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.gitattributes

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README.md

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----
-language:
-- af
-- am
-- ar
-- az
-- bn
-- cy
-- da
-- de
-- el
-- en
-- es
-- fa
-- fr
-- he
-- hi
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-- ja
-- jv
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-- ko
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-- zh
----

amazon-massive-dataset-1.0.tar.gz → af/amazon_massive_intent-test.parquet

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amazon_massive_intent.py

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-# coding=utf-8
-
-"""MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages"""
-
-import json
-import datasets
-import os
-
-logger = datasets.logging.get_logger(__name__)
-
-_DESCRIPTION = """\
-        MASSIVE is a parallel dataset of > 1M utterances across 51 languages with annotations
-        for the Natural Language Understanding tasks of intent prediction and slot annotation.
-        Utterances span 60 intents and include 55 slot types. MASSIVE was created by localizing
-        the SLURP dataset, composed of general Intelligent Voice Assistant single-shot interactions.
-"""
-_URL = "amazon-massive-dataset-1.0.tar.gz"
-
-
-_LANGUAGES = {
-    "af": "af-ZA",
-    "am": "am-ET",
-    "ar": "ar-SA",
-    "az": "az-AZ",
-    "bn": "bn-BD",
-    "cy": "cy-GB",
-    "da": "da-DK",
-    "de": "de-DE",
-    "el": "el-GR",
-    "en": "en-US",
-    "es": "es-ES",
-    "fa": "fa-IR",
-    "fi": "fi-FI",
-    "fr": "fr-FR",
-    "he": "he-IL",
-    "hi": "hi-IN",
-    "hu": "hu-HU",
-    "hy": "hy-AM",
-    "id": "id-ID",
-    "is": "is-IS",
-    "it": "it-IT",
-    "ja": "ja-JP",
-    "jv": "jv-ID",
-    "ka": "ka-GE",
-    "km": "km-KH",
-    "kn": "kn-IN",
-    "ko": "ko-KR",
-    "lv": "lv-LV",
-    "ml": "ml-IN",
-    "mn": "mn-MN",
-    "ms": "ms-MY",
-    "my": "my-MM",
-    "nb": "nb-NO",
-    "nl": "nl-NL",
-    "pl": "pl-PL",
-    "pt": "pt-PT",
-    "ro": "ro-RO",
-    "ru": "ru-RU",
-    "sl": "sl-SL",
-    "sq": "sq-AL",
-    "sv": "sv-SE",
-    "sw": "sw-KE",
-    "ta": "ta-IN",
-    "te": "te-IN",
-    "th": "th-TH",
-    "tl": "tl-PH",
-    "tr": "tr-TR",
-    "ur": "ur-PK",
-    "vi": "vi-VN",
-    "zh-CN": "zh-CN",
-    "zh-TW": "zh-TW",
-}
-
-_INTENTS = [
-    "datetime_query",
-    "iot_hue_lightchange",
-    "transport_ticket",
-    "takeaway_query",
-    "qa_stock",
-    "general_greet",
-    "recommendation_events",
-    "music_dislikeness",
-    "iot_wemo_off",
-    "cooking_recipe",
-    "qa_currency",
-    "transport_traffic",
-    "general_quirky",
-    "weather_query",
-    "audio_volume_up",
-    "email_addcontact",
-    "takeaway_order",
-    "email_querycontact",
-    "iot_hue_lightup",
-    "recommendation_locations",
-    "play_audiobook",
-    "lists_createoradd",
-    "news_query",
-    "alarm_query",
-    "iot_wemo_on",
-    "general_joke",
-    "qa_definition",
-    "social_query",
-    "music_settings",
-    "audio_volume_other",
-    "calendar_remove",
-    "iot_hue_lightdim",
-    "calendar_query",
-    "email_sendemail",
-    "iot_cleaning",
-    "audio_volume_down",
-    "play_radio",
-    "cooking_query",
-    "datetime_convert",
-    "qa_maths",
-    "iot_hue_lightoff",
-    "iot_hue_lighton",
-    "transport_query",
-    "music_likeness",
-    "email_query",
-    "play_music",
-    "audio_volume_mute",
-    "social_post",
-    "alarm_set",
-    "qa_factoid",
-    "calendar_set",
-    "play_game",
-    "alarm_remove",
-    "lists_remove",
-    "transport_taxi",
-    "recommendation_movies",
-    "iot_coffee",
-    "music_query",
-    "play_podcasts",
-    "lists_query",
-]
-
-
-class MASSIVE(datasets.GeneratorBasedBuilder):
-    """MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages"""
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name=name,
-            version=datasets.Version("1.0.0"),
-            description=f"The MASSIVE corpora for {name}",
-        )
-        for name in _LANGUAGES.keys()
-    ]
-
-    DEFAULT_CONFIG_NAME = "en"
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(names=_INTENTS),
-                    "label_text": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                },
-            ),
-            supervised_keys=None,
-            homepage="https://github.com/alexa/massive",
-            citation="_CITATION",
-            license="_LICENSE",
-        )
-
-    def _split_generators(self, dl_manager):
-
-        #   path = dl_manager.download_and_extract(_URL)
-        archive_path = dl_manager.download(_URL)
-        files = dl_manager.iter_archive(archive_path)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "files": files,
-                    "split": "train",
-                    "lang": self.config.name,
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "files": files,
-                    "split": "dev",
-                    "lang": self.config.name,
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "files": files,
-                    "split": "test",
-                    "lang": self.config.name,
-                },
-            ),
-        ]
-
-    def _generate_examples(self, files, split, lang):
-        filepath = "1.0/data/" + _LANGUAGES[lang] + ".jsonl"
-        logger.info("⏳ Generating examples from = %s", filepath)
-        for path, f in files:
-            if path == filepath:
-                lines = f.readlines()
-                key_ = 0
-                for line in lines:
-                    data = json.loads(line)
-                    if data["partition"] != split:
-                        continue
-                    yield key_, {
-                        "id": data["id"],
-                        "label": data["intent"],
-                        "label_text": data["intent"],
-                        "text": data["utt"],
-                    }
-                    key_ += 1

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