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https://api.github.com/repos/huggingface/datasets/issues/2298 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2298/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2298/comments | https://api.github.com/repos/huggingface/datasets/issues/2298/events | https://github.com/huggingface/datasets/pull/2298 | 873,771,942 | MDExOlB1bGxSZXF1ZXN0NjI4NDk2NjM2 | 2,298 | Mapping in the distributed setting | [] | closed | false | null | 0 | 2021-05-01T21:23:05Z | 2021-05-03T13:54:53Z | 2021-05-03T13:54:53Z | null | The barrier trick for distributed mapping as discussed on Thursday with @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/752 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/752/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/752/comments | https://api.github.com/repos/huggingface/datasets/issues/752/events | https://github.com/huggingface/datasets/issues/752 | 726,917,801 | MDU6SXNzdWU3MjY5MTc4MDE= | 752 | Clicking on a metric in the search page points to datasets page giving "Missing dataset" warning | [] | closed | false | null | 2 | 2020-10-21T22:56:23Z | 2020-10-22T16:19:42Z | 2020-10-22T16:19:42Z | null | Hi! Sorry if this isn't the right place to talk about the website, I just didn't exactly where to write this.
Searching a metric in https://huggingface.co/metrics gives the right results but clicking on a metric (E.g ROUGE) points to https://huggingface.co/datasets/rouge. Clicking on a metric without searching points to the right page.
Thanks for all the great work! | {
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"Thanks for the report, can reproduce. Will fix",
"Fixed now @ogabrielluiz "
] |
https://api.github.com/repos/huggingface/datasets/issues/480 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/480/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/480/comments | https://api.github.com/repos/huggingface/datasets/issues/480/events | https://github.com/huggingface/datasets/pull/480 | 674,245,959 | MDExOlB1bGxSZXF1ZXN0NDYzOTcwNjQ2 | 480 | Column indexing hotfix | [] | closed | false | null | 2 | 2020-08-06T11:37:05Z | 2020-08-12T08:36:10Z | 2020-08-12T08:36:10Z | null | As observed for example in #469 , currently `__getitem__` does not convert the data to the dataset format when indexing by column. This is a hotfix that imitates functional 0.3.0. code. In the future it'd probably be nice to have a test there. | {
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"Looks good to me as well but we'll want to add a test indeed.\r\nYou can add one if you have time @TevenLeScao.\r\nOtherwise, we'll do it when we are back with Quentin. ",
"I fixed it in #494 "
] |
https://api.github.com/repos/huggingface/datasets/issues/5984 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5984/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5984/comments | https://api.github.com/repos/huggingface/datasets/issues/5984/events | https://github.com/huggingface/datasets/issues/5984 | 1,771,571,458 | I_kwDODunzps5pmAkC | 5,984 | AutoSharding IterableDataset's when num_workers > 1 | [
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] | open | false | null | 6 | 2023-06-23T14:34:20Z | 2023-07-04T17:03:56Z | null | null | ### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
Too many dataloader workers: 2 (max is dataset.n_shards=1). Stopping 1 dataloader workers.
To parallelize data loading, we give each process some shards (or data sources) to process. Therefore it's unnecessary to have a number of workers greater than dataset.n_shards=1. To enable more parallelism, please split the dataset in more files than 1.
Expected Behavior:
Dataset is sharded each cpu uses subset (contiguously - so you can do checkpoint loading/saving)
### Motivation
I have a lot of unused cpu's and would like to be able to shard iterable datasets with pytorch's dataloader when num_workers > 1. This is for a very large single file. I am aware that we can use the `split_dataset_by_node` to ensure that each node (for distributed) gets different shards, but we should extend it so that this also continues for multiple workers.
### Your contribution
If someone points me to what needs to change, I can create a PR. | {
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"For this to be possible, we would have to switch from the \"Streaming\" Arrow format to the \"Random Access\" (IPC/Feather) format, which allows reading arbitrary record batches (explained [here](https://arrow.apache.org/docs/python/ipc.html)). We could then use these batches to construct shards.\r\n\r\n@lhoestq @... |
https://api.github.com/repos/huggingface/datasets/issues/428 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/428/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/428/comments | https://api.github.com/repos/huggingface/datasets/issues/428/events | https://github.com/huggingface/datasets/pull/428 | 664,367,086 | MDExOlB1bGxSZXF1ZXN0NDU1NjE3Nzcy | 428 | fix concatenate_datasets | [] | closed | false | null | 0 | 2020-07-23T10:30:59Z | 2020-07-23T10:35:00Z | 2020-07-23T10:34:58Z | null | `concatenate_datatsets` used to test that the different`nlp.Dataset.schema` match, but this attribute was removed in #423 | {
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https://api.github.com/repos/huggingface/datasets/issues/998 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/998/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/998/comments | https://api.github.com/repos/huggingface/datasets/issues/998/events | https://github.com/huggingface/datasets/pull/998 | 755,235,356 | MDExOlB1bGxSZXF1ZXN0NTMwOTg2MTQ3 | 998 | adding yahoo_answers_qa | [] | closed | false | null | 0 | 2020-12-02T12:33:54Z | 2020-12-02T13:45:40Z | 2020-12-02T13:26:06Z | null | Adding Yahoo Answers QA dataset.
More info:
https://ciir.cs.umass.edu/downloads/nfL6/ | {
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https://api.github.com/repos/huggingface/datasets/issues/5601 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5601/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5601/comments | https://api.github.com/repos/huggingface/datasets/issues/5601/events | https://github.com/huggingface/datasets/issues/5601 | 1,606,685,976 | I_kwDODunzps5fxBUY | 5,601 | Authorization error | [] | closed | false | null | 2 | 2023-03-02T12:08:39Z | 2023-03-14T16:55:35Z | 2023-03-14T16:55:34Z | null | ### Describe the bug
Get `Authorization error` when try to push data into hugginface datasets hub.
### Steps to reproduce the bug
I did all steps in the [tutorial](https://huggingface.co/docs/datasets/share),
1. `huggingface-cli login` with WRITE token
2. `git lfs install`
3. `git clone https://huggingface.co/datasets/namespace/your_dataset_name`
4.
```
cp /somewhere/data/*.json .
git lfs track *.json
git add .gitattributes
git add *.json
git commit -m "add json files"
```
but when I execute `git push` I got the error:
```
Uploading LFS objects: 0% (0/1), 0 B | 0 B/s, done.
batch response: Authorization error.
error: failed to push some refs to 'https://huggingface.co/datasets/zeusfsx/ukrainian-news'
```
Size of data ~100Gb. I have five json files - different parts.
### Expected behavior
All my data pushed into hub
### Environment info
- `datasets` version: 2.10.1
- Platform: macOS-13.2.1-arm64-arm-64bit
- Python version: 3.10.10
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | {
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"Hi! \r\n\r\nIt's better to report this kind of issue in the `huggingface_hub` repo, so if you still haven't resolved it, I suggest you open an issue there.",
"Yeah, I solved it. Problem was in osxkeychain. When I do `hugginface-cli login` it's add token with default account (username)`hg_user` but my repo cont... |
https://api.github.com/repos/huggingface/datasets/issues/1302 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1302/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1302/comments | https://api.github.com/repos/huggingface/datasets/issues/1302/events | https://github.com/huggingface/datasets/pull/1302 | 759,435,740 | MDExOlB1bGxSZXF1ZXN0NTM0NDQyNTA0 | 1,302 | Add Danish NER dataset | [] | closed | false | null | 0 | 2020-12-08T13:13:54Z | 2020-12-10T09:35:26Z | 2020-12-10T09:35:26Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2678 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2678/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2678/comments | https://api.github.com/repos/huggingface/datasets/issues/2678/events | https://github.com/huggingface/datasets/issues/2678 | 948,471,222 | MDU6SXNzdWU5NDg0NzEyMjI= | 2,678 | Import Error in Kaggle notebook | [
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] | closed | false | null | 4 | 2021-07-20T09:28:38Z | 2021-07-21T13:59:26Z | 2021-07-21T13:03:02Z | null | ## Describe the bug
Not able to import datasets library in kaggle notebooks
## Steps to reproduce the bug
```python
!pip install datasets
import datasets
```
## Expected results
No such error
## Actual results
```
ImportError Traceback (most recent call last)
<ipython-input-9-652e886d387f> in <module>
----> 1 import datasets
/opt/conda/lib/python3.7/site-packages/datasets/__init__.py in <module>
31 )
32
---> 33 from .arrow_dataset import Dataset, concatenate_datasets
34 from .arrow_reader import ArrowReader, ReadInstruction
35 from .arrow_writer import ArrowWriter
/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py in <module>
36 import pandas as pd
37 import pyarrow as pa
---> 38 import pyarrow.compute as pc
39 from multiprocess import Pool, RLock
40 from tqdm.auto import tqdm
/opt/conda/lib/python3.7/site-packages/pyarrow/compute.py in <module>
16 # under the License.
17
---> 18 from pyarrow._compute import ( # noqa
19 Function,
20 FunctionOptions,
ImportError: /opt/conda/lib/python3.7/site-packages/pyarrow/_compute.cpython-37m-x86_64-linux-gnu.so: undefined symbol: _ZNK5arrow7compute15KernelSignature8ToStringEv
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.9.0
- Platform: Kaggle
- Python version: 3.7.10
- PyArrow version: 4.0.1
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"This looks like an issue with PyArrow. Did you try reinstalling it ?",
"@lhoestq I did, and then let pip handle the installation in `pip import datasets`. I also tried using conda but it gives the same error.\r\n\r\nEdit: pyarrow version on kaggle is 4.0.0, it gets replaced with 4.0.1. So, I don't think uninstal... |
https://api.github.com/repos/huggingface/datasets/issues/4821 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4821/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4821/comments | https://api.github.com/repos/huggingface/datasets/issues/4821/events | https://github.com/huggingface/datasets/pull/4821 | 1,335,664,588 | PR_kwDODunzps49AvaE | 4,821 | Fix train_test_split docs | [] | closed | false | null | 1 | 2022-08-11T08:55:45Z | 2022-08-11T09:59:29Z | 2022-08-11T09:45:40Z | null | I saw that `stratify` is added to the `train_test_split` method as per #4322, hence the docs can be updated. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/4407 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4407/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4407/comments | https://api.github.com/repos/huggingface/datasets/issues/4407/events | https://github.com/huggingface/datasets/issues/4407 | 1,248,671,778 | I_kwDODunzps5KbTgi | 4,407 | Dataset Viewer issue for conll2012_ontonotesv5 | [
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] | closed | false | null | 3 | 2022-05-25T20:18:33Z | 2022-06-07T18:39:16Z | 2022-06-07T18:39:16Z | null | ### Link
https://huggingface.co/datasets/conll2012_ontonotesv5
### Description
Dataset viewer outage.
### Owner
No | {
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"Thanks for reporting, @jiangwy99.\r\n\r\nI guess this could be addressed only once we fix our issue with irresponsive backend endpoint.\r\n\r\nCC: @severo ",
"I've just sent the forcing of the refresh of the preview to the new endpoint.",
"Fixed, thanks for the patience. The issue was the amount of RAM allowed... |
https://api.github.com/repos/huggingface/datasets/issues/2461 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2461/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2461/comments | https://api.github.com/repos/huggingface/datasets/issues/2461/events | https://github.com/huggingface/datasets/pull/2461 | 915,286,150 | MDExOlB1bGxSZXF1ZXN0NjY1MTE3MTY4 | 2,461 | Support sliced list arrays in cast | [] | closed | false | null | 0 | 2021-06-08T17:38:47Z | 2021-06-08T17:56:24Z | 2021-06-08T17:56:23Z | null | There is this issue in pyarrow:
```python
import pyarrow as pa
arr = pa.array([[i * 10] for i in range(4)])
arr.cast(pa.list_(pa.int32())) # works
arr = arr.slice(1)
arr.cast(pa.list_(pa.int32())) # fails
# ArrowNotImplementedError("Casting sliced lists (non-zero offset) not yet implemented")
```
However in `Dataset.cast` we slice tables to cast their types (it's memory intensive), so we have the same issue.
Because of this it is currently not possible to cast a Dataset with a Sequence feature type (unless the table is small enough to not be sliced).
In this PR I fixed this by resetting the offset of `pyarrow.ListArray` arrays to zero in the table before casting.
I used `pyarrow.compute.subtract` function to update the offsets of the ListArray.
cc @abhi1thakur @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/1870 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1870/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1870/comments | https://api.github.com/repos/huggingface/datasets/issues/1870/events | https://github.com/huggingface/datasets/pull/1870 | 807,306,564 | MDExOlB1bGxSZXF1ZXN0NTcyNTc4Mjc4 | 1,870 | Implement Dataset add_item | [
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} | 5 | 2021-02-12T15:03:46Z | 2021-04-23T10:01:31Z | 2021-04-23T10:01:31Z | null | Implement `Dataset.add_item`.
Close #1854. | {
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"Thanks @lhoestq for your remarks. Yes, I agree there are still many issues to be tackled... This PR is just a starting point, so that we can discuss how Dataset should be generalized.",
"Sure ! I opened an issue #1877 so we can discuss this specific aspect :)",
"I am going to implement this consolidation step ... |
https://api.github.com/repos/huggingface/datasets/issues/2182 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2182/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2182/comments | https://api.github.com/repos/huggingface/datasets/issues/2182/events | https://github.com/huggingface/datasets/pull/2182 | 852,384,872 | MDExOlB1bGxSZXF1ZXN0NjEwNjQ2MDIy | 2,182 | Set default in-memory value depending on the dataset size | [
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} | 4 | 2021-04-07T13:00:18Z | 2021-04-20T14:20:12Z | 2021-04-20T10:04:04Z | null | Set a default value for `in_memory` depending on the size of the dataset to be loaded.
Close #2179.
TODO:
- [x] Add a section in the docs about this.
- ~Add a warning if someone tries to specify `cache_file_name=` in `map`, `filter` etc. on a dataset that is in memory, since the computation is not going to be cached in this case.~ | {
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"I ping @krandiash to keep him up to date.",
"TODO:\r\n- [x] Add a section in the docs about this.\r\n- ~Add a warning if someone tries to specify `cache_file_name=` in `map`, `filter` etc. on a dataset that is in memory, since the computation is not going to be cached in this case.~",
"@lhoestq I have a questi... |
https://api.github.com/repos/huggingface/datasets/issues/3153 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3153/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3153/comments | https://api.github.com/repos/huggingface/datasets/issues/3153/events | https://github.com/huggingface/datasets/pull/3153 | 1,034,179,198 | PR_kwDODunzps4tlEVE | 3,153 | Add TER (as implemented in sacrebleu) | [] | closed | false | null | 1 | 2021-10-23T14:26:45Z | 2021-11-02T11:04:11Z | 2021-11-02T11:04:11Z | null | Implements TER (Translation Edit Rate) as per its implementation in sacrebleu. Sacrebleu for BLEU scores is already implemented in `datasets` so I thought this would be a nice addition.
I started from the sacrebleu implementation, as the two metrics have a lot in common.
Verified with sacrebleu's [testing suite](https://github.com/mjpost/sacrebleu/blob/078c440168c6adc89ba75fe6d63f0d922d42bcfe/test/test_ter.py) that this indeed works as intended.
```python
import datasets
test_cases = [
(['aaaa bbbb cccc dddd'], ['aaaa bbbb cccc dddd'], 0), # perfect match
(['dddd eeee ffff'], ['aaaa bbbb cccc'], 1), # no overlap
([''], ['a'], 1), # corner case, empty hypothesis
(['d e f g h a b c'], ['a b c d e f g h'], 1 / 8), # a single shift fixes MT
(
[
'wählen Sie " Bild neu berechnen , " um beim Ändern der Bildgröße Pixel hinzuzufügen oder zu entfernen , damit das Bild ungefähr dieselbe Größe aufweist wie die andere Größe .',
'wenn Sie alle Aufgaben im aktuellen Dokument aktualisieren möchten , wählen Sie im Menü des Aufgabenbedienfelds die Option " Alle Aufgaben aktualisieren . "',
'klicken Sie auf der Registerkarte " Optionen " auf die Schaltfläche " Benutzerdefiniert " und geben Sie Werte für " Fehlerkorrektur-Level " und " Y / X-Verhältnis " ein .',
'Sie können beispielsweise ein Dokument erstellen , das ein Auto über die Bühne enthält .',
'wählen Sie im Dialogfeld " Neu aus Vorlage " eine Vorlage aus und klicken Sie auf " Neu . "',
],
[
'wählen Sie " Bild neu berechnen , " um beim Ändern der Bildgröße Pixel hinzuzufügen oder zu entfernen , damit die Darstellung des Bildes in einer anderen Größe beibehalten wird .',
'wenn Sie alle Aufgaben im aktuellen Dokument aktualisieren möchten , wählen Sie im Menü des Aufgabenbedienfelds die Option " Alle Aufgaben aktualisieren . "',
'klicken Sie auf der Registerkarte " Optionen " auf die Schaltfläche " Benutzerdefiniert " und geben Sie für " Fehlerkorrektur-Level " und " Y / X-Verhältnis " niedrigere Werte ein .',
'Sie können beispielsweise ein Dokument erstellen , das ein Auto enthalt , das sich über die Bühne bewegt .',
'wählen Sie im Dialogfeld " Neu aus Vorlage " eine Vorlage aus und klicken Sie auf " Neu . "',
],
0.136 # realistic example from WMT dev data (2019)
),
]
ter = datasets.load_metric(r"path\to\datasets\metrics\ter")
predictions = ["hello there general kenobi", "foo bar foobar"]
references = [["hello there general kenobi", "hello there !"], ["foo bar foobar", "foo bar foobar"]]
print(ter.compute(predictions=predictions, references=references))
for hyp, ref, score in test_cases:
# Note the reference transformation which is different from scarebleu's input format
results = ter.compute(predictions=hyp, references=[[r] for r in ref])
assert 100*score == results["score"], f"expected {100*score}, got {results['score']}"
```
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"The problem appears to stem from the omission of the lines that you mentioned. If you add them back and try examples from [this](https://huggingface.co/docs/datasets/using_metrics.html) tutorial (sacrebleu metric example) the code you implemented works fine.\r\n\r\nI think the purpose of these lines is follows:\r\... |
https://api.github.com/repos/huggingface/datasets/issues/2815 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2815/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2815/comments | https://api.github.com/repos/huggingface/datasets/issues/2815/events | https://github.com/huggingface/datasets/pull/2815 | 973,862,024 | MDExOlB1bGxSZXF1ZXN0NzE1MjUxNDQ5 | 2,815 | Tiny typo fixes of "fo" -> "of" | [] | closed | false | null | 0 | 2021-08-18T16:36:11Z | 2021-08-19T08:03:02Z | 2021-08-19T08:03:02Z | null | Noticed a few of these when reading docs- feel free to ignore the PR and just fix on some main contributor branch if more helpful. Thanks for the great library! :) | {
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https://api.github.com/repos/huggingface/datasets/issues/2254 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2254/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2254/comments | https://api.github.com/repos/huggingface/datasets/issues/2254/events | https://github.com/huggingface/datasets/pull/2254 | 866,169,312 | MDExOlB1bGxSZXF1ZXN0NjIyMTE1NDI0 | 2,254 | Update format, fingerprint and indices after add_item | [] | closed | false | null | 1 | 2021-04-23T14:31:49Z | 2021-04-27T16:30:49Z | 2021-04-27T16:30:48Z | null | Added fingerprint and format update wrappers + update the indices by adding the index of the newly added item in the table. | {
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"I renamed the variable, added a test for dataset._indices and fixed an issue with class_encode_column"
] |
https://api.github.com/repos/huggingface/datasets/issues/3281 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3281/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3281/comments | https://api.github.com/repos/huggingface/datasets/issues/3281/events | https://github.com/huggingface/datasets/pull/3281 | 1,055,018,876 | PR_kwDODunzps4umWZE | 3,281 | [Datasets] Improve Covost 2 | [] | closed | false | null | 2 | 2021-11-16T15:32:19Z | 2022-01-26T16:17:06Z | 2021-11-18T10:44:04Z | null | It's currently quite confusing to understand the manual data download instruction of Covost and not very user-friendly.
Currenty the user has to:
1. Go on Common Voice website
2. Find the correct dataset which is **not** mentioned in the error message
3. Download it
4. Untar it
5. Create a language id folder (why? this folder does not exist in the `.tar` downloaded file)
6. pass the folder containing the created language id folder
This PR improves this to:
1. Go on Common Voice website
2. Find the correct dataset which **is** mentioned in the error message
3. Download it
4. Untar it
5. pass the untared folder
**Note**: This PR is not at all time-critical | {
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"I am trying to use `load_dataset` with the French dataset(common voice corpus 1) which is downloaded from a common voice site and the target language is English (using colab)\r\n\r\nSteps I have followed:\r\n\r\n**1. untar:**\r\n`!tar xvzf fr.tar -C data_dir`\r\n\r\n**2. load data:**\r\n`load_dataset('covost2', 'f... |
https://api.github.com/repos/huggingface/datasets/issues/5045 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5045/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5045/comments | https://api.github.com/repos/huggingface/datasets/issues/5045/events | https://github.com/huggingface/datasets/issues/5045 | 1,391,287,609 | I_kwDODunzps5S7V05 | 5,045 | Automatically revert to last successful commit to hub when a push_to_hub is interrupted | [
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] | open | false | null | 5 | 2022-09-29T18:08:12Z | 2022-09-30T16:49:21Z | null | null | **Is your feature request related to a problem? Please describe.**
I pushed a modification of a large dataset (remove a column) to the hub. The push was interrupted after some files were committed to the repo. This left the dataset to raise an error on load_dataset() (ValueError couldn’t cast … because column names don’t match). Only by specifying the previous (complete) commit as revision=commit_hash in load_data(), I was able to repair this and after a successful, complete push, the dataset loads without error again.
**Describe the solution you'd like**
Would it make sense to detect an incomplete push_to_hub() and automatically revert to the previous commit/revision?
**Describe alternatives you've considered**
Leave everything as is, the revision parameter in load_dataset() allows to manually fix this problem.
**Additional context**
Provide useful defaults
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"Could you share the error you got please ? Maybe the full stack trace if you have it ?\r\n\r\nMaybe `push_to_hub` be implemented as a single commit @Wauplin ? This way if it fails, the repo is still at the previous (valid) state instead of ending-up in an invalid/incimplete state.",
"> Maybe push_to_hub be imple... |
https://api.github.com/repos/huggingface/datasets/issues/2757 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2757/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2757/comments | https://api.github.com/repos/huggingface/datasets/issues/2757/events | https://github.com/huggingface/datasets/issues/2757 | 959,984,081 | MDU6SXNzdWU5NTk5ODQwODE= | 2,757 | Unexpected type after `concatenate_datasets` | [
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] | closed | false | null | 2 | 2021-08-04T07:10:39Z | 2021-08-04T16:01:24Z | 2021-08-04T16:01:23Z | null | ## Describe the bug
I am trying to concatenate two `Dataset` using `concatenate_datasets` but it turns out that after concatenation the features are casted from `torch.Tensor` to `list`.
It then leads to a weird tensors when trying to convert it to a `DataLoader`. However, if I use each `Dataset` separately everything behave as expected.
## Steps to reproduce the bug
```python
>>> featurized_teacher
Dataset({
features: ['t_labels', 't_input_ids', 't_token_type_ids', 't_attention_mask'],
num_rows: 502
})
>>> for f in featurized_teacher.features:
print(featurized_teacher[f].shape)
torch.Size([502])
torch.Size([502, 300])
torch.Size([502, 300])
torch.Size([502, 300])
>>> featurized_student
Dataset({
features: ['s_features', 's_labels'],
num_rows: 502
})
>>> for f in featurized_student.features:
print(featurized_student[f].shape)
torch.Size([502, 64])
torch.Size([502])
```
The shapes seem alright to me. Then the results after concatenation are as follow:
```python
>>> concat_dataset = datasets.concatenate_datasets([featurized_student, featurized_teacher], axis=1)
>>> type(concat_dataset["t_labels"])
<class 'list'>
```
One would expect to obtain the same type as the one before concatenation.
Am I doing something wrong here? Any idea on how to fix this unexpected behavior?
## Environment info
- `datasets` version: 1.9.0
- Platform: macOS-10.14.6-x86_64-i386-64bit
- Python version: 3.9.5
- PyArrow version: 3.0.0
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} | https://api.github.com/repos/huggingface/datasets/issues/2757/timeline | null | completed | null | null | false | [
"Hi @JulesBelveze, thanks for your question.\r\n\r\nNote that 🤗 `datasets` internally store their data in Apache Arrow format.\r\n\r\nHowever, when accessing dataset columns, by default they are returned as native Python objects (lists in this case).\r\n\r\nIf you would like their columns to be returned in a more... |
https://api.github.com/repos/huggingface/datasets/issues/818 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/818/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/818/comments | https://api.github.com/repos/huggingface/datasets/issues/818/events | https://github.com/huggingface/datasets/pull/818 | 739,173,861 | MDExOlB1bGxSZXF1ZXN0NTE3ODgzMzk0 | 818 | Fix type hints pickling in python 3.6 | [] | closed | false | null | 0 | 2020-11-09T16:27:47Z | 2020-11-10T09:07:03Z | 2020-11-10T09:07:02Z | null | Type hints can't be properly pickled in python 3.6. This was causing errors the `run_mlm.py` script from `transformers` with python 3.6
However Cloupickle proposed a [fix](https://github.com/cloudpipe/cloudpickle/pull/318/files) to make it work anyway.
The idea is just to implement the pickling/unpickling of parameterized type hints. There is one detail though: since in python 3.6 we can't use `isinstance` on type hints, then we can't use pickle saving functions registry directly. Therefore we just wrap the `save_global` method of the Pickler.
This should fix https://github.com/huggingface/transformers/issues/8212 for python 3.6 and make `run_mlm.py` support python 3.6
cc @sgugger | {
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https://api.github.com/repos/huggingface/datasets/issues/543 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/543/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/543/comments | https://api.github.com/repos/huggingface/datasets/issues/543/events | https://github.com/huggingface/datasets/issues/543 | 688,644,407 | MDU6SXNzdWU2ODg2NDQ0MDc= | 543 | nlp.load_dataset is not safe for multi processes when loading from local files | [] | closed | false | null | 1 | 2020-08-30T03:20:34Z | 2020-08-31T11:15:10Z | 2020-08-31T11:15:10Z | null | Loading from local files, e.g., `dataset = nlp.load_dataset('csv', data_files=['file_1.csv', 'file_2.csv'])`
concurrently from multiple processes, will raise `FileExistsError` from builder's line 430, https://github.com/huggingface/nlp/blob/6655008c738cb613c522deb3bd18e35a67b2a7e5/src/nlp/builder.py#L423-L438
Likely because multiple processes step into download_and_prepare, https://github.com/huggingface/nlp/blob/6655008c738cb613c522deb3bd18e35a67b2a7e5/src/nlp/load.py#L550-L554
This can happen when launching distributed training with commands like `python -m torch.distributed.launch --nproc_per_node 4` on a new collection of files never loaded before.
I can create a PR that puts in some file locks. It would be helpful if I can be informed of the convention for naming and placement of the lock. | {
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"I'll take a look!"
] |
https://api.github.com/repos/huggingface/datasets/issues/2521 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2521/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2521/comments | https://api.github.com/repos/huggingface/datasets/issues/2521/events | https://github.com/huggingface/datasets/pull/2521 | 925,030,685 | MDExOlB1bGxSZXF1ZXN0NjczNTgxNzQ4 | 2,521 | Insert text classification template for Emotion dataset | [] | closed | false | null | 0 | 2021-06-18T15:56:19Z | 2021-06-21T09:22:31Z | 2021-06-21T09:22:31Z | null | This PR includes a template and updated `dataset_infos.json` for the `emotion` dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/6073 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6073/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6073/comments | https://api.github.com/repos/huggingface/datasets/issues/6073/events | https://github.com/huggingface/datasets/issues/6073 | 1,822,167,804 | I_kwDODunzps5snBL8 | 6,073 | version2.3.2 load_dataset()data_files can't include .xxxx in path | [] | open | false | null | 1 | 2023-07-26T11:09:31Z | 2023-07-26T12:34:45Z | null | null | ### Describe the bug
First, I cd workdir.
Then, I just use load_dataset("json", data_file={"train":"/a/b/c/.d/train/train.json", "test":"/a/b/c/.d/train/test.json"})
that couldn't work and
<FileNotFoundError: Unable to find
'/a/b/c/.d/train/train.jsonl' at
/a/b/c/.d/>
And I debug, it is fine in version2.1.2
So there maybe a bug in path join.
Here is the whole bug report:
/x/datasets/loa │
│ d.py:1656 in load_dataset │
│ │
│ 1653 │ ignore_verifications = ignore_verifications or save_infos │
│ 1654 │ │
│ 1655 │ # Create a dataset builder │
│ ❱ 1656 │ builder_instance = load_dataset_builder( │
│ 1657 │ │ path=path, │
│ 1658 │ │ name=name, │
│ 1659 │ │ data_dir=data_dir, │
│ │
│ x/datasets/loa │
│ d.py:1439 in load_dataset_builder │
│ │
│ 1436 │ if use_auth_token is not None: │
│ 1437 │ │ download_config = download_config.copy() if download_config e │
│ 1438 │ │ download_config.use_auth_token = use_auth_token │
│ ❱ 1439 │ dataset_module = dataset_module_factory( │
│ 1440 │ │ path, │
│ 1441 │ │ revision=revision, │
│ 1442 │ │ download_config=download_config, │
│ │
│ x/datasets/loa │
│ d.py:1097 in dataset_module_factory │
│ │
│ 1094 │ │
│ 1095 │ # Try packaged │
│ 1096 │ if path in _PACKAGED_DATASETS_MODULES: │
│ ❱ 1097 │ │ return PackagedDatasetModuleFactory( │
│ 1098 │ │ │ path, │
│ 1099 │ │ │ data_dir=data_dir, │
│ 1100 │ │ │ data_files=data_files, │
│ │
│x/datasets/loa │
│ d.py:743 in get_module │
│ │
│ 740 │ │ │ if self.data_dir is not None │
│ 741 │ │ │ else get_patterns_locally(str(Path().resolve())) │
│ 742 │ │ ) │
│ ❱ 743 │ │ data_files = DataFilesDict.from_local_or_remote( │
│ 744 │ │ │ patterns, │
│ 745 │ │ │ use_auth_token=self.download_config.use_auth_token, │
│ 746 │ │ │ base_path=str(Path(self.data_dir).resolve()) if self.data │
│ │
│ x/datasets/dat │
│ a_files.py:590 in from_local_or_remote │
│ │
│ 587 │ │ out = cls() │
│ 588 │ │ for key, patterns_for_key in patterns.items(): │
│ 589 │ │ │ out[key] = ( │
│ ❱ 590 │ │ │ │ DataFilesList.from_local_or_remote( │
│ 591 │ │ │ │ │ patterns_for_key, │
│ 592 │ │ │ │ │ base_path=base_path, │
│ 593 │ │ │ │ │ allowed_extensions=allowed_extensions, │
│ │
│ /x/datasets/dat │
│ a_files.py:558 in from_local_or_remote │
│ │
│ 555 │ │ use_auth_token: Optional[Union[bool, str]] = None, │
│ 556 │ ) -> "DataFilesList": │
│ 557 │ │ base_path = base_path if base_path is not None else str(Path() │
│ ❱ 558 │ │ data_files = resolve_patterns_locally_or_by_urls(base_path, pa │
│ 559 │ │ origin_metadata = _get_origin_metadata_locally_or_by_urls(data │
│ 560 │ │ return cls(data_files, origin_metadata) │
│ 561 │
│ │
│ /x/datasets/dat │
│ a_files.py:195 in resolve_patterns_locally_or_by_urls │
│ │
│ 192 │ │ if is_remote_url(pattern): │
│ 193 │ │ │ data_files.append(Url(pattern)) │
│ 194 │ │ else: │
│ ❱ 195 │ │ │ for path in _resolve_single_pattern_locally(base_path, pat │
│ 196 │ │ │ │ data_files.append(path) │
│ 197 │ │
│ 198 │ if not data_files: │
│ │
│ /x/datasets/dat │
│ a_files.py:145 in _resolve_single_pattern_locally │
│ │
│ 142 │ │ error_msg = f"Unable to find '{pattern}' at {Path(base_path).r │
│ 143 │ │ if allowed_extensions is not None: │
│ 144 │ │ │ error_msg += f" with any supported extension {list(allowed │
│ ❱ 145 │ │ raise FileNotFoundError(error_msg) │
│ 146 │ return sorted(out) │
│ 147
### Steps to reproduce the bug
1. Version=2.3.2
2. In shell, cd workdir.(cd /a/b/c/.d/)
3. load_dataset("json", data_file={"train":"/a/b/c/.d/train/train.json", "test":"/a/b/c/.d/train/test.json"})
### Expected behavior
fix it please~
### Environment info
2.3.2 | {
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"Version 2.3.2 is over one year old, so please use the latest release (2.14.0) to get the expected behavior. Version 2.3.2 does not contain some fixes we made to fix resolving hidden files/directories (starting with a dot)."
] |
https://api.github.com/repos/huggingface/datasets/issues/354 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/354/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/354/comments | https://api.github.com/repos/huggingface/datasets/issues/354/events | https://github.com/huggingface/datasets/pull/354 | 653,357,617 | MDExOlB1bGxSZXF1ZXN0NDQ2MjkyMTc4 | 354 | More faiss control | [] | closed | false | null | 1 | 2020-07-08T14:45:20Z | 2020-07-09T09:54:54Z | 2020-07-09T09:54:51Z | null | Allow users to specify a faiss index they created themselves, as sometimes indexes can be composite for examples | {
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"> Ok, so we're getting rid of the `FaissGpuOptions`?\r\n\r\nWe support `device=...` because it's simple, but faiss GPU options can be used in so many ways (you can set different gpu options for the different parts of your index for example) that it's probably better to let the user create and configure its index a... |
https://api.github.com/repos/huggingface/datasets/issues/5534 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5534/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5534/comments | https://api.github.com/repos/huggingface/datasets/issues/5534/events | https://github.com/huggingface/datasets/issues/5534 | 1,586,177,862 | I_kwDODunzps5eiydG | 5,534 | map() breaks at certain dataset size when using Array3D | [] | open | false | null | 2 | 2023-02-15T16:34:25Z | 2023-03-03T16:31:33Z | null | null | ### Describe the bug
`map()` magically breaks when using a `Array3D` feature and mapping it. I created a very simple dummy dataset (see below). When filtering it down to 95 elements I can apply map, but it breaks when filtering it down to just 96 entries with the following exception:
```
Traceback (most recent call last):
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3255, in _map_single
writer.finalize() # close_stream=bool(buf_writer is None)) # We only close if we are writing in a file
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/arrow_writer.py", line 581, in finalize
self.write_examples_on_file()
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/arrow_writer.py", line 440, in write_examples_on_file
batch_examples[col] = array_concat(arrays)
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/table.py", line 1931, in array_concat
return _concat_arrays(arrays)
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/table.py", line 1901, in _concat_arrays
return array_type.wrap_array(_concat_arrays([array.storage for array in arrays]))
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/table.py", line 1922, in _concat_arrays
_concat_arrays([array.values for array in arrays]),
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/table.py", line 1922, in _concat_arrays
_concat_arrays([array.values for array in arrays]),
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/table.py", line 1920, in _concat_arrays
return pa.ListArray.from_arrays(
File "pyarrow/array.pxi", line 1997, in pyarrow.lib.ListArray.from_arrays
File "pyarrow/array.pxi", line 1527, in pyarrow.lib.Array.validate
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Negative offsets in list array
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 2815, in map
return self._map_single(
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 546, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 513, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/fingerprint.py", line 480, in wrapper
out = func(self, *args, **kwargs)
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3259, in _map_single
writer.finalize()
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/arrow_writer.py", line 581, in finalize
self.write_examples_on_file()
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/arrow_writer.py", line 440, in write_examples_on_file
batch_examples[col] = array_concat(arrays)
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/table.py", line 1931, in array_concat
return _concat_arrays(arrays)
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/table.py", line 1901, in _concat_arrays
return array_type.wrap_array(_concat_arrays([array.storage for array in arrays]))
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/table.py", line 1922, in _concat_arrays
_concat_arrays([array.values for array in arrays]),
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/table.py", line 1922, in _concat_arrays
_concat_arrays([array.values for array in arrays]),
File "/home/arbi01/miniconda3/envs/tmp9/lib/python3.9/site-packages/datasets/table.py", line 1920, in _concat_arrays
return pa.ListArray.from_arrays(
File "pyarrow/array.pxi", line 1997, in pyarrow.lib.ListArray.from_arrays
File "pyarrow/array.pxi", line 1527, in pyarrow.lib.Array.validate
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Negative offsets in list array
```
### Steps to reproduce the bug
1. put following dataset loading script into: debug/debug.py
```python
import datasets
import numpy as np
class DEBUG(datasets.GeneratorBasedBuilder):
"""DEBUG dataset."""
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features(
{
"id": datasets.Value("uint8"),
"img_data": datasets.Array3D(shape=(3, 224, 224), dtype="uint8"),
},
),
supervised_keys=None,
)
def _split_generators(self, dl_manager):
return [datasets.SplitGenerator(name=datasets.Split.TRAIN)]
def _generate_examples(self):
for i in range(149):
image_np = np.zeros(shape=(3, 224, 224), dtype=np.int8).tolist()
yield f"id_{i}", {"id": i, "img_data": image_np}
```
2. try the following code:
```python
import datasets
def add_dummy_col(ex):
ex["dummy"] = "test"
return ex
ds = datasets.load_dataset(path="debug", split="train")
# works
ds_filtered_works = ds.filter(lambda example: example["id"] < 95)
print(f"filtered result size: {len(ds_filtered_works)}")
# output:
# filtered result size: 95
ds_mapped_works = ds_filtered_works.map(add_dummy_col)
# fails
ds_filtered_error = ds.filter(lambda example: example["id"] < 96)
print(f"filtered result size: {len(ds_filtered_error)}")
# output:
# filtered result size: 96
ds_mapped_error = ds_filtered_error.map(add_dummy_col)
```
### Expected behavior
The example code does not fail.
### Environment info
Python 3.9.16 (main, Jan 11 2023, 16:05:54); [GCC 11.2.0] :: Anaconda, Inc. on linux
datasets 2.9.0 | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5534/timeline | null | null | null | null | false | [
"Hi! This code works for me locally or in Colab. What's the output of `python -c \"import pyarrow as pa; print(pa.__version__)\"` when you run it inside your environment?",
"Thanks for looking into this!\r\nThe output of `python -c \"import pyarrow as pa; print(pa.__version__)\"` is:\r\n```\r\n11.0.0\r\n```\r\n\... |
https://api.github.com/repos/huggingface/datasets/issues/2506 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2506/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2506/comments | https://api.github.com/repos/huggingface/datasets/issues/2506/events | https://github.com/huggingface/datasets/pull/2506 | 921,435,598 | MDExOlB1bGxSZXF1ZXN0NjcwNDM4NTgx | 2,506 | Add course banner | [] | closed | false | null | 0 | 2021-06-15T14:03:54Z | 2021-06-15T16:25:36Z | 2021-06-15T16:25:35Z | null | This PR adds a course banner similar to the one you can now see in the [Transformers repo](https://github.com/huggingface/transformers) that links to the course. Let me know if placement seems right to you or not, I can move it just below the badges too. | {
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https://api.github.com/repos/huggingface/datasets/issues/1895 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1895/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1895/comments | https://api.github.com/repos/huggingface/datasets/issues/1895/events | https://github.com/huggingface/datasets/issues/1895 | 809,630,271 | MDU6SXNzdWU4MDk2MzAyNzE= | 1,895 | Bug Report: timestamp[ns] not recognized | [] | closed | false | null | 5 | 2021-02-16T20:38:04Z | 2021-02-19T18:27:11Z | 2021-02-19T18:27:11Z | null | Repro:
```
from datasets import Dataset
import pandas as pd
import pyarrow
df = pd.DataFrame(pd.date_range("2018-01-01", periods=3, freq="H"))
pyarrow.Table.from_pandas(df)
Dataset.from_pandas(df)
# Throws ValueError: Neither timestamp[ns] nor timestamp[ns]_ seems to be a pyarrow data type.
```
The factory function seems to be just "timestamp": https://arrow.apache.org/docs/python/generated/pyarrow.timestamp.html#pyarrow.timestamp
It seems like https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L36-L43 could have a little bit of additional structure for handling these cases? I'd be happy to take a shot at opening a PR if I could receive some guidance on whether parsing something like `timestamp[ns]` and resolving it to timestamp('ns') is the goal of this method.
Alternatively, if I'm using this incorrectly (e.g. is the expectation that we always provide a schema when timestamps are involved?), that would be very helpful to know as well!
```
$ pip list # only the relevant libraries/versions
datasets 1.2.1
pandas 1.0.3
pyarrow 3.0.0
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/1895/timeline | null | completed | null | null | false | [
"Thanks for reporting !\r\n\r\nYou're right, `string_to_arrow` should be able to take `\"timestamp[ns]\"` as input and return the right pyarrow timestamp type.\r\nFeel free to suggest a fix for `string_to_arrow` and open a PR if you want to contribute ! This would be very appreciated :)\r\n\r\nTo give you more cont... |
https://api.github.com/repos/huggingface/datasets/issues/1122 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1122/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1122/comments | https://api.github.com/repos/huggingface/datasets/issues/1122/events | https://github.com/huggingface/datasets/pull/1122 | 757,176,172 | MDExOlB1bGxSZXF1ZXN0NTMyNTk1ODE5 | 1,122 | Add Urdu fake news. | [] | closed | false | null | 0 | 2020-12-04T15:13:10Z | 2020-12-04T15:20:07Z | 2020-12-04T15:20:07Z | null | Added Urdu fake news dataset. More information about the dataset can be found <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>. | {
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https://api.github.com/repos/huggingface/datasets/issues/3582 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3582/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3582/comments | https://api.github.com/repos/huggingface/datasets/issues/3582/events | https://github.com/huggingface/datasets/issues/3582 | 1,104,877,303 | I_kwDODunzps5B2xb3 | 3,582 | conll 2003 dataset source url is no longer valid | [
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"descrip... | closed | false | null | 9 | 2022-01-15T23:04:17Z | 2022-07-20T13:06:40Z | 2022-01-21T16:57:32Z | null | ## Describe the bug
Loading `conll2003` dataset fails because it was removed (just yesterday 1/14/2022) from the location it is looking for.
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset("conll2003")
```
## Expected results
The dataset should load.
## Actual results
It is looking for the dataset at `https://github.com/davidsbatista/NER-datasets/raw/master/CONLL2003/train.txt` but it was removed from there yesterday (see [commit](https://github.com/davidsbatista/NER-datasets/commit/9d8f45cc7331569af8eb3422bbe1c97cbebd5690) that removed the file and related [issue](https://github.com/davidsbatista/NER-datasets/issues/8)).
- We should replace this with an alternate valid location.
- this is being referenced in the huggingface course chapter 7 [colab notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/chapter7/section2_pt.ipynb), which is also broken.
```python
FileNotFoundError Traceback (most recent call last)
<ipython-input-4-27c956bec93c> in <module>()
1 from datasets import load_dataset
2
----> 3 raw_datasets = load_dataset("conll2003")
11 frames
/usr/local/lib/python3.7/dist-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag, max_retries, use_auth_token, ignore_url_params)
610 )
611 elif response is not None and response.status_code == 404:
--> 612 raise FileNotFoundError(f"Couldn't find file at {url}")
613 _raise_if_offline_mode_is_enabled(f"Tried to reach {url}")
614 if head_error is not None:
FileNotFoundError: Couldn't find file at https://github.com/davidsbatista/NER-datasets/raw/master/CONLL2003/train.txt
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- Platform:
- Python version:
- PyArrow version:
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"I came to open the same issue.",
"Thanks for reporting !\r\n\r\nI pushed a temporary fix on `master` that uses an URL from a previous commit to access the dataset for now, until we have a better solution",
"I changed the URL again to use another host, the fix is available on `master` and we'll probably do a ne... |
https://api.github.com/repos/huggingface/datasets/issues/1619 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1619/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1619/comments | https://api.github.com/repos/huggingface/datasets/issues/1619/events | https://github.com/huggingface/datasets/pull/1619 | 772,508,558 | MDExOlB1bGxSZXF1ZXN0NTQzNzYyMTUw | 1,619 | data loader for reading comprehension task | [] | closed | false | null | 2 | 2020-12-21T22:40:34Z | 2020-12-28T10:32:53Z | 2020-12-28T10:32:53Z | null | added doc2dial data loader and dummy data for reading comprehension task. | {
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} | true | [
"Thank you for all the feedback! I have updated the dummy data with a zip under 30KB, which needs to include at least one data instance from both document domain and dialog domain. Please let me know if it is still too big. Thanks!",
"Thank you again for the feedback! I am not too sure what the preferable style f... |
https://api.github.com/repos/huggingface/datasets/issues/3285 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3285/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3285/comments | https://api.github.com/repos/huggingface/datasets/issues/3285/events | https://github.com/huggingface/datasets/issues/3285 | 1,055,506,730 | I_kwDODunzps4-6cEq | 3,285 | Add IEMOCAP dataset | [
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"description": "Requesting to add a new dataset",
"id": 2067376369,
"name": "dataset request",
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{
"color": "d93f0b",... | open | false | null | 8 | 2021-11-16T22:47:20Z | 2023-06-10T08:14:52Z | null | null | ## Adding a Dataset
- **Name:** IEMOCAP
- **Description:** acted, multimodal and multispeaker database
- **Paper:** https://sail.usc.edu/iemocap/Busso_2008_iemocap.pdf
- **Data:** https://sail.usc.edu/iemocap/index.html
- **Motivation:** Useful multimodal dataset
cc @anton-l
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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} | https://api.github.com/repos/huggingface/datasets/issues/3285/timeline | null | null | null | null | false | [
"The IEMOCAP dataset is private and available only on request.\r\n```\r\nTo obtain the IEMOCAP data you just need to fill out an electronic release form below.\r\n```\r\n\r\n- [Request form](https://sail.usc.edu/iemocap/release_form.php)\r\n- [License ](https://sail.usc.edu/iemocap/Data_Release_Form_IEMOCAP.pdf)\r\... |
https://api.github.com/repos/huggingface/datasets/issues/1934 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1934/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1934/comments | https://api.github.com/repos/huggingface/datasets/issues/1934/events | https://github.com/huggingface/datasets/issues/1934 | 814,437,190 | MDU6SXNzdWU4MTQ0MzcxOTA= | 1,934 | Add Stanford Sentiment Treebank (SST) | [
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] | closed | false | null | 1 | 2021-02-23T12:53:16Z | 2021-03-18T17:51:44Z | 2021-03-18T17:51:44Z | null | I am going to add SST:
- **Name:** The Stanford Sentiment Treebank
- **Description:** The first corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language
- **Paper:** [Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank](https://nlp.stanford.edu/~socherr/EMNLP2013_RNTN.pdf)
- **Data:** https://nlp.stanford.edu/sentiment/index.html
- **Motivation:** Already requested in #353, SST is a popular dataset for Sentiment Classification
What's the difference with the [_SST-2_](https://huggingface.co/datasets/viewer/?dataset=glue&config=sst2) dataset included in GLUE? Essentially, SST-2 is a version of SST where:
- the labels were mapped from real numbers in [0.0, 1.0] to a binary label: {0, 1}
- the labels of the *sub-sentences* were included only in the training set
- the labels in the test set are obfuscated
So there is a lot more information in the original SST. The tricky bit is, the data is scattered into many text files and, for one in particular, I couldn't find the original encoding ([*but I'm not the only one*](https://groups.google.com/g/word2vec-toolkit/c/QIUjLw6RqFk/m/_iEeyt428wkJ) 🎵). The only solution I found was to manually replace all the è, ë, ç and so on into an `utf-8` copy of the text file. I uploaded the result in my Dropbox and I am using that as the main repo for the dataset.
Also, the _sub-sentences_ are built at run-time from the information encoded in several text files, so generating the examples is a bit more cumbersome than usual. Luckily, the dataset is not enormous.
I plan to divide the dataset in 2 configs: one with just whole sentences with their labels, the other with sentences _and their sub-sentences_ with their labels. Each config will be split in train, validation and test. Hopefully this makes sense, we may discuss it in the PR I'm going to submit.
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"Dataset added in release [1.5.0](https://github.com/huggingface/datasets/releases/tag/1.5.0), I think I can close this."
] |
https://api.github.com/repos/huggingface/datasets/issues/1001 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1001/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1001/comments | https://api.github.com/repos/huggingface/datasets/issues/1001/events | https://github.com/huggingface/datasets/pull/1001 | 755,309,071 | MDExOlB1bGxSZXF1ZXN0NTMxMDQ0NDQ0 | 1,001 | Adding Medal: MeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretraining | [] | closed | false | null | 1 | 2020-12-02T14:12:30Z | 2020-12-02T14:13:12Z | 2020-12-02T14:13:12Z | null | null | {
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"Dupe"
] |
https://api.github.com/repos/huggingface/datasets/issues/3906 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3906/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3906/comments | https://api.github.com/repos/huggingface/datasets/issues/3906/events | https://github.com/huggingface/datasets/issues/3906 | 1,168,496,328 | I_kwDODunzps5FpdbI | 3,906 | NonMatchingChecksumError on Spider dataset | [
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] | closed | false | null | 1 | 2022-03-14T14:54:53Z | 2022-03-15T07:09:51Z | 2022-03-15T07:09:51Z | null | ## Describe the bug
Failure to generate dataset ```spider``` because of checksums error for dataset source files.
## Steps to reproduce the bug
```
from datasets import load_dataset
spider = load_dataset("spider")
```
## Expected results
Checksums should match for files from url ['https://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0']
## Actual results
```
>>> load_dataset("spider")
load_dataset("spider")
Downloading and preparing dataset spider/spider (download: 95.12 MiB, generated: 5.17 MiB, post-processed: Unknown size, total: 100.29 MiB) to /home/user/.cache/huggingface/datasets/spider/spider/1.0.0/79778ebea87c59b19411f1eb3eda317e9dd5f7788a556d837ef25c3ae6e5e8b7...
Traceback (most recent call last):
File "/home/user/py3_env/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3441, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-5-d4cb54197348>", line 1, in <module>
load_dataset("spider")
File "/home/user/py3_env/lib/python3.8/site-packages/datasets/load.py", line 1702, in load_dataset
builder_instance.download_and_prepare(
File "/home/user/py3_env/lib/python3.8/site-packages/datasets/builder.py", line 594, in download_and_prepare
self._download_and_prepare(
File "/home/user/py3_env/lib/python3.8/site-packages/datasets/builder.py", line 665, in _download_and_prepare
verify_checksums(
File "/home/user/py3_env/lib/python3.8/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0']
```
## Environment info
datasets version: 1.18.3
Platform: Ubuntu 20 LTS
Python version: 3.8.10
PyArrow version: 6.0.1
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"Hi @kolk, thanks for reporting.\r\n\r\nIndeed, Google Drive service recently changed their service and we had to add a fix to our library to cope with that change:\r\n- #3787 \r\n\r\nWe just made patch release last week: 1.18.4 https://github.com/huggingface/datasets/releases/tag/1.18.4\r\n\r\nPlease, feel free to... |
https://api.github.com/repos/huggingface/datasets/issues/3274 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3274/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3274/comments | https://api.github.com/repos/huggingface/datasets/issues/3274/events | https://github.com/huggingface/datasets/pull/3274 | 1,053,689,140 | PR_kwDODunzps4uiL8- | 3,274 | Fix some contact information formats | [] | closed | false | null | 1 | 2021-11-15T13:50:34Z | 2021-11-15T14:43:55Z | 2021-11-15T14:43:54Z | null | As reported in https://github.com/huggingface/datasets/issues/3188 some contact information are not displayed correctly.
This PR fixes this for CoNLL-2002 and some other datasets with the same issue | {
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"The CI fail are caused by some missing sections or tags, which is unrelated to this PR. Merging !"
] |
https://api.github.com/repos/huggingface/datasets/issues/1420 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1420/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1420/comments | https://api.github.com/repos/huggingface/datasets/issues/1420/events | https://github.com/huggingface/datasets/pull/1420 | 760,700,388 | MDExOlB1bGxSZXF1ZXN0NTM1NDg4MTM5 | 1,420 | Add dataset yoruba_wordsim353 | [] | closed | false | null | 1 | 2020-12-09T21:54:29Z | 2020-12-11T13:34:04Z | 2020-12-11T13:34:04Z | null | Contains loading script as well as dataset card including YAML tags. | {
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"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/4847 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4847/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4847/comments | https://api.github.com/repos/huggingface/datasets/issues/4847/events | https://github.com/huggingface/datasets/pull/4847 | 1,338,270,636 | PR_kwDODunzps49JNWX | 4,847 | Test win ci | [] | closed | false | null | 0 | 2022-08-14T14:57:00Z | 2022-08-14T14:57:45Z | 2022-08-14T14:57:45Z | null | aa | {
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https://api.github.com/repos/huggingface/datasets/issues/4621 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4621/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4621/comments | https://api.github.com/repos/huggingface/datasets/issues/4621/events | https://github.com/huggingface/datasets/issues/4621 | 1,293,030,128 | I_kwDODunzps5NEhLw | 4,621 | ImageFolder raises an error with parameters drop_metadata=True and drop_labels=False when metadata.jsonl is present | [
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"color": "d73a4a",
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"description": "Something isn't working",
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"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
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] | closed | false | null | 0 | 2022-07-04T11:21:44Z | 2022-07-15T14:24:24Z | 2022-07-15T14:24:24Z | null | ## Describe the bug
If you pass `drop_metadata=True` and `drop_labels=False` when a `data_dir` contains at least one `matadata.jsonl` file, you will get a KeyError. This is probably not a very useful case but we shouldn't get an error anyway. Asking users to move metadata files manually outside `data_dir` or pass features manually (when there is a tool that can infer them automatically) don't look like a good idea to me either.
## Steps to reproduce the bug
### Clone an example dataset from the Hub
```bash
git clone https://huggingface.co/datasets/nateraw/test-imagefolder-metadata
```
### Try to load it
```python
from datasets import load_dataset
ds = load_dataset("test-imagefolder-metadata", drop_metadata=True, drop_labels=False)
```
or even just
```python
ds = load_dataset("test-imagefolder-metadata", drop_metadata=True)
```
as `drop_labels=False` is a default value.
## Expected results
A DatasetDict object with two features: `"image"` and `"label"`.
## Actual results
```
Traceback (most recent call last):
File "/home/polina/workspace/datasets/debug.py", line 18, in <module>
ds = load_dataset(
File "/home/polina/workspace/datasets/src/datasets/load.py", line 1732, in load_dataset
builder_instance.download_and_prepare(
File "/home/polina/workspace/datasets/src/datasets/builder.py", line 704, in download_and_prepare
self._download_and_prepare(
File "/home/polina/workspace/datasets/src/datasets/builder.py", line 1227, in _download_and_prepare
super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos)
File "/home/polina/workspace/datasets/src/datasets/builder.py", line 793, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/polina/workspace/datasets/src/datasets/builder.py", line 1218, in _prepare_split
example = self.info.features.encode_example(record)
File "/home/polina/workspace/datasets/src/datasets/features/features.py", line 1596, in encode_example
return encode_nested_example(self, example)
File "/home/polina/workspace/datasets/src/datasets/features/features.py", line 1165, in encode_nested_example
{
File "/home/polina/workspace/datasets/src/datasets/features/features.py", line 1165, in <dictcomp>
{
File "/home/polina/workspace/datasets/src/datasets/utils/py_utils.py", line 249, in zip_dict
yield key, tuple(d[key] for d in dicts)
File "/home/polina/workspace/datasets/src/datasets/utils/py_utils.py", line 249, in <genexpr>
yield key, tuple(d[key] for d in dicts)
KeyError: 'label'
```
## Environment info
`datasets` master branch
- `datasets` version: 2.3.3.dev0
- Platform: Linux-5.14.0-1042-oem-x86_64-with-glibc2.17
- Python version: 3.8.12
- PyArrow version: 6.0.1
- Pandas version: 1.4.1
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https://api.github.com/repos/huggingface/datasets/issues/4415 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4415/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4415/comments | https://api.github.com/repos/huggingface/datasets/issues/4415/events | https://github.com/huggingface/datasets/pull/4415 | 1,251,002,981 | PR_kwDODunzps44mIJk | 4,415 | Update `dataset_infos.json` with new split info in `Dataset.push_to_hub` to avoid verification error | [] | closed | false | null | 1 | 2022-05-27T17:03:42Z | 2022-06-07T12:42:25Z | 2022-06-07T12:33:52Z | null | Update `dataset_infos.json` when pushing splits one by one via `Dataset.push_to_hub` to avoid the splits verification error.
TODO:
~~- [ ] handle token + `{Audio, Image}.embed_storage`~~
- [x] tests | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/3367 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3367/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3367/comments | https://api.github.com/repos/huggingface/datasets/issues/3367/events | https://github.com/huggingface/datasets/pull/3367 | 1,069,241,274 | PR_kwDODunzps4vSsfk | 3,367 | Fix typo in other-structured-to-text task tag | [] | closed | false | null | 0 | 2021-12-02T08:02:27Z | 2021-12-02T16:07:14Z | 2021-12-02T16:07:13Z | null | Fix typo in task tag:
- `other-stuctured-to-text` (before)
- `other-structured-to-text` (now) | {
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https://api.github.com/repos/huggingface/datasets/issues/938 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/938/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/938/comments | https://api.github.com/repos/huggingface/datasets/issues/938/events | https://github.com/huggingface/datasets/pull/938 | 753,940,979 | MDExOlB1bGxSZXF1ZXN0NTI5OTIxNzU5 | 938 | V-1.0.0 of isizulu_ner_corpus | [] | closed | false | null | 1 | 2020-12-01T02:04:32Z | 2020-12-01T23:34:36Z | 2020-12-01T23:34:36Z | null | {
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"closing since it's been added in #957 "
] | |
https://api.github.com/repos/huggingface/datasets/issues/2567 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2567/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2567/comments | https://api.github.com/repos/huggingface/datasets/issues/2567/events | https://github.com/huggingface/datasets/pull/2567 | 932,933,536 | MDExOlB1bGxSZXF1ZXN0NjgwMjE3OTY3 | 2,567 | Add ASR task and new languages to resources | [] | closed | false | null | 0 | 2021-06-29T17:18:01Z | 2021-07-01T09:42:23Z | 2021-07-01T09:42:09Z | null | This PR adds a new `automatic-speech-recognition` task to the list of supported tasks in `tasks.json` and also includes a few new languages missing from `common_voice`.
Note: I used the [Papers with Code list](https://www.paperswithcode.com/area/speech/speech-recognition) as inspiration for the ASR subtasks | {
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https://api.github.com/repos/huggingface/datasets/issues/2281 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2281/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2281/comments | https://api.github.com/repos/huggingface/datasets/issues/2281/events | https://github.com/huggingface/datasets/pull/2281 | 870,792,784 | MDExOlB1bGxSZXF1ZXN0NjI1OTI2MjAw | 2,281 | Update multi_woz_v22 checksum | [] | closed | false | null | 0 | 2021-04-29T09:09:11Z | 2021-04-29T13:41:35Z | 2021-04-29T13:41:34Z | null | Fix issue https://github.com/huggingface/datasets/issues/1876
The files were changed in https://github.com/budzianowski/multiwoz/pull/72 | {
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https://api.github.com/repos/huggingface/datasets/issues/765 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/765/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/765/comments | https://api.github.com/repos/huggingface/datasets/issues/765/events | https://github.com/huggingface/datasets/issues/765 | 730,668,332 | MDU6SXNzdWU3MzA2NjgzMzI= | 765 | [GEM] Add DART data-to-text generation dataset | [
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] | closed | false | null | 0 | 2020-10-27T17:32:23Z | 2020-10-27T17:34:21Z | 2020-10-27T17:34:21Z | null | ## Adding a Dataset
- **Name:** DART
- **Description:** DART consists of 82,191 examples across different domains with each input being a semantic RDF triple set derived from data records in tables and the tree ontology of the schema, annotated with sentence descriptions that cover all facts in the triple set.
- **Paper:** https://arxiv.org/abs/2007.02871v1
- **Data:** https://github.com/Yale-LILY/dart
- **Motivation:** It will likely be included in the GEM generation evaluation benchmark
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
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https://api.github.com/repos/huggingface/datasets/issues/1510 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1510/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1510/comments | https://api.github.com/repos/huggingface/datasets/issues/1510/events | https://github.com/huggingface/datasets/pull/1510 | 763,980,369 | MDExOlB1bGxSZXF1ZXN0NTM4MjU4NDg3 | 1,510 | Add Dataset for (qa_srl)Question-Answer Driven Semantic Role Labeling | [] | closed | false | null | 2 | 2020-12-12T15:48:11Z | 2020-12-17T16:06:22Z | 2020-12-17T16:06:22Z | null | - Added tags, Readme file
- Added code changes | {
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"Hii please follow me",
"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/3477 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3477/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3477/comments | https://api.github.com/repos/huggingface/datasets/issues/3477/events | https://github.com/huggingface/datasets/pull/3477 | 1,087,850,253 | PR_kwDODunzps4wPKPX | 3,477 | Use `iter_files` instead of `str(Path(...)` in image dataset | [] | closed | false | null | 6 | 2021-12-23T16:26:55Z | 2021-12-28T15:15:02Z | 2021-12-28T15:15:02Z | null | Use `iter_files` in the `beans` and the `cats_vs_dogs` dataset scripts as suggested by @albertvillanova.
Additional changes:
* Fix `iter_files` in `MockDownloadManager` (see this [CI error](https://app.circleci.com/pipelines/github/huggingface/datasets/9247/workflows/2657ff8a-b531-4fd9-a9fc-6541a72e8d83/jobs/57028))
* Add support for `os.path.isdir` and `os.path.isfile` in streaming (`os.path.isfile` is needed in `StreamingDownloadManager`'s `iter_files` to make `cats_vs_dogs` streamable)
TODO:
- [ ] add tests for `xisdir` and `xisfile` | {
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"`iter_archive` is about to support ZIP archives. I think we should use this no ?\r\n\r\nsee #3347 https://github.com/huggingface/datasets/pull/3379",
"I was interested in the support for isfile/dir in remote.\r\n\r\nAnyway, `iter_files` will be available for community users.",
"I'm not a big fan of having two ... |
https://api.github.com/repos/huggingface/datasets/issues/4716 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4716/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4716/comments | https://api.github.com/repos/huggingface/datasets/issues/4716/events | https://github.com/huggingface/datasets/pull/4716 | 1,309,455,838 | PR_kwDODunzps47pdbh | 4,716 | Support "tags" yaml tag | [] | closed | false | null | 3 | 2022-07-19T12:34:31Z | 2022-07-20T13:44:50Z | 2022-07-20T13:31:56Z | null | Added the "tags" YAML tag, so that users can specify data domain/topics keywords for dataset search | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"IMO `DatasetMetadata` shouldn't crash with attributes that it doesn't know, btw",
"Yea this PR is mostly to have a validation that this field contains a list of strings.\r\n\r\nRegarding unknown fields, the tagging app currently re... |
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https://api.github.com/repos/huggingface/datasets/issues/1515 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1515/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1515/comments | https://api.github.com/repos/huggingface/datasets/issues/1515/events | https://github.com/huggingface/datasets/pull/1515 | 764,022,753 | MDExOlB1bGxSZXF1ZXN0NTM4Mjg3NDc0 | 1,515 | Add yoruba text | [] | closed | false | null | 1 | 2020-12-12T16:29:30Z | 2020-12-13T18:37:58Z | 2020-12-13T18:37:58Z | null | Adding Yoruba text C3 | {
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"closing since #1379 got merged"
] |
https://api.github.com/repos/huggingface/datasets/issues/3371 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3371/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3371/comments | https://api.github.com/repos/huggingface/datasets/issues/3371/events | https://github.com/huggingface/datasets/pull/3371 | 1,069,821,335 | PR_kwDODunzps4vUnbp | 3,371 | New: Americas NLI dataset | [] | closed | false | null | 0 | 2021-12-02T17:44:59Z | 2021-12-08T13:58:12Z | 2021-12-08T13:58:11Z | null | This PR adds the [Americas NLI](https://arxiv.org/abs/2104.08726) dataset, extension of XNLI to 10 low-resource indigenous languages spoken in the Americas: Ashaninka, Aymara, Bribri, Guarani, Nahuatl, Otomi, Quechua, Raramuri, Shipibo-Konibo, and Wixarika.
One odd thing (not sure) is that I had to set
`datasets-cli dummy_data ./datasets/americas_nli/ --auto_generate --n_lines 7500`
`n_lines` very large to successfully generate the dummy files for all the subsets. Happy to get some guidance here.
Otherwise, I hope everything is in order :)
e: missed a step, onto fixing the tests
e2: there you go -- hope it's ok to have added more languages with their ISO codes to `languages.json`, need those tests to pass :laughing: | {
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https://api.github.com/repos/huggingface/datasets/issues/324 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/324/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/324/comments | https://api.github.com/repos/huggingface/datasets/issues/324/events | https://github.com/huggingface/datasets/issues/324 | 647,525,725 | MDU6SXNzdWU2NDc1MjU3MjU= | 324 | Error when calculating glue score | [] | closed | false | null | 4 | 2020-06-29T16:53:48Z | 2020-07-09T09:13:34Z | 2020-07-09T09:13:34Z | null | I was trying glue score along with other metrics here. But glue gives me this error;
```
import nlp
glue_metric = nlp.load_metric('glue',name="cola")
glue_score = glue_metric.compute(predictions, references)
```
```
---------------------------------------------------------------------------
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-8-b9210a524504> in <module>()
----> 1 glue_score = glue_metric.compute(predictions, references)
6 frames
/usr/local/lib/python3.6/dist-packages/nlp/metric.py in compute(self, predictions, references, timeout, **metrics_kwargs)
191 """
192 if predictions is not None:
--> 193 self.add_batch(predictions=predictions, references=references)
194 self.finalize(timeout=timeout)
195
/usr/local/lib/python3.6/dist-packages/nlp/metric.py in add_batch(self, predictions, references, **kwargs)
207 if self.writer is None:
208 self._init_writer()
--> 209 self.writer.write_batch(batch)
210
211 def add(self, prediction=None, reference=None, **kwargs):
/usr/local/lib/python3.6/dist-packages/nlp/arrow_writer.py in write_batch(self, batch_examples, writer_batch_size)
155 if self.pa_writer is None:
156 self._build_writer(pa_table=pa.Table.from_pydict(batch_examples))
--> 157 pa_table: pa.Table = pa.Table.from_pydict(batch_examples, schema=self._schema)
158 if writer_batch_size is None:
159 writer_batch_size = self.writer_batch_size
/usr/local/lib/python3.6/dist-packages/pyarrow/types.pxi in __iter__()
/usr/local/lib/python3.6/dist-packages/pyarrow/array.pxi in pyarrow.lib.asarray()
/usr/local/lib/python3.6/dist-packages/pyarrow/array.pxi in pyarrow.lib.array()
/usr/local/lib/python3.6/dist-packages/pyarrow/array.pxi in pyarrow.lib._sequence_to_array()
TypeError: an integer is required (got type str)
```
I'm not sure whether I'm doing this wrong or whether it's an issue. I would like to know a workaround. Thank you. | {
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"The glue metric for cola is a metric for classification. It expects label ids as integers as inputs.",
"I want to evaluate a sentence pair whether they are semantically equivalent, so I used MRPC and it gives the same error, does that mean we have to encode the sentences and parse as input?\r\n\r\nusing BertToke... |
https://api.github.com/repos/huggingface/datasets/issues/4427 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4427/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4427/comments | https://api.github.com/repos/huggingface/datasets/issues/4427/events | https://github.com/huggingface/datasets/pull/4427 | 1,253,959,313 | PR_kwDODunzps44vyGg | 4,427 | Add HF.co for PRs/Issues for specific datasets | [] | closed | false | null | 1 | 2022-05-31T14:31:21Z | 2022-06-01T12:37:42Z | 2022-06-01T12:29:02Z | null | As in https://github.com/huggingface/transformers/pull/17485, issues and PR for datasets under a namespace have to be on the HF Hub | {
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https://api.github.com/repos/huggingface/datasets/issues/6069 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6069/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6069/comments | https://api.github.com/repos/huggingface/datasets/issues/6069/events | https://github.com/huggingface/datasets/issues/6069 | 1,820,831,535 | I_kwDODunzps5sh68v | 6,069 | KeyError: dataset has no key "image" | [] | closed | false | null | 6 | 2023-07-25T17:45:50Z | 2023-07-27T12:42:17Z | 2023-07-27T12:42:17Z | null | ### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset. When I printed out the example_batch sent to the transformation function, it shows only the labels are being sent to the function.
For some reason, the images are not in the example batches.
### Steps to reproduce the bug
I'm using the latest stable version of datasets
### Expected behavior
I expect the example_batches to contain both images and labels
### Environment info
I'm using the latest stable version of datasets | {
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"You can list the dataset's columns with `ds.column_names` before `.map` to check whether the dataset has an `image` column. If it doesn't, then this is a bug. Otherwise, please paste the line with the `.map` call.\r\n\r\n\r\n",
"This is the piece of code I am running:\r\n```\r\ndata_transforms = utils.get_data_a... |
https://api.github.com/repos/huggingface/datasets/issues/1191 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1191/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1191/comments | https://api.github.com/repos/huggingface/datasets/issues/1191/events | https://github.com/huggingface/datasets/pull/1191 | 757,836,654 | MDExOlB1bGxSZXF1ZXN0NTMzMTMyNTg1 | 1,191 | Added Translator Human Parity Data For a Chinese-English news transla… | [] | closed | false | null | 5 | 2020-12-06T03:34:13Z | 2020-12-09T13:22:45Z | 2020-12-09T13:22:45Z | null | …tion system from Open dataset list for Dataset sprint, Microsoft Datasets tab. | {
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"Can you run `make style` to format the code and fix the CI please ?",
"> Can you run `make style` to format the code and fix the CI please ?\r\n\r\nI ran `make style` before this PR and just a few minutes ago. No changes to the code. Not sure why the CI is failing.",
"Also, I attempted to see if I can get the ... |
https://api.github.com/repos/huggingface/datasets/issues/2244 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2244/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2244/comments | https://api.github.com/repos/huggingface/datasets/issues/2244/events | https://github.com/huggingface/datasets/pull/2244 | 863,029,946 | MDExOlB1bGxSZXF1ZXN0NjE5NTAyODc0 | 2,244 | Set specific cache directories per test function call | [] | open | false | {
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"title": "1.12",
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} | 4 | 2021-04-20T17:06:22Z | 2022-07-06T15:19:48Z | null | null | Implement specific cache directories (datasets, metrics and modules) per test function call.
Currently, the cache directories are set within the temporary test directory, but they are shared across all test function calls.
This PR implements specific cache directories for each test function call, so that tests are atomic and there are no side effects.
| {
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"@lhoestq, I think this reaches some memory limit on Linux instances... (?)",
"It looks like the `comet` metric test fails because it tries to load a model in memory.\r\nIn the tests I think we have `patch_comet` that mocks the model download + inference. Not sure why it didn't work though.\r\nI can take a look t... |
https://api.github.com/repos/huggingface/datasets/issues/3310 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3310/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3310/comments | https://api.github.com/repos/huggingface/datasets/issues/3310/events | https://github.com/huggingface/datasets/issues/3310 | 1,060,098,104 | I_kwDODunzps4_L9A4 | 3,310 | Fatal error condition occurred in aws-c-io | [
{
"color": "d73a4a",
"default": true,
"description": "Something isn't working",
"id": 1935892857,
"name": "bug",
"node_id": "MDU6TGFiZWwxOTM1ODkyODU3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
}
] | closed | false | null | 28 | 2021-11-22T12:27:54Z | 2023-02-08T10:31:05Z | 2021-11-29T22:22:37Z | null | ## Describe the bug
Fatal error when using the library
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('wikiann', 'en')
```
## Expected results
No fatal errors
## Actual results
```
Fatal error condition occurred in D:\bld\aws-c-io_1633633258269\work\source\event_loop.c:74: aws_thread_launch(&cleanup_thread, s_event_loop_destroy_async_thread_fn, el_group, &thread_options) == AWS_OP_SUCCESS
Exiting Application
```
## Environment info
- `datasets` version: 1.15.2.dev0
- Platform: Windows-10-10.0.22504-SP0
- Python version: 3.8.12
- PyArrow version: 6.0.0
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"Hi ! Are you having this issue only with this specific dataset, or it also happens with other ones like `squad` ?",
"@lhoestq It happens also on `squad`. It successfully downloads the whole dataset and then crashes on: \r\n\r\n```\r\nFatal error condition occurred in D:\\bld\\aws-c-io_1633633258269\\work\\source... |
https://api.github.com/repos/huggingface/datasets/issues/4294 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4294/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4294/comments | https://api.github.com/repos/huggingface/datasets/issues/4294/events | https://github.com/huggingface/datasets/pull/4294 | 1,229,455,582 | PR_kwDODunzps43fTXA | 4,294 | Fix CLI run_beam save_infos | [] | closed | false | null | 1 | 2022-05-09T09:47:43Z | 2022-05-10T07:04:04Z | 2022-05-10T06:56:10Z | null | Currently, it raises TypeError:
```
TypeError: _download_and_prepare() got an unexpected keyword argument 'save_infos'
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/1664 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1664/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1664/comments | https://api.github.com/repos/huggingface/datasets/issues/1664/events | https://github.com/huggingface/datasets/pull/1664 | 775,956,441 | MDExOlB1bGxSZXF1ZXN0NTQ2NTM1NDcy | 1,664 | removed \n in labels | [] | closed | false | null | 0 | 2020-12-29T15:41:43Z | 2020-12-30T17:18:49Z | 2020-12-30T17:18:49Z | null | updated social_i_qa labels as per #1633 | {
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https://api.github.com/repos/huggingface/datasets/issues/967 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/967/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/967/comments | https://api.github.com/repos/huggingface/datasets/issues/967/events | https://github.com/huggingface/datasets/pull/967 | 754,578,988 | MDExOlB1bGxSZXF1ZXN0NTMwNDU0OTI3 | 967 | Add CS Restaurants dataset | [] | closed | false | null | 4 | 2020-12-01T17:17:37Z | 2020-12-02T17:57:44Z | 2020-12-02T17:57:25Z | null | This PR adds the Czech restaurants dataset for Czech NLG. | {
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"Oh yeah, for some reason I thought you had to do it after the merge, I'll get on it",
"Weird, now the CI seems to fail because of other datasets (XGLUE, Norwegian_NER)",
"Yea you just need to rebase from master",
"Re-opening a PR without the messed-up rebase"
] |
https://api.github.com/repos/huggingface/datasets/issues/317 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/317/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/317/comments | https://api.github.com/repos/huggingface/datasets/issues/317/events | https://github.com/huggingface/datasets/issues/317 | 646,555,384 | MDU6SXNzdWU2NDY1NTUzODQ= | 317 | Adding a dataset with multiple subtasks | [] | closed | false | null | 1 | 2020-06-26T23:14:19Z | 2020-10-27T15:36:52Z | 2020-10-27T15:36:52Z | null | I intent to add the datasets of the MT Quality Estimation shared tasks to `nlp`. However, they have different subtasks -- such as word-level, sentence-level and document-level quality estimation, each of which having different language pairs, and some of the data reused in different subtasks.
For example, in [QE 2019,](http://www.statmt.org/wmt19/qe-task.html) we had the same English-Russian and English-German data for word-level and sentence-level QE.
I suppose these datasets could have both their word and sentence-level labels inside `nlp.Features`; but what about other subtasks? Should they be considered a different dataset altogether?
I read the discussion on #217 but the case of QE seems a lot simpler. | {
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"For one dataset you can have different configurations that each have their own `nlp.Features`.\r\nWe imagine having one configuration per subtask for example.\r\nThey are loaded with `nlp.load_dataset(\"my_dataset\", \"my_config\")`.\r\n\r\nFor example the `glue` dataset has many configurations. It is a bit differ... |
https://api.github.com/repos/huggingface/datasets/issues/5278 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5278/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5278/comments | https://api.github.com/repos/huggingface/datasets/issues/5278/events | https://github.com/huggingface/datasets/issues/5278 | 1,459,574,490 | I_kwDODunzps5W_1ba | 5,278 | load_dataset does not read jsonl metadata file properly | [] | closed | false | null | 6 | 2022-11-22T10:24:46Z | 2023-02-14T14:48:16Z | 2022-11-23T11:38:35Z | null | ### Describe the bug
Hi, I'm following [this page](https://huggingface.co/docs/datasets/image_dataset) to create a dataset of images and captions via an image folder and a metadata.json file, but I can't seem to get the dataloader to recognize the "text" column. It just spits out "image" and "label" as features.
Below is code to reproduce my exact example/problem.
### Steps to reproduce the bug
```ruby
dataset_link="19Unu89Ih_kP6zsE7f9Mkw8dy3NwHopRF"
id = dataset_link
output = 'Godardv01.zip'
gdown.download(id=id, output=output, quiet=False)
ds = load_dataset("imagefolder", data_dir="/kaggle/working/Volumes/TOSHIBA/Godard_imgs/Volumes/TOSHIBA/Godard_imgs/Full/train", split="train", drop_labels=False)
print(ds)
```
### Expected behavior
I would expect that it returned "image" and "text" columns from the code above.
### Environment info
- `datasets` version: 2.1.0
- Platform: Linux-5.15.65+-x86_64-with-debian-bullseye-sid
- Python version: 3.7.12
- PyArrow version: 5.0.0
- Pandas version: 1.3.5 | {
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"Can you try to remove \"drop_labels=false\" ? It may force the loader to infer the labels instead of reading the metadata",
"Hi, thanks for responding. I tried that, but it does not change anything.",
"Can you try updating `datasets` ? Metadata support was added in `datasets` 2.4",
"Probably the issue, will ... |
https://api.github.com/repos/huggingface/datasets/issues/4129 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4129/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4129/comments | https://api.github.com/repos/huggingface/datasets/issues/4129/events | https://github.com/huggingface/datasets/issues/4129 | 1,197,376,796 | I_kwDODunzps5HXoUc | 4,129 | dataset metadata for reproducibility | [
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] | open | false | null | 0 | 2022-04-08T14:17:28Z | 2022-04-08T14:17:28Z | null | null | When pulling a dataset from the hub, it would be useful to have some metadata about the specific dataset and version that is used. The metadata could then be passed to the `Trainer` which could then be saved to a model card. This is useful for people who run many experiments on different versions (commits/branches) of the same dataset.
The dataset could have a list of “source datasets” metadata and ignore what happens to them before arriving in the Trainer (i.e. ignore mapping, filtering, etc.).
Here is a basic representation (made by @lhoestq )
```python
>>> from datasets import load_dataset
>>>
>>> my_dataset = load_dataset(...)["train"]
>>> my_dataset = my_dataset.map(...)
>>>
>>> my_dataset.sources
[HFHubDataset(repo_id=..., revision=..., arguments={...})]
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/2574 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2574/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2574/comments | https://api.github.com/repos/huggingface/datasets/issues/2574/events | https://github.com/huggingface/datasets/pull/2574 | 934,632,378 | MDExOlB1bGxSZXF1ZXN0NjgxNjczMzYy | 2,574 | Add streaming in load a dataset docs | [] | closed | false | null | 0 | 2021-07-01T09:32:53Z | 2021-07-01T14:12:22Z | 2021-07-01T14:12:21Z | null | Mention dataset streaming on the "loading a dataset" page of the documentation | {
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https://api.github.com/repos/huggingface/datasets/issues/4361 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4361/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4361/comments | https://api.github.com/repos/huggingface/datasets/issues/4361/events | https://github.com/huggingface/datasets/issues/4361 | 1,238,671,931 | I_kwDODunzps5J1KI7 | 4,361 | `udhr` doesn't load, dataset checksum mismatch | [
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] | closed | false | null | 0 | 2022-05-17T13:47:09Z | 2022-06-08T19:11:21Z | 2022-06-08T19:11:21Z | null | ## Describe the bug
Loading `udhr` fails due to a checksum mismatch for some source files. Looks like both of the source files on unicode.org have changed:
size + checksum in datasets repo:
```
(hfdev) leon@blade:~/datasets/datasets/udhr$ jq .default.download_checksums < dataset_infos.json
{
"https://unicode.org/udhr/assemblies/udhr_xml.zip": {
"num_bytes": 2273633,
"checksum": "0565fa62c2ff155b84123198bcc967edd8c5eb9679eadc01e6fb44a5cf730fee"
},
"https://unicode.org/udhr/assemblies/udhr_txt.zip": {
"num_bytes": 2107471,
"checksum": "087b474a070dd4096ae3028f9ee0b30dcdcb030cc85a1ca02e143be46327e5e5"
}
}
```
size + checksum regenerated from current source files:
```
(hfdev) leon@blade:~/datasets/datasets/udhr$ rm dataset_infos.json
(hfdev) leon@blade:~/datasets/datasets/udhr$ datasets-cli test --save_infos udhr.py
Using custom data configuration default
Testing builder 'default' (1/1)
Downloading and preparing dataset udhn/default (download: 4.18 MiB, generated: 6.15 MiB, post-processed: Unknown size, total: 10.33 MiB) to /home/leon/.cache/huggingface/datasets/udhn/default/0.0.0/ad74b91fa2b3c386e5751b0c52bdfda76d334f76731142fd432d4acc2e2fde66...
Dataset udhn downloaded and prepared to /home/leon/.cache/huggingface/datasets/udhn/default/0.0.0/ad74b91fa2b3c386e5751b0c52bdfda76d334f76731142fd432d4acc2e2fde66. Subsequent calls will reuse this data.
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 686.69it/s]
Dataset Infos file saved at dataset_infos.json
Test successful.
(hfdev) leon@blade:~/datasets/datasets/udhr$ jq .default.download_checksums < dataset_infos.json
{
"https://unicode.org/udhr/assemblies/udhr_xml.zip": {
"num_bytes": 2389690,
"checksum": "a3350912790196c6e1b26bfd1c8a50e8575f5cf185922ecd9bd15713d7d21438"
},
"https://unicode.org/udhr/assemblies/udhr_txt.zip": {
"num_bytes": 2215441,
"checksum": "cb87ecb25b56f34e4fd6f22b323000524fd9c06ae2a29f122b048789cf17e9fe"
}
}
(hfdev) leon@blade:~/datasets/datasets/udhr$
```
--- is unicode.org a sustainable hosting solution for this dataset?
## Steps to reproduce the bug
```python
from datasets import load_dataset
udhr = load_dataset("udhr")
```
## Expected results
That a Dataset object containing the UDHR data will be returned.
## Actual results
```
>>> d = load_dataset('udhr')
Using custom data configuration default
Downloading and preparing dataset udhn/default (download: 4.18 MiB, generated: 6.15 MiB, post-processed: Unknown size, total: 10.33 MiB) to /home/leon/.cache/huggingface/datasets/udhn/default/0.0.0/ad74b91fa2b3c386e5751b0c52bdfda76d334f76731142fd432d4acc2e2fde66...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/leon/.local/lib/python3.9/site-packages/datasets/load.py", line 1731, in load_dataset
builder_instance.download_and_prepare(
File "/home/leon/.local/lib/python3.9/site-packages/datasets/builder.py", line 613, in download_and_prepare
self._download_and_prepare(
File "/home/leon/.local/lib/python3.9/site-packages/datasets/builder.py", line 1117, in _download_and_prepare
super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos)
File "/home/leon/.local/lib/python3.9/site-packages/datasets/builder.py", line 684, in _download_and_prepare
verify_checksums(
File "/home/leon/.local/lib/python3.9/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://unicode.org/udhr/assemblies/udhr_xml.zip', 'https://unicode.org/udhr/assemblies/udhr_txt.zip']
>>>
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.2.1 commit/4110fb6034f79c5fb470cf1043ff52180e9c63b7
- Platform: Linux Ubuntu 20.04
- Python version: 3.9.12
- PyArrow version: 8.0.0
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https://api.github.com/repos/huggingface/datasets/issues/236 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/236/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/236/comments | https://api.github.com/repos/huggingface/datasets/issues/236/events | https://github.com/huggingface/datasets/pull/236 | 631,099,875 | MDExOlB1bGxSZXF1ZXN0NDI4MDUwNzI4 | 236 | CompGuessWhat?! dataset | [] | closed | false | null | 9 | 2020-06-04T19:45:50Z | 2020-06-11T09:43:42Z | 2020-06-11T07:45:21Z | null | Hello,
Thanks for the amazing library that you put together. I'm Alessandro Suglia, the first author of CompGuessWhat?!, a recently released dataset for grounded language learning accepted to ACL 2020 ([https://compguesswhat.github.io](https://compguesswhat.github.io)).
This pull-request adds the CompGuessWhat?! splits that have been extracted from the original dataset. This is only part of our evaluation framework because there is also an additional split of the dataset that has a completely different set of games. I didn't integrate it yet because I didn't know what would be the best practice in this case. Let me clarify the scenario.
In our paper, we have a main dataset (let's call it `compguesswhat-gameplay`) and a zero-shot dataset (let's call it `compguesswhat-zs-gameplay`). In the current code of the pull-request, I have only integrated `compguesswhat-gameplay`. I was thinking that it would be nice to have the `compguesswhat-zs-gameplay` in the same dataset class by simply specifying some particular option to the `nlp.load_dataset()` factory. For instance:
```python
cgw = nlp.load_dataset("compguesswhat")
cgw_zs = nlp.load_dataset("compguesswhat", zero_shot=True)
```
The other option would be to have a separate dataset class. Any preferences? | {
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"Hi @aleSuglia, thanks for this great PR. Indeed you can have both datasets in one file. You need to add a config class which will allows you to specify the different subdataset names and then you will be able to load them as follow.\r\nnlp.load_dataset(\"compguesswhat\", \"compguesswhat-gameplay\") \r\nnlp.load_d... |
https://api.github.com/repos/huggingface/datasets/issues/102 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/102/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/102/comments | https://api.github.com/repos/huggingface/datasets/issues/102/events | https://github.com/huggingface/datasets/pull/102 | 618,231,216 | MDExOlB1bGxSZXF1ZXN0NDE3OTk3MDQz | 102 | Run save infos | [] | closed | false | null | 2 | 2020-05-14T13:27:26Z | 2020-05-14T15:43:04Z | 2020-05-14T15:43:03Z | null | I replaced the old checksum file with the new `dataset_infos.json` by running the script on almost all the datasets we have. The only one that is still running on my side is the cornell dialog | {
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"Haha that cornell dialogue dataset - that ran for 3h on my computer as well. The `generate_examples` method in this script is one of the most inefficient code samples I've ever seen :D ",
"Indeed it's been 3 hours already\r\n```73111 examples [3:07:48, 2.40 examples/s]```"
] |
https://api.github.com/repos/huggingface/datasets/issues/5944 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5944/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5944/comments | https://api.github.com/repos/huggingface/datasets/issues/5944/events | https://github.com/huggingface/datasets/pull/5944 | 1,752,882,200 | PR_kwDODunzps5Sx7O4 | 5,944 | Arrow dataset builder to be able to load and stream Arrow datasets | [] | closed | false | null | 4 | 2023-06-12T14:21:49Z | 2023-06-13T17:36:02Z | 2023-06-13T17:29:01Z | null | This adds a Arrow dataset builder to be able to load and stream from already preprocessed Arrow files.
It's related to https://github.com/huggingface/datasets/issues/3035 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"@lhoestq tips applied. Thanks for a review. :smile: It's a lot of fun to improve this project. ",
"Let's add some documentation in a subsequent PR :)\r\n\r\nIn particular @mariosasko and I think it's important to note to users tha... |
https://api.github.com/repos/huggingface/datasets/issues/3641 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3641/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3641/comments | https://api.github.com/repos/huggingface/datasets/issues/3641/events | https://github.com/huggingface/datasets/pull/3641 | 1,116,284,268 | PR_kwDODunzps4xre7C | 3,641 | Fix numpy rngs when seed is None | [] | closed | false | null | 0 | 2022-01-27T14:29:09Z | 2022-01-27T18:16:08Z | 2022-01-27T18:16:07Z | null | Fixes the NumPy RNG when `seed` is `None`.
The problem becomes obvious after reading the NumPy notes on RNG (returned by `np.random.get_state()`):
> The MT19937 state vector consists of a 624-element array of 32-bit unsigned integers plus a single integer value between 0 and 624 that indexes the current position within the main array.
`The MT19937 state vector`: the seed which we currently index, but this value stays the same for multiple rounds.
`plus a single integer value`: the `pos` value in this PR (is 624 if `seed` is set to a fixed value with `np.random.seed`, so we take the first value in the `seed` array returned by `np.random.get_state()`: https://stackoverflow.com/questions/32172054/how-can-i-retrieve-the-current-seed-of-numpys-random-number-generator)
NumPy notes: https://numpy.org/doc/stable/reference/random/bit_generators/mt19937.html
Fix #3634 | {
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https://api.github.com/repos/huggingface/datasets/issues/6047 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6047/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6047/comments | https://api.github.com/repos/huggingface/datasets/issues/6047/events | https://github.com/huggingface/datasets/pull/6047 | 1,809,627,947 | PR_kwDODunzps5VxRLA | 6,047 | Bump dev version | [] | closed | false | null | 3 | 2023-07-18T10:15:39Z | 2023-07-18T10:28:01Z | 2023-07-18T10:15:52Z | null | workaround to fix an issue with transformers CI
https://github.com/huggingface/transformers/pull/24867#discussion_r1266519626 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6047). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... |
https://api.github.com/repos/huggingface/datasets/issues/216 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/216/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/216/comments | https://api.github.com/repos/huggingface/datasets/issues/216/events | https://github.com/huggingface/datasets/issues/216 | 626,896,890 | MDU6SXNzdWU2MjY4OTY4OTA= | 216 | ❓ How to get ROUGE-2 with the ROUGE metric ? | [] | closed | false | null | 3 | 2020-05-28T23:47:32Z | 2020-06-01T00:04:35Z | 2020-06-01T00:04:35Z | null | I'm trying to use ROUGE metric, but I don't know how to get the ROUGE-2 metric.
---
I compute scores with :
```python
import nlp
rouge = nlp.load_metric('rouge')
with open("pred.txt") as p, open("ref.txt") as g:
for lp, lg in zip(p, g):
rouge.add([lp], [lg])
score = rouge.compute()
```
then : _(print only the F-score for readability)_
```python
for k, s in score.items():
print(k, s.mid.fmeasure)
```
It gives :
>rouge1 0.7915168355671788
rougeL 0.7915168355671788
---
**How can I get the ROUGE-2 score ?**
Also, it's seems weird that ROUGE-1 and ROUGE-L scores are the same. Did I made a mistake ?
@lhoestq | {
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"ROUGE-1 and ROUGE-L shouldn't return the same thing. This is weird",
"For the rouge2 metric you can do\r\n\r\n```python\r\nrouge = nlp.load_metric('rouge')\r\nwith open(\"pred.txt\") as p, open(\"ref.txt\") as g:\r\n for lp, lg in zip(p, g):\r\n rouge.add(lp, lg)\r\nscore = rouge.compute(rouge_types=[\... |
https://api.github.com/repos/huggingface/datasets/issues/2225 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2225/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2225/comments | https://api.github.com/repos/huggingface/datasets/issues/2225/events | https://github.com/huggingface/datasets/pull/2225 | 858,469,561 | MDExOlB1bGxSZXF1ZXN0NjE1NzAzMTY4 | 2,225 | fixed one instance of 'train' to 'test' | [] | closed | false | null | 2 | 2021-04-15T04:26:40Z | 2021-04-15T22:09:50Z | 2021-04-15T21:19:09Z | null | I believe this should be 'test' instead of 'train' | {
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"Thanks ! good catch\r\n\r\nCould you also update the metadata of this dataset ?\r\nYou can do so by running\r\n```\r\ndatasets-cli test ./datasets/newsgroup --all_configs --save_infos --ignore_verifications\r\n```\r\nThis should update the dataset_infos.json file that contains the size of all the splits for exampl... |
https://api.github.com/repos/huggingface/datasets/issues/4870 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4870/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4870/comments | https://api.github.com/repos/huggingface/datasets/issues/4870/events | https://github.com/huggingface/datasets/pull/4870 | 1,346,160,498 | PR_kwDODunzps49jGxD | 4,870 | audio folder check CI | [] | closed | false | null | 1 | 2022-08-22T10:15:53Z | 2022-11-02T11:54:35Z | 2022-08-22T12:19:40Z | null | null | {
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} | true | [
"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/3880 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3880/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3880/comments | https://api.github.com/repos/huggingface/datasets/issues/3880/events | https://github.com/huggingface/datasets/pull/3880 | 1,164,406,008 | PR_kwDODunzps40MjM3 | 3,880 | Change the framework switches to the new syntax | [] | closed | false | null | 2 | 2022-03-09T20:29:10Z | 2022-03-15T14:13:28Z | 2022-03-15T14:13:27Z | null | This PR updates the syntax of the framework-specific code samples. With this new syntax, you'll be able to:
- have paragraphs of text be framework-specific instead of just code samples
- have support for Flax code samples if you want.
This should be merged after https://github.com/huggingface/doc-builder/pull/63 and https://github.com/huggingface/doc-builder/pull/130 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3880). All of your documentation changes will be reflected on that endpoint.",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3880). All of your documentation changes will be reflected on... |
https://api.github.com/repos/huggingface/datasets/issues/1448 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1448/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1448/comments | https://api.github.com/repos/huggingface/datasets/issues/1448/events | https://github.com/huggingface/datasets/pull/1448 | 761,080,776 | MDExOlB1bGxSZXF1ZXN0NTM1ODAyNDM3 | 1,448 | add thai_toxicity_tweet | [] | closed | false | null | 0 | 2020-12-10T09:48:02Z | 2020-12-11T16:21:27Z | 2020-12-11T16:21:27Z | null | Thai Toxicity Tweet Corpus contains 3,300 tweets (506 tweets with texts missing) annotated by humans with guidelines including a 44-word dictionary. The author obtained 2,027 and 1,273 toxic and non-toxic tweets, respectively; these were labeled by three annotators. The result of corpus analysis indicates that tweets that include toxic words are not always toxic. Further, it is more likely that a tweet is toxic, if it contains toxic words indicating their original meaning. Moreover, disagreements in annotation are primarily because of sarcasm, unclear existing target, and word sense ambiguity.
Notes from data cleaner: The data is included into [huggingface/datasets](https://www.github.com/huggingface/datasets) in Dec 2020. By this time, 506 of the tweets are not available publicly anymore. We denote these by `TWEET_NOT_FOUND` in `tweet_text`.
Processing can be found at [this PR](https://github.com/tmu-nlp/ThaiToxicityTweetCorpus/pull/1). | {
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https://api.github.com/repos/huggingface/datasets/issues/3264 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3264/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3264/comments | https://api.github.com/repos/huggingface/datasets/issues/3264/events | https://github.com/huggingface/datasets/issues/3264 | 1,052,663,513 | I_kwDODunzps4-vl7Z | 3,264 | Downloading URL change for WikiAuto Manual, jeopardy and definite_pronoun_resolution | [
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] | closed | false | null | 3 | 2021-11-13T11:47:12Z | 2022-06-01T17:38:16Z | 2022-06-01T17:38:16Z | null | ## Describe the bug
- WikiAuto Manual
The original manual datasets with the following downloading URL in this [repository](https://github.com/chaojiang06/wiki-auto) was [deleted](https://github.com/chaojiang06/wiki-auto/commit/0af9b066f2b4e02726fb8a9be49283c0ad25367f) by the author.
```
https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/train.tsv
```
- jeopardy
The downloading URL for jeopardy may move from
```
http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz
```
to
```
https://drive.google.com/file/d/0BwT5wj_P7BKXb2hfM3d2RHU1ckE/view?resourcekey=0-1abK4cJq-mqxFoSg86ieIg
```
- definite_pronoun_resolution
The following downloading URL for definite_pronoun_resolution cannot be reached for some reasons.
```
http://www.hlt.utdallas.edu/~vince/data/emnlp12/train.c.txt
```
## Steps to reproduce the bug
```python
import datasets
datasets.load_datasets('wiki_auto','manual')
datasets.load_datasets('jeopardy')
datasets.load_datasets('definite_pronoun_resolution')
```
## Expected results
Download successfully
## Actual results
- WikiAuto Manual
```
Downloading and preparing dataset wiki_auto/manual (download: 151.65 MiB, generated: 155.97 MiB, post-processed: Unknown size, total: 307.61 MiB) to /root/.cache/huggingface/datasets/wiki_auto/manual/1.0.0/5ffdd9fc62422d29bd02675fb9606f77c1251ee17169ac10b143ce07ef2f4db8...
0%| | 0/3 [00:00<?, ?it/s]Traceback (most recent call last):
File "wiki_auto.py", line 43, in <module>
main()
File "wiki_auto.py", line 40, in main
train, dev, test = dataset.generate_k_shot_data(k=16, seed=seed, path="../data/")
File "/workspace/projects/CrossFit/tasks/fewshot_gym_dataset.py", line 24, in generate_k_shot_data
dataset = self.load_dataset()
File "wiki_auto.py", line 34, in load_dataset
return datasets.load_dataset('wiki_auto', 'manual')
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/root/.cache/huggingface/modules/datasets_modules/datasets/wiki_auto/5ffdd9fc62422d29bd02675fb9606f77c1251ee17169ac10b143ce07ef2f4db8/wiki_auto.py", line 193, in _split_generators
data_dir = dl_manager.download_and_extract(my_urls)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 196, in download
downloaded_path_or_paths = map_nested(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 216, in map_nested
mapped = [
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 217, in <listcomp>
_single_map_nested((function, obj, types, None, True))
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 152, in _single_map_nested
return function(data_struct)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 295, in cached_path
output_path = get_from_cache(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 592, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/train.tsv
```
- jeopardy
```
Using custom data configuration default
Downloading and preparing dataset jeopardy/default (download: 12.13 MiB, generated: 34.46 MiB, post-processed: Unknown size, total: 46.59 MiB) to /root/.cache/huggingface/datasets/jeopardy/default/0.1.0/25ee3e4a73755e637b8810f6493fd36e4523dea3ca8a540529d0a6e24c7f9810...
Traceback (most recent call last):
File "jeopardy.py", line 45, in <module>
main()
File "jeopardy.py", line 42, in main
train, dev, test = dataset.generate_k_shot_data(k=32, seed=seed, path="../data/")
File "/workspace/projects/CrossFit/tasks/fewshot_gym_dataset.py", line 79, in generate_k_shot_data
dataset = self.load_dataset()
File "jeopardy.py", line 36, in load_dataset
return datasets.load_dataset("jeopardy")
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/root/.cache/huggingface/modules/datasets_modules/datasets/jeopardy/25ee3e4a73755e637b8810f6493fd36e4523dea3ca8a540529d0a6e24c7f9810/jeopardy.py", line 72, in _split_generators
filepath = dl_manager.download_and_extract(_DATA_URL)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 196, in download
downloaded_path_or_paths = map_nested(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 206, in map_nested
return function(data_struct)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 295, in cached_path
output_path = get_from_cache(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 594, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz
```
- definite_pronoun_resolution
```
Downloading and preparing dataset definite_pronoun_resolution/plain_text (download: 222.12 KiB, generated: 239.12 KiB, post-processed: Unknown size, total: 461.24 KiB) to /root/.cache/huggingface/datasets/definite_pronoun_resolution/plain_text/1.0.0/35a1dfd4fba4afb8ba226cbbb65ac7cef0dd3cf9302d8f803740f05d2f16ceff...
0%| | 0/2 [00:00<?, ?it/s]Traceback (most recent call last):
File "definite_pronoun_resolution.py", line 37, in <module>
main()
File "definite_pronoun_resolution.py", line 34, in main
train, dev, test = dataset.generate_k_shot_data(k=32, seed=seed, path="../data/")
File "/workspace/projects/CrossFit/tasks/fewshot_gym_dataset.py", line 79, in generate_k_shot_data
dataset = self.load_dataset()
File "definite_pronoun_resolution.py", line 28, in load_dataset
return datasets.load_dataset('definite_pronoun_resolution')
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/root/.cache/huggingface/modules/datasets_modules/datasets/definite_pronoun_resolution/35a1dfd4fba4afb8ba226cbbb65ac7cef0dd3cf9302d8f803740f05d2f16ceff/definite_pronoun_resolution.py", line 76, in _split_generators
files = dl_manager.download_and_extract(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 196, in download
downloaded_path_or_paths = map_nested(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 216, in map_nested
mapped = [
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 217, in <listcomp>
_single_map_nested((function, obj, types, None, True))
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 152, in _single_map_nested
return function(data_struct)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 295, in cached_path
output_path = get_from_cache(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 594, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://www.hlt.utdallas.edu/~vince/data/emnlp12/train.c.txt
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-4.15.0-161-generic-x86_64-with-glibc2.10
- Python version: 3.8.3
- PyArrow version: 4.0.1
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} | https://api.github.com/repos/huggingface/datasets/issues/3264/timeline | null | completed | null | null | false | [
"#take\r\nI am willing to fix this. Links can be replaced for WikiAuto Manual and jeopardy with new ones provided by authors.\r\n\r\nAs for the definite_pronoun_resolution URL, a certificate error seems to be preventing a download. I have the files on my local machine. I can include them in the dataset folder as th... |
https://api.github.com/repos/huggingface/datasets/issues/4122 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4122/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4122/comments | https://api.github.com/repos/huggingface/datasets/issues/4122/events | https://github.com/huggingface/datasets/issues/4122 | 1,196,095,072 | I_kwDODunzps5HSvZg | 4,122 | medical_dialog zh has very slow _generate_examples | [
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] | closed | false | null | 3 | 2022-04-07T14:00:51Z | 2022-04-08T16:20:51Z | 2022-04-08T16:20:51Z | null | ## Describe the bug
After downloading the files from Google Drive, `load_dataset("medical_dialog", "zh", data_dir="./")` takes an unreasonable amount of time. Generating the train/test split for 33% of the dataset takes over 4.5 hours.
## Steps to reproduce the bug
The easiest way I've found to download files from Google Drive is to use `gdown` and use Google Colab because the download speeds will be very high due to the fact that they are both in Google Cloud.
```python
file_ids = [
"1AnKxGEuzjeQsDHHqL3NqI_aplq2hVL_E",
"1tt7weAT1SZknzRFyLXOT2fizceUUVRXX",
"1A64VBbsQ_z8wZ2LDox586JIyyO6mIwWc",
"1AKntx-ECnrxjB07B6BlVZcFRS4YPTB-J",
"1xUk8AAua_x27bHUr-vNoAuhEAjTxOvsu",
"1ezKTfe7BgqVN5o-8Vdtr9iAF0IueCSjP",
"1tA7bSOxR1RRNqZst8cShzhuNHnayUf7c",
"1pA3bCFA5nZDhsQutqsJcH3d712giFb0S",
"1pTLFMdN1A3ro-KYghk4w4sMz6aGaMOdU",
"1dUSnG0nUPq9TEQyHd6ZWvaxO0OpxVjXD",
"1UfCH05nuWiIPbDZxQzHHGAHyMh8dmPQH",
]
for i in file_ids:
url = f"https://drive.google.com/uc?id={i}"
!gdown $url
from datasets import load_dataset
ds = load_dataset("medical_dialog", "zh", data_dir="./")
```
## Expected results
Faster load time
## Actual results
`Generating train split: 33%: 625519/1921127 [4:31:03<31:39:20, 11.37 examples/s]`
## Environment info
- `datasets` version: 2.0.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 6.0.1
- Pandas version: 1.3.5
@vrindaprabhu , could you take a look at this since you implemented it? I think the `_generate_examples` function might need to be rewritten | {
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} | https://api.github.com/repos/huggingface/datasets/issues/4122/timeline | null | completed | null | null | false | [
"Hi @nbroad1881, thanks for reporting.\r\n\r\nLet me have a look to try to improve its performance. ",
"Thanks @nbroad1881 for reporting! I don't recall it taking so long. I will also have a look at this. \r\n@albertvillanova please let me know if I am doing something unnecessary or time consuming.",
"Hi @nbro... |
https://api.github.com/repos/huggingface/datasets/issues/819 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/819/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/819/comments | https://api.github.com/repos/huggingface/datasets/issues/819/events | https://github.com/huggingface/datasets/pull/819 | 739,250,624 | MDExOlB1bGxSZXF1ZXN0NTE3OTQ2MjYy | 819 | Make save function use deterministic global vars order | [] | closed | false | null | 2 | 2020-11-09T18:12:03Z | 2021-11-30T13:34:09Z | 2020-11-11T15:20:51Z | null | The `dumps` function need to be deterministic for the caching mechanism.
However in #816 I noticed that one of dill's method to recursively check the globals of a function may return the globals in different orders each time it's used. To fix that I sort the globals by key in the `globs` dictionary.
I had to add a rectified `save_function` to the saving functions registry of the Pickler to make it work.
This should fix #816 | {
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"Sorry, asking for help here, but the dill thread stop around 2013. Is it possible to use dill deterministically? I tried to monkeypatch the solution presented here into dill, but I suppose it requires forking their project.",
"Hi ! What we did was to subclass `dill`'s Pickler to fix the non-deterministic behavio... |
https://api.github.com/repos/huggingface/datasets/issues/4776 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4776/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4776/comments | https://api.github.com/repos/huggingface/datasets/issues/4776/events | https://github.com/huggingface/datasets/issues/4776 | 1,324,493,860 | I_kwDODunzps5O8iwk | 4,776 | RuntimeError when using torchaudio 0.12.0 to load MP3 audio file | [] | closed | false | null | 3 | 2022-08-01T14:11:23Z | 2023-03-02T15:58:16Z | 2023-03-02T15:58:15Z | null | Current version of `torchaudio` (0.12.0) raises a RuntimeError when trying to use `sox_io` backend but non-Python dependency `sox` is not installed:
https://github.com/pytorch/audio/blob/2e1388401c434011e9f044b40bc8374f2ddfc414/torchaudio/backend/sox_io_backend.py#L21-L29
```python
def _fail_load(
filepath: str,
frame_offset: int = 0,
num_frames: int = -1,
normalize: bool = True,
channels_first: bool = True,
format: Optional[str] = None,
) -> Tuple[torch.Tensor, int]:
raise RuntimeError("Failed to load audio from {}".format(filepath))
```
Maybe we should raise a more actionable error message so that the user knows how to fix it.
UPDATE:
- this is an incompatibility of latest torchaudio (0.12.0) and the sox backend
TODO:
- [x] as a temporary solution, we should recommend installing torchaudio<0.12.0
- #4777
- #4785
- [ ] however, a stable solution must be found for torchaudio>=0.12.0
Related to:
- https://github.com/huggingface/transformers/issues/18379 | {
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"Requiring torchaudio<0.12.0 isn't really a viable solution because that implies torch<0.12.0 which means no sm_86 CUDA support which means no RTX 3090 support in PyTorch.\r\n\r\nBut in my case, the error only occurs if `_fallback_load` resolves to `_fail_load` inside torchaudio 0.12.0 which is only the case if FFM... |
https://api.github.com/repos/huggingface/datasets/issues/2679 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2679/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2679/comments | https://api.github.com/repos/huggingface/datasets/issues/2679/events | https://github.com/huggingface/datasets/issues/2679 | 948,506,638 | MDU6SXNzdWU5NDg1MDY2Mzg= | 2,679 | Cannot load the blog_authorship_corpus due to codec errors | [
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] | closed | false | null | 3 | 2021-07-20T10:13:20Z | 2021-07-21T17:02:21Z | 2021-07-21T13:11:58Z | null | ## Describe the bug
A codec error is raised while loading the blog_authorship_corpus.
## Steps to reproduce the bug
```
from datasets import load_dataset
raw_datasets = load_dataset("blog_authorship_corpus")
```
## Expected results
Loading the dataset without errors.
## Actual results
An error similar to the one below was raised for (what seems like) every XML file.
/home/izaskr/.cache/huggingface/datasets/downloads/extracted/7cf52524f6517e168604b41c6719292e8f97abbe8f731e638b13423f4212359a/blogs/788358.male.24.Arts.Libra.xml cannot be loaded. Error message: 'utf-8' codec can't decode byte 0xe7 in position 7551: invalid continuation byte
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/izaskr/anaconda3/envs/local_vae_older/lib/python3.8/site-packages/datasets/load.py", line 856, in load_dataset
builder_instance.download_and_prepare(
File "/home/izaskr/anaconda3/envs/local_vae_older/lib/python3.8/site-packages/datasets/builder.py", line 583, in download_and_prepare
self._download_and_prepare(
File "/home/izaskr/anaconda3/envs/local_vae_older/lib/python3.8/site-packages/datasets/builder.py", line 671, in _download_and_prepare
verify_splits(self.info.splits, split_dict)
File "/home/izaskr/anaconda3/envs/local_vae_older/lib/python3.8/site-packages/datasets/utils/info_utils.py", line 74, in verify_splits
raise NonMatchingSplitsSizesError(str(bad_splits))
datasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='train', num_bytes=614706451, num_examples=535568, dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation', num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='validation', num_bytes=32553710, num_examples=28521, dataset_name='blog_authorship_corpus')}]
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.9.0
- Platform: Linux-4.15.0-132-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyArrow version: 4.0.1
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} | https://api.github.com/repos/huggingface/datasets/issues/2679/timeline | null | completed | null | null | false | [
"Hi @izaskr, thanks for reporting.\r\n\r\nHowever the traceback you joined does not correspond to the codec error message: it is about other error `NonMatchingSplitsSizesError`. Maybe you missed some important part of your traceback...\r\n\r\nI'm going to have a look at the dataset anyway...",
"Hi @izaskr, thanks... |
https://api.github.com/repos/huggingface/datasets/issues/5708 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5708/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5708/comments | https://api.github.com/repos/huggingface/datasets/issues/5708/events | https://github.com/huggingface/datasets/issues/5708 | 1,655,023,642 | I_kwDODunzps5ipaga | 5,708 | Dataset sizes are in MiB instead of MB in dataset cards | [
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] | open | false | null | 10 | 2023-04-05T06:36:03Z | 2023-04-24T19:23:40Z | null | null | As @severo reported in an internal discussion (https://github.com/huggingface/moon-landing/issues/5929):
Now we show the dataset size:
- from the dataset card (in the side column)
- from the datasets-server (in the viewer)
But, even if the size is the same, we see a mismatch because the viewer shows MB, while the info from the README generally shows MiB (even if it's written MB -> https://huggingface.co/datasets/blimp/blob/main/README.md?code=true#L1932)
<img width="664" alt="Capture d’écran 2023-04-04 à 10 16 01" src="https://user-images.githubusercontent.com/1676121/229730887-0bd8fa6e-9462-46c6-bd4e-4d2c5784cabb.png">
TODO: Values to be fixed in: `Size of downloaded dataset files:`, `Size of the generated dataset:` and `Total amount of disk used:`
- [x] Bulk edit on the Hub to fix this in all canonical datasets
- [x] Bulk PR on the Hub to fix ancient canonical datasets that were moved to organizations | {
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"Example of bulk edit: https://huggingface.co/datasets/aeslc/discussions/5",
"looks great! \r\n\r\nDo you encode the fact that you've already converted a dataset? (to not convert it twice) or do you base yourself on the info contained in `dataset_info`",
"I am only looping trough the dataset cards, assuming tha... |
https://api.github.com/repos/huggingface/datasets/issues/4047 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4047/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4047/comments | https://api.github.com/repos/huggingface/datasets/issues/4047/events | https://github.com/huggingface/datasets/issues/4047 | 1,183,789,237 | I_kwDODunzps5GjzC1 | 4,047 | Dataset.unique(column: str) -> ArrowNotImplementedError | [
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] | closed | false | null | 3 | 2022-03-28T17:59:32Z | 2022-04-01T18:24:57Z | 2022-04-01T18:24:57Z | null | ## Describe the bug
I'm trying to use `unique()` function, but it fails
## Steps to reproduce the bug
1. Get dataset
2. Call `unique`
3. Error
# Sample code to reproduce the bug
```python
!pip show datasets
from datasets import load_dataset
dataset = load_dataset('wikiann', 'en')
dataset['train'].column_names
dataset['train'].unique(dataset['train'].column_names[0])
```
## Expected results
It would be nice to actually see unique items
## Actual results
Error:
```python
---------------------------------------------------------------------------
ArrowNotImplementedError Traceback (most recent call last)
[<ipython-input-10-5e0de07ed42c>](https://s0qyv2vjaji-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab-20220324-060046-RC00_436956229#) in <module>()
6
7 dataset['train'].column_names
----> 8 dataset['train'].unique(dataset['train'].column_names[0])
5 frames
/usr/local/lib/python3.7/dist-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
ArrowNotImplementedError: Function unique has no kernel matching input types (array[list<item: string>])
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.0.0
- Platform: Google Collab
- Python version: 3.7.13
- PyArrow version: 6.0.1
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"Hi @orkenstein, thanks for reporting.\r\n\r\nPlease note that for this case, our `datasets` library uses under the hood the Apache Arrow `unique` function: https://arrow.apache.org/docs/python/generated/pyarrow.compute.unique.html#pyarrow.compute.unique\r\n\r\nAnd currently the Apache Arrow `unique` function is on... |
https://api.github.com/repos/huggingface/datasets/issues/2224 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2224/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2224/comments | https://api.github.com/repos/huggingface/datasets/issues/2224/events | https://github.com/huggingface/datasets/issues/2224 | 857,983,361 | MDU6SXNzdWU4NTc5ODMzNjE= | 2,224 | Raise error if Windows max path length is not disabled | [] | open | false | null | 0 | 2021-04-14T14:57:20Z | 2021-04-14T14:59:13Z | null | null | On startup, raise an error if Windows max path length is not disabled; ask the user to disable it.
Linked to discussion in #2220. | {
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https://api.github.com/repos/huggingface/datasets/issues/4151 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4151/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4151/comments | https://api.github.com/repos/huggingface/datasets/issues/4151/events | https://github.com/huggingface/datasets/pull/4151 | 1,201,837,999 | PR_kwDODunzps42GgLu | 4,151 | Add missing label for emotion description | [] | closed | false | null | 0 | 2022-04-12T13:17:37Z | 2022-04-12T13:58:50Z | 2022-04-12T13:58:50Z | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4752 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4752/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4752/comments | https://api.github.com/repos/huggingface/datasets/issues/4752/events | https://github.com/huggingface/datasets/issues/4752 | 1,319,464,409 | I_kwDODunzps5OpW3Z | 4,752 | DatasetInfo issue when testing multiple configs: mixed task_templates | [
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] | open | false | null | 3 | 2022-07-27T12:04:54Z | 2022-08-08T18:20:50Z | null | null | ## Describe the bug
When running the `datasets-cli test` it would seem that some config properties in a DatasetInfo get mangled, leading to issues, e.g., about the ClassLabel.
## Steps to reproduce the bug
In summary, what I want to do is create three configs:
- unfiltered: no classlabel, no tasks. Gets data from unfiltered.json.gz (I'd want this without splits, just one chunk of data, but that does not seem possible?)
- filtered_sentiment: `review_sentiment` as ClassLabel, TextClassification task with `review_sentiment` as label. Gets train/test split from respective json.gz files
- filtered_rating: `review_rating0` as ClassLabel, TextClassification task with `review_rating0` as label. Gets train/test split from respective json.gz files
This might be a bit tedious to reproduce, so I am sorry, but these are the steps:
- Clone datasets -> `datasets/` and install it
- Clone `https://huggingface.co/datasets/BramVanroy/hebban-reviews` into `datasets/datasets` so that you have a new folder `datasets/datasets/hebban-reviews/`.
- Replace the HebbanReviews class with this new one:
```python
class HebbanReviews(datasets.GeneratorBasedBuilder):
"""The Hebban book reviews dataset."""
BUILDER_CONFIGS = [
HebbanReviewsConfig(
name="unfiltered",
description=_HEBBAN_REVIEWS_UNFILTERED_DESCRIPTION,
version=datasets.Version(_HEBBAN_VERSION)
),
HebbanReviewsConfig(
name="filtered_sentiment",
description=f"This config has the negative, neutral, and positive sentiment scores as ClassLabel in the 'review_sentiment' column.\n{_HEBBAN_REVIEWS_FILTERED_DESCRIPTION}",
version=datasets.Version(_HEBBAN_VERSION)
),
HebbanReviewsConfig(
name="filtered_rating",
description=f"This config has the 5-class ratings as ClassLabel in the 'review_rating0' column (which is a variant of 'review_rating' that starts counting from 0 instead of 1).\n{_HEBBAN_REVIEWS_FILTERED_DESCRIPTION}",
version=datasets.Version(_HEBBAN_VERSION)
)
]
DEFAULT_CONFIG_NAME = "filtered_sentiment"
_URLS = {
"train": "train.jsonl.gz",
"test": "test.jsonl.gz",
"unfiltered": "unfiltered.jsonl.gz",
}
def _info(self):
features = {
"review_title": datasets.Value("string"),
"review_text": datasets.Value("string"),
"review_text_without_quotes": datasets.Value("string"),
"review_n_quotes": datasets.Value("int32"),
"review_n_tokens": datasets.Value("int32"),
"review_rating": datasets.Value("int32"),
"review_rating0": datasets.Value("int32"),
"review_author_url": datasets.Value("string"),
"review_author_type": datasets.Value("string"),
"review_n_likes": datasets.Value("int32"),
"review_n_comments": datasets.Value("int32"),
"review_url": datasets.Value("string"),
"review_published_date": datasets.Value("string"),
"review_crawl_date": datasets.Value("string"),
"lid": datasets.Value("string"),
"lid_probability": datasets.Value("float32"),
"review_sentiment": datasets.features.ClassLabel(names=["negative", "neutral", "positive"]),
"review_sentiment_label": datasets.Value("string"),
"book_id": datasets.Value("int32"),
}
if self.config.name == "filtered_sentiment":
task_templates = [datasets.TextClassification(text_column="review_text_without_quotes", label_column="review_sentiment")]
elif self.config.name == "filtered_rating":
# For CrossEntropy, our classes need to start at index 0 -- not 1
features["review_rating0"] = datasets.features.ClassLabel(names=["1", "2", "3", "4", "5"])
features["review_sentiment"] = datasets.Value("int32")
task_templates = [datasets.TextClassification(text_column="review_text_without_quotes", label_column="review_rating0")]
elif self.config.name == "unfiltered": # no ClassLabels in unfiltered
features["review_sentiment"] = datasets.Value("int32")
task_templates = None
else:
raise ValueError(f"Unsupported config {self.config.name}. Expected one of 'filtered_sentiment' (default),"
f" 'filtered_rating', or 'unfiltered'")
print("AT INFO", self.config.name, task_templates)
return datasets.DatasetInfo(
description=self.config.description,
features=datasets.Features(features),
homepage="https://huggingface.co/datasets/BramVanroy/hebban-reviews",
citation=_HEBBAN_REVIEWS_CITATION,
task_templates=task_templates,
license="cc-by-4.0"
)
def _split_generators(self, dl_manager):
if self.config.name.startswith("filtered"):
files = dl_manager.download_and_extract({"train": "train.jsonl.gz",
"test": "test.jsonl.gz"})
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": files["train"]
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_file": files["test"]
},
),
]
elif self.config.name == "unfiltered":
files = dl_manager.download_and_extract({"train": "unfiltered.jsonl.gz"})
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": files["train"]
},
),
]
else:
raise ValueError(f"Unsupported config {self.config.name}. Expected one of 'filtered_sentiment' (default),"
f" 'filtered_rating', or 'unfiltered'")
def _generate_examples(self, data_file):
lines = Path(data_file).open(encoding="utf-8").readlines()
for line_idx, line in enumerate(lines):
row = json.loads(line)
yield line_idx, row
```
- finally, run `datasets-cli test ./datasets/hebban-reviews/ --save_infos --all_configs` from within the topmost `datasets` directory
## Expected results
Succeeding tests for three different configs.
## Actual results
I printed out the values that are given to `DatasetInfo` for config name and task_templates, as you can see. There, as expected, I get `unfiltered None`. I also modified datasets/info.py and added this line [at L.170](https://github.com/huggingface/datasets/blob/f5847a304aa1b38b3a3c54a8318b4df60f1299bc/src/datasets/info.py#L170):
```python
print("INTERNALLY AT INFO.PY", self.config_name, self.task_templates)
```
to my surprise, here I get `unfiltered [TextClassification(task='text-classification', text_column='review_text_without_quotes', label_column='review_sentiment')]`. So one way or another, here I suddenly see that `unfiltered` now does have a task_template -- even though that is not what is written in the data loading script, as the first print statement correctly shows.
I do not quite understand how, but it seems that the config name and task_templates get mixed.
This ultimately leads to the following error, but this trace may not be very useful in itself:
```
Traceback (most recent call last):
File "C:\Users\bramv\.virtualenvs\hebban-U6poXNQd\Scripts\datasets-cli-script.py", line 33, in <module>
sys.exit(load_entry_point('datasets', 'console_scripts', 'datasets-cli')())
File "c:\dev\python\hebban\datasets\src\datasets\commands\datasets_cli.py", line 39, in main
service.run()
File "c:\dev\python\hebban\datasets\src\datasets\commands\test.py", line 144, in run
builder.as_dataset()
File "c:\dev\python\hebban\datasets\src\datasets\builder.py", line 899, in as_dataset
datasets = map_nested(
File "c:\dev\python\hebban\datasets\src\datasets\utils\py_utils.py", line 393, in map_nested
mapped = [
File "c:\dev\python\hebban\datasets\src\datasets\utils\py_utils.py", line 394, in <listcomp>
_single_map_nested((function, obj, types, None, True, None))
File "c:\dev\python\hebban\datasets\src\datasets\utils\py_utils.py", line 330, in _single_map_nested
return function(data_struct)
File "c:\dev\python\hebban\datasets\src\datasets\builder.py", line 930, in _build_single_dataset
ds = self._as_dataset(
File "c:\dev\python\hebban\datasets\src\datasets\builder.py", line 1006, in _as_dataset
return Dataset(fingerprint=fingerprint, **dataset_kwargs)
File "c:\dev\python\hebban\datasets\src\datasets\arrow_dataset.py", line 661, in __init__
info = info.copy() if info is not None else DatasetInfo()
File "c:\dev\python\hebban\datasets\src\datasets\info.py", line 286, in copy
return self.__class__(**{k: copy.deepcopy(v) for k, v in self.__dict__.items()})
File "<string>", line 20, in __init__
File "c:\dev\python\hebban\datasets\src\datasets\info.py", line 176, in __post_init__
self.task_templates = [
File "c:\dev\python\hebban\datasets\src\datasets\info.py", line 177, in <listcomp>
template.align_with_features(self.features) for template in (self.task_templates)
File "c:\dev\python\hebban\datasets\src\datasets\tasks\text_classification.py", line 22, in align_with_features
raise ValueError(f"Column {self.label_column} is not a ClassLabel.")
ValueError: Column review_sentiment is not a ClassLabel.
```
## Environment info
- `datasets` version: 2.4.1.dev0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.8
- PyArrow version: 8.0.0
- Pandas version: 1.4.3 | {
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"I've narrowed down the issue to the `dataset_module_factory` which already creates a `dataset_infos.json` file down in the `.cache/modules/dataset_modules/..` folder. That JSON file already contains the wrong task_templates for `unfiltered`.",
"Ugh. Found the issue: apparently `datasets` was reusing the already ... |
https://api.github.com/repos/huggingface/datasets/issues/3418 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3418/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3418/comments | https://api.github.com/repos/huggingface/datasets/issues/3418/events | https://github.com/huggingface/datasets/pull/3418 | 1,077,053,296 | PR_kwDODunzps4vsHMK | 3,418 | Add Wikisource dataset | [
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] | closed | false | null | 1 | 2021-12-10T17:04:44Z | 2022-10-04T09:35:56Z | 2022-10-03T09:37:20Z | null | Add loading script for Wikisource dataset.
Fix #3399.
CC: @geohci, @yjernite | {
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"As we are removing the dataset scripts from GitHub and moving them to the Hugging Face Hub, I am going to transfer this script to the repo: https://huggingface.co/datasets/wikimedia/wikisource"
] |
https://api.github.com/repos/huggingface/datasets/issues/786 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/786/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/786/comments | https://api.github.com/repos/huggingface/datasets/issues/786/events | https://github.com/huggingface/datasets/issues/786 | 733,761,717 | MDU6SXNzdWU3MzM3NjE3MTc= | 786 | feat(dataset): multiprocessing _generate_examples | [] | closed | false | null | 2 | 2020-10-31T16:52:16Z | 2023-01-16T10:59:13Z | 2023-01-16T10:59:13Z | null | forking this out of #741, this issue is only regarding multiprocessing
I'd love if there was a dataset configuration parameter `workers`, where when it is `1` it behaves as it does right now, and when its `>1` maybe `_generate_examples` can also get the `pool` and return an iterable using the pool.
In my use case, I would instead of:
```python
for datum in data:
yield self.load_datum(datum)
```
do:
```python
return pool.map(self.load_datum, data)
```
As the dataset in question, as an example, has **only** 7000 rows, and takes 10 seconds to load each row on average, it takes almost 20 hours to load the entire dataset.
If this was a larger dataset (and many such datasets exist), it would take multiple days to complete.
Using multiprocessing, for example, 40 cores, could speed it up dramatically. For this dataset, hopefully to fully load in under an hour. | {
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} | https://api.github.com/repos/huggingface/datasets/issues/786/timeline | null | completed | null | null | false | [
"I agree that would be cool :)\r\nRight now the only distributed dataset builder is based on Apache Beam so you can use distributed processing frameworks like Dataflow, Spark, Flink etc. to build your dataset but it's not really well suited for single-worker parallel processing afaik",
"`_generate_examples` can n... |
https://api.github.com/repos/huggingface/datasets/issues/2915 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2915/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2915/comments | https://api.github.com/repos/huggingface/datasets/issues/2915/events | https://github.com/huggingface/datasets/pull/2915 | 996,870,071 | PR_kwDODunzps4rxfWb | 2,915 | Fix fsspec AbstractFileSystem access | [] | closed | false | null | 0 | 2021-09-15T09:39:20Z | 2021-09-15T11:35:24Z | 2021-09-15T11:35:24Z | null | This addresses the issue from #2914 by changing the way fsspec's AbstractFileSystem is accessed. | {
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https://api.github.com/repos/huggingface/datasets/issues/3633 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3633/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3633/comments | https://api.github.com/repos/huggingface/datasets/issues/3633/events | https://github.com/huggingface/datasets/pull/3633 | 1,115,040,174 | PR_kwDODunzps4xng6E | 3,633 | Mirror canonical datasets in prod | [] | closed | false | null | 0 | 2022-01-26T13:49:37Z | 2022-01-26T13:56:21Z | 2022-01-26T13:56:21Z | null | Push the datasets changes to the Hub in production by setting `HF_USE_PROD=1`
I also added a fix that makes the script ignore the json, csv, text, parquet and pandas dataset builders.
cc @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/5515 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5515/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5515/comments | https://api.github.com/repos/huggingface/datasets/issues/5515/events | https://github.com/huggingface/datasets/pull/5515 | 1,577,590,611 | PR_kwDODunzps5Jmj5X | 5,515 | Unify `load_from_cache_file` type and logic | [] | closed | false | null | 4 | 2023-02-09T10:04:46Z | 2023-02-14T15:38:13Z | 2023-02-14T14:26:42Z | null | * Updating type annotations for #`load_from_cache_file`
* Added logic for cache checking if needed
* Updated documentation following the wording of `Dataset.map` | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The commit also includes the changes to the `DatasetDict` methods or am I missing something?",
"Oh, indeed. Feel free to mark the PR as \"Ready for review\" then.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0... |
https://api.github.com/repos/huggingface/datasets/issues/2192 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2192/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2192/comments | https://api.github.com/repos/huggingface/datasets/issues/2192/events | https://github.com/huggingface/datasets/pull/2192 | 853,547,910 | MDExOlB1bGxSZXF1ZXN0NjExNjE5NTY0 | 2,192 | Fix typo in huggingface hub | [] | closed | false | null | 0 | 2021-04-08T14:42:24Z | 2021-04-08T15:47:41Z | 2021-04-08T15:47:40Z | null | pip knows how to resolve to `huggingface_hub`, but conda doesn't!
The `packaging` dependency is also required for the build to complete. | {
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https://api.github.com/repos/huggingface/datasets/issues/5730 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5730/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5730/comments | https://api.github.com/repos/huggingface/datasets/issues/5730/events | https://github.com/huggingface/datasets/issues/5730 | 1,662,007,926 | I_kwDODunzps5jEDp2 | 5,730 | CI is broken: ValueError: Name (mock) already in the registry and clobber is False | [
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] | closed | false | null | 0 | 2023-04-11T08:29:46Z | 2023-04-11T08:47:56Z | 2023-04-11T08:47:56Z | null | CI is broken for `test_py310`.
See: https://github.com/huggingface/datasets/actions/runs/4665326892/jobs/8258580948
```
=========================== short test summary info ============================
ERROR tests/test_builder.py::test_builder_with_filesystem_download_and_prepare - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_builder.py::test_builder_with_filesystem_download_and_prepare_reload - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_dataset_dict.py::test_dummy_datasetdict_serialize_fs - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_file_utils.py::test_get_from_cache_fsspec - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_filesystem.py::test_is_remote_filesystem - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xexists[tmp_path/file.txt-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xexists[tmp_path/file_that_doesnt_exist.txt-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xexists[mock://top_level/second_level/date=2019-10-01/a.parquet-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xexists[mock://top_level/second_level/date=2019-10-01/file_that_doesnt_exist.parquet-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xlistdir[tmp_path-expected_paths0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xlistdir[mock://-expected_paths1] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xlistdir[mock://top_level-expected_paths2] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xlistdir[mock://top_level/second_level/date=2019-10-01-expected_paths3] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisdir[tmp_path-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisdir[tmp_path/file.txt-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisdir[mock://-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisdir[mock://top_level-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisdir[mock://dir_that_doesnt_exist-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisfile[tmp_path/file.txt-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisfile[tmp_path/file_that_doesnt_exist.txt-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisfile[mock://-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisfile[mock://top_level/second_level/date=2019-10-01/a.parquet-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xgetsize[tmp_path/file.txt-100] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xgetsize[mock://-0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xgetsize[mock://top_level/second_level/date=2019-10-01/a.parquet-100] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xglob[tmp_path/*.txt-expected_paths0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xglob[mock://*-expected_paths1] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xglob[mock://top_*-expected_paths2] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xglob[mock://top_level/second_level/date=2019-10-0[1-4]-expected_paths3] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xglob[mock://top_level/second_level/date=2019-10-0[1-4]/*-expected_paths4] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xwalk[tmp_path-expected_outputs0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xwalk[mock://top_level/second_level-expected_outputs1] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_exists[tmp_path/file.txt-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_exists[tmp_path/file_that_doesnt_exist.txt-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_exists[mock://top_level/second_level/date=2019-10-01/a.parquet-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_exists[mock://top_level/second_level/date=2019-10-01/file_that_doesnt_exist.parquet-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_glob[tmp_path-*.txt-expected_paths0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_glob[mock://-*-expected_paths1] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_glob[mock://-top_*-expected_paths2] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_glob[mock://top_level/second_level-date=2019-10-0[1-4]-expected_paths3] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_glob[mock://top_level/second_level-date=2019-10-0[1-4]/*-expected_paths4] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_rglob[tmp_path-*.txt-expected_paths0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_rglob[mock://-date=2019-10-0[1-4]-expected_paths1] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_rglob[mock://top_level-date=2019-10-0[1-4]-expected_paths2] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_rglob[mock://-date=2019-10-0[1-4]/*-expected_paths3] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_rglob[mock://top_level-date=2019-10-0[1-4]/*-expected_paths4] - ValueError: Name (mock) already in the registry and clobber is False
===== 2105 passed, 18 skipped, 38 warnings, 46 errors in 236.22s (0:03:56) =====
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3665 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3665/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3665/comments | https://api.github.com/repos/huggingface/datasets/issues/3665/events | https://github.com/huggingface/datasets/pull/3665 | 1,121,753,385 | PR_kwDODunzps4x9TnU | 3,665 | Fix MP3 resampling when a dataset's audio files have different sampling rates | [] | closed | false | null | 0 | 2022-02-02T10:31:45Z | 2022-02-02T10:52:26Z | 2022-02-02T10:52:26Z | null | The resampler needs to be updated if the `orig_freq` doesn't match the audio file sampling rate
Fix https://github.com/huggingface/datasets/issues/3662 | {
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https://api.github.com/repos/huggingface/datasets/issues/5166 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5166/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5166/comments | https://api.github.com/repos/huggingface/datasets/issues/5166/events | https://github.com/huggingface/datasets/pull/5166 | 1,423,629,582 | PR_kwDODunzps5Bj5IQ | 5,166 | Support dill 0.3.6 | [] | closed | false | null | 11 | 2022-10-26T08:24:59Z | 2022-10-28T05:41:05Z | 2022-10-28T05:38:14Z | null | This PR:
- ~~Unpins dill to allow installing dill>=0.3.6~~
- ~~Removes the fix on dill for >=0.3.6 because they implemented a deterministic mode (to be confirmed by @anivegesana)~~
- Pins dill<0.3.7 to allow latest dill 0.3.6
- Implements a fix for dill `save_function` for dill 0.3.6
- Additionally had to implement a fix for dill `save_code` and `_save_regex` for dill 0.3.6
- Fixes the CI so that the latest dill version is tested (besides the minimum 0.3.1.1 required by apache-beam 2.42.0)
Fix #5162. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I think it hasn't been merged ? https://github.com/uqfoundation/dill/pull/501\r\n\r\nThough I can see that the CI is green because it uses dill 0.3.1.1 - we should probably fix the dill version in both CIs:\r\n- use 0.3.1.1 for the C... |
https://api.github.com/repos/huggingface/datasets/issues/2836 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2836/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2836/comments | https://api.github.com/repos/huggingface/datasets/issues/2836/events | https://github.com/huggingface/datasets/pull/2836 | 979,230,142 | MDExOlB1bGxSZXF1ZXN0NzE5NjY5MDUy | 2,836 | Optimize Dataset.filter to only compute the indices to keep | [] | closed | false | null | 2 | 2021-08-25T14:41:22Z | 2021-09-14T14:51:53Z | 2021-09-13T15:50:21Z | null | Optimize `Dataset.filter` to only compute the indices of the rows to keep, instead of creating a new Arrow table with the rows to keep. Creating a new table was an issue because it could take a lot of disk space.
This will be useful to process audio datasets for example cc @patrickvonplaten | {
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"Maybe worth updating the docs here as well?",
"Yup, will do !"
] |
https://api.github.com/repos/huggingface/datasets/issues/2734 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2734/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2734/comments | https://api.github.com/repos/huggingface/datasets/issues/2734/events | https://github.com/huggingface/datasets/pull/2734 | 956,844,874 | MDExOlB1bGxSZXF1ZXN0NzAwMzc4NjI4 | 2,734 | Update BibTeX entry | [] | closed | false | null | 0 | 2021-07-30T15:22:51Z | 2021-07-30T15:47:58Z | 2021-07-30T15:47:58Z | null | Update BibTeX entry. | {
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https://api.github.com/repos/huggingface/datasets/issues/4336 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4336/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4336/comments | https://api.github.com/repos/huggingface/datasets/issues/4336/events | https://github.com/huggingface/datasets/pull/4336 | 1,234,446,174 | PR_kwDODunzps43vpqG | 4,336 | Eval metadata batch 2 : Health Fact, Jigsaw Toxicity, LIAR, LJ Speech, MSRA NER, Multi News, NCBI Disease, Poem Sentiment | [] | closed | false | null | 3 | 2022-05-12T20:24:45Z | 2022-05-16T16:25:00Z | 2022-05-16T16:24:59Z | null | Adding evaluation metadata for :
- Health Fact
- Jigsaw Toxicity
- LIAR
- LJ Speech
- MSRA NER
- Multi News
- NCBI Diseas
- Poem Sentiment | {
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"Summary of CircleCI errors:\r\n- **Jjigsaw_toxicity_pred**: `Citation Information` but it is empty.\r\n- **LIAR** : `Data Instances`,`Data Fields`, `Data Splits`, `Citation Information` are empty.\r\n- **MSRA NER** : Dataset Summary`, `Data Instances`, `Data Fields`, `Data Splits`, `Citation Information` are ... |
https://api.github.com/repos/huggingface/datasets/issues/4728 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4728/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4728/comments | https://api.github.com/repos/huggingface/datasets/issues/4728/events | https://github.com/huggingface/datasets/issues/4728 | 1,312,897,454 | I_kwDODunzps5OQTmu | 4,728 | load_dataset gives "403" error when using Financial Phrasebank | [] | closed | false | null | 3 | 2022-07-21T08:43:32Z | 2022-08-04T08:32:35Z | 2022-08-04T08:32:35Z | null | I tried both codes below to download the financial phrasebank dataset (https://huggingface.co/datasets/financial_phrasebank) with the sentences_allagree subset. However, the code gives a 403 error when executed from multiple machines locally or on the cloud.
```
from datasets import load_dataset, DownloadMode
load_dataset(path='financial_phrasebank',name='sentences_allagree',download_mode=DownloadMode.FORCE_REDOWNLOAD)
```
```
from datasets import load_dataset, DownloadMode
load_dataset(path='financial_phrasebank',name='sentences_allagree')
```
**Error**
ConnectionError: Couldn't reach https://www.researchgate.net/profile/Pekka_Malo/publication/251231364_FinancialPhraseBank-v10/data/0c96051eee4fb1d56e000000/FinancialPhraseBank-v10.zip (error 403)
| {
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} | https://api.github.com/repos/huggingface/datasets/issues/4728/timeline | null | completed | null | null | false | [
"Hi @rohitvincent, thanks for reporting.\r\n\r\nUnfortunately I'm not able to reproduce your issue:\r\n```python\r\nIn [2]: from datasets import load_dataset, DownloadMode\r\n ...: load_dataset(path='financial_phrasebank',name='sentences_allagree', download_mode=\"force_redownload\")\r\nDownloading builder script... |
https://api.github.com/repos/huggingface/datasets/issues/3112 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3112/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3112/comments | https://api.github.com/repos/huggingface/datasets/issues/3112/events | https://github.com/huggingface/datasets/issues/3112 | 1,030,613,083 | I_kwDODunzps49behb | 3,112 | OverflowError: There was an overflow in the <class 'pyarrow.lib.ListArray'>. Try to reduce writer_batch_size to have batches smaller than 2GB | [
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] | open | false | null | 4 | 2021-10-19T18:21:41Z | 2021-10-19T18:52:29Z | null | null | ## Describe the bug
Despite having batches way under 2Gb when running `datasets.map()`, after processing correctly the data of the first batch without fuss and irrespective of writer_batch_size (say 2,4,8,16,32,64 and 128 in my case), it returns the following error :
> OverflowError: There was an overflow in the <class 'pyarrow.lib.ListArray'>. Try to reduce writer_batch_size to have batches smaller than 2GB
Note that I always run `batch_size=writer_batch_size` :
## Steps to reproduce the bug
```python
datasets.map(lambda example : {"column_name" : function(arguments)}, batched=False, remove_columns = datasets.column_names, batch_size=batch_size, writer_batch_size=batch_size, disable_nullable=True, num_proc=None, desc="blablabla")
```
## Introspecting CUDA memory during bug
Placed within `function(arguments)` the following statement to introspect memory usage, merely a little over 1/4 of 2Gb
`print(torch.cuda.memory_summary(device=device, abbreviated=False))`
> |===========================================================================|
| PyTorch CUDA memory summary, device ID 0 |
|---------------------------------------------------------------------------|
| CUDA OOMs: 0 | cudaMalloc retries: 0 |
|===========================================================================|
| Metric | Cur Usage | Peak Usage | Tot Alloc | Tot Freed |
|---------------------------------------------------------------------------|
| Allocated memory | 541418 KB | 545725 KB | 555695 KB | 14276 KB |
| from large pool | 540672 KB | 544431 KB | 544431 KB | 3759 KB |
| from small pool | 746 KB | 1714 KB | 11264 KB | 10517 KB |
|---------------------------------------------------------------------------|
| Active memory | 541418 KB | 545725 KB | 555695 KB | 14276 KB |
| from large pool | 540672 KB | 544431 KB | 544431 KB | 3759 KB |
| from small pool | 746 KB | 1714 KB | 11264 KB | 10517 KB |
|---------------------------------------------------------------------------|
| GPU reserved memory | 598016 KB | 598016 KB | 598016 KB | 0 B |
| from large pool | 595968 KB | 595968 KB | 595968 KB | 0 B |
| from small pool | 2048 KB | 2048 KB | 2048 KB | 0 B |
|---------------------------------------------------------------------------|
| Non-releasable memory | 36117 KB | 52292 KB | 274275 KB | 238158 KB |
| from large pool | 34816 KB | 51537 KB | 261713 KB | 226897 KB |
| from small pool | 1301 KB | 2045 KB | 12562 KB | 11261 KB |
|---------------------------------------------------------------------------|
| Allocations | 198 | 224 | 478 | 280 |
| from large pool | 74 | 75 | 75 | 1 |
| from small pool | 124 | 150 | 403 | 279 |
|---------------------------------------------------------------------------|
| Active allocs | 198 | 224 | 478 | 280 |
| from large pool | 74 | 75 | 75 | 1 |
| from small pool | 124 | 150 | 403 | 279 |
|---------------------------------------------------------------------------|
| GPU reserved segments | 21 | 21 | 21 | 0 |
| from large pool | 20 | 20 | 20 | 0 |
| from small pool | 1 | 1 | 1 | 0 |
|---------------------------------------------------------------------------|
| Non-releasable allocs | 18 | 23 | 166 | 148 |
| from large pool | 17 | 18 | 19 | 2 |
| from small pool | 1 | 6 | 147 | 146 |
|===========================================================================|
## Expected results
Efficiently process the datasets and write it down to disk.
## Actual results
--------------------------------------------------------------------------
OverflowError Traceback (most recent call last)
~\anaconda3\envs\xxx\lib\site-packages\datasets\arrow_dataset.py in _map_single(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, disable_tqdm, desc, cache_only)
2390 else:
-> 2391 writer.write(example)
2392 else:
~\anaconda3\envs\xxx\lib\site-packages\datasets\arrow_writer.py in write(self, example, key, writer_batch_size)
367
--> 368 self.write_examples_on_file()
369
~\anaconda3\envs\xxx\lib\site-packages\datasets\arrow_writer.py in write_examples_on_file(self)
316 if not isinstance(pa_array[0], pa.lib.FloatScalar):
--> 317 raise OverflowError(
318 "There was an overflow in the {}. Try to reduce writer_batch_size to have batches smaller than 2GB".format(
OverflowError: There was an overflow in the <class 'pyarrow.lib.ListArray'>. Try to reduce writer_batch_size to have batches smaller than 2GB
During handling of the above exception, another exception occurred:
OverflowError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_16268/2456940807.py in <module>
3 #tracker = OfflineEmissionsTracker(country_iso_code="FRA", project_name='xxx'+time_stamp,output_dir='./codecarbon')
4 #tracker.start()
----> 5 process_datasets(source_datasets_paths, dataset_dir, LM_tokenizer, LMhead_model, datasets_selection=['wikipedia'], from_scratch=True,
6 clean_sentences=False, negative_sampling=False, translate=False, tokenize=False, generate_embeddings=True, concatenate_embeddings=False,
7 max_sample=10000, padding='do_not_pad', truncation=True, cpu_batch_size=1000, gpu_batch_size=2, cpu_writer_batch_size=1000, gpu_writer_batch_size=2, disable_nullable=True, num_proc=None) #
~\xxx\xxx.py in process_datasets(source_datasets_paths, dataset_dir, LM_tokenizer, LMhead_model, datasets_selection, from_scratch, clean_sentences, translate, negative_sampling, tokenize, generate_embeddings, concatenate_embeddings, max_sample, padding, truncation, cpu_batch_size, gpu_batch_size, cpu_writer_batch_size, gpu_writer_batch_size, disable_nullable, num_proc)
481 for column in tqdm(dataset.column_names, desc=f'Processing column', leave=False):
482 if "xxx_" in column:
--> 483 dataset = dataset.map(lambda example :
484 {"embeddings_"+str(column).replace("translated_",""):function(input_ids=example[column],
485 token_type_ids=example[column.replace("input_ids","token_type_ids")],
~\anaconda3\envs\xxx\lib\site-packages\datasets\arrow_dataset.py in map(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc)
2034
2035 if num_proc is None or num_proc == 1:
-> 2036 return self._map_single(
2037 function=function,
2038 with_indices=with_indices,
~\anaconda3\envs\xxx\lib\site-packages\datasets\arrow_dataset.py in wrapper(*args, **kwargs)
501 self: "Dataset" = kwargs.pop("self")
502 # apply actual function
--> 503 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
504 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
505 for dataset in datasets:
~\anaconda3\envs\xxx\lib\site-packages\datasets\arrow_dataset.py in wrapper(*args, **kwargs)
468 }
469 # apply actual function
--> 470 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
471 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
472 # re-apply format to the output
~\anaconda3\envs\xxx\lib\site-packages\datasets\fingerprint.py in wrapper(*args, **kwargs)
404 # Call actual function
405
--> 406 out = func(self, *args, **kwargs)
407
408 # Update fingerprint of in-place transforms + update in-place history of transforms
~\anaconda3\envs\xxx\lib\site-packages\datasets\arrow_dataset.py in _map_single(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, disable_tqdm, desc, cache_only)
2425 if update_data:
2426 if writer is not None:
-> 2427 writer.finalize()
2428 if tmp_file is not None:
2429 tmp_file.close()
~\anaconda3\envs\xxx\lib\site-packages\datasets\arrow_writer.py in finalize(self, close_stream)
440 # Re-intializing to empty list for next batch
441 self.hkey_record = []
--> 442 self.write_examples_on_file()
443 if self.pa_writer is None:
444 if self._schema is not None:
~\anaconda3\envs\xxx\lib\site-packages\datasets\arrow_writer.py in write_examples_on_file(self)
315 # This check fails with FloatArrays with nans, which is not what we want, so account for that:
316 if not isinstance(pa_array[0], pa.lib.FloatScalar):
--> 317 raise OverflowError(
318 "There was an overflow in the {}. Try to reduce writer_batch_size to have batches smaller than 2GB".format(
319 type(pa_array)
OverflowError: There was an overflow in the <class 'pyarrow.lib.ListArray'>. Try to reduce writer_batch_size to have batches smaller than 2GB
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.13.3
- Platform: Windows-10-10.0.19042-SP0
- Python version: 3.8.11
- PyArrow version: 3.0.0
##Next steps
Testing on Linux.
@albertvillanova
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"I am very unsure on why you tagged me here. I am not a maintainer of the Datasets library and have no idea how to help you.",
"fixed",
"Ok got it, tensor full of NaNs, cf.\r\n\r\n~\\anaconda3\\envs\\xxx\\lib\\site-packages\\datasets\\arrow_writer.py in write_examples_on_file(self)\r\n315 # This check fails wit... |
https://api.github.com/repos/huggingface/datasets/issues/6007 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6007/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6007/comments | https://api.github.com/repos/huggingface/datasets/issues/6007/events | https://github.com/huggingface/datasets/issues/6007 | 1,789,782,693 | I_kwDODunzps5qreql | 6,007 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset | [
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] | open | false | null | 7 | 2023-07-05T15:16:50Z | 2023-07-10T19:11:17Z | null | null | ### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encountered the error: "OverflowError: Python int too large to convert to C long"
The error look something like:
```
OverflowError: Python int too large to convert to C long
During handling of the above exception, another exception occurred:
OverflowError Traceback (most recent call last)
<ipython-input-7-0ed8700e662d> in <module>
----> 1 dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train', cache_dir='/sfs/MNBVC/.cache/')
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)
1749 ignore_verifications=ignore_verifications,
1750 try_from_hf_gcs=try_from_hf_gcs,
-> 1751 use_auth_token=use_auth_token,
1752 )
1753
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
703 if not downloaded_from_gcs:
704 self._download_and_prepare(
--> 705 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
706 )
707 # Sync info
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos)
1225
1226 def _download_and_prepare(self, dl_manager, verify_infos):
-> 1227 super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos)
1228
1229 def _get_examples_iterable_for_split(self, split_generator: SplitGenerator) -> ExamplesIterable:
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
791 try:
792 # Prepare split will record examples associated to the split
--> 793 self._prepare_split(split_generator, **prepare_split_kwargs)
794 except OSError as e:
795 raise OSError(
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/builder.py in _prepare_split(self, split_generator, check_duplicate_keys)
1219 writer.write(example, key)
1220 finally:
-> 1221 num_examples, num_bytes = writer.finalize()
1222
1223 split_generator.split_info.num_examples = num_examples
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/arrow_writer.py in finalize(self, close_stream)
536 # Re-intializing to empty list for next batch
537 self.hkey_record = []
--> 538 self.write_examples_on_file()
539 if self.pa_writer is None:
540 if self.schema:
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/arrow_writer.py in write_examples_on_file(self)
407 # Since current_examples contains (example, key) tuples
408 batch_examples[col] = [row[0][col] for row in self.current_examples]
--> 409 self.write_batch(batch_examples=batch_examples)
410 self.current_examples = []
411
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/arrow_writer.py in write_batch(self, batch_examples, writer_batch_size)
506 col_try_type = try_features[col] if try_features is not None and col in try_features else None
507 typed_sequence = OptimizedTypedSequence(batch_examples[col], type=col_type, try_type=col_try_type, col=col)
--> 508 arrays.append(pa.array(typed_sequence))
509 inferred_features[col] = typed_sequence.get_inferred_type()
510 schema = inferred_features.arrow_schema if self.pa_writer is None else self.schema
/sfs/MNBVC/venv/lib64/python3.6/site-packages/pyarrow/array.pxi in pyarrow.lib.array()
/sfs/MNBVC/venv/lib64/python3.6/site-packages/pyarrow/array.pxi in pyarrow.lib._handle_arrow_array_protocol()
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/arrow_writer.py in __arrow_array__(self, type)
180 else:
181 trying_cast_to_python_objects = True
--> 182 out = pa.array(cast_to_python_objects(data, only_1d_for_numpy=True))
183 # use smaller integer precisions if possible
184 if self.trying_int_optimization:
/sfs/MNBVC/venv/lib64/python3.6/site-packages/pyarrow/array.pxi in pyarrow.lib.array()
/sfs/MNBVC/venv/lib64/python3.6/site-packages/pyarrow/array.pxi in pyarrow.lib._sequence_to_array()
/sfs/MNBVC/venv/lib64/python3.6/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
OverflowError: Python int too large to convert to C long
```
However, that dataset can be loaded in a streaming manner:
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train', streaming=True)
for i in dataset:
pass # it work well
```
Another issue is reported in our dataset hub:
https://huggingface.co/datasets/liwu/MNBVC/discussions/2
### Steps to reproduce the bug
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
### Expected behavior
the dataset can be safely loaded
### Environment info
- `datasets` version: 2.4.0
- Platform: Linux-3.10.0-1160.an7.x86_64-x86_64-with-centos-7.9
- Python version: 3.6.8
- PyArrow version: 6.0.1
- Pandas version: 1.1.5 | {
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} | https://api.github.com/repos/huggingface/datasets/issues/6007/timeline | null | null | null | null | false | [
"This error means that one of the int32 (`Value(\"int32\")`) columns in the dataset has a value that is out of the valid (int32) range.\r\n\r\nI'll open a PR to print the name of a problematic column to make debugging such errors easier.",
"I am afraid int32 is not the reason for this error.\r\n\r\nI have submitt... |
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