Datasets:
update notebook
Browse files- StackExchangeProcessing.ipynb +278 -123
StackExchangeProcessing.ipynb
CHANGED
@@ -2,12 +2,12 @@
|
|
2 |
"cells": [
|
3 |
{
|
4 |
"cell_type": "code",
|
5 |
-
"execution_count":
|
6 |
"id": "7821c501-8c5d-4af6-81cd-caa6ad0bd58c",
|
7 |
"metadata": {},
|
8 |
"outputs": [],
|
9 |
"source": [
|
10 |
-
"from datasets import load_dataset\n",
|
11 |
"from datasets import concatenate_datasets\n",
|
12 |
"from IPython.display import HTML\n",
|
13 |
"\n",
|
@@ -19,7 +19,7 @@
|
|
19 |
},
|
20 |
{
|
21 |
"cell_type": "code",
|
22 |
-
"execution_count":
|
23 |
"id": "dc821970-efdb-407f-bd79-59da09323280",
|
24 |
"metadata": {
|
25 |
"scrolled": true,
|
@@ -32,6 +32,19 @@
|
|
32 |
"text": [
|
33 |
"Found cached dataset parquet (/home/leandro/.cache/huggingface/datasets/HuggingFaceH4___parquet/HuggingFaceH4--stack-exchange-preferences-1d2bff9ecb5ffe2a/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec)\n"
|
34 |
]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
35 |
}
|
36 |
],
|
37 |
"source": [
|
@@ -41,7 +54,7 @@
|
|
41 |
},
|
42 |
{
|
43 |
"cell_type": "code",
|
44 |
-
"execution_count":
|
45 |
"id": "0d8d8729-6d6b-4791-a24a-cb112c399bd0",
|
46 |
"metadata": {},
|
47 |
"outputs": [
|
@@ -58,7 +71,7 @@
|
|
58 |
"<IPython.core.display.HTML object>"
|
59 |
]
|
60 |
},
|
61 |
-
"execution_count":
|
62 |
"metadata": {},
|
63 |
"output_type": "execute_result"
|
64 |
}
|
@@ -69,7 +82,7 @@
|
|
69 |
},
|
70 |
{
|
71 |
"cell_type": "code",
|
72 |
-
"execution_count":
|
73 |
"id": "b3b60caa-3bd9-4033-ab1c-90c5b08ef3ec",
|
74 |
"metadata": {},
|
75 |
"outputs": [],
|
@@ -84,7 +97,7 @@
|
|
84 |
},
|
85 |
{
|
86 |
"cell_type": "code",
|
87 |
-
"execution_count":
|
88 |
"id": "de1123a0-7468-4d13-a8d3-4011ace36c3c",
|
89 |
"metadata": {},
|
90 |
"outputs": [],
|
@@ -97,7 +110,7 @@
|
|
97 |
},
|
98 |
{
|
99 |
"cell_type": "code",
|
100 |
-
"execution_count":
|
101 |
"id": "c9da64a0-c753-4d35-9369-b70a7a9fa2f9",
|
102 |
"metadata": {},
|
103 |
"outputs": [
|
@@ -123,7 +136,7 @@
|
|
123 |
},
|
124 |
{
|
125 |
"cell_type": "code",
|
126 |
-
"execution_count":
|
127 |
"id": "3bf33a2f-fed5-49e7-8046-e813ad172b17",
|
128 |
"metadata": {},
|
129 |
"outputs": [
|
@@ -133,7 +146,7 @@
|
|
133 |
"49.935"
|
134 |
]
|
135 |
},
|
136 |
-
"execution_count":
|
137 |
"metadata": {},
|
138 |
"output_type": "execute_result"
|
139 |
}
|
@@ -144,7 +157,63 @@
|
|
144 |
},
|
145 |
{
|
146 |
"cell_type": "code",
|
147 |
-
"execution_count":
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
148 |
"id": "edc8af18-94a5-49e9-ae73-ce4ba81d9739",
|
149 |
"metadata": {},
|
150 |
"outputs": [],
|
@@ -164,7 +233,7 @@
|
|
164 |
},
|
165 |
{
|
166 |
"cell_type": "code",
|
167 |
-
"execution_count":
|
168 |
"id": "88afe90e-364e-4b21-898b-1c6ceb9cfd32",
|
169 |
"metadata": {},
|
170 |
"outputs": [],
|
@@ -204,7 +273,7 @@
|
|
204 |
},
|
205 |
{
|
206 |
"cell_type": "code",
|
207 |
-
"execution_count":
|
208 |
"id": "ac06aac5-3953-4321-9f1e-6ff210bee82d",
|
209 |
"metadata": {},
|
210 |
"outputs": [
|
@@ -216,7 +285,7 @@
|
|
216 |
"version_minor": 0
|
217 |
},
|
218 |
"text/plain": [
|
219 |
-
"Map (num_proc=60): 0%| | 0/
|
220 |
]
|
221 |
},
|
222 |
"metadata": {},
|
@@ -227,7 +296,49 @@
|
|
227 |
"output_type": "stream",
|
228 |
"text": [
|
229 |
"/opt/conda/envs/jupyter/lib/python3.8/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
|
230 |
-
" warnings.warn(\n"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
231 |
"/opt/conda/envs/jupyter/lib/python3.8/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
|
232 |
" warnings.warn(\n",
|
233 |
"/opt/conda/envs/jupyter/lib/python3.8/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
|
@@ -235,28 +346,64 @@
|
|
235 |
"/opt/conda/envs/jupyter/lib/python3.8/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
|
236 |
" warnings.warn(\n"
|
237 |
]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
238 |
}
|
239 |
],
|
240 |
"source": [
|
241 |
-
"ds_result =
|
242 |
]
|
243 |
},
|
244 |
{
|
245 |
"cell_type": "code",
|
246 |
-
"execution_count":
|
247 |
"id": "06e3d891-ffde-4762-95d5-39658a1127ef",
|
248 |
"metadata": {},
|
249 |
"outputs": [
|
250 |
{
|
251 |
"data": {
|
252 |
"text/plain": [
|
253 |
-
"
|
254 |
-
"
|
255 |
-
"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
256 |
"})"
|
257 |
]
|
258 |
},
|
259 |
-
"execution_count":
|
260 |
"metadata": {},
|
261 |
"output_type": "execute_result"
|
262 |
}
|
@@ -267,56 +414,49 @@
|
|
267 |
},
|
268 |
{
|
269 |
"cell_type": "code",
|
270 |
-
"execution_count":
|
271 |
"id": "631416dc-cf19-485d-a2f3-94c9b2cb2bfc",
|
272 |
"metadata": {},
|
273 |
"outputs": [
|
274 |
{
|
275 |
"data": {
|
276 |
"text/plain": [
|
277 |
-
"{'qid':
|
278 |
-
" 'question':
|
279 |
-
" 'answers': [{'answer_id':
|
280 |
-
" 'author': '
|
281 |
-
" 'author_id':
|
282 |
-
" 'author_profile': 'https://
|
283 |
-
" 'pm_score': 2,\n",
|
284 |
-
" 'selected': False,\n",
|
285 |
-
" 'text': '<p>I would suggest doing a bit of basic research on 3D printing (including reading questions and answers). From these you will learn more about it and hopefull you will have new questions about 3D printing that can be asked. </p>\\n\\n<p>If you are looking at getting a 3D printer, you could ask about different features listed and why they make prints better.</p>\\n'},\n",
|
286 |
-
" {'answer_id': 15,\n",
|
287 |
-
" 'author': 'kenorb',\n",
|
288 |
-
" 'author_id': 20,\n",
|
289 |
-
" 'author_profile': 'https://3dprinting.meta.stackexchange.com/users/20',\n",
|
290 |
-
" 'pm_score': 2,\n",
|
291 |
-
" 'selected': False,\n",
|
292 |
-
" 'text': '<p>That\\'s the goal of the site, learn, research and ask.</p>\\n\\n<p>While you learn, you can always perform other tasks such as:</p>\\n\\n<ul>\\n<li>improve quality posts by proposing edits,</li>\\n<li>be active in meta (propose new ideas or write your opinion which are always welcomed),</li>\\n<li>review <a href=\"https://3dprinting.stackexchange.com/review\">moderation queues</a>,</li>\\n<li>housekeeping - help to keep things organised (e.g. tags),</li>\\n<li>propose descriptions for wiki tags,</li>\\n<li>vote on questions, down-vote bad or propose changes on low-quality posts,</li>\\n<li>and so on.</li>\\n</ul>\\n'},\n",
|
293 |
-
" {'answer_id': 41,\n",
|
294 |
-
" 'author': 'Zizouz212',\n",
|
295 |
-
" 'author_id': 138,\n",
|
296 |
-
" 'author_profile': 'https://3dprinting.meta.stackexchange.com/users/138',\n",
|
297 |
" 'pm_score': 4,\n",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
298 |
" 'selected': False,\n",
|
299 |
-
" 'text': '<
|
300 |
-
" 'date': '
|
301 |
-
" 'metadata': ['https://
|
302 |
-
" 'https://
|
303 |
-
" 'https://
|
304 |
-
" 'response_j':
|
305 |
-
" 'response_k': '
|
306 |
]
|
307 |
},
|
308 |
-
"execution_count":
|
309 |
"metadata": {},
|
310 |
"output_type": "execute_result"
|
311 |
}
|
312 |
],
|
313 |
"source": [
|
314 |
-
"ds_result[0]"
|
315 |
]
|
316 |
},
|
317 |
{
|
318 |
"cell_type": "code",
|
319 |
-
"execution_count":
|
320 |
"id": "2c96653b-7a5a-4cae-a327-b6aa77aa5850",
|
321 |
"metadata": {},
|
322 |
"outputs": [],
|
@@ -326,58 +466,34 @@
|
|
326 |
},
|
327 |
{
|
328 |
"cell_type": "code",
|
329 |
-
"execution_count":
|
330 |
"id": "15c2e5ee-7c7d-4e98-9e63-e5d37a9354aa",
|
331 |
"metadata": {},
|
332 |
"outputs": [
|
333 |
{
|
334 |
"data": {
|
335 |
"text/plain": [
|
336 |
-
"{
|
337 |
-
"
|
338 |
-
" 'date'
|
339 |
-
"
|
340 |
-
"
|
341 |
-
"
|
342 |
-
" '
|
343 |
-
"
|
344 |
-
|
345 |
-
|
346 |
-
|
347 |
-
|
348 |
-
|
349 |
-
|
350 |
-
|
351 |
-
|
352 |
-
"
|
353 |
-
]
|
354 |
-
},
|
355 |
-
{
|
356 |
-
"cell_type": "code",
|
357 |
-
"execution_count": 72,
|
358 |
-
"id": "32834c62-86bb-478b-a95f-b44fc28fe7d8",
|
359 |
-
"metadata": {},
|
360 |
-
"outputs": [],
|
361 |
-
"source": [
|
362 |
-
"ds_result = ds_result.shuffle(seed=42)"
|
363 |
-
]
|
364 |
-
},
|
365 |
-
{
|
366 |
-
"cell_type": "code",
|
367 |
-
"execution_count": 73,
|
368 |
-
"id": "ae6dcb5b-b549-438d-984d-ecd54919afa1",
|
369 |
-
"metadata": {},
|
370 |
-
"outputs": [
|
371 |
-
{
|
372 |
-
"data": {
|
373 |
-
"text/plain": [
|
374 |
-
"Dataset({\n",
|
375 |
-
" features: ['qid', 'question', 'date', 'metadata', 'response_j', 'response_k'],\n",
|
376 |
-
" num_rows: 26801833\n",
|
377 |
"})"
|
378 |
]
|
379 |
},
|
380 |
-
"execution_count":
|
381 |
"metadata": {},
|
382 |
"output_type": "execute_result"
|
383 |
}
|
@@ -388,35 +504,29 @@
|
|
388 |
},
|
389 |
{
|
390 |
"cell_type": "code",
|
391 |
-
"execution_count":
|
392 |
-
"id": "
|
393 |
"metadata": {},
|
394 |
"outputs": [
|
395 |
{
|
396 |
-
"
|
397 |
-
|
398 |
-
|
399 |
-
|
400 |
-
|
401 |
-
|
402 |
-
|
403 |
-
|
404 |
-
" 'response_j': 'Since September 2018 there is the [`AgmFitBounds`](https://angular-maps.com/api-docs/agm-core/directives/agmfitbounds) directive. Super easy.\\n\\n```\\n<agm-map\\n style=\"width:100vw; height:100vh;\"\\n [fitBounds]=\"true\">\\n\\n <agm-marker\\n *ngFor=\"let location of locations\"\\n [latitude]=\"location.latitude\"\\n [longitude]=\"location.longitude\"\\n [agmFitBounds]=\"true\"></agm-marker>\\n</agm-map>\\n\\n```',\n",
|
405 |
-
" 'response_k': '@renil-babu\\n\\nInstead of doing the `fitBounds` on `mapReady`, you have to do it in your adding markers subscription block\\n\\n```\\n const bounds: LatLngBounds = new google.maps.LatLngBounds();\\n for (const mm of this.markers) {\\n bounds.extend(new google.maps.LatLng(mm.lat, mm.lng));\\n }\\n // @ts-ignore\\n this.agmMap._mapsWrapper.fitBounds(bounds);\\n\\n```'}"
|
406 |
-
]
|
407 |
-
},
|
408 |
-
"execution_count": 74,
|
409 |
-
"metadata": {},
|
410 |
-
"output_type": "execute_result"
|
411 |
}
|
412 |
],
|
413 |
"source": [
|
414 |
-
"ds_result
|
|
|
415 |
]
|
416 |
},
|
417 |
{
|
418 |
"cell_type": "code",
|
419 |
-
"execution_count":
|
420 |
"id": "e32c11d7-a88e-4d92-9dfc-92b2a67c5455",
|
421 |
"metadata": {},
|
422 |
"outputs": [],
|
@@ -436,7 +546,7 @@
|
|
436 |
" shard.to_parquet(filename)\n",
|
437 |
"\n",
|
438 |
"\n",
|
439 |
-
"def save_manual_shards(ds, user=\"lvwerra\", remote_dataset_repo=\"stack-exchange-paired\"):\n",
|
440 |
" \"\"\"Save sharded data\n",
|
441 |
" Args:\n",
|
442 |
" ds (Dataset): dataset to be saved\n",
|
@@ -458,7 +568,10 @@
|
|
458 |
" )\n",
|
459 |
"\n",
|
460 |
" # files will be numerous we save them in a folder called data inside out_path\n",
|
461 |
-
" os.
|
|
|
|
|
|
|
462 |
" SHARD_SIZE = 1000 << 20\n",
|
463 |
" if ds._indices is not None:\n",
|
464 |
" dataset_nbytes = ds.data.nbytes * len(ds._indices) / len(ds.data)\n",
|
@@ -475,7 +588,7 @@
|
|
475 |
" )\n",
|
476 |
" # use f\"{OUT_PATH}/data/train-{index:05d}-of-{num_shards:05d}.json\" instead for json files\n",
|
477 |
" filenames = (\n",
|
478 |
-
" f\"{out_path}/data/train-{index:05d}-of-{num_shards:05d}.parquet\"\n",
|
479 |
" for index in range(num_shards)\n",
|
480 |
" )\n",
|
481 |
"\n",
|
@@ -492,22 +605,63 @@
|
|
492 |
},
|
493 |
{
|
494 |
"cell_type": "code",
|
495 |
-
"execution_count":
|
496 |
"id": "a90664eb-5c54-4fae-9a8a-d509bb2abdfe",
|
497 |
"metadata": {},
|
498 |
"outputs": [
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
499 |
{
|
500 |
"name": "stderr",
|
501 |
"output_type": "stream",
|
502 |
"text": [
|
503 |
-
"
|
504 |
]
|
505 |
},
|
506 |
{
|
507 |
"name": "stdout",
|
508 |
"output_type": "stream",
|
509 |
"text": [
|
510 |
-
"
|
|
|
511 |
"sharding the dataset\n"
|
512 |
]
|
513 |
},
|
@@ -515,19 +669,20 @@
|
|
515 |
"name": "stderr",
|
516 |
"output_type": "stream",
|
517 |
"text": [
|
518 |
-
"100
|
519 |
]
|
520 |
},
|
521 |
{
|
522 |
"name": "stdout",
|
523 |
"output_type": "stream",
|
524 |
"text": [
|
525 |
-
"Time to save dataset:
|
526 |
]
|
527 |
}
|
528 |
],
|
529 |
"source": [
|
530 |
-
"
|
|
|
531 |
]
|
532 |
},
|
533 |
{
|
|
|
2 |
"cells": [
|
3 |
{
|
4 |
"cell_type": "code",
|
5 |
+
"execution_count": 86,
|
6 |
"id": "7821c501-8c5d-4af6-81cd-caa6ad0bd58c",
|
7 |
"metadata": {},
|
8 |
"outputs": [],
|
9 |
"source": [
|
10 |
+
"from datasets import load_dataset, DatasetDict\n",
|
11 |
"from datasets import concatenate_datasets\n",
|
12 |
"from IPython.display import HTML\n",
|
13 |
"\n",
|
|
|
19 |
},
|
20 |
{
|
21 |
"cell_type": "code",
|
22 |
+
"execution_count": 80,
|
23 |
"id": "dc821970-efdb-407f-bd79-59da09323280",
|
24 |
"metadata": {
|
25 |
"scrolled": true,
|
|
|
32 |
"text": [
|
33 |
"Found cached dataset parquet (/home/leandro/.cache/huggingface/datasets/HuggingFaceH4___parquet/HuggingFaceH4--stack-exchange-preferences-1d2bff9ecb5ffe2a/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec)\n"
|
34 |
]
|
35 |
+
},
|
36 |
+
{
|
37 |
+
"data": {
|
38 |
+
"text/plain": [
|
39 |
+
"Dataset({\n",
|
40 |
+
" features: ['qid', 'question', 'answers', 'date', 'metadata'],\n",
|
41 |
+
" num_rows: 10807695\n",
|
42 |
+
"})"
|
43 |
+
]
|
44 |
+
},
|
45 |
+
"execution_count": 80,
|
46 |
+
"metadata": {},
|
47 |
+
"output_type": "execute_result"
|
48 |
}
|
49 |
],
|
50 |
"source": [
|
|
|
54 |
},
|
55 |
{
|
56 |
"cell_type": "code",
|
57 |
+
"execution_count": 81,
|
58 |
"id": "0d8d8729-6d6b-4791-a24a-cb112c399bd0",
|
59 |
"metadata": {},
|
60 |
"outputs": [
|
|
|
71 |
"<IPython.core.display.HTML object>"
|
72 |
]
|
73 |
},
|
74 |
+
"execution_count": 81,
|
75 |
"metadata": {},
|
76 |
"output_type": "execute_result"
|
77 |
}
|
|
|
82 |
},
|
83 |
{
|
84 |
"cell_type": "code",
|
85 |
+
"execution_count": 82,
|
86 |
"id": "b3b60caa-3bd9-4033-ab1c-90c5b08ef3ec",
|
87 |
"metadata": {},
|
88 |
"outputs": [],
|
|
|
97 |
},
|
98 |
{
|
99 |
"cell_type": "code",
|
100 |
+
"execution_count": 83,
|
101 |
"id": "de1123a0-7468-4d13-a8d3-4011ace36c3c",
|
102 |
"metadata": {},
|
103 |
"outputs": [],
|
|
|
110 |
},
|
111 |
{
|
112 |
"cell_type": "code",
|
113 |
+
"execution_count": 84,
|
114 |
"id": "c9da64a0-c753-4d35-9369-b70a7a9fa2f9",
|
115 |
"metadata": {},
|
116 |
"outputs": [
|
|
|
136 |
},
|
137 |
{
|
138 |
"cell_type": "code",
|
139 |
+
"execution_count": 85,
|
140 |
"id": "3bf33a2f-fed5-49e7-8046-e813ad172b17",
|
141 |
"metadata": {},
|
142 |
"outputs": [
|
|
|
146 |
"49.935"
|
147 |
]
|
148 |
},
|
149 |
+
"execution_count": 85,
|
150 |
"metadata": {},
|
151 |
"output_type": "execute_result"
|
152 |
}
|
|
|
157 |
},
|
158 |
{
|
159 |
"cell_type": "code",
|
160 |
+
"execution_count": 87,
|
161 |
+
"id": "88ea2dd5-b885-4f65-bae3-1319c7816044",
|
162 |
+
"metadata": {},
|
163 |
+
"outputs": [],
|
164 |
+
"source": [
|
165 |
+
"ds = ds.shuffle(seed=42)\n",
|
166 |
+
"index = list(range(len(ds)))\n",
|
167 |
+
"\n",
|
168 |
+
"ds_splits = DatasetDict({\n",
|
169 |
+
" \"finetune\": ds.select(index[:3_000_000]),\n",
|
170 |
+
" \"reward\": ds.select(index[3_000_000:6_000_000]),\n",
|
171 |
+
" \"rl\": ds.select(index[6_000_000:9_000_000]),\n",
|
172 |
+
" \"evaluation\": ds.select(index[9_000_000:]),\n",
|
173 |
+
"})"
|
174 |
+
]
|
175 |
+
},
|
176 |
+
{
|
177 |
+
"cell_type": "code",
|
178 |
+
"execution_count": 88,
|
179 |
+
"id": "1607922d-f585-4de7-be70-2205b5170102",
|
180 |
+
"metadata": {},
|
181 |
+
"outputs": [
|
182 |
+
{
|
183 |
+
"data": {
|
184 |
+
"text/plain": [
|
185 |
+
"DatasetDict({\n",
|
186 |
+
" finetune: Dataset({\n",
|
187 |
+
" features: ['qid', 'question', 'answers', 'date', 'metadata'],\n",
|
188 |
+
" num_rows: 3000000\n",
|
189 |
+
" })\n",
|
190 |
+
" reward: Dataset({\n",
|
191 |
+
" features: ['qid', 'question', 'answers', 'date', 'metadata'],\n",
|
192 |
+
" num_rows: 3000000\n",
|
193 |
+
" })\n",
|
194 |
+
" rl: Dataset({\n",
|
195 |
+
" features: ['qid', 'question', 'answers', 'date', 'metadata'],\n",
|
196 |
+
" num_rows: 3000000\n",
|
197 |
+
" })\n",
|
198 |
+
" evaluation: Dataset({\n",
|
199 |
+
" features: ['qid', 'question', 'answers', 'date', 'metadata'],\n",
|
200 |
+
" num_rows: 1807695\n",
|
201 |
+
" })\n",
|
202 |
+
"})"
|
203 |
+
]
|
204 |
+
},
|
205 |
+
"execution_count": 88,
|
206 |
+
"metadata": {},
|
207 |
+
"output_type": "execute_result"
|
208 |
+
}
|
209 |
+
],
|
210 |
+
"source": [
|
211 |
+
"ds_splits"
|
212 |
+
]
|
213 |
+
},
|
214 |
+
{
|
215 |
+
"cell_type": "code",
|
216 |
+
"execution_count": 89,
|
217 |
"id": "edc8af18-94a5-49e9-ae73-ce4ba81d9739",
|
218 |
"metadata": {},
|
219 |
"outputs": [],
|
|
|
233 |
},
|
234 |
{
|
235 |
"cell_type": "code",
|
236 |
+
"execution_count": 90,
|
237 |
"id": "88afe90e-364e-4b21-898b-1c6ceb9cfd32",
|
238 |
"metadata": {},
|
239 |
"outputs": [],
|
|
|
273 |
},
|
274 |
{
|
275 |
"cell_type": "code",
|
276 |
+
"execution_count": 91,
|
277 |
"id": "ac06aac5-3953-4321-9f1e-6ff210bee82d",
|
278 |
"metadata": {},
|
279 |
"outputs": [
|
|
|
285 |
"version_minor": 0
|
286 |
},
|
287 |
"text/plain": [
|
288 |
+
"Map (num_proc=60): 0%| | 0/3000000 [00:00<?, ? examples/s]"
|
289 |
]
|
290 |
},
|
291 |
"metadata": {},
|
|
|
296 |
"output_type": "stream",
|
297 |
"text": [
|
298 |
"/opt/conda/envs/jupyter/lib/python3.8/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
|
299 |
+
" warnings.warn(\n"
|
300 |
+
]
|
301 |
+
},
|
302 |
+
{
|
303 |
+
"data": {
|
304 |
+
"application/vnd.jupyter.widget-view+json": {
|
305 |
+
"model_id": "",
|
306 |
+
"version_major": 2,
|
307 |
+
"version_minor": 0
|
308 |
+
},
|
309 |
+
"text/plain": [
|
310 |
+
"Map (num_proc=60): 0%| | 0/3000000 [00:00<?, ? examples/s]"
|
311 |
+
]
|
312 |
+
},
|
313 |
+
"metadata": {},
|
314 |
+
"output_type": "display_data"
|
315 |
+
},
|
316 |
+
{
|
317 |
+
"name": "stderr",
|
318 |
+
"output_type": "stream",
|
319 |
+
"text": [
|
320 |
+
"/opt/conda/envs/jupyter/lib/python3.8/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
|
321 |
+
" warnings.warn(\n"
|
322 |
+
]
|
323 |
+
},
|
324 |
+
{
|
325 |
+
"data": {
|
326 |
+
"application/vnd.jupyter.widget-view+json": {
|
327 |
+
"model_id": "",
|
328 |
+
"version_major": 2,
|
329 |
+
"version_minor": 0
|
330 |
+
},
|
331 |
+
"text/plain": [
|
332 |
+
"Map (num_proc=60): 0%| | 0/3000000 [00:00<?, ? examples/s]"
|
333 |
+
]
|
334 |
+
},
|
335 |
+
"metadata": {},
|
336 |
+
"output_type": "display_data"
|
337 |
+
},
|
338 |
+
{
|
339 |
+
"name": "stderr",
|
340 |
+
"output_type": "stream",
|
341 |
+
"text": [
|
342 |
"/opt/conda/envs/jupyter/lib/python3.8/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
|
343 |
" warnings.warn(\n",
|
344 |
"/opt/conda/envs/jupyter/lib/python3.8/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
|
|
|
346 |
"/opt/conda/envs/jupyter/lib/python3.8/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
|
347 |
" warnings.warn(\n"
|
348 |
]
|
349 |
+
},
|
350 |
+
{
|
351 |
+
"data": {
|
352 |
+
"application/vnd.jupyter.widget-view+json": {
|
353 |
+
"model_id": "",
|
354 |
+
"version_major": 2,
|
355 |
+
"version_minor": 0
|
356 |
+
},
|
357 |
+
"text/plain": [
|
358 |
+
"Map (num_proc=60): 0%| | 0/1807695 [00:00<?, ? examples/s]"
|
359 |
+
]
|
360 |
+
},
|
361 |
+
"metadata": {},
|
362 |
+
"output_type": "display_data"
|
363 |
+
},
|
364 |
+
{
|
365 |
+
"name": "stderr",
|
366 |
+
"output_type": "stream",
|
367 |
+
"text": [
|
368 |
+
"/opt/conda/envs/jupyter/lib/python3.8/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
|
369 |
+
" warnings.warn(\n"
|
370 |
+
]
|
371 |
}
|
372 |
],
|
373 |
"source": [
|
374 |
+
"ds_result = ds_splits.map(preprocess, batch_size=1000, batched=True, num_proc=60)"
|
375 |
]
|
376 |
},
|
377 |
{
|
378 |
"cell_type": "code",
|
379 |
+
"execution_count": 92,
|
380 |
"id": "06e3d891-ffde-4762-95d5-39658a1127ef",
|
381 |
"metadata": {},
|
382 |
"outputs": [
|
383 |
{
|
384 |
"data": {
|
385 |
"text/plain": [
|
386 |
+
"DatasetDict({\n",
|
387 |
+
" finetune: Dataset({\n",
|
388 |
+
" features: ['qid', 'question', 'answers', 'date', 'metadata', 'response_j', 'response_k'],\n",
|
389 |
+
" num_rows: 7440923\n",
|
390 |
+
" })\n",
|
391 |
+
" reward: Dataset({\n",
|
392 |
+
" features: ['qid', 'question', 'answers', 'date', 'metadata', 'response_j', 'response_k'],\n",
|
393 |
+
" num_rows: 7441998\n",
|
394 |
+
" })\n",
|
395 |
+
" rl: Dataset({\n",
|
396 |
+
" features: ['qid', 'question', 'answers', 'date', 'metadata', 'response_j', 'response_k'],\n",
|
397 |
+
" num_rows: 7435908\n",
|
398 |
+
" })\n",
|
399 |
+
" evaluation: Dataset({\n",
|
400 |
+
" features: ['qid', 'question', 'answers', 'date', 'metadata', 'response_j', 'response_k'],\n",
|
401 |
+
" num_rows: 4483004\n",
|
402 |
+
" })\n",
|
403 |
"})"
|
404 |
]
|
405 |
},
|
406 |
+
"execution_count": 92,
|
407 |
"metadata": {},
|
408 |
"output_type": "execute_result"
|
409 |
}
|
|
|
414 |
},
|
415 |
{
|
416 |
"cell_type": "code",
|
417 |
+
"execution_count": 93,
|
418 |
"id": "631416dc-cf19-485d-a2f3-94c9b2cb2bfc",
|
419 |
"metadata": {},
|
420 |
"outputs": [
|
421 |
{
|
422 |
"data": {
|
423 |
"text/plain": [
|
424 |
+
"{'qid': 12891264,\n",
|
425 |
+
" 'question': \"I am using jQuery fileupload plugin and I want to do some custom jQuery stuff once fileupload is done\\n\\nfrom here <https://github.com/blueimp/jQuery-File-Upload/wiki/Options>\\n\\nNow it says this\\n\\n```\\nCallback for successful upload requests.\\n$('#fileupload')\\n .bind('fileuploaddone', function (e, data) {/* ... */})\\n\\n```\\n\\nNow I have defined this custom function for testing in my own js file\\n\\n```\\n$('#fileupload').bind('fileuploaddone', function (e, data) {/* ... */\\nalert('Hello');\\n})\\n\\n```\\n\\nBut it's not working.\\n\\nBut if I edit the main file in here\\n\\n```\\n // Callback for successful uploads:\\n done: function (e, data) {\\n\\n```\\n\\nThen it works.\",\n",
|
426 |
+
" 'answers': [{'answer_id': 12891484,\n",
|
427 |
+
" 'author': 'Reflective',\n",
|
428 |
+
" 'author_id': 1686626,\n",
|
429 |
+
" 'author_profile': 'https://Stackoverflow.com/users/1686626',\n",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
430 |
" 'pm_score': 4,\n",
|
431 |
+
" 'selected': True,\n",
|
432 |
+
" 'text': \"<p>Looking at the library code, seems all events are renamed removing 'fileupload' ... so 'fileuploaddone' becomes just 'done'. It is valid for all other callbacks.\\nlook at this section:</p>\\n\\n<pre><code> // Other callbacks:\\n // Callback for the submit event of each file upload:\\n // submit: function (e, data) {}, // .bind('fileuploadsubmit', func);\\n // Callback for the start of each file upload request:\\n // send: function (e, data) {}, // .bind('fileuploadsend', func);\\n // Callback for successful uploads:\\n // done: function (e, data) {}, // .bind('fileuploaddone', func);\\n // Callback for failed (abort or error) uploads:\\n // fail: function (e, data) {}, // .bind('fileuploadfail', func);\\n // Callback for completed (success, abort or error) requests:\\n // always: function (e, data) {}, // .bind('fileuploadalways', func);\\n // Callback for upload progress events:\\n // progress: function (e, data) {}, // .bind('fileuploadprogress', func);\\n // Callback for global upload progress events:\\n // progressall: function (e, data) {}, // .bind('fileuploadprogressall', func);\\n // Callback for uploads start, equivalent to the global ajaxStart event:\\n // start: function (e) {}, // .bind('fileuploadstart', func);\\n // Callback for uploads stop, equivalent to the global ajaxStop event:\\n // stop: function (e) {}, // .bind('fileuploadstop', func);\\n // Callback for change events of the fileInput(s):\\n // change: function (e, data) {}, // .bind('fileuploadchange', func);\\n // Callback for paste events to the pasteZone(s):\\n // paste: function (e, data) {}, // .bind('fileuploadpaste', func);\\n // Callback for drop events of the dropZone(s):\\n // drop: function (e, data) {}, // .bind('fileuploaddrop', func);\\n // Callback for dragover events of the dropZone(s):\\n // dragover: function (e) {}, // .bind('fileuploaddragover', func);\\n</code></pre>\\n\\n<p>If you have some doubts about what's happening, just look at the code inside. This library is not compressed so it is easy to see. for example</p>\\n\\n<pre><code>// start: function (e) {}, // .bind('fileuploadstart', func);\\n</code></pre>\\n\\n<p><code>start</code> callback is implemented. <code>fileuploadstart</code> is not.</p>\\n\"},\n",
|
433 |
+
" {'answer_id': 15419140,\n",
|
434 |
+
" 'author': 'NXT',\n",
|
435 |
+
" 'author_id': 1554649,\n",
|
436 |
+
" 'author_profile': 'https://Stackoverflow.com/users/1554649',\n",
|
437 |
+
" 'pm_score': 3,\n",
|
438 |
" 'selected': False,\n",
|
439 |
+
" 'text': '<p>Check if the server-side uploading script returns a JSON reply - in my case it didn\\'t work when the reply was empty, but file was uploaded successfully.</p>\\n\\n<p>So, below is working for me with jQuery 1.9.1 and the newest version of the \"jQuery File Upload Plugin\" - 5.21.3</p>\\n\\n<pre><code>$(\"#fileupload\").bind(\"fileuploaddone\", function (e, data) {\\n console.log(\"fileuploaddone event fired\");\\n});\\n</code></pre>\\n'}],\n",
|
440 |
+
" 'date': '2012/10/15',\n",
|
441 |
+
" 'metadata': ['https://Stackoverflow.com/questions/12891264',\n",
|
442 |
+
" 'https://Stackoverflow.com',\n",
|
443 |
+
" 'https://Stackoverflow.com/users/767244/'],\n",
|
444 |
+
" 'response_j': \"Looking at the library code, seems all events are renamed removing 'fileupload' ... so 'fileuploaddone' becomes just 'done'. It is valid for all other callbacks.\\nlook at this section:\\n\\n```\\n // Other callbacks:\\n // Callback for the submit event of each file upload:\\n // submit: function (e, data) {}, // .bind('fileuploadsubmit', func);\\n // Callback for the start of each file upload request:\\n // send: function (e, data) {}, // .bind('fileuploadsend', func);\\n // Callback for successful uploads:\\n // done: function (e, data) {}, // .bind('fileuploaddone', func);\\n // Callback for failed (abort or error) uploads:\\n // fail: function (e, data) {}, // .bind('fileuploadfail', func);\\n // Callback for completed (success, abort or error) requests:\\n // always: function (e, data) {}, // .bind('fileuploadalways', func);\\n // Callback for upload progress events:\\n // progress: function (e, data) {}, // .bind('fileuploadprogress', func);\\n // Callback for global upload progress events:\\n // progressall: function (e, data) {}, // .bind('fileuploadprogressall', func);\\n // Callback for uploads start, equivalent to the global ajaxStart event:\\n // start: function (e) {}, // .bind('fileuploadstart', func);\\n // Callback for uploads stop, equivalent to the global ajaxStop event:\\n // stop: function (e) {}, // .bind('fileuploadstop', func);\\n // Callback for change events of the fileInput(s):\\n // change: function (e, data) {}, // .bind('fileuploadchange', func);\\n // Callback for paste events to the pasteZone(s):\\n // paste: function (e, data) {}, // .bind('fileuploadpaste', func);\\n // Callback for drop events of the dropZone(s):\\n // drop: function (e, data) {}, // .bind('fileuploaddrop', func);\\n // Callback for dragover events of the dropZone(s):\\n // dragover: function (e) {}, // .bind('fileuploaddragover', func);\\n\\n```\\n\\nIf you have some doubts about what's happening, just look at the code inside. This library is not compressed so it is easy to see. for example\\n\\n```\\n// start: function (e) {}, // .bind('fileuploadstart', func);\\n\\n```\\n\\n`start` callback is implemented. `fileuploadstart` is not.\",\n",
|
445 |
+
" 'response_k': 'Check if the server-side uploading script returns a JSON reply - in my case it didn\\'t work when the reply was empty, but file was uploaded successfully.\\n\\nSo, below is working for me with jQuery 1.9.1 and the newest version of the \"jQuery File Upload Plugin\" - 5.21.3\\n\\n```\\n$(\"#fileupload\").bind(\"fileuploaddone\", function (e, data) {\\n console.log(\"fileuploaddone event fired\");\\n});\\n\\n```'}"
|
446 |
]
|
447 |
},
|
448 |
+
"execution_count": 93,
|
449 |
"metadata": {},
|
450 |
"output_type": "execute_result"
|
451 |
}
|
452 |
],
|
453 |
"source": [
|
454 |
+
"ds_result[\"finetune\"][0]"
|
455 |
]
|
456 |
},
|
457 |
{
|
458 |
"cell_type": "code",
|
459 |
+
"execution_count": 94,
|
460 |
"id": "2c96653b-7a5a-4cae-a327-b6aa77aa5850",
|
461 |
"metadata": {},
|
462 |
"outputs": [],
|
|
|
466 |
},
|
467 |
{
|
468 |
"cell_type": "code",
|
469 |
+
"execution_count": 95,
|
470 |
"id": "15c2e5ee-7c7d-4e98-9e63-e5d37a9354aa",
|
471 |
"metadata": {},
|
472 |
"outputs": [
|
473 |
{
|
474 |
"data": {
|
475 |
"text/plain": [
|
476 |
+
"DatasetDict({\n",
|
477 |
+
" finetune: Dataset({\n",
|
478 |
+
" features: ['qid', 'question', 'date', 'metadata', 'response_j', 'response_k'],\n",
|
479 |
+
" num_rows: 7440923\n",
|
480 |
+
" })\n",
|
481 |
+
" reward: Dataset({\n",
|
482 |
+
" features: ['qid', 'question', 'date', 'metadata', 'response_j', 'response_k'],\n",
|
483 |
+
" num_rows: 7441998\n",
|
484 |
+
" })\n",
|
485 |
+
" rl: Dataset({\n",
|
486 |
+
" features: ['qid', 'question', 'date', 'metadata', 'response_j', 'response_k'],\n",
|
487 |
+
" num_rows: 7435908\n",
|
488 |
+
" })\n",
|
489 |
+
" evaluation: Dataset({\n",
|
490 |
+
" features: ['qid', 'question', 'date', 'metadata', 'response_j', 'response_k'],\n",
|
491 |
+
" num_rows: 4483004\n",
|
492 |
+
" })\n",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
493 |
"})"
|
494 |
]
|
495 |
},
|
496 |
+
"execution_count": 95,
|
497 |
"metadata": {},
|
498 |
"output_type": "execute_result"
|
499 |
}
|
|
|
504 |
},
|
505 |
{
|
506 |
"cell_type": "code",
|
507 |
+
"execution_count": 96,
|
508 |
+
"id": "4d42b35c-5252-4b49-ba4b-20818bc9e086",
|
509 |
"metadata": {},
|
510 |
"outputs": [
|
511 |
{
|
512 |
+
"name": "stdout",
|
513 |
+
"output_type": "stream",
|
514 |
+
"text": [
|
515 |
+
"finetune\n",
|
516 |
+
"reward\n",
|
517 |
+
"rl\n",
|
518 |
+
"evaluation\n"
|
519 |
+
]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
520 |
}
|
521 |
],
|
522 |
"source": [
|
523 |
+
"for key in ds_result:\n",
|
524 |
+
" print(key)"
|
525 |
]
|
526 |
},
|
527 |
{
|
528 |
"cell_type": "code",
|
529 |
+
"execution_count": 100,
|
530 |
"id": "e32c11d7-a88e-4d92-9dfc-92b2a67c5455",
|
531 |
"metadata": {},
|
532 |
"outputs": [],
|
|
|
546 |
" shard.to_parquet(filename)\n",
|
547 |
"\n",
|
548 |
"\n",
|
549 |
+
"def save_manual_shards(ds, user=\"lvwerra\", remote_dataset_repo=\"stack-exchange-paired\", subfolder=\"train\"):\n",
|
550 |
" \"\"\"Save sharded data\n",
|
551 |
" Args:\n",
|
552 |
" ds (Dataset): dataset to be saved\n",
|
|
|
568 |
" )\n",
|
569 |
"\n",
|
570 |
" # files will be numerous we save them in a folder called data inside out_path\n",
|
571 |
+
" if not os.path.exists(out_path):\n",
|
572 |
+
" os.mkdir(out_path + \"/data\")\n",
|
573 |
+
" os.mkdir(out_path + f\"/data/{subfolder}\")\n",
|
574 |
+
" \n",
|
575 |
" SHARD_SIZE = 1000 << 20\n",
|
576 |
" if ds._indices is not None:\n",
|
577 |
" dataset_nbytes = ds.data.nbytes * len(ds._indices) / len(ds.data)\n",
|
|
|
588 |
" )\n",
|
589 |
" # use f\"{OUT_PATH}/data/train-{index:05d}-of-{num_shards:05d}.json\" instead for json files\n",
|
590 |
" filenames = (\n",
|
591 |
+
" f\"{out_path}/data/{subfolder}/train-{index:05d}-of-{num_shards:05d}.parquet\"\n",
|
592 |
" for index in range(num_shards)\n",
|
593 |
" )\n",
|
594 |
"\n",
|
|
|
605 |
},
|
606 |
{
|
607 |
"cell_type": "code",
|
608 |
+
"execution_count": 101,
|
609 |
"id": "a90664eb-5c54-4fae-9a8a-d509bb2abdfe",
|
610 |
"metadata": {},
|
611 |
"outputs": [
|
612 |
+
{
|
613 |
+
"name": "stdout",
|
614 |
+
"output_type": "stream",
|
615 |
+
"text": [
|
616 |
+
"Number of shards: 20\n",
|
617 |
+
"sharding the dataset\n"
|
618 |
+
]
|
619 |
+
},
|
620 |
+
{
|
621 |
+
"name": "stderr",
|
622 |
+
"output_type": "stream",
|
623 |
+
"text": [
|
624 |
+
"100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 20/20 [00:28<00:00, 1.43s/it]\n"
|
625 |
+
]
|
626 |
+
},
|
627 |
+
{
|
628 |
+
"name": "stdout",
|
629 |
+
"output_type": "stream",
|
630 |
+
"text": [
|
631 |
+
"Time to save dataset: 29.15\n",
|
632 |
+
"Number of shards: 20\n",
|
633 |
+
"sharding the dataset\n"
|
634 |
+
]
|
635 |
+
},
|
636 |
+
{
|
637 |
+
"name": "stderr",
|
638 |
+
"output_type": "stream",
|
639 |
+
"text": [
|
640 |
+
"100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 20/20 [00:22<00:00, 1.15s/it]\n"
|
641 |
+
]
|
642 |
+
},
|
643 |
+
{
|
644 |
+
"name": "stdout",
|
645 |
+
"output_type": "stream",
|
646 |
+
"text": [
|
647 |
+
"Time to save dataset: 23.42\n",
|
648 |
+
"Number of shards: 20\n",
|
649 |
+
"sharding the dataset\n"
|
650 |
+
]
|
651 |
+
},
|
652 |
{
|
653 |
"name": "stderr",
|
654 |
"output_type": "stream",
|
655 |
"text": [
|
656 |
+
"100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 20/20 [00:10<00:00, 1.83it/s]\n"
|
657 |
]
|
658 |
},
|
659 |
{
|
660 |
"name": "stdout",
|
661 |
"output_type": "stream",
|
662 |
"text": [
|
663 |
+
"Time to save dataset: 11.36\n",
|
664 |
+
"Number of shards: 12\n",
|
665 |
"sharding the dataset\n"
|
666 |
]
|
667 |
},
|
|
|
669 |
"name": "stderr",
|
670 |
"output_type": "stream",
|
671 |
"text": [
|
672 |
+
"100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 12/12 [00:10<00:00, 1.12it/s]\n"
|
673 |
]
|
674 |
},
|
675 |
{
|
676 |
"name": "stdout",
|
677 |
"output_type": "stream",
|
678 |
"text": [
|
679 |
+
"Time to save dataset: 11.13\n"
|
680 |
]
|
681 |
}
|
682 |
],
|
683 |
"source": [
|
684 |
+
"for key in ds_result:\n",
|
685 |
+
" save_manual_shards(ds_result[key], subfolder=key)"
|
686 |
]
|
687 |
},
|
688 |
{
|