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https://api.github.com/repos/huggingface/datasets/issues/4224 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4224/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4224/comments | https://api.github.com/repos/huggingface/datasets/issues/4224/events | https://github.com/huggingface/datasets/pull/4224 | 1,216,209,667 | PR_kwDODunzps420KX2 | 4,224 | autoeval config | {
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https://api.github.com/repos/huggingface/datasets/issues/514 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/514/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/514/comments | https://api.github.com/repos/huggingface/datasets/issues/514/events | https://github.com/huggingface/datasets/issues/514 | 681,256,348 | MDU6SXNzdWU2ODEyNTYzNDg= | 514 | dataset.shuffle(keep_in_memory=True) is never allowed | {
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"defa... | closed | false | null | [] | null | [
"This seems to be fixed in #513 for the filter function, replacing `cache_file_name` with `indices_cache_file_name` in the assert. Although not for the `map()` function @thomwolf ",
"Maybe I'm a bit tired but I fail to see the issue here.\r\n\r\nSince `cache_file_name` is `None` by default, if you set `keep_in_me... | 2020-08-18T18:47:40Z | 2022-10-10T12:21:58Z | 2022-10-10T12:21:58Z | CONTRIBUTOR | null | null | null | As of commit ef4aac2, the usage of the parameter `keep_in_memory=True` is never possible: `dataset.select(keep_in_memory=True)`
The commit added the lines
```python
# lines 994-996 in src/nlp/arrow_dataset.py
assert (
not keep_in_memory or cache_file_name is None
), "Please use either `keep_in_memory` or `cache_file_name` but not both."
```
This affects both `shuffle()` as `select()` is a sub-routine, and `map()` that has the same check.
I'd love to fix this myself, but unsure what the intention of the assert is given the rest of the logic in the function concerning `ccache_file_name` and `keep_in_memory`. | {
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https://api.github.com/repos/huggingface/datasets/issues/2157 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2157/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2157/comments | https://api.github.com/repos/huggingface/datasets/issues/2157/events | https://github.com/huggingface/datasets/pull/2157 | 847,205,239 | MDExOlB1bGxSZXF1ZXN0NjA2MjM1NjUx | 2,157 | updated user permissions based on umask | {
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} | Updated user permissions based on running user's umask (#2065). Let me know if `0o666` is looking good or should I change it to `~umask` only (to give execute permissions as well) | {
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https://api.github.com/repos/huggingface/datasets/issues/5630 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5630/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5630/comments | https://api.github.com/repos/huggingface/datasets/issues/5630/events | https://github.com/huggingface/datasets/pull/5630 | 1,620,327,510 | PR_kwDODunzps5L1ahF | 5,630 | adds early exit if url is `PathLike` | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5630). All of your documentation changes will be reflected on that endpoint."
] | 2023-03-12T11:23:28Z | 2023-03-15T11:58:38Z | null | NONE | null | 0 | {
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} | Closes #4864
Should fix errors thrown when attempting to load `json` dataset using `pathlib.Path` in `data_files` argument. | {
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https://api.github.com/repos/huggingface/datasets/issues/6191 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6191/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6191/comments | https://api.github.com/repos/huggingface/datasets/issues/6191/events | https://github.com/huggingface/datasets/pull/6191 | 1,871,634,840 | PR_kwDODunzps5ZCKmv | 6,191 | Add missing `revision` argument | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I have found the same issue. Good fix. Should be merged as soon as possible.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_a... | 2023-08-29T13:05:04Z | 2023-09-04T06:38:17Z | 2023-08-31T13:50:00Z | CONTRIBUTOR | null | 0 | {
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} | I've noticed that when you're not working on the main branch, there are sometimes errors in the files returned. After some investigation, I realized that the revision was not properly passed everywhere. This PR proposes a fix. | {
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https://api.github.com/repos/huggingface/datasets/issues/5264 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5264/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5264/comments | https://api.github.com/repos/huggingface/datasets/issues/5264/events | https://github.com/huggingface/datasets/issues/5264 | 1,455,252,906 | I_kwDODunzps5WvWWq | 5,264 | `datasets` can't read a Parquet file in Python 3.9.13 | {
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"Could you share the full stack trace please ?\r\n\r\n\r\nCan you also try running this code ? It can be useful to determine if the issue comes from `datasets` or `fsspec` (streaming) or `pyarrow` (parquet reading):\r\n```python\r\nds = load_dataset(\"parquet\", data_files=a_parquet_file_url, use_auth_token=True)\r... | 2022-11-18T14:44:01Z | 2023-05-07T09:52:59Z | 2022-11-22T11:18:08Z | NONE | null | null | null | ### Describe the bug
I have an error when trying to load this [dataset](https://huggingface.co/datasets/bigcode/the-stack-dedup-pjj) (it's private but I can add you to the bigcode org). `datasets` can't read one of the parquet files in the Java subset
```python
from datasets import load_dataset
ds = load_dataset("bigcode/the-stack-dedup-pjj", data_dir="data/java", split="train", revision="v1.1.a1", use_auth_token=True)
````
```
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.
```
It seems to be an issue with new Python versions, Because it works in these two environements:
```
- `datasets` version: 2.6.1
- Platform: Linux-5.4.0-131-generic-x86_64-with-glibc2.31
- Python version: 3.9.7
- PyArrow version: 9.0.0
- Pandas version: 1.3.4
```
```
- `datasets` version: 2.6.1
- Platform: Linux-4.19.0-22-cloud-amd64-x86_64-with-debian-10.13
- Python version: 3.7.12
- PyArrow version: 9.0.0
- Pandas version: 1.3.4
```
But not in this:
```
- `datasets` version: 2.6.1
- Platform: Linux-4.19.0-22-cloud-amd64-x86_64-with-glibc2.28
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.3.4
```
### Steps to reproduce the bug
Load the dataset in python 3.9.13
### Expected behavior
Load the dataset without the pyarrow error.
### Environment info
```
- `datasets` version: 2.6.1
- Platform: Linux-4.19.0-22-cloud-amd64-x86_64-with-glibc2.28
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.3.4
``` | {
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} | [] | closed | false | null | [] | null | [
"Hi! \r\n\r\nThis would only work if `bigscience/xP3` was a no-code dataset, but it isn't (it has a Python builder script).\r\n\r\nBut this should work: \r\n```python\r\nload_dataset(\"json\", data_files=\"https://huggingface.co/datasets/bigscience/xP3/resolve/main/ur/xp3_facebook_flores_spa_Latn-urd_Arab_devtest_a... | 2023-05-05T09:49:55Z | 2023-08-16T10:02:01Z | 2023-08-16T10:02:01Z | CONTRIBUTOR | null | null | null | ### Describe the bug
I'm trying to download https://huggingface.co/datasets/bigscience/xP3/resolve/main/ur/xp3_facebook_flores_spa_Latn-urd_Arab_devtest_ab-spa_Latn-urd_Arab.jsonl which works fine in my webbrowser, but somehow not with datasets. Am I doing sth wrong?
```
Downloading builder script: 100%
2.82k/2.82k [00:00<00:00, 64.2kB/s]
Downloading readme: 100%
12.6k/12.6k [00:00<00:00, 585kB/s]
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
[<ipython-input-2-4b45446a91d5>](https://localhost:8080/#) in <cell line: 4>()
2 lang = "ur"
3 fname = "xp3_facebook_flores_spa_Latn-urd_Arab_devtest_ab-spa_Latn-urd_Arab.jsonl"
----> 4 dataset = load_dataset("bigscience/xP3", data_files=f"{lang}/{fname}")
6 frames
[/usr/local/lib/python3.10/dist-packages/datasets/data_files.py](https://localhost:8080/#) in _resolve_single_pattern_locally(base_path, pattern, allowed_extensions)
291 if allowed_extensions is not None:
292 error_msg += f" with any supported extension {list(allowed_extensions)}"
--> 293 raise FileNotFoundError(error_msg)
294 return sorted(out)
295
FileNotFoundError: Unable to find 'https://huggingface.co/datasets/bigscience/xP3/resolve/main/ur/xp3_facebook_flores_spa_Latn-urd_Arab_devtest_ab-spa_Latn-urd_Arab.jsonl' at /content/https:/huggingface.co/datasets/bigscience/xP3/resolve/main
```
### Steps to reproduce the bug
```
!pip install -q datasets
from datasets import load_dataset
lang = "ur"
fname = "xp3_facebook_flores_spa_Latn-urd_Arab_devtest_ab-spa_Latn-urd_Arab.jsonl"
dataset = load_dataset("bigscience/xP3", data_files=f"{lang}/{fname}")
```
### Expected behavior
Correctly downloads
### Environment info
latest versions | {
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https://api.github.com/repos/huggingface/datasets/issues/6397 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6397/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6397/comments | https://api.github.com/repos/huggingface/datasets/issues/6397/events | https://github.com/huggingface/datasets/issues/6397 | 1,987,622,152 | I_kwDODunzps52eLUI | 6,397 | Raise a different exception for inexisting dataset vs files without known extension | {
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We have the same error for:
- https://huggingface.co/datasets/severo/a_dataset_that_does_not_exist: a dataset that does not exist
- https://huggingface.co/datasets/severo/test_files_without_extension: a dataset with files without a known extension
```
>>> import datasets
>>> datasets.get_dataset_config_names('severo/a_dataset_that_does_not_exist')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1508, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at /home/slesage/hf/datasets-server/services/worker/severo/a_dataset_that_does_not_exist/a_dataset_that_does_not_exist.py or any data file in the same directory. Couldn't find 'severo/a_dataset_that_does_not_exist' on the Hugging Face Hub either: FileNotFoundError: Dataset 'severo/a_dataset_that_does_not_exist' doesn't exist on the Hub. If the repo is private or gated, make sure to log in with `huggingface-cli login`.
>>> datasets.get_dataset_config_names('severo/test_files_without_extension')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1508, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at /home/slesage/hf/datasets-server/services/worker/severo/test_files_without_extension/test_files_without_extension.py or any data file in the same directory. Couldn't find 'severo/test_files_without_extension' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in severo/test_files_without_extension.
```
To differentiate, we must parse the error message (only the end is different). We should have a different exception for these two errors. | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-10-11T18:28:00Z | 2023-10-17T13:25:33Z | null | CONTRIBUTOR | null | 0 | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-11-23T17:35:02Z | 2023-11-27T10:02:56Z | 2023-11-24T17:13:02Z | CONTRIBUTOR | null | 0 | {
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} | Refetch metadata files in case they were dropped by `filter_extensions` in the previous step.
Fix #6442
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"Thanks for your contribution, @abhishekkrthakur. Are you still interested in adding this dataset?\r\n\r\nWe are removing the dataset scripts from this GitHub repo and moving them to the Hugging Face Hub: https://huggingface.co/datasets\r\n\r\nWe would suggest you create this dataset there. Please, feel free to tel... | 2020-12-07T11:09:17Z | 2023-09-24T09:40:49Z | 2022-10-03T09:39:32Z | MEMBER | null | 1 | {
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https://api.github.com/repos/huggingface/datasets/issues/1863 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1863/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1863/comments | https://api.github.com/repos/huggingface/datasets/issues/1863/events | https://github.com/huggingface/datasets/issues/1863 | 806,171,311 | MDU6SXNzdWU4MDYxNzEzMTE= | 1,863 | Add WikiCREM | {
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"Hi @NielsRogge I would like to work on this dataset.\r\n\r\nThanks!",
"Hi @udapy, are you working on this?"
] | 2021-02-11T08:16:00Z | 2021-03-07T07:27:13Z | null | CONTRIBUTOR | null | null | null | ## Adding a Dataset
- **Name:** WikiCREM
- **Description:** A large unsupervised corpus for coreference resolution.
- **Paper:** https://arxiv.org/abs/1905.06290
- **Github repo:**: https://github.com/vid-koci/bert-commonsense
- **Data:** https://ora.ox.ac.uk/objects/uuid:c83e94bb-7584-41a1-aef9-85b0e764d9e3
- **Motivation:** Coreference resolution, common sense reasoning
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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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-02-12T11:51:25Z | 2023-02-13T10:29:03Z | 2023-02-13T09:24:16Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2750 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2750/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2750/comments | https://api.github.com/repos/huggingface/datasets/issues/2750/events | https://github.com/huggingface/datasets/issues/2750 | 958,984,730 | MDU6SXNzdWU5NTg5ODQ3MzA= | 2,750 | Second concatenation of datasets produces errors | {
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"@albertvillanova ",
"Hi @Aktsvigun, thanks for reporting.\r\n\r\nI'm investigating this.",
"Hi @albertvillanova ,\r\nany update on this? Can I probably help in some way?",
"Hi @Aktsvigun! We are planning to address this issue before our next release, in a couple of weeks at most. 😅 \r\n\r\nIn the meantime, ... | 2021-08-03T10:47:04Z | 2022-01-19T14:23:43Z | 2022-01-19T14:19:05Z | NONE | null | null | null | Hi,
I am need to concatenate my dataset with others several times, and after I concatenate it for the second time, the features of features (e.g. tags names) are collapsed. This hinders, for instance, the usage of tokenize function with `data.map`.
```
from datasets import load_dataset, concatenate_datasets
data = load_dataset('trec')['train']
concatenated = concatenate_datasets([data, data])
concatenated_2 = concatenate_datasets([concatenated, concatenated])
print('True features of features:', concatenated.features)
print('\nProduced features of features:', concatenated_2.features)
```
outputs
```
True features of features: {'label-coarse': ClassLabel(num_classes=6, names=['DESC', 'ENTY', 'ABBR', 'HUM', 'NUM', 'LOC'], names_file=None, id=None), 'label-fine': ClassLabel(num_classes=47, names=['manner', 'cremat', 'animal', 'exp', 'ind', 'gr', 'title', 'def', 'date', 'reason', 'event', 'state', 'desc', 'count', 'other', 'letter', 'religion', 'food', 'country', 'color', 'termeq', 'city', 'body', 'dismed', 'mount', 'money', 'product', 'period', 'substance', 'sport', 'plant', 'techmeth', 'volsize', 'instru', 'abb', 'speed', 'word', 'lang', 'perc', 'code', 'dist', 'temp', 'symbol', 'ord', 'veh', 'weight', 'currency'], names_file=None, id=None), 'text': Value(dtype='string', id=None)}
Produced features of features: {'label-coarse': Value(dtype='int64', id=None), 'label-fine': Value(dtype='int64', id=None), 'text': Value(dtype='string', id=None)}
```
I am using `datasets` v.1.11.0 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"@lhoestq / @albertvillanova / @mariosasko \r\nI am facing the same scenario. Let me explain the situation point. I have a glue ETL job\r\n\r\n1--> My files are in parquet format and stored in AWS s3.\r\n2--> I am iterating a loop fo... | 2022-04-01T14:58:50Z | 2022-07-14T19:22:06Z | 2022-04-01T16:16:19Z | MEMBER | null | 0 | {
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} | We don’t call writer.close(), which causes https://github.com/huggingface/datasets/issues/4077. It can happen that we upload the file before the writer is garbage collected and writes the footer.
I fixed this by explicitly closing the parquet writer.
Close https://github.com/huggingface/datasets/issues/4077. | {
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https://api.github.com/repos/huggingface/datasets/issues/1835 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1835/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1835/comments | https://api.github.com/repos/huggingface/datasets/issues/1835/events | https://github.com/huggingface/datasets/issues/1835 | 803,524,790 | MDU6SXNzdWU4MDM1MjQ3OTA= | 1,835 | Add CHiME4 dataset | {
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"color": "d93f0b",... | open | false | null | [] | null | [] | 2021-02-08T12:36:38Z | 2021-02-08T13:13:31Z | null | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** Chime4
- **Description:** Chime4 is a dataset for automatic speech recognition. It is especially useful for evaluating models in a noisy environment and for multi-channel ASR
- **Paper:** Dataset comes from a channel: http://spandh.dcs.shef.ac.uk/chime_challenge/CHiME4/ . Results paper:
- **Data:** http://spandh.dcs.shef.ac.uk/chime_challenge/CHiME4/download.html
- **Motivation:** So far there are very little datasets for speech in `datasets`. Only `lbirispeech_asr` so far.
If interested in tackling this issue, feel free to tag @patrickvonplaten
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/3847 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3847/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3847/comments | https://api.github.com/repos/huggingface/datasets/issues/3847/events | https://github.com/huggingface/datasets/issues/3847 | 1,161,856,417 | I_kwDODunzps5FQIWh | 3,847 | Datasets' cache not re-used | {
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"<s>I think this is because the tokenizer is stateful and because the order in which the splits are processed is not deterministic. Because of that, the hash of the tokenizer may change for certain splits, which causes issues with caching.\r\n\r\nTo fix this we can try making the order of the splits deterministic f... | 2022-03-07T19:55:15Z | 2023-11-20T18:14:37Z | null | NONE | null | null | null | ## Describe the bug
For most tokenizers I have tested (e.g. the RoBERTa tokenizer), the data preprocessing cache are not fully reused in the first few runs, although their `.arrow` cache files are in the cache directory.
## Steps to reproduce the bug
Here is a reproducer. The GPT2 tokenizer works perfectly with caching, but not the RoBERTa tokenizer in this example.
```python
from datasets import load_dataset
from transformers import AutoTokenizer
raw_datasets = load_dataset("wikitext", "wikitext-2-raw-v1")
# tokenizer = AutoTokenizer.from_pretrained("gpt2")
tokenizer = AutoTokenizer.from_pretrained("roberta-base")
text_column_name = "text"
column_names = raw_datasets["train"].column_names
def tokenize_function(examples):
return tokenizer(examples[text_column_name], return_special_tokens_mask=True)
tokenized_datasets = raw_datasets.map(
tokenize_function,
batched=True,
remove_columns=column_names,
load_from_cache_file=True,
desc="Running tokenizer on every text in dataset",
)
```
## Expected results
No tokenization would be required after the 1st run. Everything should be loaded from the cache.
## Actual results
Tokenization for some subsets are repeated at the 2nd and 3rd run. Starting from the 4th run, everything are loaded from cache.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Ubuntu 18.04.6 LTS
- Python version: 3.6.9
- PyArrow version: 6.0.1
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"Cool, I'm in favor of this PR. Our official examples in speech already make use of `\"audio\"` so no need to change anything there. It would be great if we could prominently feature how one can get the audio path without decoding in the docs.",
"@patrickvonplaten Yes, I agree.\r\n\r\ncc @stevhliu we should add a... | 2021-12-16T16:35:15Z | 2023-09-24T10:09:30Z | 2023-09-24T10:09:27Z | CONTRIBUTOR | null | 1 | {
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} | Remove the redundant path information in the audio/image dataset as discussed in https://github.com/huggingface/datasets/pull/3430#issuecomment-994734828
TODOs:
* [ ] merge https://github.com/huggingface/datasets/pull/3430
* [ ] merge https://github.com/huggingface/datasets/pull/3364
* [ ] re-generate the info files of the updated audio datasets
cc: @patrickvonplaten @anton-l @nateraw (I expect this to break the audio/vision examples in Transformers; after this change you'll be able to access underlying paths as follows `dset = dset.cast_column("audio", Audio(..., decode=False)); path = dset[0]["audio"]`)
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} | Previously, the order of the columns in the features passes to `cast_` mattered.
However even though features passed to `cast_` had the same order as the dataset features, it could fail because the schema that was built was always in alphabetical order.
This issue was reported by @lewtun in #623
To fix that I fixed the schema to follow the order of the arrow table columns.
I also added the possibility to give features that are not ordered the same way as the dataset features. | {
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https://api.github.com/repos/huggingface/datasets/issues/451 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/451/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/451/comments | https://api.github.com/repos/huggingface/datasets/issues/451/events | https://github.com/huggingface/datasets/pull/451 | 667,210,468 | MDExOlB1bGxSZXF1ZXN0NDU3OTIxNDMx | 451 | Fix csv/json/txt cache dir | {
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"I think this is the way to go but I’m afraid this might be a little slow. I was thinking that we could use a high quality very fast non crypto hash like xxhash for these stuff (hashing data files)",
"Yep good idea, I'll take a look",
"I tested the hashing speed [here](https://colab.research.google.com/drive/1h... | 2020-07-28T16:30:51Z | 2020-07-29T13:57:23Z | 2020-07-29T13:57:22Z | MEMBER | null | 0 | {
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} | The cache dir for csv/json/txt datasets was always the same. This is an issue because it should be different depending on the data files provided by the user.
To fix that, I added a line that use the hash of the data files provided by the user to define the cache dir.
This should fix #444 | {
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https://api.github.com/repos/huggingface/datasets/issues/2961 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2961/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2961/comments | https://api.github.com/repos/huggingface/datasets/issues/2961/events | https://github.com/huggingface/datasets/pull/2961 | 1,006,453,781 | PR_kwDODunzps4sPTXV | 2,961 | Fix CI doc build | {
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} | Pin `fsspec`.
Before the issue: 'fsspec-2021.8.1', 's3fs-2021.8.1'
Generating the issue: 'fsspec-2021.9.0', 's3fs-0.5.1'
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https://api.github.com/repos/huggingface/datasets/issues/2103 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2103/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2103/comments | https://api.github.com/repos/huggingface/datasets/issues/2103/events | https://github.com/huggingface/datasets/issues/2103 | 838,946,916 | MDU6SXNzdWU4Mzg5NDY5MTY= | 2,103 | citation, homepage, and license fields of `dataset_info.json` are duplicated many times | {
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"default": true... | closed | false | null | [] | null | [
"Thanks for reporting :)\r\nMaybe we can concatenate fields only if they are different.\r\n\r\nCurrently this is done here:\r\n\r\nhttps://github.com/huggingface/nlp/blob/349ac4398a3bcae6356f14c5754483383a60e8a4/src/datasets/info.py#L180-L196\r\n\r\nThis can be a good first contribution to the library.\r\nPlease co... | 2021-03-23T17:18:09Z | 2021-04-06T14:39:59Z | 2021-04-06T14:39:59Z | NONE | null | null | null | This happens after a `map` operation when `num_proc` is set to `>1`. I tested this by cleaning up the json before running the `map` op on the dataset so it's unlikely it's coming from an earlier concatenation.
Example result:
```
"citation": "@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n
```
@lhoestq and I believe this is happening due to the fields being concatenated `num_proc` times. | {
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https://api.github.com/repos/huggingface/datasets/issues/4116 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4116/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4116/comments | https://api.github.com/repos/huggingface/datasets/issues/4116/events | https://github.com/huggingface/datasets/pull/4116 | 1,194,926,459 | PR_kwDODunzps41wCEO | 4,116 | Pretty print dataset info files | {
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"maybe just do it from now on no? (i.e. not for existing `dataset_infos.json` files)",
"_The documentation is not available anymore as the PR was closed or merged._",
"> maybe just do it from now on no? (i.e. not for existing dataset_infos.json files)\r\n\r\nYes, or do this only for datasets created with `push_... | 2022-04-06T17:40:48Z | 2022-04-08T11:28:01Z | 2022-04-08T11:21:53Z | CONTRIBUTOR | null | 0 | {
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} | Adds indentation to the `dataset_infos.json` file when saving for nicer diffs.
(suggested by @julien-c)
This PR also updates the info files of the GH datasets. Note that this change adds more than **10 MB** to the repo size (the total file size before the change: 29.672298 MB, after: 41.666475 MB), so I'm not sure this change is a good idea.
`src/datasets/info.py` is the only relevant file for reviewers.
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https://api.github.com/repos/huggingface/datasets/issues/6187 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6187/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6187/comments | https://api.github.com/repos/huggingface/datasets/issues/6187/events | https://github.com/huggingface/datasets/issues/6187 | 1,870,936,143 | I_kwDODunzps5vhDhP | 6,187 | Couldn't find a dataset script at /content/tsv/tsv.py or any data file in the same directory | {
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"Hi! You can load this dataset with:\r\n```python\r\ndata_files = {\r\n \"train\": \"/content/PUBHEALTH/train.tsv\",\r\n \"validation\": \"/content/PUBHEALTH/dev.tsv\",\r\n \"test\": \"/content/PUBHEALTH/test.tsv\",\r\n}\r\n\r\ntsv_datasets_reloaded = load_dataset(\"csv\", data_files=data_files, sep=\"\\t\... | 2023-08-29T05:49:56Z | 2023-08-29T16:21:45Z | null | NONE | null | null | null | ### Describe the bug
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
[<ipython-input-48-6a7b3e847019>](https://localhost:8080/#) in <cell line: 7>()
5 }
6
----> 7 csv_datasets_reloaded = load_dataset("tsv", data_files=data_files)
8 csv_datasets_reloaded
2 frames
[/usr/local/lib/python3.10/dist-packages/datasets/load.py](https://localhost:8080/#) in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)
1489 raise e1 from None
1490 if isinstance(e1, FileNotFoundError):
-> 1491 raise FileNotFoundError(
1492 f"Couldn't find a dataset script at {relative_to_absolute_path(combined_path)} or any data file in the same directory. "
1493 f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}"
FileNotFoundError: Couldn't find a dataset script at /content/tsv/tsv.py or any data file in the same directory. Couldn't find 'tsv' on the Hugging Face Hub either: FileNotFoundError: Dataset 'tsv' doesn't exist on the Hub
```
### Steps to reproduce the bug
```
data_files = {
"train": "/content/PUBHEALTH/train.tsv",
"validation": "/content/PUBHEALTH/dev.tsv",
"test": "/content/PUBHEALTH/test.tsv",
}
tsv_datasets_reloaded = load_dataset("tsv", data_files=data_files)
tsv_datasets_reloaded
```
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
<ipython-input-48-6a7b3e847019> in <cell line: 7>()
5 }
6
----> 7 csv_datasets_reloaded = load_dataset("tsv", data_files=data_files)
8 csv_datasets_reloaded
2 frames
/usr/local/lib/python3.10/dist-packages/datasets/load.py in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)
1489 raise e1 from None
1490 if isinstance(e1, FileNotFoundError):
-> 1491 raise FileNotFoundError(
1492 f"Couldn't find a dataset script at {relative_to_absolute_path(combined_path)} or any data file in the same directory. "
1493 f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}"
FileNotFoundError: Couldn't find a dataset script at /content/tsv/tsv.py or any data file in the same directory. Couldn't find 'tsv' on the Hugging Face Hub either: FileNotFoundError: Dataset 'tsv' doesn't exist on the Hub
```
### Expected behavior
load the data, push to hub
### Environment info
jupyter notebook RTX 3090 | {
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https://api.github.com/repos/huggingface/datasets/issues/5229 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5229/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5229/comments | https://api.github.com/repos/huggingface/datasets/issues/5229/events | https://github.com/huggingface/datasets/issues/5229 | 1,445,121,028 | I_kwDODunzps5WIswE | 5,229 | Type error when calling `map` over dataset containing 0-d tensors | {
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"Hi! \r\n\r\nWe could address this by calling `.item()` on such tensors to extract the value, but this would lose us the type, which could lead to storing the generated dataset in a suboptimal format. Considering this, I think the only proper fix would be implementing support for 0-D tensors on Apache Arrow's side ... | 2022-11-11T08:27:28Z | 2023-01-13T16:00:53Z | 2023-01-13T16:00:53Z | NONE | null | null | null | ### Describe the bug
0-dimensional tensors in a dataset lead to `TypeError: iteration over a 0-d array` when calling `map`. It is easy to generate such tensors by using `.with_format("...")` on the whole dataset.
### Steps to reproduce the bug
```
ds = datasets.Dataset.from_list([{"a": 1}, {"a": 1}]).with_format("torch")
ds.map(None)
```
### Expected behavior
Getting back `ds` without errors.
### Environment info
Python 3.10.8
datasets 2.6.
torch 1.13.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1616 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1616/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1616/comments | https://api.github.com/repos/huggingface/datasets/issues/1616/events | https://github.com/huggingface/datasets/pull/1616 | 772,074,229 | MDExOlB1bGxSZXF1ZXN0NTQzNDEwNDc1 | 1,616 | added TurkishMovieSentiment dataset | {
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"> I just generated the dataset_infos.json file\r\n> \r\n> Thanks for adding this one !\r\n\r\nThank you very much for your support."
] | 2020-12-21T11:03:16Z | 2020-12-24T07:08:41Z | 2020-12-23T16:50:06Z | CONTRIBUTOR | null | 0 | {
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} | This PR adds the **TurkishMovieSentiment: This dataset contains turkish movie reviews.**
- **Homepage:** [https://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset/tasks](https://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset/tasks)
- **Point of Contact:** [Mustafa Keskin](https://www.linkedin.com/in/mustfkeskin/) | {
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https://api.github.com/repos/huggingface/datasets/issues/4261 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4261/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4261/comments | https://api.github.com/repos/huggingface/datasets/issues/4261/events | https://github.com/huggingface/datasets/issues/4261 | 1,221,883,779 | I_kwDODunzps5I1HeD | 4,261 | data leakage in `webis/conclugen` dataset | {
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"Hi @xflashxx, thanks for reporting.\r\n\r\nPlease note that this dataset was generated and shared by Webis Group: https://huggingface.co/webis\r\n\r\nWe are contacting the dataset owners to inform them about the issue you found. We'll keep you updated of their reply.",
"i'd suggest just pinging the authors here ... | 2022-04-30T17:43:37Z | 2022-05-03T06:04:26Z | 2022-05-03T06:04:26Z | NONE | null | null | null | ## Describe the bug
Some samples (argument-conclusion pairs) in the *training* split of the `webis/conclugen` dataset are present in both the *validation* and *test* splits, creating data leakage and distorting model results.
Furthermore, all splits contain duplicate samples.
## Steps to reproduce the bug
```python
from datasets import load_dataset
training = load_dataset("webis/conclugen", "base", split="train")
validation = load_dataset("webis/conclugen", "base", split="validation")
testing = load_dataset("webis/conclugen", "base", split="test")
# collect which sample id's are present in the training split
ids_validation = list()
ids_testing = list()
for train_sample in training:
train_argument = train_sample["argument"]
train_conclusion = train_sample["conclusion"]
train_id = train_sample["id"]
# test if current sample is in validation split
if train_argument in validation["argument"]:
for validation_sample in validation:
validation_argument = validation_sample["argument"]
validation_conclusion = validation_sample["conclusion"]
validation_id = validation_sample["id"]
if train_argument == validation_argument and train_conclusion == validation_conclusion:
ids_validation.append(validation_id)
# test if current sample is in test split
if train_argument in testing["argument"]:
for testing_sample in testing:
testing_argument = testing_sample["argument"]
testing_conclusion = testing_sample["conclusion"]
testing_id = testing_sample["id"]
if train_argument == testing_argument and train_conclusion == testing_conclusion:
ids_testing.append(testing_id)
```
## Expected results
Length of both lists `ids_validation` and `ids_testing` should be zero.
## Actual results
Length of `ids_validation` = `2556`
Length of `ids_testing` = `287`
Furthermore, there seems to be duplicate samples in (at least) the *training* split, since:
`print(len(set(ids_validation)))` = `950`
`print(len(set(ids_testing)))` = `101`
All in all, around 7% of the samples of each the *validation* and *test* split seems to be present in the *training* split.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.4
- Platform: macOS-12.3.1-arm64-arm-64bit
- Python version: 3.9.10
- PyArrow version: 7.0.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/523 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/523/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/523/comments | https://api.github.com/repos/huggingface/datasets/issues/523/events | https://github.com/huggingface/datasets/pull/523 | 682,573,232 | MDExOlB1bGxSZXF1ZXN0NDcwNzkxMjA1 | 523 | Speed up Tokenization by optimizing cast_to_python_objects | {
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"I took your comments into account and added tests for `cast_to_python_objects`"
] | 2020-08-20T09:42:02Z | 2020-08-24T08:54:15Z | 2020-08-24T08:54:14Z | MEMBER | null | 0 | {
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} | I changed how `cast_to_python_objects` works to make it faster.
It is used to cast numpy/pytorch/tensorflow/pandas objects to python lists, and it works recursively.
To avoid iterating over possibly long lists, it first checks if the first element that is not None has to be casted.
If the first element needs to be casted, then all the elements of the list will be casted, otherwise they'll stay the same.
This trick allows to cast objects that contain tokenizers outputs without iterating over every single token for example.
Speed improvement:
```python
import transformers
import nlp
tok = transformers.BertTokenizerFast.from_pretrained("bert-base-uncased")
txt = ["a " * 512] * 1000
dataset = nlp.Dataset.from_dict({"txt": txt})
# Tokenization using .map is now faster. Previously it was taking 3.5s
%time _ = dataset.map(lambda x: tok(x["txt"]), batched=True, load_from_cache_file=False)
# 450ms
# for comparison
%time _ = tok(txt)
# 280ms
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3384 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3384/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3384/comments | https://api.github.com/repos/huggingface/datasets/issues/3384/events | https://github.com/huggingface/datasets/pull/3384 | 1,071,594,165 | PR_kwDODunzps4vaNwL | 3,384 | Adding mMARCO dataset | {
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} | We are adding mMARCO dataset to HuggingFace datasets repo.
This way, all the languages covered in the translation are available in a easy way. | {
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https://api.github.com/repos/huggingface/datasets/issues/5042 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5042/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5042/comments | https://api.github.com/repos/huggingface/datasets/issues/5042/events | https://github.com/huggingface/datasets/pull/5042 | 1,390,762,877 | PR_kwDODunzps4_2eqa | 5,042 | Update swiss judgment prediction | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-29T12:10:02Z | 2022-09-30T07:14:00Z | 2022-09-29T14:32:02Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6460 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6460/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6460/comments | https://api.github.com/repos/huggingface/datasets/issues/6460/events | https://github.com/huggingface/datasets/issues/6460 | 2,017,433,899 | I_kwDODunzps54P5kr | 6,460 | jsonlines files don't load with `load_dataset` | {
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"Hi @serenalotreck,\r\n\r\nWe use Apache Arrow `pyarrow` to read jsonlines and it throws an error when trying to load your data files:\r\n```python\r\nIn [1]: import pyarrow as pa\r\n\r\nIn [2]: data = pa.json.read_json(\"train.jsonl\")\r\n---------------------------------------------------------------------------\... | 2023-11-29T21:20:11Z | 2023-12-05T14:02:12Z | 2023-12-05T13:30:53Z | NONE | null | null | null | ### Describe the bug
While [the docs](https://huggingface.co/docs/datasets/upload_dataset#upload-dataset) seem to state that `.jsonl` is a supported extension for `datasets`, loading the dataset results in a `JSONDecodeError`.
### Steps to reproduce the bug
Code:
```
from datasets import load_dataset
dset = load_dataset('slotreck/pickle')
```
Traceback:
```
Downloading readme: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 925/925 [00:00<00:00, 3.11MB/s]
Downloading and preparing dataset json/slotreck--pickle to /mnt/home/lotrecks/.cache/huggingface/datasets/slotreck___json/slotreck--pickle-0c311f36ed032b04/0.0.0/8bb11242116d547c741b2e8a1f18598ffdd40a1d4f2a2872c7a28b697434bc96...
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 589k/589k [00:00<00:00, 18.9MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 104k/104k [00:00<00:00, 4.61MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 170k/170k [00:00<00:00, 7.71MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 3.77it/s]
Extracting data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 523.92it/s]
Generating train split: 0 examples [00:00, ? examples/s]Failed to read file '/mnt/home/lotrecks/.cache/huggingface/datasets/downloads/6ec07bb2f279c9377036af6948532513fa8f48244c672d2644a2d7018ee5c9cb' with error <class 'pyarrow.lib.ArrowInvalid'>: JSON parse error: Column(/ner/[]/[]/[]) changed from number to string in row 0
Traceback (most recent call last):
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/site-packages/datasets/packaged_modules/json/json.py", line 144, in _generate_tables
dataset = json.load(f)
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/json/__init__.py", line 296, in load
parse_constant=parse_constant, object_pairs_hook=object_pairs_hook, **kw)
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/json/__init__.py", line 348, in loads
return _default_decoder.decode(s)
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/json/decoder.py", line 340, in decode
raise JSONDecodeError("Extra data", s, end)
json.decoder.JSONDecodeError: Extra data: line 2 column 1 (char 3086)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/site-packages/datasets/builder.py", line 1879, in _prepare_split_single
for _, table in generator:
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/site-packages/datasets/packaged_modules/json/json.py", line 147, in _generate_tables
raise e
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/site-packages/datasets/packaged_modules/json/json.py", line 122, in _generate_tables
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
File "pyarrow/_json.pyx", line 259, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 144, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Column(/ner/[]/[]/[]) changed from number to string in row 0
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/site-packages/datasets/load.py", line 1815, in load_dataset
storage_options=storage_options,
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/site-packages/datasets/builder.py", line 913, in download_and_prepare
**download_and_prepare_kwargs,
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/site-packages/datasets/builder.py", line 1004, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/site-packages/datasets/builder.py", line 1768, in _prepare_split
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
File "/mnt/home/lotrecks/anaconda3/envs/pickle/lib/python3.7/site-packages/datasets/builder.py", line 1912, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.builder.DatasetGenerationError: An error occurred while generating the dataset
```
### Expected behavior
For the dataset to be loaded without error.
### Environment info
- `datasets` version: 2.13.1
- Platform: Linux-3.10.0-1160.80.1.el7.x86_64-x86_64-with-centos-7.9.2009-Core
- Python version: 3.7.12
- Huggingface_hub version: 0.15.1
- PyArrow version: 8.0.0
- Pandas version: 1.3.5 | {
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https://api.github.com/repos/huggingface/datasets/issues/6294 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6294/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6294/comments | https://api.github.com/repos/huggingface/datasets/issues/6294/events | https://github.com/huggingface/datasets/issues/6294 | 1,937,359,605 | I_kwDODunzps5zecL1 | 6,294 | IndexError: Invalid key is out of bounds for size 0 despite having a populated dataset | {
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"It looks to be the same issue as the one reported in https://discuss.huggingface.co/t/indexerror-invalid-key-16-is-out-of-bounds-for-size-0.\r\n\r\nCan you check the length of `train_dataset` before the `train_sampler = self._get_train_sampler()` (and after `_remove_unused_columns`) line?"
] | 2023-10-11T09:59:38Z | 2023-10-17T11:24:06Z | 2023-10-17T11:24:06Z | NONE | null | null | null | ### Describe the bug
I am encountering an `IndexError` when trying to access data from a DataLoader which wraps around a dataset I've loaded using the `datasets` library. The error suggests that the dataset size is `0`, but when I check the length and print the dataset, it's clear that it has `1166` entries.
### Steps to reproduce the bug
1. Load a dataset with `1166` entries.
2. Create a DataLoader using this dataset.
3. Try iterating over the DataLoader.
code:
```python
def get_train_dataloader(self) -> DataLoader:
if self.train_dataset is None:
raise ValueError("Trainer: training requires a train_dataset.")
train_dataset = self.train_dataset
data_collator = self.data_collator
print(len(train_dataset))
print(train_dataset)
if is_datasets_available() and isinstance(train_dataset, datasets.Dataset):
train_dataset = self._remove_unused_columns(train_dataset, description="training")
else:
data_collator = self._get_collator_with_removed_columns(data_collator, description="training")
train_sampler = self._get_train_sampler()
dl = DataLoader(
train_dataset,
batch_size=self._train_batch_size,
sampler=train_sampler,
collate_fn=data_collator,
drop_last=self.args.dataloader_drop_last,
num_workers=self.args.dataloader_num_workers,
pin_memory=self.args.dataloader_pin_memory,
worker_init_fn=seed_worker,
)
print(dl)
print(len(dl))
for i in dl:
print(i)
break
return dl
```
output :
```
1166
Dataset({
features: ['input_ids', 'special_tokens_mask'],
num_rows: 1166
})
<torch.utils.data.dataloader.DataLoader object ...>
146
```
Error:
```
Traceback (most recent call last):
File "/home/dl/zym/llamaJP/TestUseContinuePretrainLlama.py", line 266, in <module>
train()
File "/home/dl/zym/llamaJP/TestUseContinuePretrainLlama.py", line 260, in train
trainer.train()
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/transformers/trainer.py", line 1506, in train
return inner_training_loop(
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/transformers/trainer.py", line 1520, in _inner_training_loop
train_dataloader = self.get_train_dataloader()
File "/home/dl/zym/llamaJP/TestUseContinuePretrainLlama.py", line 80, in get_train_dataloader
for i in dl:
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 630, in __next__
data = self._next_data()
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 674, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch
data = self.dataset.__getitems__(possibly_batched_index)
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 2807, in __getitems__
batch = self.__getitem__(keys)
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 2803, in __getitem__
return self._getitem(key)
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 2787, in _getitem
pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/datasets/formatting/formatting.py", line 583, in query_table
_check_valid_index_key(key, size)
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/datasets/formatting/formatting.py", line 536, in _check_valid_index_key
_check_valid_index_key(int(max(key)), size=size)
File "/root/miniconda3/envs/LLM/lib/python3.10/site-packages/datasets/formatting/formatting.py", line 526, in _check_valid_index_key
raise IndexError(f"Invalid key: {key} is out of bounds for size {size}")
IndexError: Invalid key: 1116 is out of bounds for size 0
```
### Expected behavior
I expect to be able to iterate over the DataLoader without encountering an IndexError since the dataset is populated.
### Environment info
- `datasets` library version: [2.14.5]
- Platform: [Linux]
- Python version: 3.10
- Other libraries involved: HuggingFace Transformers | {
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https://api.github.com/repos/huggingface/datasets/issues/3642 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3642/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3642/comments | https://api.github.com/repos/huggingface/datasets/issues/3642/events | https://github.com/huggingface/datasets/pull/3642 | 1,116,306,986 | PR_kwDODunzps4xrj2S | 3,642 | Fix dataset slicing with negative bounds when indices mapping is not `None` | {
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https://api.github.com/repos/huggingface/datasets/issues/3269 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3269/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3269/comments | https://api.github.com/repos/huggingface/datasets/issues/3269/events | https://github.com/huggingface/datasets/issues/3269 | 1,053,218,769 | I_kwDODunzps4-xtfR | 3,269 | coqa NonMatchingChecksumError | {
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"Hi @ZhaofengWu, thanks for reporting.\r\n\r\nUnfortunately, I'm not able to reproduce your bug:\r\n```python\r\nIn [1]: from datasets import load_dataset\r\n\r\nIn [2]: ds = load_dataset(\"coqa\")\r\nDownloading: 3.82kB [00:00, 1.91MB/s]\r\nDownloading: 1.79kB [00:00, 1.79MB/s]\r\nUsing custom data configuration d... | 2021-11-15T05:04:07Z | 2022-01-19T13:58:19Z | 2022-01-19T13:58:19Z | NONE | null | null | null | ```
>>> from datasets import load_dataset
>>> dataset = load_dataset("coqa")
Downloading: 3.82kB [00:00, 1.26MB/s]
Downloading: 1.79kB [00:00, 733kB/s]
Using custom data configuration default
Downloading and preparing dataset coqa/default (download: 55.40 MiB, generated: 18.35 MiB, post-processed: Unknown size, total: 73.75 MiB) to /Users/zhaofengw/.cache/huggingface/datasets/coqa/default/1.0.0/553ce70bfdcd15ff4b5f4abc4fc2f37137139cde1f58f4f60384a53a327716f0...
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 222/222 [00:00<00:00, 1.38MB/s]
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 222/222 [00:00<00:00, 1.32MB/s]
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:01<00:00, 1.91it/s]
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1117.44it/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/builder.py", line 679, in _download_and_prepare
verify_checksums(
File "/Users/zhaofengw/miniconda3/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://nlp.stanford.edu/data/coqa/coqa-train-v1.0.json', 'https://nlp.stanford.edu/data/coqa/coqa-dev-v1.0.json']
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4561 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4561/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4561/comments | https://api.github.com/repos/huggingface/datasets/issues/4561/events | https://github.com/huggingface/datasets/pull/4561 | 1,283,624,242 | PR_kwDODunzps46TnVe | 4,561 | Add evaluation data to acronym_identification | {
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"Sure this sounds great! Would this be pure torchvision, albumentations, or something else?",
"I am considering `torchvision` and `albumentations`. Also [works with TensorFlow](https://github.com/deep-diver/segformer-tf-transformers/blob/main/notebooks/TFSegFormer_Finetune.ipynb). \r\n\r\nI am assigning the issue... | 2022-11-01T07:54:50Z | 2022-11-04T18:23:36Z | 2022-11-04T18:23:36Z | MEMBER | null | null | null | Currently, we have these guides for object detection and image classification:
* https://huggingface.co/docs/datasets/object_detection
* https://huggingface.co/docs/datasets/image_classification
I am proposing adding a similar guide for semantic segmentation.
I am happy to contribute a PR for it.
Cc: @osanseviero @nateraw | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-11-22T19:04:45Z | 2023-11-23T18:47:30Z | 2023-11-23T18:41:23Z | CONTRIBUTOR | null | 0 | {
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} | Use the `filelock` package instead of `datasets.utils.filelock` for file locking to be consistent with `huggingface_hub` and not to be responsible for improving the `filelock` capabilities 🙂.
(Reverts https://github.com/huggingface/datasets/pull/859, but these `INFO` logs are not printed by default (anymore?), so this should be okay)
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} | After contacting the authors of the VIVOS dataset to report that their data server is down, we have received a reply from Hieu-Thi Luong that their data is now hosted on Zenodo: https://doi.org/10.5281/zenodo.7068130
This PR updates their data URL and some metadata (homepage, citation and license).
Fix #4936. | {
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"I fixed those two things, the two remaining failing checks seem to be due to some dependency missing in the tests."
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https://api.github.com/repos/huggingface/datasets/issues/5684 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5684/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5684/comments | https://api.github.com/repos/huggingface/datasets/issues/5684/events | https://github.com/huggingface/datasets/pull/5684 | 1,646,013,226 | PR_kwDODunzps5NLXWm | 5,684 | Release: 2.11.0 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-03-29T15:06:07Z | 2023-03-29T18:30:34Z | 2023-03-29T18:15:54Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6416 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6416/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6416/comments | https://api.github.com/repos/huggingface/datasets/issues/6416/events | https://github.com/huggingface/datasets/pull/6416 | 1,992,954,723 | PR_kwDODunzps5fbA4H | 6,416 | Rename audio_classificiation.py to audio_classification.py | {
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"Oh good catch. Can you also rename it in `src/datasets/tasks/__init__.py` ?",
"Fixed! \r\n\r\n(I think, tough word to spell right TBH)",
"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show... | 2023-11-14T15:15:29Z | 2023-11-15T11:59:32Z | 2023-11-15T11:53:20Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6395 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6395/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6395/comments | https://api.github.com/repos/huggingface/datasets/issues/6395/events | https://github.com/huggingface/datasets/issues/6395 | 1,986,484,124 | I_kwDODunzps52Z1ec | 6,395 | Add ability to set lock type | {
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"We've replaced our filelock implementation with the `filelock` package, so their repo is the right place to request this feature.\r\n\r\nIn the meantime, the following should work: \r\n```python\r\nimport filelock\r\nfilelock.FileLock = filelock.SoftFileLock\r\n\r\nimport datasets\r\n...\r\n```"
] | 2023-11-09T22:12:30Z | 2023-11-23T18:50:00Z | 2023-11-23T18:50:00Z | NONE | null | null | null | ### Feature request
Allow setting file lock type, maybe from an environment variable
Currently, it only depends on whether fnctl is available:
https://github.com/huggingface/datasets/blob/12ebe695b4748c5a26e08b44ed51955f74f5801d/src/datasets/utils/filelock.py#L463-L470C16
### Motivation
In my environment, flock isn't supported on a network attached drive
### Your contribution
I'll be happy to submit a pr. | {
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https://api.github.com/repos/huggingface/datasets/issues/6499 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6499/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6499/comments | https://api.github.com/repos/huggingface/datasets/issues/6499/events | https://github.com/huggingface/datasets/pull/6499 | 2,043,166,976 | PR_kwDODunzps5iFIUF | 6,499 | docs: add reference Git over SSH | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6499). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2023-12-15T08:38:31Z | 2023-12-15T11:48:47Z | 2023-12-15T11:42:38Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6041 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6041/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6041/comments | https://api.github.com/repos/huggingface/datasets/issues/6041/events | https://github.com/huggingface/datasets/pull/6041 | 1,807,441,055 | PR_kwDODunzps5Vp0GX | 6,041 | Flatten repository_structure docs on yaml | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6041). 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... | 2023-07-17T10:15:10Z | 2023-07-17T10:24:51Z | 2023-07-17T10:16:22Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3224 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3224/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3224/comments | https://api.github.com/repos/huggingface/datasets/issues/3224/events | https://github.com/huggingface/datasets/pull/3224 | 1,046,495,831 | PR_kwDODunzps4uLk2q | 3,224 | User-pickling with dynamic sub-classing | {
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"@lhoestq Feel free to have a look. The implementation is slightly different from what you suggested. I have opted to overwrite `save` instead of meddling with `save_global`. `save_global` is called very late down in dill/pickle so it is hard to control for what is happening there. I might be wrong. Pickling is mor... | 2021-11-06T12:08:24Z | 2022-07-06T15:19:48Z | null | CONTRIBUTOR | null | 1 | {
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} | This is a continuation of the now closed PR in https://github.com/huggingface/datasets/pull/3206. The discussion there has shaped a new approach to do this.
In this PR, behavior of `pklregister` and `Pickler` is extended. Earlier, users were already able to register custom pickle functions. That is useful if they have objects that are not easily picklable with default methods. When one registers a custom function to a type, an object of that type will be pickled with the given function by `Pickler` which looks up the type in its `dispatch` table. The downside of this method, and of `pickle` in general, is that it is limited to direct type-matching and does not allow sub-classes. In many, default, cases that is not an issue. But when you are using external libraries where classes (e.g. parsers, models) are sub-classed this is not ideal.
```python
from datasets.fingerprint import Hasher
from datasets.utils.py_utils import pklregister
class BaseParser:
pass
class EnglishParser(BaseParser):
pass
@pklregister(BaseParser)
def custom_pkl_func(pickler, obj):
print(f"Called the custom pickle function for type {type(obj)}!")
# do something with the obj and ultimately save with the pickler
base = BaseParser()
en = EnglishParser()
# Hasher.hash uses the Pickler behind the scenes
# `custom_pkl_func` called for base
Hasher.hash(base)
# `custom_pkl_func` not called for en :-(
Hasher.hash(en)
```
In the example above we'd want to sub-class `EnglishParser` to be handled in the same way as its super-class `BaseParser`. This PR solves that by allowing for a keyword-argument `allow_subclasses` in `pklregister` (default: `False`).
```python
@pklregister(BaseParser, allow_subclasses=True)
```
When this option is enabled, we not only save the function in `Pickler.dispatch` but also save it in a custom table `Pickler.subclass_dispatch` **which allows us to dynamically add sub-classes of that class to the real dispatch table**. Then, if we want to pickle an object `obj` with `Pickler.dump()` (which ultimately will call `Pickler.save()`) we _first_ check whether any of the object's super-classes exist in `Pickler.sublcass_dispatch` and get the related custom pickle function. If we find one, we add the type of `obj` alongside the function to `Pickler.dispatch`. All of this happens at the start of the call to `Pickler.save()`. _Only then_ dill.Pickler's `save` will be called, which in turn will call `pickle._Pickler.save` which handles everything. Here, the `Pickler.dispatch` table will be used to look up custom pickler functions - and it now also includes the function for `obj`, which was copied from its super-class, which we added at the very start of our custom `Pickler.save()`.
For edge cases and, especially, for testing, a contextmanager class `TempPickleRegistry` is included that resets the pickle registry on exit to its previous state.
```python
with TempPickleRegistry():
@pklregister(MyObjClass)
def pickle_registry_test_false(pickler, obj):
pickler.save(obj.fancy_method())
some_obj = MyObjClass()
dumps(some_obj)
# `MyObjClass` is in Pickler.dispatch
# ... `MyObjClass` is _not_ in Pickler.dispatch anymore
```
closes https://github.com/huggingface/datasets/issues/3178
To Do
====
- [x] Write tests
- [ ] Write documentation/examples? | {
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https://api.github.com/repos/huggingface/datasets/issues/3779 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3779/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3779/comments | https://api.github.com/repos/huggingface/datasets/issues/3779/events | https://github.com/huggingface/datasets/pull/3779 | 1,148,050,636 | PR_kwDODunzps4zV4qr | 3,779 | Update manual download URL in newsroom dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/2629 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2629/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2629/comments | https://api.github.com/repos/huggingface/datasets/issues/2629/events | https://github.com/huggingface/datasets/issues/2629 | 941,819,205 | MDU6SXNzdWU5NDE4MTkyMDU= | 2,629 | Load datasets from the Hub without requiring a dataset script | {
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"This is so cool, let us know if we can help with anything on the hub side (@Pierrci @elishowk) 🎉 "
] | 2021-07-12T08:45:17Z | 2021-08-25T14:18:08Z | 2021-08-25T14:18:08Z | MEMBER | null | null | null | As a user I would like to be able to upload my csv/json/text/parquet/etc. files in a dataset repository on the Hugging Face Hub and be able to load this dataset with `load_dataset` without having to implement a dataset script.
Moreover I would like to be able to specify which file goes into which split using the `data_files` argument.
This feature should be compatible with private repositories and dataset streaming.
This can be implemented by checking the extension of the files in the dataset repository and then by using the right dataset builder that is already packaged in the library (csv/json/text/parquet/etc.) | {
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"Hi !\r\n\r\nAs you noticed, \"big\" datasets like Wikipedia require apache beam to be processed.\r\nHowever users usually don't have an apache beam runtime available (spark, dataflow, etc.) so our goal for this library is to also make available processed versions of these datasets, so that users can just download ... | 2020-06-17T15:06:21Z | 2020-06-19T12:53:02Z | 2020-06-19T12:53:02Z | NONE | null | null | null | Hi, first off let me say thank you for all the awesome work you're doing at Hugging Face across all your projects (NLP, Transformers, Tokenizers) - they're all amazing contributions to us working with NLP models :)
I'm trying to download the German Wikipedia dataset as follows:
```
wiki = nlp.load_dataset("wikipedia", "20200501.de", split="train")
```
However, when I do so, I get the following error:
```
Downloading and preparing dataset wikipedia/20200501.de (download: Unknown size, generated: Unknown size, total: Unknown size) to /home/ubuntu/.cache/huggingface/datasets/wikipedia/20200501.de/1.0.0...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/ubuntu/anaconda3/envs/albert/lib/python3.7/site-packages/nlp/load.py", line 520, in load_dataset
save_infos=save_infos,
File "/home/ubuntu/anaconda3/envs/albert/lib/python3.7/site-packages/nlp/builder.py", line 433, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/ubuntu/anaconda3/envs/albert/lib/python3.7/site-packages/nlp/builder.py", line 824, in _download_and_prepare
"\n\t`{}`".format(usage_example)
nlp.builder.MissingBeamOptions: Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided in `load_dataset` or in the builder arguments. For big datasets it has to run on large-scale data processing tools like Dataflow, Spark, etc. More information about Apache Beam runners at https://beam.apache.org/documentation/runners/capability-matrix/
If you really want to run it locally because you feel like the Dataset is small enough, you can use the local beam runner called `DirectRunner` (you may run out of memory).
Example of usage:
`load_dataset('wikipedia', '20200501.de', beam_runner='DirectRunner')`
```
So, following on from the example usage at the bottom, I tried specifying `beam_runner='DirectRunner`, however when I do this after about 20 min after the data has all downloaded, I get a `MemoryError` as warned.
This isn't an issue for the English or French Wikipedia datasets (I've tried both), as neither seem to require that `beam_runner` be specified. Can you please clarify why this is an issue for the German dataset?
My nlp version is 0.2.1.
Thank you! | {
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"Hi @hwijeen, you might want to look at issues #1796 and #1949. I think it could be something related to the I/O operations being performed.",
"I see that many people are experiencing the same issue. Is this problem considered an \"official\" bug that is worth a closer look? @lhoestq",
"Yes this looks like a bu... | 2021-03-05T02:10:02Z | 2023-06-08T12:31:55Z | null | NONE | null | null | null | Hi, thank you for the great library.
I've been using datasets to pretrain language models, and it often involves datasets as large as ~70G.
My data preparation step is roughly two steps: `load_dataset` which splits corpora into a table of sentences, and `map` converts a sentence into a list of integers, using a tokenizer.
I noticed that `map` function with `num_proc=mp.cpu_count() //2` takes more than 20 hours to finish the job where as `num_proc=1` gets the job done in about 5 hours. The machine I used has 40 cores, with 126G of RAM. There were no other jobs when `map` function was running.
What could be the reason? I would be happy to provide information necessary to spot the reason.
p.s. I was experiencing the imbalance issue mentioned in [here](https://github.com/huggingface/datasets/issues/610#issuecomment-705177036) when I was using multi processing.
p.s.2 When I run `map` with `num_proc=1`, I see one tqdm bar but all the cores are working. When `num_proc=20`, only 20 cores work.
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https://api.github.com/repos/huggingface/datasets/issues/2495 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2495/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2495/comments | https://api.github.com/repos/huggingface/datasets/issues/2495/events | https://github.com/huggingface/datasets/issues/2495 | 920,170,030 | MDU6SXNzdWU5MjAxNzAwMzA= | 2,495 | JAX formatting | {
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"gists... | null | [] | 2021-06-14T08:32:07Z | 2021-06-21T16:15:49Z | 2021-06-21T16:15:49Z | MEMBER | null | null | null | We already support pytorch, tensorflow, numpy, pandas and arrow dataset formatting. Let's add jax as well | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Nit: We should also update the `Disclaimers` section to let the dataset owners know they should use Hub discussions rather than GH issues for removal requests/updates",
"Updated the disclaimers section, thanks !\r\n\r\nDoes it soun... | 2022-11-07T14:51:23Z | 2022-11-24T11:35:07Z | 2022-11-24T11:26:16Z | MEMBER | null | 0 | {
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} | Tweaked some paragraphs mentioning the modalities we support + added a paragraph on security | {
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https://api.github.com/repos/huggingface/datasets/issues/4746 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4746/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4746/comments | https://api.github.com/repos/huggingface/datasets/issues/4746/events | https://github.com/huggingface/datasets/issues/4746 | 1,318,486,599 | I_kwDODunzps5OloJH | 4,746 | Dataset Viewer issue for yanekyuk/wikikey | {
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"The dataset is empty, as far as I can tell: there are no files in the repository at https://huggingface.co/datasets/yanekyuk/wikikey/tree/main\r\n\r\nMaybe the viewer can display a better message for empty datasets",
"OK. Closing as it's not an error. We will work on making the error message a lot clearer."
] | 2022-07-26T16:25:16Z | 2022-09-08T08:15:22Z | 2022-09-08T08:15:22Z | NONE | null | null | null | ### Link
_No response_
### Description
_No response_
### Owner
_No response_ | {
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https://api.github.com/repos/huggingface/datasets/issues/43 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/43/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/43/comments | https://api.github.com/repos/huggingface/datasets/issues/43/events | https://github.com/huggingface/datasets/pull/43 | 611,773,279 | MDExOlB1bGxSZXF1ZXN0NDEyODcxNTE5 | 43 | [Checksums] If no configs exist prevent to run over empty list | {
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"Whoops I fixed it directly on master before checking that you have done it in this PR. We may close it",
"Yeah, I saw :-) But I think we should add this as well since some datasets have an empty list of configs and then as the code is now it would fail. \r\n\r\nIn this PR, I just make sure that the code jumps in... | 2020-05-04T10:39:42Z | 2022-10-04T09:32:02Z | 2020-05-04T13:18:03Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1995 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1995/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1995/comments | https://api.github.com/repos/huggingface/datasets/issues/1995/events | https://github.com/huggingface/datasets/pull/1995 | 822,878,431 | MDExOlB1bGxSZXF1ZXN0NTg1NDI5NTg0 | 1,995 | [Timit_asr] Make sure not only the first sample is used | {
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"cc @lhoestq @vrindaprabhu",
"Failing `run (push)` is unrelated -> merging",
"Thanks for fixing this, it was affecting my runs for https://github.com/huggingface/transformers/pull/10581/",
"I am seeing this very late! Sorry for the blunder everyone! :("
] | 2021-03-05T08:42:51Z | 2021-06-30T06:25:53Z | 2021-03-05T08:58:59Z | MEMBER | null | 0 | {
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} | When playing around with timit I noticed that only the first sample is used for all indices. I corrected this typo so that the dataset is correctly loaded. | {
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https://api.github.com/repos/huggingface/datasets/issues/6508 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6508/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6508/comments | https://api.github.com/repos/huggingface/datasets/issues/6508/events | https://github.com/huggingface/datasets/pull/6508 | 2,045,733,273 | PR_kwDODunzps5iNvAu | 6,508 | Read GeoParquet files using parquet reader | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6508). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2023-12-18T04:50:37Z | 2023-12-18T10:36:34Z | null | NONE | null | 0 | {
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} | Let GeoParquet files with the file extension `*.geoparquet` or `*.gpq` be readable by the default parquet reader.
Those two file extensions are the ones most commonly used for GeoParquet files, and is included in the `gpq` validator tool at https://github.com/planetlabs/gpq/blob/e5576b4ee7306b4d2259d56c879465a9364dab90/cmd/gpq/command/convert.go#L73-L75
Addresses https://github.com/huggingface/datasets/issues/6438 | {
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https://api.github.com/repos/huggingface/datasets/issues/2364 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2364/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2364/comments | https://api.github.com/repos/huggingface/datasets/issues/2364/events | https://github.com/huggingface/datasets/pull/2364 | 892,420,500 | MDExOlB1bGxSZXF1ZXN0NjQ1MTI4MDYx | 2,364 | README updated for SNLI, MNLI | {
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"Regarding the license issue, I think we should allow it since it starts with `other-`. Cc @gchhablani what do you think ?",
"@lhoestq I agree, I'll look into it."
] | 2021-05-15T11:37:59Z | 2021-05-17T14:14:27Z | 2021-05-17T13:34:19Z | CONTRIBUTOR | null | 0 | {
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} | Closes #2275. Mentioned about -1 labels in MNLI, SNLI and how they should be removed before training. @lhoestq `check_code_quality` test might fail for MNLI as the license name `other-Open Portion of the American National Corpus` is not a registered tag for 'licenses' | {
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https://api.github.com/repos/huggingface/datasets/issues/5565 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5565/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5565/comments | https://api.github.com/repos/huggingface/datasets/issues/5565/events | https://github.com/huggingface/datasets/pull/5565 | 1,595,281,752 | PR_kwDODunzps5KhfTH | 5,565 | Add writer_batch_size for ArrowBasedBuilder | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-02-22T15:09:30Z | 2023-03-10T13:53:03Z | 2023-03-10T13:45:43Z | MEMBER | null | 0 | {
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} | This way we can control the size of the record_batches/row_groups of arrow/parquet files.
This can be useful for `datasets-server` to keep control of the row groups size which can affect random access performance for audio/image/video datasets
Right now having 1,000 examples per row group cause some image datasets to be pretty slow for random access (e.g. 4seconds for `beans` to get 20 rows) | {
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https://api.github.com/repos/huggingface/datasets/issues/3037 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3037/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3037/comments | https://api.github.com/repos/huggingface/datasets/issues/3037/events | https://github.com/huggingface/datasets/pull/3037 | 1,018,091,919 | PR_kwDODunzps4syi15 | 3,037 | SberQuad | {
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https://api.github.com/repos/huggingface/datasets/issues/3049 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3049/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3049/comments | https://api.github.com/repos/huggingface/datasets/issues/3049/events | https://github.com/huggingface/datasets/issues/3049 | 1,021,770,008 | I_kwDODunzps485vkY | 3,049 | TimeoutError during streaming | {
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] | closed | false | null | [] | null | [] | 2021-10-09T18:06:51Z | 2021-10-11T09:35:38Z | 2021-10-11T09:35:38Z | CONTRIBUTOR | null | null | null | ## Describe the bug
I got a TimeoutError after streaming for about 10h.
## Steps to reproduce the bug
Very long code but we could do a test of streaming indefinitely data, though error may take a while to appear.
## Expected results
This error was not expected in the code which considers only `ClientError` but not `TimeoutError`.
See [this line](https://github.com/huggingface/datasets/blob/2814fbd0e18150be409f10804670e98d9ecb87d4/src/datasets/utils/streaming_download_manager.py#L129).
Based on the traceback, it looks like the `TimeoutError` was not captured.
## Actual results
```
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/fsspec/asyn.py", line 25, in _runner
result[0] = await coro
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/fsspec/implementations/http.py", line 614, in async_fetch_range
out = await r.read()
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/aiohttp/client_reqrep.py", line 1032, in read
self._body = await self.content.read()
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/aiohttp/streams.py", line 370, in read
block = await self.readany()
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/aiohttp/streams.py", line 392, in readany
await self._wait("readany")
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/aiohttp/streams.py", line 306, in _wait
await waiter
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/aiohttp/helpers.py", line 656, in __exit__
raise asyncio.TimeoutError from None
asyncio.exceptions.TimeoutError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/koush/dalle-mini/dev/seq2seq/run_seq2seq_flax.py", line 1027, in <module>
main()
File "/home/koush/dalle-mini/dev/seq2seq/run_seq2seq_flax.py", line 991, in main
for batch in tqdm(
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/tqdm/std.py", line 1180, in __iter__
for obj in iterable:
File "/home/koush/dalle-mini/dev/seq2seq/run_seq2seq_flax.py", line 376, in data_loader_streaming
for item in dataset:
File "/home/koush/datasets/src/datasets/iterable_dataset.py", line 341, in __iter__
for key, example in self._iter():
File "/home/koush/datasets/src/datasets/iterable_dataset.py", line 338, in _iter
yield from ex_iterable
File "/home/koush/datasets/src/datasets/iterable_dataset.py", line 179, in __iter__
key_examples_list = [(key, example)] + [
File "/home/koush/datasets/src/datasets/iterable_dataset.py", line 179, in <listcomp>
key_examples_list = [(key, example)] + [
File "/home/koush/datasets/src/datasets/iterable_dataset.py", line 176, in __iter__
for key, example in iterator:
File "/home/koush/datasets/src/datasets/iterable_dataset.py", line 225, in __iter__
for x in self.ex_iterable:
File "/home/koush/datasets/src/datasets/iterable_dataset.py", line 99, in __iter__
for key, example in self.generate_examples_fn(**kwargs_with_shuffled_shards):
File "/home/koush/datasets/src/datasets/iterable_dataset.py", line 287, in wrapper
for key, table in generate_tables_fn(**kwargs):
File "/home/koush/datasets/src/datasets/packaged_modules/json/json.py", line 107, in _generate_tables
batch = f.read(self.config.chunksize)
File "/home/koush/datasets/src/datasets/utils/streaming_download_manager.py", line 126, in read_with_retries
out = read(*args, **kwargs)
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/fsspec/implementations/http.py", line 572, in read
return super().read(length)
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/fsspec/spec.py", line 1533, in read
out = self.cache._fetch(self.loc, self.loc + length)
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/fsspec/caching.py", line 390, in _fetch
self.cache = self.fetcher(start, bend)
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/fsspec/asyn.py", line 91, in wrapper
return sync(self.loop, func, *args, **kwargs)
File "/home/koush/.pyenv/versions/dev/lib/python3.9/site-packages/fsspec/asyn.py", line 69, in sync
raise FSTimeoutError from return_result
fsspec.exceptions.FSTimeoutError
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.2.dev0
- Platform: Linux-5.4.0-1043-gcp-x86_64-with-glibc2.31
- Python version: 3.9.7
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/5673 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5673/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5673/comments | https://api.github.com/repos/huggingface/datasets/issues/5673/events | https://github.com/huggingface/datasets/pull/5673 | 1,641,066,352 | PR_kwDODunzps5M6wc3 | 5,673 | Pass down storage options | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> download_and_prepare is not called when streaming a dataset, so we may need to have storage_options in the DatasetBuilder.__init__ ? This way it could also be passed later to as_streaming_dataset and the StreamingDownloadManager\r\... | 2023-03-26T20:09:37Z | 2023-03-28T15:03:38Z | 2023-03-28T14:54:17Z | CONTRIBUTOR | null | 0 | {
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} | Remove implementation-specific kwargs from `file_utils.fsspec_get` and `file_utils.fsspec_head`, instead allowing them to be passed down via `storage_options`. This fixes an issue where s3fs did not recognize a timeout arg as well as fixes an issue mentioned in https://github.com/huggingface/datasets/issues/5281 by allowing users to pass down `storage_options` all the way from `datasets.load_dataset` to support implementation-specific credentials
Supports something like the following to provide credentials explicitly instead of relying on boto's methods of locating them
```
load_dataset(..., data_files=["s3://..."], storage_options={"profile": "..."})
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/1339 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1339/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1339/comments | https://api.github.com/repos/huggingface/datasets/issues/1339/events | https://github.com/huggingface/datasets/pull/1339 | 759,744,088 | MDExOlB1bGxSZXF1ZXN0NTM0Njk0NDI4 | 1,339 | hate_speech_18 initial commit | {
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"> Nice thanks !\r\n> \r\n> Can you rename the dataset folder and the dataset script name `hate_speech18` instead of `hate_speech_18` to follow the snake case convention we're using ?\r\n> \r\n> Also it looks like the dummy_data.zip file is quite big (almost 4MB).\r\n> Can you try to reduce its size ?\r\n> \r\n> To... | 2020-12-08T20:10:08Z | 2020-12-12T16:17:32Z | 2020-12-12T16:17:32Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5589 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5589/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5589/comments | https://api.github.com/repos/huggingface/datasets/issues/5589/events | https://github.com/huggingface/datasets/pull/5589 | 1,603,535,704 | PR_kwDODunzps5K9K1i | 5,589 | Revert "pass the dataset features to the IterableDataset.from_generator" | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-02-28T17:52:04Z | 2023-09-24T10:07:33Z | 2023-03-21T14:18:18Z | MEMBER | null | 0 | {
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} | This reverts commit b91070b9c09673e2e148eec458036ab6a62ac042 (temporarily)
It hurts iterable dataset performance a lot (e.g. x4 slower because it encodes+decodes images unnecessarily). I think we need to fix this before re-adding it
cc @mariosasko @Hubert-Bonisseur | {
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https://api.github.com/repos/huggingface/datasets/issues/1107 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1107/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1107/comments | https://api.github.com/repos/huggingface/datasets/issues/1107/events | https://github.com/huggingface/datasets/pull/1107 | 757,031,179 | MDExOlB1bGxSZXF1ZXN0NTMyNDc0MzMy | 1,107 | Add arsentd_lev dataset | {
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"thanks ! can you also regenerate the dataset_infos.json file please ?"
] | 2020-12-04T11:31:04Z | 2020-12-05T15:38:09Z | 2020-12-05T15:38:09Z | CONTRIBUTOR | null | 0 | {
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} | Add The Arabic Sentiment Twitter Dataset for Levantine dialect (ArSenTD-LEV)
Paper: [ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets](https://arxiv.org/abs/1906.01830)
Homepage: http://oma-project.com/ | {
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https://api.github.com/repos/huggingface/datasets/issues/4760 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4760/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4760/comments | https://api.github.com/repos/huggingface/datasets/issues/4760/events | https://github.com/huggingface/datasets/issues/4760 | 1,320,878,223 | I_kwDODunzps5OuwCP | 4,760 | Issue with offline mode | {
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"Hi @SaulLu, thanks for reporting.\r\n\r\nI think offline mode is not supported for datasets containing only data files (without any loading script). I'm having a look into this...",
"Thanks for your feedback! \r\n\r\nTo give you a little more info, if you don't set the offline mode flag, the script will load the... | 2022-07-28T12:45:14Z | 2023-10-26T13:18:33Z | null | CONTRIBUTOR | null | null | null | ## Describe the bug
I can't retrieve a cached dataset with offline mode enabled
## Steps to reproduce the bug
To reproduce my issue, first, you'll need to run a script that will cache the dataset
```python
import os
os.environ["HF_DATASETS_OFFLINE"] = "0"
import datasets
datasets.logging.set_verbosity_info()
ds_name = "SaulLu/toy_struc_dataset"
ds = datasets.load_dataset(ds_name)
print(ds)
```
then, you can try to reload it in offline mode:
```python
import os
os.environ["HF_DATASETS_OFFLINE"] = "1"
import datasets
datasets.logging.set_verbosity_info()
ds_name = "SaulLu/toy_struc_dataset"
ds = datasets.load_dataset(ds_name)
print(ds)
```
## Expected results
I would have expected the 2nd snippet not to return any errors
## Actual results
The 2nd snippet returns:
```
Traceback (most recent call last):
File "/home/lucile_huggingface_co/sandbox/evaluate/test_cache_datasets.py", line 8, in <module>
ds = datasets.load_dataset(ds_name)
File "/home/lucile_huggingface_co/anaconda3/envs/evaluate-dev/lib/python3.8/site-packages/datasets/load.py", line 1723, in load_dataset
builder_instance = load_dataset_builder(
File "/home/lucile_huggingface_co/anaconda3/envs/evaluate-dev/lib/python3.8/site-packages/datasets/load.py", line 1500, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/home/lucile_huggingface_co/anaconda3/envs/evaluate-dev/lib/python3.8/site-packages/datasets/load.py", line 1241, in dataset_module_factory
raise ConnectionError(f"Couln't reach the Hugging Face Hub for dataset '{path}': {e1}") from None
ConnectionError: Couln't reach the Hugging Face Hub for dataset 'SaulLu/toy_struc_dataset': Offline mode is enabled.
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.4.0
- Platform: Linux-4.19.0-21-cloud-amd64-x86_64-with-glibc2.17
- Python version: 3.8.13
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
Maybe I'm misunderstanding something in the use of the offline mode (see [doc](https://huggingface.co/docs/datasets/v2.4.0/en/loading#offline)), is that the case?
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https://api.github.com/repos/huggingface/datasets/issues/613 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/613/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/613/comments | https://api.github.com/repos/huggingface/datasets/issues/613/events | https://github.com/huggingface/datasets/pull/613 | 699,117,070 | MDExOlB1bGxSZXF1ZXN0NDg0ODkyMTUx | 613 | Add CoNLL-2003 shared task dataset | {
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"I think we should somewhere mention, that is the dataset in IOB2 tagging scheme, whereas the original dataset uses IOB1 :)",
"Indeed this is something we want to mention.\r\n\r\nIf would want to add more details about the IOB1->2 change, feel free to ignore my suggestions and edit the description + update the da... | 2020-09-11T10:02:30Z | 2020-10-05T10:43:05Z | 2020-09-17T10:36:38Z | CONTRIBUTOR | null | 0 | {
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} | Please consider adding CoNLL-2003 shared task dataset as it's beneficial for token classification tasks. The motivation behind this PR is the [PR](https://github.com/huggingface/transformers/pull/7041) in the transformers project. This dataset would be not only useful for the usual run-of-the-mill NER tasks but also for syntactic chunking and part-of-speech (POS) tagging. | {
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https://api.github.com/repos/huggingface/datasets/issues/6466 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6466/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6466/comments | https://api.github.com/repos/huggingface/datasets/issues/6466/events | https://github.com/huggingface/datasets/issues/6466 | 2,022,601,176 | I_kwDODunzps54jnHY | 6,466 | Can't align optional features of struct | {
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"Friendly bump, I would be happy to work on this issue once I get the go-ahead from the dev team. "
] | 2023-12-03T15:57:07Z | 2023-12-11T14:38:34Z | null | CONTRIBUTOR | null | null | null | ### Describe the bug
Hello!
I'm currently experiencing an issue where I can't concatenate datasets if an inner field of a Feature is Optional.
I have a column named `speaker`, and this holds some information about a speaker.
```python
@dataclass
class Speaker:
name: str
email: Optional[str]
```
If I have two datasets, one happens to have `email` always None, then I get `The features can't be aligned because the key email of features`
### Steps to reproduce the bug
You can run the following script:
```python
ds = Dataset.from_dict({'speaker': [{'name': 'Ben', 'email': None}]})
ds2 = Dataset.from_dict({'speaker': [{'name': 'Fred', 'email': 'abc@aol.com'}]})
concatenate_datasets([ds, ds2])
>>>The features can't be aligned because the key speaker of features {'speaker': {'email': Value(dtype='string', id=None), 'name': Value(dtype='string', id=None)}} has unexpected type - {'email': Value(dtype='string', id=None), 'name': Value(dtype='string', id=None)} (expected either {'email': Value(dtype='null', id=None), 'name': Value(dtype='string', id=None)} or Value("null").
```
### Expected behavior
I think this should work; if two top-level columns were in the same situation it would properly cast to `string`.
```python
ds = Dataset.from_dict({'email': [None, None]})
ds2 = Dataset.from_dict({'email': ['abc@aol.com', 'one@yahoo.com']})
concatenate_datasets([ds, ds2])
>>> # Works!
```
### Environment info
- `datasets` version: 2.15.1.dev0
- Platform: Linux-5.15.0-89-generic-x86_64-with-glibc2.35
- Python version: 3.9.13
- `huggingface_hub` version: 0.19.4
- PyArrow version: 9.0.0
- Pandas version: 1.4.4
- `fsspec` version: 2023.6.0
I would be happy to fix this issue. | {
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} | Updated user permissions based on running user's umask. Let me know if `0o666` is looking good or should I change it to `~umask` only (to give execute permissions as well) | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Are you sure it's safe to remove? https://github.com/huggingface/datasets/pull/3866",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benc... | 2023-03-03T15:46:31Z | 2023-03-03T21:57:18Z | 2023-03-03T21:50:17Z | CONTRIBUTOR | null | 0 | {
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} | This pull request adds HANS missing information: the sentence parses, as well as the heuristic category. | {
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https://api.github.com/repos/huggingface/datasets/issues/5089 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5089/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5089/comments | https://api.github.com/repos/huggingface/datasets/issues/5089/events | https://github.com/huggingface/datasets/issues/5089 | 1,400,788,486 | I_kwDODunzps5TflYG | 5,089 | Resume failed process | {
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] | open | false | null | [] | null | [] | 2022-10-07T08:07:03Z | 2022-10-07T08:07:03Z | null | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
When a process (`map`, `filter`, etc.) crashes part-way through, you lose all progress.
**Describe the solution you'd like**
It would be good if the cache reflected the partial progress, so that after we restart the script, the process can restart where it left off.
**Describe alternatives you've considered**
Doing processing outside of `datasets`, by writing the dataset to json files and building a restart mechanism myself.
**Additional context**
N/A
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"I'm having the same issue，Can you tell me how to solve it？",
"I have the same issue, can you tell me how to solve it? Thanks"
] | 2022-06-08T13:59:20Z | 2023-07-28T08:12:22Z | 2022-06-08T14:41:00Z | NONE | null | null | null | ## Describe the bug
I have piped install datasets, but this package doesn't have these attributes: load_dataset, load_metric.
## Environment info
- `datasets` version: 1.9.0
- Platform: Linux-5.13.0-44-generic-x86_64-with-debian-bullseye-sid
- Python version: 3.6.13
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/6288 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6288/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6288/comments | https://api.github.com/repos/huggingface/datasets/issues/6288/events | https://github.com/huggingface/datasets/issues/6288 | 1,935,005,457 | I_kwDODunzps5zVdcR | 6,288 | Dataset.from_pandas with a DataFrame of PIL.Images | {
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"A duplicate of https://github.com/huggingface/datasets/issues/4796.\r\n\r\nWe could get this for free by implementing the `Image` feature as an extension type, as shown in [this](https://colab.research.google.com/drive/1Uzm_tXVpGTwbzleDConWcNjacwO1yxE4?usp=sharing) Colab (example with UUIDs).\r\n",
"+1 to this\r... | 2023-10-10T10:29:16Z | 2023-10-20T18:23:05Z | null | MEMBER | null | null | null | Currently type inference doesn't know what to do with a Pandas Series of PIL.Image objects, though it would be nice to get a Dataset with the Image type this way | {
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https://api.github.com/repos/huggingface/datasets/issues/5289 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5289/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5289/comments | https://api.github.com/repos/huggingface/datasets/issues/5289/events | https://github.com/huggingface/datasets/pull/5289 | 1,462,543,139 | PR_kwDODunzps5Dmrk9 | 5,289 | Added support for JXL images. | {
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"I'm fine with the addition of jxl in the list of known image extensions, this way users that have the plugin can work with their JXL datasets. WDYT @mariosasko ?",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5289). All of your documentation changes will be reflected on ... | 2022-11-23T23:16:33Z | 2022-11-29T18:49:46Z | null | NONE | null | 0 | {
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} | JPEG-XL is the most advanced of the next-generation of image codecs, supporting both lossless and lossy files — with better compression and quality than PNG and JPG respectively. It has reduced the disk sizes and bandwidth required for many of the datasets I use.
Pillow does not yet support JXL, but there's a plugin as a separate Python library that does (`pip install jxlpy`), and I've tested that this change works as expected when the plugin is imported.
Dataset used for testing, you must `git pull` as loading it from Python won't work until `datasets-server` is also changed to support JXL files:
https://huggingface.co/datasets/texturedesign/td01_natural-ground-textures
The case where the plugin is not imported first raises an error:
```
PIL.UnidentifiedImageError: cannot identify image file 'td01/train/set01/01_145523.jxl'
```
In order to enable support for JXL even before pillow supports this, should this exception be handled with a better error message? I'd expect/hope JXL support to follow in one of the pillow quarterly releases in the next 6-9 months. | {
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https://api.github.com/repos/huggingface/datasets/issues/5009 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5009/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5009/comments | https://api.github.com/repos/huggingface/datasets/issues/5009/events | https://github.com/huggingface/datasets/issues/5009 | 1,381,194,067 | I_kwDODunzps5SU1lT | 5,009 | Error loading StonyBrookNLP/tellmewhy dataset from hub even though local copy loads correctly | {
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"I think this is because some columns are mostly empty lists. In particular the train and validation splits only have empty lists for `val_ann`. Therefore the type inference doesn't know which type is inside (or it would have to scan the other splits first before knowing).\r\n\r\nYou can fix that by specifying the ... | 2022-09-21T16:23:06Z | 2022-09-29T13:07:29Z | 2022-09-29T13:07:29Z | NONE | null | null | null | ## Describe the bug
I have added a new dataset with the identifier `StonyBrookNLP/tellmewhy` to the hub. When I load the individual files using my local copy using `dataset = datasets.load_dataset("json", data_files="data/train.jsonl")`, it loads the dataset correctly. However, when I try to load it from the hub, I get an error (pasted below). Additionally, `dataset = datasets.load_dataset("json", data_dir="data/")` throws the same error.
## Steps to reproduce the bug
```python
dataset = datasets.load_dataset('StonyBrookNLP/tellmewhy')
```
## Expected results
Successfully load the `StonyBrookNLP/tellmewhy` dataset.
## Actual results
```
Using custom data configuration StonyBrookNLP--tellmewhy-82712924092694ff
Downloading and preparing dataset json/StonyBrookNLP--tellmewhy to /home/yklal95/.cache/huggingface/datasets/StonyBrookNLP___json/StonyBrookNLP--tellmewhy-82712924092694ff/0.0.0/a3e658c4731e59120d44081ac10bf85dc7e1388126b92338344ce9661907f253...
Downloading data files: 100%|██████████████████████████████| 3/3 [00:00<00:00, 957.46it/s]
Extracting data files: 100%|███████████████████████████████| 3/3 [00:00<00:00, 299.14it/s]
Traceback (most recent call last):
File "/home/yklal95/tmw-generalization/src/load_datasets.py", line 17, in <module>
main(args)
File "/home/yklal95/tmw-generalization/src/load_datasets.py", line 11, in main
dataset = datasets.load_dataset(args.dataset_name)
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/load.py", line 1746, in load_dataset
builder_instance.download_and_prepare(
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 704, in download_and_prepare
self._download_and_prepare(
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 793, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 1277, in _prepare_split
writer.write_table(table)
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/arrow_writer.py", line 524, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 2005, in table_cast
return cast_table_to_schema(table, schema)
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1969, in cast_table_to_schema
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1969, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1681, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1681, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1822, in cast_array_to_feature
casted_values = _c(array.values, feature.feature)
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1683, in wrapper
return func(array, *args, **kwargs)
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1853, in cast_array_to_feature
return array_cast(array, feature(), allow_number_to_str=allow_number_to_str)
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1683, in wrapper
return func(array, *args, **kwargs)
File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1761, in array_cast
raise TypeError(f"Couldn't cast array of type {array.type} to {pa_type}")
TypeError: Couldn't cast array of type int64 to null
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.4.0
- Platform: Linux-4.15.0-121-generic-x86_64-with-glibc2.27
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.5.0
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https://api.github.com/repos/huggingface/datasets/issues/392 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/392/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/392/comments | https://api.github.com/repos/huggingface/datasets/issues/392/events | https://github.com/huggingface/datasets/pull/392 | 657,313,738 | MDExOlB1bGxSZXF1ZXN0NDQ5NDUwOTkx | 392 | Style change detection | {
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} | Another [PAN task](https://pan.webis.de/clef20/pan20-web/style-change-detection.html). This time about identifying when the style/author changes in documents.
- There's the possibility of adding the [PAN19](https://zenodo.org/record/3577602) and PAN18 style change detection tasks too (these are datasets whose labels are a subset of PAN20's). These would probably make more sense as separate datasets (like wmt is now)
- I've converted the integer 0,1 values to a boolean
- Using manually downloaded data again. This might be changed at some point following the discussion in https://github.com/huggingface/nlp/pull/349. | {
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https://api.github.com/repos/huggingface/datasets/issues/5913 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5913/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5913/comments | https://api.github.com/repos/huggingface/datasets/issues/5913/events | https://github.com/huggingface/datasets/issues/5913 | 1,731,427,484 | I_kwDODunzps5nM3yc | 5,913 | I tried to load a custom dataset using the following statement: dataset = load_dataset('json', data_files=data_files). The dataset contains 50 million text-image pairs, but an error occurred. | {
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"Thanks for reporting, @cjt222.\r\n\r\nWhat is the structure of your JSON files. Please note that it is normally simpler if the data file format is JSON-Lines instead. ",
"> Thanks for reporting, @cjt222.\r\n> \r\n> What is the structure of your JSON files. Please note that it is normally simpler if the data file... | 2023-05-30T02:55:26Z | 2023-07-24T12:00:38Z | 2023-07-24T12:00:38Z | NONE | null | null | null | ### Describe the bug
File "/home/kas/.conda/envs/diffusers/lib/python3.7/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
Downloading and preparing dataset json/default to /home/kas/diffusers/examples/dreambooth/cache_data/datasets/json/default-acf423d8c6ef99d0/0.0.0/e347ab1c932092252e717ff3f949105a4dd28b27e842dd53157d2f72e276c2e4...
Downloading data files: 0%| | 0/1 [00:00<?, ?it/s] Downloading data files: 100%|██████████| 1/1 [00:00<00:00, 84.35it/s]
Extracting data files: 0%| | 0/1 [00:00<?, ?it/s] for _, table in generator:
File "/home/kas/.conda/envs/diffusers/lib/python3.7/site-packages/datasets/packaged_modules/json/json.py", line 114, in _generate_tables
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
File "pyarrow/_json.pyx", line 258, in pyarrow._json.read_json
Extracting data files: 100%|██████████| 1/1 [00:00<00:00, 27.72it/s]
Generating train split: 0 examples [00:00, ? examples/s] File "pyarrow/error.pxi", line 144, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 125, in pyarrow.lib.check_status
pyarrow.lib.ArrowCapacityError: array cannot contain more than 2147483646 bytes, have 2390448764
### Steps to reproduce the bug
1、data_files = ["1.json", "2.json", "3.json"]
2、dataset = load_dataset('json', data_files=data_files)
### Expected behavior
Read the dataset normally.
### Environment info
- `datasets` version: 2.12.0
- Platform: Linux-4.15.0-29-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.16
- Huggingface_hub version: 0.14.1
- PyArrow version: 12.0.0
- Pandas version: 1.3.5 | {
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https://api.github.com/repos/huggingface/datasets/issues/1385 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1385/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1385/comments | https://api.github.com/repos/huggingface/datasets/issues/1385/events | https://github.com/huggingface/datasets/pull/1385 | 760,351,405 | MDExOlB1bGxSZXF1ZXN0NTM1MTk3Nzk5 | 1,385 | add best2009 | {
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} | `best2009` is a Thai word-tokenization dataset from encyclopedia, novels, news and articles by [NECTEC](https://www.nectec.or.th/) (148,995/2,252 lines of train/test). It was created for [BEST 2010: Word Tokenization Competition](https://thailang.nectec.or.th/archive/indexa290.html?q=node/10). The test set answers are not provided publicly. | {
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https://api.github.com/repos/huggingface/datasets/issues/3348 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3348/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3348/comments | https://api.github.com/repos/huggingface/datasets/issues/3348/events | https://github.com/huggingface/datasets/pull/3348 | 1,067,831,113 | PR_kwDODunzps4vOBOQ | 3,348 | BLEURT: Match key names to correspond with filename | {
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"Thanks for the suggestion! I think the current checked-in `CHECKPOINT_URLS` is already not working. I believe anyone who tried using the new ckpts (`BLEURT-20-X`) can't unless this fix is in. The zip file from bleurt side unzips to directory name matching the filename (capitalized for new ones). For example withou... | 2021-12-01T01:01:18Z | 2021-12-07T16:06:57Z | 2021-12-07T16:06:57Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3714 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3714/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3714/comments | https://api.github.com/repos/huggingface/datasets/issues/3714/events | https://github.com/huggingface/datasets/issues/3714 | 1,136,105,530 | I_kwDODunzps5Dt5g6 | 3,714 | tatoeba_mt: File not found error and key error | {
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"Looks like I solved my problems ..."
] | 2022-02-13T16:35:45Z | 2022-02-13T20:44:04Z | 2022-02-13T20:44:04Z | NONE | null | null | null | ## Dataset viewer issue for 'tatoeba_mt'
**Link:** https://huggingface.co/datasets/Helsinki-NLP/tatoeba_mt
My data loader script does not seem to work.
The files are part of the local repository but cannot be found. An example where it should work is the subset for "afr-eng".
Another problem is that I do not have validation data for all subsets and I don't know how to properly check whether validation exists in the configuration before I try to download it. An example is the subset for "afr-deu".
Am I the one who added this dataset ? Yes
| {
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https://api.github.com/repos/huggingface/datasets/issues/6486 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6486/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6486/comments | https://api.github.com/repos/huggingface/datasets/issues/6486/events | https://github.com/huggingface/datasets/pull/6486 | 2,035,206,206 | PR_kwDODunzps5hqCSc | 6,486 | Fix docs phrasing about supported formats when sharing a dataset | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6486). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2023-12-11T09:21:22Z | 2023-12-13T14:21:29Z | 2023-12-13T14:15:21Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4613 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4613/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4613/comments | https://api.github.com/repos/huggingface/datasets/issues/4613/events | https://github.com/huggingface/datasets/pull/4613 | 1,291,181,193 | PR_kwDODunzps46skd6 | 4,613 | Align/fix license metadata info | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thank you thank you! Let's merge and pray? 😱 ",
"I just need to add `license_details` to the validator and yup we can merge"
] | 2022-07-01T09:50:50Z | 2022-07-01T12:53:57Z | 2022-07-01T12:42:47Z | MEMBER | null | 0 | {
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} | fix bad "other-*" licenses and add the corresponding "license_details" when relevant | {
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https://api.github.com/repos/huggingface/datasets/issues/5668 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5668/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5668/comments | https://api.github.com/repos/huggingface/datasets/issues/5668/events | https://github.com/huggingface/datasets/pull/5668 | 1,638,018,598 | PR_kwDODunzps5MwuIp | 5,668 | Support for downloading only provided split | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5668). All of your documentation changes will be reflected on that endpoint.",
"My previous comment didn't create the retro-link in the PR. I write it here again.\r\n\r\nYou can check the context and the discussions we had abou... | 2023-03-23T17:53:39Z | 2023-03-24T06:43:14Z | null | CONTRIBUTOR | null | 1 | {
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} | We can pass split to `_split_generators()`.
But I'm not sure if it's possible to solve cache issues, mostly with `dataset_info.json` | {
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https://api.github.com/repos/huggingface/datasets/issues/4913 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4913/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4913/comments | https://api.github.com/repos/huggingface/datasets/issues/4913/events | https://github.com/huggingface/datasets/pull/4913 | 1,355,232,007 | PR_kwDODunzps4-BP00 | 4,913 | Add license and citation information to cosmos_qa dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-30T06:23:19Z | 2022-08-30T09:49:31Z | 2022-08-30T09:47:35Z | MEMBER | null | 0 | {
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} | This PR adds the license information to `cosmos_qa` dataset, once reported via email by Yejin Choi, the dataset is licensed under CC BY 4.0.
This PR also updates the citation information. | {
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https://api.github.com/repos/huggingface/datasets/issues/5572 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5572/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5572/comments | https://api.github.com/repos/huggingface/datasets/issues/5572/events | https://github.com/huggingface/datasets/issues/5572 | 1,597,257,624 | I_kwDODunzps5fNDeY | 5,572 | Datasets 2.10.0 does not reuse the dataset cache | {
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download_mode="reuse_dataset_if_exists" will always consider that a dataset doesn't exist.
Specifically, upon losing an internet connection trying to load a dataset for a second time in ten seconds, a connection error results, showing a breakpoint of:
```
File ~/jupyterlab/.direnv/python-3.9.6/lib/python3.9/site-packages/datasets/load.py:1174, in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)
1165 except Exception as e: # noqa: catch any exception of hf_hub and consider that the dataset doesn't exist
1166 if isinstance(
1167 e,
1168 (
(...)
1172 ),
1173 ):
-> 1174 raise ConnectionError(f"Couldn't reach '{path}' on the Hub ({type(e).__name__})")
1175 elif "404" in str(e):
1176 msg = f"Dataset '{path}' doesn't exist on the Hub"
ConnectionError: Couldn't reach 'lsb/tenk' on the Hub (ConnectionError)
```
This has been around since at least v2.0.
### Steps to reproduce the bug
```
from datasets import load_dataset
import numpy as np
tenk = load_dataset("lsb/tenk") # ten thousand integers
print(np.average(tenk['train']['a'])) # prints 4999.5
### now disconnect your internet
tenk_too = load_dataset("lsb/tenk", download_mode="reuse_dataset_if_exists")
# Raises ConnectionError: Couldn't reach 'lsb/tenk' on the Hub (ConnectionError)
```
### Expected behavior
I expected that I would be able to reuse the dataset I just downloaded.
### Environment info
- `datasets` version: 2.10.0
- Platform: macOS-13.1-arm64-arm-64bit
- Python version: 3.9.6
- PyArrow version: 7.0.0
- Pandas version: 1.5.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/1913 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1913/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1913/comments | https://api.github.com/repos/huggingface/datasets/issues/1913/events | https://github.com/huggingface/datasets/pull/1913 | 812,127,307 | MDExOlB1bGxSZXF1ZXN0NTc2NTQ0NjQw | 1,913 | Add keep_linebreaks parameter to text loader | {
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"Just so I understand how it can be used in practice, do you have an example showing how to load a text dataset with this option?",
"Sure ! Here is an example:\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nload_dataset(\"text\", keep_linebreaks=True, data_files=...)\r\n```\r\n\r\nI'll update the docume... | 2021-02-19T15:43:45Z | 2021-02-19T18:36:12Z | 2021-02-19T18:36:11Z | MEMBER | null | 0 | {
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} | As asked in #870 and https://github.com/huggingface/transformers/issues/10269 there should be a parameter to keep the linebreaks when loading a text dataset.
cc @sgugger @jncasey | {
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https://api.github.com/repos/huggingface/datasets/issues/1720 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1720/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1720/comments | https://api.github.com/repos/huggingface/datasets/issues/1720/events | https://github.com/huggingface/datasets/pull/1720 | 783,721,833 | MDExOlB1bGxSZXF1ZXN0NTUzMDM0MzYx | 1,720 | Adding the NorNE dataset for NER | {
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"Quick question, @lhoestq. In this specific dataset, two special types `GPE_LOC` and `GPE_ORG` can easily be altered depending on the task, choosing either the more general `GPE` tag or the more specific `LOC`/`ORG` tags, conflating them with the other annotations of the same type. However, I have not found an easy... | 2021-01-11T21:34:13Z | 2021-03-31T14:23:49Z | 2021-03-31T14:13:17Z | CONTRIBUTOR | null | 0 | {
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} | NorNE is a manually annotated corpus of named entities which extends the annotation of the existing Norwegian Dependency Treebank. Comprising both of the official standards of written Norwegian (Bokmål and Nynorsk), the corpus contains around 600,000 tokens and annotates a rich set of entity types including persons, organizations, locations, geo-political entities, products, and events, in addition to a class corresponding to nominals derived from names. | {
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https://api.github.com/repos/huggingface/datasets/issues/582 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/582/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/582/comments | https://api.github.com/repos/huggingface/datasets/issues/582/events | https://github.com/huggingface/datasets/issues/582 | 695,126,456 | MDU6SXNzdWU2OTUxMjY0NTY= | 582 | Allow for PathLike objects | {
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} | [] | closed | false | null | [] | null | [] | 2020-09-07T13:54:51Z | 2020-09-08T07:45:17Z | 2020-09-08T07:45:17Z | CONTRIBUTOR | null | null | null | Using PathLike objects as input for `load_dataset` does not seem to work. The following will throw an error.
```python
files = list(Path(r"D:\corpora\yourcorpus").glob("*.txt"))
dataset = load_dataset("text", data_files=files)
```
Traceback:
```
Traceback (most recent call last):
File "C:/dev/python/dutch-simplification/main.py", line 7, in <module>
dataset = load_dataset("text", data_files=files)
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\load.py", line 548, in load_dataset
builder_instance.download_and_prepare(
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\builder.py", line 470, in download_and_prepare
self._save_info()
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\builder.py", line 564, in _save_info
self.info.write_to_directory(self._cache_dir)
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\info.py", line 149, in write_to_directory
self._dump_info(f)
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\info.py", line 156, in _dump_info
file.write(json.dumps(asdict(self)).encode("utf-8"))
File "c:\users\bramv\appdata\local\programs\python\python38\lib\json\__init__.py", line 231, in dumps
return _default_encoder.encode(obj)
File "c:\users\bramv\appdata\local\programs\python\python38\lib\json\encoder.py", line 199, in encode
chunks = self.iterencode(o, _one_shot=True)
File "c:\users\bramv\appdata\local\programs\python\python38\lib\json\encoder.py", line 257, in iterencode
return _iterencode(o, 0)
TypeError: keys must be str, int, float, bool or None, not WindowsPath
```
We have to cast to a string explicitly to make this work. It would be nicer if we could actually use PathLike objects.
```python
files = [str(f) for f in Path(r"D:\corpora\wablieft").glob("*.txt")]
```
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https://api.github.com/repos/huggingface/datasets/issues/4582 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4582/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4582/comments | https://api.github.com/repos/huggingface/datasets/issues/4582/events | https://github.com/huggingface/datasets/pull/4582 | 1,286,517,060 | PR_kwDODunzps46dC59 | 4,582 | add_column should preserve _indexes | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4582). All of your documentation changes will be reflected on that endpoint."
] | 2022-06-27T22:35:47Z | 2022-07-06T15:19:54Z | null | CONTRIBUTOR | null | 0 | {
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} | https://github.com/huggingface/datasets/issues/3769#issuecomment-1167146126
doing `.add_column("x",x_data)` also removed any `_indexes` on the dataset, decided this shouldn't be the case.
This was because `add_column` was creating a new `Dataset(...)` and wasn't possible to pass indexes on init.
with this PR now can pass 'indexes' on init through `IndexableMixin`
- [x] Added test | {
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https://api.github.com/repos/huggingface/datasets/issues/406 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/406/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/406/comments | https://api.github.com/repos/huggingface/datasets/issues/406/events | https://github.com/huggingface/datasets/issues/406 | 658,581,764 | MDU6SXNzdWU2NTg1ODE3NjQ= | 406 | Faster Shuffling? | {
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"I think the slowness here probably come from the fact that we are copying from and to python.\r\n\r\n@lhoestq for all the `select`-based methods I think we should stay in Arrow format and update the writer so that it can accept Arrow tables or batches as well. What do you think?",
"> @lhoestq for all the `select... | 2020-07-16T21:21:53Z | 2023-08-16T09:52:39Z | 2020-09-07T14:45:25Z | CONTRIBUTOR | null | null | null | Consider shuffling bookcorpus:
```
dataset = nlp.load_dataset('bookcorpus', split='train')
dataset.shuffle()
```
According to tqdm, this will take around 2.5 hours on my machine to complete (even with the faster version of select from #405). I've also tried with `keep_in_memory=True` and `writer_batch_size=1000`.
But I can also just write the lines to a text file:
```
batch_size = 100000
with open('tmp.txt', 'w+') as out_f:
for i in tqdm(range(0, len(dataset), batch_size)):
batch = dataset[i:i+batch_size]['text']
print("\n".join(batch), file=out_f)
```
Which completes in a couple minutes, followed by `shuf tmp.txt > tmp2.txt` which completes in under a minute. And finally,
```
dataset = nlp.load_dataset('text', data_files='tmp2.txt')
```
Which completes in under 10 minutes. I read up on Apache Arrow this morning, and it seems like the columnar data format is not especially well-suited to shuffling rows, since moving items around requires a lot of book-keeping.
Is shuffle inherently slow, or am I just using it wrong? And if it is slow, would it make sense to try converting the data to a row-based format on disk and then shuffling? (Instead of calling select with a random permutation, as is currently done.) | {
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https://api.github.com/repos/huggingface/datasets/issues/6504 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6504/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6504/comments | https://api.github.com/repos/huggingface/datasets/issues/6504/events | https://github.com/huggingface/datasets/issues/6504 | 2,044,541,154 | I_kwDODunzps553Tji | 6,504 | Error Pushing to Hub | {
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} | [] | closed | false | null | [] | null | [] | 2023-12-16T01:05:22Z | 2023-12-16T06:20:53Z | 2023-12-16T06:20:53Z | NONE | null | null | null | ### Describe the bug
Error when trying to push a dataset in a special format to hub
### Steps to reproduce the bug
```
import datasets
from datasets import Dataset
dataset_dict = {
"filename": ["apple", "banana"],
"token": [[[1,2],[3,4]],[[1,2],[3,4]]],
"label": [0, 1],
}
dataset = Dataset.from_dict(dataset_dict)
dataset = dataset.cast_column("token", datasets.features.features.Array2D(shape=(2, 2),dtype="int16"))
dataset.push_to_hub("SequenceModel/imagenet_val_256")
```
Error:
```
...
ConstructorError: could not determine a constructor for the tag 'tag:yaml.org,2002:python/tuple'
in "<unicode string>", line 8, column 16:
shape: !!python/tuple
^
```
### Expected behavior
Dataset being pushed to hub
### Environment info
- `datasets` version: 2.15.0
- Platform: Linux-5.19.0-1022-gcp-x86_64-with-glibc2.35
- Python version: 3.11.5
- `huggingface_hub` version: 0.19.4
- PyArrow version: 14.0.1
- Pandas version: 2.1.4
- `fsspec` version: 2023.10.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3864 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3864/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3864/comments | https://api.github.com/repos/huggingface/datasets/issues/3864/events | https://github.com/huggingface/datasets/pull/3864 | 1,162,804,942 | PR_kwDODunzps40HQZ_ | 3,864 | Update image dataset tags | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3864). All of your documentation changes will be reflected on that endpoint."
] | 2022-03-08T15:36:32Z | 2022-03-08T17:04:47Z | 2022-03-08T17:04:46Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2266 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2266/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2266/comments | https://api.github.com/repos/huggingface/datasets/issues/2266/events | https://github.com/huggingface/datasets/pull/2266 | 867,864,353 | MDExOlB1bGxSZXF1ZXN0NjIzNDY1OTI5 | 2,266 | Make tests run faster | {
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"LOL, I was also working on something similar 😅. I'm gonna have a look!!!",
"Sorry I didn't know you were also working on it ^^'\r\nAnd yes I 100% agree with you on the points you mentioned. We should definitely improve the coverage. It would be nice to have a clearer separation to know which tests in the suite ... | 2021-04-26T15:55:40Z | 2021-04-29T10:00:13Z | 2021-04-29T10:00:04Z | MEMBER | null | 0 | {
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} | From 7min to 2min to run pytest.
Ideally we should keep the whole CI run time below 10min.
In this PR I removed the remote tests that were never used.
I also replaced nested parametrized tests with unit tests.
This makes me think that we could still add more high level tests to check for a few combinations of parameters (but not all of them since there are too many of them).
Let me know what you think
Finally in another PR we can also separate in two circleci jobs:
- the tests of the code code of the lib
- the tests of the all the dataset/metric scripts. | {
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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 | {
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https://api.github.com/repos/huggingface/datasets/issues/1276 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1276/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1276/comments | https://api.github.com/repos/huggingface/datasets/issues/1276/events | https://github.com/huggingface/datasets/pull/1276 | 758,965,936 | MDExOlB1bGxSZXF1ZXN0NTM0MDQyODYy | 1,276 | add One Million Posts Corpus | {
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"merging since the CI is fixed on master"
] | 2020-12-08T00:50:08Z | 2020-12-11T18:28:18Z | 2020-12-11T18:28:18Z | CONTRIBUTOR | null | 0 | {
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} | - **Name:** One Million Posts Corpus
- **Description:** The “One Million Posts” corpus is an annotated data set consisting of user comments posted to an Austrian newspaper website (in German language).
- **Paper:** https://dl.acm.org/doi/10.1145/3077136.3080711
- **Data:** https://github.com/OFAI/million-post-corpus
- **Motivation:** Big German (real-life) dataset containing different annotations around forum moderation with expert annotations.
### Checkbox
- [X] Create the dataset script `/datasets/my_dataset/my_dataset.py` using the template
- [X] Fill the `_DESCRIPTION` and `_CITATION` variables
- [X] Implement `_infos()`, `_split_generators()` and `_generate_examples()`
- [X] Make sure that the `BUILDER_CONFIGS` class attribute is filled with the different configurations of the dataset and that the `BUILDER_CONFIG_CLASS` is specified if there is a custom config class.
- [X] Generate the metadata file `dataset_infos.json` for all configurations
- [X] Generate the dummy data `dummy_data.zip` files to have the dataset script tested and that they don't weigh too much (<50KB)
- [X] Add the dataset card `README.md` using the template : fill the tags and the various paragraphs
- [X] Both tests for the real data and the dummy data pass.
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