Convert dataset to Parquet (#5)

- Convert dataset to Parquet (79cc05a408d566ef67222afd05c4728032295384)
- Add plus data files (3731e6933c98beb3bb53342ff11518de99c22f71)
- Add small data files (c78dcdda8e141f0572e2664fa901140c9a3a602f)
- Delete loading script (161a65568f7f274a37e586b41e743a85ee8a48aa)
- Delete data file (c0f23d8450ff2747ae8ccce9f93f659ec885bf07)
- Delete data file (23d3c66a0090ce1f613643e327fc3e4b1ac012ba)
- Delete data file (76be542076d36165b3b9fc8ce0d6d15a0d1b1875)

README.md

@@ -189,7 +189,7 @@ dataset_info:
   - name: test
     num_bytes: 286966
     num_examples: 5500
-  download_size: 246833
+  download_size: 441918
   dataset_size: 994165
 - config_name: plus
   features:
@@ -360,7 +360,7 @@ dataset_info:
   - name: test
     num_bytes: 286966
     num_examples: 5500
-  download_size: 291179
+  download_size: 525729
   dataset_size: 1238511
 - config_name: small
   features:
@@ -531,8 +531,33 @@ dataset_info:
   - name: test
     num_bytes: 286966
     num_examples: 5500
-  download_size: 216522
+  download_size: 385185
   dataset_size: 841388
+configs:
+- config_name: imbalanced
+  data_files:
+  - split: train
+    path: imbalanced/train-*
+  - split: validation
+    path: imbalanced/validation-*
+  - split: test
+    path: imbalanced/test-*
+- config_name: plus
+  data_files:
+  - split: train
+    path: plus/train-*
+  - split: validation
+    path: plus/validation-*
+  - split: test
+    path: plus/test-*
+- config_name: small
+  data_files:
+  - split: train
+    path: small/train-*
+  - split: validation
+    path: small/validation-*
+  - split: test
+    path: small/test-*
 ---
 
 # Dataset Card for CLINC150

clinc_oos.py

@@ -1,275 +0,0 @@
-"""An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction"""
-
-
-import json
-import textwrap
-
-import datasets
-
-
-_CITATION = """\
-    @inproceedings{larson-etal-2019-evaluation,
-    title = "An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction",
-    author = "Larson, Stefan  and
-      Mahendran, Anish  and
-      Peper, Joseph J.  and
-      Clarke, Christopher  and
-      Lee, Andrew  and
-      Hill, Parker  and
-      Kummerfeld, Jonathan K.  and
-      Leach, Kevin  and
-      Laurenzano, Michael A.  and
-      Tang, Lingjia  and
-      Mars, Jason",
-    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
-    year = "2019",
-    url = "https://www.aclweb.org/anthology/D19-1131"
-}
-"""
-
-_DESCRIPTION = """\
-    This dataset is for evaluating the performance of intent classification systems in the
-    presence of "out-of-scope" queries. By "out-of-scope", we mean queries that do not fall
-    into any of the system-supported intent classes. Most datasets include only data that is
-    "in-scope". Our dataset includes both in-scope and out-of-scope data. You might also know
-    the term "out-of-scope" by other terms, including "out-of-domain" or "out-of-distribution".
-"""
-
-_DESCRIPTIONS = {
-    "small": textwrap.dedent(
-        """\
-        Small, in which there are only 50 training queries per each in-scope intent
-        """
-    ),
-    "imbalanced": textwrap.dedent(
-        """\
-        Imbalanced, in which intents have either 25, 50, 75, or 100 training queries.
-        """
-    ),
-    "plus": textwrap.dedent(
-        """\
-        OOS+, in which there are 250 out-of-scope training examples, rather than 100.
-        """
-    ),
-}
-
-_URL = "https://github.com/clinc/oos-eval/"
-
-# Source:
-# - https://raw.githubusercontent.com/clinc/oos-eval/master/data/data_small.json
-# - https://raw.githubusercontent.com/clinc/oos-eval/master/data/data_imbalanced.json
-# - https://raw.githubusercontent.com/clinc/oos-eval/master/data/data_oos_plus.json
-_DATA_URLS = {
-    "small": "data/data_small.json.gz",
-    "imbalanced": "data/data_imbalanced.json.gz",
-    "plus": "data/data_oos_plus.json.gz",
-}
-
-
-class ClincConfig(datasets.BuilderConfig):
-
-    """BuilderConfig for CLINC150"""
-
-    def __init__(self, description, data_url, citation, url, **kwrags):
-        """
-        Args:
-            description: `string`, brief description of the dataset
-            data_url: `dictionary`, dict with url for each split of data.
-            citation: `string`, citation for the dataset.
-            url: `string`, url for information about the dataset.
-            **kwrags: keyword arguments frowarded to super
-        """
-        super(ClincConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwrags)
-        self.description = description
-        self.data_url = data_url
-        self.citation = citation
-        self.url = url
-
-
-class ClincOos(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        ClincConfig(
-            name=name, description=_DESCRIPTIONS[name], data_url=_DATA_URLS[name], citation=_CITATION, url=_URL
-        )
-        for name in ["small", "imbalanced", "plus"]
-    ]
-
-    def _info(self):
-        features = {}
-        features["text"] = datasets.Value("string")
-        labels_list = [
-            "restaurant_reviews",
-            "nutrition_info",
-            "account_blocked",
-            "oil_change_how",
-            "time",
-            "weather",
-            "redeem_rewards",
-            "interest_rate",
-            "gas_type",
-            "accept_reservations",
-            "smart_home",
-            "user_name",
-            "report_lost_card",
-            "repeat",
-            "whisper_mode",
-            "what_are_your_hobbies",
-            "order",
-            "jump_start",
-            "schedule_meeting",
-            "meeting_schedule",
-            "freeze_account",
-            "what_song",
-            "meaning_of_life",
-            "restaurant_reservation",
-            "traffic",
-            "make_call",
-            "text",
-            "bill_balance",
-            "improve_credit_score",
-            "change_language",
-            "no",
-            "measurement_conversion",
-            "timer",
-            "flip_coin",
-            "do_you_have_pets",
-            "balance",
-            "tell_joke",
-            "last_maintenance",
-            "exchange_rate",
-            "uber",
-            "car_rental",
-            "credit_limit",
-            "oos",
-            "shopping_list",
-            "expiration_date",
-            "routing",
-            "meal_suggestion",
-            "tire_change",
-            "todo_list",
-            "card_declined",
-            "rewards_balance",
-            "change_accent",
-            "vaccines",
-            "reminder_update",
-            "food_last",
-            "change_ai_name",
-            "bill_due",
-            "who_do_you_work_for",
-            "share_location",
-            "international_visa",
-            "calendar",
-            "translate",
-            "carry_on",
-            "book_flight",
-            "insurance_change",
-            "todo_list_update",
-            "timezone",
-            "cancel_reservation",
-            "transactions",
-            "credit_score",
-            "report_fraud",
-            "spending_history",
-            "directions",
-            "spelling",
-            "insurance",
-            "what_is_your_name",
-            "reminder",
-            "where_are_you_from",
-            "distance",
-            "payday",
-            "flight_status",
-            "find_phone",
-            "greeting",
-            "alarm",
-            "order_status",
-            "confirm_reservation",
-            "cook_time",
-            "damaged_card",
-            "reset_settings",
-            "pin_change",
-            "replacement_card_duration",
-            "new_card",
-            "roll_dice",
-            "income",
-            "taxes",
-            "date",
-            "who_made_you",
-            "pto_request",
-            "tire_pressure",
-            "how_old_are_you",
-            "rollover_401k",
-            "pto_request_status",
-            "how_busy",
-            "application_status",
-            "recipe",
-            "calendar_update",
-            "play_music",
-            "yes",
-            "direct_deposit",
-            "credit_limit_change",
-            "gas",
-            "pay_bill",
-            "ingredients_list",
-            "lost_luggage",
-            "goodbye",
-            "what_can_i_ask_you",
-            "book_hotel",
-            "are_you_a_bot",
-            "next_song",
-            "change_speed",
-            "plug_type",
-            "maybe",
-            "w2",
-            "oil_change_when",
-            "thank_you",
-            "shopping_list_update",
-            "pto_balance",
-            "order_checks",
-            "travel_alert",
-            "fun_fact",
-            "sync_device",
-            "schedule_maintenance",
-            "apr",
-            "transfer",
-            "ingredient_substitution",
-            "calories",
-            "current_location",
-            "international_fees",
-            "calculator",
-            "definition",
-            "next_holiday",
-            "update_playlist",
-            "mpg",
-            "min_payment",
-            "change_user_name",
-            "restaurant_suggestion",
-            "travel_notification",
-            "cancel",
-            "pto_used",
-            "travel_suggestion",
-            "change_volume",
-        ]
-        features["intent"] = datasets.ClassLabel(names=labels_list)
-
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION + "\n" + self.config.description,
-            features=datasets.Features(features),
-            homepage=self.config.url,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        file_ = dl_manager.download_and_extract(self.config.data_url)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": file_, "split": "train"}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": file_, "split": "val"}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": file_, "split": "test"}),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        with open(filepath, encoding="utf-8") as f:
-            j = json.load(f)
-            for id_, row in enumerate(j[split] + j["oos_" + split]):
-                yield id_, {"text": row[0], "intent": row[1]}

data/data_imbalanced.json.gz → imbalanced/test-00000-of-00001.parquet

@@ -1,3 +1,3 @@
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-size 246833
+oid sha256:3e60e45b25bf86543aa5df8ba4fcc674114164e6184f0197690648c2908d0102
+size 135844

data/data_oos_plus.json.gz → imbalanced/train-00000-of-00001.parquet

@@ -1,3 +1,3 @@
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-size 291179
+oid sha256:c9a2315625025628a812c0d8788a822518eacb25898edc2febb08e3b800f1251
+size 228285

data/data_small.json.gz → imbalanced/validation-00000-of-00001.parquet

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+size 77789

plus/test-00000-of-00001.parquet

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+size 135844

plus/train-00000-of-00001.parquet

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plus/validation-00000-of-00001.parquet

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small/test-00000-of-00001.parquet

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small/train-00000-of-00001.parquet

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small/validation-00000-of-00001.parquet

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