Convert dataset to Parquet (#3)

- Convert dataset to Parquet (7460f81f4375cfb9b5087b5ea2c4233773262e85)
- Delete loading script (c8399e588cc0b891a4ddaf60ae5bc6327461e065)

CSRestaurants/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4a4b571b009305d9284b4320834ce51a76eb8695afc84435750c80caa2a09dc8
+size 50096

CSRestaurants/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9238f3610ea85353232436aac6f45692e22fdb0ff2195f386f355df8961224c4
+size 185914

CSRestaurants/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c2a6a44b0b86ea8725190f1643340e21459d5f0808fbb6f4b71410cdaa7735ee
+size 46784

README.md

@@ -27,28 +27,38 @@ pretty_name: Czech Restaurant
 tags:
 - intent-to-text
 dataset_info:
+  config_name: CSRestaurants
   features:
-  - name: dialogue_act
+  - name: da
     dtype: string
-  - name: delexicalized_dialogue_act
+  - name: delex_da
     dtype: string
   - name: text
     dtype: string
-  - name: delexicalized_text
+  - name: delex_text
     dtype: string
-  config_name: CSRestaurants
   splits:
   - name: train
-    num_bytes: 654071
+    num_bytes: 654055
     num_examples: 3569
   - name: validation
-    num_bytes: 181528
+    num_bytes: 181512
     num_examples: 781
   - name: test
-    num_bytes: 191334
+    num_bytes: 191318
     num_examples: 842
-  download_size: 1463019
-  dataset_size: 1026933
+  download_size: 282794
+  dataset_size: 1026885
+configs:
+- config_name: CSRestaurants
+  data_files:
+  - split: train
+    path: CSRestaurants/train-*
+  - split: validation
+    path: CSRestaurants/validation-*
+  - split: test
+    path: CSRestaurants/test-*
+  default: true
 ---
 
 # Dataset Card for Czech Restaurant

cs_restaurants.py

@@ -1,102 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""Czech restaurant information dataset for NLG"""
-
-
-import json
-
-import datasets
-
-
-# Find for instance the citation on arxiv or on the dataset repo/website
-_CITATION = """\
-@article{DBLP:journals/corr/abs-1910-05298,
-  author    = {Ondrej Dusek and
-               Filip Jurcicek},
-  title     = {Neural Generation for Czech: Data and Baselines},
-  journal   = {CoRR},
-  volume    = {abs/1910.05298},
-  year      = {2019},
-  url       = {http://arxiv.org/abs/1910.05298},
-  archivePrefix = {arXiv},
-  eprint    = {1910.05298},
-  timestamp = {Wed, 16 Oct 2019 16:25:53 +0200},
-  biburl    = {https://dblp.org/rec/journals/corr/abs-1910-05298.bib},
-  bibsource = {dblp computer science bibliography, https://dblp.org}
-}
-"""
-
-_DESCRIPTION = """\
-This is a dataset for NLG in task-oriented spoken dialogue systems with Czech as the target language. It originated as
-a translation of the English San Francisco Restaurants dataset by Wen et al. (2015).
-"""
-
-_LICENSE = "Creative Commons 4.0 BY-SA"
-
-_URLs = {
-    "CSRestaurants": "https://raw.githubusercontent.com/UFAL-DSG/cs_restaurant_dataset/master/",
-}
-
-
-class CSRestaurants(datasets.GeneratorBasedBuilder):
-    """Czech restaurant information dataset for NLG"""
-
-    VERSION = datasets.Version("1.0.0")
-    BUILDER_CONFIGS = [datasets.BuilderConfig(name="CSRestaurants", description="NLG data for Czech")]
-    DEFAULT_CONFIG_NAME = "CSRestaurants"
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "da": datasets.Value("string"),
-                "delex_da": datasets.Value("string"),
-                "text": datasets.Value("string"),
-                "delex_text": datasets.Value("string"),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage="https://github.com/UFAL-DSG/cs_restaurant_dataset",
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        master_url = _URLs[self.config.name]
-        train_path = dl_manager.download_and_extract(master_url + "train.json")
-        valid_path = dl_manager.download_and_extract(master_url + "devel.json")
-        test_path = dl_manager.download_and_extract(master_url + "test.json")
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": valid_path}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-
-        with open(filepath, encoding="utf8") as f:
-            data = json.load(f)
-            for id_, instance in enumerate(data):
-                yield id_, {
-                    "da": instance["da"],
-                    "delex_da": instance["delex_da"],
-                    "text": instance["text"],
-                    "delex_text": instance["delex_text"],
-                }