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lewtun HF staff commited on
Commit
fe8663f
1 Parent(s): 7a16153

Move task information to loading script

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Files changed (1) hide show
  1. raft.py +204 -36
raft.py CHANGED
@@ -17,6 +17,7 @@
17
  import csv
18
  import json
19
  import os
 
20
 
21
  import datasets
22
 
@@ -45,10 +46,186 @@ _LICENSE = ""
45
  # The HuggingFace dataset library don't host the datasets but only point to the original files
46
  # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
47
  # This gets all folders within the directory named `data`
48
- DATA_DIRS = next(os.walk('data'))[1]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
49
 
50
- _URLs = {s: {'train': f"data/{s}/train.csv",
51
- 'test': f"data/{s}/test_unlabeled.csv"} for s in DATA_DIRS}
52
 
53
 
54
  class Raft(datasets.GeneratorBasedBuilder):
@@ -67,36 +244,28 @@ class Raft(datasets.GeneratorBasedBuilder):
67
  # You will be able to load one or the other configurations in the following list with
68
  # data = datasets.load_dataset('my_dataset', 'first_domain')
69
  # data = datasets.load_dataset('my_dataset', 'second_domain')
70
-
71
- # TODO: Load task jsons
72
-
73
- tasks = {}
74
- for sd in DATA_DIRS:
75
- with open(os.path.join('data', sd, 'task.json')) as f:
76
- task_data = json.load(f)
77
- tasks[sd] = task_data
78
-
79
  BUILDER_CONFIGS = []
80
- for key in tasks:
81
- td = tasks[key]
82
- name = td['name']
83
- description = td['description']
84
- BUILDER_CONFIGS.append(datasets.BuilderConfig(name=name, version=VERSION,
85
- description=description))
86
 
87
- DEFAULT_CONFIG_NAME = "tai_safety_research" # It's not mandatory to have a default configuration. Just use one if it make sense.
 
 
 
 
 
 
 
 
88
 
89
  def _info(self):
90
  DEFAULT_LABEL_NAME = "Unlabeled"
91
 
92
- task = Raft.tasks[self.config.name]
93
  # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
94
- data_columns = {col_name: datasets.Value("string") for col_name in
95
- task['data_columns']}
96
 
97
  label_columns = {}
98
- for label_name in task['label_columns']:
99
- labels = ["Unlabeled"] + task['label_columns'][label_name]
100
  label_columns[label_name] = datasets.ClassLabel(len(labels), labels)
101
 
102
  # Merge dicts
@@ -130,27 +299,26 @@ class Raft(datasets.GeneratorBasedBuilder):
130
  data_dir = dl_manager.download_and_extract(_URLs)
131
  dataset = self.config.name.split("-")[0]
132
  return [
133
- datasets.SplitGenerator(name=datasets.Split.TRAIN,
134
- gen_kwargs={"filepath": data_dir[dataset]['train'],
135
- "split": "train"}),
136
- datasets.SplitGenerator(name=datasets.Split.TEST,
137
- gen_kwargs={"filepath": data_dir[dataset]['test'],
138
- "split": "test"})
139
  ]
140
 
141
  def _generate_examples(
142
- self, filepath, split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
143
  ):
144
- """ Yields examples as (key, example) tuples. """
145
  # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
146
  # The `key` is here for legacy reason (tfds) and is not important in itself.
147
 
148
- task = Raft.tasks[self.config.name]
149
- labels = list(task['label_columns'])
150
 
151
  with open(filepath, encoding="utf-8") as f:
152
- csv_reader = csv.reader(f, quotechar='"', delimiter=",",
153
- quoting=csv.QUOTE_ALL, skipinitialspace=True)
154
  column_names = next(csv_reader)
155
  # Test csvs don't have any label columns.
156
  if split == "test":
 
17
  import csv
18
  import json
19
  import os
20
+ from pathlib import Path
21
 
22
  import datasets
23
 
 
46
  # The HuggingFace dataset library don't host the datasets but only point to the original files
47
  # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
48
  # This gets all folders within the directory named `data`
49
+ DATA_DIR_URL = "data/" # "https://huggingface.co/datasets/ought/raft/resolve/main/data/"
50
+ # print([p for p in DATA_DIR_PATH.iterdir() if p.is_dir()])
51
+ TASKS = {
52
+ "banking_77": {
53
+ "name": "banking_77",
54
+ "description": "",
55
+ "data_columns": ["Query", "ID"],
56
+ "label_columns": {
57
+ "Label": [
58
+ "Refund_not_showing_up",
59
+ "activate_my_card",
60
+ "age_limit",
61
+ "apple_pay_or_google_pay",
62
+ "atm_support",
63
+ "automatic_top_up",
64
+ "balance_not_updated_after_bank_transfer",
65
+ "balance_not_updated_after_cheque_or_cash_deposit",
66
+ "beneficiary_not_allowed",
67
+ "cancel_transfer",
68
+ "card_about_to_expire",
69
+ "card_acceptance",
70
+ "card_arrival",
71
+ "card_delivery_estimate",
72
+ "card_linking",
73
+ "card_not_working",
74
+ "card_payment_fee_charged",
75
+ "card_payment_not_recognised",
76
+ "card_payment_wrong_exchange_rate",
77
+ "card_swallowed",
78
+ "cash_withdrawal_charge",
79
+ "cash_withdrawal_not_recognised",
80
+ "change_pin",
81
+ "compromised_card",
82
+ "contactless_not_working",
83
+ "country_support",
84
+ "declined_card_payment",
85
+ "declined_cash_withdrawal",
86
+ "declined_transfer",
87
+ "direct_debit_payment_not_recognised",
88
+ "disposable_card_limits",
89
+ "edit_personal_details",
90
+ "exchange_charge",
91
+ "exchange_rate",
92
+ "exchange_via_app",
93
+ "extra_charge_on_statement",
94
+ "failed_transfer",
95
+ "fiat_currency_support",
96
+ "get_disposable_virtual_card",
97
+ "get_physical_card",
98
+ "getting_spare_card",
99
+ "getting_virtual_card",
100
+ "lost_or_stolen_card",
101
+ "lost_or_stolen_phone",
102
+ "order_physical_card",
103
+ "passcode_forgotten",
104
+ "pending_card_payment",
105
+ "pending_cash_withdrawal",
106
+ "pending_top_up",
107
+ "pending_transfer",
108
+ "pin_blocked",
109
+ "receiving_money",
110
+ "request_refund",
111
+ "reverted_card_payment?",
112
+ "supported_cards_and_currencies",
113
+ "terminate_account",
114
+ "top_up_by_bank_transfer_charge",
115
+ "top_up_by_card_charge",
116
+ "top_up_by_cash_or_cheque",
117
+ "top_up_failed",
118
+ "top_up_limits",
119
+ "top_up_reverted",
120
+ "topping_up_by_card",
121
+ "transaction_charged_twice",
122
+ "transfer_fee_charged",
123
+ "transfer_into_account",
124
+ "transfer_not_received_by_recipient",
125
+ "transfer_timing",
126
+ "unable_to_verify_identity",
127
+ "verify_my_identity",
128
+ "verify_source_of_funds",
129
+ "verify_top_up",
130
+ "virtual_card_not_working",
131
+ "visa_or_mastercard",
132
+ "why_verify_identity",
133
+ "wrong_amount_of_cash_received",
134
+ "wrong_exchange_rate_for_cash_withdrawal",
135
+ ]
136
+ },
137
+ },
138
+ "medical_subdomain_of_clinical_notes": {
139
+ "name": "medical_subdomain_of_clinical_notes",
140
+ "description": "",
141
+ "data_columns": ["Note", "ID"],
142
+ "label_columns": {
143
+ "Label": ["cardiology", "gastroenterology", "nephrology", "neurology", "psychiatry", "pulmonary disease"]
144
+ },
145
+ },
146
+ "overruling": {
147
+ "name": "overruling",
148
+ "description": "",
149
+ "data_columns": ["Sentence", "ID"],
150
+ "label_columns": {"Label": ["not overruling", "overruling"]},
151
+ },
152
+ "gpai_initiatives": {
153
+ "name": "gpai_initiatives",
154
+ "description": "",
155
+ "data_columns": [
156
+ "Name",
157
+ "Link",
158
+ "Organization / Author",
159
+ "Brief Description",
160
+ "Sector",
161
+ "Geographical scope",
162
+ "Target Audience",
163
+ "Stage of Development",
164
+ "Date started",
165
+ "Country/region of origin",
166
+ "Notes (including specific SDG(s) and OECD AI Principles addressed)",
167
+ "ID",
168
+ ],
169
+ "label_columns": {
170
+ "Label: AI and Ethics": ["0", "1"],
171
+ "Label: AI and Governance": ["0", "1"],
172
+ "Label: AI and Social Good": ["0", "1"],
173
+ },
174
+ },
175
+ "semiconductor_org_types": {
176
+ "name": "semiconductor_org_types",
177
+ "description": "",
178
+ "data_columns": ["Paper title", "Organization name", "ID"],
179
+ "label_columns": {"Label": ["company", "research institute", "university"]},
180
+ },
181
+ "twitter_complaints": {
182
+ "name": "twitter_complaints",
183
+ "description": "",
184
+ "data_columns": ["Tweet text", "ID"],
185
+ "label_columns": {"Label": ["complaint", "no complaint"]},
186
+ },
187
+ "neurips_impact_statement_risks": {
188
+ "name": "neurips_impact_statement_risks",
189
+ "description": "",
190
+ "data_columns": ["Paper title", "Paper link", "Impact statement", "ID"],
191
+ "label_columns": {"Label": ["doesn't mention a harmful application", "mentions a harmful application"]},
192
+ },
193
+ "systematic_review_inclusion": {
194
+ "name": "systematic_review_inclusion",
195
+ "description": "",
196
+ "data_columns": ["Title", "Abstract", "Authors", "Journal", "ID"],
197
+ "label_columns": {"Label": ["included", "not included"]},
198
+ },
199
+ "terms_of_service": {
200
+ "name": "terms_of_service",
201
+ "description": "",
202
+ "data_columns": ["Sentence", "ID"],
203
+ "label_columns": {"Label": ["not potentially unfair", "potentially unfair"]},
204
+ },
205
+ "tai_safety_research": {
206
+ "name": "tai_safety_research",
207
+ "description": "",
208
+ "data_columns": [
209
+ "Title",
210
+ "Abstract Note",
211
+ "Url",
212
+ "Publication Year",
213
+ "Item Type",
214
+ "Author",
215
+ "Publication Title",
216
+ "ID",
217
+ ],
218
+ "label_columns": {"Label": ["TAI safety research", "not TAI safety research"]},
219
+ },
220
+ "one_stop_english": {
221
+ "name": "one_stop_english",
222
+ "description": "",
223
+ "data_columns": ["Text", "ID"],
224
+ "label_columns": {"Label": ["advanced", "elementary", "intermediate"]},
225
+ },
226
+ }
227
 
228
+ _URLs = {s: {"train": f"{DATA_DIR_URL}{s}/train.csv", "test": f"{DATA_DIR_URL}{s}/test_unlabeled.csv"} for s in TASKS}
 
229
 
230
 
231
  class Raft(datasets.GeneratorBasedBuilder):
 
244
  # You will be able to load one or the other configurations in the following list with
245
  # data = datasets.load_dataset('my_dataset', 'first_domain')
246
  # data = datasets.load_dataset('my_dataset', 'second_domain')
 
 
 
 
 
 
 
 
 
247
  BUILDER_CONFIGS = []
 
 
 
 
 
 
248
 
249
+ for key in TASKS:
250
+ td = TASKS[key]
251
+ name = td["name"]
252
+ description = td["description"]
253
+ BUILDER_CONFIGS.append(datasets.BuilderConfig(name=name, version=VERSION, description=description))
254
+
255
+ DEFAULT_CONFIG_NAME = (
256
+ "tai_safety_research" # It's not mandatory to have a default configuration. Just use one if it make sense.
257
+ )
258
 
259
  def _info(self):
260
  DEFAULT_LABEL_NAME = "Unlabeled"
261
 
262
+ task = TASKS[self.config.name]
263
  # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
264
+ data_columns = {col_name: datasets.Value("string") for col_name in task["data_columns"]}
 
265
 
266
  label_columns = {}
267
+ for label_name in task["label_columns"]:
268
+ labels = ["Unlabeled"] + task["label_columns"][label_name]
269
  label_columns[label_name] = datasets.ClassLabel(len(labels), labels)
270
 
271
  # Merge dicts
 
299
  data_dir = dl_manager.download_and_extract(_URLs)
300
  dataset = self.config.name.split("-")[0]
301
  return [
302
+ datasets.SplitGenerator(
303
+ name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir[dataset]["train"], "split": "train"}
304
+ ),
305
+ datasets.SplitGenerator(
306
+ name=datasets.Split.TEST, gen_kwargs={"filepath": data_dir[dataset]["test"], "split": "test"}
307
+ ),
308
  ]
309
 
310
  def _generate_examples(
311
+ self, filepath, split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
312
  ):
313
+ """Yields examples as (key, example) tuples."""
314
  # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
315
  # The `key` is here for legacy reason (tfds) and is not important in itself.
316
 
317
+ task = TASKS[self.config.name]
318
+ labels = list(task["label_columns"])
319
 
320
  with open(filepath, encoding="utf-8") as f:
321
+ csv_reader = csv.reader(f, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True)
 
322
  column_names = next(csv_reader)
323
  # Test csvs don't have any label columns.
324
  if split == "test":