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https://api.github.com/repos/huggingface/datasets/issues/3298 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3298/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3298/comments | https://api.github.com/repos/huggingface/datasets/issues/3298/events | https://github.com/huggingface/datasets/issues/3298 | 1,058,420,201 | I_kwDODunzps4_FjXp | 3,298 | Agnews dataset viewer is not working | {
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"Hi ! Thanks for reporting\r\nWe've already fixed the code that generates the preview for this dataset, we'll release the fix soon :)",
"Hi @lhoestq, thanks for your feedback!",
"Fixed in the viewer.\r\n\r\nhttps://huggingface.co/datasets/ag_news"
] | 2021-11-19T11:18:59Z | 2021-12-21T16:24:05Z | 2021-12-21T16:24:05Z | NONE | null | null | null | ## Dataset viewer issue for '*name of the dataset*'
**Link:** https://huggingface.co/datasets/ag_news
Hi there, the `ag_news` dataset viewer is not working.
Am I the one who added this dataset? No
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"Thanks Quentin !"
] | 2020-12-09T08:57:10Z | 2020-12-09T18:16:20Z | 2020-12-09T18:13:48Z | MEMBER | null | 0 | {
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http://opus.nlpl.eu/infopankki-v1.php | {
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"cc @anton-l @albertvillanova ",
"Thanks for reporting, @patrickvonplaten.\r\n\r\nI think the issue is related to mp3 resampling, not to `cast_column`.\r\n\r\nYou can check that `cast_column` works OK with non-mp3 audio files:\r\n```python\r\nfrom datasets import load_dataset\r\nimport datasets\r\nds = load_datas... | 2021-10-15T13:36:58Z | 2023-04-07T09:43:20Z | 2021-10-15T15:38:30Z | MEMBER | null | null | null | ## Describe the bug
After changing the sampling rate automatic decoding fails.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import datasets
ds = load_dataset("common_voice", "ab", split="train")
ds = ds.cast_column("audio", datasets.features.Audio(sampling_rate=16_000))
print(ds[0]["audio"]) # <- this fails currently
```
yields:
```
TypeError: forward() takes 2 positional arguments but 4 were given
```
## Expected results
no failure
## Actual results
Specify the actual results or traceback.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 1.13.2 (master)
- Platform: Linux-5.11.0-1019-aws-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 5.0.0
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-05-23T07:19:49Z | 2022-05-23T10:38:26Z | 2022-05-23T10:29:55Z | MEMBER | null | 0 | {
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} | This PR fixes some URLs.
Fix #4386. | {
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"This has been fixed by https://github.com/huggingface/datasets/pull/2900\r\nWe're doing a new release 1.12 today to make the fix available :)"
] | 2021-09-10T14:11:43Z | 2021-09-13T14:18:13Z | 2021-09-13T14:17:42Z | MEMBER | null | null | null | There is an error when encoding a dataset with None objects with a Sequence feature
To reproduce:
```python
from datasets import Dataset, Features, Value, Sequence
data = {"a": [[0], None]}
features = Features({"a": Sequence(Value("int32"))})
dataset = Dataset.from_dict(data, features=features)
```
raises
```python
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-24-40add67f8751> in <module>
2 data = {"a": [[0], None]}
3 features = Features({"a": Sequence(Value("int32"))})
----> 4 dataset = Dataset.from_dict(data, features=features)
[...]
~/datasets/features.py in encode_nested_example(schema, obj)
888 if isinstance(obj, str): # don't interpret a string as a list
889 raise ValueError("Got a string but expected a list instead: '{}'".format(obj))
--> 890 return [encode_nested_example(schema.feature, o) for o in obj]
891 # Object with special encoding:
892 # ClassLabel will convert from string to int, TranslationVariableLanguages does some checks
TypeError: 'NoneType' object is not iterable
```
Instead, if should run without error, as if the `features` were not passed | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3876). All of your documentation changes will be reflected on that endpoint."
] | 2022-03-09T14:54:33Z | 2022-03-10T08:47:00Z | 2022-03-10T08:46:59Z | MEMBER | null | 0 | {
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Before the fix, it was set to `bool` (default to `False`).
Also set properly its default value in all public functions. | {
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"I don't know what happened, my first commit passed on all checks, but after just a README.md update one of the scripts failed, is it normal? 😕 ",
"Looks like a flaky connection error, I've launched a re-run, it should be fine :)",
"The RemoteDatasetTest error in the CI is just a connection error, we can ignor... | 2020-12-09T00:06:38Z | 2020-12-10T14:11:33Z | 2020-12-10T14:11:33Z | CONTRIBUTOR | null | 0 | {
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"Just note that docstrings injected from PyArrow do not follow the same convention for formatting types in `Args` or `Returns` as we do... Not a big problem, anyway! 😄 "
] | 2021-03-31T14:36:10Z | 2021-04-01T16:46:30Z | 2021-03-31T15:42:08Z | MEMBER | null | 0 | {
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cc @albertvillanova | {
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https://api.github.com/repos/huggingface/datasets/issues/5665 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5665/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5665/comments | https://api.github.com/repos/huggingface/datasets/issues/5665/events | https://github.com/huggingface/datasets/issues/5665 | 1,637,193,648 | I_kwDODunzps5hlZew | 5,665 | Feature request: IterableDataset.push_to_hub | {
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] | open | false | null | [] | null | [] | 2023-03-23T09:53:04Z | 2023-03-23T09:53:16Z | null | CONTRIBUTOR | null | null | null | ### Feature request
It'd be great to have a lazy push to hub, similar to the lazy loading we have with `IterableDataset`.
Suppose you'd like to filter [LAION](https://huggingface.co/datasets/laion/laion400m) based on certain conditions, but as LAION doesn't fit into your disk, you'd like to leverage streaming:
```
from datasets import load_dataset
dataset = load_dataset("laion/laion400m", streaming=True, split="train")
```
Then you could filter the dataset based on certain conditions:
```
filtered_dataset = dataset.filter(lambda example: example['HEIGHT'] > 400)
```
In order to persist this dataset and push it back to the hub, one currently needs to first load the entire filtered dataset on disk and then push:
```
from datasets import Dataset
Dataset.from_generator(filtered_dataset.__iter__).push_to_hub(...)
```
It would be great if we can instead lazy push to the data to the hub (basically stream the data to the hub), not being limited by our disk size:
```
filtered_dataset.push_to_hub("my-filtered-dataset")
```
### Motivation
This feature would be very useful for people that want to filter huge datasets without having to load the entire dataset or a filtered version thereof on their local disk.
### Your contribution
Happy to test out a PR :) | {
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https://api.github.com/repos/huggingface/datasets/issues/5959 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5959/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5959/comments | https://api.github.com/repos/huggingface/datasets/issues/5959/events | https://github.com/huggingface/datasets/issues/5959 | 1,757,397,507 | I_kwDODunzps5ov8ID | 5,959 | read metric glue.py from local file | {
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"Sorry, I solve this by call `evaluate.load('glue_metric.py','sst-2')`\r\n"
] | 2023-06-14T17:59:35Z | 2023-06-14T18:04:16Z | 2023-06-14T18:04:16Z | NONE | null | null | null | ### Describe the bug
Currently, The server is off-line. I am using the glue metric from the local file downloaded from the hub.
I download / cached datasets using `load_dataset('glue','sst2', cache_dir='/xxx')` to cache them and then in the off-line mode, I use `load_dataset('xxx/glue.py','sst2', cache_dir='/xxx')`. I can successfully reuse cached datasets.
My problem is about the load_metric.
When I run `load_dataset('xxx/glue_metric.py','sst2',cache_dir='/xxx')` , it returns
` File "xx/lib64/python3.9/site-packages/datasets/utils/deprecation_utils.py", line 46, in wrapper
return deprecated_function(*args, **kwargs)
File "xx//lib64/python3.9/site-packages/datasets/load.py", line 1392, in load_metric
metric = metric_cls(
TypeError: 'NoneType' object is not callable`
Thanks in advance for help!
### Steps to reproduce the bug
N/A
### Expected behavior
N/A
### Environment info
`datasets == 2.12.0` | {
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"Also this could be extended to the rest of the GitHub Action `yml` files, so let me know whether you want me to have a look into it! 🤗",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5903). All of your documentation changes will be reflected on that endpoint.",
"Maybe ... | 2023-05-26T10:46:52Z | 2023-09-07T15:52:36Z | null | CONTRIBUTOR | null | 0 | {
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} | ## What's in this PR?
As of a previous PR at #5902, I've seen that the CI was automatically trigger on any file, in that case when modifying a Jupyter Notebook (.ipynb), which IMO could be skipped, as the modification on the Jupyter Notebook has no effect/impact on the `ci.yml` outcome. So this PR controls the paths that trigger the `ci.yml` to avoid wasting resources when not needed.
## What's pending in this PR?
I would like to confirm whether this should affect both `push` and `pull_request`, since just modifications in those files won't change the `ci.yml` outcome, so maybe it's worth skipping it too in the `push` trigger. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3905). All of your documentation changes will be reflected on that endpoint.",
"I'm wondering if we should add that perplexity can be used for analyzing datasets as well",
"Otherwise, looks good! Good job, @emibaylor !"
] | 2022-03-14T12:39:40Z | 2022-03-16T19:38:56Z | 2022-03-16T19:38:56Z | CONTRIBUTOR | null | 0 | {
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Note that it is currently still missing the citation, but I plan to add it later today. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-03-30T18:08:01Z | 2022-04-01T19:02:58Z | 2022-04-01T18:57:25Z | NONE | null | 0 | {
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} | The latest s3fs version has new constrains on aiobotocore, and therefore on boto3 and botocore
This PR changes the constrains to avoid the new conflicts
In particular it pins the version of s3fs. | {
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https://api.github.com/repos/huggingface/datasets/issues/2560 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2560/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2560/comments | https://api.github.com/repos/huggingface/datasets/issues/2560/events | https://github.com/huggingface/datasets/pull/2560 | 932,143,634 | MDExOlB1bGxSZXF1ZXN0Njc5NTMyODk4 | 2,560 | fix Dataset.map when num_procs > num rows | {
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"Hi ! Thanks for fixing this :)\r\n\r\nLooks like you have tons of changes due to code formatting.\r\nWe're using `black` for this, with a custom line length. To run our code formatting, you just need to run\r\n```\r\nmake style\r\n```\r\n\r\nThen for the windows error in the CI, I'm looking into it. It's probably ... | 2021-06-29T02:24:11Z | 2021-06-29T15:00:18Z | 2021-06-29T14:53:31Z | CONTRIBUTOR | null | 0 | {
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} | closes #2470
## Testing notes
To run updated tests:
```sh
pytest tests/test_arrow_dataset.py -k "BaseDatasetTest and test_map_multiprocessing" -s
```
With Python code (to view warning):
```python
from datasets import Dataset
dataset = Dataset.from_dict({"x": ["sample"]})
print(len(dataset))
dataset.map(lambda x: x, num_proc=10)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6274 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6274/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6274/comments | https://api.github.com/repos/huggingface/datasets/issues/6274/events | https://github.com/huggingface/datasets/issues/6274 | 1,921,036,328 | I_kwDODunzps5ygLAo | 6,274 | FileNotFoundError for dataset with multiple builder config | {
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"Please tell me if the above info is not enough for solving the problem. I will then make my dataset public temporarily so that you can really reproduce the bug. "
] | 2023-10-01T23:45:56Z | 2023-10-02T20:09:38Z | 2023-10-02T20:09:38Z | NONE | null | null | null | ### Describe the bug
When there is only one config and only the dataset name is entered when using datasets.load_dataset(), it works fine. But if I create a second builder_config for my dataset and enter the config name when using datasets.load_dataset(), the following error will happen.
FileNotFoundError: [Errno 2] No such file or directory: 'C:/Users/chenx/.cache/huggingface/datasets/my_dataset/0_shot_multiple_choice/1.0.0/97c3854a012cfd6b045e3be4c864739902af2d818bb9235b047baa94c302e9a2.incomplete/my_dataset-test-00000-00000-of-NNNNN.arrow'
The "XXX.incomplete folder" in the cache folder of my dataset will disappear before "generating test split", which does not happen when config name is not entered and the config name is "default"
C:\Users\chenx\.cache\huggingface\datasets\my_dataset\0_shot_multiple_choice\1.0.0
The folder that is supposed to remain under the above directory will disappear, and the data generator will not have a place to generate data into.
### Steps to reproduce the bug
test = load_dataset('my_dataset', '0_shot_multiple_choice')
### Expected behavior
FileNotFoundError: [Errno 2] No such file or directory: 'C:/Users/chenx/.cache/huggingface/datasets/my_dataset/0_shot_multiple_choice/1.0.0/97c3854a012cfd6b045e3be4c864739902af2d818bb9235b047baa94c302e9a2.incomplete/my_dataset-test-00000-00000-of-NNNNN.arrow'
### Environment info
datasets 2.14.5
python 3.8.18 | {
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https://api.github.com/repos/huggingface/datasets/issues/1440 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1440/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1440/comments | https://api.github.com/repos/huggingface/datasets/issues/1440/events | https://github.com/huggingface/datasets/pull/1440 | 760,973,057 | MDExOlB1bGxSZXF1ZXN0NTM1NzEyNDY1 | 1,440 | Adding english plaintext jokes dataset | {
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"Hi @purvimisal, thanks for your contributions!\r\n\r\nThis jokes dataset has come up before, and after a conversation with the initial submitter, we decided not to add it then. Humor is important, but looking at the actual data points in this set raises several concerns :) \r\n\r\nThe main issue is the Reddit part... | 2020-12-10T07:04:17Z | 2020-12-13T05:22:00Z | 2020-12-12T05:55:43Z | CONTRIBUTOR | null | 0 | {
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} | This PR adds a dataset of 200k English plaintext Jokes from three sources: Reddit, Stupidstuff, and Wocka.
Link: https://github.com/taivop/joke-dataset
This is my second PR.
First was: [#1269 ](https://github.com/huggingface/datasets/pull/1269) | {
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https://api.github.com/repos/huggingface/datasets/issues/1618 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1618/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1618/comments | https://api.github.com/repos/huggingface/datasets/issues/1618/events | https://github.com/huggingface/datasets/issues/1618 | 772,248,730 | MDU6SXNzdWU3NzIyNDg3MzA= | 1,618 | Can't filter language:EN on https://huggingface.co/datasets | {
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"cc'ing @mapmeld ",
"Full language list is now deployed to https://huggingface.co/datasets ! Recommend close",
"Cool @mapmeld ! My 2 cents (for a next iteration), it would be cool to have a small search widget in the filter dropdown as you have a ton of languages now here! Closing this in the meantime."
] | 2020-12-21T15:23:23Z | 2020-12-22T17:17:00Z | 2020-12-22T17:16:09Z | NONE | null | null | null | When visiting https://huggingface.co/datasets, I don't see an obvious way to filter only English datasets. This is unexpected for me, am I missing something? I'd expect English to be selectable in the language widget. This problem reproduced on Mozilla Firefox and MS Edge:
| {
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https://api.github.com/repos/huggingface/datasets/issues/2995 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2995/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2995/comments | https://api.github.com/repos/huggingface/datasets/issues/2995/events | https://github.com/huggingface/datasets/pull/2995 | 1,013,143,868 | PR_kwDODunzps4sjThd | 2,995 | Fix trivia_qa unfiltered | {
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"CI fails due to missing tags, but they will be added in https://github.com/huggingface/datasets/pull/2949"
] | 2021-10-01T09:53:43Z | 2021-10-01T10:04:11Z | 2021-10-01T10:04:10Z | MEMBER | null | 0 | {
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} | Fix https://github.com/huggingface/datasets/issues/2993 | {
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https://api.github.com/repos/huggingface/datasets/issues/5600 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5600/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5600/comments | https://api.github.com/repos/huggingface/datasets/issues/5600/events | https://github.com/huggingface/datasets/issues/5600 | 1,606,585,596 | I_kwDODunzps5fwoz8 | 5,600 | Dataloader getitem not working for DreamboothDatasets | {
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} | [] | closed | false | null | [] | null | [
"Hi! \r\n\r\n> (see example of DreamboothDatasets)\r\n\r\n\r\nCould you please provide a link to it? If you are referring to the example in the `diffusers` repo, your issue is unrelated to `datasets` as that example uses `Dataset` from PyTorch to load data."
] | 2023-03-02T11:00:27Z | 2023-03-13T17:59:35Z | 2023-03-13T17:59:35Z | NONE | null | null | null | ### Describe the bug
Dataloader getitem is not working as before (see example of [DreamboothDatasets](https://github.com/huggingface/peft/blob/main/examples/lora_dreambooth/train_dreambooth.py#L451C14-L529))
moving Datasets to 2.8.0 solved the issue.
### Steps to reproduce the bug
1- using DreamBoothDataset to load some images
2- error after loading when trying to visualise the images
### Expected behavior
I was expecting a numpy array of the image
### Environment info
- Platform: Linux-5.10.147+-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 9.0.0
- Pandas version: 1.3.5 | {
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https://api.github.com/repos/huggingface/datasets/issues/5398 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5398/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5398/comments | https://api.github.com/repos/huggingface/datasets/issues/5398/events | https://github.com/huggingface/datasets/issues/5398 | 1,514,425,231 | I_kwDODunzps5aREuP | 5,398 | Unpin pydantic | {
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See issue:
- #5394
See temporary fix:
- #5395 | {
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https://api.github.com/repos/huggingface/datasets/issues/5938 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5938/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5938/comments | https://api.github.com/repos/huggingface/datasets/issues/5938/events | https://github.com/huggingface/datasets/pull/5938 | 1,749,462,851 | PR_kwDODunzps5SmbkI | 5,938 | Make get_from_cache use custom temp filename that is locked | {
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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... | 2023-06-09T09:01:13Z | 2023-06-14T13:35:38Z | 2023-06-14T13:27:24Z | MEMBER | null | 0 | {
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} | This PR ensures that the temporary filename created is the same as the one that is locked, while writing to the cache.
This PR stops using `tempfile` to generate the temporary filename.
Additionally, the behavior now is aligned for both `resume_download` `True` and `False`.
Refactor temp_file_manager so that it uses the filename that is locked:
- Use: `cache_path + ".incomplete"`, when the locked one is `cache_path + ".lock"`
Before it was using `tempfile` inside `cache_dir`, which was not locked: although very improbable name collision (8 random characters), this was not impossible when huge number of multiple processes.
Maybe related to "Stale file handle" issues caused by `tempfile`:
- [ ] https://huggingface.co/datasets/tapaco/discussions/4
- [ ] https://huggingface.co/datasets/xcsr/discussions/1
- [ ] https://huggingface.co/datasets/covost2/discussions/3
```
Error code: ConfigNamesError
Exception: OSError
Message: [Errno 116] Stale file handle
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 61, in compute_config_names_response
for config in sorted(get_dataset_config_names(path=dataset, use_auth_token=use_auth_token))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 323, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1219, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1188, in dataset_module_factory
return HubDatasetModuleFactoryWithScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 907, in get_module
dataset_readme_path = self.download_dataset_readme_file()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 896, in download_dataset_readme_file
return cached_path(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 183, in cached_path
output_path = get_from_cache(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 611, in get_from_cache
http_get(
File "/usr/local/lib/python3.9/tempfile.py", line 496, in __exit__
result = self.file.__exit__(exc, value, tb)
OSError: [Errno 116] Stale file handle
```
- the stale file handle error can be raised when `tempfile` tries to close (when exiting its context manager) a filename that has been already closed by other process
- note that `tempfile` filenames are randomly generated but not locked in our code
CC: @severo | {
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https://api.github.com/repos/huggingface/datasets/issues/2391 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2391/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2391/comments | https://api.github.com/repos/huggingface/datasets/issues/2391/events | https://github.com/huggingface/datasets/issues/2391 | 898,128,099 | MDU6SXNzdWU4OTgxMjgwOTk= | 2,391 | Missing original answers in kilt-TriviaQA | {
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] | closed | false | null | [] | null | [
"That could be useful indeed! Feel free to open a PR on the dataset card if you already have some code that runs, otherwise we'll take care of it soon :) ",
"I can open a PR but there is 2 details to fix:\r\n- the name for the corresponding key (e.g. `original_answer`)\r\n- how to implement it: I’m not sure what ... | 2021-05-21T14:57:07Z | 2021-06-14T17:29:11Z | 2021-06-14T17:29:11Z | CONTRIBUTOR | null | null | null | I previously opened an issue at https://github.com/facebookresearch/KILT/issues/42 but from the answer of @fabiopetroni it seems that the problem comes from HF-datasets
## Describe the bug
The `answer` field in kilt-TriviaQA, e.g. `kilt_tasks['train_triviaqa'][0]['output']['answer']` contains a list of alternative answer which are accepted for the question.
However it'd be nice to know the original answer to the question (the only fields in `output` are `'answer', 'meta', 'provenance'`)
## How to fix
It can be fixed by retrieving the original answer from the original TriviaQA (e.g. `trivia_qa['train'][0]['answer']['value']`), perhaps at the same place as here where one retrieves the questions https://github.com/huggingface/datasets/blob/master/datasets/kilt_tasks/README.md#loading-the-kilt-knowledge-source-and-task-data
cc @yjernite who previously answered to an issue about KILT and TriviaQA :)
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https://api.github.com/repos/huggingface/datasets/issues/5400 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5400/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5400/comments | https://api.github.com/repos/huggingface/datasets/issues/5400/events | https://github.com/huggingface/datasets/pull/5400 | 1,517,032,972 | PR_kwDODunzps5GhaGI | 5,400 | Support streaming datasets with os.path.exists and Path.exists | {
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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... | 2023-01-03T07:42:37Z | 2023-01-06T10:42:44Z | 2023-01-06T10:35:44Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4159 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4159/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4159/comments | https://api.github.com/repos/huggingface/datasets/issues/4159/events | https://github.com/huggingface/datasets/pull/4159 | 1,202,522,153 | PR_kwDODunzps42Izmd | 4,159 | Add `TruthfulQA` dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Bump. (I'm not sure which reviewer to `@` but, previously, @lhoestq has been very helpful 🤗 )"
] | 2022-04-12T23:19:04Z | 2022-06-08T15:51:33Z | 2022-06-08T14:43:34Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6208 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6208/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6208/comments | https://api.github.com/repos/huggingface/datasets/issues/6208/events | https://github.com/huggingface/datasets/pull/6208 | 1,879,572,646 | PR_kwDODunzps5ZcnpJ | 6,208 | Do not filter out .zip extensions from no-script datasets | {
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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... | 2023-09-04T06:07:12Z | 2023-09-04T09:22:19Z | 2023-09-04T09:13:32Z | MEMBER | null | 0 | {
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} | This PR is a hotfix of:
- #6207
That PR introduced the filtering out of `.zip` extensions. This PR reverts that.
Hot fix #6207.
Maybe we should do patch releases: the bug was introduced in 2.13.1.
CC: @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/2251 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2251/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2251/comments | https://api.github.com/repos/huggingface/datasets/issues/2251/events | https://github.com/huggingface/datasets/issues/2251 | 865,848,705 | MDU6SXNzdWU4NjU4NDg3MDU= | 2,251 | while running run_qa.py, ran into a value error | {
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} | [] | open | false | null | [] | null | [] | 2021-04-23T07:51:03Z | 2021-04-23T07:51:03Z | null | NONE | null | null | null | command:
python3 run_qa.py --model_name_or_path hyunwoongko/kobart --dataset_name squad_kor_v2 --do_train --do_eval --per_device_train_batch_size 8 --learning_rate 3e-5 --num_train_epochs 3 --max_seq_length 512 --doc_stride 128 --output_dir /tmp/debug_squad/
error:
ValueError: External features info don't match the dataset:
Got
{'id': Value(dtype='string', id=None), 'title': Value(dtype='string', id=None), 'context': Value(dtype='string', id=None), 'question': Value(dtype='string', id=None), 'answer': {'text': Value(dtype='string', id=None), 'answer_start': Value(dtype='int32', id=None), 'html_answer_start': Value(dtype='int32', id=None)}, 'url': Value(dtype='string', id=None), 'raw_html': Value(dtype='string', id=None)}
with type
struct<answer: struct<text: string, answer_start: int32, html_answer_start: int32>, context: string, id: string, question: string, raw_html: string, title: string, url: string>
but expected something like
{'answer': {'answer_start': Value(dtype='int32', id=None), 'html_answer_start': Value(dtype='int32', id=None), 'text': Value(dtype='string', id=None)}, 'context': Value(dtype='string', id=None), 'id': Value(dtype='string', id=None), 'question': Value(dtype='string', id=None), 'raw_html': Value(dtype='string', id=None), 'title': Value(dtype='string', id=None), 'url': Value(dtype='string', id=None)}
with type
struct<answer: struct<answer_start: int32, html_answer_start: int32, text: string>, context: string, id: string, question: string, raw_html: string, title: string, url: string>
I didn't encounter this error 4 hours ago. any solutions for this kind of issue?
looks like gained dataset format refers to 'Data Fields', while expected refers to 'Data Instances'. | {
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https://api.github.com/repos/huggingface/datasets/issues/4288 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4288/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4288/comments | https://api.github.com/repos/huggingface/datasets/issues/4288/events | https://github.com/huggingface/datasets/pull/4288 | 1,226,821,732 | PR_kwDODunzps43XLKi | 4,288 | Add missing `faiss` import to fix https://github.com/huggingface/datasets/issues/4287 | {
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https://api.github.com/repos/huggingface/datasets/issues/1990 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1990/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1990/comments | https://api.github.com/repos/huggingface/datasets/issues/1990/events | https://github.com/huggingface/datasets/issues/1990 | 822,384,502 | MDU6SXNzdWU4MjIzODQ1MDI= | 1,990 | OSError: Memory mapping file failed: Cannot allocate memory | {
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"Do you think this is trying to bring the dataset into memory and if I can avoid it to save on memory so it only brings a batch into memory? @lhoestq thank you",
"It's not trying to bring the dataset into memory.\r\n\r\nActually, it's trying to memory map the dataset file, which is different. It allows to load l... | 2021-03-04T18:21:58Z | 2021-08-04T18:04:25Z | 2021-08-04T18:04:25Z | NONE | null | null | null | Hi,
I am trying to run a code with a wikipedia dataset, here is the command to reproduce the error. You can find the codes for run_mlm.py in huggingface repo here: https://github.com/huggingface/transformers/blob/v4.3.2/examples/language-modeling/run_mlm.py
```
python run_mlm.py --model_name_or_path bert-base-multilingual-cased --dataset_name wikipedia --dataset_config_name 20200501.en --do_train --do_eval --output_dir /dara/test --max_seq_length 128
```
I am using transformer version: 4.3.2
But I got memory erorr using this dataset, is there a way I could save on memory with dataset library with wikipedia dataset?
Specially I need to train a model with multiple of wikipedia datasets concatenated. thank you very much @lhoestq for your help and suggestions:
```
File "run_mlm.py", line 441, in <module>
main()
File "run_mlm.py", line 233, in main
split=f"train[{data_args.validation_split_percentage}%:]",
File "/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/load.py", line 750, in load_dataset
ds = builder_instance.as_dataset(split=split, ignore_verifications=ignore_verifications, in_memory=keep_in_memory)
File "/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/builder.py", line 740, in as_dataset
map_tuple=True,
File "/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/utils/py_utils.py", line 225, in map_nested
return function(data_struct)
File "/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/builder.py", line 757, in _build_single_dataset
in_memory=in_memory,
File "/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/builder.py", line 829, in _as_dataset
in_memory=in_memory,
File "/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/arrow_reader.py", line 215, in read
return self.read_files(files=files, original_instructions=instructions, in_memory=in_memory)
File "/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/arrow_reader.py", line 236, in read_files
pa_table = self._read_files(files, in_memory=in_memory)
File "/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/arrow_reader.py", line 171, in _read_files
pa_table: pa.Table = self._get_dataset_from_filename(f_dict, in_memory=in_memory)
File "/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/arrow_reader.py", line 302, in _get_dataset_from_filename
pa_table = ArrowReader.read_table(filename, in_memory=in_memory)
File "/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/arrow_reader.py", line 322, in read_table
stream = stream_from(filename)
File "pyarrow/io.pxi", line 782, in pyarrow.lib.memory_map
File "pyarrow/io.pxi", line 743, in pyarrow.lib.MemoryMappedFile._open
File "pyarrow/error.pxi", line 122, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 99, in pyarrow.lib.check_status
OSError: Memory mapping file failed: Cannot allocate memory
```
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https://api.github.com/repos/huggingface/datasets/issues/3788 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3788/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3788/comments | https://api.github.com/repos/huggingface/datasets/issues/3788/events | https://github.com/huggingface/datasets/issues/3788 | 1,150,375,720 | I_kwDODunzps5EkVco | 3,788 | Only-data dataset loaded unexpectedly as validation split | {
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"I see two options:\r\n1. drop the \"dev\" keyword since it can be considered too generic\r\n2. improve the pattern to something more reasonable, e.g. asking for a separator before and after \"dev\"\r\n```python\r\n[\"*[ ._-]dev[ ._-]*\", \"dev[ ._-]*\"]\r\n```\r\n\r\nI think 2. is nice. If we agree on this one we ... | 2022-02-25T12:11:39Z | 2022-02-28T11:22:22Z | null | MEMBER | null | null | null | ## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`. | {
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https://api.github.com/repos/huggingface/datasets/issues/4586 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4586/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4586/comments | https://api.github.com/repos/huggingface/datasets/issues/4586/events | https://github.com/huggingface/datasets/pull/4586 | 1,287,105,636 | PR_kwDODunzps46e9xB | 4,586 | Host pn_summary data on the Hub instead of Google Drive | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-28T10:05:05Z | 2022-06-28T14:52:56Z | 2022-06-28T14:42:03Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3347 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3347/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3347/comments | https://api.github.com/repos/huggingface/datasets/issues/3347/events | https://github.com/huggingface/datasets/pull/3347 | 1,067,738,902 | PR_kwDODunzps4vNthw | 3,347 | iter_archive for zip files | {
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"And also don't always try streaming with Google Drive - it can have issues because of how Google Drive works (with quotas, restrictions, etc.) and it can indeed cause `BlockSizeError`.\r\n\r\nFeel free to host your test data elsewhere, such as in a dataset repository on https://huggingface.co (see [here](https://h... | 2021-11-30T22:34:17Z | 2021-12-04T00:22:22Z | 2021-12-04T00:22:11Z | CONTRIBUTOR | null | 0 | {
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} | * In this PR, I added the option to iterate through zipfiles for `download_manager.py` only.
* Next PR will be the same applied to `streaming_download_manager.py`.
* Related issue #3272.
## Comments :
* There is no `.isreg()` equivalent in zipfile library to check if file is Regular so I used `.is_dir()` instead to skip directories.
* For now I got `streaming_download_manager.py` working for local zip files, but not for urls. I get the following error when I test it on an archive in google drive, so still working on it. `BlockSizeError: Got more bytes so far (>2112) than requested (22)`
## Tasks :
- [x] download_manager.py
- [ ] streaming_download_manager.py | {
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https://api.github.com/repos/huggingface/datasets/issues/2027 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2027/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2027/comments | https://api.github.com/repos/huggingface/datasets/issues/2027/events | https://github.com/huggingface/datasets/pull/2027 | 828,490,444 | MDExOlB1bGxSZXF1ZXN0NTkwMjkzNDA1 | 2,027 | Update format columns in Dataset.rename_columns | {
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https://api.github.com/repos/huggingface/datasets/issues/5185 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5185/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5185/comments | https://api.github.com/repos/huggingface/datasets/issues/5185/events | https://github.com/huggingface/datasets/issues/5185 | 1,432,021,611 | I_kwDODunzps5VWupr | 5,185 | Allow passing a subset of output features to Dataset.map | {
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] | open | false | null | [] | null | [] | 2022-11-01T20:07:20Z | 2022-11-01T20:07:34Z | null | CONTRIBUTOR | null | null | null | ### Feature request
Currently, map does one of two things to the features (if I'm not mistaken):
* when you do not pass features, types are assumed to be equal to the input if they can be cast, and inferred otherwise
* when you pass a full specification of features, output features are set to this
However, sometimes you want to just pass some of the output types, particularly when the first of these modes makes an incorrect type. This currently crashes.
### Motivation
To give a little background: this problem appears in converting labels to ids, where the labels happen to be floats rather than strings
Consider the following use of map to convert from float to int
```python
data = Dataset.from_dict({'y':[1.0,2.0,3.0]})
mapped = data.map(lambda r: {'y': int(r['y'])})
mapped['y'] # is floats, not ints
```
The result is a float again, since after the mapping operation it forces the old datatypes back on the data.
Passing `features=Features({"y": Value(dtype="int64")})` to map works in principle, but then extending it a little to e.g.
```python
def format_data(r):
return {**tokenizer(r["text"]), "y": int(r["y"])}
data = Dataset.from_dict({"y": [1.0, 2.0, 3.0], "text": ["one", "two", "three"]})
mapped = data.map(
format_data,
features=Features({'y': Value(dtype="int64")}),
remove_columns=["text"],
)
```
Results in a crash in dataset internals, as it expects either all or no output features to be specified.
Of course one can pass a full feature specification, but this becomes tokenizer specific and very awkward.
### Your contribution
I've looked at `write_batch` and particularly `col_type = features[col] if features else None`, but checking for `col in features` here makes it fail elsewhere, but the structure makes it hard to understand how and why. I do not think I would have the time myself to get to the bottom of this anytime soon. | {
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https://api.github.com/repos/huggingface/datasets/issues/2642 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2642/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2642/comments | https://api.github.com/repos/huggingface/datasets/issues/2642/events | https://github.com/huggingface/datasets/issues/2642 | 944,175,697 | MDU6SXNzdWU5NDQxNzU2OTc= | 2,642 | Support multi-worker with streaming dataset (IterableDataset). | {
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"Hi ! This is a great idea :)\r\nI think we could have something similar to what we have in `datasets.Dataset.map`, i.e. a `num_proc` parameter that tells how many processes to spawn to parallelize the data processing. \r\n\r\nRegarding AUTOTUNE, this could be a nice feature as well, we could see how to add it in a... | 2021-07-14T08:22:58Z | 2021-07-15T09:37:34Z | null | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
The current `.map` does not support multi-process, CPU can become bottleneck if the pre-processing is complex (e.g. t5 span masking).
**Describe the solution you'd like**
Ideally `.map` should support multi-worker like tfds, with `AUTOTUNE`.
**Describe alternatives you've considered**
A simpler solution is to shard the dataset and process it in parallel with pytorch dataloader. The shard does not need to be of equal size.
* https://pytorch.org/docs/stable/data.html#torch.utils.data.IterableDataset
**Additional context**
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] | open | false | null | [] | null | [] | 2021-09-07T15:15:05Z | 2021-09-07T15:15:05Z | null | NONE | null | null | null | ## Describe the bug
Trying to load saved dataset or dataset directory from Amazon S3 on a Windows machine fails.
Performing the same operation succeeds on non-windows environment (AWS Sagemaker).
## Steps to reproduce the bug
```python
# Followed https://huggingface.co/docs/datasets/filesystems.html#loading-a-processed-dataset-from-s3
from datasets import load_from_disk
from datasets.filesystems import S3FileSystem
s3_file = "output of save_to_disk"
s3_filesystem = S3FileSystem()
load_from_disk(s3_file, fs=s3_filesystem)
```
## Expected results
load_from_disk succeeds without error
## Actual results
Seems like it succeeds in pulling the file into a windows temp directory, as it exists in my system, but fails to process it.
```
Exception ignored in: <finalize object at 0x26409231ce0; dead>
Traceback (most recent call last):
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\weakref.py", line 566, in __call__
return info.func(*info.args, **(info.kwargs or {}))
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 817, in _cleanup
cls._rmtree(name)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
[Previous line repeated 2 more times]
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 618, in _rmtree_unsafe
onerror(os.unlink, fullname, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 805, in onerror
cls._rmtree(path)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 599, in _rmtree_unsafe
onerror(os.scandir, path, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 596, in _rmtree_unsafe
with os.scandir(path) as scandir_it:
NotADirectoryError: [WinError 267] The directory name is invalid: 'C:\\Users\\grassycup\\AppData\\Local\\Temp\\tmp45f_qbma\\tests3bucket\\output\\test_output\\train\\dataset.arrow'
Exception ignored in: <finalize object at 0x264091c7880; dead>
Traceback (most recent call last):
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\weakref.py", line 566, in __call__
return info.func(*info.args, **(info.kwargs or {}))
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 817, in _cleanup
cls._rmtree(name)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
[Previous line repeated 2 more times]
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 618, in _rmtree_unsafe
onerror(os.unlink, fullname, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 805, in onerror
cls._rmtree(path)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 599, in _rmtree_unsafe
onerror(os.scandir, path, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 596, in _rmtree_unsafe
with os.scandir(path) as scandir_it:
NotADirectoryError: [WinError 267] The directory name is invalid:
'C:\\Users\\grassycup\\AppData\\Local\\Temp\\tmp45f_qbma\\tests3bucket\\output\\test_output\\train\\dataset.arrow'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Platform: Windows-10-10.0.19042-SP0
- Python version: 3.8.11
- PyArrow version: 3.0.0
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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... | 2023-10-09T09:23:23Z | 2023-10-10T07:13:22Z | 2023-10-10T07:03:04Z | MEMBER | null | 0 | {
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} | Create `DefunctDatasetError` as a specific error to be raised when a dataset is defunct and no longer accessible.
See Hub discussion: https://huggingface.co/datasets/the_pile_books3/discussions/7#6523c13a94f3a1a2092d251b | {
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"Cleaned-up version of previous PR: https://github.com/huggingface/datasets/pull/1129",
"@lhoestq FYI",
"Before merging I might tweak a little bit the dummy data to avoid having to check if the `document_parses` and `embeddings` directories exist or not. I'll do that later today",
"Looks all good now ! Thanks... | 2021-02-09T10:22:08Z | 2021-02-09T15:16:26Z | 2021-02-09T15:16:26Z | CONTRIBUTOR | null | 0 | {
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} | Initial version only reading the metadata in CSV.
### Checklist:
- [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 and at least fill the tags
- [x] Both tests for the real data and the dummy data pass.
### Extras:
- [x] add more metadata
- [x] add full text
- [x] add pre-computed document embedding | {
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https://api.github.com/repos/huggingface/datasets/issues/5292 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5292/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5292/comments | https://api.github.com/repos/huggingface/datasets/issues/5292/events | https://github.com/huggingface/datasets/issues/5292 | 1,463,053,832 | I_kwDODunzps5XNG4I | 5,292 | Missing documentation build for versions 2.7.1 and 2.6.2 | {
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"- Build docs for 2.6.2:\r\n - Commit: a6a5a1cf4cdf1e0be65168aed5a327f543001fe8\r\n - Build docs GH Action: https://github.com/huggingface/datasets/actions/runs/3539470622/jobs/5941404044\r\n- Build docs for 2.7.1:\r\n - Commit: 5ef1ab1cc06c2b7a574bf2df454cd9fcb071ccb2\r\n - Build docs GH Action: https://github... | 2022-11-24T09:42:10Z | 2022-11-24T10:10:02Z | 2022-11-24T10:10:02Z | MEMBER | null | null | null | After the patch releases [2.7.1](https://github.com/huggingface/datasets/releases/tag/2.7.1) and [2.6.2](https://github.com/huggingface/datasets/releases/tag/2.6.2), the online docs were not properly built (the build_documentation workflow was not triggered).
There was a fix by:
- #5291
However, both documentations were built from main branch, instead of their corresponding version branch.
We are rebuilding them. | {
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https://api.github.com/repos/huggingface/datasets/issues/1668 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1668/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1668/comments | https://api.github.com/repos/huggingface/datasets/issues/1668/events | https://github.com/huggingface/datasets/pull/1668 | 776,552,854 | MDExOlB1bGxSZXF1ZXN0NTQ3MDIxODI0 | 1,668 | xed_en_fi dataset Cleanup | {
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https://api.github.com/repos/huggingface/datasets/issues/4933 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4933/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4933/comments | https://api.github.com/repos/huggingface/datasets/issues/4933/events | https://github.com/huggingface/datasets/issues/4933 | 1,363,013,023 | I_kwDODunzps5RPe2f | 4,933 | Dataset/DatasetDict.filter() cannot have `batched=True` due to `mask` (numpy array?) being non-iterable. | {
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"Hi ! When `batched=True`, you filter function must take a batch as input, and return a list of booleans.\r\n\r\nIn your case, something like\r\n```python\r\nfrom datasets import load_dataset\r\n\r\n\r\nds_mc4_ja = load_dataset(\"mc4\", \"ja\") # This will take 6+ hours... perhaps test it with a toy dataset instea... | 2022-09-06T09:47:48Z | 2022-09-06T11:44:27Z | 2022-09-06T11:44:27Z | CONTRIBUTOR | null | null | null | ## Describe the bug
`Dataset/DatasetDict.filter()` cannot have `batched=True` due to `mask` (numpy array?) being non-iterable.
## Steps to reproduce the bug
(In a python 3.7.12 env, I've tried 2.4.0 and 2.3.2 with both `pyarraw==9.0.0` and `pyarrow==8.0.0`.)
```python
from datasets import load_dataset
ds_mc4_ja = load_dataset("mc4", "ja") # This will take 6+ hours... perhaps test it with a toy dataset instead?
ds_mc4_ja_2020 = ds_mc4_ja.filter(
lambda example: example["timestamp"][:4] == "2020",
batched=True,
)
```
## Expected results
No error
## Actual results
```python
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/opt/conda/lib/python3.7/site-packages/multiprocess/pool.py", line 121, in worker
result = (True, func(*args, **kwds))
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 557, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 524, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/fingerprint.py", line 480, in wrapper
out = func(self, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2779, in _map_single
offset=offset,
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2655, in apply_function_on_filtered_inputs
processed_inputs = function(*fn_args, *additional_args, **fn_kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2347, in decorated
result = f(decorated_item, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 4946, in get_indices_from_mask_function
indices_array = [i for i, to_keep in zip(indices, mask) if to_keep]
TypeError: zip argument #2 must support iteration
"""
The above exception was the direct cause of the following exception:
TypeError Traceback (most recent call last)
/tmp/ipykernel_51348/2345782281.py in <module>
7 batched=True,
8 # batch_size=10_000,
----> 9 num_proc=111,
10 )
11 # ds_mc4_ja_clean_2020 = ds_mc4_ja.filter(
/opt/conda/lib/python3.7/site-packages/datasets/dataset_dict.py in filter(self, function, with_indices, input_columns, batched, batch_size, keep_in_memory, load_from_cache_file, cache_file_names, writer_batch_size, fn_kwargs, num_proc, desc)
878 desc=desc,
879 )
--> 880 for k, dataset in self.items()
881 }
882 )
/opt/conda/lib/python3.7/site-packages/datasets/dataset_dict.py in <dictcomp>(.0)
878 desc=desc,
879 )
--> 880 for k, dataset in self.items()
881 }
882 )
/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs)
522 }
523 # apply actual function
--> 524 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
525 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
526 # re-apply format to the output
/opt/conda/lib/python3.7/site-packages/datasets/fingerprint.py in wrapper(*args, **kwargs)
478 # Call actual function
479
--> 480 out = func(self, *args, **kwargs)
481
482 # Update fingerprint of in-place transforms + update in-place history of transforms
/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py in filter(self, function, with_indices, input_columns, batched, batch_size, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc)
2920 new_fingerprint=new_fingerprint,
2921 input_columns=input_columns,
-> 2922 desc=desc,
2923 )
2924 new_dataset = copy.deepcopy(self)
/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py in map(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc)
2498
2499 for index, async_result in results.items():
-> 2500 transformed_shards[index] = async_result.get()
2501
2502 assert (
/opt/conda/lib/python3.7/site-packages/multiprocess/pool.py in get(self, timeout)
655 return self._value
656 else:
--> 657 raise self._value
658
659 def _set(self, i, obj):
TypeError: zip argument #2 must support iteration
```
## 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-debian-10.12
- Python version: 3.7.12
- PyArrow version: 9.0.0
- Pandas version: 1.3.5
(I've tried 2.4.0 and 2.3.2 with both `pyarraw==9.0.0` and `pyarrow==8.0.0`.) | {
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https://api.github.com/repos/huggingface/datasets/issues/1253 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1253/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1253/comments | https://api.github.com/repos/huggingface/datasets/issues/1253/events | https://github.com/huggingface/datasets/pull/1253 | 758,517,391 | MDExOlB1bGxSZXF1ZXN0NTMzNjc4MDE1 | 1,253 | add thainer | {
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} | ThaiNER (v1.3) is a 6,456-sentence named entity recognition dataset created from expanding the 2,258-sentence
[unnamed dataset](http://pioneer.chula.ac.th/~awirote/Data-Nutcha.zip) by
[Tirasaroj and Aroonmanakun (2012)](http://pioneer.chula.ac.th/~awirote/publications/).
It is used to train NER taggers in [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp).
The NER tags are annotated by [Tirasaroj and Aroonmanakun (2012)]((http://pioneer.chula.ac.th/~awirote/publications/))
for 2,258 sentences and the rest by [@wannaphong](https://github.com/wannaphong/).
The POS tags are done by [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp)'s `perceptron` engine trained on `orchid_ud`.
[@wannaphong](https://github.com/wannaphong/) is now the only maintainer of this dataset. | {
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"You can use a `Sequence(ClassLabel(...))` feature type to represent a list of labels, and `cast_column`/`cast` to perform the \"string to label\" conversion (`class_encode_column` does support nested fields), e.g., in your case:\r\n```python\r\nfrom datasets import Dataset, Sequence, ClassLabel\r\ndata = {\r\n ... | 2023-09-27T22:48:08Z | 2023-10-15T21:13:08Z | null | NONE | null | null | null | ### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like to encode:
```
data = {
'text': ['one', 'two', 'three', 'four'],
'labels': [['a', 'b'], ['b'], ['b', 'c'], ['a', 'd']]
}
dataset = Dataset.from_dict(data)
dataset = dataset.class_encode_column('labels')
```
I did some digging into the code base to evaluate the feasibility of this (note I'm very new to this code base) and from what I noticed the `ClassLabel` feature is still stored as an underlying raw data type of int so I thought a `MultiLabel` feature could similarly be stored as a Sequence of ints, thus not requiring significant serialization / conversion work to / from arrow.
I did a POC of this [here](https://github.com/huggingface/datasets/commit/15443098e9ce053943172f7ec6fce3769d7dff6e) and included a simple test case (please excuse all the commented out tests, going for speed of POC here and didn't want to fight IDE to debug a single test). In the test I just assert that `num_classes` is the same to show that things are properly serializing, but if you break after loading from disk you'll see the dataset correct and the dataset feature is as expected.
After digging more I did notice a few issues
- After loading from disk I noticed type of the `labels` class is `Sequence` not `MultiLabel` (though the added `feature` attribute came through). This doesn't happen for `ClassLabel` but I couldn't find the encode / decode code paths that handle this.
- I subclass `Sequence` in `MultiLabel` to leverage existing serialization, but this does miss the custom encode logic that `ClassLabel` has. I'm not sure of the best way to approach this as I haven't fully understood the encode / decode flow for datasets. I suspect my simple implementation will need some improvement as it'll require a significant amount of repeated logic to mimic `ClassLabel` behavior.
### Motivation
See above - would like to support multi label class encodings.
### Your contribution
This would be a big help for us and we're open to contributing but I'll likely need some guidance on how to implement to fit the encode / decode flow. Some suggestions on tests / would be great too, I'm guessing in addition to the class encode tests (that I'll need to expand) we'll need encode / decode tests. | {
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https://api.github.com/repos/huggingface/datasets/issues/1499 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1499/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1499/comments | https://api.github.com/repos/huggingface/datasets/issues/1499/events | https://github.com/huggingface/datasets/pull/1499 | 763,464,693 | MDExOlB1bGxSZXF1ZXN0NTM3OTIyNjA3 | 1,499 | update the dataset id_newspapers_2018 | {
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} | Hi, I need to update the link to the dataset. The link in the previous PR was to a small test dataset. Thanks | {
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https://api.github.com/repos/huggingface/datasets/issues/5895 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5895/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5895/comments | https://api.github.com/repos/huggingface/datasets/issues/5895/events | https://github.com/huggingface/datasets/issues/5895 | 1,725,467,252 | I_kwDODunzps5m2Ip0 | 5,895 | The dir name and split strings are confused when loading ArmelR/stack-exchange-instruction dataset | {
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"Thanks for reporting, @DongHande.\r\n\r\nI think the issue is caused by the metadata in the dataset card: in the header of the `README.md`, they state that the dataset has 4 splits (\"finetune\", \"reward\", \"rl\", \"evaluation\"). \r\n```yaml\r\n splits:\r\n - name: finetune\r\n num_bytes: 6674567576\r\... | 2023-05-25T09:39:06Z | 2023-05-29T02:32:12Z | 2023-05-29T02:32:12Z | NONE | null | null | null | ### Describe the bug
When I load the ArmelR/stack-exchange-instruction dataset, I encounter a bug that may be raised by confusing the dir name string and the split string about the dataset.
When I use the script "datasets.load_dataset('ArmelR/stack-exchange-instruction', data_dir="data/finetune", split="train", use_auth_token=True)", it fails. But it succeeds when I add the "streaming = True" parameter.
The website of the dataset is https://huggingface.co/datasets/ArmelR/stack-exchange-instruction/ .
The traceback logs are as below:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/load.py", line 1797, in load_dataset
builder_instance.download_and_prepare(
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/builder.py", line 890, in download_and_prepare
self._download_and_prepare(
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/builder.py", line 985, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/builder.py", line 1706, in _prepare_split
split_info = self.info.splits[split_generator.name]
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/splits.py", line 530, in __getitem__
instructions = make_file_instructions(
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/arrow_reader.py", line 112, in make_file_instructions
name2filenames = {
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/arrow_reader.py", line 113, in <dictcomp>
info.name: filenames_for_dataset_split(
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/naming.py", line 70, in filenames_for_dataset_split
prefix = filename_prefix_for_split(dataset_name, split)
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/naming.py", line 54, in filename_prefix_for_split
if os.path.basename(name) != name:
File "/home/xxx/miniconda3/envs/code/lib/python3.9/posixpath.py", line 142, in basename
p = os.fspath(p)
TypeError: expected str, bytes or os.PathLike object, not NoneType
### Steps to reproduce the bug
1. import datasets library function: ```from datasets import load_dataset```
2. load dataset: ```ds=load_dataset('ArmelR/stack-exchange-instruction', data_dir="data/finetune", split="train", use_auth_token=True)```
### Expected behavior
The dataset can be loaded successfully without the streaming setting.
### Environment info
Linux,
python=3.9
datasets=2.12.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1579 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1579/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1579/comments | https://api.github.com/repos/huggingface/datasets/issues/1579/events | https://github.com/huggingface/datasets/pull/1579 | 767,808,465 | MDExOlB1bGxSZXF1ZXN0NTQwMzk5OTY5 | 1,579 | Adding CLIMATE-FEVER dataset | {
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"I `git rebase`ed my branch to `upstream/master` as suggested in point 7 of <https://huggingface.co/docs/datasets/share_dataset.html> and subsequently used `git pull` to be able to push to my remote branch. However, I think this messed up the history.\r\n\r\nPlease let me know if I should create a clean new PR with... | 2020-12-15T16:49:22Z | 2020-12-22T13:43:16Z | 2020-12-22T13:43:15Z | CONTRIBUTOR | null | 0 | {
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} | This PR request the addition of the CLIMATE-FEVER dataset:
A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim totalling in 7,675 claim-evidence pairs. The dataset features challenging claims that relate multiple facets and disputed cases of claims where both supporting and refuting evidence are present.
More information can be found at:
- Homepage: <http://climatefever.ai>
- Paper: <https://arxiv.org/abs/2012.00614>
| {
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https://api.github.com/repos/huggingface/datasets/issues/3017 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3017/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3017/comments | https://api.github.com/repos/huggingface/datasets/issues/3017/events | https://github.com/huggingface/datasets/pull/3017 | 1,015,215,528 | PR_kwDODunzps4spE9m | 3,017 | Remove unused parameter in xdirname | {
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https://api.github.com/repos/huggingface/datasets/issues/1897 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1897/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1897/comments | https://api.github.com/repos/huggingface/datasets/issues/1897/events | https://github.com/huggingface/datasets/pull/1897 | 810,113,263 | MDExOlB1bGxSZXF1ZXN0NTc0ODU3MTIy | 1,897 | Fix PandasArrayExtensionArray conversion to native type | {
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} | To make the conversion to csv work in #1887 , we need PandasArrayExtensionArray used for multidimensional numpy arrays to be converted to pandas native types.
However previously pandas.core.internals.ExtensionBlock.to_native_types would fail with an PandasExtensionArray because
1. the PandasExtensionArray.isna method was wrong
2. the conversion of a PandasExtensionArray to a numpy array with dtype=object was returning a multidimensional array while pandas excepts a 1D array in this case (more info [here](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.api.extensions.ExtensionArray.html#pandas.api.extensions.ExtensionArray))
I fixed these two issues and now the conversion to native types works, and so is the export to csv.
cc @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/4120 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4120/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4120/comments | https://api.github.com/repos/huggingface/datasets/issues/4120/events | https://github.com/huggingface/datasets/issues/4120 | 1,195,887,430 | I_kwDODunzps5HR8tG | 4,120 | Representing dictionaries (json) objects as features | {
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] | open | false | null | [] | null | [] | 2022-04-07T11:07:41Z | 2022-04-07T11:07:41Z | null | CONTRIBUTOR | null | null | null | In the process of adding a new dataset to the hub, I stumbled upon the inability to represent dictionaries that contain different key names, unknown in advance (and may differ between samples), original asked in the [forum](https://discuss.huggingface.co/t/representing-nested-dictionary-with-different-keys/16442).
For instance:
```
sample1 = {"nps": {
"a": {"id": 0, "text": "text1"},
"b": {"id": 1, "text": "text2"},
}}
sample2 = {"nps": {
"a": {"id": 0, "text": "text1"},
"b": {"id": 1, "text": "text2"},
"c": {"id": 2, "text": "text3"},
}}
sample3 = {"nps": {
"a": {"id": 0, "text": "text1"},
"b": {"id": 1, "text": "text2"},
"c": {"id": 2, "text": "text3"},
"d": {"id": 3, "text": "text4"},
}}
```
the `nps` field cannot be represented as a Feature while maintaining its original structure.
@lhoestq suggested to add JSON as a new feature type, which will solve this problem.
It seems like an alternative solution would be to change the original data format, which isn't an optimal solution in my case. Moreover, JSON is a common structure, that will likely to be useful in future datasets as well. | {
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https://api.github.com/repos/huggingface/datasets/issues/5637 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5637/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5637/comments | https://api.github.com/repos/huggingface/datasets/issues/5637/events | https://github.com/huggingface/datasets/issues/5637 | 1,625,295,691 | I_kwDODunzps5g4AtL | 5,637 | IterableDataset with_format does not support 'device' keyword for jax | {
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"Hi! Yes, only `torch` is currently supported. Unlike `Dataset`, `IterableDataset` is not PyArrow-backed, so we cannot simply call `to_numpy` on the underlying subtables to format them numerically. Instead, we must manually convert examples to (numeric) arrays while preserving consistency with `Dataset`, which is n... | 2023-03-15T11:04:12Z | 2023-03-16T18:30:59Z | null | NONE | null | null | null | ### Describe the bug
As seen here: https://huggingface.co/docs/datasets/use_with_jax dataset.with_format() supports the keyword 'device', to put data on a specific device when loaded as jax. However, when called on an IterableDataset, I got the error `TypeError: with_format() got an unexpected keyword argument 'device'`
Looking over the code, it seems IterableDataset support only pytorch and no support for jax device keyword?
https://github.com/huggingface/datasets/blob/fc5c84f36684343bff3e424cb0fd1ac5ecdd66da/src/datasets/iterable_dataset.py#L1029
### Steps to reproduce the bug
1. Load an IterableDataset (tested in streaming mode)
2. Call with_format('jax',device=device)
### Expected behavior
I expect to call `with_format('jax', device=device)` as per [documentation](https://huggingface.co/docs/datasets/use_with_jax) without error
### Environment info
Tested with installing newest (dev) and also pip release (2.10.1).
- `datasets` version: 2.10.2.dev0
- Platform: Linux-5.15.89+-x86_64-with-debian-bullseye-sid
- Python version: 3.7.12
- Huggingface_hub version: 0.12.1
- PyArrow version: 11.0.0
- Pandas version: 1.3.5
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"Independently of this I think it raises the need to allow multiprocessing during streaming so that we get samples from multiple shards in one batch."
] | 2021-10-09T17:46:35Z | 2021-10-09T20:24:17Z | null | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
I'm training on a large dataset made of multiple sub-datasets.
During training I can observe some jumps in loss which may correspond to different shards.
My suspicion is that either:
* some of the sub-datasets are harder for the model than others
* some of the sub-datasets are not formatted properly
I'd like to identify which shards correspond to those jumps.
**Describe the solution you'd like**
It would be nice to have a key associated to each data sample or data batch containing details on where the data comes from (shard idx + item idx within the shard).
This should be supported both in local and streaming mode.
**Describe alternatives you've considered**
A fix would be for me to add myself details (shard id, sample id) as part of each data sample.
The inconvenient is that it requires users to process/reupload every dataset when they need this feature. | {
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https://api.github.com/repos/huggingface/datasets/issues/1274 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1274/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1274/comments | https://api.github.com/repos/huggingface/datasets/issues/1274/events | https://github.com/huggingface/datasets/pull/1274 | 758,943,174 | MDExOlB1bGxSZXF1ZXN0NTM0MDI0MTQx | 1,274 | oclar-dataset | {
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"merging since the CI is fixed on master"
] | 2020-12-07T23:56:45Z | 2020-12-09T15:36:08Z | 2020-12-09T15:36:08Z | CONTRIBUTOR | null | 0 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> Thanks! I've left some comments.\r\n> \r\n> We should also add some tests, mainly to make sure `reverse` behaves as expected. Let me know if you need help with that.\r\n\r\nThanks for the offer! I couldn't find any guidelines on ho... | 2023-02-03T16:17:00Z | 2023-02-21T14:46:49Z | 2023-02-21T14:39:23Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4543 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4543/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4543/comments | https://api.github.com/repos/huggingface/datasets/issues/4543/events | https://github.com/huggingface/datasets/pull/4543 | 1,280,379,781 | PR_kwDODunzps46IiEp | 4,543 | [CI] Fix upstream hub test url | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Remaining CI failures are unrelated to this fix, merging"
] | 2022-06-22T15:34:27Z | 2022-06-22T16:37:40Z | 2022-06-22T16:27:37Z | MEMBER | null | 0 | {
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I also updated the token to use one dedicated to `datasets` | {
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"merging since the CI is fixed on master"
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] | open | false | null | [] | null | [] | 2021-07-15T23:32:18Z | 2021-07-15T23:33:53Z | null | CONTRIBUTOR | null | null | null | While using `to_json` 2 things came to mind that would have made the experience easier on the user:
1. Could we have a `desc` arg for the tqdm use and a fallback to just `to_json` so that it'd be clear to the user what's happening? Surely, one can just print the description before calling json, but I thought perhaps it'd help to have it self-identify like you did for other progress bars recently.
2. It took me a while to make sense of the reported numbers:
```
22%|██▏ | 1536/7076 [12:30:57<44:09:42, 28.70s/it]
```
So iteration here happens to be 10K samples, and the total is 70M records. But the user does't know that, so the progress bar is perfect, but the numbers it reports are meaningless until one discovers that 1it=10K samples. And one still has to convert these in the head - so it's not quick. Not exactly sure what's the best way to approach this, perhaps it can be part of `desc`? or report M or K, so it'd be built-in if it were to print, e.g.:
```
22%|██▏ | 15360K/70760K [12:30:57<44:09:42, 28.70s/it]
```
or
```
22%|██▏ | 15.36M/70.76M [12:30:57<44:09:42, 28.70s/it]
```
(while of course remaining friendly to small datasets)
I forget if tqdm lets you add a magnitude identifier to the running count.
Thank you! | {
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] | open | false | null | [] | null | [] | 2021-08-09T21:23:17Z | 2021-08-09T21:23:17Z | null | CONTRIBUTOR | null | null | null | https://github.com/huggingface/datasets/pull/1976 implemented `HF_DATASETS_OFFLINE`, but:
1. `config.HF_DATASETS_OFFLINE` is not documented
2. the precedence is not documented (env, config)
I'm thinking it probably should be similar to what it says https://huggingface.co/docs/datasets/loading_datasets.html#from-the-huggingface-hub about `datasets.config.IN_MEMORY_MAX_SIZE`:
Quote:
> The default in 🤗 Datasets is to memory-map the dataset on disk unless you set datasets.config.IN_MEMORY_MAX_SIZE different from 0 bytes (default). In that case, the dataset will be copied in-memory if its size is smaller than datasets.config.IN_MEMORY_MAX_SIZE bytes, and memory-mapped otherwise. This behavior can be enabled by setting either the configuration option datasets.config.IN_MEMORY_MAX_SIZE (higher precedence) or the environment variable HF_DATASETS_IN_MEMORY_MAX_SIZE (lower precedence) to nonzero.
Context: trying to use `config.HF_DATASETS_OFFLINE` here:
https://github.com/bigscience-workshop/Megatron-DeepSpeed/pull/48
but are uncertain if it's safe, since it's not documented as a public API.
Thank you!
@lhoestq, @albertvillanova | {
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https://api.github.com/repos/huggingface/datasets/issues/4176 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4176/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4176/comments | https://api.github.com/repos/huggingface/datasets/issues/4176/events | https://github.com/huggingface/datasets/issues/4176 | 1,206,515,563 | I_kwDODunzps5H6fdr | 4,176 | Very slow between two operations | {
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] | closed | false | null | [] | null | [] | 2022-04-17T23:52:29Z | 2022-04-18T00:03:00Z | 2022-04-18T00:03:00Z | NONE | null | null | null | Hello, in the processing stage, I use two operations. The first one : map + filter, is very fast and it uses the full cores, while the socond step is very slow and did not use full cores.
Also, there is a significant lag between them. Am I missing something ?
```
raw_datasets = raw_datasets.map(split_func,
batched=False,
num_proc=args.preprocessing_num_workers,
load_from_cache_file=not args.overwrite_cache,
desc = "running split para ==>")\
.filter(lambda example: example['text1']!='' and example['text2']!='',
num_proc=args.preprocessing_num_workers, desc="filtering ==>")
processed_datasets = raw_datasets.map(
preprocess_function,
batched=True,
num_proc=args.preprocessing_num_workers,
remove_columns=column_names,
load_from_cache_file=not args.overwrite_cache,
desc="Running tokenizer on dataset===>",
)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3585 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3585/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3585/comments | https://api.github.com/repos/huggingface/datasets/issues/3585/events | https://github.com/huggingface/datasets/issues/3585 | 1,105,821,470 | I_kwDODunzps5B6X8e | 3,585 | Datasets streaming + map doesn't work for `Audio` | {
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"This seems related to https://github.com/huggingface/datasets/issues/3505."
] | 2022-01-17T12:55:42Z | 2022-01-20T13:28:00Z | 2022-01-20T13:28:00Z | MEMBER | null | null | null | ## Describe the bug
When using audio datasets in streaming mode, applying a `map(...)` before iterating leads to an error as the key `array` does not exist anymore.
## Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset("common_voice", "en", streaming=True, split="train")
def map_fn(batch):
print("audio keys", batch["audio"].keys())
batch["audio"] = batch["audio"]["array"][:100]
return batch
ds = ds.map(map_fn)
sample = next(iter(ds))
```
I think the audio is somehow decoded before `.map(...)` is actually called.
## Expected results
IMO, the above code snippet should work.
## Actual results
```bash
audio keys dict_keys(['path', 'bytes'])
Traceback (most recent call last):
File "./run_audio.py", line 15, in <module>
sample = next(iter(ds))
File "/home/patrick/python_bin/datasets/iterable_dataset.py", line 341, in __iter__
for key, example in self._iter():
File "/home/patrick/python_bin/datasets/iterable_dataset.py", line 338, in _iter
yield from ex_iterable
File "/home/patrick/python_bin/datasets/iterable_dataset.py", line 192, in __iter__
yield key, self.function(example)
File "./run_audio.py", line 9, in map_fn
batch["input"] = batch["audio"]["array"][:100]
KeyError: 'array'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.17.1.dev0
- Platform: Linux-5.3.0-64-generic-x86_64-with-glibc2.17
- Python version: 3.8.12
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/1324 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1324/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1324/comments | https://api.github.com/repos/huggingface/datasets/issues/1324/events | https://github.com/huggingface/datasets/issues/1324 | 759,587,864 | MDU6SXNzdWU3NTk1ODc4NjQ= | 1,324 | ❓ Sharing ElasticSearch indexed dataset | {
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"Hello @pietrolesci , I am not sure to understand what you are trying to do here.\r\n\r\nIf you're looking for ways to save a dataset on disk, you can you the `save_to_disk` method:\r\n```python\r\n>>> import datasets\r\n>>> loaded_dataset = datasets.load(\"dataset_name\")\r\n>>> loaded_dataset.save_to_disk(\"/path... | 2020-12-08T16:25:58Z | 2020-12-22T07:50:56Z | null | NONE | null | null | null | Hi there,
First of all, thank you very much for this amazing library. Datasets have become my preferred data structure for basically everything I am currently doing.
**Question:** I'm working with a dataset and I have an elasticsearch container running at localhost:9200. I added an elasticsearch index and I was wondering
- how can I know where it has been saved?
- how can I share the indexed dataset with others?
I tried to dig into the docs, but could not find anything about that.
Thank you very much for your help.
Best,
Pietro
Edit: apologies for the wrong label | {
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https://api.github.com/repos/huggingface/datasets/issues/6035 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6035/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6035/comments | https://api.github.com/repos/huggingface/datasets/issues/6035/events | https://github.com/huggingface/datasets/pull/6035 | 1,805,087,687 | PR_kwDODunzps5Vh_QR | 6,035 | Dataset representation | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6035). All of your documentation changes will be reflected on that endpoint."
] | 2023-07-14T15:42:37Z | 2023-07-19T19:41:35Z | null | NONE | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3071 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3071/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3071/comments | https://api.github.com/repos/huggingface/datasets/issues/3071/events | https://github.com/huggingface/datasets/issues/3071 | 1,024,893,493 | I_kwDODunzps49FqI1 | 3,071 | Custom plain text dataset, plain json dataset and plain csv dataset are remove from datasets template folder | {
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"Hi @zixiliuUSC, \r\n\r\nAs explained in the documentation (https://huggingface.co/docs/datasets/loading.html#json), we support loading any dataset in JSON (as well as CSV, text, Parquet) format:\r\n```python\r\nds = load_dataset('json', data_files='my_file.json')\r\n```"
] | 2021-10-13T07:32:10Z | 2021-10-13T08:27:04Z | 2021-10-13T08:27:03Z | NONE | null | null | null | ## Adding a Dataset
- **Name:** text, json, csv
- **Description:** I am developing a customized dataset loading script. The problem is mainly about my custom dataset is seperate into many files and I only find a dataset loading template in [https://github.com/huggingface/datasets/blob/1.2.1/datasets/json/json.py](https://github.com/huggingface/datasets/blob/1.2.1/datasets/json/json.py) that can handle my circumstance. I'm afraid these templates are too old to use. Could you re-add these three templates to current master branch?
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https://api.github.com/repos/huggingface/datasets/issues/4006 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4006/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4006/comments | https://api.github.com/repos/huggingface/datasets/issues/4006/events | https://github.com/huggingface/datasets/pull/4006 | 1,179,367,195 | PR_kwDODunzps408YnW | 4,006 | Use audio feature in ASR task template | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-03-24T11:15:22Z | 2022-03-24T17:19:29Z | 2022-03-24T16:48:02Z | MEMBER | null | 0 | {
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} | The AutomaticSpeechRecognition task template is outdated: it still uses the file path column as input instead of the audio column.
I changed that and updated all the datasets as well as the tests.
The only community dataset that will need to be updated is `facebook/multilingual_librispeech`. It has almost zero usage unfortunately (probably because users load the duplicate `multilingual_librispeech` directly instead), but it means we can update it.
(this makes me think that we should deprecate `multilingual_librispeech` it and redirect users to `facebook/multilingual_librispeech`).
This PR is also useful for the AudioFolder in https://github.com/huggingface/datasets/pull/3963 | {
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https://api.github.com/repos/huggingface/datasets/issues/5014 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5014/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5014/comments | https://api.github.com/repos/huggingface/datasets/issues/5014/events | https://github.com/huggingface/datasets/issues/5014 | 1,383,422,639 | I_kwDODunzps5SdVqv | 5,014 | I need to read the custom dataset in conll format | {
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"Hi! We don't currently have a builder for parsing custom `conll` datasets, but I guess we could add one as a packaged module (similarly to what [TFDS](https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/core/dataset_builders/conll/conll_dataset_builder.py) did). @lhoestq @albertvillanova WDYT?\r... | 2022-09-23T07:49:42Z | 2022-11-02T11:57:15Z | null | NONE | null | null | null | I need to read the custom dataset in conll format
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https://api.github.com/repos/huggingface/datasets/issues/2528 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2528/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2528/comments | https://api.github.com/repos/huggingface/datasets/issues/2528/events | https://github.com/huggingface/datasets/issues/2528 | 926,314,656 | MDU6SXNzdWU5MjYzMTQ2NTY= | 2,528 | Logging cannot be set to NOTSET similar to transformers | {
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"Hi @joshzwiebel, thanks for reporting. We are going to align with `transformers`."
] | 2021-06-21T15:04:54Z | 2021-06-24T14:42:47Z | 2021-06-24T14:42:47Z | NONE | null | null | null | ## Describe the bug
In the transformers library you can set the verbosity level to logging.NOTSET to work around the usage of tqdm and IPywidgets, however in Datasets this is no longer possible. This is because transformers set the verbosity level of tqdm with [this](https://github.com/huggingface/transformers/blob/b53bc55ba9bb10d5ee279eab51a2f0acc5af2a6b/src/transformers/file_utils.py#L1449)
`disable=bool(logging.get_verbosity() == logging.NOTSET)`
and datasets accomplishes this like [so](https://github.com/huggingface/datasets/blob/83554e410e1ab8c6f705cfbb2df7953638ad3ac1/src/datasets/utils/file_utils.py#L493)
`not_verbose = bool(logger.getEffectiveLevel() > WARNING)`
## Steps to reproduce the bug
```python
import datasets
import logging
datasets.logging.get_verbosity = lambda : logging.NOTSET
datasets.load_dataset("patrickvonplaten/librispeech_asr_dummy")
```
## Expected results
The code should download and load the dataset as normal without displaying progress bars
## Actual results
```ImportError Traceback (most recent call last)
<ipython-input-4-aec65c0509c6> in <module>
----> 1 datasets.load_dataset("patrickvonplaten/librispeech_asr_dummy")
~/venv/lib/python3.7/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, script_version, use_auth_token, task, **config_kwargs)
713 dataset=True,
714 return_resolved_file_path=True,
--> 715 use_auth_token=use_auth_token,
716 )
717 # Set the base path for downloads as the parent of the script location
~/venv/lib/python3.7/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, dynamic_modules_path, return_resolved_file_path, **download_kwargs)
350 file_path = hf_bucket_url(path, filename=name, dataset=False)
351 try:
--> 352 local_path = cached_path(file_path, download_config=download_config)
353 except FileNotFoundError:
354 raise FileNotFoundError(
~/venv/lib/python3.7/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
289 use_etag=download_config.use_etag,
290 max_retries=download_config.max_retries,
--> 291 use_auth_token=download_config.use_auth_token,
292 )
293 elif os.path.exists(url_or_filename):
~/venv/lib/python3.7/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag, max_retries, use_auth_token)
668 headers=headers,
669 cookies=cookies,
--> 670 max_retries=max_retries,
671 )
672
~/venv/lib/python3.7/site-packages/datasets/utils/file_utils.py in http_get(url, temp_file, proxies, resume_size, headers, cookies, timeout, max_retries)
493 initial=resume_size,
494 desc="Downloading",
--> 495 disable=not_verbose,
496 )
497 for chunk in response.iter_content(chunk_size=1024):
~/venv/lib/python3.7/site-packages/tqdm/notebook.py in __init__(self, *args, **kwargs)
217 total = self.total * unit_scale if self.total else self.total
218 self.container = self.status_printer(
--> 219 self.fp, total, self.desc, self.ncols)
220 self.sp = self.display
221
~/venv/lib/python3.7/site-packages/tqdm/notebook.py in status_printer(_, total, desc, ncols)
95 if IProgress is None: # #187 #451 #558 #872
96 raise ImportError(
---> 97 "IProgress not found. Please update jupyter and ipywidgets."
98 " See https://ipywidgets.readthedocs.io/en/stable"
99 "/user_install.html")
ImportError: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.0
- Platform: Linux-5.4.95-42.163.amzn2.x86_64-x86_64-with-debian-10.8
- Python version: 3.7.10
- PyArrow version: 3.0.0
I am running this code on Deepnote and which important to this issue **does not** support IPywidgets
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https://api.github.com/repos/huggingface/datasets/issues/1623 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1623/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1623/comments | https://api.github.com/repos/huggingface/datasets/issues/1623/events | https://github.com/huggingface/datasets/pull/1623 | 772,950,710 | MDExOlB1bGxSZXF1ZXN0NTQ0MTI2ODQ4 | 1,623 | Add CLIMATE-FEVER dataset | {
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"Thank you @lhoestq for your comments! 😄 I added your suggested changes, ran the tests and regenerated `dataset_infos.json` and `dummy_data`."
] | 2020-12-22T13:34:05Z | 2020-12-22T17:53:53Z | 2020-12-22T17:53:53Z | CONTRIBUTOR | null | 0 | {
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} | As suggested by @SBrandeis , fresh PR that adds CLIMATE-FEVER. Replaces PR #1579.
---
A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim totalling in 7,675 claim-evidence pairs. The dataset features challenging claims that relate multiple facets and disputed cases of claims where both supporting and refuting evidence are present.
More information can be found at:
* Homepage: http://climatefever.ai
* Paper: https://arxiv.org/abs/2012.00614 | {
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https://api.github.com/repos/huggingface/datasets/issues/1971 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1971/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1971/comments | https://api.github.com/repos/huggingface/datasets/issues/1971/events | https://github.com/huggingface/datasets/pull/1971 | 819,714,231 | MDExOlB1bGxSZXF1ZXN0NTgyNzgyNTU0 | 1,971 | Fix ArrowWriter closes stream at exit | {
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"Oh nice thanks for adding the context manager ! All the streams and RecordBatchWriter will be properly closed now. Hopefully this gives a better experience on windows on which it's super important to close stuff.\r\n\r\nNot sure about the error, it looks like a process crashed silently.\r\nLet me take a look",
"... | 2021-03-02T07:12:34Z | 2021-03-10T16:36:57Z | 2021-03-10T16:36:57Z | MEMBER | null | 0 | {
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} | Current implementation of ArrowWriter does not properly release the `stream` resource (by closing it) if its `finalize()` method is not called and/or an Exception is raised before/during the call to its `finalize()` method.
Therefore, ArrowWriter should be used as a context manager that properly closes its `stream` resource at exit. | {
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https://api.github.com/repos/huggingface/datasets/issues/4873 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4873/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4873/comments | https://api.github.com/repos/huggingface/datasets/issues/4873/events | https://github.com/huggingface/datasets/issues/4873 | 1,347,592,022 | I_kwDODunzps5QUp9W | 4,873 | Multiple dataloader memory error | {
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"Hi!\r\n\r\n200+ data loaders is a lot. Have you tried to reduce the number of datasets by concatenating/interleaving the ones with the same structure/task (the API is `{concatenate_datasets/interleave_datasets}([dset1, ..., dset_N])`)?",
"Hi @mariosasko, thank you for your reply. I tried pre-concatenating differ... | 2022-08-23T08:59:50Z | 2023-01-26T02:01:11Z | null | NONE | null | null | null | For the use of multiple datasets and tasks, we use around more than 200+ dataloaders, then pass it into `dataloader1, dataloader2, ..., dataloader200=accelerate.prepare(dataloader1, dataloader2, ..., dataloader200)`
It causes the memory error when generating batches. Any solutions to it?
```bash
File "/home/xxx/my_code/src/utils/data_utils.py", line 54, in generate_batch
x = next(iterator)
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/accelerate/data_loader.py", line 301, in __iter__
for batch in super().__iter__():
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 435, in __next__
data = self._next_data()
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 475, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 28, in fetch
data.append(next(self.dataset_iter))
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/accelerate/data_loader.py", line 249, in __iter__
for element in self.dataset:
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 503, in __iter__
for key, example in self._iter():
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 500, in _iter
yield from ex_iterable
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 231, in __iter__
new_key = "_".join(str(key) for key in keys)
MemoryError
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5681 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5681/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5681/comments | https://api.github.com/repos/huggingface/datasets/issues/5681/events | https://github.com/huggingface/datasets/issues/5681 | 1,645,630,784 | I_kwDODunzps5iFlVA | 5,681 | Add information about patterns search order to the doc about structuring repo | {
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"gi... | null | [
"Good idea, I think I've seen this a couple of times before too on the forums. I can work on this :)",
"Closed in #5693 "
] | 2023-03-29T11:44:49Z | 2023-04-03T18:31:11Z | 2023-04-03T18:31:11Z | CONTRIBUTOR | null | null | null | Following [this](https://github.com/huggingface/datasets/issues/5650) issue I think we should add a note about the order of patterns that is used to find splits, see [my comment](https://github.com/huggingface/datasets/issues/5650#issuecomment-1488412527). Also we should reference this page in pages about packaged loaders.
I have a déjà vu that it had already been discussed as some point but I don't remember.... | {
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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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https://api.github.com/repos/huggingface/datasets/issues/5456 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5456/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5456/comments | https://api.github.com/repos/huggingface/datasets/issues/5456/events | https://github.com/huggingface/datasets/pull/5456 | 1,553,905,148 | PR_kwDODunzps5IXq92 | 5,456 | feat: tqdm for `to_parquet` | {
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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... | 2023-01-23T22:05:38Z | 2023-01-24T11:26:47Z | 2023-01-24T11:17:12Z | CONTRIBUTOR | null | 0 | {
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} | As described in #5418
I noticed also that the `to_json` function supports multi-workers whereas `to_parquet`, is that not possible/not needed with Parquet or something that hasn't been implemented yet? | {
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https://api.github.com/repos/huggingface/datasets/issues/5325 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5325/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5325/comments | https://api.github.com/repos/huggingface/datasets/issues/5325/events | https://github.com/huggingface/datasets/issues/5325 | 1,471,536,822 | I_kwDODunzps5Xtd62 | 5,325 | map(...batch_size=None) for IterableDataset | {
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"Hi! I agree it makes sense for `IterableDataset.map` to support the `batch_size=None` case. This should be super easy to fix.",
"@mariosasko as this is something simple maybe I can include it as part of https://github.com/huggingface/datasets/pull/5311? Let me know :+1:",
"#self-assign",
"Feel free to close ... | 2022-12-01T15:43:42Z | 2022-12-07T15:54:43Z | 2022-12-07T15:54:42Z | CONTRIBUTOR | null | null | null | ### Feature request
Dataset.map(...) allows batch_size to be None. It would be nice if IterableDataset did too.
### Motivation
Although it may seem a bit of a spurious request given that `IterableDataset` is meant for larger than memory datasets, but there are a couple of reasons why this might be nice.
One is that load_dataset(...) can return either IterableDataset or Dataset. mypy will then complain if batch_size=None even if we know it is Dataset. Of course we can do:
assert isinstance(d, datasets.DatasetDict)
But it is a mild inconvenience. What's more annoying is that whenever we use something like e.g. `combine_datasets(...)`, we end up with the union again, and so have to do the assert again.
Another is that we could actually end up with an IterableDataset small enough for memory in normal/correct usage, e.g. by filtering a massive IterableDataset.
For practical usages, an alternative to this would be to convert from an iterable dataset to a map-style dataset, but it is not obvious how to do this.
### Your contribution
Not this time. | {
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https://api.github.com/repos/huggingface/datasets/issues/4087 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4087/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4087/comments | https://api.github.com/repos/huggingface/datasets/issues/4087/events | https://github.com/huggingface/datasets/pull/4087 | 1,191,819,805 | PR_kwDODunzps41lnfO | 4,087 | Fix BeamWriter output Parquet file | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-04-04T13:46:50Z | 2022-04-05T15:00:40Z | 2022-04-05T14:54:48Z | MEMBER | null | 0 | {
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} | Since now, the `BeamWriter` saved a Parquet file with a simplified schema, where each field value was serialized to JSON. That resulted in Parquet files larger than Arrow files.
This PR:
- writes Parquet file preserving original schema and without serialization, thus avoiding serialization overhead and resulting in a smaller output file size.
- fixes `parquet_to_arrow` function | {
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https://api.github.com/repos/huggingface/datasets/issues/4335 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4335/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4335/comments | https://api.github.com/repos/huggingface/datasets/issues/4335/events | https://github.com/huggingface/datasets/pull/4335 | 1,234,157,123 | PR_kwDODunzps43usJP | 4,335 | Eval metadata batch 1: BillSum, CoNLL2003, CoNLLPP, CUAD, Emotion, GigaWord, GLUE, Hate Speech 18, Hate Speech | {
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"Summary of CircleCI errors:\r\n- **BoolQ**: missing 8 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', 'source_datasets', 'task_categories', and 'task_ids'\r\n- **Conllpp**: expected some content in section `Citation Information` but it i... | 2022-05-12T15:28:16Z | 2022-05-16T16:31:10Z | 2022-05-16T16:23:09Z | NONE | null | 0 | {
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} | Adding evaluation metadata for:
- BillSum
- CoNLL2003
- CoNLLPP
- CUAD
- Emotion
- GigaWord
- GLUE
- Hate Speech 18
- Hate Speech Offensive | {
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https://api.github.com/repos/huggingface/datasets/issues/2469 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2469/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2469/comments | https://api.github.com/repos/huggingface/datasets/issues/2469/events | https://github.com/huggingface/datasets/pull/2469 | 916,440,418 | MDExOlB1bGxSZXF1ZXN0NjY2MTA1OTk1 | 2,469 | Bump tqdm version | {
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"i tried both the latest version of `tqdm` and the version required by `autonlp` - no luck with windows 😞 \r\n\r\nit's very weird that a progress bar would trigger these kind of errors, so i'll have a look to see if it's something unique to `datasets`",
"Closing since this is now fixed in #2482 "
] | 2021-06-09T17:24:40Z | 2021-06-11T15:03:42Z | 2021-06-11T15:03:36Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3829 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3829/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3829/comments | https://api.github.com/repos/huggingface/datasets/issues/3829/events | https://github.com/huggingface/datasets/issues/3829 | 1,160,154,352 | I_kwDODunzps5FJozw | 3,829 | [📄 Docs] Create a `datasets` performance guide. | {
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"Hi ! Yes this is definitely something we'll explore, since optimizing processing pipelines can be challenging and because performance is key here: we want anyone to be able to play with large-scale datasets more easily.\r\n\r\nI think we'll start by documenting the performance of the dataset transforms we provide,... | 2022-03-05T00:28:06Z | 2022-03-10T16:24:27Z | null | NONE | null | null | null | ## Brief Overview
Downloading, saving, and preprocessing large datasets from the `datasets` library can often result in [performance bottlenecks](https://github.com/huggingface/datasets/issues/3735). These performance snags can be challenging to identify and to debug, especially for users who are less experienced with building deep learning experiments.
## Feature Request
Could we create a performance guide for using `datasets`, similar to:
* [Better performance with the `tf.data` API](https://github.com/huggingface/datasets/issues/3735)
* [Analyze `tf.data` performance with the TF Profiler](https://www.tensorflow.org/guide/data_performance_analysis)
This performance guide should detail practical options for improving performance with `datasets`, and enumerate any common best practices. It should also show how to use tools like the PyTorch Profiler or the TF Profiler to identify any performance bottlenecks (example below).
## Related Issues
* [wiki_dpr pre-processing performance #1670](https://github.com/huggingface/datasets/issues/1670)
* [Adjusting chunk size for streaming datasets #3499](https://github.com/huggingface/datasets/issues/3499)
* [how large datasets are handled under the hood #1004](https://github.com/huggingface/datasets/issues/1004)
* [using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? #1830](https://github.com/huggingface/datasets/issues/1830)
* [Best way to batch a large dataset? #315](https://github.com/huggingface/datasets/issues/315)
* [Saving processed dataset running infinitely #1911](https://github.com/huggingface/datasets/issues/1911) | {
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https://api.github.com/repos/huggingface/datasets/issues/4496 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4496/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4496/comments | https://api.github.com/repos/huggingface/datasets/issues/4496/events | https://github.com/huggingface/datasets/pull/4496 | 1,271,945,704 | PR_kwDODunzps45sUnW | 4,496 | Replace `assertEqual` with `assertTupleEqual` in unit tests for verbosity | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"FYI I used the following regex to look for the `assertEqual` statements where the assertion was being done over a Tuple: `self.assertEqual(.*, \\(.*,)(\\)\\))$`, hope this is useful!"
] | 2022-06-15T09:29:16Z | 2022-07-07T17:06:51Z | 2022-07-07T16:55:48Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1887 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1887/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1887/comments | https://api.github.com/repos/huggingface/datasets/issues/1887/events | https://github.com/huggingface/datasets/pull/1887 | 809,229,809 | MDExOlB1bGxSZXF1ZXN0NTc0MTI2NTMy | 1,887 | Implement to_csv for Dataset | {
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"@lhoestq I stumbled upon an interesting failure when adding tests for CSV serialization of `ArrayXD` features (see the failing unit tests in the CI)\r\n\r\nIt's due to the fact that booleans cannot be converted from arrow format to numpy without copy: https://arrow.apache.org/docs/python/generated/pyarrow.Array.ht... | 2021-02-16T11:27:29Z | 2021-02-19T09:41:59Z | 2021-02-19T09:41:59Z | CONTRIBUTOR | null | 0 | {
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} | cc @thomwolf
`to_csv` supports passing either a file path or a *binary* file object
The writing is batched to avoid loading the whole table in memory | {
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https://api.github.com/repos/huggingface/datasets/issues/2930 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2930/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2930/comments | https://api.github.com/repos/huggingface/datasets/issues/2930/events | https://github.com/huggingface/datasets/issues/2930 | 998,154,311 | I_kwDODunzps47fqBH | 2,930 | Mutable columns argument breaks set_format | {
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"Pushed a fix to my branch #2731 "
] | 2021-09-16T12:27:22Z | 2021-09-16T13:50:53Z | 2021-09-16T13:50:53Z | MEMBER | null | null | null | ## Describe the bug
If you pass a mutable list to the `columns` argument of `set_format` and then change the list afterwards, the returned columns also change.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("glue", "cola")
column_list = ["idx", "label"]
dataset.set_format("python", columns=column_list)
column_list[1] = "foo" # Change the list after we call `set_format`
dataset['train'][:4].keys()
```
## Expected results
```python
dict_keys(['idx', 'label'])
```
## Actual results
```python
dict_keys(['idx'])
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4312 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4312/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4312/comments | https://api.github.com/repos/huggingface/datasets/issues/4312/events | https://github.com/huggingface/datasets/pull/4312 | 1,231,662,775 | PR_kwDODunzps43mlug | 4,312 | added TR-News dataset | {
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"Thanks for your contribution, @batubayk.\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\nI would suggest you create this dataset there. Please, feel free to tell us if you need some help."
] | 2022-05-10T20:33:00Z | 2022-10-03T09:36:45Z | 2022-10-03T09:36:45Z | NONE | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5225 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5225/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5225/comments | https://api.github.com/repos/huggingface/datasets/issues/5225/events | https://github.com/huggingface/datasets/issues/5225 | 1,444,305,183 | I_kwDODunzps5WFlkf | 5,225 | Add video feature | {
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"@NielsRogge @rwightman may have additional requirements regarding this feature.\r\n\r\nWhen adding a new (decodable) type, the hardest part is choosing the right decoding library. What I mean by \"right\" here is that it has all the features we need and is easy to install (with GPU support?).\r\n\r\nSome candidate... | 2022-11-10T17:36:11Z | 2022-12-02T15:13:15Z | null | CONTRIBUTOR | null | null | null | ### Feature request
Add a `Video` feature to the library so folks can include videos in their datasets.
### Motivation
Being able to load Video data would be quite helpful. However, there are some challenges when it comes to videos:
1. Videos, unlike images, can end up being extremely large files
2. Often times when training video models, you need to do some very specific sampling. Videos might end up needing to be broken down into X number of clips used for training/inference
3. Videos have an additional audio stream, which must be accounted for
4. The feature needs to be able to encode/decode videos (with right video settings) from bytes.
### Your contribution
I did work on this a while back in [this (now closed) PR](https://github.com/huggingface/datasets/pull/4532). It used a library I made called [encoded_video](https://github.com/nateraw/encoded-video), which is basically the utils from [pytorchvideo](https://github.com/facebookresearch/pytorchvideo), but without the `torch` dep. It included the ability to read/write from bytes, as we need to do here. We don't want to be using a sketchy library that I made as a dependency in this repo, though.
Would love to use this issue as a place to:
- brainstorm ideas on how to do this right
- list ways/examples to work around it for now
CC @sayakpaul @mariosasko @fcakyon | {
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https://api.github.com/repos/huggingface/datasets/issues/1407 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1407/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1407/comments | https://api.github.com/repos/huggingface/datasets/issues/1407/events | https://github.com/huggingface/datasets/pull/1407 | 760,581,756 | MDExOlB1bGxSZXF1ZXN0NTM1Mzg5ODQx | 1,407 | Add Tweet Eval Dataset | {
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"Hi @lhoestq,\r\n\r\nSeeing that it has been almost two months to this draft, I'm willing to take this forward if you and @abhishekkrthakur don't mind. :)",
"Hi @gchhablani !\r\nSure if @abhishekkrthakur doesn't mind\r\nThanks for your help :)",
"Please feel free :) ",
"Hi @lhoestq, @abhishekkrthakur \r\n\r\n... | 2020-12-09T18:48:57Z | 2023-09-24T09:52:03Z | 2021-02-26T08:54:04Z | MEMBER | null | 1 | {
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https://api.github.com/repos/huggingface/datasets/issues/1492 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1492/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1492/comments | https://api.github.com/repos/huggingface/datasets/issues/1492/events | https://github.com/huggingface/datasets/pull/1492 | 762,965,239 | MDExOlB1bGxSZXF1ZXN0NTM3NDYxMjc3 | 1,492 | OPUS UBUNTU dataset | {
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"merging since the CI is fixed on master"
] | 2020-12-11T22:01:37Z | 2020-12-17T14:38:16Z | 2020-12-17T14:38:15Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4804 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4804/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4804/comments | https://api.github.com/repos/huggingface/datasets/issues/4804/events | https://github.com/huggingface/datasets/issues/4804 | 1,332,630,358 | I_kwDODunzps5PblNW | 4,804 | streaming dataset with concatenating splits raises an error | {
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"Hi! Only the name of a particular split (\"train\", \"test\", ...) is supported as a split pattern if `streaming=True`. We plan to address this limitation soon.",
"Hi, have you addressed this yet?",
"yes, same error occurs.\r\n```python\r\nfrom datasets import load_dataset\r\n\r\n# error\r\nrepo = \"nateraw/ad... | 2022-08-09T02:41:56Z | 2023-05-11T01:42:59Z | null | NONE | null | null | null | ## Describe the bug
streaming dataset with concatenating splits raises an error
## Steps to reproduce the bug
```python
from datasets import load_dataset
# no error
repo = "nateraw/ade20k-tiny"
dataset = load_dataset(repo, split="train+validation")
```
```python
from datasets import load_dataset
# error
repo = "nateraw/ade20k-tiny"
dataset = load_dataset(repo, split="train+validation", streaming=True)
```
```sh
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
[<ipython-input-4-a6ae02d63899>](https://localhost:8080/#) in <module>()
3 # error
4 repo = "nateraw/ade20k-tiny"
----> 5 dataset = load_dataset(repo, split="train+validation", streaming=True)
1 frames
[/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in as_streaming_dataset(self, split, base_path)
1030 splits_generator = splits_generators[split]
1031 else:
-> 1032 raise ValueError(f"Bad split: {split}. Available splits: {list(splits_generators)}")
1033
1034 # Create a dataset for each of the given splits
ValueError: Bad split: train+validation. Available splits: ['validation', 'train']
```
[Colab](https://colab.research.google.com/drive/1wMj08_0bym9jnGgByib4lsBPu8NCZBG9?usp=sharing)
## Expected results
load successfully or throws an error saying it is not supported.
## Actual results
above
## Environment info
- `datasets` version: 2.4.0
- Platform: Windows-10-10.0.22000-SP0 (windows11 x64)
- Python version: 3.9.13
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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https://api.github.com/repos/huggingface/datasets/issues/3231 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3231/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3231/comments | https://api.github.com/repos/huggingface/datasets/issues/3231/events | https://github.com/huggingface/datasets/pull/3231 | 1,047,170,906 | PR_kwDODunzps4uNmWT | 3,231 | Group tests in multiprocessing workers by test file | {
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} | By grouping tests by test file, we make sure that all the tests in `test_load.py` are sent to the same worker.
Therefore, the fixture `hf_token` will be called only once (and from the same worker).
Related to: #3200.
Fix #3219. | {
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https://api.github.com/repos/huggingface/datasets/issues/1829 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1829/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1829/comments | https://api.github.com/repos/huggingface/datasets/issues/1829/events | https://github.com/huggingface/datasets/pull/1829 | 802,693,600 | MDExOlB1bGxSZXF1ZXN0NTY4NzgzNjA5 | 1,829 | Add Tweet Eval Dataset | {
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} | Closes Draft PR #1407.
Notes:
1. I have excluded `mapping.txt` from the dataset at it only contained the name mappings, which are already present in the ClassLabels.
2. I have also exluded the textual names for the emojis mentioned in the [mapping](https://github.com/cardiffnlp/tweeteval/blob/main/datasets/emoji/mapping.txt).
3. I do not understand @abhishekkrthakur's example generator on #1407. Maybe he was trying to build up on code from some other dataset.
Requesting @lhoestq to review. | {
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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/6290 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6290/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6290/comments | https://api.github.com/repos/huggingface/datasets/issues/6290/events | https://github.com/huggingface/datasets/issues/6290 | 1,935,629,679 | I_kwDODunzps5zX11v | 6,290 | Incremental dataset (e.g. `.push_to_hub(..., append=True)`) | {
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"Yea I think waiting for #6269 would be best, or branching from it. For reference, this [PR](https://github.com/LAION-AI/Discord-Scrapers/pull/2) is progressing pretty well which will do similar using the hf hub for our LAION dataset bot https://github.com/LAION-AI/Discord-Scrapers/pull/2. "
] | 2023-10-10T15:18:03Z | 2023-10-13T16:05:26Z | null | CONTRIBUTOR | null | null | null | ### Feature request
Have the possibility to do `ds.push_to_hub(..., append=True)`.
### Motivation
Requested in this [comment](https://huggingface.co/datasets/laion/dalle-3-dataset/discussions/3#65252597c4edc168202a5eaa) and
this [comment](https://huggingface.co/datasets/laion/dalle-3-dataset/discussions/4#6524f675c9607bdffb208d8f). Discussed internally on [slack](https://huggingface.slack.com/archives/C02EMARJ65P/p1696950642610639?thread_ts=1690554266.830949&cid=C02EMARJ65P).
### Your contribution
What I suggest to do for parquet datasets is to use `CommitOperationCopy` + `CommitOperationDelete` from `huggingface_hub`:
1. list files
2. copy files from parquet-0001-of-0004 to parquet-0001-of-0005
3. delete files like parquet-0001-of-0004
4. generate + add last parquet file parquet-0005-of-0005
=> make a single commit with all commit operations at once
I think it should be quite straightforward to implement. Happy to review a PR (maybe conflicting with the ongoing "1 commit push_to_hub" PR https://github.com/huggingface/datasets/pull/6269) | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"@mariosasko Sorry, I didn't check tests/style after doing a merge from the Git UI last week. Thx for fixing. \r\n\r\nFYI I'm getting \"Only those with [write access](https://docs.github.com/articles/what-are-the-different-access-perm... | 2022-12-13T22:35:51Z | 2023-01-05T16:46:31Z | 2023-01-05T15:59:51Z | CONTRIBUTOR | null | 0 | {
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} | Invoking `{load,save}_from_dict` results in resource leak warnings, this should fix.
Introduces no significant logic changes. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6220). 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... | 2023-09-06T15:40:33Z | 2023-09-06T15:52:33Z | 2023-09-06T15:41:13Z | MEMBER | null | 0 | {
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"Hi @hazalturkmen, thanks for reporting.\r\n\r\nNote that your dataset repository does not contain any loading script; it only contains a data file named `tr_article_2`.\r\n\r\nWhen there is no loading script but only data files, the `datasets` library tries to infer how to load the data by looking at the data file... | 2022-03-25T07:12:02Z | 2022-04-04T08:05:01Z | 2022-03-25T14:16:11Z | NONE | null | null | null | ## Dataset viewer issue for '*hazal/Turkish-Biomedical-corpus-trM'
**Link:** *https://huggingface.co/datasets/hazal/Turkish-Biomedical-corpus-trM*
*I cannot see the dataset preview.*
```
Server Error
Status code: 400
Exception: HTTPError
Message: 403 Client Error: Forbidden for url: https://huggingface.co/api/datasets/hazal/Turkish-Biomedical-corpus-trM?full=true
```
Am I the one who added this dataset ? Yes
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https://api.github.com/repos/huggingface/datasets/issues/5166 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5166/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5166/comments | https://api.github.com/repos/huggingface/datasets/issues/5166/events | https://github.com/huggingface/datasets/pull/5166 | 1,423,629,582 | PR_kwDODunzps5Bj5IQ | 5,166 | Support dill 0.3.6 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I think it hasn't been merged ? https://github.com/uqfoundation/dill/pull/501\r\n\r\nThough I can see that the CI is green because it uses dill 0.3.1.1 - we should probably fix the dill version in both CIs:\r\n- use 0.3.1.1 for the C... | 2022-10-26T08:24:59Z | 2022-10-28T05:41:05Z | 2022-10-28T05:38:14Z | MEMBER | null | 0 | {
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} | This PR:
- ~~Unpins dill to allow installing dill>=0.3.6~~
- ~~Removes the fix on dill for >=0.3.6 because they implemented a deterministic mode (to be confirmed by @anivegesana)~~
- Pins dill<0.3.7 to allow latest dill 0.3.6
- Implements a fix for dill `save_function` for dill 0.3.6
- Additionally had to implement a fix for dill `save_code` and `_save_regex` for dill 0.3.6
- Fixes the CI so that the latest dill version is tested (besides the minimum 0.3.1.1 required by apache-beam 2.42.0)
Fix #5162. | {
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https://api.github.com/repos/huggingface/datasets/issues/6264 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6264/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6264/comments | https://api.github.com/repos/huggingface/datasets/issues/6264/events | https://github.com/huggingface/datasets/pull/6264 | 1,914,958,781 | PR_kwDODunzps5bTvzh | 6,264 | Temporarily pin tensorflow < 2.14.0 | {
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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... | 2023-09-27T08:16:06Z | 2023-09-27T08:45:24Z | 2023-09-27T08:36:39Z | MEMBER | null | 0 | {
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} | Temporarily pin tensorflow < 2.14.0 until permanent solution is found.
Hot fix #6263. | {
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} | Make sure that there's no duplidate keys in yaml tags.
I added the check in the yaml tree constructor's method, so that the verification is done at every level in the yaml structure.
cc @julien-c | {
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https://api.github.com/repos/huggingface/datasets/issues/1340 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1340/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1340/comments | https://api.github.com/repos/huggingface/datasets/issues/1340/events | https://github.com/huggingface/datasets/pull/1340 | 759,765,408 | MDExOlB1bGxSZXF1ZXN0NTM0NzExMjc5 | 1,340 | :fist: ¡Viva la Independencia! | {
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"I've added the changes / fixes - ready for a second pass :)"
] | 2020-12-08T20:43:43Z | 2020-12-14T10:36:01Z | 2020-12-14T10:36:01Z | MEMBER | null | 0 | {
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} | Adds the Catalonia Independence Corpus for stance-detection of Tweets.
Ready for review! | {
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https://api.github.com/repos/huggingface/datasets/issues/3499 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3499/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3499/comments | https://api.github.com/repos/huggingface/datasets/issues/3499/events | https://github.com/huggingface/datasets/issues/3499 | 1,090,132,618 | I_kwDODunzps5A-hqK | 3,499 | Adjusting chunk size for streaming datasets | {
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"Hi ! Data streaming uses `fsspec` to read the data files progressively. IIRC the block size for buffering is 5MiB by default. So every time you finish iterating over a block, it downloads the next one. You can still try to increase the `fsspec` block size for buffering if it can help. To do so you just need to inc... | 2021-12-28T21:17:53Z | 2022-05-06T16:29:05Z | 2022-05-06T16:29:05Z | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
I want to use mc4 which I cannot save locally, so I stream it. However, I want to process the entire dataset and filter some documents from it. With the current chunk size of around 1000 documents (right?) I hit a performance bottleneck because of the frequent decompressing.
**Describe the solution you'd like**
I would appreciate a parameter in the load_dataset function, that allows me to set the chunksize myself (to a value like 100'000 in my case). Like that, I hope to improve the processing time.
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https://api.github.com/repos/huggingface/datasets/issues/5829 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5829/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5829/comments | https://api.github.com/repos/huggingface/datasets/issues/5829/events | https://github.com/huggingface/datasets/issues/5829 | 1,699,958,189 | I_kwDODunzps5lU02t | 5,829 | (mach-o file, but is an incompatible architecture (have 'arm64', need 'x86_64')) | {
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"Can you paste the error stack trace?",
"That is weird. I can't reproduce it again after reboot.\r\n```python\r\nIn [2]: import platform\r\n\r\nIn [3]: platform.platform()\r\nOut[3]: 'macOS-13.2-arm64-arm-64bit'\r\n\r\nIn [4]: from datasets import load_dataset\r\n ...:\r\n ...: jazzy = load_dataset(\"nomic-ai... | 2023-05-08T10:07:14Z | 2023-06-30T11:39:14Z | 2023-05-09T00:46:42Z | NONE | null | null | null | ### Describe the bug
M2 MBP can't run
```python
from datasets import load_dataset
jazzy = load_dataset("nomic-ai/gpt4all-j-prompt-generations", revision='v1.2-jazzy')
```
### Steps to reproduce the bug
1. Use M2 MBP
2. Python 3.10.10 from pyenv
3. Run
```
from datasets import load_dataset
jazzy = load_dataset("nomic-ai/gpt4all-j-prompt-generations", revision='v1.2-jazzy')
```
### Expected behavior
Be able to run normally
### Environment info
```
from datasets import load_dataset
jazzy = load_dataset("nomic-ai/gpt4all-j-prompt-generations", revision='v1.2-jazzy')
```
OSX: 13.2
CPU: M2
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