fix skip download feature

binding_affinity.py

@@ -34,7 +34,7 @@ year={2021}
 # TODO: Add description of the dataset here
 # You can copy an official description
 _DESCRIPTION = """\
-A dataset to refine language models on protein-ligand binding affinity prediction.
+A dataset to fine-tune language models on protein-ligand binding affinity prediction.
 """
 
 # TODO: Add a link to an official homepage for the dataset here
@@ -47,9 +47,9 @@ _LICENSE = "BSD two-clause"
 # The HuggingFace dataset library don't host the datasets but only point to the original files
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 _URL = "https://huggingface.co/datasets/jglaser/binding_affinity/resolve/main/"
-
-_file_names = {'default': 'data/all.parquet',
-               'no_kras': 'data/all_nokras.parquet'}
+_data_dir = "data/"
+_file_names = {'default': _data_dir+'all.parquet',
+               'no_kras': _data_dir+'all_nokras.parquet'}
 
 _URLs = {name: _URL+_file_names[name] for name in _file_names}
 
@@ -60,23 +60,6 @@ class BindingAffinity(datasets.ArrowBasedBuilder):
 
     VERSION = datasets.Version("1.1.0")
 
-    # If you don't want/need to define several sub-sets in your dataset,
-    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
-
-    # If you need to make complex sub-parts in the datasets with configurable options
-    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
-    # BUILDER_CONFIG_CLASS = MyBuilderConfig
-
-    # You will be able to load one or the other configurations in the following list with
-    # data = datasets.load_dataset('my_dataset', 'first_domain')
-    # data = datasets.load_dataset('my_dataset', 'second_domain')
-    # BUILDER_CONFIGS = [
-    #    datasets.BuilderConfig(name="first_domain", version=VERSION, description="This part of my dataset covers a first domain"),
-    #    datasets.BuilderConfig(name="second_domain", version=VERSION, description="This part of my dataset covers a second domain"),
-    #]
-
-    #DEFAULT_CONFIG_NAME = "affinities"  # It's not mandatory to have a default configuration. Just use one if it make sense.
-
     def _info(self):
         # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
         #if self.config.name == "first_domain":  # This is the name of the configuration selected in BUILDER_CONFIGS above
@@ -125,11 +108,12 @@ class BindingAffinity(datasets.ArrowBasedBuilder):
         # 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
-        files = _file_names
-        try:
+        import os
+        if os.path.exists(dl_manager._base_path):
+            # this is a hack to force the use of the local copy
+            files = dl_manager.download_and_extract({fn: os.path.join(dl_manager._base_path, _file_names[fn]) for fn in _file_names})
+        else:
             files = dl_manager.download_and_extract(_URLs)
-        except:
-            pass
 
         return [
             datasets.SplitGenerator(
@@ -156,5 +140,4 @@ class BindingAffinity(datasets.ArrowBasedBuilder):
         local = fs.LocalFileSystem()
 
         for i, f in enumerate([filepath]):
-            print(f)
             yield i, pq.read_table(f,filesystem=local)