MichaelR207
commited on
Commit
•
b34b79d
1
Parent(s):
349ca84
Fix MultiSim.py to download large files properly from huggingface
Browse files- MultiSim.py +16 -24
MultiSim.py
CHANGED
@@ -18,6 +18,7 @@ import pandas as pd
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import os
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from collections import defaultdict
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import urllib.parse
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import datasets
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@@ -300,34 +301,27 @@ class MultiSim(datasets.GeneratorBasedBuilder):
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# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
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# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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if (self.config.name == 'all'):
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for subcorpus in _SUBCORPORA:
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-
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download_urls[subcorpus + "-test"] = _URLS[subcorpus+"-test"]
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download_urls[subcorpus + "-val"] = _URLS[subcorpus+"-val"]
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elif (self.config.name in _LANGUAGES):
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lang_code = _LANGUAGES[self.config.name]
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for subcorpus in _SUBCORPORA:
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if _SUBCORPORA[subcorpus]['language'] == lang_code:
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-
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download_urls[subcorpus + "-test"] = _URLS[subcorpus+"-test"]
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download_urls[subcorpus + "-val"] = _URLS[subcorpus+"-val"]
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elif (self.config.name in _SUBCORPORA):
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download_urls[self.config.name + "-test"] = _URLS[self.config.name+"-test"]
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download_urls[self.config.name + "-val"] = _URLS[self.config.name+"-val"]
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else:
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print("Invalid configuration name: " + self.config.name + ". Try 'all', 'English', 'ASSET', etc.")
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-
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downloaded_files = dl_manager.download_and_extract(download_urls)
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-
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepaths":
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"split": "train",
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},
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),
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@@ -335,7 +329,7 @@ class MultiSim(datasets.GeneratorBasedBuilder):
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name=datasets.Split.VALIDATION,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepaths":
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"split": "val",
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},
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),
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@@ -343,7 +337,7 @@ class MultiSim(datasets.GeneratorBasedBuilder):
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name=datasets.Split.TEST,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepaths":
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"split": "test"
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},
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),
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@@ -355,18 +349,16 @@ class MultiSim(datasets.GeneratorBasedBuilder):
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# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
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df = pd.DataFrame()
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if (len(filepaths
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for
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if os.path.exists(
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df = pd.concat([df, pd.read_csv(path)])
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# shuffle the combined dataset
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df = df.sample(frac=1, random_state=3600).reset_index(drop=True)
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else:
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df = pd.read_csv(filepaths[dataset])
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if len(df) > 0:
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for key, row in df.iterrows():
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import os
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from collections import defaultdict
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import urllib.parse
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+
from huggingface_hub import snapshot_download
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import datasets
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# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
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# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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dataset_path = snapshot_download(repo_id="MichaelR207/MultiSim", repo_type="dataset")
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+
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filepaths = []
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if (self.config.name == 'all'):
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for subcorpus in _SUBCORPORA:
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filepaths.append(os.path.join(dataset_path,_SUBCORPORA[subcorpus]['path']))
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elif (self.config.name in _LANGUAGES):
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lang_code = _LANGUAGES[self.config.name]
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for subcorpus in _SUBCORPORA:
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if _SUBCORPORA[subcorpus]['language'] == lang_code:
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filepaths.append(os.path.join(dataset_path,_SUBCORPORA[subcorpus]['path']))
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elif (self.config.name in _SUBCORPORA):
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filepaths = [os.path.join(dataset_path,_SUBCORPORA[self.config.name]['path'])]
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else:
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print("Invalid configuration name: " + self.config.name + ". Try 'all', 'English', 'ASSET', etc.")
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepaths": filepaths,
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"split": "train",
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},
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),
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name=datasets.Split.VALIDATION,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepaths": filepaths,
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"split": "val",
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},
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),
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name=datasets.Split.TEST,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepaths": filepaths,
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"split": "test"
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},
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),
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# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
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df = pd.DataFrame()
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if (len(filepaths) > 1):
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for filepath in filepaths:
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if os.path.exists(filepath + "_" + split + ".csv"):
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df = pd.concat([df, pd.read_csv(filepath + "_" + split + ".csv")])
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# shuffle the combined dataset
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df = df.sample(frac=1, random_state=3600).reset_index(drop=True)
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else:
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if os.path.exists(filepaths[0] + "_" + split + ".csv"):
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df = pd.read_csv(filepaths[0] + "_" + split + ".csv")
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if len(df) > 0:
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for key, row in df.iterrows():
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