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https://api.github.com/repos/huggingface/datasets/issues/5272 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5272/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5272/comments | https://api.github.com/repos/huggingface/datasets/issues/5272/events | https://github.com/huggingface/datasets/issues/5272 | 1,456,940,021 | I_kwDODunzps5W1yP1 | 5,272 | Use pyarrow Tensor dtype | [
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] | open | false | null | 15 | 2022-11-20T15:18:41Z | 2023-07-04T04:57:50Z | null | null | ### Feature request
I was going the discussion of converting tensors to lists.
Is there a way to leverage pyarrow's Tensors for nested arrays / embeddings?
For example:
```python
import pyarrow as pa
import numpy as np
x = np.array([[2, 2, 4], [4, 5, 100]], np.int32)
pa.Tensor.from_numpy(x, dim_names=["dim1","dim2"])
```
[Apache docs](https://arrow.apache.org/docs/python/generated/pyarrow.Tensor.html)
Maybe this belongs into the pyarrow features / repo.
### Motivation
Working with big data, we need to make sure to use the best data structures and IO out there
### Your contribution
Can try to a PR if code changes necessary | {
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"Hi ! We're using the Arrow format for the datasets, and PyArrow tensors are not part of the Arrow format AFAIK:\r\n\r\n> There is no direct support in the arrow columnar format to store Tensors as column values.\r\n\r\nsource: https://github.com/apache/arrow/issues/4802#issuecomment-508494694",
"@wesm @rok its b... |
https://api.github.com/repos/huggingface/datasets/issues/1574 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1574/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1574/comments | https://api.github.com/repos/huggingface/datasets/issues/1574/events | https://github.com/huggingface/datasets/pull/1574 | 767,015,317 | MDExOlB1bGxSZXF1ZXN0NTM5ODY1Mzcy | 1,574 | Diplomacy detection 3 | [] | closed | false | null | 0 | 2020-12-14T23:28:51Z | 2020-12-14T23:29:32Z | 2020-12-14T23:29:32Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2137 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2137/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2137/comments | https://api.github.com/repos/huggingface/datasets/issues/2137/events | https://github.com/huggingface/datasets/pull/2137 | 843,502,835 | MDExOlB1bGxSZXF1ZXN0NjAyODc0MDYw | 2,137 | Fix missing infos from concurrent dataset loading | [] | closed | false | null | 0 | 2021-03-29T15:46:12Z | 2021-03-31T10:35:56Z | 2021-03-31T10:35:55Z | null | This should fix issue #2131
When calling `load_dataset` at the same time from 2 workers, one of the worker could have missing split infos when reloading the dataset from the cache.
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https://api.github.com/repos/huggingface/datasets/issues/2904 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2904/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2904/comments | https://api.github.com/repos/huggingface/datasets/issues/2904/events | https://github.com/huggingface/datasets/issues/2904 | 995,814,222 | I_kwDODunzps47WutO | 2,904 | FORCE_REDOWNLOAD does not work | [
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] | open | false | null | 3 | 2021-09-14T09:45:26Z | 2021-10-06T09:37:19Z | null | null | ## Describe the bug
With GenerateMode.FORCE_REDOWNLOAD, the documentation says
+------------------------------------+-----------+---------+
| | Downloads | Dataset |
+====================================+===========+=========+
| `REUSE_DATASET_IF_EXISTS` (default)| Reuse | Reuse |
+------------------------------------+-----------+---------+
| `REUSE_CACHE_IF_EXISTS` | Reuse | Fresh |
+------------------------------------+-----------+---------+
| `FORCE_REDOWNLOAD` | Fresh | Fresh |
+------------------------------------+-----------+---------+
However, the old dataset is loaded even when FORCE_REDOWNLOAD is chosen.
## Steps to reproduce the bug
```python
import pandas as pd
from datasets import load_dataset, GenerateMode
pd.DataFrame(range(5), columns=['numbers']).to_csv('/tmp/test.tsv.gz', index=False)
ee = load_dataset('csv', data_files=['/tmp/test.tsv.gz'], delimiter='\t', split='train', download_mode=GenerateMode.FORCE_REDOWNLOAD)
print(ee)
pd.DataFrame(range(10), columns=['numerals']).to_csv('/tmp/test.tsv.gz', index=False)
ee = load_dataset('csv', data_files=['/tmp/test.tsv.gz'], delimiter='\t', split='train', download_mode=GenerateMode.FORCE_REDOWNLOAD)
print(ee)
```
## Expected results
Dataset({
features: ['numbers'],
num_rows: 5
})
Dataset({
features: ['numerals'],
num_rows: 10
})
## Actual results
Dataset({
features: ['numbers'],
num_rows: 5
})
Dataset({
features: ['numbers'],
num_rows: 5
})
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.0
- Platform: Linux-4.14.181-108.257.amzn1.x86_64-x86_64-with-glibc2.10
- Python version: 3.7.10
- PyArrow version: 3.0.0
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"Hi ! Thanks for reporting. The error seems to happen only if you use compressed files.\r\n\r\nThe second dataset is prepared in another dataset cache directory than the first - which is normal, since the source file is different. However, it doesn't uncompress the new data file because it finds the old uncompresse... |
https://api.github.com/repos/huggingface/datasets/issues/4673 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4673/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4673/comments | https://api.github.com/repos/huggingface/datasets/issues/4673/events | https://github.com/huggingface/datasets/issues/4673 | 1,301,010,331 | I_kwDODunzps5Ni9eb | 4,673 | load_datasets on csv returns everything as a string | [
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] | closed | false | null | 2 | 2022-07-11T17:30:24Z | 2022-07-12T13:33:09Z | 2022-07-12T13:33:08Z | null | ## Describe the bug
If you use:
`conll_dataset.to_csv("ner_conll.csv")`
It will create a csv file with all of your data as expected, however when you load it with:
`conll_dataset = load_dataset("csv", data_files="ner_conll.csv")`
everything is read in as a string. For example if I look at everything in 'ner_tags' I get back `['[3 0 7 0 0 0 7 0 0]', '[1 2]', '[5 0]']` instead of what I originally saved which was `[[3, 0, 7, 0, 0, 0, 7, 0, 0], [1, 2], [5, 0]]`
I think maybe there is something funky going on with the csv delimiter
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
#load original conll dataset
orig_conll = load_dataset("conll2003")
#save original conll as a csv
orig_conll.to_csv("ner_conll.csv")
#reload conll data as a csv
new_conll = load_dataset("csv", data_files="ner_conll.csv")`
```
## Expected results
A clear and concise description of the expected results.
I would expect the data be returned as the data type I saved it as. I.e. if I save a list of ints
[[3, 0, 7, 0, 0, 0, 7, 0, 0]], I shouldnt get back a string ['[3 0 7 0 0 0 7 0 0]']
I also get back a string when I pass a list of strings ['EU', 'rejects', 'German', 'call', 'to', 'boycott', 'British', 'lamb', '.']
## Actual results
A list of strings `['[3 0 7 0 0 0 7 0 0]', '[1 2]', '[5 0]']`
A string "['EU' 'rejects' 'German' 'call' 'to' 'boycott' 'British' 'lamb' '.']"
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Linux-5.4.0-121-generic-x86_64-with-glibc2.17
- Python version: 3.8.13
- PyArrow version: 8.0.0
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"Hi @courtneysprouse, thanks for reporting.\r\n\r\nYes, you are right: by default the \"csv\" loader loads all columns as strings. \r\n\r\nYou could tweak this behavior by passing the `feature` argument to `load_dataset`, but it is also true that currently it is not possible to perform some kind of casts, due to la... |
https://api.github.com/repos/huggingface/datasets/issues/6065 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6065/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6065/comments | https://api.github.com/repos/huggingface/datasets/issues/6065/events | https://github.com/huggingface/datasets/pull/6065 | 1,819,334,932 | PR_kwDODunzps5WR8jI | 6,065 | Add column type guessing from map return function | [] | closed | false | null | 5 | 2023-07-25T00:34:17Z | 2023-07-26T15:13:45Z | 2023-07-26T15:13:44Z | null | As discussed [here](https://github.com/huggingface/datasets/issues/5965), there are some cases where datasets is unable to automatically promote columns during mapping. The fix is to explicitly provide a `features` definition so pyarrow can configure itself with the right column types from the outset.
This PR provides an alternative approach, which is functionally equivalent to specifying features but a bit cleaner within a larger mapping pipeline. It allows clients to typehint the return variable coming from the mapper function - if we find one of these type annotations specified, and no explicit features have been passed in, we'll try to convert it into a Features map. If the map function runs and casting is unable to succeed, it will raise a DatasetTransformationNotAllowedError that indicates the typehint may be to blame. It works for batched and non-batched mapping functions.
Currently supported column types:
- builtins primitives: string, int, float, bool
- dictionaries, lists (nested and one-deep)
- Optional types and None-Unions (synonymous with optional types)
It's used like:
```python
class DatasetTyped(TypedDict):
texts: list[str]
def dataset_typed_map(batch) -> DatasetTyped:
return {"texts": [text.split() for text in batch["raw_text"]]}
dataset = {"raw_text": ["", "This is a test", "This is another test"]}
with Dataset.from_dict(dataset) as dset:
new_dataset = dset.map(
dataset_typed_map,
batched=True,
batch_size=1,
num_proc=1,
)
```
Open questions:
- Should logging indicate we have automatically guessed these types? Or proceed quietly until we hit an error (as is the current implementation). | {
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"Thanks for working on this. However, having thought about this issue a bit more, supporting this doesn't seem like a good idea - it's better to be explicit than implicit, according to the Zen of Python 🙂. Also, I don't think many users would use this, so this raises the question of whether this is something we wa... |
https://api.github.com/repos/huggingface/datasets/issues/4060 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4060/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4060/comments | https://api.github.com/repos/huggingface/datasets/issues/4060/events | https://github.com/huggingface/datasets/pull/4060 | 1,186,281,033 | PR_kwDODunzps41Tbmg | 4,060 | Deprecate canonical Multilingual Librispeech | [] | closed | false | null | 7 | 2022-03-30T10:56:56Z | 2022-04-01T12:54:05Z | 2022-04-01T12:48:51Z | null | Deprecate canonical Multilingual Librispeech in favor of [the community one](https://huggingface.co/datasets/facebook/multilingual_librispeech) which supports streaming.
However, there is a problem regarding new ASR template schema: since it's changed, I guess all community datasets that use this template do not work with new version of the library, including MLS. Should we somehow notify users about that or is it possible to change this line ourselves? For MLS specifically, I cannot change the code directly as I'm not the member of the Facebook org.
Hm, and the code should be change after the release, no? | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Yes, as discussed in #4006 we should update facebook/multilingual_librispeech indeed before we do a release. @anton-l could you help taking care of updating facebook/multilingual_librispeech ? We need to update the task template\r\n`... |
https://api.github.com/repos/huggingface/datasets/issues/162 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/162/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/162/comments | https://api.github.com/repos/huggingface/datasets/issues/162/events | https://github.com/huggingface/datasets/pull/162 | 620,513,554 | MDExOlB1bGxSZXF1ZXN0NDE5NzQ4Mzky | 162 | fix prev files hash in map | [] | closed | false | null | 3 | 2020-05-18T21:20:51Z | 2020-05-18T21:36:21Z | 2020-05-18T21:36:20Z | null | Fix the `.map` issue in #160.
This makes sure it takes the previous files when computing the hash. | {
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"Awesome! ",
"Hi, yes, this seems to fix #160 -- I cloned the branch locally and verified",
"Perfect then :)"
] |
https://api.github.com/repos/huggingface/datasets/issues/5992 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5992/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5992/comments | https://api.github.com/repos/huggingface/datasets/issues/5992/events | https://github.com/huggingface/datasets/pull/5992 | 1,776,460,964 | PR_kwDODunzps5UAk3C | 5,992 | speedup | [] | closed | false | null | 1 | 2023-06-27T09:17:58Z | 2023-06-27T09:23:07Z | 2023-06-27T09:18:04Z | null | null | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5992). All of your documentation changes will be reflected on that endpoint."
] |
https://api.github.com/repos/huggingface/datasets/issues/133 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/133/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/133/comments | https://api.github.com/repos/huggingface/datasets/issues/133/events | https://github.com/huggingface/datasets/issues/133 | 619,094,954 | MDU6SXNzdWU2MTkwOTQ5NTQ= | 133 | [Question] Using/adding a local dataset | [] | closed | false | null | 5 | 2020-05-15T16:26:06Z | 2020-07-23T16:44:09Z | 2020-07-23T16:44:09Z | null | Users may want to either create/modify a local copy of a dataset, or use a custom-built dataset with the same `Dataset` API as externally downloaded datasets.
It appears to be possible to point to a local dataset path rather than downloading the external ones, but I'm not exactly sure how to go about doing this.
A notebook/example script demonstrating this would be very helpful. | {
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"Hi @zphang,\r\n\r\nSo you can just give the local path to a dataset script file and it should work.\r\n\r\nHere is an example:\r\n- you can download one of the scripts in the `datasets` folder of the present repo (or clone the repo)\r\n- then you can load it with `load_dataset('PATH/TO/YOUR/LOCAL/SCRIPT.py')`\r\n\... |
https://api.github.com/repos/huggingface/datasets/issues/39 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/39/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/39/comments | https://api.github.com/repos/huggingface/datasets/issues/39/events | https://github.com/huggingface/datasets/pull/39 | 611,712,135 | MDExOlB1bGxSZXF1ZXN0NDEyODIxNTA4 | 39 | [Test] improve slow testing | [] | closed | false | null | 0 | 2020-05-04T08:58:33Z | 2020-05-04T08:59:50Z | 2020-05-04T08:59:49Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/660 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/660/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/660/comments | https://api.github.com/repos/huggingface/datasets/issues/660/events | https://github.com/huggingface/datasets/pull/660 | 706,324,032 | MDExOlB1bGxSZXF1ZXN0NDkwODkyMjQ0 | 660 | add openwebtext | [] | closed | false | null | 3 | 2020-09-22T12:05:22Z | 2020-10-06T09:20:10Z | 2020-09-28T09:07:26Z | null | This adds [The OpenWebText Corpus](https://skylion007.github.io/OpenWebTextCorpus/), which is a clean and large text corpus for nlp pretraining. It is an open source effort to reproduce OpenAI’s WebText dataset used by GPT-2, and it is also needed to reproduce ELECTRA.
It solves #132 .
### Besides dataset building script, I made some changes to the library.
1. Extract large amount of compressed files with multi processing
I add a `num_proc` argument to `DownloadManager.extract` and pass this `num_proc` to `map_nested`. So I can decompress 20 thousands compressed files faster. `num_proc` I add is default to `None`, so it shouldn't break any other thing.
2. In `cached_path`, I change the order to deal with different kind of compressed files (zip, tar, gzip)
Because there is no way to 100% detect a file is a zip file (see [this](https://stackoverflow.com/questions/18194688/how-can-i-determine-if-a-file-is-a-zip-file)), I found it wrongly detect `'./datasets/downloads/extracted/58764bd6898fa339b25d92e7fbbc3d8dbf64fb504edff1a30a1d7d99d1561027/openwebtext/urlsf_subset13-630_data.xz'` as a zip and try decompress it with zip, sure it will get error. So I made it detect wheter the file is tar or gzip first and detect zip in the last.
3. `MockDownloadManager.extract`
Cuz I pass `num_proc` to `DownloadManager.extract`, I also have to make `MockDownloadManager.extract` to accept extra keywork arguments. So I make it `extract(path, *args, **kwargs)`, but just return the path as original implementation.
**Note**: If there is better way for points mentioned above, thought I would like to help, unless we can solve point4 (make dataset building fast), I may not be able to afford rebuild the dataset again because of change of the dataset script (Building the dataset cost me 4 days).
### There is something I think we can improve
4. Long time to decompress compressed files
Even I decompress those 20 thousands compressed files with 12 process on my 16 core 3.x Ghz server. It still took about 3 ~ 4days to complete dataset building. Most of time spent on decompress those files.
### Info about the source data
The source data is an tar.xz file with following structure, files/directory beyond compressed file is what can we get after decompress it.
```
openwebtext.tar.xz
|__ openwebtext
|__subset000.xz
| |__ ....txt
| |__ ....txt
| ...
|__ subset001.xz
|
....
```
And this the structure of dummy data, same as the original one.
```
dummy_data.zip
|__ dummy_data
|__ openwebtext
|__fake_subset-1_data-dirxz # actually it is a directory
| |__ ....txt
| |__ ....txt
|__ fake_subset-2_data-dirxz
|__ ....txt
|__ ....txt
``` | {
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"BTW, is there a one-line command to make our building scripts pass flake8 test? (included code quality test), I got like trailing space or mixed space and tab warning and error, and fixed them manually.",
"> BTW, is there a one-line command to make our building scripts pass flake8 test? (included code quality te... |
https://api.github.com/repos/huggingface/datasets/issues/2672 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2672/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2672/comments | https://api.github.com/repos/huggingface/datasets/issues/2672/events | https://github.com/huggingface/datasets/pull/2672 | 947,294,605 | MDExOlB1bGxSZXF1ZXN0NjkyMjk2NDQ4 | 2,672 | Fix potential DuplicatedKeysError in LibriSpeech | [] | closed | false | null | 0 | 2021-07-19T06:00:49Z | 2021-07-19T06:28:57Z | 2021-07-19T06:28:56Z | null | DONE:
- Fix unnecessary path join.
- Fix potential DiplicatedKeysError by ensuring keys are unique.
We should promote as a good practice, that the keys should be programmatically generated as unique, instead of read from data (which might be not unique). | {
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https://api.github.com/repos/huggingface/datasets/issues/3565 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3565/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3565/comments | https://api.github.com/repos/huggingface/datasets/issues/3565/events | https://github.com/huggingface/datasets/pull/3565 | 1,099,296,693 | PR_kwDODunzps4wzjhH | 3,565 | Add parameter `preserve_index` to `from_pandas` | [] | closed | false | null | 2 | 2022-01-11T15:26:37Z | 2022-01-12T16:11:27Z | 2022-01-12T16:11:27Z | null | Added optional parameter, so that user can get rid of useless index preserving. [Issue](https://github.com/huggingface/datasets/issues/3563) | {
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"> \r\n\r\nI did `make style` and it affected over 500 files\r\n\r\n```\r\nAll done! ✨ 🍰 ✨\r\n575 files reformatted, 372 files left unchanged.\r\nisort tests src benchmarks datasets/**/*.py metri\r\n```\r\n\r\n(result)\r\n![image](https://user-images.githubusercontent.com/20703486/149166681-2f9d1bc4-116a-4f53-ad42... |
https://api.github.com/repos/huggingface/datasets/issues/3441 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3441/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3441/comments | https://api.github.com/repos/huggingface/datasets/issues/3441/events | https://github.com/huggingface/datasets/issues/3441 | 1,081,571,784 | I_kwDODunzps5Ad3nI | 3,441 | Add QuALITY dataset | [
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] | open | false | null | 1 | 2021-12-15T22:26:19Z | 2021-12-28T15:17:05Z | null | null | ## Adding a Dataset
- **Name:** QuALITY
- **Description:** A challenging question answering with very long contexts (Twitter [thread](https://twitter.com/sleepinyourhat/status/1471225421794529281?s=20))
- **Paper:** No ArXiv link yet, but draft is [here](https://github.com/nyu-mll/quality/blob/main/quality_preprint.pdf)
- **Data:** GitHub repo [here](https://github.com/nyu-mll/quality)
- **Motivation:** This dataset would serve as a nice way to benchmark long-range Transformer models like BigBird, Longformer and their descendants. In particular, it would be very interesting to see how the S4 model fares on this given it's impressive performance on the Long Range Arena
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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"I'll take this one if no one hasn't yet!"
] |
https://api.github.com/repos/huggingface/datasets/issues/2636 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2636/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2636/comments | https://api.github.com/repos/huggingface/datasets/issues/2636/events | https://github.com/huggingface/datasets/pull/2636 | 943,044,514 | MDExOlB1bGxSZXF1ZXN0Njg4NzEyMTY4 | 2,636 | Streaming for the Pandas loader | [] | closed | false | null | 0 | 2021-07-13T09:18:21Z | 2021-07-13T14:37:24Z | 2021-07-13T14:37:23Z | null | It was not using open in the builder. Therefore pd.read_pickle could fail when streaming from a private repo for example.
Indeed, when streaming, open is extended to support reading from remote files and handles authentication to the HF Hub | {
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https://api.github.com/repos/huggingface/datasets/issues/2335 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2335/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2335/comments | https://api.github.com/repos/huggingface/datasets/issues/2335/events | https://github.com/huggingface/datasets/issues/2335 | 881,291,887 | MDU6SXNzdWU4ODEyOTE4ODc= | 2,335 | Index error in Dataset.map | [
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] | closed | false | null | 0 | 2021-05-08T20:44:57Z | 2021-05-10T13:26:12Z | 2021-05-10T13:26:12Z | null | The following code, if executed on master, raises an IndexError (due to overflow):
```python
>>> from datasets import *
>>> d = load_dataset("bookcorpus", split="train")
Reusing dataset bookcorpus (C:\Users\Mario\.cache\huggingface\datasets\bookcorpus\plain_text\1.0.0\44662c4a114441c35200992bea923b170e6f13f2f0beb7c14e43759cec498700)
2021-05-08 21:23:46.859818: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
>>> d.map(lambda ex: ex)
0%|▎ | 289430/74004228 [00:13<58:41, 20935.33ex/s]c:\users\mario\desktop\projects\datasets-1\src\datasets\table.py:84: RuntimeWarning: overflow encountered in int_scalars
k = i + ((j - i) * (x - arr[i]) // (arr[j] - arr[i]))
0%|▎ | 290162/74004228 [00:13<59:11, 20757.23ex/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "c:\users\mario\desktop\projects\datasets-1\src\datasets\arrow_dataset.py", line 1498, in map
new_fingerprint=new_fingerprint,
File "c:\users\mario\desktop\projects\datasets-1\src\datasets\arrow_dataset.py", line 174, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "c:\users\mario\desktop\projects\datasets-1\src\datasets\fingerprint.py", line 340, in wrapper
out = func(self, *args, **kwargs)
File "c:\users\mario\desktop\projects\datasets-1\src\datasets\arrow_dataset.py", line 1799, in _map_single
for i, example in enumerate(pbar):
File "C:\Users\Mario\Anaconda3\envs\hf-datasets\lib\site-packages\tqdm\std.py", line 1133, in __iter__
for obj in iterable:
File "c:\users\mario\desktop\projects\datasets-1\src\datasets\arrow_dataset.py", line 1145, in __iter__
format_kwargs=format_kwargs,
File "c:\users\mario\desktop\projects\datasets-1\src\datasets\arrow_dataset.py", line 1337, in _getitem
pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
File "c:\users\mario\desktop\projects\datasets-1\src\datasets\formatting\formatting.py", line 368, in query_table
pa_subtable = _query_table(table, key)
File "c:\users\mario\desktop\projects\datasets-1\src\datasets\formatting\formatting.py", line 79, in _query_table
return table.fast_slice(key % table.num_rows, 1)
File "c:\users\mario\desktop\projects\datasets-1\src\datasets\table.py", line 128, in fast_slice
i = _interpolation_search(self._offsets, offset)
File "c:\users\mario\desktop\projects\datasets-1\src\datasets\table.py", line 91, in _interpolation_search
raise IndexError(f"Invalid query '{x}' for size {arr[-1] if len(arr) else 'none'}.")
IndexError: Invalid query '290162' for size 74004228.
```
Tested on Windows, can run on Linux if needed.
EDIT:
It seems like for this to happen, the default NumPy dtype has to be np.int32. | {
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https://api.github.com/repos/huggingface/datasets/issues/4592 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4592/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4592/comments | https://api.github.com/repos/huggingface/datasets/issues/4592/events | https://github.com/huggingface/datasets/issues/4592 | 1,288,029,377 | I_kwDODunzps5MxcTB | 4,592 | Issue with jalFaizy/detect_chess_pieces when running datasets-cli test | [] | closed | false | null | 3 | 2022-06-29T00:15:54Z | 2022-06-29T10:30:03Z | 2022-06-29T07:49:27Z | null | ### Link
https://huggingface.co/datasets/jalFaizy/detect_chess_pieces
### Description
I am trying to write a appropriate data loader for [a custom dataset](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces) using [this script](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces/blob/main/detect_chess_pieces.py)
When I run the command
`$ datasets-cli test "D:\workspace\HF\detect_chess_pieces" --save_infos --all_configs`
It gives the following error
```
Using custom data configuration default
Traceback (most recent call last):
File "c:\users\faiza\anaconda3\lib\runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "c:\users\faiza\anaconda3\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "C:\Users\faiza\anaconda3\Scripts\datasets-cli.exe\__main__.py", line 7, in <module>
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\commands\datasets_cli.py", line 39, in main
service.run()
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\commands\test.py", line 132, in run
for j, builder in enumerate(get_builders()):
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\commands\test.py", line 125, in get_builders
yield builder_cls(
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\builder.py", line 1148, in __init__
super().__init__(*args, **kwargs)
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\builder.py", line 306, in __init__
info = self.get_exported_dataset_info()
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\builder.py", line 405, in get_exported_dataset_info
return self.get_all_exported_dataset_infos().get(self.config.name, DatasetInfo())
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\builder.py", line 390, in get_all_exported_dataset_infos
return DatasetInfosDict.from_directory(cls.get_imported_module_dir())
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\info.py", line 309, in from_directory
dataset_infos_dict = {
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\info.py", line 310, in <dictcomp>
config_name: DatasetInfo.from_dict(dataset_info_dict)
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\info.py", line 272, in from_dict
return cls(**{k: v for k, v in dataset_info_dict.items() if k in field_names})
File "<string>", line 20, in __init__
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\info.py", line 160, in __post_init__
templates = [
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\info.py", line 161, in <listcomp>
template if isinstance(template, TaskTemplate) else task_template_from_dict(template)
File "c:\users\faiza\anaconda3\lib\site-packages\datasets\tasks\__init__.py", line 43, in task_template_from_dict
return template.from_dict(task_template_dict)
AttributeError: 'NoneType' object has no attribute 'from_dict'
```
My assumption is that there is some kind of issue in how the "task_templates" are read, because even if I keep them as None, or not include the argument at all, the same error occurs
### Owner
Yes | {
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"Hi @faizankshaikh\r\n\r\nPlease note that we have recently launched the Community feature, specifically targeted to create Discussions (about issues/questions/asking-for-help) on each Dataset on the Hub:\r\n- Blog post: https://huggingface.co/blog/community-update\r\n- Docs: https://huggingface.co/docs/hub/reposit... |
https://api.github.com/repos/huggingface/datasets/issues/6027 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6027/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6027/comments | https://api.github.com/repos/huggingface/datasets/issues/6027/events | https://github.com/huggingface/datasets/pull/6027 | 1,803,008,486 | PR_kwDODunzps5Va4g3 | 6,027 | Delete `task_templates` in `IterableDataset` when they are no longer valid | [] | closed | false | null | 3 | 2023-07-13T13:16:17Z | 2023-07-13T14:06:20Z | 2023-07-13T13:57:35Z | null | Fix #6025 | {
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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... |
https://api.github.com/repos/huggingface/datasets/issues/1166 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1166/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1166/comments | https://api.github.com/repos/huggingface/datasets/issues/1166/events | https://github.com/huggingface/datasets/pull/1166 | 757,721,208 | MDExOlB1bGxSZXF1ZXN0NTMzMDQ1NDUy | 1,166 | Opus montenegrinsubs | [] | closed | false | null | 1 | 2020-12-05T17:00:44Z | 2020-12-07T11:02:49Z | 2020-12-07T11:02:49Z | null | Opus montenegrinsubs - language pair en-me
more info : http://opus.nlpl.eu/MontenegrinSubs.php | {
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"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/3146 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3146/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3146/comments | https://api.github.com/repos/huggingface/datasets/issues/3146/events | https://github.com/huggingface/datasets/issues/3146 | 1,033,605,947 | I_kwDODunzps49m5M7 | 3,146 | CLI test command throws NonMatchingSplitsSizesError when saving infos | [
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] | closed | false | null | 0 | 2021-10-22T13:50:53Z | 2021-10-27T08:01:49Z | 2021-10-27T08:01:49Z | null | When trying to generate a datset JSON metadata, a `NonMatchingSplitsSizesError` is thrown:
```
$ datasets-cli test datasets/arabic_billion_words --save_infos --all_configs
Testing builder 'Alittihad' (1/10)
Downloading and preparing dataset arabic_billion_words/Alittihad (download: 332.13 MiB, generated: Unknown size, post-processed: Unknown size, total: 332.13 MiB) to .cache\arabic_billion_words\Alittihad\1.1.0\8175ff1c9714c6d5d15b1141b6042e5edf048276bb81a9c14e35e149a7a62ae4...
Traceback (most recent call last):
File "path\huggingface\datasets\.venv\Scripts\datasets-cli-script.py", line 33, in <module>
sys.exit(load_entry_point('datasets', 'console_scripts', 'datasets-cli')())
File "path\huggingface\datasets\src\datasets\commands\datasets_cli.py", line 33, in main
service.run()
File "path\huggingface\datasets\src\datasets\commands\test.py", line 144, in run
builder.download_and_prepare(
File "path\huggingface\datasets\src\datasets\builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "path\huggingface\datasets\src\datasets\builder.py", line 709, in _download_and_prepare
verify_splits(self.info.splits, split_dict)
File "path\huggingface\datasets\src\datasets\utils\info_utils.py", line 74, in verify_splits
raise NonMatchingSplitsSizesError(str(bad_splits))
datasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=0, num_examples=0, dataset_name='arabic_billion_words'), 'recorded': SplitInfo(name='train', num_bytes=1601790302, num_examples=349342, dataset_name='arabic_billion_words')}]
```
This is due because a previous run generated a wrong `dataset_info.json`.
This error can be avoided by passing `--ignore_verifications`, but I think this should be assumed when passing `--save_infos`. | {
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https://api.github.com/repos/huggingface/datasets/issues/2479 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2479/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2479/comments | https://api.github.com/repos/huggingface/datasets/issues/2479/events | https://github.com/huggingface/datasets/pull/2479 | 918,672,431 | MDExOlB1bGxSZXF1ZXN0NjY4MDc3NTI4 | 2,479 | ❌ load_datasets ❌ | [] | closed | false | null | 0 | 2021-06-11T12:14:36Z | 2021-06-11T14:46:25Z | 2021-06-11T14:46:25Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/1445 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1445/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1445/comments | https://api.github.com/repos/huggingface/datasets/issues/1445/events | https://github.com/huggingface/datasets/pull/1445 | 761,057,851 | MDExOlB1bGxSZXF1ZXN0NTM1NzgzMzY2 | 1,445 | Added dataset clickbait_news_bg | [] | closed | false | null | 2 | 2020-12-10T09:17:28Z | 2020-12-15T07:45:19Z | 2020-12-15T07:45:19Z | null | {
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} | true | [
"Looks like this PR includes changes about many other files than the ones for clickbait_news_bg\r\n\r\nCan you create another branch and another PR please ?",
"I created a new branch with the dataset code and submitted a new PR for it: https://github.com/huggingface/datasets/pull/1568"
] | |
https://api.github.com/repos/huggingface/datasets/issues/1131 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1131/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1131/comments | https://api.github.com/repos/huggingface/datasets/issues/1131/events | https://github.com/huggingface/datasets/pull/1131 | 757,278,341 | MDExOlB1bGxSZXF1ZXN0NTMyNjgxMTI0 | 1,131 | Adding XQUAD-R Dataset | [] | closed | false | null | 0 | 2020-12-04T17:35:43Z | 2020-12-04T18:27:22Z | 2020-12-04T18:27:22Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5249 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5249/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5249/comments | https://api.github.com/repos/huggingface/datasets/issues/5249/events | https://github.com/huggingface/datasets/issues/5249 | 1,451,692,247 | I_kwDODunzps5WhxDX | 5,249 | Protect the main branch from inadvertent direct pushes | [
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] | open | false | null | 1 | 2022-11-16T14:19:03Z | 2023-07-21T14:34:44Z | null | null | We have decided to implement a protection mechanism in this repository, so that nobody (not even administrators) can inadvertently push accidentally directly to the main branch.
See context here:
- d7c942228b8dcf4de64b00a3053dce59b335f618
To do:
- [x] Protect main branch
- Settings > Branches > Branch protection rules > main > Edit
- [x] Check: Do not allow bypassing the above settings
- The above settings will apply to administrators and custom roles with the "bypass branch protections" permission.
- [x] Additionally, uncheck: Require approvals [under "Require a pull request before merging", which was already checked]
- Before, we could exceptionally merge a non-approved PR, using Administrator bypass
- Now that Administrator bypass is no longer possible, we would always need an approval to be able to merge; and pull request authors cannot approve their own pull requests. This could be an inconvenient in some exceptional circumstances when an urgent fix is needed
- Nevertheless, although it is no longer enforced, it is strongly recommended to merge PRs only if they have at least one approval
- [ ] #5250
- So that direct pushes to main branch are no longer necessary | {
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"It seems all the tasks have been addressed, meaning this issue can be closed, no?"
] |
https://api.github.com/repos/huggingface/datasets/issues/4162 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4162/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4162/comments | https://api.github.com/repos/huggingface/datasets/issues/4162/events | https://github.com/huggingface/datasets/pull/4162 | 1,203,421,909 | PR_kwDODunzps42LtGO | 4,162 | Add Conceptual 12M | [] | closed | false | null | 2 | 2022-04-13T14:57:23Z | 2022-04-15T08:13:01Z | 2022-04-15T08:06:25Z | null | null | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Looks like your dummy_data.zip file is not in the right location ;)\r\ndatasets/datasets/conceptual_12m/dummy/default/0.0.0/dummy_data.zip\r\n->\r\ndatasets/conceptual_12m/dummy/default/0.0.0/dummy_data.zip"
] |
https://api.github.com/repos/huggingface/datasets/issues/4384 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4384/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4384/comments | https://api.github.com/repos/huggingface/datasets/issues/4384/events | https://github.com/huggingface/datasets/pull/4384 | 1,243,919,748 | PR_kwDODunzps44OwFr | 4,384 | Refactor download | [] | closed | false | null | 4 | 2022-05-21T08:49:24Z | 2022-05-25T10:52:02Z | 2022-05-25T10:43:43Z | null | This PR performs a refactoring of the download functionalities, by proposing a modular solution and moving them to their own package "download". Some motivating arguments:
- understandability: from a logical partitioning of the library, it makes sense to have all download functionalities grouped together instead of scattered in a much larger directory containing many more different functionalities
- abstraction: the level of abstraction of "download" (higher) is not the same as "utils" (lower); putting different levels of abstraction together, makes dependencies more intricate (potential circular dependencies) and the system more tightly coupled; when the levels of abstraction are clearly separated, the dependencies flow in a neat direction from higher to lower
- architectural: "download" is a domain-specific functionality of our library/application (a dataset builder performs several actions: download, generate dataset and cache it); these functionalities are at the core of our library; on the other hand, "utils" are always a low-level set of functionalities, not directly related to our domain/business core logic (all libraries have "utils"), thus at the periphery of our lib architecture
Also note that when a library is not architecturally designed following simple, neat, clean principles, this has a negative impact on extensibility, making more and more difficult to make enhancements.
As a concrete example in this case, please see: https://app.circleci.com/pipelines/github/huggingface/datasets/12185/workflows/ff25a790-8e3f-45a1-aadd-9d79dfb73c4d/jobs/72860
- After an extension, a circular import is found
- Diving into the cause of this circular import, see the dependency flow, which should be from higher to lower levels of abstraction:
```
ImportError while loading conftest '/home/circleci/datasets/tests/conftest.py'.
tests/conftest.py:12: in <module>
import datasets
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/datasets/__init__.py:37: in <module>
from .arrow_dataset import Dataset, concatenate_datasets
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/datasets/arrow_dataset.py:59: in <module>
from . import config
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/datasets/config.py:8: in <module>
from .utils.logging import get_logger
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/datasets/utils/__init__.py:30: in <module>
from .download_manager import DownloadConfig, DownloadManager, DownloadMode
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/datasets/utils/download_manager.py:39: in <module>
from .py_utils import NestedDataStructure, map_nested, size_str
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/datasets/utils/py_utils.py:608: in <module>
if config.DILL_VERSION < version.parse("0.3.5"):
E AttributeError: module 'datasets.config' has no attribute 'DILL_VERSION'
```
Imports:
- datasets
- Dataset: lower level than datasets
- config: lower level than Dataset
- logger: lower level than config
- DownloadManager: !!! HIGHER level of abstraction than logger!!
Why when importing logger we require importing DownloadManager?!?
- Logically, it does not make sense
- This is due to an error in the design/architecture of our library:
- To import the logger, we need to import it from `.utils.logging`
- To import `.utils.logging` we need to import `.utils`
- The import of `.utils` require the import of all its submodules defined in `utils.__init__.py`, among them: `.utils.download_manager`!
When putting `logging` and `download_manager` both inside `utils`, in order to import `logging` we need to import `download_manager` first: this is a strong coupling between modules and moreover between modules at different levels of abstraction (to import a lower level module, we require to import a higher level module). Additionally, it is clear that is makes no sense that in order to import `logging` we require to import `download_manager` first. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"This looks like a breaking change no ?\r\nAlso could you explain why it would be better this way ?",
"The might be only there to help type checkers, but I am not too familiar with the code base to know for sure. I think this might ... |
https://api.github.com/repos/huggingface/datasets/issues/1456 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1456/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1456/comments | https://api.github.com/repos/huggingface/datasets/issues/1456/events | https://github.com/huggingface/datasets/pull/1456 | 761,231,296 | MDExOlB1bGxSZXF1ZXN0NTM1OTI4MTc2 | 1,456 | Add CC100 Dataset | [] | closed | false | null | 0 | 2020-12-10T13:14:37Z | 2020-12-14T10:20:09Z | 2020-12-14T10:20:08Z | null | Closes #773 | {
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https://api.github.com/repos/huggingface/datasets/issues/6060 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6060/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6060/comments | https://api.github.com/repos/huggingface/datasets/issues/6060/events | https://github.com/huggingface/datasets/issues/6060 | 1,816,614,120 | I_kwDODunzps5sR1To | 6,060 | Dataset.map() execute twice when in PyTorch DDP mode | [] | open | false | null | 3 | 2023-07-22T05:06:43Z | 2023-07-24T19:29:55Z | null | null | ### Describe the bug
I use `torchrun --standalone --nproc_per_node=2 train.py` to start training. And write the code following the [docs](https://huggingface.co/docs/datasets/process#distributed-usage). The trick about using `torch.distributed.barrier()` to only execute map at the main process doesn't always work. When I am training model, it will map twice. When I am running a test for dataset and dataloader (just print the batches), it can work. Their code about loading dataset are same.
And on another server with 30 CPU cores, I use 2 GPUs and it can't work neither.
I have tried to use `rank` and `local_rank` to check, they all didn't make sense.
### Steps to reproduce the bug
use `torchrun --standalone --nproc_per_node=2 train.py` or `torchrun --standalone train.py` to run
This is my code:
```python
if args.distributed and world_size > 1:
if args.local_rank > 0:
print(f"Rank {args.rank}: Gpu {args.gpu} waiting for main process to perform the mapping", force=True)
torch.distributed.barrier()
print("Mapping dataset")
dataset = dataset.map(lambda x: cut_reorder_keys(x, num_stations_list=args.num_stations_list, is_pad=True, is_train=True), num_proc=8, desc="cut_reorder_keys")
dataset = dataset.map(lambda x: random_shift(x, shift_range=(-160, 0), feature_scale=16), num_proc=8, desc="random_shift")
dataset_test = dataset_test.map(lambda x: cut_reorder_keys(x, num_stations_list=args.num_stations_list, is_pad=True, is_train=False), num_proc=8, desc="cut_reorder_keys")
if args.local_rank == 0:
print("Mapping finished, loading results from main process")
torch.distributed.barrier()
```
### Expected behavior
Only the main process will execute `map`, while the sub process will load cache from disk.
### Environment info
server with 64 CPU cores (AMD Ryzen Threadripper PRO 5995WX 64-Cores) and 2 RTX 4090
- `python==3.9.16`
- `datasets==2.13.1`
- `torch==2.0.1+cu117`
- `22.04.1-Ubuntu`
server with 30 CPU cores (Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz) and 2 RTX 4090
- `python==3.9.0`
- `datasets==2.13.1`
- `torch==2.0.1+cu117`
- `Ubuntu 20.04` | {
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"Sorry for asking a duplicate question about `num_proc`, I searched the forum and find the solution.\r\n\r\nBut I still can't make the trick with `torch.distributed.barrier()` to only map at the main process work. The [post on forum]( https://discuss.huggingface.co/t/slow-processing-with-map-when-using-deepspeed-or... |
https://api.github.com/repos/huggingface/datasets/issues/1929 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1929/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1929/comments | https://api.github.com/repos/huggingface/datasets/issues/1929/events | https://github.com/huggingface/datasets/pull/1929 | 813,929,669 | MDExOlB1bGxSZXF1ZXN0NTc3OTk1MTE4 | 1,929 | Improve typing and style and fix some inconsistencies | [] | closed | false | null | 2 | 2021-02-22T22:47:41Z | 2021-02-24T16:16:14Z | 2021-02-24T14:03:54Z | null | This PR:
* improves typing (mostly more consistent use of `typing.Optional`)
* `DatasetDict.cleanup_cache_files` now correctly returns a dict
* replaces `dict()` with the corresponding literal
* uses `dict_to_copy.copy()` instead of `dict(dict_to_copy)` for shallow copying | {
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"@lhoestq Thanks for the quick review.",
"I merged master to this branch to re-run the CI before merging :)"
] |
https://api.github.com/repos/huggingface/datasets/issues/3412 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3412/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3412/comments | https://api.github.com/repos/huggingface/datasets/issues/3412/events | https://github.com/huggingface/datasets/pull/3412 | 1,075,846,368 | PR_kwDODunzps4voLs4 | 3,412 | Fix flaky test again for s3 serialization | [] | closed | false | null | 0 | 2021-12-09T17:54:41Z | 2021-12-09T18:00:52Z | 2021-12-09T18:00:52Z | null | Following https://github.com/huggingface/datasets/pull/3388 that wasn't enough (see CI error [here](https://app.circleci.com/pipelines/github/huggingface/datasets/9080/workflows/b971fb27-ff20-4220-9416-c19acdfdf6f4/jobs/55985)) | {
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https://api.github.com/repos/huggingface/datasets/issues/2496 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2496/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2496/comments | https://api.github.com/repos/huggingface/datasets/issues/2496/events | https://github.com/huggingface/datasets/issues/2496 | 920,216,314 | MDU6SXNzdWU5MjAyMTYzMTQ= | 2,496 | Dataset fingerprint changes after moving the cache directory, which prevent cache reload when using `map` | [] | closed | false | null | 0 | 2021-06-14T09:20:26Z | 2021-06-21T15:05:03Z | 2021-06-21T15:05:03Z | null | `Dataset.map` uses the dataset fingerprint (a hash) for caching.
However the fingerprint seems to change when someone moves the cache directory of the dataset.
This is because it uses the default fingerprint generation:
1. the dataset path is used to get the fingerprint
2. the modification times of the arrow file is also used to get the fingerprint
To fix that we could set the fingerprint of the dataset to be a hash of (<dataset_name>, <config_name>, <version>, <script_hash>), i.e. a hash of the the cache path relative to the cache directory. | {
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https://api.github.com/repos/huggingface/datasets/issues/3523 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3523/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3523/comments | https://api.github.com/repos/huggingface/datasets/issues/3523/events | https://github.com/huggingface/datasets/pull/3523 | 1,093,819,227 | PR_kwDODunzps4wiJc2 | 3,523 | Added links to licensing and PII message in vctk dataset | [] | closed | false | null | 0 | 2022-01-04T22:56:58Z | 2022-01-06T19:33:50Z | 2022-01-06T19:33:50Z | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/686 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/686/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/686/comments | https://api.github.com/repos/huggingface/datasets/issues/686/events | https://github.com/huggingface/datasets/issues/686 | 711,385,739 | MDU6SXNzdWU3MTEzODU3Mzk= | 686 | Dataset browser url is still https://huggingface.co/nlp/viewer/ | [] | closed | false | null | 2 | 2020-09-29T19:21:52Z | 2021-01-08T18:29:26Z | 2021-01-08T18:29:26Z | null | Might be worth updating to https://huggingface.co/datasets/viewer/ | {
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"Yes! might do it with @srush one of these days. Hopefully it won't break too many links (we can always redirect from old url to new)",
"This was fixed but forgot to close the issue. cc @lhoestq @yjernite \r\n\r\nThanks @jarednielsen!"
] |
https://api.github.com/repos/huggingface/datasets/issues/2267 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2267/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2267/comments | https://api.github.com/repos/huggingface/datasets/issues/2267/events | https://github.com/huggingface/datasets/issues/2267 | 868,291,129 | MDU6SXNzdWU4NjgyOTExMjk= | 2,267 | DatasetDict save load Failing test in 1.6 not in 1.5 | [
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] | open | false | null | 6 | 2021-04-27T00:03:25Z | 2021-05-28T15:27:34Z | null | null | ## Describe the bug
We have a test that saves a DatasetDict to disk and then loads it from disk. In 1.6 there is an incompatibility in the schema.
Downgrading to `>1.6` -- fixes the problem.
## Steps to reproduce the bug
```python
### Load a dataset dict from jsonl
path = '/test/foo'
ds_dict.save_to_disk(path)
ds_from_disk = DatasetDict.load_from_disk(path). ## <-- this is where I see the error on 1.6
```
## Expected results
Upgrading to 1.6 shouldn't break that test. We should be able to serialize to and from disk.
## Actual results
```
# Infer features if None
inferred_features = Features.from_arrow_schema(arrow_table.schema)
if self.info.features is None:
self.info.features = inferred_features
# Infer fingerprint if None
if self._fingerprint is None:
self._fingerprint = generate_fingerprint(self)
# Sanity checks
assert self.features is not None, "Features can't be None in a Dataset object"
assert self._fingerprint is not None, "Fingerprint can't be None in a Dataset object"
if self.info.features.type != inferred_features.type:
> raise ValueError(
"External features info don't match the dataset:\nGot\n{}\nwith type\n{}\n\nbut expected something like\n{}\nwith type\n{}".format(
self.info.features, self.info.features.type, inferred_features, inferred_features.type
)
)
E ValueError: External features info don't match the dataset:
E Got
E {'_input_hash': Value(dtype='int64', id=None), '_task_hash': Value(dtype='int64', id=None), '_view_id': Value(dtype='string', id=None), 'answer': Value(dtype='string', id=None), 'encoding__ids': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), 'encoding__offsets': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'encoding__overflowing': Sequence(feature=Value(dtype='null', id=None), length=-1, id=None), 'encoding__tokens': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'encoding__words': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), 'ner_ids': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), 'ner_labels': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'relations': [{'child': Value(dtype='int64', id=None), 'child_span': {'end': Value(dtype='int64', id=None), 'label': Value(dtype='string', id=None), 'start': Value(dtype='int64', id=None), 'token_end': Value(dtype='int64', id=None), 'token_start': Value(dtype='int64', id=None)}, 'color': Value(dtype='string', id=None), 'head': Value(dtype='int64', id=None), 'head_span': {'end': Value(dtype='int64', id=None), 'label': Value(dtype='string', id=None), 'start': Value(dtype='int64', id=None), 'token_end': Value(dtype='int64', id=None), 'token_start': Value(dtype='int64', id=None)}, 'label': Value(dtype='string', id=None)}], 'spans': [{'end': Value(dtype='int64', id=None), 'label': Value(dtype='string', id=None), 'start': Value(dtype='int64', id=None), 'text': Value(dtype='string', id=None), 'token_end': Value(dtype='int64', id=None), 'token_start': Value(dtype='int64', id=None), 'type': Value(dtype='string', id=None)}], 'text': Value(dtype='string', id=None), 'tokens': [{'disabled': Value(dtype='bool', id=None), 'end': Value(dtype='int64', id=None), 'id': Value(dtype='int64', id=None), 'start': Value(dtype='int64', id=None), 'text': Value(dtype='string', id=None), 'ws': Value(dtype='bool', id=None)}]}
E with type
E struct<_input_hash: int64, _task_hash: int64, _view_id: string, answer: string, encoding__ids: list<item: int64>, encoding__offsets: list<item: list<item: int64>>, encoding__overflowing: list<item: null>, encoding__tokens: list<item: string>, encoding__words: list<item: int64>, ner_ids: list<item: int64>, ner_labels: list<item: string>, relations: list<item: struct<child: int64, child_span: struct<end: int64, label: string, start: int64, token_end: int64, token_start: int64>, color: string, head: int64, head_span: struct<end: int64, label: string, start: int64, token_end: int64, token_start: int64>, label: string>>, spans: list<item: struct<end: int64, label: string, start: int64, text: string, token_end: int64, token_start: int64, type: string>>, text: string, tokens: list<item: struct<disabled: bool, end: int64, id: int64, start: int64, text: string, ws: bool>>>
E
E but expected something like
E {'_input_hash': Value(dtype='int64', id=None), '_task_hash': Value(dtype='int64', id=None), '_view_id': Value(dtype='string', id=None), 'answer': Value(dtype='string', id=None), 'encoding__ids': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), 'encoding__offsets': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'encoding__overflowing': Sequence(feature=Value(dtype='null', id=None), length=-1, id=None), 'encoding__tokens': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'encoding__words': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), 'ner_ids': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), 'ner_labels': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'relations': [{'head': Value(dtype='int64', id=None), 'child': Value(dtype='int64', id=None), 'head_span': {'start': Value(dtype='int64', id=None), 'end': Value(dtype='int64', id=None), 'token_start': Value(dtype='int64', id=None), 'token_end': Value(dtype='int64', id=None), 'label': Value(dtype='string', id=None)}, 'child_span': {'start': Value(dtype='int64', id=None), 'end': Value(dtype='int64', id=None), 'token_start': Value(dtype='int64', id=None), 'token_end': Value(dtype='int64', id=None), 'label': Value(dtype='string', id=None)}, 'color': Value(dtype='string', id=None), 'label': Value(dtype='string', id=None)}], 'spans': [{'text': Value(dtype='string', id=None), 'start': Value(dtype='int64', id=None), 'token_start': Value(dtype='int64', id=None), 'token_end': Value(dtype='int64', id=None), 'end': Value(dtype='int64', id=None), 'type': Value(dtype='string', id=None), 'label': Value(dtype='string', id=None)}], 'text': Value(dtype='string', id=None), 'tokens': [{'text': Value(dtype='string', id=None), 'start': Value(dtype='int64', id=None), 'end': Value(dtype='int64', id=None), 'id': Value(dtype='int64', id=None), 'ws': Value(dtype='bool', id=None), 'disabled': Value(dtype='bool', id=None)}]}
E with type
E struct<_input_hash: int64, _task_hash: int64, _view_id: string, answer: string, encoding__ids: list<item: int64>, encoding__offsets: list<item: list<item: int64>>, encoding__overflowing: list<item: null>, encoding__tokens: list<item: string>, encoding__words: list<item: int64>, ner_ids: list<item: int64>, ner_labels: list<item: string>, relations: list<item: struct<head: int64, child: int64, head_span: struct<start: int64, end: int64, token_start: int64, token_end: int64, label: string>, child_span: struct<start: int64, end: int64, token_start: int64, token_end: int64, label: string>, color: string, label: string>>, spans: list<item: struct<text: string, start: int64, token_start: int64, token_end: int64, end: int64, type: string, label: string>>, text: string, tokens: list<item: struct<text: string, start: int64, end: int64, id: int64, ws: bool, disabled: bool>>>
../../../../../.virtualenvs/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:274: ValueError
```
## Versions
- Datasets: 1.6.1
- Python: 3.8.5 (default, Jan 26 2021, 10:01:04)
[Clang 12.0.0 (clang-1200.0.32.2)]
- Platform: macOS-10.15.7-x86_64-i386-64bit
```
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} | https://api.github.com/repos/huggingface/datasets/issues/2267/timeline | null | null | null | null | false | [
"Thanks for reporting ! We're looking into it",
"I'm not able to reproduce this, do you think you can provide a code that creates a DatasetDict that has this issue when saving and reloading ?",
"Hi, I just ran into a similar error. Here is the minimal code to reproduce:\r\n```python\r\nfrom datasets import load... |
https://api.github.com/repos/huggingface/datasets/issues/1374 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1374/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1374/comments | https://api.github.com/repos/huggingface/datasets/issues/1374/events | https://github.com/huggingface/datasets/pull/1374 | 760,288,291 | MDExOlB1bGxSZXF1ZXN0NTM1MTQ1Mzgw | 1,374 | Add OPUS Tilde Model Dataset | [] | closed | false | null | 1 | 2020-12-09T12:29:23Z | 2020-12-10T16:11:29Z | 2020-12-10T16:11:28Z | null | {
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"merging since the CI is fixed on master"
] | |
https://api.github.com/repos/huggingface/datasets/issues/4154 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4154/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4154/comments | https://api.github.com/repos/huggingface/datasets/issues/4154/events | https://github.com/huggingface/datasets/pull/4154 | 1,202,145,721 | PR_kwDODunzps42Hh14 | 4,154 | Generate tasks.json taxonomy from `huggingface_hub` | [] | closed | false | null | 7 | 2022-04-12T17:12:46Z | 2022-04-14T10:32:32Z | 2022-04-14T10:26:13Z | null | null | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Ok recomputed the json file, this should be ready to review now! @lhoestq ",
"Note: the generated JSON from `hf/hub-docs` can be found in the output of a GitHub Action run on that repo, for instance in https://github.com/huggingfac... |
https://api.github.com/repos/huggingface/datasets/issues/5354 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5354/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5354/comments | https://api.github.com/repos/huggingface/datasets/issues/5354/events | https://github.com/huggingface/datasets/issues/5354 | 1,492,174,125 | I_kwDODunzps5Y8MUt | 5,354 | Consider using "Sequence" instead of "List" | [
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"default": true... | open | false | null | 7 | 2022-12-12T15:39:45Z | 2023-07-26T16:25:51Z | null | null | ### Feature request
Hi, please consider using `Sequence` type annotation instead of `List` in function arguments such as in [`Dataset.from_parquet()`](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L1088). It leads to type checking errors, see below.
**How to reproduce**
```py
list_of_filenames = ["foo.parquet", "bar.parquet"]
ds = Dataset.from_parquet(list_of_filenames)
```
**Expected mypy output:**
```
Success: no issues found
```
**Actual mypy output:**
```py
test.py:19: error: Argument 1 to "from_parquet" of "Dataset" has incompatible type "List[str]"; expected "Union[Union[str, bytes, PathLike[Any]], List[Union[str, bytes, PathLike[Any]]]]" [arg-type]
test.py:19: note: "List" is invariant -- see https://mypy.readthedocs.io/en/stable/common_issues.html#variance
test.py:19: note: Consider using "Sequence" instead, which is covariant
```
**Env:** mypy 0.991, Python 3.10.0, datasets 2.7.1 | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5354/timeline | null | null | null | null | false | [
"Hi! Linking a comment to provide more info on the issue: https://stackoverflow.com/a/39458225. This means we should replace all (most of) the occurrences of `List` with `Sequence` in function signatures.\r\n\r\n@tranhd95 Would you be interested in submitting a PR?",
"Hi all! I tried to reproduce this issue and d... |
https://api.github.com/repos/huggingface/datasets/issues/581 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/581/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/581/comments | https://api.github.com/repos/huggingface/datasets/issues/581/events | https://github.com/huggingface/datasets/issues/581 | 695,120,517 | MDU6SXNzdWU2OTUxMjA1MTc= | 581 | Better error message when input file does not exist | [] | closed | false | null | 0 | 2020-09-07T13:47:59Z | 2020-09-09T09:00:07Z | 2020-09-09T09:00:07Z | null | In the following scenario, when `data_files` is an empty list, the stack trace and error message could be improved. This can probably be solved by checking for each file whether it actually exists and/or whether the argument is not false-y.
```python
dataset = load_dataset("text", data_files=[])
```
Example error trace.
```
Using custom data configuration default
Downloading and preparing dataset text/default-d18f9b6611eb8e16 (download: Unknown size, generated: Unknown size, post-processed: Unknown sizetotal: Unknown size) to C:\Users\bramv\.cache\huggingface\datasets\text\default-d18f9b6611eb8e16\0.0.0\3a79870d85f1982d6a2af884fde86a71c771747b4b161fd302d28ad22adf985b...
Traceback (most recent call last):
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\builder.py", line 424, in incomplete_dir
yield tmp_dir
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\builder.py", line 462, in download_and_prepare
self._download_and_prepare(
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\builder.py", line 537, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\builder.py", line 813, in _prepare_split
num_examples, num_bytes = writer.finalize()
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\arrow_writer.py", line 217, in finalize
self.pa_writer.close()
AttributeError: 'NoneType' object has no attribute 'close'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:/dev/python/dutch-simplification/main.py", line 7, in <module>
dataset = load_dataset("text", data_files=files)
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\load.py", line 548, in load_dataset
builder_instance.download_and_prepare(
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\builder.py", line 470, in download_and_prepare
self._save_info()
File "c:\users\bramv\appdata\local\programs\python\python38\lib\contextlib.py", line 131, in __exit__
self.gen.throw(type, value, traceback)
File "C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\nlp\builder.py", line 430, in incomplete_dir
shutil.rmtree(tmp_dir)
File "c:\users\bramv\appdata\local\programs\python\python38\lib\shutil.py", line 737, in rmtree
return _rmtree_unsafe(path, onerror)
File "c:\users\bramv\appdata\local\programs\python\python38\lib\shutil.py", line 615, in _rmtree_unsafe
onerror(os.unlink, fullname, sys.exc_info())
File "c:\users\bramv\appdata\local\programs\python\python38\lib\shutil.py", line 613, in _rmtree_unsafe
os.unlink(fullname)
PermissionError: [WinError 32] The process cannot access the file because it is being used by another process: 'C:\\Users\\bramv\\.cache\\huggingface\\datasets\\text\\default-d18f9b6611eb8e16\\0.0.0\\3a79870d85f1982d6a2af884fde86a71c771747b4b161fd302d28ad22adf985b.incomplete\\text-train.arrow'
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/658 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/658/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/658/comments | https://api.github.com/repos/huggingface/datasets/issues/658/events | https://github.com/huggingface/datasets/pull/658 | 706,206,247 | MDExOlB1bGxSZXF1ZXN0NDkwNzk4MDc0 | 658 | Fix squad metric's Features | [] | closed | false | null | 1 | 2020-09-22T09:09:52Z | 2020-09-29T15:58:30Z | 2020-09-29T15:58:30Z | null | Resolves issue [657](https://github.com/huggingface/datasets/issues/657). | {
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"Closing this one in favor of #670 \r\n\r\nThanks again for reporting the issue and proposing this fix !\r\nLet me know if you have other remarks"
] |
https://api.github.com/repos/huggingface/datasets/issues/946 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/946/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/946/comments | https://api.github.com/repos/huggingface/datasets/issues/946/events | https://github.com/huggingface/datasets/pull/946 | 754,278,632 | MDExOlB1bGxSZXF1ZXN0NTMwMjA1Nzgw | 946 | add PEC dataset | [] | closed | false | null | 3 | 2020-12-01T10:41:41Z | 2020-12-03T02:47:14Z | 2020-12-03T02:47:14Z | null | A persona-based empathetic conversation dataset published at EMNLP 2020. | {
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"The checks failed again even if I didn't make any changes.",
"you just need to rebase from master to fix the CI :)",
"Sorry for the mess, I'm confused by the rebase and thus created a new branch."
] |
https://api.github.com/repos/huggingface/datasets/issues/3397 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3397/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3397/comments | https://api.github.com/repos/huggingface/datasets/issues/3397/events | https://github.com/huggingface/datasets/pull/3397 | 1,073,502,444 | PR_kwDODunzps4vgh1U | 3,397 | add BNL newspapers | [] | closed | false | null | 9 | 2021-12-07T15:43:21Z | 2022-01-17T18:35:34Z | 2022-01-17T18:35:34Z | null | This pull request adds the BNL's [processed newspaper collections](https://data.bnl.lu/data/historical-newspapers/) as a dataset. This is partly done to support BigScience see: https://github.com/bigscience-workshop/data_tooling/issues/192.
The Datacard is more sparse than I would like but I plan to make a separate pull request to try and make this more complete at a later date.
I had to manually add the `dummy_data` but I believe I've done this correctly (the tests pass locally).
| {
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"\r\n> Also, maybe calling the dataset as \"bnl_historical_newspapers\" and setting \"processed\" as one configuration name?\r\n\r\nThis sounds like a good idea but my only question around this is how easy it would be to use the same approach for processing the other newspaper collections [https://data.bnl.lu/data/... |
https://api.github.com/repos/huggingface/datasets/issues/458 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/458/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/458/comments | https://api.github.com/repos/huggingface/datasets/issues/458/events | https://github.com/huggingface/datasets/pull/458 | 668,972,666 | MDExOlB1bGxSZXF1ZXN0NDU5Mzk5ODg2 | 458 | Install CoVal metric from github | [] | closed | false | null | 0 | 2020-07-30T16:59:25Z | 2020-07-31T13:56:33Z | 2020-07-31T13:56:33Z | null | Changed the import statements in `coval.py` to direct the user to install the original package from github if it's not already installed (the warning will only display properly after merging [PR455](https://github.com/huggingface/nlp/pull/455))
Also changed the function call to use named rather than positional arguments. | {
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https://api.github.com/repos/huggingface/datasets/issues/5929 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5929/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5929/comments | https://api.github.com/repos/huggingface/datasets/issues/5929/events | https://github.com/huggingface/datasets/issues/5929 | 1,744,478,456 | I_kwDODunzps5n-qD4 | 5,929 | Importing PyTorch reduces multiprocessing performance for map | [] | closed | false | null | 2 | 2023-06-06T19:42:25Z | 2023-06-16T13:09:12Z | 2023-06-16T13:09:12Z | null | ### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import datasets
datasets.disable_caching()
from datasets import Dataset
import time
PROC=32
if __name__ == "__main__":
dataset = [True] * 10000000
dataset = Dataset.from_dict({'train': dataset})
start = time.time()
dataset.map(lambda x: x, num_proc=PROC)
end = time.time()
print(end - start)
```
Takes around 4 seconds on my machine.
While the same code, but with an `import torch`:
```
import datasets
datasets.disable_caching()
from datasets import Dataset
import time
import torch
PROC=32
if __name__ == "__main__":
dataset = [True] * 10000000
dataset = Dataset.from_dict({'train': dataset})
start = time.time()
dataset.map(lambda x: x, num_proc=PROC)
end = time.time()
print(end - start)
```
takes around 22 seconds.
### Expected behavior
I would expect that the import of torch to not have such a significant effect on the performance of map using multiprocessing.
### Environment info
- `datasets` version: 2.12.0
- Platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.35
- Python version: 3.11.3
- Huggingface_hub version: 0.15.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.2
- torch: 2.0.1 | {
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"Hi! The times match when I run this code locally or on Colab.\r\n\r\nAlso, we use `multiprocess`, not `multiprocessing`, for parallelization, and torch's `__init__.py` (executed on `import torch` ) slightly modifies the latter.",
"Hey Mariosasko,\r\n\r\nThanks for looking into it. We further did some investigati... |
https://api.github.com/repos/huggingface/datasets/issues/5109 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5109/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5109/comments | https://api.github.com/repos/huggingface/datasets/issues/5109/events | https://github.com/huggingface/datasets/issues/5109 | 1,407,434,706 | I_kwDODunzps5T47_S | 5,109 | Map caching not working for some class methods | [
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] | closed | false | null | 2 | 2022-10-13T09:12:58Z | 2022-10-17T10:38:45Z | 2022-10-17T10:38:45Z | null | ## Describe the bug
The cache loading is not working as expected for some class methods with a model stored in an attribute.
The new fingerprint for `_map_single` is not the same at each run. The hasher generate a different hash for the class method.
This comes from `dumps` function in `datasets.utils.py_utils` which generates a different dump at each run.
## Steps to reproduce the bug
```python
from datasets import load_dataset
from transformers import AutoConfig, AutoModel, AutoTokenizer
dataset = load_dataset("ethos", "binary")
BASE_MODELNAME = "sentence-transformers/all-MiniLM-L6-v2"
class Object:
def __init__(self):
config = AutoConfig.from_pretrained(BASE_MODELNAME)
self.bert = AutoModel.from_config(config=config, add_pooling_layer=False)
self.tok = AutoTokenizer.from_pretrained(BASE_MODELNAME)
def tokenize(self, examples):
tokenized_texts = self.tok(
examples["text"],
padding="max_length",
truncation=True,
max_length=256,
)
return tokenized_texts
instance = Object()
result = dict()
for phase in ["train"]:
result[phase] = dataset[phase].map(instance.tokenize, batched=True, load_from_cache_file=True, num_proc=2)
```
## Expected results
Load cache instead of recompute result.
## Actual results
Result recomputed from scratch at each run.
The cache works fine when deleting `bert` attribute.
## Environment info
- `datasets` version: 2.5.3.dev0
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.9.13
- PyArrow version: 7.0.0
- Pandas version: 1.5.0
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"The hash used for caching is computed by pickling recursively the function passed to `map`. Maybe some objects don't have the same hash across sessions. In particular you can check the hash of your model using\r\n```python\r\nfrom datasets.fingerprint import Hasher\r\nobj = AutoModel.from_config(config=config, ad... |
https://api.github.com/repos/huggingface/datasets/issues/3247 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3247/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3247/comments | https://api.github.com/repos/huggingface/datasets/issues/3247/events | https://github.com/huggingface/datasets/issues/3247 | 1,049,699,088 | I_kwDODunzps4-kSMQ | 3,247 | Loading big json dataset raises pyarrow.lib.ArrowNotImplementedError | [
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] | closed | false | null | 3 | 2021-11-10T11:17:59Z | 2022-04-10T14:05:57Z | 2022-04-10T14:05:57Z | null | ## Describe the bug
When trying to create a dataset from a json file with around 25MB, the following error is raised `pyarrow.lib.ArrowNotImplementedError: Unsupported cast from struct<b: int64, c: int64> to struct using function cast_struct`
Splitting the big file into smaller ones and then loading it with the `load_dataset` method did also not work.
Creating a pandas dataframe from it and then loading it with `Dataset.from_pandas` works
## Steps to reproduce the bug
```python
load_dataset("json", data_files="test.json")
```
test.json ~25MB
```json
{"a": {"c": 8, "b": 5}}
{"a": {"b": 7, "c": 6}}
{"a": {"c": 8, "b": 5}}
{"a": {"b": 7, "c": 6}}
{"a": {"c": 8, "b": 5}}
...
```
working.json ~160bytes
```json
{"a": {"c": 8, "b": 5}}
{"a": {"b": 7, "c": 6}}
{"a": {"c": 8, "b": 5}}
{"a": {"b": 7, "c": 6}}
{"a": {"c": 8, "b": 5}}
```
## Expected results
It should load the dataset from the json file without error.
## Actual results
It raises Exception `pyarrow.lib.ArrowNotImplementedError: Unsupported cast from struct<b: int64, c: int64> to struct using function cast_struct`
```
Traceback (most recent call last):
File "/Users/m/workspace/xxx/project/main.py", line 60, in <module>
dataset = load_dataset("json", data_files="result.json")
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/datasets/load.py", line 1627, in load_dataset
builder_instance.download_and_prepare(
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/datasets/builder.py", line 697, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/datasets/builder.py", line 1159, in _prepare_split
writer.write_table(table)
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/datasets/arrow_writer.py", line 428, in write_table
pa_table = pa.Table.from_arrays([pa_table[name] for name in self._schema.names], schema=self._schema)
File "pyarrow/table.pxi", line 1685, in pyarrow.lib.Table.from_arrays
File "pyarrow/table.pxi", line 630, in pyarrow.lib._sanitize_arrays
File "pyarrow/array.pxi", line 338, in pyarrow.lib.asarray
File "pyarrow/table.pxi", line 304, in pyarrow.lib.ChunkedArray.cast
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/pyarrow/compute.py", line 309, in cast
return call_function("cast", [arr], options)
File "pyarrow/_compute.pyx", line 528, in pyarrow._compute.call_function
File "pyarrow/_compute.pyx", line 327, in pyarrow._compute.Function.call
File "pyarrow/error.pxi", line 143, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 120, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Unsupported cast from struct<b: int64, c: int64> to struct using function cast_struct
```
## Environment info
- `datasets` version: 1.14.0
- Platform: macOS-12.0.1-arm64-arm-64bit
- Python version: 3.9.7
- PyArrow version: 6.0.0
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} | https://api.github.com/repos/huggingface/datasets/issues/3247/timeline | null | completed | null | null | false | [
"Hi,\r\n\r\nthis issue is similar to https://github.com/huggingface/datasets/issues/3093, so you can either use the solution provided there or try to load the data in one chunk (you can control the chunk size by specifying the `chunksize` parameter (`int`) in `load_dataset`).\r\n\r\n@lhoestq Is this worth opening a... |
https://api.github.com/repos/huggingface/datasets/issues/1533 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1533/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1533/comments | https://api.github.com/repos/huggingface/datasets/issues/1533/events | https://github.com/huggingface/datasets/pull/1533 | 764,835,913 | MDExOlB1bGxSZXF1ZXN0NTM4NzE4MDAz | 1,533 | add id_panl_bppt, a parallel corpus for en-id | [] | closed | false | null | 2 | 2020-12-13T03:11:27Z | 2020-12-21T10:40:36Z | 2020-12-21T10:40:36Z | null | Parallel Text Corpora for English - Indonesian | {
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"Hi @lhoestq, thanks for the review. I will have a look and update it accordingly.",
"Strange error message :-)\r\n\r\n```\r\n> tf_context = tf.python.context.context() # eager mode context\r\nE AttributeError: module 'tensorflow' has no attribute 'python'\r\n```\r\n"
] |
https://api.github.com/repos/huggingface/datasets/issues/3868 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3868/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3868/comments | https://api.github.com/repos/huggingface/datasets/issues/3868/events | https://github.com/huggingface/datasets/pull/3868 | 1,162,914,114 | PR_kwDODunzps40HnWA | 3,868 | Ignore duplicate keys if `ignore_verifications=True` | [] | closed | false | null | 2 | 2022-03-08T17:14:56Z | 2022-03-09T13:50:45Z | 2022-03-09T13:50:44Z | null | Currently, it's impossible to generate a dataset if some keys from `_generate_examples` are duplicated. This PR allows skipping the check for duplicate keys if `ignore_verifications` is set to `True`. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3868). All of your documentation changes will be reflected on that endpoint.",
"Cool thanks ! Could you add a test please ?"
] |
https://api.github.com/repos/huggingface/datasets/issues/1055 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1055/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1055/comments | https://api.github.com/repos/huggingface/datasets/issues/1055/events | https://github.com/huggingface/datasets/pull/1055 | 756,298,372 | MDExOlB1bGxSZXF1ZXN0NTMxODY1NjM4 | 1,055 | Add hebrew-sentiment | [] | closed | false | null | 4 | 2020-12-03T15:24:31Z | 2022-02-21T15:26:05Z | 2020-12-04T11:24:16Z | null | hebrew-sentiment dataset is ready! (including tests, tags etc) | {
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"@elronbandel it looks like something went wrong with the renaming, as the old files are still in the PR. Can you `git rm datasets/hebrew-sentiment` ?",
"merging since the CI is fixed on master",
"This is the old version of the data.\r\nHere is the fixed version.\r\nhttps://github.com/OnlpLab/Hebrew-Sentiment-D... |
https://api.github.com/repos/huggingface/datasets/issues/5488 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5488/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5488/comments | https://api.github.com/repos/huggingface/datasets/issues/5488/events | https://github.com/huggingface/datasets/issues/5488 | 1,565,025,262 | I_kwDODunzps5dSGPu | 5,488 | Error loading MP3 files from CommonVoice | [] | closed | false | null | 4 | 2023-01-31T21:25:33Z | 2023-03-02T16:25:14Z | 2023-03-02T16:25:13Z | null | ### Describe the bug
When loading a CommonVoice dataset with `datasets==2.9.0` and `torchaudio>=0.12.0`, I get an error reading the audio arrays:
```python
---------------------------------------------------------------------------
LibsndfileError Traceback (most recent call last)
~/.local/lib/python3.8/site-packages/datasets/features/audio.py in _decode_mp3(self, path_or_file)
310 try: # try torchaudio anyway because sometimes it works (depending on the os and os packages installed)
--> 311 array, sampling_rate = self._decode_mp3_torchaudio(path_or_file)
312 except RuntimeError:
~/.local/lib/python3.8/site-packages/datasets/features/audio.py in _decode_mp3_torchaudio(self, path_or_file)
351
--> 352 array, sampling_rate = torchaudio.load(path_or_file, format="mp3")
353 if self.sampling_rate and self.sampling_rate != sampling_rate:
~/.local/lib/python3.8/site-packages/torchaudio/backend/soundfile_backend.py in load(filepath, frame_offset, num_frames, normalize, channels_first, format)
204 """
--> 205 with soundfile.SoundFile(filepath, "r") as file_:
206 if file_.format != "WAV" or normalize:
~/.local/lib/python3.8/site-packages/soundfile.py in __init__(self, file, mode, samplerate, channels, subtype, endian, format, closefd)
654 format, subtype, endian)
--> 655 self._file = self._open(file, mode_int, closefd)
656 if set(mode).issuperset('r+') and self.seekable():
~/.local/lib/python3.8/site-packages/soundfile.py in _open(self, file, mode_int, closefd)
1212 err = _snd.sf_error(file_ptr)
-> 1213 raise LibsndfileError(err, prefix="Error opening {0!r}: ".format(self.name))
1214 if mode_int == _snd.SFM_WRITE:
LibsndfileError: Error opening <_io.BytesIO object at 0x7fa539462090>: File contains data in an unknown format.
```
I assume this is because there's some issue with the mp3 decoding process. I've verified that I have `ffmpeg>=4` (on a Linux distro), which appears to be the fallback backend for `torchaudio,` (at least according to #4889).
### Steps to reproduce the bug
```python
dataset = load_dataset("mozilla-foundation/common_voice_11_0", "be", split="train")
dataset[0]
```
### Expected behavior
Similar behavior to `torchaudio<0.12.0`, which doesn't result in a `LibsndfileError`
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-5.15.0-52-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 10.0.1
- Pandas version: 1.5.1 | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5488/timeline | null | completed | null | null | false | [
"Hi @kradonneoh, thanks for reporting.\r\n\r\nPlease note that to work with audio datasets (and specifically with MP3 files) we have detailed installation instructions in our docs: https://huggingface.co/docs/datasets/installation#audio\r\n- one of the requirements is torchaudio<0.12.0\r\n\r\nLet us know if the pro... |
https://api.github.com/repos/huggingface/datasets/issues/2368 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2368/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2368/comments | https://api.github.com/repos/huggingface/datasets/issues/2368/events | https://github.com/huggingface/datasets/pull/2368 | 893,411,076 | MDExOlB1bGxSZXF1ZXN0NjQ1OTI5NzM0 | 2,368 | Allow "other-X" in licenses | [] | closed | false | null | 0 | 2021-05-17T14:47:54Z | 2021-05-17T16:36:27Z | 2021-05-17T16:36:27Z | null | This PR allows "other-X" licenses during metadata validation.
@lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/1433 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1433/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1433/comments | https://api.github.com/repos/huggingface/datasets/issues/1433/events | https://github.com/huggingface/datasets/pull/1433 | 760,813,539 | MDExOlB1bGxSZXF1ZXN0NTM1NTgxNzE3 | 1,433 | Adding the ASSIN 2 dataset | [] | closed | false | null | 0 | 2020-12-10T01:57:02Z | 2020-12-11T14:32:56Z | 2020-12-11T14:32:56Z | null | Adding the ASSIN 2 dataset, a Portuguese language dataset for Natural Language Inference and Semantic Similarity Scoring | {
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https://api.github.com/repos/huggingface/datasets/issues/2497 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2497/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2497/comments | https://api.github.com/repos/huggingface/datasets/issues/2497/events | https://github.com/huggingface/datasets/pull/2497 | 920,250,382 | MDExOlB1bGxSZXF1ZXN0NjY5NDI3OTU3 | 2,497 | Use default cast for sliced list arrays if pyarrow >= 4 | [] | closed | false | {
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} | 2 | 2021-06-14T10:02:47Z | 2021-06-15T18:06:18Z | 2021-06-14T14:24:37Z | null | From pyarrow version 4, it is supported to cast sliced lists.
This PR uses default pyarrow cast in Datasets to cast sliced list arrays if pyarrow version is >= 4.
In relation with PR #2461 and #2490.
cc: @lhoestq, @abhi1thakur, @SBrandeis | {
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"I believe we don't use PyArrow >= 4.0.0 because of some segfault issues:\r\nhttps://github.com/huggingface/datasets/blob/1206ffbcd42dda415f6bfb3d5040708f50413c93/setup.py#L78\r\nCan you confirm @lhoestq ?",
"@SBrandeis pyarrow version 4.0.1 has fixed that issue: #2489 😉 "
] |
https://api.github.com/repos/huggingface/datasets/issues/2036 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2036/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2036/comments | https://api.github.com/repos/huggingface/datasets/issues/2036/events | https://github.com/huggingface/datasets/issues/2036 | 829,909,258 | MDU6SXNzdWU4Mjk5MDkyNTg= | 2,036 | Cannot load wikitext | [] | closed | false | null | 1 | 2021-03-12T09:09:39Z | 2021-03-15T08:45:02Z | 2021-03-15T08:44:44Z | null | when I execute these codes
```
>>> from datasets import load_dataset
>>> test_dataset = load_dataset("wikitext")
```
I got an error,any help?
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/xxx/anaconda3/envs/transformer/lib/python3.7/site-packages/datasets/load.py", line 589, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/home/xxx/anaconda3/envs/transformer/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/home/xxx/anaconda3/envs/transformer/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/xxx/anaconda3/envs/transformer/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 487, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/wikitext/wikitext.py
``` | {
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"Solved!"
] |
https://api.github.com/repos/huggingface/datasets/issues/4466 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4466/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4466/comments | https://api.github.com/repos/huggingface/datasets/issues/4466/events | https://github.com/huggingface/datasets/pull/4466 | 1,266,159,920 | PR_kwDODunzps45ZLsd | 4,466 | Optimize contiguous shard and select | [] | closed | false | null | 3 | 2022-06-09T13:45:39Z | 2022-06-14T16:04:30Z | 2022-06-14T15:54:45Z | null | Currently `.shard()` and `.select()` always create an indices mapping. However if the requested data are contiguous, it's much more optimized to simply slice the Arrow table instead of building an indices mapping. In particular:
- the shard/select operation will be much faster
- reading speed will be much faster in the resulting dataset, since it won't have to do a lookup step in the indices mapping
Since `.shard()` is also used for `.map()` with `num_proc>1`, it will also significantly improve the reading speed of multiprocessed `.map()` operations
Here is an example of speed-up:
```python
>>> import io
>>> import numpy as np
>>> from datasets import Dataset
>>> ds = Dataset.from_dict({"a": np.random.rand(10_000_000)})
>>> shard = ds.shard(num_shards=4, index=0, contiguous=True) # this calls `.select(range(2_500_000))`
>>> buf = io.BytesIO()
>>> %time dd.to_json(buf)
Creating json from Arrow format: 100%|██████████████████| 100/100 [00:00<00:00, 376.17ba/s]
CPU times: user 258 ms, sys: 9.06 ms, total: 267 ms
Wall time: 266 ms
```
while previously it was
```python
Creating json from Arrow format: 100%|███████████████████| 100/100 [00:03<00:00, 29.41ba/s]
CPU times: user 3.33 s, sys: 69.1 ms, total: 3.39 s
Wall time: 3.4 s
```
In this simple case the speed-up is x10, but @sayakpaul experienced a x100 speed-up on its data when exporting to JSON.
## Implementation details
I mostly improved `.select()`: it now checks if the input corresponds to a contiguous chunk of data and then it slices the main Arrow table (or the indices mapping table if it exists). To check if the input indices are contiguous it checks two possibilities:
- if the indices is of type `range`, it checks that start >= 0 and step = 1
- otherwise in the general case, it iterates over the indices. If all the indices are contiguous then we're good, otherwise we have to build an indices mapping.
Having to iterate over the indices doesn't cause performance issues IMO because:
- either they are contiguous and in this case the cost of iterating over the indices is much less than the cost of creating an indices mapping
- or they are not contiguous, and then iterating generally stops quickly when it first encounters the first indice that is not contiguous. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I thought of just mentioning the benefits I got. Here's the code that @lhoestq provided:\r\n\r\n```py\r\nimport os\r\nfrom datasets import load_dataset\r\nfrom tqdm.auto import tqdm\r\n\r\nds = load_dataset(\"squad\", split=\"train\"... |
https://api.github.com/repos/huggingface/datasets/issues/3997 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3997/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3997/comments | https://api.github.com/repos/huggingface/datasets/issues/3997/events | https://github.com/huggingface/datasets/pull/3997 | 1,178,566,568 | PR_kwDODunzps4058xr | 3,997 | Sync Features dictionaries | [] | closed | false | null | 1 | 2022-03-23T19:23:51Z | 2022-04-13T15:52:27Z | 2022-04-13T15:46:19Z | null | This PR adds a wrapper to the `Features` class to keep the secondary dict, `_column_requires_decoding`, aligned with the main dict (as discussed in https://github.com/huggingface/datasets/pull/3723#discussion_r806912731).
A more elegant approach would be to subclass `UserDict` and override `__setitem__` and `__delitem__`, but this PR doesn't implement it for the following reasons:
* it requires replacing all occurrences of `isinstance(obj, dict)` with `isinstance(obj, Mapping)`, which is five times slower than `isinstance(obj, dict)` on my machine, in `features.py`
* is a breaking change, i.e., `isinstance(Features(...), dict)` would return `False` after it
* IMO, it makes sense to be consistent in the user-facing API and subclass either `dict` or `UserDict`. The problem with the latter is that it can't be used for `DatasetDict` because `DatasetDict` exposes the `data` property, which is also used by `UserDict`, so this would result in a collision.
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https://api.github.com/repos/huggingface/datasets/issues/2604 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2604/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2604/comments | https://api.github.com/repos/huggingface/datasets/issues/2604/events | https://github.com/huggingface/datasets/issues/2604 | 938,602,237 | MDU6SXNzdWU5Mzg2MDIyMzc= | 2,604 | Add option to delete temporary files (e.g. extracted files) when loading dataset | [
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} | 14 | 2021-07-07T07:56:16Z | 2021-07-19T09:08:18Z | 2021-07-19T09:08:18Z | null | I'm loading a dataset constituted of 44 GB of compressed JSON files.
When loading the dataset with the JSON script, extracting the files create about 200 GB of uncompressed files before creating the 180GB of arrow cache tables
Having a simple way to delete the extracted files after usage (or even better, to stream extraction/delete) would be nice to avoid disk cluter.
I can maybe tackle this one in the JSON script unless you want a more general solution. | {
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"Hi !\r\nIf we want something more general, we could either\r\n1. delete the extracted files after the arrow data generation automatically, or \r\n2. delete each extracted file during the arrow generation right after it has been closed.\r\n\r\nSolution 2 is better to save disk space during the arrow generation. Is ... |
https://api.github.com/repos/huggingface/datasets/issues/5002 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5002/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5002/comments | https://api.github.com/repos/huggingface/datasets/issues/5002/events | https://github.com/huggingface/datasets/issues/5002 | 1,380,589,402 | I_kwDODunzps5SSh9a | 5,002 | Dataset Viewer issue for loubnabnl/humaneval-x | [
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] | closed | false | null | 2 | 2022-09-21T09:06:17Z | 2022-09-21T11:49:49Z | 2022-09-21T11:49:49Z | null | ### Link
https://huggingface.co/datasets/loubnabnl/humaneval-x/viewer/
### Description
The dataset has subsets but the viewer gets stuck in the default subset even when I select another one (the data loading of the subsets works fine)
### Owner
Yes | {
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"It's a bug! Thanks for reporting, I'm looking at it",
"Fixed."
] |
https://api.github.com/repos/huggingface/datasets/issues/5513 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5513/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5513/comments | https://api.github.com/repos/huggingface/datasets/issues/5513/events | https://github.com/huggingface/datasets/issues/5513 | 1,576,300,803 | I_kwDODunzps5d9HED | 5,513 | Some functions use a param named `type` shouldn't that be avoided since it's a Python reserved name? | [] | closed | false | null | 4 | 2023-02-08T15:13:46Z | 2023-07-24T16:02:18Z | 2023-07-24T14:27:59Z | null | Hi @mariosasko, @lhoestq, or whoever reads this! :)
After going through `ArrowDataset.set_format` I found out that the `type` param is actually named `type` which is a Python reserved name as you may already know, shouldn't that be renamed to `format_type` before the 3.0.0 is released?
Just wanted to get your input, and if applicable, tackle this issue myself! Thanks 🤗 | {
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"Hi! Let's not do this - renaming it would be a breaking change, and going through the deprecation cycle is only worth it if it improves user experience.",
"Hi @mariosasko, ok it makes sense. Anyway, don't you think it's worth it at some point to start a deprecation cycle e.g. `fs` in `load_from_disk`? It doesn't... |
https://api.github.com/repos/huggingface/datasets/issues/6046 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6046/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6046/comments | https://api.github.com/repos/huggingface/datasets/issues/6046/events | https://github.com/huggingface/datasets/issues/6046 | 1,808,154,414 | I_kwDODunzps5rxj8u | 6,046 | Support proxy and user-agent in fsspec calls | [
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"default": fals... | open | false | null | 0 | 2023-07-17T16:39:26Z | 2023-07-17T16:40:37Z | null | null | Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage_options`.
Though ideally the `HfFileSystem` could support passing at least the proxies | {
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https://api.github.com/repos/huggingface/datasets/issues/1495 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1495/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1495/comments | https://api.github.com/repos/huggingface/datasets/issues/1495/events | https://github.com/huggingface/datasets/pull/1495 | 763,025,562 | MDExOlB1bGxSZXF1ZXN0NTM3NTE2ODE4 | 1,495 | Opus DGT added | [] | closed | false | null | 1 | 2020-12-11T23:05:09Z | 2020-12-17T14:38:41Z | 2020-12-17T14:38:41Z | null | Dataset : http://opus.nlpl.eu/DGT.php | {
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"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/3911 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3911/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3911/comments | https://api.github.com/repos/huggingface/datasets/issues/3911/events | https://github.com/huggingface/datasets/pull/3911 | 1,168,652,374 | PR_kwDODunzps40aQHz | 3,911 | Create README.md for CER metric | [] | closed | false | null | 1 | 2022-03-14T16:54:51Z | 2022-03-17T17:49:40Z | 2022-03-17T17:45:54Z | null | Initial proposal for a CER metric card
cc @patrickvonplaten - wdyt this time around? :smile: | {
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https://api.github.com/repos/huggingface/datasets/issues/210 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/210/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/210/comments | https://api.github.com/repos/huggingface/datasets/issues/210/events | https://github.com/huggingface/datasets/pull/210 | 626,504,243 | MDExOlB1bGxSZXF1ZXN0NDI0NDgyNDgz | 210 | fix xnli metric kwargs description | [] | closed | false | null | 0 | 2020-05-28T13:21:44Z | 2020-05-28T13:22:11Z | 2020-05-28T13:22:10Z | null | The text was wrong as noticed in #202 | {
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https://api.github.com/repos/huggingface/datasets/issues/2213 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2213/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2213/comments | https://api.github.com/repos/huggingface/datasets/issues/2213/events | https://github.com/huggingface/datasets/pull/2213 | 856,025,320 | MDExOlB1bGxSZXF1ZXN0NjEzNjcwODk2 | 2,213 | Fix lc_quad download checksum | [] | closed | false | null | 0 | 2021-04-12T14:16:59Z | 2021-04-14T22:04:54Z | 2021-04-14T13:42:25Z | null | Fixes #2211 | {
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https://api.github.com/repos/huggingface/datasets/issues/5405 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5405/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5405/comments | https://api.github.com/repos/huggingface/datasets/issues/5405/events | https://github.com/huggingface/datasets/issues/5405 | 1,517,879,386 | I_kwDODunzps5aeQBa | 5,405 | size_in_bytes the same for all splits | [] | open | false | null | 1 | 2023-01-03T20:25:48Z | 2023-01-04T09:22:59Z | null | null | ### Describe the bug
Hi, it looks like whenever you pull a dataset and get size_in_bytes, it returns the same size for all splits (and that size is the combined size of all splits). It seems like this shouldn't be the intended behavior since it is misleading. Here's an example:
```
>>> from datasets import load_dataset
>>> x = load_dataset("glue", "wnli")
Found cached dataset glue (/Users/breakend/.cache/huggingface/datasets/glue/wnli/1.0.0/dacbe3125aa31d7f70367a07a8a9e72a5a0bfeb5fc42e75c9db75b96da6053ad)
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 1097.70it/s]
>>> x["train"].size_in_bytes
186159
>>> x["validation"].size_in_bytes
186159
>>> x["test"].size_in_bytes
186159
>>>
```
### Steps to reproduce the bug
```
>>> from datasets import load_dataset
>>> x = load_dataset("glue", "wnli")
>>> x["train"].size_in_bytes
186159
>>> x["validation"].size_in_bytes
186159
>>> x["test"].size_in_bytes
186159
```
### Expected behavior
The expected behavior is that it should return the separate sizes for all splits.
### Environment info
- `datasets` version: 2.7.1
- Platform: macOS-12.5-arm64-arm-64bit
- Python version: 3.10.8
- PyArrow version: 10.0.1
- Pandas version: 1.5.2 | {
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"Hi @Breakend,\r\n\r\nIndeed, the attribute `size_in_bytes` refers to the size of the entire dataset configuration, for all splits (size of downloaded files + Arrow files), not the specific split.\r\nThis is also the case for `download_size` (downloaded files) and `dataset_size` (Arrow files).\r\n\r\nThe size of th... |
https://api.github.com/repos/huggingface/datasets/issues/416 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/416/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/416/comments | https://api.github.com/repos/huggingface/datasets/issues/416/events | https://github.com/huggingface/datasets/pull/416 | 661,635,393 | MDExOlB1bGxSZXF1ZXN0NDUzMjg1NTM4 | 416 | Fix xtreme panx directory | [] | closed | false | null | 1 | 2020-07-20T10:09:17Z | 2020-07-21T08:15:46Z | 2020-07-21T08:15:44Z | null | Fix #412 | {
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"great, I think I did not download the data the way you do, but yours is more reasonable."
] |
https://api.github.com/repos/huggingface/datasets/issues/2701 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2701/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2701/comments | https://api.github.com/repos/huggingface/datasets/issues/2701/events | https://github.com/huggingface/datasets/pull/2701 | 950,422,403 | MDExOlB1bGxSZXF1ZXN0Njk0OTcxMzM3 | 2,701 | Fix download_mode docstrings | [
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https://api.github.com/repos/huggingface/datasets/issues/5397 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5397/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5397/comments | https://api.github.com/repos/huggingface/datasets/issues/5397/events | https://github.com/huggingface/datasets/pull/5397 | 1,514,412,246 | PR_kwDODunzps5GYirs | 5,397 | Unpin pydantic test dependency | [] | closed | false | null | 2 | 2022-12-30T10:22:09Z | 2022-12-30T10:53:11Z | 2022-12-30T10:43:40Z | null | Once pydantic-1.10.3 has been yanked, we can unpin it: https://pypi.org/project/pydantic/1.10.3/
See reply by pydantic team https://github.com/pydantic/pydantic/issues/4885#issuecomment-1367819807
```
v1.10.3 has been yanked.
```
in response to spacy request: https://github.com/pydantic/pydantic/issues/4885#issuecomment-1367810049
```
On behalf of spacy-related packages: would it be possible for you to temporarily yank v1.10.3?
To address this and be compatible with v1.10.4, we'd have to release new versions of a whole series of packages and nearly everyone (including me) is currently on vacation. Even if v1.10.4 is released with a fix, pip would still back off to v1.10.3 for spacy, etc. because of its current pins for typing_extensions. If it could instead back off to v1.10.2, we'd have a bit more breathing room to make the updates on our end.
```
Close #5398.
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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... |
https://api.github.com/repos/huggingface/datasets/issues/3970 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3970/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3970/comments | https://api.github.com/repos/huggingface/datasets/issues/3970/events | https://github.com/huggingface/datasets/pull/3970 | 1,174,327,367 | PR_kwDODunzps40sSfx | 3,970 | Apply index-filters on scores in get_nearest_examples and get_nearest… | [] | closed | false | null | 0 | 2022-03-19T18:32:31Z | 2022-03-19T18:38:12Z | 2022-03-19T18:38:12Z | null | Updated search.py to resolve the issue mentioned in https://github.com/huggingface/datasets/issues/3961.
Applied index-filters on scores in get_nearest_examples and get_nearest_examples_batch methods of search.py. | {
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https://api.github.com/repos/huggingface/datasets/issues/5206 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5206/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5206/comments | https://api.github.com/repos/huggingface/datasets/issues/5206/events | https://github.com/huggingface/datasets/issues/5206 | 1,437,223,894 | I_kwDODunzps5VqkvW | 5,206 | Use logging instead of printing to console | [] | closed | false | null | 1 | 2022-11-05T23:48:02Z | 2022-11-06T00:06:00Z | 2022-11-06T00:05:59Z | null | ### Describe the bug
Some logs ([here](https://github.com/huggingface/datasets/blob/4a6e1fe2735505efc7e3a3dbd3e1835da0702575/src/datasets/builder.py#L778), [here](https://github.com/huggingface/datasets/blob/4a6e1fe2735505efc7e3a3dbd3e1835da0702575/src/datasets/builder.py#L786), and [here](https://github.com/huggingface/datasets/blob/4a6e1fe2735505efc7e3a3dbd3e1835da0702575/src/datasets/builder.py#L830)) generated by the `DatasetBuilder` are printed to the console instead of passed to `datasets` logger.
### Steps to reproduce the bug
```python
>> import datasets
>> datasets.load_dataset("some-dataset")
Downloading and preparing dataset csv/data to <path>...
Downloading data files: 100%|██████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 7729.06it/s]
Extracting data files: 100%|████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 527.23it/s]
Dataset csv downloaded and prepared to <path>. Subsequent calls will reuse this data.
```
### Expected behavior
The logs should not be printed to the console directly but passed to the logger so that the user can redirect them wherever he wants.
### Environment info
- `datasets` version: 2.6.1
- Platform: macOS-13.0-x86_64-i386-64bit
- Python version: 3.9.15
- PyArrow version: 10.0.0
- Pandas version: 1.5.1 | {
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"Actually upon closer inspection, it is documented in the code that this behavior is intentional, so I'll close this."
] |
https://api.github.com/repos/huggingface/datasets/issues/3740 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3740/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3740/comments | https://api.github.com/repos/huggingface/datasets/issues/3740/events | https://github.com/huggingface/datasets/pull/3740 | 1,140,720,739 | PR_kwDODunzps4y9XAP | 3,740 | Support streaming for pubmed | [] | closed | false | null | 3 | 2022-02-17T00:18:22Z | 2022-02-18T14:42:13Z | 2022-02-18T14:42:13Z | null | This PR makes some minor changes to the `pubmed` dataset to allow for `streaming=True`. Fixes #3739.
Basically, I followed the C4 dataset which works in streaming mode as an example, and made the following changes:
* Change URL prefix from `ftp://` to `https://`
* Explicilty `open` the filename and pass the XML contents to `etree.fromstring(xml_str)`
The Github diff tool makes it look like the changes are larger than they are, sorry about that.
I tested locally and the `pubmed` dataset now works in both normal and streaming modes. There is some overhead at the start of each shard in streaming mode as building the XML tree online is quite slow (each pubmed .xml.gz file is ~20MB), but the overhead gets amortized over all the samples in the shard. On my laptop with a single CPU worker I am able to stream at about ~600 samples/s. | {
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"@albertvillanova just FYI, since you were so helpful with the previous pubmed issue :) ",
"IIRC streaming from FTP is not fully tested yet, so I'm fine with switching to HTTPS for now, as long as the download speed/availability is great",
"@albertvillanova Thanks for pointing me to the `ET` module replacement.... |
https://api.github.com/repos/huggingface/datasets/issues/1217 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1217/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1217/comments | https://api.github.com/repos/huggingface/datasets/issues/1217/events | https://github.com/huggingface/datasets/pull/1217 | 758,008,321 | MDExOlB1bGxSZXF1ZXN0NTMzMjU2MjU4 | 1,217 | adding DataCommons fact checking | [] | closed | false | null | 0 | 2020-12-06T19:56:12Z | 2020-12-16T16:22:48Z | 2020-12-16T16:22:48Z | null | Adding the data from: https://datacommons.org/factcheck/
Had to cheat a bit with the dummy data as the test doesn't recognize `.txt.gz`: had to rename uncompressed files with the `.gz` extension manually without actually compressing | {
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https://api.github.com/repos/huggingface/datasets/issues/1181 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1181/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1181/comments | https://api.github.com/repos/huggingface/datasets/issues/1181/events | https://github.com/huggingface/datasets/pull/1181 | 757,791,992 | MDExOlB1bGxSZXF1ZXN0NTMzMTAwNjYz | 1,181 | added emotions detection in arabic dataset | [] | closed | false | null | 3 | 2020-12-05T22:08:46Z | 2020-12-21T09:53:51Z | 2020-12-21T09:53:51Z | null | Dataset for Emotions detection in Arabic text
more info: https://github.com/AmrMehasseb/Emotional-Tone | {
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"Hi @abdulelahsm did you manage to fix your issue ?\r\nFeel free to ping me if you have questions or if you're ready for a review",
"@lhoestq fixed it! ready to merge. I hope haha",
"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/804 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/804/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/804/comments | https://api.github.com/repos/huggingface/datasets/issues/804/events | https://github.com/huggingface/datasets/issues/804 | 736,858,507 | MDU6SXNzdWU3MzY4NTg1MDc= | 804 | Empty output/answer in TriviaQA test set (both in 'kilt_tasks' and 'trivia_qa') | [] | closed | false | null | 3 | 2020-11-05T11:38:01Z | 2020-11-09T14:14:59Z | 2020-11-09T14:14:58Z | null | # The issue
It's all in the title, it appears to be fine on the train and validation sets.
Is there some kind of mapping to do like for the questions (see https://github.com/huggingface/datasets/blob/master/datasets/kilt_tasks/README.md) ?
# How to reproduce
```py
from datasets import load_dataset
kilt_tasks = load_dataset("kilt_tasks")
trivia_qa = load_dataset('trivia_qa', 'unfiltered.nocontext')
# both in "kilt_tasks"
In [18]: any([output['answer'] for output in kilt_tasks['test_triviaqa']['output']])
Out[18]: False
# and "trivia_qa"
In [13]: all([answer['value'] == '<unk>' for answer in trivia_qa['test']['answer']])
Out[13]: True
# appears to be fine on the train and validation sets.
In [14]: all([answer['value'] == '<unk>' for answer in trivia_qa['train']['answer']])
Out[14]: False
In [15]: all([answer['value'] == '<unk>' for answer in trivia_qa['validation']['answer']])
Out[15]: False
In [16]: any([output['answer'] for output in kilt_tasks['train_triviaqa']['output']])
Out[16]: True
In [17]: any([output['answer'] for output in kilt_tasks['validation_triviaqa']['output']])
Out[17]: True
``` | {
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"cc @yjernite is this expected ?",
"Yes: TriviaQA has a private test set for the leaderboard [here](https://competitions.codalab.org/competitions/17208)\r\n\r\nFor the KILT training and validation portions, you need to link the examples from the TriviaQA dataset as detailed here:\r\nhttps://github.com/huggingface... |
https://api.github.com/repos/huggingface/datasets/issues/3080 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3080/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3080/comments | https://api.github.com/repos/huggingface/datasets/issues/3080/events | https://github.com/huggingface/datasets/issues/3080 | 1,026,380,626 | I_kwDODunzps49LVNS | 3,080 | Error related to timeout keyword argument | [
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] | closed | false | null | 0 | 2021-10-14T13:10:58Z | 2021-10-14T14:39:51Z | 2021-10-14T14:39:51Z | null | ## Describe the bug
As reported by @patrickvonplaten, a TypeError is raised when trying to load a dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean")
```
## Actual results
```
TypeError: dataset_info() got an unexpected keyword argument 'timeout'
```
| {
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https://api.github.com/repos/huggingface/datasets/issues/5554 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5554/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5554/comments | https://api.github.com/repos/huggingface/datasets/issues/5554/events | https://github.com/huggingface/datasets/pull/5554 | 1,592,285,062 | PR_kwDODunzps5KXhZh | 5,554 | Add resampy dep | [] | closed | false | null | 5 | 2023-02-20T18:15:43Z | 2023-02-21T12:46:10Z | 2023-02-21T12:43:38Z | null | In librosa 0.10 they removed the `resmpy` dependency and set it to optional.
However it is necessary for resampling. I added it to the "audio" extra dependencies. | {
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"<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 | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... |
https://api.github.com/repos/huggingface/datasets/issues/2531 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2531/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2531/comments | https://api.github.com/repos/huggingface/datasets/issues/2531/events | https://github.com/huggingface/datasets/pull/2531 | 927,017,924 | MDExOlB1bGxSZXF1ZXN0Njc1MjM2MDYz | 2,531 | Fix dev version | [] | closed | false | null | 0 | 2021-06-22T09:17:10Z | 2021-06-22T09:47:10Z | 2021-06-22T09:47:09Z | null | The dev version that ends in `.dev0` should be greater than the current version.
However it happens that `1.8.0 > 1.8.0.dev0` for example.
Therefore we need to use `1.8.1.dev0` for example in this case.
I updated the dev version to use `1.8.1.dev0`, and I also added a comment in the setup.py in the release steps about this. | {
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https://api.github.com/repos/huggingface/datasets/issues/1625 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1625/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1625/comments | https://api.github.com/repos/huggingface/datasets/issues/1625/events | https://github.com/huggingface/datasets/pull/1625 | 773,771,596 | MDExOlB1bGxSZXF1ZXN0NTQ0Nzk4MDM1 | 1,625 | Fixed bug in the shape property | [] | closed | false | null | 0 | 2020-12-23T13:33:21Z | 2021-01-02T23:22:52Z | 2020-12-23T14:13:13Z | null | Fix to the bug reported in issue #1622. Just replaced `return tuple(self._indices.num_rows, self._data.num_columns)` by `return (self._indices.num_rows, self._data.num_columns)`. | {
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https://api.github.com/repos/huggingface/datasets/issues/4876 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4876/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4876/comments | https://api.github.com/repos/huggingface/datasets/issues/4876/events | https://github.com/huggingface/datasets/issues/4876 | 1,348,202,678 | I_kwDODunzps5QW_C2 | 4,876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | [] | closed | false | null | 15 | 2022-08-23T16:16:41Z | 2022-10-03T09:11:13Z | 2022-10-03T09:11:13Z | null | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- train-eval-index
- and more
It would be nice to have a single place instead. We can rely on the YAML tags more than the JSON file for consistency with models. And it would all be indexed by our back-end directly, which is nice to have.
One way would be to move everything to the YAML tags except the checksums (there can be tens of thousands of them). The description/citation is already in the dataset card so we probably don't need to have them in the YAML card, it would be redundant.
Here is an example for SQuAD
```yaml
download_size: 35142551
dataset_size: 89789763
version: 1.0.0
splits:
- name: train
num_examples: 87599
num_bytes: 79317110
- name: validation
num_examples: 10570
num_bytes: 10472653
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
struct:
- name: text
list:
dtype: string
- name: answer_start
list:
dtype: int32
```
Since there is only one configuration for SQuAD, this structure is ok. For datasets with several configs we can see in a second step, but IMO it would be ok to have these fields per config using another syntax
```yaml
configs:
- config: unlabeled
splits:
- name: train
num_examples: 10000
features:
- name: text
dtype: string
- config: labeled
splits:
- name: train
num_examples: 100
features:
- name: text
dtype: string
- name: label
dtype: ClassLabel
names:
- negative
- positive
```
So in the end you could specify a YAML tag either at the top level (for all configs) or per config in the `configs` field
Alternatively we could keep config specific stuff in the `dataset_infos.json` as it it today
Not sure yet what's the best approach here but cc @julien-c @mariosasko @albertvillanova @polinaeterna for feedback :) | {
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"also @osanseviero @Pierrci @SBrandeis potentially",
"Love this in principle 🚀 \r\n\r\nLet's keep in mind users might rely on `dataset_infos.json` already.\r\n\r\nI'm not convinced by the two-syntax solution, wouldn't it be simpler to have only one syntax with a `default` config for datasets with only one config... |
https://api.github.com/repos/huggingface/datasets/issues/5237 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5237/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5237/comments | https://api.github.com/repos/huggingface/datasets/issues/5237/events | https://github.com/huggingface/datasets/pull/5237 | 1,448,202,491 | PR_kwDODunzps5C2KGz | 5,237 | Encode path only for old versions of hfh | [] | closed | false | null | 1 | 2022-11-14T14:46:57Z | 2022-11-14T17:38:18Z | 2022-11-14T17:35:59Z | null | Next version of `huggingface-hub` 0.11 does encode the `path`, and we don't want to encode twice | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/4649 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4649/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4649/comments | https://api.github.com/repos/huggingface/datasets/issues/4649/events | https://github.com/huggingface/datasets/issues/4649 | 1,296,673,712 | I_kwDODunzps5NSauw | 4,649 | Add PAQ dataset | [
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] | closed | false | null | 1 | 2022-07-07T01:29:42Z | 2022-07-14T02:06:27Z | 2022-07-14T02:06:27Z | null | ## Adding a Dataset
- **Name:** *PAQ*
- **Description:** *This repository contains code and models to support the research paper PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them*
- **Paper:** *https://arxiv.org/abs/2102.07033*
- **Data:** *https://huggingface.co/datasets/sentence-transformers/embedding-training-data/resolve/main/PAQ_pairs.jsonl.gz*
- **Motivation:** *Dataset for training and evaluating models of conversational response*
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"uploaded dataset [here](https://huggingface.co/datasets/embedding-data/PAQ_pairs)"
] |
https://api.github.com/repos/huggingface/datasets/issues/3466 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3466/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3466/comments | https://api.github.com/repos/huggingface/datasets/issues/3466/events | https://github.com/huggingface/datasets/pull/3466 | 1,085,722,837 | PR_kwDODunzps4wII3w | 3,466 | Add CRASS dataset | [
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] | closed | false | null | 2 | 2021-12-21T11:17:22Z | 2022-10-03T09:37:06Z | 2022-10-03T09:37:06Z | null | Added crass dataset | {
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"Hi Albert,\r\nThank you for your comments.\r\nI hope I have uploaded my local git repo to include the dummy files and style reworkings.\r\nAdded YAML in Readme as well.\r\n\r\nPlease check again.\r\n\r\nHope it works now :)",
"Thanks for your contribution, @apergo-ai. \r\n\r\nWe are removing the dataset scripts ... |
https://api.github.com/repos/huggingface/datasets/issues/152 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/152/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/152/comments | https://api.github.com/repos/huggingface/datasets/issues/152/events | https://github.com/huggingface/datasets/pull/152 | 619,971,900 | MDExOlB1bGxSZXF1ZXN0NDE5MzA4OTE2 | 152 | Add GLUE config name check | [] | closed | false | null | 5 | 2020-05-18T07:23:43Z | 2020-05-27T22:09:12Z | 2020-05-27T22:09:12Z | null | Fixes #130 by adding a name check to the Glue class | {
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"If tests are being added, any guidance on where to add tests would be helpful!\r\n\r\nTagging @thomwolf for review",
"Looks good to me. Is this compatible with the way we are doing tests right now @patrickvonplaten ?",
"If the tests pass it should be fine :-) \r\n\r\n@Bharat123rox could you check whether the t... |
https://api.github.com/repos/huggingface/datasets/issues/2028 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2028/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2028/comments | https://api.github.com/repos/huggingface/datasets/issues/2028/events | https://github.com/huggingface/datasets/pull/2028 | 828,721,393 | MDExOlB1bGxSZXF1ZXN0NTkwNDk1NzEx | 2,028 | Adding PersiNLU reading-comprehension | [] | closed | false | null | 3 | 2021-03-11T04:41:13Z | 2021-03-15T09:39:57Z | 2021-03-15T09:39:57Z | null | {
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"@lhoestq I think I have addressed all your comments. ",
"Thanks! @lhoestq Let me know if you want me to address anything to get this merged. ",
"It's all good thanks ;)\r\nmerging"
] | |
https://api.github.com/repos/huggingface/datasets/issues/3316 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3316/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3316/comments | https://api.github.com/repos/huggingface/datasets/issues/3316/events | https://github.com/huggingface/datasets/issues/3316 | 1,062,185,822 | I_kwDODunzps4_T6te | 3,316 | Add RedCaps dataset | [
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"color": "bfdadc",... | closed | false | null | 0 | 2021-11-24T09:23:02Z | 2022-01-12T14:13:15Z | 2022-01-12T14:13:15Z | null | ## Adding a Dataset
- **Name:** RedCaps
- **Description:** Web-curated image-text data created by the people, for the people
- **Paper:** https://arxiv.org/abs/2111.11431
- **Data:** https://redcaps.xyz/
- **Motivation:** Multimodal image-text dataset: 12M+ Image-text pairs
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Proposed by @patil-suraj | {
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https://api.github.com/repos/huggingface/datasets/issues/3697 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3697/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3697/comments | https://api.github.com/repos/huggingface/datasets/issues/3697/events | https://github.com/huggingface/datasets/pull/3697 | 1,129,795,724 | PR_kwDODunzps4yXeXo | 3,697 | Add code-fill datasets for pretraining/finetuning/evaluating | [] | closed | false | null | 1 | 2022-02-10T10:31:48Z | 2022-07-06T15:19:58Z | 2022-07-06T15:19:58Z | null | null | {
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"Hi ! Thanks for adding this dataset :)\r\n\r\nIt looks like your PR contains many changes in files that are unrelated to your changes, I think it might come from running `make style` with an outdated version of `black`. Could you try opening a new PR that only contains your additions ? (or force push to this PR)"
... |
https://api.github.com/repos/huggingface/datasets/issues/4251 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4251/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4251/comments | https://api.github.com/repos/huggingface/datasets/issues/4251/events | https://github.com/huggingface/datasets/pull/4251 | 1,219,116,354 | PR_kwDODunzps4293dB | 4,251 | Metric card for the XTREME-S dataset | [] | closed | false | null | 1 | 2022-04-28T18:32:19Z | 2022-04-29T16:46:11Z | 2022-04-29T16:38:46Z | null | Proposing a metric card for the XTREME-S dataset :hugs: | {
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https://api.github.com/repos/huggingface/datasets/issues/4678 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4678/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4678/comments | https://api.github.com/repos/huggingface/datasets/issues/4678/events | https://github.com/huggingface/datasets/issues/4678 | 1,303,741,432 | I_kwDODunzps5NtYP4 | 4,678 | Cant pass streaming dataset to dataloader after take() | [
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] | open | false | null | 1 | 2022-07-13T17:34:18Z | 2022-07-14T13:07:21Z | null | null | ## Describe the bug
I am trying to pass a streaming version of c4 to a dataloader, but it can't be passed after I call `dataset.take(n)`. Some functions such as `shuffle()` can be applied without breaking the dataloader but not take.
## Steps to reproduce the bug
```python
import datasets
import torch
dset = datasets.load_dataset(path='c4', name='en', split="train", streaming=True)
dset = dset.take(50_000)
dset = dset.with_format("torch")
num_workers = 8
batch_size = 512
loader = torch.utils.data.DataLoader(dataset=dset,
batch_size=batch_size,
num_workers=num_workers)
for batch in loader:
...
```
## Expected results
No error thrown when iterating over the dataloader
## Actual results
Original Traceback (most recent call last):
File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/fetch.py", line 32, in fetch
data.append(next(self.dataset_iter))
File "/root/.local/lib/python3.9/site-packages/datasets/formatting/dataset_wrappers/torch_iterable_dataset.py", line 48, in __iter__
for key, example in self._iter_shard(shard_idx):
File "/root/.local/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 586, in _iter_shard
yield from ex_iterable.shard_data_sources(shard_idx)
File "/root/.local/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 60, in shard_data_sources
raise NotImplementedError(f"{type(self)} doesn't implement shard_data_sources yet")
NotImplementedError: <class 'datasets.iterable_dataset.TakeExamplesIterable'> doesn't implement shard_data_sources yet
## Environment info
- `datasets` version: 2.3.2
- Platform: Linux-5.4.0-120-generic-x86_64-with-glibc2.31
- Python version: 3.9.13
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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"Hi! Calling `take` on an iterable/streamable dataset makes it not possible to shard the dataset, which in turn disables multi-process loading (attempts to split the workload over the shards), so to go past this limitation, you can either use single-process loading in `DataLoader` (`num_workers=None`) or fetch the ... |
https://api.github.com/repos/huggingface/datasets/issues/4518 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4518/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4518/comments | https://api.github.com/repos/huggingface/datasets/issues/4518/events | https://github.com/huggingface/datasets/pull/4518 | 1,274,010,628 | PR_kwDODunzps45zMnB | 4,518 | Patch tests for hfh v0.8.0 | [] | closed | false | null | 1 | 2022-06-16T19:45:32Z | 2022-06-17T16:15:57Z | 2022-06-17T16:06:07Z | null | This PR patches testing utilities that would otherwise fail with hfh v0.8.0. | {
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https://api.github.com/repos/huggingface/datasets/issues/5654 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5654/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5654/comments | https://api.github.com/repos/huggingface/datasets/issues/5654/events | https://github.com/huggingface/datasets/issues/5654 | 1,633,523,705 | I_kwDODunzps5hXZf5 | 5,654 | Offset overflow when executing Dataset.map | [] | open | false | null | 2 | 2023-03-21T09:33:27Z | 2023-03-21T10:32:07Z | null | null | ### Describe the bug
Hi, I'm trying to use `.map` method to cache multiple random crops from the image to speed up data processing during training, as the image size is too big.
The map function executes all iterations, and then returns the following error:
```bash
Traceback (most recent call last):
File "/home/ubuntu/miniconda3/envs/enhancement/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 3353, in _map_single
writer.finalize() # close_stream=bool(buf_writer is None)) # We only close if we are writing in a file
File "/home/ubuntu/miniconda3/envs/enhancement/lib/python3.8/site-packages/datasets/arrow_writer.py", line 582, in finalize
self.write_examples_on_file()
File "/home/ubuntu/miniconda3/envs/enhancement/lib/python3.8/site-packages/datasets/arrow_writer.py", line 446, in write_examples_on_file
self.write_batch(batch_examples=batch_examples)
File "/home/ubuntu/miniconda3/envs/enhancement/lib/python3.8/site-packages/datasets/arrow_writer.py", line 555, in write_batch
self.write_table(pa_table, writer_batch_size)
File "/home/ubuntu/miniconda3/envs/enhancement/lib/python3.8/site-packages/datasets/arrow_writer.py", line 567, in write_table
pa_table = pa_table.combine_chunks()
File "pyarrow/table.pxi", line 3315, in pyarrow.lib.Table.combine_chunks
File "pyarrow/error.pxi", line 144, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: offset overflow while concatenating arrays
```
Here is the minimal code (`/home/datasets/DIV2K_train_HR` is just a folder of images that can be replaced by any appropriate):
### Steps to reproduce the bug
```python
from glob import glob
import torch
from datasets import Dataset, Image
from torchvision.transforms import PILToTensor, RandomCrop
file_paths = glob("/home/datasets/DIV2K_train_HR/*")
to_tensor = PILToTensor()
crop_transf = RandomCrop(size=256)
def prepare_data(example):
tensor = to_tensor(example["image"].convert("RGB"))
return {"hr": torch.stack([crop_transf(tensor) for _ in range(25)])}
train_data = Dataset.from_dict({"image": file_paths}).cast_column("image", Image())
train_data = train_data.map(
prepare_data,
cache_file_name="/home/datasets/DIV2K_train_HR_crops.tmp",
desc="Caching multiple random crops of image",
remove_columns="image",
)
print(train_data[0].keys(), train_data[0]["hr"].shape)
```
### Expected behavior
Cached file is stored at `"/home/datasets/DIV2K_train_HR_crops.tmp"`, output is `dict_keys(['hr']) torch.Size([25, 3, 256, 256])`
### Environment info
- `datasets` version: 2.10.1
- Platform: Linux-5.15.0-67-generic-x86_64-with-glibc2.10
- Python version: 3.8.16
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
- Pytorch version: 2.0.0+cu117
- torchvision version: 0.15.1+cu117 | {
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"Upd. the above code works if we replace `25` with `1`, but the result value at key \"hr\" is not a tensor but a list of lists of lists of uint8.\r\n\r\nAdding `train_data.set_format(\"torch\")` after map fixes this, but the original issue remains\r\n\r\n",
"As a workaround, one can replace\r\n`return {\"hr\": to... |
https://api.github.com/repos/huggingface/datasets/issues/1546 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1546/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1546/comments | https://api.github.com/repos/huggingface/datasets/issues/1546/events | https://github.com/huggingface/datasets/pull/1546 | 765,559,923 | MDExOlB1bGxSZXF1ZXN0NTM4OTkwMjgw | 1,546 | Add persian ner dataset | [] | closed | false | null | 3 | 2020-12-13T17:45:48Z | 2020-12-23T09:53:03Z | 2020-12-23T09:53:03Z | null | Adding the following dataset:
https://github.com/HaniehP/PersianNER
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"HI @SBrandeis. Thanks for all the comments - very helpful. I realised that the tests had failed and had been trying to figure out what was causing them to do so. All the tests pass when I run the load_real_dataset test however when I run `RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_... |
https://api.github.com/repos/huggingface/datasets/issues/1059 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1059/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1059/comments | https://api.github.com/repos/huggingface/datasets/issues/1059/events | https://github.com/huggingface/datasets/pull/1059 | 756,348,623 | MDExOlB1bGxSZXF1ZXN0NTMxOTA3ODYy | 1,059 | Add TLC | [] | closed | false | null | 3 | 2020-12-03T16:23:06Z | 2020-12-04T11:15:33Z | 2020-12-04T11:15:33Z | null | Added TLC dataset | {
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"I have reduced the size of the dummy file and added README sections as you suggested. ",
"I have a little issue to run the test. It seems there is no failed case in my machine. ",
"Thanks !\r\nIt looks like the PR includes changes to many other files than the ones of `tlc`, can you create another branch and an... |
https://api.github.com/repos/huggingface/datasets/issues/2186 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2186/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2186/comments | https://api.github.com/repos/huggingface/datasets/issues/2186/events | https://github.com/huggingface/datasets/pull/2186 | 852,840,819 | MDExOlB1bGxSZXF1ZXN0NjExMDMxNzE0 | 2,186 | GEM: new challenge sets | [] | closed | false | null | 1 | 2021-04-07T21:39:07Z | 2021-04-07T21:56:35Z | 2021-04-07T21:56:35Z | null | This PR updates the GEM dataset to:
- remove extraneous fields in WikiAuto after https://github.com/huggingface/datasets/pull/2171 fixed the source
- add context and services to Schema Guided Dialog
- Add new or update challenge sets for MLSUM ES and DE, XSUM, and SGD | {
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"cc @sebastiangehrmann"
] |
https://api.github.com/repos/huggingface/datasets/issues/4904 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4904/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4904/comments | https://api.github.com/repos/huggingface/datasets/issues/4904/events | https://github.com/huggingface/datasets/pull/4904 | 1,353,002,837 | PR_kwDODunzps4959Ad | 4,904 | [LibriSpeech] Fix dev split local_extracted_archive for 'all' config | [] | closed | false | null | 2 | 2022-08-27T10:04:57Z | 2022-08-30T10:06:21Z | 2022-08-30T10:03:25Z | null | We define the keys for the `_DL_URLS` of the dev split as `dev.clean` and `dev.other`:
https://github.com/huggingface/datasets/blob/2e7142a3c6500b560da45e8d5128e320a09fcbd4/datasets/librispeech_asr/librispeech_asr.py#L60-L61
These keys get forwarded to the `dl_manager` and thus the `local_extracted_archive`.
However, when calling `SplitGenerator` for the dev sets, we query the `local_extracted_archive` keys `validation.clean` and `validation.other`:
https://github.com/huggingface/datasets/blob/2e7142a3c6500b560da45e8d5128e320a09fcbd4/datasets/librispeech_asr/librispeech_asr.py#L212
https://github.com/huggingface/datasets/blob/2e7142a3c6500b560da45e8d5128e320a09fcbd4/datasets/librispeech_asr/librispeech_asr.py#L219
The consequence of this is that the `local_extracted_archive` arg passed to `_generate_examples` is always `None`, as the keys `validation.clean` and `validation.other` do not exists in the `local_extracted_archive`.
When defining the `audio_file` in `_generate_examples`, since `local_extracted_archive` is always `None`, we always omit the `local_extracted_archive` path from the `audio_file` path, **even** if in non-streaming mode:
https://github.com/huggingface/datasets/blob/2e7142a3c6500b560da45e8d5128e320a09fcbd4/datasets/librispeech_asr/librispeech_asr.py#L259-L263
Thus, `audio_file` will only ever be the streaming path (`audio_file`, not `os.path.join(local_extracted_archive, audio_file)`).
This PR fixes the `.get()` keys for the `local_extracted_archive` for the dev splits.
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"_The documentation is not available anymore as the PR was closed or merged._",
"This PR fixes a bug introduced in:\r\n- #4184"
] |
https://api.github.com/repos/huggingface/datasets/issues/2471 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2471/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2471/comments | https://api.github.com/repos/huggingface/datasets/issues/2471/events | https://github.com/huggingface/datasets/issues/2471 | 917,067,165 | MDU6SXNzdWU5MTcwNjcxNjU= | 2,471 | Fix PermissionError on Windows when using tqdm >=4.50.0 | [
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} | 0 | 2021-06-10T08:31:49Z | 2021-06-11T15:11:50Z | 2021-06-11T15:11:50Z | null | See: https://app.circleci.com/pipelines/github/huggingface/datasets/235/workflows/cfb6a39f-68eb-4802-8b17-2cd5e8ea7369/jobs/1111
```
PermissionError: [WinError 32] The process cannot access the file because it is being used by another process
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3837 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3837/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3837/comments | https://api.github.com/repos/huggingface/datasets/issues/3837/events | https://github.com/huggingface/datasets/pull/3837 | 1,161,109,031 | PR_kwDODunzps40BwE1 | 3,837 | Release: 1.18.4 | [] | closed | false | null | 0 | 2022-03-07T09:13:29Z | 2022-03-07T11:07:35Z | 2022-03-07T11:07:02Z | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/616 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/616/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/616/comments | https://api.github.com/repos/huggingface/datasets/issues/616/events | https://github.com/huggingface/datasets/issues/616 | 699,462,293 | MDU6SXNzdWU2OTk0NjIyOTM= | 616 | UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors | [] | open | false | null | 14 | 2020-09-11T15:39:16Z | 2021-07-22T21:12:21Z | null | null | I am trying out the library and want to load in pickled data with `from_dict`. In that dict, one column `text` should be tokenized and the other (an embedding vector) should be retained. All other columns should be removed. When I eventually try to set the format for the columns with `set_format` I am getting this strange Userwarning without a stack trace:
> Set __getitem__(key) output type to torch for ['input_ids', 'sembedding'] columns (when key is int or slice) and don't output other (un-formatted) columns.
> C:\Users\bramv\.virtualenvs\dutch-simplification-nbNdqK9u\lib\site-packages\datasets\arrow_dataset.py:835: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at ..\torch\csrc\utils\tensor_numpy.cpp:141.)
> return torch.tensor(x, **format_kwargs)
The first one might not be related to the warning, but it is odd that it is shown, too. It is unclear whether that is something that I should do or something that that the program is doing at that moment.
Snippet:
```
dataset = Dataset.from_dict(torch.load("data/dummy.pt.pt"))
print(dataset)
tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
keys_to_retain = {"input_ids", "sembedding"}
dataset = dataset.map(lambda example: tokenizer(example["text"], padding='max_length'), batched=True)
dataset.remove_columns_(set(dataset.column_names) - keys_to_retain)
dataset.set_format(type="torch", columns=["input_ids", "sembedding"])
dataloader = torch.utils.data.DataLoader(dataset, batch_size=2)
print(next(iter(dataloader)))
```
PS: the input type for `remove_columns_` should probably be an Iterable rather than just a List. | {
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"I have the same issue",
"Same issue here when Trying to load a dataset from disk.",
"I am also experiencing this issue, and don't know if it's affecting my training.",
"Same here. I hope the dataset is not being modified in-place.",
"I think the only way to avoid this warning would be to do a copy of the n... |
https://api.github.com/repos/huggingface/datasets/issues/2016 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2016/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2016/comments | https://api.github.com/repos/huggingface/datasets/issues/2016/events | https://github.com/huggingface/datasets/pull/2016 | 825,965,493 | MDExOlB1bGxSZXF1ZXN0NTg4MDA5NjEz | 2,016 | Not all languages have 2 digit codes. | [] | closed | false | null | 0 | 2021-03-09T13:53:39Z | 2021-03-11T18:01:03Z | 2021-03-11T18:01:03Z | null | . | {
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https://api.github.com/repos/huggingface/datasets/issues/3605 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3605/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3605/comments | https://api.github.com/repos/huggingface/datasets/issues/3605/events | https://github.com/huggingface/datasets/pull/3605 | 1,108,738,561 | PR_kwDODunzps4xS9rX | 3,605 | Adding Turkic X-WMT evaluation set for machine translation | [] | closed | false | null | 5 | 2022-01-20T01:40:29Z | 2022-01-31T09:50:57Z | 2022-01-31T09:50:57Z | null | This dataset is a human-translated evaluation set for MT crowdsourced and provided by the [Turkic Interlingua ](turkic-interlingua.org) community. It contains eval sets for 8 Turkic languages covering 88 language directions. Languages being covered are:
Azerbaijani (az)
Bashkir (ba)
English (en)
Karakalpak (kaa)
Kazakh (kk)
Kirghiz (ky)
Russian (ru)
Turkish (tr)
Sakha (sah)
Uzbek (uz)
More info about the corpus is here: [https://github.com/turkic-interlingua/til-mt/tree/master/xwmt](https://github.com/turkic-interlingua/til-mt/tree/master/xwmt)
A paper describing the test set is here: [https://arxiv.org/abs/2109.04593](https://arxiv.org/abs/2109.04593)
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"hi! Thank you for all the comments! I believe I addressed them all. Let me know if there is anything else",
"Hi there! I was wondering if there is anything else to change before this can be merged",
"@lhoestq Hi! Just a gentle reminder about the steps to merge this one! ",
"Thanks for the heads up ! I think ... |
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 | [] | closed | false | null | 0 | 2020-12-12T08:47:12Z | 2020-12-14T15:28:07Z | 2020-12-14T15:28:07Z | null | 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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