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https://api.github.com/repos/huggingface/datasets/issues/5458 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5458/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5458/comments | https://api.github.com/repos/huggingface/datasets/issues/5458/events | https://github.com/huggingface/datasets/issues/5458 | 1,555,054,737 | I_kwDODunzps5csECR | 5,458 | slice split while streaming | {
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"Hi! Yes, that's correct. When `streaming` is `True`, only split names can be specified as `split`, and for slicing, you have to use `.skip`/`.take` instead.\r\n\r\nE.g. \r\n`load_dataset(\"lhoestq/demo1\",revision=None, streaming=True, split=\"train[:3]\")`\r\n\r\nrewritten with `.skip`/`.take`:\r\n`load_dataset(\... | 2023-01-24T14:08:17Z | 2023-01-24T15:11:47Z | 2023-01-24T15:11:47Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
When using the `load_dataset` function with streaming set to True, slicing splits is apparently not supported.
Did I miss this in the documentation?
### Steps to reproduce the bug
`load_dataset("lhoestq/demo1",revision=None, streaming=True, split="train[:3]")`
causes ValueError: Bad split: train[:3]. Available splits: ['train', 'test'] in builder.py, line 1213, in as_streaming_dataset
### Expected behavior
The first 3 entries of the dataset as a stream
### Environment info
- `datasets` version: 2.8.0
- Platform: Windows-10-10.0.19045-SP0
- Python version: 3.10.9
- PyArrow version: 10.0.1
- Pandas version: 1.5.2
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https://api.github.com/repos/huggingface/datasets/issues/7381 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7381/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7381/comments | https://api.github.com/repos/huggingface/datasets/issues/7381/events | https://github.com/huggingface/datasets/issues/7381 | 2,815,649,092 | I_kwDODunzps6n02VE | 7,381 | Iterating over values of a column in the IterableDataset | {
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"I'd be in favor of that ! I saw many people implementing their own iterables that wrap a dataset just to iterate on a single column, that would make things more practical.\n\nKinda related: https://github.com/huggingface/datasets/issues/5847",
"(For anyone's information, I'm going on vacation for the next 3 week... | 2025-01-28T13:17:36Z | 2025-04-06T12:28:16Z | null | NONE | null | null | {
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} | ### Feature request
I would like to be able to iterate (and re-iterate if needed) over a column of an `IterableDataset` instance. The following example shows the supposed API:
```
def gen():
yield {"text": "Good", "label": 0}
yield {"text": "Bad", "label": 1}
ds = IterableDataset.from_generator(gen)
texts = ds["text"]
for v in texts:
print(v) # Prints "Good" and "Bad"
for v in texts:
print(v) # Prints "Good" and "Bad" again
```
### Motivation
In the real world problems, huge NNs like Transformer are not always the best option, so there is a need to conduct experiments with different methods. While 🤗Datasets is perfectly adapted to 🤗Transformers, it may be inconvenient when being used with other libraries. The ability to retrieve a particular column is the case (e.g., gensim's FastText [requires](https://radimrehurek.com/gensim/models/fasttext.html#gensim.models.fasttext.FastText.train) only lists of strings, not dictionaries).
While there are ways to achieve the desired functionality, they are not good ([forum](https://discuss.huggingface.co/t/how-to-iterate-over-values-of-a-column-in-the-iterabledataset/135649)). It would be great if there was a built-in solution.
### Your contribution
Theoretically, I can submit a PR, but I have very little knowledge of the internal structure of 🤗Datasets, so some help may be needed.
Moreover, I can only work on weekends, since I have a full-time job. However, the feature does not seem to be popular, so there is no need to implement it as fast as possible. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4774 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4774/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4774/comments | https://api.github.com/repos/huggingface/datasets/issues/4774/events | https://github.com/huggingface/datasets/issues/4774 | 1,323,375,844 | I_kwDODunzps5O4Rzk | 4,774 | Training hangs at the end of epoch, with set_transform/with_transform+multiple workers | {
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] | open | false | null | [] | null | [] | 2022-07-31T06:32:28Z | 2022-07-31T06:36:43Z | null | NONE | null | null | {
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} | ## Describe the bug
I use load_dataset() (I tried with [wiki](https://huggingface.co/datasets/wikipedia) and my own json data) and use set_transform/with_transform for preprocessing. But it hangs at the end of the 1st epoch if dataloader_num_workers>=1. No problem with single worker.
## Steps to reproduce the bug
```python
train_dataset = datasets.load_dataset("wikipedia", "20220301.en",
split='train',
cache_dir=model_args.cache_dir,
streaming=False)
train_dataset.set_transform(psg_parse_fn)
train_dataloader = DataLoader(
train_dataset,
batch_size=args.train_batch_size,
sampler=DistributedSampler(train_dataset),
collate_fn=data_collator,
drop_last=args.dataloader_drop_last,
num_workers=args.dataloader_num_workers,
)
```
## Expected results
## Actual results
It simply hangs. The ending step is num_example/batch_size (one epoch).
## Environment info
- `datasets` version: 2.4.1.dev0
- Platform: Linux-5.4.170+-x86_64-with-glibc2.17
- Python version: 3.8.12
- PyArrow version: 8.0.0
- Pandas version: 1.4.1 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7035 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7035/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7035/comments | https://api.github.com/repos/huggingface/datasets/issues/7035/events | https://github.com/huggingface/datasets/issues/7035 | 2,400,021,225 | I_kwDODunzps6PDWrp | 7,035 | Docs are not generated when a parameter defaults to a NamedSplit value | {
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} | While generating the docs, we get an error when some parameter defaults to a `NamedSplit` value, like:
```python
def call_function(split=Split.TRAIN):
...
```
The error is: ValueError: Equality not supported between split train and <class 'inspect._empty'>
See: https://github.com/huggingface/datasets/actions/runs/9869660902/job/27254359863?pr=7015
```
Building the MDX files: 97%|█████████▋| 58/60 [00:00<00:00, 91.94it/s]
Traceback (most recent call last):
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 197, in build_mdx_files
content, new_anchors, source_files, errors = resolve_autodoc(
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 123, in resolve_autodoc
doc = autodoc(
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/autodoc.py", line 499, in autodoc
method_doc, check = document_object(
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/autodoc.py", line 395, in document_object
signature = format_signature(obj)
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/autodoc.py", line 126, in format_signature
if param.default != inspect._empty:
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/datasets/splits.py", line 136, in __ne__
return not self.__eq__(other)
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/datasets/splits.py", line 379, in __eq__
raise ValueError(f"Equality not supported between split {self} and {other}")
ValueError: Equality not supported between split train and <class 'inspect._empty'>
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/runner/work/datasets/datasets/.venv/bin/doc-builder", line 8, in <module>
sys.exit(main())
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/commands/doc_builder_cli.py", line 47, in main
args.func(args)
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/commands/build.py", line 102, in build_command
build_doc(
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 367, in build_doc
anchors_mapping, source_files_mapping = build_mdx_files(
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 230, in build_mdx_files
raise type(e)(f"There was an error when converting {file} to the MDX format.\n" + e.args[0]) from e
ValueError: There was an error when converting ../datasets/docs/source/package_reference/main_classes.mdx to the MDX format.
Equality not supported between split train and <class 'inspect._empty'>
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4553 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4553/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4553/comments | https://api.github.com/repos/huggingface/datasets/issues/4553/events | https://github.com/huggingface/datasets/pull/4553 | 1,282,779,560 | PR_kwDODunzps46Q1q7 | 4,553 | Stop dropping columns in to_tf_dataset() before we load batches | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"@lhoestq Rebasing fixed the test failures, so this should be ready to review now! There's still a failure on Win but it seems unrelated.",
"Gentle ping @lhoestq ! This is a simple fix (dropping columns after loading a batch from th... | 2022-06-23T18:21:05Z | 2022-07-04T19:00:13Z | 2022-07-04T18:49:01Z | MEMBER | null | null | null | `to_tf_dataset()` dropped unnecessary columns before loading batches from the dataset, but this is causing problems when using a transform, because the dropped columns might be needed to compute the transform. Since there's no real way to check which columns the transform might need, we skip dropping columns and instead drop keys from the batch after we load it.
cc @amyeroberts and https://github.com/huggingface/notebooks/pull/202 | {
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https://api.github.com/repos/huggingface/datasets/issues/5848 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5848/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5848/comments | https://api.github.com/repos/huggingface/datasets/issues/5848/events | https://github.com/huggingface/datasets/pull/5848 | 1,707,506,734 | PR_kwDODunzps5QYa1B | 5,848 | Add `accelerate` as metric's test dependency to fix CI error | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-05-12T12:01:01Z | 2023-05-12T13:48:47Z | 2023-05-12T13:39:06Z | COLLABORATOR | null | null | null | The `frugalscore` metric uses Transformers' Trainer, which requires `accelerate` (as of recently).
Fixes the following [CI error](https://github.com/huggingface/datasets/actions/runs/4950900048/jobs/8855148703?pr=5845). | {
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https://api.github.com/repos/huggingface/datasets/issues/4813 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4813/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4813/comments | https://api.github.com/repos/huggingface/datasets/issues/4813/events | https://github.com/huggingface/datasets/pull/4813 | 1,333,287,756 | PR_kwDODunzps48446r | 4,813 | Fix loading example in opus dataset cards | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-09T13:47:38Z | 2022-08-09T17:52:15Z | 2022-08-09T17:38:18Z | MEMBER | null | null | null | This PR:
- fixes the examples to load the datasets, with the corrected dataset name, in their dataset cards for:
- opus_dgt
- opus_paracrawl
- opus_wikipedia
- fixes their dataset cards with the missing required information: title, data instances/fields/splits
- enumerates the supported languages
- adds a missing citation reference for opus_wikipedia
Related to:
- #4806 | {
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https://api.github.com/repos/huggingface/datasets/issues/7278 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7278/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7278/comments | https://api.github.com/repos/huggingface/datasets/issues/7278/events | https://github.com/huggingface/datasets/pull/7278 | 2,633,436,151 | PR_kwDODunzps6A1ORG | 7,278 | Let soundfile directly read local audio files | {
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https://api.github.com/repos/huggingface/datasets/issues/7001 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7001/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7001/comments | https://api.github.com/repos/huggingface/datasets/issues/7001/events | https://github.com/huggingface/datasets/issues/7001 | 2,372,930,879 | I_kwDODunzps6NcA0_ | 7,001 | Datasetbuilder Local Download FileNotFoundError | {
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"Ok it seems the solution is to use the directory string without the trailing \"/\" which in my case as: \r\n\r\n`parquet_dir = \"~/data/Parquet\" `\r\n\r\nStill i think this is a weird behavior... "
] | 2024-06-25T15:02:34Z | 2024-06-25T15:21:19Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
So I was trying to download a dataset and save it as parquet and I follow the [tutorial](https://huggingface.co/docs/datasets/filesystems#download-and-prepare-a-dataset-into-a-cloud-storage) of Huggingface. However, during the excution I face a FileNotFoundError.
I debug the code and it seems there is a bug there:
So first it creates a .incomplete folder and before moving its contents the following code deletes the directory
[Code](https://github.com/huggingface/datasets/blob/98fdc9e78e6d057ca66e58a37f49d6618aab8130/src/datasets/builder.py#L984)
hence as a result I face with:
``` FileNotFoundError: [Errno 2] No such file or directory: '~/data/Parquet/.incomplete '```
### Steps to reproduce the bug
```
from datasets import load_dataset_builder
from pathlib import Path
parquet_dir = "~/data/Parquet/"
Path(parquet_dir).mkdir(parents=True, exist_ok=True)
builder = load_dataset_builder(
"rotten_tomatoes",
)
builder.download_and_prepare(parquet_dir, file_format="parquet")
```
### Expected behavior
Downloads the files and saves as parquet
### Environment info
Ubuntu,
Python 3.10
```
datasets 2.19.1
``` | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7416 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7416/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7416/comments | https://api.github.com/repos/huggingface/datasets/issues/7416/events | https://github.com/huggingface/datasets/pull/7416 | 2,866,862,143 | PR_kwDODunzps6L77G2 | 7,416 | Release: 3.3.2 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7416). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-02-20T17:42:11Z | 2025-02-20T17:44:35Z | 2025-02-20T17:43:28Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6258 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6258/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6258/comments | https://api.github.com/repos/huggingface/datasets/issues/6258/events | https://github.com/huggingface/datasets/pull/6258 | 1,911,445,373 | PR_kwDODunzps5bHxHl | 6,258 | [DOCS] Fix typo: Elasticsearch | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-09-25T12:50:59Z | 2023-09-26T14:55:35Z | 2023-09-26T13:36:40Z | CONTRIBUTOR | null | null | null | Not ElasticSearch :) | {
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https://api.github.com/repos/huggingface/datasets/issues/5170 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5170/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5170/comments | https://api.github.com/repos/huggingface/datasets/issues/5170/events | https://github.com/huggingface/datasets/issues/5170 | 1,425,301,835 | I_kwDODunzps5U9GFL | 5,170 | [Caching] Deterministic hashing of torch tensors | {
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] | closed | false | null | [] | null | [] | 2022-10-27T09:15:15Z | 2022-11-02T17:18:43Z | 2022-11-02T17:18:43Z | MEMBER | null | null | {
"completed": 0,
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} | Currently this fails
```python
import torch
from datasets.fingerprint import Hasher
t = torch.tensor([1.])
def func(x):
return t + x
hash1 = Hasher.hash(func)
t = torch.tensor([1.])
hash2 = Hasher.hash(func)
assert hash1 == hash2
```
Also as noticed in https://discuss.huggingface.co/t/dataset-cant-cache-models-outputs/24945, using a model in a `map` function doesn't work well with caching. Indeed the `bert-base-uncased` model has a different hash every time you reload it. Supporting torch tensors may also help in this case.
This can be fixed by registering a custom pickling functions for torch tensors - as we did for other objects such as CodeType, FunctionType and Regex in `py_utils.py` | {
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https://api.github.com/repos/huggingface/datasets/issues/4729 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4729/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4729/comments | https://api.github.com/repos/huggingface/datasets/issues/4729/events | https://github.com/huggingface/datasets/pull/4729 | 1,313,374,015 | PR_kwDODunzps473GmR | 4,729 | Refactor Hub tests | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-21T14:43:13Z | 2022-07-22T15:09:49Z | 2022-07-22T14:56:29Z | MEMBER | null | null | null | This PR refactors `test_upstream_hub` by removing unittests and using the following pytest Hub fixtures:
- `ci_hub_config`
- `set_ci_hub_access_token`: to replace setUp/tearDown
- `temporary_repo` context manager: to replace `try... finally`
- `cleanup_repo`: to delete repo accidentally created if one of the tests fails
This is a preliminary work done to manage unit/integration tests separately. | {
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https://api.github.com/repos/huggingface/datasets/issues/7229 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7229/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7229/comments | https://api.github.com/repos/huggingface/datasets/issues/7229/events | https://github.com/huggingface/datasets/pull/7229 | 2,588,847,398 | PR_kwDODunzps5-rgrx | 7,229 | handle config_name=None in push_to_hub | {
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"not sure it's a good idea, we always need a config name so better have the correct default and not support None (which could lead to think it doesn't have a config name, while it does)"
] | 2024-10-15T13:48:57Z | 2024-10-24T17:51:52Z | 2024-10-24T17:51:52Z | CONTRIBUTOR | null | null | null | This caught me out - thought it might be better to explicitly handle None? | {
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https://api.github.com/repos/huggingface/datasets/issues/6145 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6145/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6145/comments | https://api.github.com/repos/huggingface/datasets/issues/6145/events | https://github.com/huggingface/datasets/pull/6145 | 1,847,811,310 | PR_kwDODunzps5Xx5If | 6,145 | Export to_iterable_dataset to document | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-08-12T07:00:14Z | 2023-08-15T17:04:01Z | 2023-08-15T16:55:24Z | CONTRIBUTOR | null | null | null | Fix the export of a missing method of `Dataset` | {
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https://api.github.com/repos/huggingface/datasets/issues/5909 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5909/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5909/comments | https://api.github.com/repos/huggingface/datasets/issues/5909/events | https://github.com/huggingface/datasets/pull/5909 | 1,728,900,068 | PR_kwDODunzps5Rgga6 | 5,909 | Use more efficient and idiomatic way to construct list. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-05-27T18:54:47Z | 2023-05-31T15:37:11Z | 2023-05-31T13:28:29Z | CONTRIBUTOR | null | null | null | Using `*` is ~2X faster according to [benchmark](https://colab.research.google.com/gist/ttsugriy/c964a2604edf70c41911b10335729b6a/for-vs-mult.ipynb) with just 4 patterns. This doesn't matter much since this tiny difference is not going to be noticeable, but why not? | {
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https://api.github.com/repos/huggingface/datasets/issues/4741 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4741/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4741/comments | https://api.github.com/repos/huggingface/datasets/issues/4741/events | https://github.com/huggingface/datasets/pull/4741 | 1,316,621,272 | PR_kwDODunzps48B2fl | 4,741 | Fix to dict conversion of `DatasetInfo`/`Features` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-25T10:41:27Z | 2022-07-25T12:50:36Z | 2022-07-25T12:37:53Z | COLLABORATOR | null | null | null | Fix #4681 | {
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https://api.github.com/repos/huggingface/datasets/issues/5875 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5875/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5875/comments | https://api.github.com/repos/huggingface/datasets/issues/5875/events | https://github.com/huggingface/datasets/issues/5875 | 1,716,770,394 | I_kwDODunzps5mU9Za | 5,875 | Why split slicing doesn't behave like list slicing ? | {
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"A duplicate of https://github.com/huggingface/datasets/issues/1774"
] | 2023-05-19T07:21:10Z | 2024-01-31T15:54:18Z | 2024-01-31T15:54:18Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
If I want to get the first 10 samples of my dataset, I can do :
```
ds = datasets.load_dataset('mnist', split='train[:10]')
```
But if I exceed the number of samples in the dataset, an exception is raised :
```
ds = datasets.load_dataset('mnist', split='train[:999999999]')
```
> ValueError: Requested slice [:999999999] incompatible with 60000 examples.
### Steps to reproduce the bug
```
ds = datasets.load_dataset('mnist', split='train[:999999999]')
```
### Expected behavior
I would expect it to behave like python lists (no exception raised, the whole list is kept) :
```
d = list(range(1000))[:999999]
print(len(d)) # > 1000
```
### Environment info
- `datasets` version: 2.9.0
- Platform: macOS-12.6-arm64-arm-64bit
- Python version: 3.9.12
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/4585 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4585/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4585/comments | https://api.github.com/repos/huggingface/datasets/issues/4585/events | https://github.com/huggingface/datasets/pull/4585 | 1,287,064,929 | PR_kwDODunzps46e1Ne | 4,585 | Host multi_news data on the Hub instead of Google Drive | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-28T09:32:06Z | 2022-06-28T14:19:35Z | 2022-06-28T14:08:48Z | MEMBER | null | null | null | Host data files of multi_news dataset on the Hub.
They were on Google Drive.
Fix #4580. | {
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https://api.github.com/repos/huggingface/datasets/issues/5664 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5664/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5664/comments | https://api.github.com/repos/huggingface/datasets/issues/5664/events | https://github.com/huggingface/datasets/pull/5664 | 1,637,192,684 | PR_kwDODunzps5Mt6vp | 5,664 | Fix CI by temporarily pinning tensorflow < 2.12.0 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-03-23T09:52:26Z | 2023-03-23T10:17:11Z | 2023-03-23T10:09:54Z | MEMBER | null | null | null | As a hotfix for our CI, temporarily pin `tensorflow` upper version:
- In Python 3.10, tensorflow-2.12.0 also installs `jax`
Fix #5663
Until root cause is fixed. | {
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https://api.github.com/repos/huggingface/datasets/issues/5227 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5227/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5227/comments | https://api.github.com/repos/huggingface/datasets/issues/5227/events | https://github.com/huggingface/datasets/issues/5227 | 1,444,620,094 | I_kwDODunzps5WGyc- | 5,227 | datasets.data_files.EmptyDatasetError: The directory at wikisql doesn't contain any data files | {
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"Fixed. Please close.",
"how to fix?i need your help"
] | 2022-11-10T21:57:06Z | 2023-10-07T05:04:41Z | 2022-11-10T22:05:43Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
From these lines:
from datasets import list_datasets, load_dataset
dataset = load_dataset("wikisql","binary")
I get error message:
datasets.data_files.EmptyDatasetError: The directory at wikisql doesn't contain any data files
And yet the 'wikisql' is reported to exist via the list_datasets().
Any help appreciated.
### Steps to reproduce the bug
From these lines:
from datasets import list_datasets, load_dataset
dataset = load_dataset("wikisql","binary")
I get error message:
datasets.data_files.EmptyDatasetError: The directory at wikisql doesn't contain any data files
And yet the 'wikisql' is reported to exist via the list_datasets().
Any help appreciated.
### Expected behavior
Dataset should load. This same code used to work.
### Environment info
Mac OS | {
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https://api.github.com/repos/huggingface/datasets/issues/4930 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4930/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4930/comments | https://api.github.com/repos/huggingface/datasets/issues/4930/events | https://github.com/huggingface/datasets/pull/4930 | 1,362,193,587 | PR_kwDODunzps4-Yflc | 4,930 | Add cc-by-nc-2.0 to list of licenses | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"this list needs to be kept in sync with the ones in moon-landing and hub-docs :)",
"@julien-c don't you think it might be better to a have a single file (source of truth) in one of the repos and then use it in every other repo, ins... | 2022-09-05T15:37:32Z | 2022-09-06T16:43:32Z | 2022-09-05T17:01:04Z | MEMBER | null | null | null | This PR adds the `cc-by-nc-2.0` to the list of licenses because it is required by `scifact` dataset: https://github.com/allenai/scifact/blob/master/LICENSE.md | {
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https://api.github.com/repos/huggingface/datasets/issues/7099 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7099/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7099/comments | https://api.github.com/repos/huggingface/datasets/issues/7099/events | https://github.com/huggingface/datasets/pull/7099 | 2,465,221,827 | PR_kwDODunzps54U7s4 | 7,099 | Set dev version | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7099). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-08-14T08:31:17Z | 2024-08-14T08:45:17Z | 2024-08-14T08:39:25Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5259 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5259/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5259/comments | https://api.github.com/repos/huggingface/datasets/issues/5259/events | https://github.com/huggingface/datasets/issues/5259 | 1,453,555,923 | I_kwDODunzps5Wo4DT | 5,259 | datasets 2.7 introduces sharding error | {
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"I notice a comment in the code says:\r\n`Having lists of different sizes makes sharding ambigious, raise an error in this case until we decide how to define sharding without ambiguity for users` \r\n \r\n ... which suggests this update was pushed knowing that it might break some things. But, it didn't seem to h... | 2022-11-17T15:36:52Z | 2022-12-24T01:44:02Z | 2022-11-18T12:52:05Z | NONE | null | null | {
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} | ### Describe the bug
dataset fails to load with runtime error
`RuntimeError: Sharding is ambiguous for this dataset: we found several data sources lists of different lengths, and we don't know over which list we should parallelize:
- key audio_files has length 46
- key data has length 0
To fix this, check the 'gen_kwargs' and make sure to use lists only for data sources, and use tuples otherwise. In the end there should only be one single list, or several lists with the same length.`
### Steps to reproduce the bug
With datasets[audio] 2.7 loaded, and logged into hugging face,
`data = datasets.load_dataset('sil-ai/bloom-speech', 'bis', use_auth_token=True)`
creates the error.
Full stack trace:
```---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
[<ipython-input-7-8cb9ca0f79f0>](https://localhost:8080/#) in <module>
----> 1 data = datasets.load_dataset('sil-ai/bloom-speech', 'bis', use_auth_token=True)
5 frames
[/usr/local/lib/python3.7/dist-packages/datasets/load.py](https://localhost:8080/#) in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, num_proc, **config_kwargs)
1745 try_from_hf_gcs=try_from_hf_gcs,
1746 use_auth_token=use_auth_token,
-> 1747 num_proc=num_proc,
1748 )
1749
[/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in download_and_prepare(self, output_dir, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, file_format, max_shard_size, num_proc, storage_options, **download_and_prepare_kwargs)
824 verify_infos=verify_infos,
825 **prepare_split_kwargs,
--> 826 **download_and_prepare_kwargs,
827 )
828 # Sync info
[/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in _download_and_prepare(self, dl_manager, verify_infos, **prepare_splits_kwargs)
1554 def _download_and_prepare(self, dl_manager, verify_infos, **prepare_splits_kwargs):
1555 super()._download_and_prepare(
-> 1556 dl_manager, verify_infos, check_duplicate_keys=verify_infos, **prepare_splits_kwargs
1557 )
1558
[/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
911 try:
912 # Prepare split will record examples associated to the split
--> 913 self._prepare_split(split_generator, **prepare_split_kwargs)
914 except OSError as e:
915 raise OSError(
[/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split(self, split_generator, check_duplicate_keys, file_format, num_proc, max_shard_size)
1362 fpath = path_join(self._output_dir, fname)
1363
-> 1364 num_input_shards = _number_of_shards_in_gen_kwargs(split_generator.gen_kwargs)
1365 if num_input_shards <= 1 and num_proc is not None:
1366 logger.warning(
[/usr/local/lib/python3.7/dist-packages/datasets/utils/sharding.py](https://localhost:8080/#) in _number_of_shards_in_gen_kwargs(gen_kwargs)
16 + "\n".join(f"\t- key {key} has length {length}" for key, length in lists_lengths.items())
17 + "\nTo fix this, check the 'gen_kwargs' and make sure to use lists only for data sources, "
---> 18 + "and use tuples otherwise. In the end there should only be one single list, or several lists with the same length."
19 )
20 )
RuntimeError: Sharding is ambiguous for this dataset: we found several data sources lists of different lengths, and we don't know over which list we should parallelize:
- key audio_files has length 46
- key data has length 0
To fix this, check the 'gen_kwargs' and make sure to use lists only for data sources, and use tuples otherwise. In the end there should only be one single list, or several lists with the same length.```
### Expected behavior
the dataset loads in datasets version 2.6.1 and should load with datasets 2.7
### Environment info
- `datasets` version: 2.7.0
- Platform: Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.15
- PyArrow version: 6.0.1
- Pandas version: 1.3.5 | {
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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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"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... | 2022-10-13T09:12:58Z | 2022-10-17T10:38:45Z | 2022-10-17T10:38:45Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ## 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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https://api.github.com/repos/huggingface/datasets/issues/7206 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7206/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7206/comments | https://api.github.com/repos/huggingface/datasets/issues/7206/events | https://github.com/huggingface/datasets/issues/7206 | 2,573,567,467 | I_kwDODunzps6ZZYXr | 7,206 | Slow iteration for iterable dataset with numpy formatting for array data | {
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"The below easily eats up 32G of RAM. Leaving it for a while bricked the laptop with 16GB.\r\n\r\n```\r\ndataset = load_dataset(\"Voxel51/OxfordFlowers102\", data_dir=\"data\").with_format(\"numpy\")\r\nprocessed_dataset = dataset.map(lambda x: x)\r\n```\r\n\r\n![image](https://github.com/user-attachments/assets/c1... | 2024-10-08T15:38:11Z | 2024-10-17T17:14:52Z | null | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
When working with large arrays, setting with_format to e.g. numpy then applying map causes a significant slowdown for iterable datasets.
### Steps to reproduce the bug
```python
import numpy as np
import time
from datasets import Dataset, Features, Array3D
features=Features(**{"array0": Array3D((None, 10, 10), dtype="float32"), "array1": Array3D((None,10,10), dtype="float32")})
dataset = Dataset.from_dict({f"array{i}": [np.zeros((x,10,10), dtype=np.float32) for x in [2000,1000]*25] for i in range(2)}, features=features)
```
Then
```python
ds = dataset.to_iterable_dataset()
ds = ds.with_format("numpy").map(lambda x: x)
t0 = time.time()
for ex in ds:
pass
t1 = time.time()
print(t1-t0)
```
takes 27 s, whereas
```python
ds = dataset.to_iterable_dataset()
ds = ds.with_format("numpy")
ds = dataset.to_iterable_dataset()
t0 = time.time()
for ex in ds:
pass
t1 = time.time()
print(t1 - t0)
```
takes ~1s
### Expected behavior
Map should not introduce a slowdown when formatting is enabled.
### Environment info
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https://api.github.com/repos/huggingface/datasets/issues/7188 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7188/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7188/comments | https://api.github.com/repos/huggingface/datasets/issues/7188/events | https://github.com/huggingface/datasets/pull/7188 | 2,560,712,689 | PR_kwDODunzps59VSrf | 7,188 | Pin multiprocess<0.70.1 to align with dill<0.3.9 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7188). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2024-10-02T05:40:18Z | 2024-10-02T06:08:25Z | 2024-10-02T06:08:23Z | MEMBER | null | null | null | Pin multiprocess<0.70.1 to align with dill<0.3.9.
Note that multiprocess-0.70.1 requires dill-0.3.9: https://github.com/uqfoundation/multiprocess/releases/tag/0.70.17
Fix #7186. | {
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https://api.github.com/repos/huggingface/datasets/issues/4873 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4873/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4873/comments | https://api.github.com/repos/huggingface/datasets/issues/4873/events | https://github.com/huggingface/datasets/issues/4873 | 1,347,592,022 | I_kwDODunzps5QUp9W | 4,873 | Multiple dataloader memory error | {
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] | open | false | null | [] | null | [
"Hi!\r\n\r\n200+ data loaders is a lot. Have you tried to reduce the number of datasets by concatenating/interleaving the ones with the same structure/task (the API is `{concatenate_datasets/interleave_datasets}([dset1, ..., dset_N])`)?",
"Hi @mariosasko, thank you for your reply. I tried pre-concatenating differ... | 2022-08-23T08:59:50Z | 2023-01-26T02:01:11Z | null | NONE | null | null | {
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} | For the use of multiple datasets and tasks, we use around more than 200+ dataloaders, then pass it into `dataloader1, dataloader2, ..., dataloader200=accelerate.prepare(dataloader1, dataloader2, ..., dataloader200)`
It causes the memory error when generating batches. Any solutions to it?
```bash
File "/home/xxx/my_code/src/utils/data_utils.py", line 54, in generate_batch
x = next(iterator)
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/accelerate/data_loader.py", line 301, in __iter__
for batch in super().__iter__():
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 435, in __next__
data = self._next_data()
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 475, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 28, in fetch
data.append(next(self.dataset_iter))
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/accelerate/data_loader.py", line 249, in __iter__
for element in self.dataset:
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 503, in __iter__
for key, example in self._iter():
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 500, in _iter
yield from ex_iterable
File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 231, in __iter__
new_key = "_".join(str(key) for key in keys)
MemoryError
``` | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4742 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4742/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4742/comments | https://api.github.com/repos/huggingface/datasets/issues/4742/events | https://github.com/huggingface/datasets/issues/4742 | 1,317,260,663 | I_kwDODunzps5Og813 | 4,742 | Dummy data nowhere to be found | {
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"Hi @BramVanroy, thanks for reporting.\r\n\r\nFirst of all, please note that you do not need the dummy data: this was the case when we were adding datasets to the `datasets` library (on this GitHub repo), so that we could test the correct loading of all datasets with our CI. However, this is no longer the case for ... | 2022-07-25T19:18:42Z | 2022-11-04T14:04:24Z | 2022-11-04T14:04:10Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ## Describe the bug
To finalize my dataset, I wanted to create dummy data as per the guide and I ran
```shell
datasets-cli dummy_data datasets/hebban-reviews --auto_generate
```
where hebban-reviews is [this repo](https://huggingface.co/datasets/BramVanroy/hebban-reviews). And even though the scripts runs and shows a message at the end that it succeeded, I cannot find the dummy data anywhere. Where is it?
## Expected results
To see the dummy data in the datasets' folder or in the folder where I ran the command.
## Actual results
I see the following message but I cannot find the dummy data anywhere.
```
Dummy data generation done and dummy data test succeeded for config 'filtered''.
Automatic dummy data generation succeeded for all configs of '.\datasets\hebban-reviews\'
```
## Environment info
- `datasets` version: 2.4.1.dev0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.8
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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```
error: `ruff <path>` has been removed. Use `ruff check <path>` instead.
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4575 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4575/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4575/comments | https://api.github.com/repos/huggingface/datasets/issues/4575/events | https://github.com/huggingface/datasets/issues/4575 | 1,285,446,700 | I_kwDODunzps5Mnlws | 4,575 | Problem about wmt17 zh-en dataset | {
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"Running into the same error with `wmt17/zh-en`, `wmt18/zh-en` and `wmt19/zh-en`.",
"@albertvillanova @lhoestq Could you take a look at this issue?",
"@winterfell2021 Hi, I wonder where the code you provided should be added. I tried to add them in the `datasets/table.py` in `array_cast` function, however, the '... | 2022-06-27T08:35:42Z | 2022-08-23T10:01:02Z | 2022-08-23T10:00:21Z | NONE | null | null | {
"completed": 0,
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} | It seems that in subset casia2015, some samples are like `{'c[hn]':'xxx', 'en': 'aa'}`.
So when using `data = load_dataset('wmt17', "zh-en")` to load the wmt17 zh-en dataset, which will raise the exception:
```
Traceback (most recent call last):
File "train.py", line 78, in <module>
data = load_dataset(args.dataset, "zh-en")
File "/usr/local/lib/python3.7/dist-packages/datasets/load.py", line 1684, in load_dataset
use_auth_token=use_auth_token,
File "/usr/local/lib/python3.7/dist-packages/datasets/builder.py", line 705, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/usr/local/lib/python3.7/dist-packages/datasets/builder.py", line 1221, in _download_and_prepare
super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos)
File "/usr/local/lib/python3.7/dist-packages/datasets/builder.py", line 793, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.7/dist-packages/datasets/builder.py", line 1215, in _prepare_split
num_examples, num_bytes = writer.finalize()
File "/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py", line 533, in finalize
self.write_examples_on_file()
File "/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py", line 410, in write_examples_on_file
self.write_batch(batch_examples=batch_examples)
File "/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py", line 503, in write_batch
arrays.append(pa.array(typed_sequence))
File "pyarrow/array.pxi", line 230, in pyarrow.lib.array
File "pyarrow/array.pxi", line 110, in pyarrow.lib._handle_arrow_array_protocol
File "/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py", line 198, in __arrow_array__
out = cast_array_to_feature(out, type, allow_number_to_str=not self.trying_type)
File "/usr/local/lib/python3.7/dist-packages/datasets/table.py", line 1675, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/datasets/table.py", line 1846, in cast_array_to_feature
return array_cast(array, feature(), allow_number_to_str=allow_number_to_str)
File "/usr/local/lib/python3.7/dist-packages/datasets/table.py", line 1675, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/datasets/table.py", line 1756, in array_cast
raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{pa_type}")
TypeError: Couldn't cast array of type
struct<c[hn]: string, en: string, zh: string>
to
struct<en: string, zh: string>
```
So the solution of this problem is to change the original array manually:
```
if 'c[hn]' in str(array.type):
py_array = array.to_pylist()
data_list = []
for vo in py_array:
tmp = {
'en': vo['en'],
}
if 'zh' not in vo:
tmp['zh'] = vo['c[hn]']
else:
tmp['zh'] = vo['zh']
data_list.append(tmp)
array = pa.array(data_list, type=pa.struct([
pa.field('en', pa.string()),
pa.field('zh', pa.string()),
]))
```
Therefore, maybe a correct version of original casia2015 file need to be updated | {
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https://api.github.com/repos/huggingface/datasets/issues/7195 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7195/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7195/comments | https://api.github.com/repos/huggingface/datasets/issues/7195/events | https://github.com/huggingface/datasets/issues/7195 | 2,564,070,809 | I_kwDODunzps6Y1J2Z | 7,195 | Add support for 3D datasets | {
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"maybe related: https://github.com/huggingface/datasets/issues/6388",
"Also look at https://github.com/huggingface/dataset-viewer/blob/f5fd117ceded990a7766e705bba1203fa907d6ad/services/worker/src/worker/job_runners/dataset/modalities.py#L241 which lists the 3D file formats that will assign the 3D modality to a da... | 2024-10-03T13:27:44Z | 2024-10-04T09:23:36Z | null | COLLABORATOR | null | null | {
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} | See https://huggingface.co/datasets/allenai/objaverse for example | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5396 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5396/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5396/comments | https://api.github.com/repos/huggingface/datasets/issues/5396/events | https://github.com/huggingface/datasets/pull/5396 | 1,514,002,934 | PR_kwDODunzps5GXMhp | 5,396 | Fix checksum verification | {
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} | [] | closed | false | null | [] | null | [
"Hi ! If I'm not mistaken both `expected_checksums[url]` and `recorded_checksums[url]` are dictionaries with keys \"checksum\" and \"num_bytes\". So we need to check whether `expected_checksums[url] != recorded_checksums[url]` (or simply `expected_checksums[url][\"checksum\"] != recorded_checksums[url][\"checksum\"... | 2022-12-29T19:45:17Z | 2023-02-13T11:11:22Z | 2023-02-13T11:11:22Z | CONTRIBUTOR | null | null | null | Expected checksum was verified against checksum dict (not checksum). | {
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https://api.github.com/repos/huggingface/datasets/issues/5538 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5538/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5538/comments | https://api.github.com/repos/huggingface/datasets/issues/5538/events | https://github.com/huggingface/datasets/issues/5538 | 1,587,732,596 | I_kwDODunzps5eouB0 | 5,538 | load_dataset in seaborn is not working for me. getting this error. | {
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"Hi! `seaborn`'s `load_dataset` pulls datasets from [here](https://github.com/mwaskom/seaborn-data) and not from our Hub, so this issue is not related to our library in any way and should be reported in their repo instead."
] | 2023-02-16T14:01:58Z | 2023-02-16T14:44:36Z | 2023-02-16T14:44:36Z | NONE | null | null | {
"completed": 0,
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} | TimeoutError Traceback (most recent call last)
~\anaconda3\lib\urllib\request.py in do_open(self, http_class, req, **http_conn_args)
1345 try:
-> 1346 h.request(req.get_method(), req.selector, req.data, headers,
1347 encode_chunked=req.has_header('Transfer-encoding'))
~\anaconda3\lib\http\client.py in request(self, method, url, body, headers, encode_chunked)
1278 """Send a complete request to the server."""
-> 1279 self._send_request(method, url, body, headers, encode_chunked)
1280
~\anaconda3\lib\http\client.py in _send_request(self, method, url, body, headers, encode_chunked)
1324 body = _encode(body, 'body')
-> 1325 self.endheaders(body, encode_chunked=encode_chunked)
1326
~\anaconda3\lib\http\client.py in endheaders(self, message_body, encode_chunked)
1273 raise CannotSendHeader()
-> 1274 self._send_output(message_body, encode_chunked=encode_chunked)
1275
~\anaconda3\lib\http\client.py in _send_output(self, message_body, encode_chunked)
1033 del self._buffer[:]
-> 1034 self.send(msg)
1035
~\anaconda3\lib\http\client.py in send(self, data)
973 if self.auto_open:
--> 974 self.connect()
975 else:
~\anaconda3\lib\http\client.py in connect(self)
1440
-> 1441 super().connect()
1442
~\anaconda3\lib\http\client.py in connect(self)
944 """Connect to the host and port specified in __init__."""
--> 945 self.sock = self._create_connection(
946 (self.host,self.port), self.timeout, self.source_address)
~\anaconda3\lib\socket.py in create_connection(address, timeout, source_address)
843 try:
--> 844 raise err
845 finally:
~\anaconda3\lib\socket.py in create_connection(address, timeout, source_address)
831 sock.bind(source_address)
--> 832 sock.connect(sa)
833 # Break explicitly a reference cycle
TimeoutError: [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond
During handling of the above exception, another exception occurred:
URLError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_12220/2927704185.py in <module>
1 import seaborn as sn
----> 2 iris = sn.load_dataset('iris')
~\anaconda3\lib\site-packages\seaborn\utils.py in load_dataset(name, cache, data_home, **kws)
594 if name not in get_dataset_names():
595 raise ValueError(f"'{name}' is not one of the example datasets.")
--> 596 urlretrieve(url, cache_path)
597 full_path = cache_path
598 else:
~\anaconda3\lib\urllib\request.py in urlretrieve(url, filename, reporthook, data)
237 url_type, path = _splittype(url)
238
--> 239 with contextlib.closing(urlopen(url, data)) as fp:
240 headers = fp.info()
241
~\anaconda3\lib\urllib\request.py in urlopen(url, data, timeout, cafile, capath, cadefault, context)
212 else:
213 opener = _opener
--> 214 return opener.open(url, data, timeout)
215
216 def install_opener(opener):
~\anaconda3\lib\urllib\request.py in open(self, fullurl, data, timeout)
515
516 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method())
--> 517 response = self._open(req, data)
518
519 # post-process response
~\anaconda3\lib\urllib\request.py in _open(self, req, data)
532
533 protocol = req.type
--> 534 result = self._call_chain(self.handle_open, protocol, protocol +
535 '_open', req)
536 if result:
~\anaconda3\lib\urllib\request.py in _call_chain(self, chain, kind, meth_name, *args)
492 for handler in handlers:
493 func = getattr(handler, meth_name)
--> 494 result = func(*args)
495 if result is not None:
496 return result
~\anaconda3\lib\urllib\request.py in https_open(self, req)
1387
1388 def https_open(self, req):
-> 1389 return self.do_open(http.client.HTTPSConnection, req,
1390 context=self._context, check_hostname=self._check_hostname)
1391
~\anaconda3\lib\urllib\request.py in do_open(self, http_class, req, **http_conn_args)
1347 encode_chunked=req.has_header('Transfer-encoding'))
1348 except OSError as err: # timeout error
-> 1349 raise URLError(err)
1350 r = h.getresponse()
1351 except:
URLError: <urlopen error [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond>
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https://api.github.com/repos/huggingface/datasets/issues/4819 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4819/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4819/comments | https://api.github.com/repos/huggingface/datasets/issues/4819/events | https://github.com/huggingface/datasets/pull/4819 | 1,335,064,449 | PR_kwDODunzps48-xc6 | 4,819 | Add missing language tags to resources | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-10T19:06:42Z | 2022-08-10T19:45:49Z | 2022-08-10T19:32:15Z | MEMBER | null | null | null | Add missing language tags to resources, required by existing datasets on GitHub. | {
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https://api.github.com/repos/huggingface/datasets/issues/6384 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6384/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6384/comments | https://api.github.com/repos/huggingface/datasets/issues/6384/events | https://github.com/huggingface/datasets/issues/6384 | 1,979,117,069 | I_kwDODunzps519u4N | 6,384 | Load the local dataset folder from other place | {
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"Solved"
] | 2023-11-06T13:07:04Z | 2023-11-19T05:42:06Z | 2023-11-19T05:42:05Z | NONE | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6210 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6210/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6210/comments | https://api.github.com/repos/huggingface/datasets/issues/6210/events | https://github.com/huggingface/datasets/pull/6210 | 1,879,649,731 | PR_kwDODunzps5Zc4JF | 6,210 | Temporarily pin fsspec < 2023.9.0 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-09-04T07:07:07Z | 2023-09-04T07:40:23Z | 2023-09-04T07:30:00Z | MEMBER | null | null | null | Temporarily pin fsspec < 2023.9.0 until permanent solution is found.
Hot fix #6209. | {
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https://api.github.com/repos/huggingface/datasets/issues/7471 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7471/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7471/comments | https://api.github.com/repos/huggingface/datasets/issues/7471/events | https://github.com/huggingface/datasets/issues/7471 | 2,937,530,069 | I_kwDODunzps6vFybV | 7,471 | Adding argument to `_get_data_files_patterns` | {
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"Hi ! The pattern can be specified in advance in YAML in the README.md of the dataset :)\n\nFor example\n\n```\n---\nconfigs:\n- config_name: default\n data_files:\n - split: train\n path: \"train/*\"\n - split: test\n path: \"test/*\"\n---\n```\n\nSee the docs at https://huggingface.co/docs/hub/en/dataset... | 2025-03-21T07:17:53Z | 2025-03-27T12:30:52Z | 2025-03-26T07:26:27Z | NONE | null | null | {
"completed": 0,
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} | ### Feature request
How about adding if the user already know about the pattern?
https://github.com/huggingface/datasets/blob/a256b85cbc67aa3f0e75d32d6586afc507cf535b/src/datasets/data_files.py#L252
### Motivation
While using this load_dataset people might use 10M of images for the local files.
However, due to searching all the appropriate file pattern in fsspec, purely searching this pattern takes more than 10 hours (real use-case).
### Your contribution
Yeah I can make this happen if this seems valid. @lhoestq WDYT?
such like
```
def _get_data_files_patterns(pattern_resolver: Callable[[str], list[str]], patterns: PATTERNS) -> dict[str, list[str]]:
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4853 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4853/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4853/comments | https://api.github.com/repos/huggingface/datasets/issues/4853/events | https://github.com/huggingface/datasets/pull/4853 | 1,339,456,490 | PR_kwDODunzps49NFNL | 4,853 | Fix bug and checksums in exams dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-15T20:17:57Z | 2022-08-16T06:43:57Z | 2022-08-16T06:29:06Z | MEMBER | null | null | null | Fix #4852. | {
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https://api.github.com/repos/huggingface/datasets/issues/5361 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5361/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5361/comments | https://api.github.com/repos/huggingface/datasets/issues/5361/events | https://github.com/huggingface/datasets/issues/5361 | 1,497,153,889 | I_kwDODunzps5ZPMFh | 5,361 | How concatenate `Audio` elements using batch mapping | {
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"You can try something like this ?\r\n```python\r\ndef mapper_function(batch):\r\n return {\"concatenated_audio\": [np.concatenate([audio[\"array\"] for audio in batch[\"audio\"]])]}\r\n\r\ndataset = dataset.map(\r\n mapper_function,\r\n batched=True,\r\n batch_size=3,\r\n remove_columns=list(dataset.... | 2022-12-14T18:13:55Z | 2023-07-21T14:30:51Z | 2023-07-21T14:30:51Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I am trying to do concatenate audios in a dataset e.g. `google/fleurs`.
```python
print(dataset)
# Dataset({
# features: ['path', 'audio'],
# num_rows: 24
# })
def mapper_function(batch):
# to merge every 3 audio
# np.concatnate(audios[i: i+3]) for i in range(i, len(batch), 3)
dataset = dataset.map(mapper_function, batch=True, batch_size=24)
print(dataset)
# Expected output:
# Dataset({
# features: ['path', 'audio'],
# num_rows: 8
# })
```
I tried to construct `result={}` dictionary inside the mapper function, I just found it will not work because it needs `byte` also needed :((
I'd appreciate if your share any use cases similar to my problem or any solutions really. Thanks!
cc: @lhoestq
### Steps to reproduce the bug
1. load audio dataset
2. try to merge every k audios and return as one
### Expected behavior
Merged dataset with a fewer rows. If we merge every 3 rows, then `n // 3` number of examples.
### Environment info
- `datasets` version: 2.1.0
- Platform: Linux-5.15.65+-x86_64-with-debian-bullseye-sid
- Python version: 3.7.12
- PyArrow version: 8.0.0
- Pandas version: 1.3.5 | {
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https://api.github.com/repos/huggingface/datasets/issues/5953 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5953/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5953/comments | https://api.github.com/repos/huggingface/datasets/issues/5953/events | https://github.com/huggingface/datasets/issues/5953 | 1,756,520,523 | I_kwDODunzps5osmBL | 5,953 | Bad error message when trying to download gated dataset | {
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"cc @sanchit-gandhi @Vaibhavs10 @lhoestq - this is mainly for demos that use Common Voice datasets as done here: https://github.com/facebookresearch/fairseq/tree/main/examples/mms#-transformers\r\n",
"Hi ! the error for me is\r\n\r\n```\r\nFileNotFoundError: Couldn't find a dataset script at /content/mozilla-foun... | 2023-06-14T10:03:39Z | 2023-06-14T16:36:51Z | 2023-06-14T12:26:32Z | CONTRIBUTOR | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make sure you specified the correct `repo_id` and `repo_type`.
If you are trying to access a private or gated repo, make sure you are authenticated.
Invalid username or password..
Will try to load from local cache.
```
If I do the same for a gated dataset on the Hub, I'm not gated a nice error message IMO:
```sh
File ~/hf/lib/python3.10/site-packages/fsspec/implementations/http.py:430, in HTTPFileSystem._info(self, url, **kwargs)
427 except Exception as exc:
428 if policy == "get":
429 # If get failed, then raise a FileNotFoundError
--> 430 raise FileNotFoundError(url) from exc
431 logger.debug(str(exc))
433 return {"name": url, "size": None, **info, "type": "file"}
FileNotFoundError: https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0/resolve/main/n_shards.json
```
### Steps to reproduce the bug
```
huggingface-cli logout
```
and then:
```py
from datasets import load_dataset, Audio
# English
stream_data = load_dataset("mozilla-foundation/common_voice_13_0", "en", split="test", streaming=True)
stream_data = stream_data.cast_column("audio", Audio(sampling_rate=16000))
en_sample = next(iter(stream_data))["audio"]["array"]
# Swahili
stream_data = load_dataset("mozilla-foundation/common_voice_13_0", "sw", split="test", streaming=True)
stream_data = stream_data.cast_column("audio", Audio(sampling_rate=16000))
sw_sample = next(iter(stream_data))["audio"]["array"]
```
### Expected behavior
Better error message
### Environment info
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 2.12.0
- Platform: Linux-6.2.0-76060200-generic-x86_64-with-glibc2.35
- Python version: 3.10.6
- Huggingface_hub version: 0.16.0.dev0
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
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https://api.github.com/repos/huggingface/datasets/issues/6405 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6405/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6405/comments | https://api.github.com/repos/huggingface/datasets/issues/6405/events | https://github.com/huggingface/datasets/issues/6405 | 1,990,358,743 | I_kwDODunzps52onbX | 6,405 | ConfigNamesError on a simple CSV file | {
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"The viewer is working now. \r\n\r\nBased on the repo commit history, the bug was due to the incorrect format of the `features` field in the README YAML (`Value` requires `dtype`, e.g., `Value(\"string\")`, but it was not specified)",
"Feel free to close the issue",
"Oh, OK! Thanks. So, there was no reason to o... | 2023-11-13T10:28:29Z | 2023-11-13T20:01:24Z | 2023-11-13T20:01:24Z | COLLABORATOR | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | See https://huggingface.co/datasets/Nguyendo1999/mmath/discussions/1
```
Error code: ConfigNamesError
Exception: TypeError
Message: __init__() missing 1 required positional argument: 'dtype'
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 65, in compute_config_names_response
for config in sorted(get_dataset_config_names(path=dataset, token=hf_token))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1512, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1489, in dataset_module_factory
return HubDatasetModuleFactoryWithoutScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1039, in get_module
dataset_infos = DatasetInfosDict.from_dataset_card_data(dataset_card_data)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 468, in from_dataset_card_data
dataset_info = DatasetInfo._from_yaml_dict(dataset_card_data["dataset_info"])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 399, in _from_yaml_dict
yaml_data["features"] = Features._from_yaml_list(yaml_data["features"])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1838, in _from_yaml_list
return cls.from_dict(from_yaml_inner(yaml_data))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1690, in from_dict
obj = generate_from_dict(dic)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1345, in generate_from_dict
return {key: generate_from_dict(value) for key, value in obj.items()}
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1345, in <dictcomp>
return {key: generate_from_dict(value) for key, value in obj.items()}
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1353, in generate_from_dict
return class_type(**{k: v for k, v in obj.items() if k in field_names})
TypeError: __init__() missing 1 required positional argument: 'dtype'
```
This is the CSV file: https://huggingface.co/datasets/Nguyendo1999/mmath/blob/dbcdd7c2c6fc447f852ec136a7532292802bb46f/math_train.csv | {
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https://api.github.com/repos/huggingface/datasets/issues/6520 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6520/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6520/comments | https://api.github.com/repos/huggingface/datasets/issues/6520/events | https://github.com/huggingface/datasets/pull/6520 | 2,052,059,078 | PR_kwDODunzps5ijUiw | 6,520 | Support commit_description parameter in push_to_hub | {
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} | [] | closed | false | null | [] | null | [
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6520). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2023-12-21T09:36:11Z | 2023-12-21T14:49:47Z | 2023-12-21T14:43:35Z | MEMBER | null | null | null | Support `commit_description` parameter in `push_to_hub`.
CC: @Wauplin | {
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https://api.github.com/repos/huggingface/datasets/issues/6368 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6368/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6368/comments | https://api.github.com/repos/huggingface/datasets/issues/6368/events | https://github.com/huggingface/datasets/pull/6368 | 1,971,193,692 | PR_kwDODunzps5eRZwQ | 6,368 | Fix python formatting for complex types in `format_table` | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-10-31T19:48:08Z | 2023-11-02T14:42:28Z | 2023-11-02T14:21:16Z | COLLABORATOR | null | null | null | Fix #6366 | {
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https://api.github.com/repos/huggingface/datasets/issues/5421 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5421/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5421/comments | https://api.github.com/repos/huggingface/datasets/issues/5421/events | https://github.com/huggingface/datasets/issues/5421 | 1,532,278,307 | I_kwDODunzps5bVLYj | 5,421 | Support case-insensitive Hub dataset name in load_dataset | {
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"Closing as case-insensitivity should be only for URL redirection on the Hub. In the APIs, we will only support the canonical name (https://github.com/huggingface/moon-landing/pull/2399#issuecomment-1382085611)"
] | 2023-01-13T13:07:07Z | 2023-01-13T20:12:32Z | 2023-01-13T20:12:32Z | COLLABORATOR | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Feature request
The dataset name on the Hub is case-insensitive (see https://github.com/huggingface/moon-landing/pull/2399, internal issue), i.e., https://huggingface.co/datasets/GLUE redirects to https://huggingface.co/datasets/glue.
Ideally, we could load the glue dataset using the following:
```
from datasets import load_dataset
load_dataset('GLUE', 'cola')
```
It breaks because the loading script `GLUE.py` does not exist (`glue.py` should be selected instead).
Minor additional comment: in other cases without a loading script, we can load the dataset, but the automatically generated config name depends on the casing:
- `load_dataset('severo/danish-wit')` generates the config name `severo--danish-wit-e6fda5b070deb133`, while
- `load_dataset('severo/danish-WIT')` generates the config name `severo--danish-WIT-e6fda5b070deb133`
### Motivation
To follow the same UX on the Hub and in the datasets library.
### Your contribution
... | {
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https://api.github.com/repos/huggingface/datasets/issues/5380 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5380/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5380/comments | https://api.github.com/repos/huggingface/datasets/issues/5380/events | https://github.com/huggingface/datasets/issues/5380 | 1,504,404,043 | I_kwDODunzps5Zq2JL | 5,380 | Improve dataset `.skip()` speed in streaming mode | {
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"Hi! I agree `skip` can be inefficient to use in the current state.\r\n\r\nTo make it fast, we could use \"statistics\" stored in Parquet metadata and read only the chunks needed to form a dataset. \r\n\r\nAnd thanks to the \"datasets-server\" project, which aims to store the Parquet versions of the Hub datasets (o... | 2022-12-20T11:25:23Z | 2023-03-08T10:47:12Z | null | CONTRIBUTOR | null | null | {
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} | ### Feature request
Add extra information to the `dataset_infos.json` file to include the number of samples/examples in each shard, for example in a new field `num_examples` alongside `num_bytes`. The `.skip()` function could use this information to ignore the download of a shard when in streaming mode, which AFAICT it should speed up the skipping process.
### Motivation
When resuming from a checkpoint after a crashed run, using `dataset.skip()` is very convenient to recover the exact state of the data and to not train again over the same examples (assuming same seed, no shuffling). However, I have noticed that for audio datasets in streaming mode this is very costly in terms of time, as shards need to be downloaded every time before skipping the right number of examples.
### Your contribution
I took a look already at the code, but it seems a change like this is way deeper than I am able to manage, as it touches the library in several parts. I could give it a try but might need some guidance on the internals. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4897 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4897/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4897/comments | https://api.github.com/repos/huggingface/datasets/issues/4897/events | https://github.com/huggingface/datasets/issues/4897 | 1,351,784,727 | I_kwDODunzps5QkpkX | 4,897 | datasets generate large arrow file | {
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"Hi ! The cache files are the results of all the transforms you applied to the dataset using `map` for example.\r\nDid you run a transform that could potentially blow up the size of the dataset ?",
"@lhoestq,\r\nI don't remember, but I can't imagine what kind of transform may generate data that grow over 200 time... | 2022-08-26T05:51:16Z | 2022-09-18T05:07:52Z | 2022-09-18T05:07:52Z | NONE | null | null | {
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} | Checking the large file in disk, and found the large cache file in the cifar10 data directory:
As we know, the size of cifar10 dataset is ~130MB, but the cache file has almost 30GB size, there may be some problems here. | {
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https://api.github.com/repos/huggingface/datasets/issues/5961 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5961/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5961/comments | https://api.github.com/repos/huggingface/datasets/issues/5961/events | https://github.com/huggingface/datasets/issues/5961 | 1,758,525,111 | I_kwDODunzps5o0Pa3 | 5,961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | {
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"Does \"number of shards\" refer to the total number of data?\r\n\r\nmy config:\r\nnproc_per_node=2\r\nds=ds['train'] = load_dataset(streaming=True).take(50000)\r\n\r\nI'm test again: in prepare_data(), data have the same for each GPU\r\n",
"The number of shards is `ds.n_shards`. It corresponds generally to the ... | 2023-06-15T10:29:10Z | 2023-09-01T10:35:11Z | null | NONE | null | null | {
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} | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's therefore possible to have the same examples passed to `prepare_dataset` for each GPU.
This doesn't sound optimized though, because it runs the preprocessing on samples that won't be used in the end.
Could you open a new issue so that we can discuss about this and find a solution ?
_Originally posted by @lhoestq in https://github.com/huggingface/datasets/issues/5360#issuecomment-1592729051_
| null | {
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https://api.github.com/repos/huggingface/datasets/issues/6720 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6720/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6720/comments | https://api.github.com/repos/huggingface/datasets/issues/6720/events | https://github.com/huggingface/datasets/issues/6720 | 2,173,603,459 | I_kwDODunzps6Bjo6D | 6,720 | TypeError: 'str' object is not callable | {
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"Hi ! I opened a PR to fix an issue in the Features defined in your code\r\n\r\nBasically changing\r\n```python\r\nSequence(\"float32\")\r\n```\r\n\r\nto\r\n```python\r\nSequence(Value(\"float32\"))\r\n```\r\n\r\n\r\nhttps://huggingface.co/datasets/BramVanroy/hplt_mono_v1_2/discussions/1",
"D'oh! Was wondering wh... | 2024-03-07T11:07:09Z | 2024-03-08T07:34:53Z | 2024-03-07T15:13:58Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
I am trying to get the HPLT datasets on the hub. Downloading/re-uploading would be too time- and resource consuming so I wrote [a dataset loader script](https://huggingface.co/datasets/BramVanroy/hplt_mono_v1_2/blob/main/hplt_mono_v1_2.py). I think I am very close but for some reason I always get the error below. It happens during the clean-up phase where the directory cannot be removed because it is not empty.
My only guess would be that this may have to do with zstandard
```
Traceback (most recent call last):
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1744, in _prepare_split_single
writer.write(example, key)
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/arrow_writer.py", line 492, in write
self.write_examples_on_file()
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/arrow_writer.py", line 434, in write_examples_on_file
if self.schema
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/arrow_writer.py", line 409, in schema
else (pa.schema(self._features.type) if self._features is not None else None)
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/features/features.py", line 1643, in type
return get_nested_type(self)
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/features/features.py", line 1209, in get_nested_type
{key: get_nested_type(schema[key]) for key in schema}
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/features/features.py", line 1209, in <dictcomp>
{key: get_nested_type(schema[key]) for key in schema}
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/features/features.py", line 1221, in get_nested_type
value_type = get_nested_type(schema.feature)
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/features/features.py", line 1228, in get_nested_type
return schema()
TypeError: 'str' object is not callable
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1753, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/arrow_writer.py", line 588, in finalize
self.write_examples_on_file()
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/arrow_writer.py", line 434, in write_examples_on_file
if self.schema
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/arrow_writer.py", line 409, in schema
else (pa.schema(self._features.type) if self._features is not None else None)
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/features/features.py", line 1643, in type
return get_nested_type(self)
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/features/features.py", line 1209, in get_nested_type
{key: get_nested_type(schema[key]) for key in schema}
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/features/features.py", line 1209, in <dictcomp>
{key: get_nested_type(schema[key]) for key in schema}
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/features/features.py", line 1221, in get_nested_type
value_type = get_nested_type(schema.feature)
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/features/features.py", line 1228, in get_nested_type
return schema()
TypeError: 'str' object is not callable
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/builder.py", line 959, in incomplete_dir
yield tmp_dir
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1005, in download_and_prepare
self._download_and_prepare(
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1767, in _download_and_prepare
super()._download_and_prepare(
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1100, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1605, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1762, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/pricie/vanroy/.config/JetBrains/PyCharm2023.3/scratches/scratch_5.py", line 4, in <module>
ds = load_dataset(
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/load.py", line 2549, in load_dataset
builder_instance.download_and_prepare(
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/builder.py", line 985, in download_and_prepare
with incomplete_dir(self._output_dir) as tmp_output_dir:
File "/home/pricie/vanroy/.pyenv/versions/3.10.13/lib/python3.10/contextlib.py", line 153, in __exit__
self.gen.throw(typ, value, traceback)
File "/home/local/vanroy/dutch-instruction-datasets/.venv/lib/python3.10/site-packages/datasets/builder.py", line 966, in incomplete_dir
shutil.rmtree(tmp_dir)
File "/home/pricie/vanroy/.pyenv/versions/3.10.13/lib/python3.10/shutil.py", line 731, in rmtree
onerror(os.rmdir, path, sys.exc_info())
File "/home/pricie/vanroy/.pyenv/versions/3.10.13/lib/python3.10/shutil.py", line 729, in rmtree
os.rmdir(path)
OSError: [Errno 39] Directory not empty: '/home/pricie/vanroy/.cache/huggingface/datasets/BramVanroy___hplt_mono_v1_2/ky/1.2.0/7ab138629fe7e9e29fe93ce63d809d5ef9d963273b829f61ab538e012dc9cc47.incomplete'
```
Interestingly, though, this directory _does_ appear to be empty:
```shell
> cd /home/pricie/vanroy/.cache/huggingface/datasets/BramVanroy___hplt_mono_v1_2/ky/1.2.0/7ab138629fe7e9e29fe93ce63d809d5ef9d963273b829f61ab538e012dc9cc47.incomplete
> ls -lah
total 0
drwxr-xr-x. 1 vanroy vanroy 0 Mar 7 12:01 .
drwxr-xr-x. 1 vanroy vanroy 304 Mar 7 11:52 ..
> cd ..
> ls
7ab138629fe7e9e29fe93ce63d809d5ef9d963273b829f61ab538e012dc9cc47_builder.lock 7ab138629fe7e9e29fe93ce63d809d5ef9d963273b829f61ab538e012dc9cc47.incomplete
```
### Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset(
"BramVanroy/hplt_mono_v1_2",
"ky",
trust_remote_code=True
)
```
### Expected behavior
No error.
### Environment info
- `datasets` version: 2.16.1
- Platform: Linux-5.14.0-284.25.1.el9_2.x86_64-x86_64-with-glibc2.34
- Python version: 3.10.13
- `huggingface_hub` version: 0.20.2
- PyArrow version: 14.0.1
- Pandas version: 2.1.3
- `fsspec` version: 2023.10.0
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https://api.github.com/repos/huggingface/datasets/issues/4850 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4850/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4850/comments | https://api.github.com/repos/huggingface/datasets/issues/4850/events | https://github.com/huggingface/datasets/pull/4850 | 1,338,702,306 | PR_kwDODunzps49KnZ8 | 4,850 | Fix test of _get_extraction_protocol for TAR files | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-15T08:37:58Z | 2022-08-15T09:42:56Z | 2022-08-15T09:28:46Z | MEMBER | null | null | null | While working in another PR, I discovered an xpass test (a test that is supposed to xfail but nevertheless passes) when testing `_get_extraction_protocol`: https://github.com/huggingface/datasets/runs/7818845285?check_suite_focus=true
```
XPASS tests/test_streaming_download_manager.py::test_streaming_dl_manager_get_extraction_protocol_throws[https://foo.bar/train.tar]
```
This PR:
- refactors the test so that it tests the raise of the exceptions instead of xfailing
- fixes the test for TAR files: it does not raise an exception, but returns "tar"
- fixes some tests wrongly named: exchange `test_streaming_dl_manager_get_extraction_protocol` with `test_streaming_dl_manager_get_extraction_protocol_gg_drive` | {
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https://api.github.com/repos/huggingface/datasets/issues/6339 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6339/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6339/comments | https://api.github.com/repos/huggingface/datasets/issues/6339/events | https://github.com/huggingface/datasets/pull/6339 | 1,956,912,627 | PR_kwDODunzps5dhFfg | 6,339 | minor release step improvement | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-10-23T11:07:04Z | 2023-11-07T10:38:54Z | 2023-11-07T10:32:41Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6725 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6725/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6725/comments | https://api.github.com/repos/huggingface/datasets/issues/6725/events | https://github.com/huggingface/datasets/issues/6725 | 2,175,527,530 | I_kwDODunzps6Bq-pq | 6,725 | Request for a comparison of huggingface datasets compared with other data format especially webdataset | {
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] | open | false | null | [] | null | [] | 2024-03-08T08:23:01Z | 2024-03-08T08:23:01Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Feature request
Request for a comparison of huggingface datasets compared with other data format especially webdataset
### Motivation
I see huggingface datasets uses Apache Arrow as its backend, it seems to be great, but I'm curious about how it is good compared with other dataset format, like webdataset, what's the pros/cons of them.
### Your contribution
More information | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4999 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4999/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4999/comments | https://api.github.com/repos/huggingface/datasets/issues/4999/events | https://github.com/huggingface/datasets/pull/4999 | 1,379,610,030 | PR_kwDODunzps4_SQxL | 4,999 | Add EmptyDatasetError | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-20T15:28:05Z | 2022-09-21T12:23:43Z | 2022-09-21T12:21:24Z | MEMBER | null | null | null | examples:
from the hub:
```python
Traceback (most recent call last):
File "playground/ttest.py", line 3, in <module>
print(load_dataset("lhoestq/empty"))
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1686, in load_dataset
**config_kwargs,
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1458, in load_dataset_builder
data_files=data_files,
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1171, in dataset_module_factory
raise e1 from None
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1162, in dataset_module_factory
download_mode=download_mode,
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 760, in get_module
else get_data_patterns_in_dataset_repository(hfh_dataset_info, self.data_dir)
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/data_files.py", line 678, in get_data_patterns_in_dataset_repository
) from None
datasets.data_files.EmptyDatasetError: The dataset repository at 'lhoestq/empty' doesn't contain any data file.
```
from local directory:
```python
Traceback (most recent call last):
File "playground/ttest.py", line 3, in <module>
print(load_dataset("playground/empty"))
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1686, in load_dataset
**config_kwargs,
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1458, in load_dataset_builder
data_files=data_files,
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1107, in dataset_module_factory
path, data_dir=data_dir, data_files=data_files, download_mode=download_mode
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 625, in get_module
else get_data_patterns_locally(base_path)
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/data_files.py", line 460, in get_data_patterns_locally
raise EmptyDatasetError(f"The directory at {base_path} doesn't contain any data file") from None
datasets.data_files.EmptyDatasetError: The directory at playground/empty doesn't contain any data file
```
Close https://github.com/huggingface/datasets/issues/4995 | {
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https://api.github.com/repos/huggingface/datasets/issues/6842 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6842/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6842/comments | https://api.github.com/repos/huggingface/datasets/issues/6842/events | https://github.com/huggingface/datasets/issues/6842 | 2,264,692,159 | I_kwDODunzps6G_HW_ | 6,842 | Datasets with files with colon : in filenames cannot be used on Windows | {
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} | ### Describe the bug
Datasets (such as https://huggingface.co/datasets/MLCommons/peoples_speech) cannot be used on Windows due to the fact that windows does not allow colons ":" in filenames. These should be converted into alternative strings.
### Steps to reproduce the bug
1. Attempt to run load_dataset on MLCommons/peoples_speech
### Expected behavior
Does not crash during extraction
### Environment info
Windows 11, NTFS filesystem, Python 3.12
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https://api.github.com/repos/huggingface/datasets/issues/6366 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6366/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6366/comments | https://api.github.com/repos/huggingface/datasets/issues/6366/events | https://github.com/huggingface/datasets/issues/6366 | 1,970,213,490 | I_kwDODunzps51bxJy | 6,366 | with_format() function returns bytes instead of PIL images even when image column is not part of "columns" | {
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"Thanks for reporting! I've opened a PR with a fix."
] | 2023-10-31T11:10:48Z | 2023-11-02T14:21:17Z | 2023-11-02T14:21:17Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
When using the with_format() function on a dataset containing images, even if the image column is not part of the columns provided in the function, its type will be changed to bytes.
Here is a minimal reproduction of the bug:
https://colab.research.google.com/drive/1hyaOspgyhB41oiR1-tXE3k_gJCdJUQCf?usp=sharing
### Steps to reproduce the bug
1. Load the image dataset
2. apply with_format(columns=["text"])
3. Check the type of images in the "image" column before and after applying with_format
### Expected behavior
The type should stay the same, but it does not
### Environment info
datasets==2.14.6
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"Hi ! To skip the verification step that checks if newer data exist, you can enable offline mode with `HF_DATASETS_OFFLINE=1`.\r\n\r\nAlthough I agree this step should be much faster for datasets hosted on the HF Hub - we could just compare the commit hash from the local data and the remote git repository. We're no... | 2023-02-02T23:34:50Z | 2023-02-07T19:35:11Z | null | NONE | null | null | {
"completed": 0,
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"total": 0
} | ### Feature request
When loading a dataset that has been cached locally, the `load_dataset` function takes a lot longer than it should take to fetch the dataset from disk (or memory).
This is particularly noticeable for smaller datasets. For example, wikitext-2, comparing `load_data` (once cached) and `load_from_disk`, the `load_dataset` method takes 40 times longer.
⏱ 4.84s ⮜ load_dataset
⏱ 119ms ⮜ load_from_disk
### Motivation
I assume this is doing something like checking for a newer version.
If so, that's an age old problem: do you make the user wait _every single time they load from cache_ or do you do something like load from cache always, _then_ check for a newer version and alert if they have stale data. The decision usually revolves around what percentage of the time the data will have been updated, and how dangerous old data is.
For most datasets it's extremely unlikely that there will be a newer version on any given run, so 99% of the time this is just wasted time.
Maybe you don't want to make that decision for all users, but at least having the _option_ to not wait for checks would be an improvement.
### Your contribution
. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6887 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6887/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6887/comments | https://api.github.com/repos/huggingface/datasets/issues/6887/events | https://github.com/huggingface/datasets/issues/6887 | 2,286,786,396 | I_kwDODunzps6ITZdc | 6,887 | FAISS load to None | {
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"Hello,\r\n\r\nI'm not sure I understand. \r\nThe return value of `ds.load_faiss_index` is None as expected.\r\n\r\nI see that loading an Index on a dataset that doesn't have an `embedding` column doesn't raise an Issue. Is that the issue?\r\n\r\nSo `ds` doesn't have an `embedding` column, but we load an index that... | 2024-05-09T02:43:50Z | 2024-05-16T20:44:23Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
I've use FAISS with Datasets and save to FAISS.
Then load to save FAISS then no error, then ds to None
```python
ds.load_faiss_index('embeddings', 'my_index.faiss')
```
### Steps to reproduce the bug
# 1.
```python
ds_with_embeddings = ds.map(lambda example: {'embeddings': model(transforms(example['image']).unsqueeze(0)).squeeze()}, batch_size=64)
ds_with_embeddings.add_faiss_index(column='embeddings')
ds_with_embeddings.save_faiss_index('embeddings', 'index.faiss')
```
# 2.
```python
ds.load_faiss_index('embeddings', 'my_index.faiss')
```
### Expected behavior
Add column in Datasets.
### Environment info
Google Colab, SageMaker Notebook | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6642 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6642/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6642/comments | https://api.github.com/repos/huggingface/datasets/issues/6642/events | https://github.com/huggingface/datasets/issues/6642 | 2,119,085,766 | I_kwDODunzps5-Tq7G | 6,642 | Differently dataset object saved than it is loaded. | {
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"I see now, that I have to use `load_from_disk`, in order to load dataset properly, not `load_dataset`. Why is this behavior split? Why do we need both, `load_dataset` and `load_from_disk`?\r\n\r\nUnless answered, I believe this might be helpful for other hf datasets newbies.\r\n\r\nAnyway, made a `load_dataset` co... | 2024-02-05T17:28:57Z | 2024-02-06T09:50:19Z | 2024-02-06T09:50:19Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Differently sized object is saved than it is loaded.
### Steps to reproduce the bug
Hi, I save dataset in a following way:
```
dataset = load_dataset("json",
data_files={
"train": os.path.join(input_folder, f"{task_meta_type}_{task_type}_train.jsonl"),
"test": os.path.join(input_folder, f"{task_meta_type}_{task_type}_test.jsonl")})
print(os.path.join(output_folder, f"{task_meta_type}_{task_type}"))
print(f"Length of train dataset: {len(dataset['train'])}")
print(f"Length of test dataset: {len(dataset['test'])}")
dataset.save_to_disk(os.path.join(output_folder, f"{task_meta_type}_{task_type}"))
```
this yields output
```
.data/hf_dataset/propaganda_zanr
Length of train dataset: 7642
Length of test dataset: 1000
```
Everything looks fine.
Then I load the dataset
```python
from datasets import load_dataset
dataset_path = ".data/hf_dataset/propaganda_zanr"
dataset = load_dataset(dataset_path)
print(f"Length of train dataset: {len(dataset['train'])}")
print(f"Length of test dataset: {len(dataset['test'])}")
```
this prints
```
Generating train split: 1 examples [00:00, 72.10 examples/s]
Generating test split: 1 examples [00:00, 100.69 examples/s]
Length of train dataset: 1
Length of test dataset: 1
```
I dont' understand :(
### Expected behavior
same object is loaded
### Environment info
datasets==2.16.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/7153 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7153/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7153/comments | https://api.github.com/repos/huggingface/datasets/issues/7153/events | https://github.com/huggingface/datasets/issues/7153 | 2,532,788,555 | I_kwDODunzps6W90lL | 7,153 | Support data files with .ndjson extension | {
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"total": 0
} | ### Feature request
Support data files with `.ndjson` extension.
### Motivation
We already support data files with `.jsonl` extension.
### Your contribution
I am opening a PR. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6492). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"This PR is ready to review @huggingface/datasets.",
"<details>\n<summary>Show benchma... | 2023-12-12T15:18:16Z | 2023-12-13T14:29:01Z | 2023-12-13T14:22:41Z | MEMBER | null | null | null | Make `push_to_hub` return `CommitInfo`.
This is useful, for example, if we pass `create_pr=True` and we want to know the created PR ID.
CC: @severo for the use case in https://huggingface.co/datasets/jmhessel/newyorker_caption_contest/discussions/4 | {
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https://api.github.com/repos/huggingface/datasets/issues/6997 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6997/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6997/comments | https://api.github.com/repos/huggingface/datasets/issues/6997/events | https://github.com/huggingface/datasets/issues/6997 | 2,371,966,127 | I_kwDODunzps6NYVSv | 6,997 | CI is broken for tests using hf-internal-testing/librispeech_asr_dummy | {
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```
FAILED tests/test_inspect.py::test_get_dataset_config_names[hf-internal-testing/librispeech_asr_dummy-expected4] - AssertionError: assert ['clean'] == ['clean', 'other']
Right contains one more item: 'other'
Full diff:
[
'clean',
- 'other',
]
FAILED tests/test_inspect.py::test_get_dataset_default_config_name[hf-internal-testing/librispeech_asr_dummy-None] - AssertionError: assert 'clean' is None
```
Note that repository was recently converted to Parquet: https://huggingface.co/datasets/hf-internal-testing/librispeech_asr_dummy/commit/5be91486e11a2d616f4ec5db8d3fd248585ac07a | {
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https://api.github.com/repos/huggingface/datasets/issues/5837 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5837/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5837/comments | https://api.github.com/repos/huggingface/datasets/issues/5837/events | https://github.com/huggingface/datasets/issues/5837 | 1,703,019,816 | I_kwDODunzps5lggUo | 5,837 | Use DeepSpeed load myself " .csv " dataset. | {
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"Hi ! Doing `load_dataset(\"path/to/data.csv\")` is not supported yet, but you can do\r\n\r\n```python\r\nds = load_dataset(\"csv\", data_files=[\"path/to/data.csv\"])\r\n```",
"@lhoestq thank you.",
"The other question: \r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n Fil... | 2023-05-10T02:39:28Z | 2023-05-15T03:51:36Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
When I use DeepSpeed train a model with my own " XXX.csv" dataset I got the follow question:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/fm001/.conda/envs/hzl/lib/python3.8/site-packages/datasets/load.py", line 1767, in load_dataset
builder_instance = load_dataset_builder(
File "/home/fm001/.conda/envs/hzl/lib/python3.8/site-packages/datasets/load.py", line 1498, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/home/fm001/.conda/envs/hzl/lib/python3.8/site-packages/datasets/load.py", line 1217, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at /home/fm001/hzl/Data/qa.csv/qa.csv.py or any data file in the same directory.
### Steps to reproduce the bug
my code is :
from datasets import load_dataset
mydata = load_dataset("/home/fm001/hzl/Data/qa.csv")
### Expected behavior
。。。
### Environment info
。。。 | null | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-10-31T17:57:17Z | 2023-10-31T18:35:53Z | 2023-10-31T18:24:02Z | COLLABORATOR | null | null | null | Fix https://discuss.huggingface.co/t/attributeerror-enter/60509 | {
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https://api.github.com/repos/huggingface/datasets/issues/7385 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7385/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7385/comments | https://api.github.com/repos/huggingface/datasets/issues/7385/events | https://github.com/huggingface/datasets/pull/7385 | 2,830,664,522 | PR_kwDODunzps6KBO6i | 7,385 | Make IterableDataset (optionally) resumable | {
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"@lhoestq Hi again~ Just circling back on this\r\nWondering if there’s anything I can do to help move this forward. 🤗 \r\nThanks!",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7385). All of your documentation changes will be reflected on that endpoint. The docs are avai... | 2025-02-04T15:55:33Z | 2025-03-03T17:31:40Z | null | CONTRIBUTOR | null | null | null | ### What does this PR do?
This PR introduces a new `stateful` option to the `dataset.shuffle` method, which defaults to `False`.
When enabled, this option allows for resumable shuffling of `IterableDataset` instances, albeit with some additional memory overhead.
Key points:
* All tests have passed
* Docstrings have been updated to reflect the new functionality
I'm very looking forward to receiving feedback on this implementation! @lhoestq | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6981 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6981/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6981/comments | https://api.github.com/repos/huggingface/datasets/issues/6981/events | https://github.com/huggingface/datasets/pull/6981 | 2,361,520,022 | PR_kwDODunzps5y6tnN | 6,981 | Update docs on trust_remote_code defaults to False | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6981). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-06-19T07:12:21Z | 2024-06-19T14:32:59Z | 2024-06-19T14:26:37Z | MEMBER | null | null | null | Update docs on trust_remote_code defaults to False.
The docs needed to be updated due to this PR:
- #6954 | {
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https://api.github.com/repos/huggingface/datasets/issues/7487 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7487/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7487/comments | https://api.github.com/repos/huggingface/datasets/issues/7487/events | https://github.com/huggingface/datasets/pull/7487 | 2,956,533,448 | PR_kwDODunzps6QlF8N | 7,487 | Write pdf in map | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7487). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-03-28T15:49:25Z | 2025-03-28T17:09:53Z | 2025-03-28T17:09:51Z | MEMBER | null | null | null | Fix this error when mapping a PDF dataset
```
pyarrow.lib.ArrowInvalid: Could not convert <pdfplumber.pdf.PDF object at 0x13498ee40> with type PDF: did not recognize Python value type when inferring an Arrow data type
```
and also let map() outputs be lists of images or pdfs | {
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https://api.github.com/repos/huggingface/datasets/issues/6454 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6454/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6454/comments | https://api.github.com/repos/huggingface/datasets/issues/6454/events | https://github.com/huggingface/datasets/pull/6454 | 2,013,001,584 | PR_kwDODunzps5gej3H | 6,454 | Refactor `dill` logic | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-11-27T20:01:25Z | 2023-11-28T16:29:58Z | 2023-11-28T16:29:31Z | COLLABORATOR | null | null | null | Refactor the `dill` logic to make it easier to maintain (and fix some issues along the way)
It makes the following improvements to the serialization API:
* consistent order of a `dict`'s keys
* support for hashing `torch.compile`-ed modules and functions
* deprecates `datasets.fingerprint.hashregister` as the `hashregister`-ed reducers are never invoked anyways (does not support nested data as `pickle`/`dill` do)
~~TODO: optimize hashing of `pa.Table` and `datasets.table.Table`~~ The `pa_array.to_string` approach is faster for large arrays because it outputs the first 10 and last 10 elements (by default). The problem is that this can produce identical hashes for non-identical arrays if their differing elements get ellipsed...
Fix https://github.com/huggingface/datasets/issues/6440, fix https://github.com/huggingface/datasets/issues/5839 | {
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https://api.github.com/repos/huggingface/datasets/issues/5822 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5822/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5822/comments | https://api.github.com/repos/huggingface/datasets/issues/5822/events | https://github.com/huggingface/datasets/issues/5822 | 1,696,627,308 | I_kwDODunzps5lIHps | 5,822 | Audio Dataset with_format torch problem | {
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} | [] | closed | false | null | [] | null | [
"Hi ! Can you try with a more recent version of `datasets` ?",
"Ok, yes it worked with the most recent version. Thanks"
] | 2023-05-04T20:07:51Z | 2023-05-11T20:45:53Z | 2023-05-11T20:45:53Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Common Voice v10 Delta (German) Dataset from here https://commonvoice.mozilla.org/de/datasets
```
audio_dataset = \
(Dataset
.from_dict({"audio": ('/tmp/cv-corpus-10.0-delta-2022-07-04/de/clips/' + df.path).to_list()})
.cast_column("audio", Audio(sampling_rate=16_000))
.with_format('numpy'))
audio_dataset[0]["audio"]
```
works, but
```
audio_dataset = \
(Dataset
.from_dict({"audio": ('/tmp/cv-corpus-10.0-delta-2022-07-04/de/clips/' + df.path).to_list()})
.cast_column("audio", Audio(sampling_rate=16_000))
.with_format('torch'))
audio_dataset[0]["audio"]
```
does not instead I get
```
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[54], line 1
----> 1 audio_dataset[0]["audio"]
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/arrow_dataset.py:2154, in Dataset.__getitem__(self, key)
2152 def __getitem__(self, key): # noqa: F811
2153 """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools)."""
-> 2154 return self._getitem(
2155 key,
2156 )
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/arrow_dataset.py:2139, in Dataset._getitem(self, key, decoded, **kwargs)
2137 formatter = get_formatter(format_type, features=self.features, decoded=decoded, **format_kwargs)
2138 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
-> 2139 formatted_output = format_table(
2140 pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
2141 )
2142 return formatted_output
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/formatting/formatting.py:532, in format_table(table, key, formatter, format_columns, output_all_columns)
530 python_formatter = PythonFormatter(features=None)
531 if format_columns is None:
--> 532 return formatter(pa_table, query_type=query_type)
533 elif query_type == "column":
534 if key in format_columns:
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/formatting/formatting.py:281, in Formatter.__call__(self, pa_table, query_type)
279 def __call__(self, pa_table: pa.Table, query_type: str) -> Union[RowFormat, ColumnFormat, BatchFormat]:
280 if query_type == "row":
--> 281 return self.format_row(pa_table)
282 elif query_type == "column":
283 return self.format_column(pa_table)
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/formatting/torch_formatter.py:58, in TorchFormatter.format_row(self, pa_table)
56 def format_row(self, pa_table: pa.Table) -> dict:
57 row = self.numpy_arrow_extractor().extract_row(pa_table)
---> 58 return self.recursive_tensorize(row)
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/formatting/torch_formatter.py:54, in TorchFormatter.recursive_tensorize(self, data_struct)
53 def recursive_tensorize(self, data_struct: dict):
---> 54 return map_nested(self._recursive_tensorize, data_struct, map_list=False)
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/utils/py_utils.py:356, in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, types, disable_tqdm, desc)
354 num_proc = 1
355 if num_proc <= 1 or len(iterable) <= num_proc:
--> 356 mapped = [
357 _single_map_nested((function, obj, types, None, True, None))
358 for obj in logging.tqdm(iterable, disable=disable_tqdm, desc=desc)
359 ]
360 else:
361 split_kwds = [] # We organize the splits ourselve (contiguous splits)
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/utils/py_utils.py:357, in <listcomp>(.0)
354 num_proc = 1
355 if num_proc <= 1 or len(iterable) <= num_proc:
356 mapped = [
--> 357 _single_map_nested((function, obj, types, None, True, None))
358 for obj in logging.tqdm(iterable, disable=disable_tqdm, desc=desc)
359 ]
360 else:
361 split_kwds = [] # We organize the splits ourselve (contiguous splits)
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/utils/py_utils.py:309, in _single_map_nested(args)
306 pbar = logging.tqdm(pbar_iterable, disable=disable_tqdm, position=rank, unit="obj", desc=pbar_desc)
308 if isinstance(data_struct, dict):
--> 309 return {k: _single_map_nested((function, v, types, None, True, None)) for k, v in pbar}
310 else:
311 mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/utils/py_utils.py:309, in <dictcomp>(.0)
306 pbar = logging.tqdm(pbar_iterable, disable=disable_tqdm, position=rank, unit="obj", desc=pbar_desc)
308 if isinstance(data_struct, dict):
--> 309 return {k: _single_map_nested((function, v, types, None, True, None)) for k, v in pbar}
310 else:
311 mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/utils/py_utils.py:293, in _single_map_nested(args)
291 # Singleton first to spare some computation
292 if not isinstance(data_struct, dict) and not isinstance(data_struct, types):
--> 293 return function(data_struct)
295 # Reduce logging to keep things readable in multiprocessing with tqdm
296 if rank is not None and logging.get_verbosity() < logging.WARNING:
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/formatting/torch_formatter.py:51, in TorchFormatter._recursive_tensorize(self, data_struct)
49 if data_struct.dtype == np.object: # pytorch tensors cannot be instantied from an array of objects
50 return [self.recursive_tensorize(substruct) for substruct in data_struct]
---> 51 return self._tensorize(data_struct)
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/datasets/formatting/torch_formatter.py:38, in TorchFormatter._tensorize(self, value)
35 import torch
37 default_dtype = {}
---> 38 if np.issubdtype(value.dtype, np.integer):
39 default_dtype = {"dtype": torch.int64}
40 elif np.issubdtype(value.dtype, np.floating):
AttributeError: 'NoneType' object has no attribute 'dtype'
```
### Steps to reproduce the bug
1. Download some audio dataset in this case I used Common Voice v10 Delta (German) Dataset from here https://commonvoice.mozilla.org/de/datasets
2. Try the Code from above
### Expected behavior
It should work for torch
### Environment info
pytorch: 2.0.0
datasets: 2.3.2
numpy: 1.21.6
Python: 3.8
Linux | {
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https://api.github.com/repos/huggingface/datasets/issues/5994 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5994/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5994/comments | https://api.github.com/repos/huggingface/datasets/issues/5994/events | https://github.com/huggingface/datasets/pull/5994 | 1,776,829,004 | PR_kwDODunzps5UB1cA | 5,994 | Fix select_columns columns order | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-06-27T12:32:46Z | 2023-06-27T15:40:47Z | 2023-06-27T15:32:43Z | MEMBER | null | null | null | Fix the order of the columns in dataset.features when the order changes with `dataset.select_columns()`.
I also fixed the same issue for `dataset.flatten()`
Close https://github.com/huggingface/datasets/issues/5993 | {
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https://api.github.com/repos/huggingface/datasets/issues/4936 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4936/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4936/comments | https://api.github.com/repos/huggingface/datasets/issues/4936/events | https://github.com/huggingface/datasets/issues/4936 | 1,363,274,907 | I_kwDODunzps5RQeyb | 4,936 | vivos (Vietnamese speech corpus) dataset not accessible | {
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"If you need an example of a small audio datasets, I just created few hours ago a speech dataset with only 300MB of compressed audio files https://huggingface.co/datasets/indonesian-nlp/librivox-indonesia. It works also with streaming (@albertvillanova helped me adding this functionality) :-)",
"@cahya-wirawan om... | 2022-09-06T13:17:55Z | 2022-09-21T06:06:02Z | 2022-09-12T07:14:20Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ## Describe the bug
VIVOS data is not accessible anymore, neither of these links work (at least from France):
* https://ailab.hcmus.edu.vn/assets/vivos.tar.gz (data)
* https://ailab.hcmus.edu.vn/vivos (dataset page)
Therefore `load_dataset` doesn't work.
## Steps to reproduce the bug
```python
ds = load_dataset("vivos")
```
## Expected results
dataset loaded
## Actual results
```
ConnectionError: Couldn't reach https://ailab.hcmus.edu.vn/assets/vivos.tar.gz (ConnectionError(MaxRetryError("HTTPSConnectionPool(host='ailab.hcmus.edu.vn', port=443): Max retries exceeded with url: /assets/vivos.tar.gz (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f9d8a27d190>: Failed to establish a new connection: [Errno -5] No address associated with hostname'))")))
```
Will try to contact the authors, as we wanted to use Vivos as an example in documentation on how to create scripts for audio datasets (https://github.com/huggingface/datasets/pull/4872), because it's small and straightforward and uses tar archives. | {
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https://api.github.com/repos/huggingface/datasets/issues/4582 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4582/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4582/comments | https://api.github.com/repos/huggingface/datasets/issues/4582/events | https://github.com/huggingface/datasets/pull/4582 | 1,286,517,060 | PR_kwDODunzps46dC59 | 4,582 | add_column should preserve _indexes | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4582). All of your documentation changes will be reflected on that endpoint."
] | 2022-06-27T22:35:47Z | 2022-07-06T15:19:54Z | null | CONTRIBUTOR | null | null | null | https://github.com/huggingface/datasets/issues/3769#issuecomment-1167146126
doing `.add_column("x",x_data)` also removed any `_indexes` on the dataset, decided this shouldn't be the case.
This was because `add_column` was creating a new `Dataset(...)` and wasn't possible to pass indexes on init.
with this PR now can pass 'indexes' on init through `IndexableMixin`
- [x] Added test | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6669 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6669/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6669/comments | https://api.github.com/repos/huggingface/datasets/issues/6669/events | https://github.com/huggingface/datasets/issues/6669 | 2,138,322,662 | I_kwDODunzps5_dDbm | 6,669 | attribute error when writing trainer.train() | {
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"Hi! Kaggle notebooks use an outdated version of `datasets`, so you should update the `datasets` installation (with `!pip install -U datasets`) to avoid the error.",
"Thank you for your response\r\n\r\nOn Thu, Feb 29, 2024 at 10:55 PM Mario Šaško ***@***.***>\r\nwrote:\r\n\r\n> Closed #6669 <https://github.com/hu... | 2024-02-16T10:40:49Z | 2024-03-01T10:58:00Z | 2024-02-29T17:25:17Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
AttributeError Traceback (most recent call last)
Cell In[39], line 2
1 # Start the training process
----> 2 trainer.train()
File /opt/conda/lib/python3.10/site-packages/transformers/trainer.py:1539, in Trainer.train(self, resume_from_checkpoint, trial, ignore_keys_for_eval, **kwargs)
1537 hf_hub_utils.enable_progress_bars()
1538 else:
-> 1539 return inner_training_loop(
1540 args=args,
1541 resume_from_checkpoint=resume_from_checkpoint,
1542 trial=trial,
1543 ignore_keys_for_eval=ignore_keys_for_eval,
1544 )
File /opt/conda/lib/python3.10/site-packages/transformers/trainer.py:1836, in Trainer._inner_training_loop(self, batch_size, args, resume_from_checkpoint, trial, ignore_keys_for_eval)
1833 rng_to_sync = True
1835 step = -1
-> 1836 for step, inputs in enumerate(epoch_iterator):
1837 total_batched_samples += 1
1839 if self.args.include_num_input_tokens_seen:
File /opt/conda/lib/python3.10/site-packages/accelerate/data_loader.py:451, in DataLoaderShard.__iter__(self)
449 # We iterate one batch ahead to check when we are at the end
450 try:
--> 451 current_batch = next(dataloader_iter)
452 except StopIteration:
453 yield
File /opt/conda/lib/python3.10/site-packages/torch/utils/data/dataloader.py:630, in _BaseDataLoaderIter.__next__(self)
627 if self._sampler_iter is None:
628 # TODO([https://github.com/pytorch/pytorch/issues/76750)](https://github.com/pytorch/pytorch/issues/76750)%3C/span%3E)
629 self._reset() # type: ignore[call-arg]
--> 630 data = self._next_data()
631 self._num_yielded += 1
632 if self._dataset_kind == _DatasetKind.Iterable and \
633 self._IterableDataset_len_called is not None and \
634 self._num_yielded > self._IterableDataset_len_called:
File /opt/conda/lib/python3.10/site-packages/torch/utils/data/dataloader.py:674, in _SingleProcessDataLoaderIter._next_data(self)
672 def _next_data(self):
673 index = self._next_index() # may raise StopIteration
--> 674 data = self._dataset_fetcher.fetch(index) # may raise StopIteration
675 if self._pin_memory:
676 data = _utils.pin_memory.pin_memory(data, self._pin_memory_device)
File /opt/conda/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py:51, in _MapDatasetFetcher.fetch(self, possibly_batched_index)
49 data = self.dataset.__getitems__(possibly_batched_index)
50 else:
---> 51 data = [self.dataset[idx] for idx in possibly_batched_index]
52 else:
53 data = self.dataset[possibly_batched_index]
File /opt/conda/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py:51, in <listcomp>(.0)
49 data = self.dataset.__getitems__(possibly_batched_index)
50 else:
---> 51 data = [self.dataset[idx] for idx in possibly_batched_index]
52 else:
53 data = self.dataset[possibly_batched_index]
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:1764, in Dataset.__getitem__(self, key)
1762 def __getitem__(self, key): # noqa: F811
1763 """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools)."""
-> 1764 return self._getitem(
1765 key,
1766 )
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:1749, in Dataset._getitem(self, key, decoded, **kwargs)
1747 formatter = get_formatter(format_type, features=self.features, decoded=decoded, **format_kwargs)
1748 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
-> 1749 formatted_output = format_table(
1750 pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
1751 )
1752 return formatted_output
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:540, in format_table(table, key, formatter, format_columns, output_all_columns)
538 else:
539 pa_table_to_format = pa_table.drop(col for col in pa_table.column_names if col not in format_columns)
--> 540 formatted_output = formatter(pa_table_to_format, query_type=query_type)
541 if output_all_columns:
542 if isinstance(formatted_output, MutableMapping):
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:281, in Formatter.__call__(self, pa_table, query_type)
279 def __call__(self, pa_table: pa.Table, query_type: str) -> Union[RowFormat, ColumnFormat, BatchFormat]:
280 if query_type == "row":
--> 281 return self.format_row(pa_table)
282 elif query_type == "column":
283 return self.format_column(pa_table)
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/torch_formatter.py:57, in TorchFormatter.format_row(self, pa_table)
56 def format_row(self, pa_table: pa.Table) -> dict:
---> 57 row = self.numpy_arrow_extractor().extract_row(pa_table)
58 return self.recursive_tensorize(row)
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:154, in NumpyArrowExtractor.extract_row(self, pa_table)
153 def extract_row(self, pa_table: pa.Table) -> dict:
--> 154 return _unnest(self.extract_batch(pa_table))
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:160, in NumpyArrowExtractor.extract_batch(self, pa_table)
159 def extract_batch(self, pa_table: pa.Table) -> dict:
--> 160 return {col: self._arrow_array_to_numpy(pa_table[col]) for col in pa_table.column_names}
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:160, in <dictcomp>(.0)
159 def extract_batch(self, pa_table: pa.Table) -> dict:
--> 160 return {col: self._arrow_array_to_numpy(pa_table[col]) for col in pa_table.column_names}
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:196, in NumpyArrowExtractor._arrow_array_to_numpy(self, pa_array)
194 array: List = pa_array.to_numpy(zero_copy_only=zero_copy_only).tolist()
195 if len(array) > 0:
--> 196 if any(
197 (isinstance(x, np.ndarray) and (x.dtype == np.object or x.shape != array[0].shape))
198 or (isinstance(x, float) and np.isnan(x))
199 for x in array
200 ):
201 return np.array(array, copy=False, **{**self.np_array_kwargs, "dtype": np.object})
202 return np.array(array, copy=False, **self.np_array_kwargs)
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:197, in <genexpr>(.0)
194 array: List = pa_array.to_numpy(zero_copy_only=zero_copy_only).tolist()
195 if len(array) > 0:
196 if any(
--> 197 (isinstance(x, np.ndarray) and (x.dtype == np.object or x.shape != array[0].shape))
198 or (isinstance(x, float) and np.isnan(x))
199 for x in array
200 ):
201 return np.array(array, copy=False, **{**self.np_array_kwargs, "dtype": np.object})
202 return np.array(array, copy=False, **self.np_array_kwargs)
File /opt/conda/lib/python3.10/site-packages/numpy/__init__.py:324, in __getattr__(attr)
319 warnings.warn(
320 f"In the future `np.{attr}` will be defined as the "
321 "corresponding NumPy scalar.", FutureWarning, stacklevel=2)
323 if attr in __former_attrs__:
--> 324 raise AttributeError(__former_attrs__[attr])
326 if attr == 'testing':
327 import numpy.testing as testing
AttributeError: module 'numpy' has no attribute 'object'.
`np.object` was a deprecated alias for the builtin `object`. To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecationsAttributeError Traceback (most recent call last)
Cell In[39], line 2
1 # Start the training process
----> 2 trainer.train()
File /opt/conda/lib/python3.10/site-packages/transformers/trainer.py:1539, in Trainer.train(self, resume_from_checkpoint, trial, ignore_keys_for_eval, **kwargs)
1537 hf_hub_utils.enable_progress_bars()
1538 else:
-> 1539 return inner_training_loop(
1540 args=args,
1541 resume_from_checkpoint=resume_from_checkpoint,
1542 trial=trial,
1543 ignore_keys_for_eval=ignore_keys_for_eval,
1544 )
File /opt/conda/lib/python3.10/site-packages/transformers/trainer.py:1836, in Trainer._inner_training_loop(self, batch_size, args, resume_from_checkpoint, trial, ignore_keys_for_eval)
1833 rng_to_sync = True
1835 step = -1
-> 1836 for step, inputs in enumerate(epoch_iterator):
1837 total_batched_samples += 1
1839 if self.args.include_num_input_tokens_seen:
File /opt/conda/lib/python3.10/site-packages/accelerate/data_loader.py:451, in DataLoaderShard.__iter__(self)
449 # We iterate one batch ahead to check when we are at the end
450 try:
--> 451 current_batch = next(dataloader_iter)
452 except StopIteration:
453 yield
File /opt/conda/lib/python3.10/site-packages/torch/utils/data/dataloader.py:630, in _BaseDataLoaderIter.__next__(self)
627 if self._sampler_iter is None:
628 # TODO([https://github.com/pytorch/pytorch/issues/76750)](https://github.com/pytorch/pytorch/issues/76750)%3C/span%3E)
629 self._reset() # type: ignore[call-arg]
--> 630 data = self._next_data()
631 self._num_yielded += 1
632 if self._dataset_kind == _DatasetKind.Iterable and \
633 self._IterableDataset_len_called is not None and \
634 self._num_yielded > self._IterableDataset_len_called:
File /opt/conda/lib/python3.10/site-packages/torch/utils/data/dataloader.py:674, in _SingleProcessDataLoaderIter._next_data(self)
672 def _next_data(self):
673 index = self._next_index() # may raise StopIteration
--> 674 data = self._dataset_fetcher.fetch(index) # may raise StopIteration
675 if self._pin_memory:
676 data = _utils.pin_memory.pin_memory(data, self._pin_memory_device)
File /opt/conda/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py:51, in _MapDatasetFetcher.fetch(self, possibly_batched_index)
49 data = self.dataset.__getitems__(possibly_batched_index)
50 else:
---> 51 data = [self.dataset[idx] for idx in possibly_batched_index]
52 else:
53 data = self.dataset[possibly_batched_index]
File /opt/conda/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py:51, in <listcomp>(.0)
49 data = self.dataset.__getitems__(possibly_batched_index)
50 else:
---> 51 data = [self.dataset[idx] for idx in possibly_batched_index]
52 else:
53 data = self.dataset[possibly_batched_index]
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:1764, in Dataset.__getitem__(self, key)
1762 def __getitem__(self, key): # noqa: F811
1763 """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools)."""
-> 1764 return self._getitem(
1765 key,
1766 )
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:1749, in Dataset._getitem(self, key, decoded, **kwargs)
1747 formatter = get_formatter(format_type, features=self.features, decoded=decoded, **format_kwargs)
1748 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
-> 1749 formatted_output = format_table(
1750 pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
1751 )
1752 return formatted_output
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:540, in format_table(table, key, formatter, format_columns, output_all_columns)
538 else:
539 pa_table_to_format = pa_table.drop(col for col in pa_table.column_names if col not in format_columns)
--> 540 formatted_output = formatter(pa_table_to_format, query_type=query_type)
541 if output_all_columns:
542 if isinstance(formatted_output, MutableMapping):
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:281, in Formatter.__call__(self, pa_table, query_type)
279 def __call__(self, pa_table: pa.Table, query_type: str) -> Union[RowFormat, ColumnFormat, BatchFormat]:
280 if query_type == "row":
--> 281 return self.format_row(pa_table)
282 elif query_type == "column":
283 return self.format_column(pa_table)
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/torch_formatter.py:57, in TorchFormatter.format_row(self, pa_table)
56 def format_row(self, pa_table: pa.Table) -> dict:
---> 57 row = self.numpy_arrow_extractor().extract_row(pa_table)
58 return self.recursive_tensorize(row)
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:154, in NumpyArrowExtractor.extract_row(self, pa_table)
153 def extract_row(self, pa_table: pa.Table) -> dict:
--> 154 return _unnest(self.extract_batch(pa_table))
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:160, in NumpyArrowExtractor.extract_batch(self, pa_table)
159 def extract_batch(self, pa_table: pa.Table) -> dict:
--> 160 return {col: self._arrow_array_to_numpy(pa_table[col]) for col in pa_table.column_names}
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:160, in <dictcomp>(.0)
159 def extract_batch(self, pa_table: pa.Table) -> dict:
--> 160 return {col: self._arrow_array_to_numpy(pa_table[col]) for col in pa_table.column_names}
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:196, in NumpyArrowExtractor._arrow_array_to_numpy(self, pa_array)
194 array: List = pa_array.to_numpy(zero_copy_only=zero_copy_only).tolist()
195 if len(array) > 0:
--> 196 if any(
197 (isinstance(x, np.ndarray) and (x.dtype == np.object or x.shape != array[0].shape))
198 or (isinstance(x, float) and np.isnan(x))
199 for x in array
200 ):
201 return np.array(array, copy=False, **{**self.np_array_kwargs, "dtype": np.object})
202 return np.array(array, copy=False, **self.np_array_kwargs)
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:197, in <genexpr>(.0)
194 array: List = pa_array.to_numpy(zero_copy_only=zero_copy_only).tolist()
195 if len(array) > 0:
196 if any(
--> 197 (isinstance(x, np.ndarray) and (x.dtype == np.object or x.shape != array[0].shape))
198 or (isinstance(x, float) and np.isnan(x))
199 for x in array
200 ):
201 return np.array(array, copy=False, **{**self.np_array_kwargs, "dtype": np.object})
202 return np.array(array, copy=False, **self.np_array_kwargs)
File /opt/conda/lib/python3.10/site-packages/numpy/__init__.py:324, in __getattr__(attr)
319 warnings.warn(
320 f"In the future `np.{attr}` will be defined as the "
321 "corresponding NumPy scalar.", FutureWarning, stacklevel=2)
323 if attr in __former_attrs__:
--> 324 raise AttributeError(__former_attrs__[attr])
326 if attr == 'testing':
327 import numpy.testing as testing
AttributeError: module 'numpy' has no attribute 'object'.
`np.object` was a deprecated alias for the builtin `object`. To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
Please help me to resolve the above error
### Steps to reproduce the bug
Please resolve the issue of deprecated function np.object to object in the numpy
### Expected behavior
np.object should be written as object only
### Environment info
kaggle notebook | {
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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 | {
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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... | 2023-02-20T18:15:43Z | 2023-09-24T10:07:29Z | 2023-02-21T12:43:38Z | MEMBER | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/6319 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6319/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6319/comments | https://api.github.com/repos/huggingface/datasets/issues/6319/events | https://github.com/huggingface/datasets/issues/6319 | 1,952,101,717 | I_kwDODunzps50WrVV | 6,319 | Datasets.map is severely broken | {
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"Hi! Instead of processing a single example at a time, you should use the batched `map` for the best performance (with `num_proc=1`) - the fast tokenizers can process a batch's samples in parallel in that scenario.\r\n\r\nE.g., the following code in Colab takes an hour to complete:\r\n```python\r\n# !pip install da... | 2023-10-19T12:19:33Z | 2024-08-08T17:05:08Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Regardless of how many cores I used, I have 16 or 32 threads, map slows down to a crawl at around 80% done, lingers maybe until 97% extremely slowly and NEVER finishes the job. It just hangs.
After watching this for 27 hours I control-C out of it. Until the end one process appears to be doing something, but it never ends.
I saw some comments about fast tokenizers using Rust and all and tried different variations. NOTHING works.
### Steps to reproduce the bug
Running it without breaking the dataset into parts results in the same behavior. The loop was an attempt to see if this was a RAM issue.
for idx in range(100):
dataset = load_dataset("togethercomputer/RedPajama-Data-1T-Sample", cache_dir=cache_dir, split=f'train[{idx}%:{idx+1}%]')
dataset = dataset.map(partial(tokenize_fn, tokenizer), batched=False, num_proc=1, remove_columns=["text", "meta"])
dataset.save_to_disk(training_args.cache_dir + f"/training_data_{idx}")
### Expected behavior
I expect map to run at more or less the same speed it starts with and FINISH its processing.
### Environment info
Python 3.8, same with 3.10 makes no difference.
Ubuntu 20.04, | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6964 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6964/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6964/comments | https://api.github.com/repos/huggingface/datasets/issues/6964/events | https://github.com/huggingface/datasets/pull/6964 | 2,344,973,229 | PR_kwDODunzps5yCNGa | 6,964 | Fix resuming arrow format | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6964). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-06-10T22:40:33Z | 2024-06-14T15:04:49Z | 2024-06-14T14:58:37Z | MEMBER | null | null | null | following https://github.com/huggingface/datasets/pull/6658 | {
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https://api.github.com/repos/huggingface/datasets/issues/5775 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5775/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5775/comments | https://api.github.com/repos/huggingface/datasets/issues/5775/events | https://github.com/huggingface/datasets/issues/5775 | 1,677,089,901 | I_kwDODunzps5j9lxt | 5,775 | ArrowDataset.save_to_disk lost some logic of remote | {
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"We just fixed this on `main` and will do a new release soon :)"
] | 2023-04-20T16:58:01Z | 2023-04-26T12:11:36Z | 2023-04-26T12:11:17Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
https://github.com/huggingface/datasets/blob/e7ce0ac60c7efc10886471932854903a7c19f172/src/datasets/arrow_dataset.py#L1371
Here is the bug point, when I want to save from a `DatasetDict` class and the items of the instance is like `[('train', Dataset({features: ..., num_rows: ...}))]` , there is no guarantee that there exists a directory name `train` under `dataset_dict_path`.
### Steps to reproduce the bug
1. Mock a DatasetDict with items like what I said.
2. using save_to_disk with storage_options, u can use local sftp. code may like below
```python
from datasets import load_dataset
dataset = load_dataset(...)
dataset.save_to_disk('sftp:///tmp', storage_options={'host': 'localhost', 'username': 'admin'})
```
I suppose u can reproduce the bug by these steps.
### Expected behavior
Should create the folder if it does not exists, just like we do locally.
### Environment info
- `datasets` version: 2.11.0
- Platform: Linux-6.2.10-arch1-1-x86_64-with-glibc2.35
- Python version: 3.10.9
- Huggingface_hub version: 0.13.2
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/6762 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6762/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6762/comments | https://api.github.com/repos/huggingface/datasets/issues/6762/events | https://github.com/huggingface/datasets/pull/6762 | 2,213,275,468 | PR_kwDODunzps5rDpBe | 6,762 | Allow polars as valid output type | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6762). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"Hello @lhoestq, I added the test and modified [update_data](https://github.com/huggingf... | 2024-03-28T13:40:28Z | 2024-08-16T15:54:37Z | 2024-08-16T13:10:37Z | CONTRIBUTOR | null | null | null | I was trying out polars as an output for a map function and found that it wasn't a valid return type in `validate_function_output`. Thought that we should accommodate this by creating and adding it to the `allowed_processed_input_types` variable. | {
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https://api.github.com/repos/huggingface/datasets/issues/5356 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5356/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5356/comments | https://api.github.com/repos/huggingface/datasets/issues/5356/events | https://github.com/huggingface/datasets/pull/5356 | 1,494,961,609 | PR_kwDODunzps5FW-c9 | 5,356 | Clean filesystem and logging docstrings | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-12-13T18:54:09Z | 2022-12-14T17:25:58Z | 2022-12-14T17:22:16Z | MEMBER | null | null | null | This PR cleans the `Filesystems` and `Logging` docstrings. | {
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https://api.github.com/repos/huggingface/datasets/issues/5390 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5390/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5390/comments | https://api.github.com/repos/huggingface/datasets/issues/5390/events | https://github.com/huggingface/datasets/issues/5390 | 1,509,357,553 | I_kwDODunzps5Z9vfx | 5,390 | Error when pushing to the CI hub | {
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"Hmmm, git bisect tells me that the behavior is the same since https://github.com/huggingface/datasets/commit/67e65c90e9490810b89ee140da11fdd13c356c9c (3 Oct), i.e. https://github.com/huggingface/datasets/pull/4926",
"Maybe related to the discussions in https://github.com/huggingface/datasets/pull/5196",
"Maybe... | 2022-12-23T13:36:37Z | 2022-12-23T20:29:02Z | 2022-12-23T20:29:02Z | COLLABORATOR | null | null | {
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} | ### Describe the bug
Note that it's a special case where the Hub URL is "https://hub-ci.huggingface.co", which does not appear if we do the same on the Hub (https://huggingface.co).
The call to `dataset.push_to_hub(` fails:
```
Pushing dataset shards to the dataset hub: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:01<00:00, 1.93s/it]
Traceback (most recent call last):
File "reproduce_hubci.py", line 16, in <module>
dataset.push_to_hub(repo_id=repo_id, private=False, token=USER_TOKEN, embed_external_files=True)
File "/home/slesage/hf/datasets/src/datasets/arrow_dataset.py", line 5025, in push_to_hub
HfApi(endpoint=config.HF_ENDPOINT).upload_file(
File "/home/slesage/.pyenv/versions/datasets/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1346, in upload_file
raise err
File "/home/slesage/.pyenv/versions/datasets/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1337, in upload_file
r.raise_for_status()
File "/home/slesage/.pyenv/versions/datasets/lib/python3.8/site-packages/requests/models.py", line 953, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: https://hub-ci.huggingface.co/api/datasets/__DUMMY_DATASETS_SERVER_USER__/bug-16718047265472/upload/main/README.md
```
### Steps to reproduce the bug
```python
# reproduce.py
from datasets import Dataset
import time
USER = "__DUMMY_DATASETS_SERVER_USER__"
USER_TOKEN = "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"
dataset = Dataset.from_dict({"a": [1, 2, 3]})
repo_id = f"{USER}/bug-{int(time.time() * 10e3)}"
dataset.push_to_hub(repo_id=repo_id, private=False, token=USER_TOKEN, embed_external_files=True)
```
```bash
$ HF_ENDPOINT="https://hub-ci.huggingface.co" python reproduce.py
```
### Expected behavior
No error and the dataset should be uploaded to the Hub with the README file (which generates the error).
### Environment info
- `datasets` version: 2.8.0
- Platform: Linux-5.15.0-1026-aws-x86_64-with-glibc2.35
- Python version: 3.9.15
- PyArrow version: 7.0.0
- Pandas version: 1.5.2
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https://api.github.com/repos/huggingface/datasets/issues/5948 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5948/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5948/comments | https://api.github.com/repos/huggingface/datasets/issues/5948/events | https://github.com/huggingface/datasets/pull/5948 | 1,754,794,611 | PR_kwDODunzps5S4dUt | 5,948 | Fix sequence of array support for most dtype | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-06-13T12:38:59Z | 2023-06-14T15:11:55Z | 2023-06-14T15:03:33Z | MEMBER | null | null | null | Fixes #5936
Also, a related fix to #5927 | {
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https://api.github.com/repos/huggingface/datasets/issues/5854 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5854/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5854/comments | https://api.github.com/repos/huggingface/datasets/issues/5854/events | https://github.com/huggingface/datasets/issues/5854 | 1,708,779,300 | I_kwDODunzps5l2eck | 5,854 | Can not load audiofolder dataset on kaggle | {
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"Hi! `audiofolder` requires `datasets>=2.5.0`, so please update the `datasets`' installation (`pip install -U datasets`) in the environment (and restart the env for the update to take effect) to resolve the issue.",
"> Hi! `audiofolder` requires `datasets>=2.5.0`, so please update the `datasets`' installation (`p... | 2023-05-14T00:50:47Z | 2023-08-16T13:35:36Z | 2023-07-21T13:53:45Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
It's crash log:
FileNotFoundError: Couldn't find a dataset script at /kaggle/working/audiofolder/audiofolder.py or any data file in the same directory. Couldn't find 'audiofolder' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/audiofolder/audiofolder.py
### Steps to reproduce the bug
common_voice = load_dataset("audiofolder", data_dir="/kaggle/working/data")
### Expected behavior
load dataset without error. It works ok on colab, but on kaggle it happends.
### Environment info
- `datasets` version: 2.1.0
- Platform: Linux-5.15.109+-x86_64-with-glibc2.31
- Python version: 3.10.10
- PyArrow version: 9.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/5765 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5765/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5765/comments | https://api.github.com/repos/huggingface/datasets/issues/5765/events | https://github.com/huggingface/datasets/issues/5765 | 1,671,388,824 | I_kwDODunzps5jn16Y | 5,765 | ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text'] | {
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"You need to remove the `text` and `text_en` columns before passing the dataset to the `DataLoader` to avoid this error:\r\n```python\r\ntokenized_datasets = tokenized_datasets.remove_columns([\"text\", \"text_en\"])\r\n```\r\n",
"Thanks @mariosasko. Now I am getting this error:\r\n\r\n```\r\nTraceback (most rece... | 2023-04-17T15:00:50Z | 2023-04-25T13:50:45Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Following is my code that I am trying to run, but facing an error (have attached the whole error below):
My code:
```
from collections import OrderedDict
import warnings
import flwr as fl
import torch
import numpy as np
import random
from torch.utils.data import DataLoader
from datasets import load_dataset, load_metric
from transformers import AutoTokenizer, DataCollatorWithPadding
from transformers import AutoModelForSequenceClassification
from transformers import AdamW
#from transformers import tokenized_datasets
warnings.filterwarnings("ignore", category=UserWarning)
# DEVICE = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
DEVICE = "cpu"
CHECKPOINT = "distilbert-base-uncased" # transformer model checkpoint
def load_data():
"""Load IMDB data (training and eval)"""
raw_datasets = load_dataset("yhavinga/imdb_dutch")
raw_datasets = raw_datasets.shuffle(seed=42)
# remove unnecessary data split
del raw_datasets["unsupervised"]
tokenizer = AutoTokenizer.from_pretrained(CHECKPOINT)
def tokenize_function(examples):
return tokenizer(examples["text"], truncation=True)
# random 100 samples
population = random.sample(range(len(raw_datasets["train"])), 100)
tokenized_datasets = raw_datasets.map(tokenize_function, batched=True)
tokenized_datasets["train"] = tokenized_datasets["train"].select(population)
tokenized_datasets["test"] = tokenized_datasets["test"].select(population)
# tokenized_datasets = tokenized_datasets.remove_columns("text")
# tokenized_datasets = tokenized_datasets.rename_column("label", "labels")
tokenized_datasets = tokenized_datasets.remove_columns("attention_mask")
tokenized_datasets = tokenized_datasets.remove_columns("input_ids")
tokenized_datasets = tokenized_datasets.remove_columns("label")
tokenized_datasets = tokenized_datasets.remove_columns("text_en")
# tokenized_datasets = tokenized_datasets.remove_columns(raw_datasets["train"].column_names)
data_collator = DataCollatorWithPadding(tokenizer=tokenizer)
trainloader = DataLoader(
tokenized_datasets["train"],
shuffle=True,
batch_size=32,
collate_fn=data_collator,
)
testloader = DataLoader(
tokenized_datasets["test"], batch_size=32, collate_fn=data_collator
)
return trainloader, testloader
def train(net, trainloader, epochs):
optimizer = AdamW(net.parameters(), lr=5e-4)
net.train()
for _ in range(epochs):
for batch in trainloader:
batch = {k: v.to(DEVICE) for k, v in batch.items()}
outputs = net(**batch)
loss = outputs.loss
loss.backward()
optimizer.step()
optimizer.zero_grad()
def test(net, testloader):
metric = load_metric("accuracy")
loss = 0
net.eval()
for batch in testloader:
batch = {k: v.to(DEVICE) for k, v in batch.items()}
with torch.no_grad():
outputs = net(**batch)
logits = outputs.logits
loss += outputs.loss.item()
predictions = torch.argmax(logits, dim=-1)
metric.add_batch(predictions=predictions, references=batch["labels"])
loss /= len(testloader.dataset)
accuracy = metric.compute()["accuracy"]
return loss, accuracy
def main():
net = AutoModelForSequenceClassification.from_pretrained(
CHECKPOINT, num_labels=2
).to(DEVICE)
trainloader, testloader = load_data()
# Flower client
class IMDBClient(fl.client.NumPyClient):
def get_parameters(self, config):
return [val.cpu().numpy() for _, val in net.state_dict().items()]
def set_parameters(self, parameters):
params_dict = zip(net.state_dict().keys(), parameters)
state_dict = OrderedDict({k: torch.Tensor(v) for k, v in params_dict})
net.load_state_dict(state_dict, strict=True)
def fit(self, parameters, config):
self.set_parameters(parameters)
print("Training Started...")
train(net, trainloader, epochs=1)
print("Training Finished.")
return self.get_parameters(config={}), len(trainloader), {}
def evaluate(self, parameters, config):
self.set_parameters(parameters)
loss, accuracy = test(net, testloader)
return float(loss), len(testloader), {"accuracy": float(accuracy)}
# Start client
fl.client.start_numpy_client(server_address="localhost:8080", client=IMDBClient())
if __name__ == "__main__":
main()
```
Error:
```
Traceback (most recent call last):
File "client_2.py", line 136, in <module>
main()
File "client_2.py", line 132, in main
fl.client.start_numpy_client(server_address="localhost:8080", client=IMDBClient())
File "/home/saurav/.local/lib/python3.8/site-packages/flwr/client/app.py", line 208, in start_numpy_client
start_client(
File "/home/saurav/.local/lib/python3.8/site-packages/flwr/client/app.py", line 142, in start_client
client_message, sleep_duration, keep_going = handle(
File "/home/saurav/.local/lib/python3.8/site-packages/flwr/client/grpc_client/message_handler.py", line 68, in handle
return _fit(client, server_msg.fit_ins), 0, True
File "/home/saurav/.local/lib/python3.8/site-packages/flwr/client/grpc_client/message_handler.py", line 157, in _fit
fit_res = client.fit(fit_ins)
File "/home/saurav/.local/lib/python3.8/site-packages/flwr/client/app.py", line 252, in _fit
results = self.numpy_client.fit(parameters, ins.config) # type: ignore
File "client_2.py", line 122, in fit
train(net, trainloader, epochs=1)
File "client_2.py", line 76, in train
for batch in trainloader:
File "/home/saurav/.local/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 652, in __next__
data = self._next_data()
File "/home/saurav/.local/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 692, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/saurav/.local/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 52, in fetch
return self.collate_fn(data)
File "/home/saurav/.local/lib/python3.8/site-packages/transformers/data/data_collator.py", line 221, in __call__
batch = self.tokenizer.pad(
File "/home/saurav/.local/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 2713, in pad
raise ValueError(
ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text']
```
### Steps to reproduce the bug
Run the above code.
### Expected behavior
Don't know, doing it for the first time.
### Environment info
- `datasets` version: 1.12.1
- Platform: Linux-5.4.0-58-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 11.0.0
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https://api.github.com/repos/huggingface/datasets/issues/7487 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7487/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7487/comments | https://api.github.com/repos/huggingface/datasets/issues/7487/events | https://github.com/huggingface/datasets/pull/7487 | 2,956,533,448 | PR_kwDODunzps6QlF8N | 7,487 | Write pdf in map | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7487). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-03-28T15:49:25Z | 2025-03-28T17:09:53Z | 2025-03-28T17:09:51Z | MEMBER | null | null | null | Fix this error when mapping a PDF dataset
```
pyarrow.lib.ArrowInvalid: Could not convert <pdfplumber.pdf.PDF object at 0x13498ee40> with type PDF: did not recognize Python value type when inferring an Arrow data type
```
and also let map() outputs be lists of images or pdfs | {
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https://api.github.com/repos/huggingface/datasets/issues/5115 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5115/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5115/comments | https://api.github.com/repos/huggingface/datasets/issues/5115/events | https://github.com/huggingface/datasets/pull/5115 | 1,409,250,020 | PR_kwDODunzps5Az9Pm | 5,115 | Fix iter_batches | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I also ran the code in https://github.com/huggingface/datasets/issues/5111 and it works fine now :)",
"This is ready for review :)"
] | 2022-10-14T12:06:14Z | 2022-10-14T15:02:15Z | 2022-10-14T14:59:58Z | MEMBER | null | null | null | The `pa.Table.to_reader()` method available in `pyarrow>=8.0.0` may return chunks of size < `max_chunksize`, therefore `iter_batches` can return batches smaller than the `batch_size` specified by the user
Therefore batched `map` couldn't always use batches of the right size, e.g. this fails because it runs only on one batch of one element:
```python
from datasets import Dataset, concatenate_datasets
ds = concatenate_datasets([Dataset.from_dict({"a": [i]}) for i in range(10)])
ds2 = ds.map(lambda _: {}, batched=True)
assert list(ds2) == list(ds)
```
This was introduced in https://github.com/huggingface/datasets/pull/5030
Close https://github.com/huggingface/datasets/issues/5111
This will require a patch release along with https://github.com/huggingface/datasets/pull/5113
TODO:
- [x] fix tests
- [x] add more tests | {
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https://api.github.com/repos/huggingface/datasets/issues/7156 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7156/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7156/comments | https://api.github.com/repos/huggingface/datasets/issues/7156/events | https://github.com/huggingface/datasets/issues/7156 | 2,539,360,617 | I_kwDODunzps6XW5Fp | 7,156 | interleave_datasets resets shuffle state | {
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"It also does preserve `split_by_node`, so in the meantime you should call `shuffle` or `split_by_node` AFTER `interleave_datasets` or `concatenate_datasets`"
] | 2024-09-20T17:57:54Z | 2025-03-18T10:56:25Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
```
import datasets
import torch.utils.data
def gen(shards):
yield {"shards": shards}
def main():
dataset = datasets.IterableDataset.from_generator(
gen,
gen_kwargs={'shards': list(range(25))}
)
dataset = dataset.shuffle(buffer_size=1)
dataset = datasets.interleave_datasets(
[dataset, dataset], probabilities=[1, 0], stopping_strategy="all_exhausted"
)
dataloader = torch.utils.data.DataLoader(
dataset,
batch_size=8,
num_workers=8,
)
for i, batch in enumerate(dataloader):
print(batch)
if i >= 10:
break
if __name__ == "__main__":
main()
```
### Steps to reproduce the bug
Run the script, it will output
```
{'shards': [tensor([ 0, 8, 16, 24, 0, 8, 16, 24])]}
{'shards': [tensor([ 1, 9, 17, 1, 9, 17, 1, 9])]}
{'shards': [tensor([ 2, 10, 18, 2, 10, 18, 2, 10])]}
{'shards': [tensor([ 3, 11, 19, 3, 11, 19, 3, 11])]}
{'shards': [tensor([ 4, 12, 20, 4, 12, 20, 4, 12])]}
{'shards': [tensor([ 5, 13, 21, 5, 13, 21, 5, 13])]}
{'shards': [tensor([ 6, 14, 22, 6, 14, 22, 6, 14])]}
{'shards': [tensor([ 7, 15, 23, 7, 15, 23, 7, 15])]}
{'shards': [tensor([ 0, 8, 16, 24, 0, 8, 16, 24])]}
{'shards': [tensor([17, 1, 9, 17, 1, 9, 17, 1])]}
{'shards': [tensor([18, 2, 10, 18, 2, 10, 18, 2])]}
```
### Expected behavior
The shards should be shuffled.
### Environment info
- `datasets` version: 3.0.0
- Platform: Linux-5.15.153.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
- Python version: 3.10.12
- `huggingface_hub` version: 0.25.0
- PyArrow version: 17.0.0
- Pandas version: 2.0.3
- `fsspec` version: 2023.6.0 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7495 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7495/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7495/comments | https://api.github.com/repos/huggingface/datasets/issues/7495/events | https://github.com/huggingface/datasets/issues/7495 | 2,967,034,060 | I_kwDODunzps6w2VjM | 7,495 | Columns in the dataset obtained though load_dataset do not correspond to the one in the dataset viewer since 3.4.0 | {
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} | [] | open | false | null | [] | null | [] | 2025-04-02T17:01:11Z | 2025-04-03T09:54:22Z | null | CONTRIBUTOR | null | null | {
"completed": 0,
"percent_completed": 0,
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} | ### Describe the bug
I have noticed that on my dataset named [BrunoHays/Accueil_UBS](https://huggingface.co/datasets/BrunoHays/Accueil_UBS), since the version 3.4.0, every column except audio is missing when I load the dataset.
Interestingly, the dataset viewer still shows the correct columns
### Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset("BrunoHays/Accueil_UBS", streaming=True)
print(next(iter(ds["test"])).keys())
```
With datasets >= 3.4.0:
-> dict_keys(['audio'])
With datasets == 3.3.2:
-> dict_keys(['audio', 'id', 'speaker', 'sentence', 'raw_sentence', 'start_timestamp', 'end_timestamp', 'overlap'])
### Expected behavior
All the columns should be present
### Environment info
- `datasets` version: 3.3.2
- Platform: macOS-14.6.1-x86_64-i386-64bit
- Python version: 3.10.15
- `huggingface_hub` version: 0.30.1
- PyArrow version: 16.1.0
- Pandas version: 1.5.3
- `fsspec` version: 2023.10.0
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https://api.github.com/repos/huggingface/datasets/issues/4928 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4928/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4928/comments | https://api.github.com/repos/huggingface/datasets/issues/4928/events | https://github.com/huggingface/datasets/pull/4928 | 1,360,941,172 | PR_kwDODunzps4-Ubi4 | 4,928 | Add ability to read-write to SQL databases. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Ah CI runs with `pandas=1.3.5` which doesn't return the number of row inserted.",
"wow this is super cool!",
"@lhoestq I'm getting error in integration tests, not sure if it's related to my PR. Any help would be appreciated :) \r... | 2022-09-03T19:09:08Z | 2022-10-03T16:34:36Z | 2022-10-03T16:32:28Z | CONTRIBUTOR | null | null | null | Fixes #3094
Add ability to read/write to SQLite files and also read from any SQL database supported by SQLAlchemy.
I didn't add SQLAlchemy as a dependence as it is fairly big and it remains optional.
I also recorded a Loom to showcase the feature.
https://www.loom.com/share/f0e602c2de8a46f58bca4b43333d541f | {
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https://api.github.com/repos/huggingface/datasets/issues/7297 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7297/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7297/comments | https://api.github.com/repos/huggingface/datasets/issues/7297/events | https://github.com/huggingface/datasets/issues/7297 | 2,683,977,430 | I_kwDODunzps6f-j7W | 7,297 | wrong return type for `IterableDataset.shard()` | {
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"Oops my bad ! thanks for reporting"
] | 2024-11-22T17:25:46Z | 2024-12-03T14:27:27Z | 2024-12-03T14:27:03Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
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} | ### Describe the bug
`IterableDataset.shard()` has the wrong typing for its return as `"Dataset"`. It should be `"IterableDataset"`. Makes my IDE unhappy.
### Steps to reproduce the bug
look at [the source code](https://github.com/huggingface/datasets/blob/main/src/datasets/iterable_dataset.py#L2668)?
### Expected behavior
Correct return type as `"IterableDataset"`
### Environment info
datasets==3.1.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6007 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6007/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6007/comments | https://api.github.com/repos/huggingface/datasets/issues/6007/events | https://github.com/huggingface/datasets/issues/6007 | 1,789,782,693 | I_kwDODunzps5qreql | 6,007 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset | {
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] | open | false | null | [] | null | [
"This error means that one of the int32 (`Value(\"int32\")`) columns in the dataset has a value that is out of the valid (int32) range.\r\n\r\nI'll open a PR to print the name of a problematic column to make debugging such errors easier.",
"I am afraid int32 is not the reason for this error.\r\n\r\nI have submitt... | 2023-07-05T15:16:50Z | 2024-02-07T22:22:35Z | null | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encountered the error: "OverflowError: Python int too large to convert to C long"
The error look something like:
```
OverflowError: Python int too large to convert to C long
During handling of the above exception, another exception occurred:
OverflowError Traceback (most recent call last)
<ipython-input-7-0ed8700e662d> in <module>
----> 1 dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train', cache_dir='/sfs/MNBVC/.cache/')
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)
1749 ignore_verifications=ignore_verifications,
1750 try_from_hf_gcs=try_from_hf_gcs,
-> 1751 use_auth_token=use_auth_token,
1752 )
1753
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
703 if not downloaded_from_gcs:
704 self._download_and_prepare(
--> 705 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
706 )
707 # Sync info
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos)
1225
1226 def _download_and_prepare(self, dl_manager, verify_infos):
-> 1227 super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos)
1228
1229 def _get_examples_iterable_for_split(self, split_generator: SplitGenerator) -> ExamplesIterable:
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
791 try:
792 # Prepare split will record examples associated to the split
--> 793 self._prepare_split(split_generator, **prepare_split_kwargs)
794 except OSError as e:
795 raise OSError(
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/builder.py in _prepare_split(self, split_generator, check_duplicate_keys)
1219 writer.write(example, key)
1220 finally:
-> 1221 num_examples, num_bytes = writer.finalize()
1222
1223 split_generator.split_info.num_examples = num_examples
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/arrow_writer.py in finalize(self, close_stream)
536 # Re-intializing to empty list for next batch
537 self.hkey_record = []
--> 538 self.write_examples_on_file()
539 if self.pa_writer is None:
540 if self.schema:
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/arrow_writer.py in write_examples_on_file(self)
407 # Since current_examples contains (example, key) tuples
408 batch_examples[col] = [row[0][col] for row in self.current_examples]
--> 409 self.write_batch(batch_examples=batch_examples)
410 self.current_examples = []
411
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/arrow_writer.py in write_batch(self, batch_examples, writer_batch_size)
506 col_try_type = try_features[col] if try_features is not None and col in try_features else None
507 typed_sequence = OptimizedTypedSequence(batch_examples[col], type=col_type, try_type=col_try_type, col=col)
--> 508 arrays.append(pa.array(typed_sequence))
509 inferred_features[col] = typed_sequence.get_inferred_type()
510 schema = inferred_features.arrow_schema if self.pa_writer is None else self.schema
/sfs/MNBVC/venv/lib64/python3.6/site-packages/pyarrow/array.pxi in pyarrow.lib.array()
/sfs/MNBVC/venv/lib64/python3.6/site-packages/pyarrow/array.pxi in pyarrow.lib._handle_arrow_array_protocol()
/sfs/MNBVC/venv/lib64/python3.6/site-packages/datasets/arrow_writer.py in __arrow_array__(self, type)
180 else:
181 trying_cast_to_python_objects = True
--> 182 out = pa.array(cast_to_python_objects(data, only_1d_for_numpy=True))
183 # use smaller integer precisions if possible
184 if self.trying_int_optimization:
/sfs/MNBVC/venv/lib64/python3.6/site-packages/pyarrow/array.pxi in pyarrow.lib.array()
/sfs/MNBVC/venv/lib64/python3.6/site-packages/pyarrow/array.pxi in pyarrow.lib._sequence_to_array()
/sfs/MNBVC/venv/lib64/python3.6/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
OverflowError: Python int too large to convert to C long
```
However, that dataset can be loaded in a streaming manner:
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train', streaming=True)
for i in dataset:
pass # it work well
```
Another issue is reported in our dataset hub:
https://huggingface.co/datasets/liwu/MNBVC/discussions/2
### Steps to reproduce the bug
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
### Expected behavior
the dataset can be safely loaded
### Environment info
- `datasets` version: 2.4.0
- Platform: Linux-3.10.0-1160.an7.x86_64-x86_64-with-centos-7.9
- Python version: 3.6.8
- PyArrow version: 6.0.1
- Pandas version: 1.1.5 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4704 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4704/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4704/comments | https://api.github.com/repos/huggingface/datasets/issues/4704/events | https://github.com/huggingface/datasets/pull/4704 | 1,308,147,876 | PR_kwDODunzps47lCFt | 4,704 | Skip tests only for lz4/zstd params if not installed | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-18T15:41:40Z | 2022-07-19T13:02:31Z | 2022-07-19T12:49:18Z | MEMBER | null | null | null | Currently, if `zstandard` or `lz4` are not installed, `test_compression_filesystems` and `test_streaming_dl_manager_extract_all_supported_single_file_compression_types` are skipped for all compression format parameters.
This PR fixes these tests, so that if `zstandard` or `lz4` are not installed, the tests are skipped only for the corresponding compression parameters (`zstd` or `lz4`), whereas the tests are not skipped for all the other compression parameters (`gzip`, `xz` and `bz2`).
Related to:
- #4688 | {
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https://api.github.com/repos/huggingface/datasets/issues/6937 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6937/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6937/comments | https://api.github.com/repos/huggingface/datasets/issues/6937/events | https://github.com/huggingface/datasets/issues/6937 | 2,327,212,611 | I_kwDODunzps6KtnJD | 6,937 | JSON loader implicitly coerces floats to integers | {
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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | [] | 2024-05-31T08:09:12Z | 2024-05-31T08:11:57Z | null | MEMBER | null | null | {
"completed": 0,
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} | The JSON loader implicitly coerces floats to integers.
The column values `[0.0, 1.0, 2.0]` are coerced to `[0, 1, 2]`.
See CI error in dataset-viewer: https://github.com/huggingface/dataset-viewer/actions/runs/9290164936/job/25576926446
```
=================================== FAILURES ===================================
___________________________ test_statistics_endpoint ___________________________
normal_user_public_json_dataset = 'DVUser/tmp-dataset-17170199043860'
def test_statistics_endpoint(normal_user_public_json_dataset: str) -> None:
dataset = normal_user_public_json_dataset
config, split = get_default_config_split()
statistics_response = poll_until_ready_and_assert(
relative_url=f"/statistics?dataset={dataset}&config={config}&split={split}",
check_x_revision=True,
dataset=dataset,
)
content = statistics_response.json()
assert len(content) == 3
assert sorted(content) == ["num_examples", "partial", "statistics"], statistics_response
statistics = content["statistics"]
num_examples = content["num_examples"]
partial = content["partial"]
assert isinstance(statistics, list), statistics
assert len(statistics) == 6
assert num_examples == 4
assert partial is False
string_label_column = statistics[0]
assert "column_name" in string_label_column
assert "column_statistics" in string_label_column
assert "column_type" in string_label_column
assert string_label_column["column_name"] == "col_1"
assert string_label_column["column_type"] == "string_label" # 4 unique values -> label
assert isinstance(string_label_column["column_statistics"], dict)
assert string_label_column["column_statistics"] == {
"nan_count": 0,
"nan_proportion": 0.0,
"no_label_count": 0,
"no_label_proportion": 0.0,
"n_unique": 4,
"frequencies": {
"There goes another one.": 1,
"Vader turns round and round in circles as his ship spins into space.": 1,
"We count thirty Rebel ships, Lord Vader.": 1,
"The wingman spots the pirateship coming at him and warns the Dark Lord": 1,
},
}
int_column = statistics[1]
assert "column_name" in int_column
assert "column_statistics" in int_column
assert "column_type" in int_column
assert int_column["column_name"] == "col_2"
assert int_column["column_type"] == "int"
assert isinstance(int_column["column_statistics"], dict)
assert int_column["column_statistics"] == {
"histogram": {"bin_edges": [0, 1, 2, 3, 3], "hist": [1, 1, 1, 1]},
"max": 3,
"mean": 1.5,
"median": 1.5,
"min": 0,
"nan_count": 0,
"nan_proportion": 0.0,
"std": 1.29099,
}
float_column = statistics[2]
assert "column_name" in float_column
assert "column_statistics" in float_column
assert "column_type" in float_column
assert float_column["column_name"] == "col_3"
> assert float_column["column_type"] == "float"
E AssertionError: assert 'int' == 'float'
E - float
E + int
tests/test_14_statistics.py:72: AssertionError
=========================== short test summary info ============================
FAILED tests/test_14_statistics.py::test_statistics_endpoint - AssertionError: assert 'int' == 'float'
- float
+ int
```
This bug was introduced after:
- #6914
We have reported the issue to pandas:
- https://github.com/pandas-dev/pandas/issues/58866 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4623 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4623/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4623/comments | https://api.github.com/repos/huggingface/datasets/issues/4623/events | https://github.com/huggingface/datasets/issues/4623 | 1,293,042,894 | I_kwDODunzps5NEkTO | 4,623 | Loading MNIST as Pytorch Dataset | {
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] | open | false | null | [] | null | [
"Hi ! We haven't implemented the conversion from images data to PyTorch tensors yet I think\r\n\r\ncc @mariosasko ",
"So I understand:\r\n\r\nset_format() does not properly do the conversion to pytorch tensors from PIL images.\r\n\r\nSo that someone who stumbles on this can use the package:\r\n\r\n```python\r\nda... | 2022-07-04T11:33:10Z | 2022-07-04T14:40:50Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ## Describe the bug
Conversion of MNIST dataset to pytorch fails with bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("mnist", split="train")
dataset.set_format('torch')
dataset[0]
print()
```
## Expected results
Expect to see torch tensors image and label
## Actual results
Traceback (most recent call last):
File "C:\Program Files\JetBrains\PyCharm 2020.3.3\plugins\python\helpers\pydev\pydevd.py", line 1491, in _exec
pydev_imports.execfile(file, globals, locals) # execute the script
File "C:\Program Files\JetBrains\PyCharm 2020.3.3\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "C:/Users/chapm/PycharmProjects/multiviewdata/multiviewdata/huggingface/mnist.py", line 13, in <module>
dataset[0]
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\arrow_dataset.py", line 2154, in __getitem__
return self._getitem(
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\arrow_dataset.py", line 2139, in _getitem
formatted_output = format_table(
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\formatting\formatting.py", line 532, in format_table
return formatter(pa_table, query_type=query_type)
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\formatting\formatting.py", line 281, in __call__
return self.format_row(pa_table)
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\formatting\torch_formatter.py", line 58, in format_row
return self.recursive_tensorize(row)
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\formatting\torch_formatter.py", line 54, in recursive_tensorize
return map_nested(self._recursive_tensorize, data_struct, map_list=False)
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\utils\py_utils.py", line 356, in map_nested
mapped = [
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\utils\py_utils.py", line 357, in <listcomp>
_single_map_nested((function, obj, types, None, True, None))
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\utils\py_utils.py", line 309, in _single_map_nested
return {k: _single_map_nested((function, v, types, None, True, None)) for k, v in pbar}
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\utils\py_utils.py", line 309, in <dictcomp>
return {k: _single_map_nested((function, v, types, None, True, None)) for k, v in pbar}
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\utils\py_utils.py", line 293, in _single_map_nested
return function(data_struct)
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\formatting\torch_formatter.py", line 51, in _recursive_tensorize
return self._tensorize(data_struct)
File "C:\Users\chapm\PycharmProjects\multiviewdata\venv\lib\site-packages\datasets\formatting\torch_formatter.py", line 38, in _tensorize
if np.issubdtype(value.dtype, np.integer):
AttributeError: 'bytes' object has no attribute 'dtype'
python-BaseException
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.2
- Platform: Windows-10-10.0.22579-SP0
- Python version: 3.9.2
- PyArrow version: 8.0.0
- Pandas version: 1.4.1
| null | {
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https://api.github.com/repos/huggingface/datasets/issues/6813 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6813/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6813/comments | https://api.github.com/repos/huggingface/datasets/issues/6813/events | https://github.com/huggingface/datasets/pull/6813 | 2,245,626,870 | PR_kwDODunzps5sx-9V | 6,813 | Add Dataset.take and Dataset.skip | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6813). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-04-16T09:53:42Z | 2024-04-16T14:12:14Z | 2024-04-16T14:06:07Z | MEMBER | null | null | null | ...to be aligned with IterableDataset.take and IterableDataset.skip | {
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https://api.github.com/repos/huggingface/datasets/issues/6169 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6169/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6169/comments | https://api.github.com/repos/huggingface/datasets/issues/6169/events | https://github.com/huggingface/datasets/issues/6169 | 1,862,360,199 | I_kwDODunzps5vAVyH | 6,169 | Configurations in yaml not working | {
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"Unfortunately, I cannot reproduce this behavior on my machine or Colab - the reproducer returns `['main_data', 'additional_data']` as expected.",
"Thank you for looking into this, Mario. Is this on [my repository](https://huggingface.co/datasets/tsor13/test), or on another one that you have reproduced? Would you... | 2023-08-23T00:13:22Z | 2023-08-23T15:35:31Z | null | NONE | null | null | {
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} | ### Dataset configurations cannot be created in YAML/README
Hello! I'm trying to follow the docs here in order to create structure in my dataset as added from here (#5331): https://github.com/huggingface/datasets/blob/8b8e6ee067eb74e7965ca2a6768f15f9398cb7c8/docs/source/repository_structure.mdx#L110-L118
I have the exact example in my config file for [my data repo](https://huggingface.co/datasets/tsor13/test):
```
configs:
- config_name: main_data
data_files: "main_data.csv"
- config_name: additional_data
data_files: "additional_data.csv"
```
Yet, I'm unable to load different configurations:
```
from datasets import get_dataset_config_names
get_dataset_config_names('tsor13/test', use_auth_token=True)
```
returns a single split, `['tsor13--test']`
Does anyone have any insights?
@polinaeterna thank you for adding this feature, it is super useful. Do you happen to have any ideas?
### Steps to reproduce the bug
from datasets import get_dataset_config_names
get_dataset_config_names('tsor13/test')
### Expected behavior
I would expect there to be two splits, `main_data` and `additional_data`. However, only `['tsor13--test']` test is returned.
### Environment info
- `datasets` version: 2.14.4
- Platform: macOS-13.4-arm64-arm-64bit
- Python version: 3.11.4
- Huggingface_hub version: 0.16.4
- PyArrow version: 12.0.1
- Pandas version: 1.5.1 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4967 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4967/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4967/comments | https://api.github.com/repos/huggingface/datasets/issues/4967/events | https://github.com/huggingface/datasets/pull/4967 | 1,369,092,452 | PR_kwDODunzps4-vbS- | 4,967 | Strip "/" in local dataset path to avoid empty dataset name error | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Cool :-)"
] | 2022-09-11T23:09:16Z | 2022-09-29T10:46:21Z | 2022-09-12T15:30:38Z | CONTRIBUTOR | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7391 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7391/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7391/comments | https://api.github.com/repos/huggingface/datasets/issues/7391/events | https://github.com/huggingface/datasets/issues/7391 | 2,845,184,764 | I_kwDODunzps6plhL8 | 7,391 | AttributeError: module 'pyarrow.lib' has no attribute 'ListViewType' | {
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https://api.github.com/repos/huggingface/datasets/issues/4838 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4838/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4838/comments | https://api.github.com/repos/huggingface/datasets/issues/4838/events | https://github.com/huggingface/datasets/pull/4838 | 1,337,194,918 | PR_kwDODunzps49F08R | 4,838 | Fix documentation card of adv_glue dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The failing test has nothing to do with this PR:\r\n```\r\nFAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_multiple_files\r\n```"
] | 2022-08-12T13:15:26Z | 2022-08-15T10:17:14Z | 2022-08-15T10:02:11Z | MEMBER | null | null | null | Fix documentation card of adv_glue dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/6371 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6371/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6371/comments | https://api.github.com/repos/huggingface/datasets/issues/6371/events | https://github.com/huggingface/datasets/issues/6371 | 1,972,807,579 | I_kwDODunzps51lqeb | 6,371 | `Dataset.from_generator` should not try to download from HF GCS | {
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"Indeed, setting `try_from_gcs` to `False` makes sense for `from_generator`.\r\n\r\nWe plan to deprecate and remove `try_from_hf_gcs` soon, as we can use Hub for file hosting now, but this is a good temporary fix.\r\n"
] | 2023-11-01T17:36:17Z | 2023-11-02T15:52:10Z | 2023-11-02T15:52:10Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
When using [`Dataset.from_generator`](https://github.com/huggingface/datasets/blob/c9c1166e1cf81d38534020f9c167b326585339e5/src/datasets/arrow_dataset.py#L1072) with `streaming=False`, the internal logic will call [`download_and_prepare`](https://github.com/huggingface/datasets/blob/main/src/datasets/io/generator.py#L47) which will attempt to download from HF GCS which is redundant, because user has already provided the generator from which the data should be drawn.
If someone attempts to call `Dataset.from_generator` from an environment that doesn't have external internet access (for example internal production machine) and doesn't set `HF_DATASETS_OFFLINE=1`, this will result in process being stuck at building connection.
### Steps to reproduce the bug
```python
import datasets
def gen():
for _ in range(100):
yield {"text": "dummy text"}
dataset = datasets.Dataset.from_generator(gen)
```
A minimum example executed on any environment that doesn't have access to HF GCS can result in the error
### Expected behavior
`try_from_hf_gcs` should be set to False here https://github.com/huggingface/datasets/blob/c9c1166e1cf81d38534020f9c167b326585339e5/src/datasets/io/generator.py#L51
### Environment info
- `datasets` version: 2.14.4
- Platform: Linux-3.10.0-1160.90.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.10.12
- Huggingface_hub version: 0.17.1
- PyArrow version: 12.0.1
- Pandas version: 2.0.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/6847 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6847/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6847/comments | https://api.github.com/repos/huggingface/datasets/issues/6847/events | https://github.com/huggingface/datasets/issues/6847 | 2,268,589,177 | I_kwDODunzps6HN-x5 | 6,847 | [Streaming] Only load requested splits without resolving files for the other splits | {
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"This should help fixing this issue: https://github.com/huggingface/datasets/pull/6832",
"I'm having a similar issue when using splices:\r\n<img width=\"947\" alt=\"image\" src=\"https://github.com/huggingface/datasets/assets/28941213/2153faac-e1fe-4b6d-a79b-30b2699407e8\">\r\n<img width=\"823\" alt=\"image\" src... | 2024-04-29T09:49:32Z | 2024-05-07T04:43:59Z | null | MEMBER | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | e.g. [thangvip](https://huggingface.co/thangvip)/[cosmopedia_vi_math](https://huggingface.co/datasets/thangvip/cosmopedia_vi_math) has 300 splits and it takes a very long time to load only one split.
This is due to `load_dataset()` resolving the files of all the splits even if only one is needed.
In `dataset-viewer` the splits are loaded in different jobs so it results in 300 jobs that resolve 300 splits -> 90k calls to `/paths-info` | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5938 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5938/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5938/comments | https://api.github.com/repos/huggingface/datasets/issues/5938/events | https://github.com/huggingface/datasets/pull/5938 | 1,749,462,851 | PR_kwDODunzps5SmbkI | 5,938 | Make get_from_cache use custom temp filename that is locked | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-06-09T09:01:13Z | 2023-06-14T13:35:38Z | 2023-06-14T13:27:24Z | MEMBER | null | null | null | This PR ensures that the temporary filename created is the same as the one that is locked, while writing to the cache.
This PR stops using `tempfile` to generate the temporary filename.
Additionally, the behavior now is aligned for both `resume_download` `True` and `False`.
Refactor temp_file_manager so that it uses the filename that is locked:
- Use: `cache_path + ".incomplete"`, when the locked one is `cache_path + ".lock"`
Before it was using `tempfile` inside `cache_dir`, which was not locked: although very improbable name collision (8 random characters), this was not impossible when huge number of multiple processes.
Maybe related to "Stale file handle" issues caused by `tempfile`:
- [ ] https://huggingface.co/datasets/tapaco/discussions/4
- [ ] https://huggingface.co/datasets/xcsr/discussions/1
- [ ] https://huggingface.co/datasets/covost2/discussions/3
```
Error code: ConfigNamesError
Exception: OSError
Message: [Errno 116] Stale file handle
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 61, in compute_config_names_response
for config in sorted(get_dataset_config_names(path=dataset, use_auth_token=use_auth_token))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 323, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1219, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1188, in dataset_module_factory
return HubDatasetModuleFactoryWithScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 907, in get_module
dataset_readme_path = self.download_dataset_readme_file()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 896, in download_dataset_readme_file
return cached_path(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 183, in cached_path
output_path = get_from_cache(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 611, in get_from_cache
http_get(
File "/usr/local/lib/python3.9/tempfile.py", line 496, in __exit__
result = self.file.__exit__(exc, value, tb)
OSError: [Errno 116] Stale file handle
```
- the stale file handle error can be raised when `tempfile` tries to close (when exiting its context manager) a filename that has been already closed by other process
- note that `tempfile` filenames are randomly generated but not locked in our code
CC: @severo | {
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