remove custom datasets (story_cloze) (#549)

* remove custom datasets (story_cloze)

* remove pkg

Author: VictorSanh

promptsource/custom_datasets/story_cloze/dataset_infos.json

@@ -1,7 +1,6 @@
 import re
 
 import datasets
-import pkg_resources
 import tensorflow as tf
 
 import promptsource.utils
@@ -64,13 +63,6 @@ def filter_fn(ex):
 
 
 def get_dataset_splits(dataset_name, subset_name=None):
-    # `datasets.get_dataset_infos` pulls infos from hf/datasets's master.
-    # story_cloze hasn't been merged yet (https://github.com/huggingface/datasets/pull/2907)
-    # This is a temporary fix to be able to do `import promptsource.seqio_tasks`
-    # Once PR 2907 is merged, we can remove this if condition (along with the `custom_datasets` folder)
-    # Also see `promptsource.utils.get_dataset_builder`
-    if dataset_name == "story_cloze":
-        dataset_name = pkg_resources.resource_filename("promptsource", "custom_datasets/story_cloze")
     info = datasets.get_dataset_infos(dataset_name)
     subset_name = subset_name or list(info.keys())[0]
     return info[subset_name].splits

promptsource/custom_datasets/story_cloze/story_cloze.py

@@ -1,7 +1,6 @@
 # coding=utf-8
 
 import datasets
-import pkg_resources
 import requests
 
 from promptsource.templates import INCLUDED_USERS
@@ -34,13 +33,6 @@ def renameDatasetColumn(dataset):
 
 def get_dataset_builder(path, conf=None):
     "Get a dataset builder from name and conf."
-    # `datasets.load.prepare_module` pulls infos from hf/datasets's master.
-    # story_cloze hasn't been merged yet (https://github.com/huggingface/datasets/pull/2907)
-    # This is a temporary fix for the tests (more specifically test_templates.py)
-    # Once PR 2907 is merged, we can remove this if condition (along with the `custom_datasets` folder)
-    # Also see `promptsource.seqio_tasks.utils.get_dataset_splits`
-    if path == "story_cloze":
-        path = pkg_resources.resource_filename("promptsource", "custom_datasets/story_cloze")
     module_path = datasets.load.prepare_module(path, dataset=True)
     builder_cls = datasets.load.import_main_class(module_path[0], dataset=True)
     if conf: