Move task information to loading script

raft.py

@@ -17,6 +17,7 @@
 import csv
 import json
 import os
+from pathlib import Path
 
 import datasets
 
@@ -45,10 +46,186 @@ _LICENSE = ""
 # 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)
 # This gets all folders within the directory named `data`
-DATA_DIRS = next(os.walk('data'))[1]
+DATA_DIR_URL = "data/"  # "https://huggingface.co/datasets/ought/raft/resolve/main/data/"
+# print([p for p in DATA_DIR_PATH.iterdir() if p.is_dir()])
+TASKS = {
+    "banking_77": {
+        "name": "banking_77",
+        "description": "",
+        "data_columns": ["Query", "ID"],
+        "label_columns": {
+            "Label": [
+                "Refund_not_showing_up",
+                "activate_my_card",
+                "age_limit",
+                "apple_pay_or_google_pay",
+                "atm_support",
+                "automatic_top_up",
+                "balance_not_updated_after_bank_transfer",
+                "balance_not_updated_after_cheque_or_cash_deposit",
+                "beneficiary_not_allowed",
+                "cancel_transfer",
+                "card_about_to_expire",
+                "card_acceptance",
+                "card_arrival",
+                "card_delivery_estimate",
+                "card_linking",
+                "card_not_working",
+                "card_payment_fee_charged",
+                "card_payment_not_recognised",
+                "card_payment_wrong_exchange_rate",
+                "card_swallowed",
+                "cash_withdrawal_charge",
+                "cash_withdrawal_not_recognised",
+                "change_pin",
+                "compromised_card",
+                "contactless_not_working",
+                "country_support",
+                "declined_card_payment",
+                "declined_cash_withdrawal",
+                "declined_transfer",
+                "direct_debit_payment_not_recognised",
+                "disposable_card_limits",
+                "edit_personal_details",
+                "exchange_charge",
+                "exchange_rate",
+                "exchange_via_app",
+                "extra_charge_on_statement",
+                "failed_transfer",
+                "fiat_currency_support",
+                "get_disposable_virtual_card",
+                "get_physical_card",
+                "getting_spare_card",
+                "getting_virtual_card",
+                "lost_or_stolen_card",
+                "lost_or_stolen_phone",
+                "order_physical_card",
+                "passcode_forgotten",
+                "pending_card_payment",
+                "pending_cash_withdrawal",
+                "pending_top_up",
+                "pending_transfer",
+                "pin_blocked",
+                "receiving_money",
+                "request_refund",
+                "reverted_card_payment?",
+                "supported_cards_and_currencies",
+                "terminate_account",
+                "top_up_by_bank_transfer_charge",
+                "top_up_by_card_charge",
+                "top_up_by_cash_or_cheque",
+                "top_up_failed",
+                "top_up_limits",
+                "top_up_reverted",
+                "topping_up_by_card",
+                "transaction_charged_twice",
+                "transfer_fee_charged",
+                "transfer_into_account",
+                "transfer_not_received_by_recipient",
+                "transfer_timing",
+                "unable_to_verify_identity",
+                "verify_my_identity",
+                "verify_source_of_funds",
+                "verify_top_up",
+                "virtual_card_not_working",
+                "visa_or_mastercard",
+                "why_verify_identity",
+                "wrong_amount_of_cash_received",
+                "wrong_exchange_rate_for_cash_withdrawal",
+            ]
+        },
+    },
+    "medical_subdomain_of_clinical_notes": {
+        "name": "medical_subdomain_of_clinical_notes",
+        "description": "",
+        "data_columns": ["Note", "ID"],
+        "label_columns": {
+            "Label": ["cardiology", "gastroenterology", "nephrology", "neurology", "psychiatry", "pulmonary disease"]
+        },
+    },
+    "overruling": {
+        "name": "overruling",
+        "description": "",
+        "data_columns": ["Sentence", "ID"],
+        "label_columns": {"Label": ["not overruling", "overruling"]},
+    },
+    "gpai_initiatives": {
+        "name": "gpai_initiatives",
+        "description": "",
+        "data_columns": [
+            "Name",
+            "Link",
+            "Organization / Author",
+            "Brief Description",
+            "Sector",
+            "Geographical scope",
+            "Target Audience",
+            "Stage of Development",
+            "Date started",
+            "Country/region of origin",
+            "Notes (including specific SDG(s) and OECD AI Principles addressed)",
+            "ID",
+        ],
+        "label_columns": {
+            "Label: AI and Ethics": ["0", "1"],
+            "Label: AI and Governance": ["0", "1"],
+            "Label: AI and Social Good": ["0", "1"],
+        },
+    },
+    "semiconductor_org_types": {
+        "name": "semiconductor_org_types",
+        "description": "",
+        "data_columns": ["Paper title", "Organization name", "ID"],
+        "label_columns": {"Label": ["company", "research institute", "university"]},
+    },
+    "twitter_complaints": {
+        "name": "twitter_complaints",
+        "description": "",
+        "data_columns": ["Tweet text", "ID"],
+        "label_columns": {"Label": ["complaint", "no complaint"]},
+    },
+    "neurips_impact_statement_risks": {
+        "name": "neurips_impact_statement_risks",
+        "description": "",
+        "data_columns": ["Paper title", "Paper link", "Impact statement", "ID"],
+        "label_columns": {"Label": ["doesn't mention a harmful application", "mentions a harmful application"]},
+    },
+    "systematic_review_inclusion": {
+        "name": "systematic_review_inclusion",
+        "description": "",
+        "data_columns": ["Title", "Abstract", "Authors", "Journal", "ID"],
+        "label_columns": {"Label": ["included", "not included"]},
+    },
+    "terms_of_service": {
+        "name": "terms_of_service",
+        "description": "",
+        "data_columns": ["Sentence", "ID"],
+        "label_columns": {"Label": ["not potentially unfair", "potentially unfair"]},
+    },
+    "tai_safety_research": {
+        "name": "tai_safety_research",
+        "description": "",
+        "data_columns": [
+            "Title",
+            "Abstract Note",
+            "Url",
+            "Publication Year",
+            "Item Type",
+            "Author",
+            "Publication Title",
+            "ID",
+        ],
+        "label_columns": {"Label": ["TAI safety research", "not TAI safety research"]},
+    },
+    "one_stop_english": {
+        "name": "one_stop_english",
+        "description": "",
+        "data_columns": ["Text", "ID"],
+        "label_columns": {"Label": ["advanced", "elementary", "intermediate"]},
+    },
+}
 
-_URLs = {s: {'train': f"data/{s}/train.csv",
-             'test': f"data/{s}/test_unlabeled.csv"} for s in DATA_DIRS}
+_URLs = {s: {"train": f"{DATA_DIR_URL}{s}/train.csv", "test": f"{DATA_DIR_URL}{s}/test_unlabeled.csv"} for s in TASKS}
 
 
 class Raft(datasets.GeneratorBasedBuilder):
@@ -67,36 +244,28 @@ class Raft(datasets.GeneratorBasedBuilder):
     # 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')
-
-    # TODO: Load task jsons
-
-    tasks = {}
-    for sd in DATA_DIRS:
-        with open(os.path.join('data', sd, 'task.json')) as f:
-            task_data = json.load(f)
-        tasks[sd] = task_data
-
     BUILDER_CONFIGS = []
-    for key in tasks:
-        td = tasks[key]
-        name = td['name']
-        description = td['description']
-        BUILDER_CONFIGS.append(datasets.BuilderConfig(name=name, version=VERSION,
-                                                      description=description))
 
-    DEFAULT_CONFIG_NAME = "tai_safety_research"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+    for key in TASKS:
+        td = TASKS[key]
+        name = td["name"]
+        description = td["description"]
+        BUILDER_CONFIGS.append(datasets.BuilderConfig(name=name, version=VERSION, description=description))
+
+    DEFAULT_CONFIG_NAME = (
+        "tai_safety_research"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+    )
 
     def _info(self):
         DEFAULT_LABEL_NAME = "Unlabeled"
 
-        task = Raft.tasks[self.config.name]
+        task = TASKS[self.config.name]
         # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
-        data_columns = {col_name: datasets.Value("string") for col_name in
-                        task['data_columns']}
+        data_columns = {col_name: datasets.Value("string") for col_name in task["data_columns"]}
 
         label_columns = {}
-        for label_name in task['label_columns']:
-            labels = ["Unlabeled"] + task['label_columns'][label_name]
+        for label_name in task["label_columns"]:
+            labels = ["Unlabeled"] + task["label_columns"][label_name]
             label_columns[label_name] = datasets.ClassLabel(len(labels), labels)
 
         # Merge dicts
@@ -130,27 +299,26 @@ class Raft(datasets.GeneratorBasedBuilder):
         data_dir = dl_manager.download_and_extract(_URLs)
         dataset = self.config.name.split("-")[0]
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN,
-                                    gen_kwargs={"filepath": data_dir[dataset]['train'],
-                                                "split": "train"}),
-            datasets.SplitGenerator(name=datasets.Split.TEST,
-                                    gen_kwargs={"filepath": data_dir[dataset]['test'],
-                                                "split": "test"})
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir[dataset]["train"], "split": "train"}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": data_dir[dataset]["test"], "split": "test"}
+            ),
         ]
 
     def _generate_examples(
-            self, filepath, split  # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+        self, filepath, split  # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     ):
-        """ Yields examples as (key, example) tuples. """
+        """Yields examples as (key, example) tuples."""
         # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
         # The `key` is here for legacy reason (tfds) and is not important in itself.
 
-        task = Raft.tasks[self.config.name]
-        labels = list(task['label_columns'])
+        task = TASKS[self.config.name]
+        labels = list(task["label_columns"])
 
         with open(filepath, encoding="utf-8") as f:
-            csv_reader = csv.reader(f, quotechar='"', delimiter=",",
-                                    quoting=csv.QUOTE_ALL, skipinitialspace=True)
+            csv_reader = csv.reader(f, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True)
             column_names = next(csv_reader)
             # Test csvs don't have any label columns.
             if split == "test":