Fix MultiSim.py to download large files properly from huggingface

MultiSim.py

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