noisy':
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-
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test_archive_path = dl_manager.download_and_extract(_TEST_URL)
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metadata_archive_path = dl_manager.download_and_extract(_METADATA_URL)
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@@ -148,3 +168,62 @@ def fast_scandir(path: str, exts: tp.List[str], recursive: bool = False):
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files.extend(f) # type: ignore
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return subfolders, files
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import os
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import requests
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import textwrap
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import datasets
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import itertools
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import typing as tp
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from pathlib import Path
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from copy import deepcopy
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from tqdm.auto import tqdm
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from ._fsd2019 import CLASSES
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VERSION = "0.0.1"
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SAMPLE_RATE = 44_100
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_TRAIN_CURATED_URL = "https://zenodo.org/records/3612637/files/FSDKaggle2019.audio_train_curated.zip"
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_TEST_URL = "https://zenodo.org/records/3612637/files/FSDKaggle2019.audio_test.zip"
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_METADATA_URL = "https://zenodo.org/records/3612637/files/FSDKaggle2019.meta.zip"
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# Cache location
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DEFAULT_XDG_CACHE_HOME = "~/.cache"
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XDG_CACHE_HOME = os.getenv("XDG_CACHE_HOME", DEFAULT_XDG_CACHE_HOME)
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DEFAULT_HF_CACHE_HOME = os.path.join(XDG_CACHE_HOME, "huggingface")
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HF_CACHE_HOME = os.path.expanduser(os.getenv("HF_HOME", DEFAULT_HF_CACHE_HOME))
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DEFAULT_HF_DATASETS_CACHE = os.path.join(HF_CACHE_HOME, "datasets")
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HF_DATASETS_CACHE = Path(os.getenv("HF_DATASETS_CACHE", DEFAULT_HF_DATASETS_CACHE))
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class FSDKaggle2019Config(datasets.BuilderConfig):
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"""BuilderConfig for FSDKaggle2019."""
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def __init__(self, features, **kwargs):
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super(FSDKaggle2019Config, self).__init__(version=datasets.Version(VERSION, ""), **kwargs)
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self.features = features
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if self.config.name == 'curated':
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train_archive_path = dl_manager.download_and_extract(_TRAIN_CURATED_URL)
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elif self.config.name == 'noisy':
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for zip_file_url in _TRAIN_NOISY_URLS:
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name = zip_file_url.split("/")[-1]
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download_file(
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zip_file_url,
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os.path.join('confit___fsdkaggle2019-script/noisy', VERSION, name)
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)
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_input_file = os.path.join('confit___fsdkaggle2019-script/noisy', VERSION, 'FSDKaggle2019.audio_train_noisy.zip')
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_output_file = os.path.join('confit___fsdkaggle2019-script/noisy', VERSION, 'FSDKaggle2019.audio_train_noisy.combine.zip')
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os.system(f"zip -F {_input_file} --out {_output_file}")
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train_archive_path = dl_manager.extract(_output_file)
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test_archive_path = dl_manager.download_and_extract(_TEST_URL)
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metadata_archive_path = dl_manager.download_and_extract(_METADATA_URL)
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files.extend(f) # type: ignore
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return subfolders, files
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def download_file(
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download_url, download_path, split_name, filename, resume_byte_pos=None
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):
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"""
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Download file from given URL
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Arguments
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---------
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download_url : str
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URL of file being downloaded
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download_path : str
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Full path of the file that is to be downloaded
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(or already downloaded)
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split_name : str
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Split name of the file being downloaded
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e.g. read_speech
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filename : str
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Filename of the file being downloaded
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resume_byte_pos: (int, optional)
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Starting byte position for resuming the download.
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Default is None, which means a fresh download.
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Returns
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-------
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bool
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If True, the file need not be downloaded again.
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Else the download might have failed or is incomplete.
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"""
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print("Downloading:", split_name, "=>", filename)
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resume_header = (
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{"Range": f"bytes={resume_byte_pos}-"} if resume_byte_pos else None
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)
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response = requests.get(download_url, headers=resume_header, stream=True)
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file_size = int(response.headers.get("Content-Length"))
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mode = "ab" if resume_byte_pos else "wb"
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initial_pos = resume_byte_pos if resume_byte_pos else 0
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with open(download_path, mode) as f:
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with tqdm(
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total=file_size,
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unit="B",
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unit_scale=True,
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unit_divisor=1024,
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initial=initial_pos,
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miniters=1,
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) as pbar:
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for chunk in response.iter_content(32 * 1024):
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f.write(chunk)
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pbar.update(len(chunk))
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# Validate downloaded file
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if validate_file(download_url, download_path):
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return True
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else:
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print("Download failed. Moving on.")
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return False
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