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https://api.github.com/repos/huggingface/datasets/issues/6283 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6283/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6283/comments | https://api.github.com/repos/huggingface/datasets/issues/6283/events | https://github.com/huggingface/datasets/pull/6283 | 1,928,552,257 | PR_kwDODunzps5cBlKq | 6,283 | Fix array cast/embed with null values | {
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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... | 2023-10-05T15:24:05Z | 2024-07-04T07:24:20Z | 2024-02-06T19:24:19Z | COLLABORATOR | null | null | null | Fixes issues with casting/embedding PyArrow list arrays with null values. It also bumps the required PyArrow version to 12.0.0 (over 9 months old) to simplify the implementation.
Fix #6280, fix #6311, fix #6360
(Also fixes https://github.com/huggingface/datasets/issues/5430 to make Beam compatible with PyArrow>=12.0.0) | {
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https://api.github.com/repos/huggingface/datasets/issues/4715 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4715/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4715/comments | https://api.github.com/repos/huggingface/datasets/issues/4715/events | https://github.com/huggingface/datasets/pull/4715 | 1,309,405,980 | PR_kwDODunzps47pSui | 4,715 | Fix POS tags | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"CI failures are about missing content in the dataset cards or bad tags, and this is unrelated to this PR. Merging :)"
] | 2022-07-19T11:52:54Z | 2022-07-19T12:54:34Z | 2022-07-19T12:41:16Z | MEMBER | null | null | null | We're now using `part-of-speech` and not `part-of-speech-tagging`, see discussion here: https://github.com/huggingface/datasets/commit/114c09aff2fa1519597b46fbcd5a8e0c0d3ae020#r78794777 | {
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https://api.github.com/repos/huggingface/datasets/issues/7107 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7107/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7107/comments | https://api.github.com/repos/huggingface/datasets/issues/7107/events | https://github.com/huggingface/datasets/issues/7107 | 2,470,444,732 | I_kwDODunzps6TP_68 | 7,107 | load_dataset broken in 2.21.0 | {
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"There seems to be a PR related to the load_dataset path that went into 2.21.0 -- https://github.com/huggingface/datasets/pull/6862/files\r\n\r\nTaking a look at it now",
"+1\r\n\r\nDowngrading to 2.20.0 fixed my issue, hopefully helpful for others.",
"I tried adding a simple test to `test_load.py` with the alp... | 2024-08-16T14:59:51Z | 2024-08-18T09:28:43Z | 2024-08-18T09:27:12Z | NONE | null | null | {
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} | ### Describe the bug
`eval_set = datasets.load_dataset("tatsu-lab/alpaca_eval", "alpaca_eval_gpt4_baseline", trust_remote_code=True)`
used to work till 2.20.0 but doesn't work in 2.21.0
In 2.20.0:
in 2.21.0:
### Steps to reproduce the bug
1. Spin up a new google collab
2. `pip install datasets==2.21.0`
3. `import datasets`
4. `eval_set = datasets.load_dataset("tatsu-lab/alpaca_eval", "alpaca_eval_gpt4_baseline", trust_remote_code=True)`
5. Will throw an error.
### Expected behavior
Try steps 1-5 again but replace datasets version with 2.20.0, it will work
### Environment info
- `datasets` version: 2.21.0
- Platform: Linux-6.1.85+-x86_64-with-glibc2.35
- Python version: 3.10.12
- `huggingface_hub` version: 0.23.5
- PyArrow version: 17.0.0
- Pandas version: 2.1.4
- `fsspec` version: 2024.5.0
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"_The documentation is not available anymore as the PR was closed or merged._",
"close in favor of https://github.com/huggingface/datasets/pull/5192"
] | 2022-10-25T17:21:49Z | 2022-11-16T14:21:16Z | 2022-11-02T14:03:02Z | CONTRIBUTOR | null | null | null | will fix https://github.com/huggingface/datasets/issues/5153 and redundant labels displaying for most of the images datasets on the Hub (which are used just to store files)
TODO: discuss adding `drop_labels` (and `drop_metadata`) params to yaml | {
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"Thanks for reporting, @DanielHesslow. We are fixing it. ",
"@albertvillanova thanks for taking care of this so quickly!",
"The dataset metadata is fixed. You can download it normally."
] | 2022-09-29T06:56:20Z | 2022-09-29T10:23:30Z | 2022-09-29T10:04:20Z | NONE | null | null | {
"completed": 0,
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} | Hi,
The checksum for [hendrycks_test](https://huggingface.co/datasets/hendrycks_test) does not compare correctly, I guess it has been updated on the remote.
```
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://people.eecs.berkeley.edu/~hendrycks/data.tar']
```
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https://api.github.com/repos/huggingface/datasets/issues/7441 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7441/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7441/comments | https://api.github.com/repos/huggingface/datasets/issues/7441/events | https://github.com/huggingface/datasets/issues/7441 | 2,904,702,329 | I_kwDODunzps6tIj15 | 7,441 | `drop_last_batch` does not drop the last batch using IterableDataset + interleave_datasets + multi_worker | {
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"Hi @memray, I’d like to help fix the issue with `drop_last_batch` not working when `num_workers > 1`. I’ll investigate and propose a solution. Thanks!\n",
"Thank you very much for offering to help! I also noticed a problem related to a previous issue and left a comment [here](https://github.com/huggingface/datas... | 2025-03-08T10:28:44Z | 2025-03-09T21:27:33Z | null | NONE | null | null | {
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} | ### Describe the bug
See the script below
`drop_last_batch=True` is defined using map() for each dataset.
The last batch for each dataset is expected to be dropped, id 21-25.
The code behaves as expected when num_workers=0 or 1.
When using num_workers>1, 'a-11', 'b-11', 'a-12', 'b-12' are gone and instead 21 and 22 are sampled.
### Steps to reproduce the bug
```
from datasets import Dataset
from datasets import interleave_datasets
from torch.utils.data import DataLoader
def convert_to_str(batch, dataset_name):
batch['a'] = [f"{dataset_name}-{e}" for e in batch['a']]
return batch
def gen1():
for ii in range(1, 25):
yield {"a": ii}
def gen2():
for ii in range(1, 25):
yield {"a": ii}
# https://github.com/huggingface/datasets/issues/6565
if __name__ == '__main__':
dataset1 = Dataset.from_generator(gen1).to_iterable_dataset(num_shards=2)
dataset2 = Dataset.from_generator(gen2).to_iterable_dataset(num_shards=2)
dataset1 = dataset1.map(lambda x: convert_to_str(x, dataset_name="a"), batched=True, batch_size=10, drop_last_batch=True)
dataset2 = dataset2.map(lambda x: convert_to_str(x, dataset_name="b"), batched=True, batch_size=10, drop_last_batch=True)
interleaved = interleave_datasets([dataset1, dataset2], stopping_strategy="all_exhausted")
print(f"num_workers=0")
loader = DataLoader(interleaved, batch_size=5, num_workers=0)
i = 0
for b in loader:
print(i, b['a'])
i += 1
print('=-' * 20)
print(f"num_workers=1")
loader = DataLoader(interleaved, batch_size=5, num_workers=1)
i = 0
for b in loader:
print(i, b['a'])
i += 1
print('=-' * 20)
print(f"num_workers=2")
loader = DataLoader(interleaved, batch_size=5, num_workers=2)
i = 0
for b in loader:
print(i, b['a'])
i += 1
print('=-' * 20)
print(f"num_workers=3")
loader = DataLoader(interleaved, batch_size=5, num_workers=3)
i = 0
for b in loader:
print(i, b['a'])
i += 1
```
output is:
```
num_workers=0
0 ['a-1', 'b-1', 'a-2', 'b-2', 'a-3']
1 ['b-3', 'a-4', 'b-4', 'a-5', 'b-5']
2 ['a-6', 'b-6', 'a-7', 'b-7', 'a-8']
3 ['b-8', 'a-9', 'b-9', 'a-10', 'b-10']
4 ['a-11', 'b-11', 'a-12', 'b-12', 'a-13']
5 ['b-13', 'a-14', 'b-14', 'a-15', 'b-15']
6 ['a-16', 'b-16', 'a-17', 'b-17', 'a-18']
7 ['b-18', 'a-19', 'b-19', 'a-20', 'b-20']
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
num_workers=1
0 ['a-1', 'b-1', 'a-2', 'b-2', 'a-3']
1 ['b-3', 'a-4', 'b-4', 'a-5', 'b-5']
2 ['a-6', 'b-6', 'a-7', 'b-7', 'a-8']
3 ['b-8', 'a-9', 'b-9', 'a-10', 'b-10']
4 ['a-11', 'b-11', 'a-12', 'b-12', 'a-13']
5 ['b-13', 'a-14', 'b-14', 'a-15', 'b-15']
6 ['a-16', 'b-16', 'a-17', 'b-17', 'a-18']
7 ['b-18', 'a-19', 'b-19', 'a-20', 'b-20']
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
num_workers=2
0 ['a-1', 'b-1', 'a-2', 'b-2', 'a-3']
1 ['a-13', 'b-13', 'a-14', 'b-14', 'a-15']
2 ['b-3', 'a-4', 'b-4', 'a-5', 'b-5']
3 ['b-15', 'a-16', 'b-16', 'a-17', 'b-17']
4 ['a-6', 'b-6', 'a-7', 'b-7', 'a-8']
5 ['a-18', 'b-18', 'a-19', 'b-19', 'a-20']
6 ['b-8', 'a-9', 'b-9', 'a-10', 'b-10']
7 ['b-20', 'a-21', 'b-21', 'a-22', 'b-22']
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
num_workers=3
Too many dataloader workers: 3 (max is dataset.num_shards=2). Stopping 1 dataloader workers.
0 ['a-1', 'b-1', 'a-2', 'b-2', 'a-3']
1 ['a-13', 'b-13', 'a-14', 'b-14', 'a-15']
2 ['b-3', 'a-4', 'b-4', 'a-5', 'b-5']
3 ['b-15', 'a-16', 'b-16', 'a-17', 'b-17']
4 ['a-6', 'b-6', 'a-7', 'b-7', 'a-8']
5 ['a-18', 'b-18', 'a-19', 'b-19', 'a-20']
6 ['b-8', 'a-9', 'b-9', 'a-10', 'b-10']
7 ['b-20', 'a-21', 'b-21', 'a-22', 'b-22']
```
### Expected behavior
`'a-21', 'b-21', 'a-22', 'b-22'` should be dropped
### Environment info
- `datasets` version: 3.3.2
- Platform: Linux-5.15.0-1056-aws-x86_64-with-glibc2.31
- Python version: 3.10.16
- `huggingface_hub` version: 0.28.0
- PyArrow version: 19.0.0
- Pandas version: 2.2.3
- `fsspec` version: 2024.6.1
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https://api.github.com/repos/huggingface/datasets/issues/5419 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5419/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5419/comments | https://api.github.com/repos/huggingface/datasets/issues/5419/events | https://github.com/huggingface/datasets/issues/5419 | 1,531,999,850 | I_kwDODunzps5bUHZq | 5,419 | label_column='labels' in datasets.TextClassification and 'label' or 'label_ids' in transformers.DataColator | {
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"Hi! Thanks for pointing out this inconsistency. Changing the default value at this point is probably not worth it, considering we've started discussing the state of the task API internally - we will most likely deprecate the current one and replace it with a more robust solution that relies on the `train_eval_inde... | 2023-01-13T09:40:07Z | 2023-07-21T14:27:08Z | 2023-07-21T14:27:08Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
When preparing a dataset for a task using `datasets.TextClassification`, the output feature is named `labels`. When preparing the trainer using the `transformers.DataCollator` the default column name is `label` if binary or `label_ids` if multi-class problem.
It is required to rename the column accordingly to the expected name : `label` or `label_ids`
### Steps to reproduce the bug
```python
from datasets import TextClassification, AutoTokenized, DataCollatorWithPadding
ds_prepared = my_dataset.prepare_for_task(TextClassification(text_column='TEXT', label_column='MY_LABEL_COLUMN_1_OR_0'))
print(ds_prepared)
tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")
ds_tokenized = ds_prepared.map(lambda x: tokenizer(x['text'], truncation=True), batched=True)
print(ds_tokenized)
data_collator = DataCollatorWithPadding(tokenizer=tokenizer, return_tensors="tf")
tf_data = model.prepare_tf_dataset(ds_tokenized, shuffle=True, batch_size=16, collate_fn=data_collator)
print(tf_data)
```
### Expected behavior
Without renaming the the column, the target column is not in the final tf_data since it is not in the column name expected by the data_collator.
To correct this, we have to rename the column:
```python
ds_prepared = my_dataset.prepare_for_task(TextClassification(text_column='TEXT', label_column='MY_LABEL_COLUMN_1_OR_0')).rename_column('labels', 'label')
```
### Environment info
- `datasets` version: 2.8.0
- Platform: Linux-5.15.79.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
- Python version: 3.10.6
- PyArrow version: 10.0.1
- Pandas version: 1.5.2
- `transformers` version: 4.26.0.dev0
- Platform: Linux-5.15.79.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
- Python version: 3.10.6
- Huggingface_hub version: 0.11.1
- PyTorch version (GPU?): not installed (NA)
- Tensorflow version (GPU?): 2.11.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in> | {
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https://api.github.com/repos/huggingface/datasets/issues/6674 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6674/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6674/comments | https://api.github.com/repos/huggingface/datasets/issues/6674/events | https://github.com/huggingface/datasets/issues/6674 | 2,139,595,576 | I_kwDODunzps5_h6M4 | 6,674 | Depprcated Overview.ipynb Link to new Quickstart Notebook invalid | {
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"Good catch! Feel free to open a PR to fix the link."
] | 2024-02-16T22:51:35Z | 2024-02-25T18:48:09Z | 2024-02-25T18:48:09Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
For the dreprecated notebook found [here](https://github.com/huggingface/datasets/blob/main/notebooks/Overview.ipynb). The link to the new notebook is broken.
### Steps to reproduce the bug
Click the [Quickstart notebook](https://github.com/huggingface/notebooks/blob/main/datasets_doc/quickstart.ipynb) link in the notebook.
### Expected behavior
I believe is it suposed to link [here](https://github.com/huggingface/notebooks/blob/main/datasets_doc/en/quickstart.ipynb). That is mentioned in the readme.
### Environment info
Colab | {
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https://api.github.com/repos/huggingface/datasets/issues/6173 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6173/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6173/comments | https://api.github.com/repos/huggingface/datasets/issues/6173/events | https://github.com/huggingface/datasets/issues/6173 | 1,863,422,065 | I_kwDODunzps5vEZBx | 6,173 | Fix CI for pyarrow 13.0.0 | {
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"url": "https://api.github.com/users/lhoestq",
"user_view_type": "public"
} | [] | closed | false | null | [] | null | [] | 2023-08-23T14:11:20Z | 2023-08-25T13:06:53Z | 2023-08-25T13:06:53Z | MEMBER | null | null | {
"completed": 0,
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} | pyarrow 13.0.0 just came out
```
FAILED tests/test_formatting.py::ArrowExtractorTest::test_pandas_extractor - AssertionError: Attributes of Series are different
Attribute "dtype" are different
[left]: datetime64[us, UTC]
[right]: datetime64[ns, UTC]
```
```
FAILED tests/test_table.py::test_cast_sliced_fixed_size_array_to_features - TypeError: Couldn't cast array of type
fixed_size_list<item: int32>[3]
to
Sequence(feature=Value(dtype='int64', id=None), length=3, id=None)
```
e.g. in https://github.com/huggingface/datasets/actions/runs/5952253963/job/16143847230
first error may be related to https://github.com/apache/arrow/issues/33321
second one maybe because `feature.length * len(array) == len(array_values)` is not satisfied anymore somehow ? | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6878). 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>... | 2024-05-07T10:27:07Z | 2024-05-16T14:46:44Z | 2024-05-16T14:38:23Z | MEMBER | null | null | null | Analogously with `delete_from_hub`, this PR:
- creates the Python function `convert_to_parquet`
- makes the corresponding CLI command use that function.
This way, the functionality can be used both from a terminal and from a Python console.
This PR also implements a test for convert_to_parquet function. | {
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"On second thought, probably not a good idea."
] | 2025-02-08T14:27:55Z | 2025-02-08T14:30:10Z | 2025-02-08T14:30:09Z | NONE | null | null | {
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} | ### Feature request
This feature proposes adding a new dataset builder called bookfolder to the datasets library. This builder would allow users to easily load datasets consisting of various digital book formats, including: AZW, AZW3, CB7, CBR, CBT, CBZ, EPUB, MOBI, and PDF.
### Motivation
Currently, loading datasets of these digital book files requires manual effort. This would also lower the barrier to entry for working with these formats, enabling more diverse and interesting datasets to be used within the Hugging Face ecosystem.
### Your contribution
This feature is rather simple as it will be based on the folder-based builder, similar to imagefolder. I'm willing to contribute to this feature by submitting a PR | {
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https://api.github.com/repos/huggingface/datasets/issues/6984 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6984/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6984/comments | https://api.github.com/repos/huggingface/datasets/issues/6984/events | https://github.com/huggingface/datasets/issues/6984 | 2,362,143,554 | I_kwDODunzps6My3NC | 6,984 | Convert polars DataFrame back to datasets | {
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"Hi ! Thanks for reporting :)\r\n\r\nWe don't support `large_list` yet, though it should be added to `Sequence` IMO (maybe with a parameter `large=True` ?)"
] | 2024-06-19T11:38:48Z | 2024-08-12T14:43:46Z | 2024-08-12T14:43:46Z | NONE | null | null | {
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} | ### Feature request
This returns error.
```python
from datasets import Dataset
dsdf = Dataset.from_dict({"x": [[1, 2], [3, 4, 5]], "y": ["a", "b"]})
Dataset.from_polars(dsdf.to_polars())
```
ValueError: Arrow type large_list<item: int64> does not have a datasets dtype equivalent.
### Motivation
When datasets contain Sequence data type, it will be converted to Arrow type large_list. However, the reverse (from large_list to Sequence) does not work.
### Your contribution
No | {
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https://api.github.com/repos/huggingface/datasets/issues/4557 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4557/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4557/comments | https://api.github.com/repos/huggingface/datasets/issues/4557/events | https://github.com/huggingface/datasets/pull/4557 | 1,283,473,889 | PR_kwDODunzps46TGZK | 4,557 | Add evaluation metadata to wmt16 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4557). All of your documentation changes will be reflected on that endpoint.",
"> Just to confirm: we should add this metadata via GitHub and not Hub PRs for canonical datasets right?\r\n\r\nyes :)",
"As discussed with @lewtu... | 2022-06-24T09:04:23Z | 2023-09-24T09:35:49Z | 2022-09-23T09:36:32Z | MEMBER | null | null | null | Just to confirm: we should add this metadata via GitHub and not Hub PRs for canonical datasets right? | {
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} | CI check_code_quality is broken:
```
src/datasets/arrow_dataset.py:3267:35: C416 [*] Unnecessary `dict` comprehension (rewrite using `dict()`)
Found 1 error.
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4848 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4848/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4848/comments | https://api.github.com/repos/huggingface/datasets/issues/4848/events | https://github.com/huggingface/datasets/pull/4848 | 1,338,271,833 | PR_kwDODunzps49JNj_ | 4,848 | a | {
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https://api.github.com/repos/huggingface/datasets/issues/5927 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5927/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5927/comments | https://api.github.com/repos/huggingface/datasets/issues/5927/events | https://github.com/huggingface/datasets/issues/5927 | 1,744,009,032 | I_kwDODunzps5n83dI | 5,927 | `IndexError` when indexing `Sequence` of `Array2D` with `None` values | {
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"Easy fix would be to add:\r\n\r\n```python\r\nnull_indices -= np.arange(len(null_indices))\r\n```\r\n\r\nbefore L279, but I'm not sure it's the most intuitive way to fix it.",
"Same issue here:\r\n\r\nhttps://github.com/huggingface/datasets/blob/7fcbe5b1575c8d162b65b9397b3dfda995a4e048/src/datasets/features/feat... | 2023-06-06T14:36:22Z | 2023-06-13T12:39:39Z | 2023-06-09T13:23:50Z | MEMBER | null | null | {
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} | ### Describe the bug
Having `None` values in a `Sequence` of `ArrayND` fails.
### Steps to reproduce the bug
```python
from datasets import Array2D, Dataset, Features, Sequence
data = [
[
[[0]],
None,
None,
]
]
feature = Sequence(Array2D((1, 1), dtype="int64"))
dataset = Dataset.from_dict({"a": data}, features=Features({"a": feature}))
dataset[0] # error raised only when indexing
```
```
Traceback (most recent call last):
File "/Users/quentingallouedec/gia/c.py", line 13, in <module>
dataset[0] # error raised only when indexing
File "/Users/quentingallouedec/gia/env/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 2658, in __getitem__
return self._getitem(key)
File "/Users/quentingallouedec/gia/env/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 2643, in _getitem
formatted_output = format_table(
File "/Users/quentingallouedec/gia/env/lib/python3.10/site-packages/datasets/formatting/formatting.py", line 634, in format_table
return formatter(pa_table, query_type=query_type)
File "/Users/quentingallouedec/gia/env/lib/python3.10/site-packages/datasets/formatting/formatting.py", line 406, in __call__
return self.format_row(pa_table)
File "/Users/quentingallouedec/gia/env/lib/python3.10/site-packages/datasets/formatting/formatting.py", line 441, in format_row
row = self.python_arrow_extractor().extract_row(pa_table)
File "/Users/quentingallouedec/gia/env/lib/python3.10/site-packages/datasets/formatting/formatting.py", line 144, in extract_row
return _unnest(pa_table.to_pydict())
File "pyarrow/table.pxi", line 4146, in pyarrow.lib.Table.to_pydict
File "pyarrow/table.pxi", line 1312, in pyarrow.lib.ChunkedArray.to_pylist
File "pyarrow/array.pxi", line 1521, in pyarrow.lib.Array.to_pylist
File "pyarrow/scalar.pxi", line 675, in pyarrow.lib.ListScalar.as_py
File "/Users/quentingallouedec/gia/env/lib/python3.10/site-packages/datasets/features/features.py", line 760, in to_pylist
return self.to_numpy(zero_copy_only=zero_copy_only).tolist()
File "/Users/quentingallouedec/gia/env/lib/python3.10/site-packages/datasets/features/features.py", line 725, in to_numpy
numpy_arr = np.insert(numpy_arr.astype(np.float64), null_indices, np.nan, axis=0)
File "<__array_function__ internals>", line 200, in insert
File "/Users/quentingallouedec/gia/env/lib/python3.10/site-packages/numpy/lib/function_base.py", line 5426, in insert
old_mask[indices] = False
IndexError: index 3 is out of bounds for axis 0 with size 3
```
AFAIK, the problem only occurs when you use a `Sequence` of `ArrayND`.
I strongly suspect that the problem comes from this line, or `np.insert` is misused:
https://github.com/huggingface/datasets/blob/02ee418831aba68d0be93227bce8b3f42ef8980f/src/datasets/features/features.py#L729
To put t simply, you want something that do that:
```python
import numpy as np
numpy_arr = np.zeros((1, 1, 1))
null_indices = np.array([1, 2])
np.insert(numpy_arr, null_indices, np.nan, axis=0)
# raise an error, instead of outputting
# array([[[ 0.]],
# [[nan]],
# [[nan]]])
```
### Expected behavior
The previous code should not raise an error.
### Environment info
- Python 3.10.11
- datasets 2.10.0
- pyarrow 12.0.0 | {
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"I just noticed the [docs](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L2881C11-L2881C200) say:\r\n\r\n>If batched is `True` and `batch_size` is `n > 1`, then the function takes a batch of `n` examples as input and can return a batch with `n` examples, or with an arbitrary number... | 2023-06-29T22:15:21Z | 2023-07-03T17:58:52Z | null | NONE | null | null | {
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"total": 0
} | ### Feature request
I understand `dataset` provides a [`map`](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L2849) function. This function in turn takes in a callable that is used to tokenize the text on which a model is trained. Frequently this text will not fit within a models's context window. In this case it would be useful to wrap around the text into multiple rows with each row fitting the model's context window. I tried to do it using this code as example which in turn I have borrowed from [here](https://stackoverflow.com/a/76343993/147530):
```
data = data.map(lambda samples: tokenizer(samples["text"], max_length=tokenizer.model_max_length, truncation=True, stride=4, return_overflowing_tokens=True), batched=True)
```
but running the code gives me this error:
```
File "/llm/fine-tune.py", line 117, in <module>
data = data.map(lambda samples: tokenizer(samples["text"], max_length=tokenizer.model_max_length, truncation=True, stride=4, return_overflowing_tokens=True), batched=True)
File "/llm/.env/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 580, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/llm/.env/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 545, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/llm/.env/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3087, in map
for rank, done, content in Dataset._map_single(**dataset_kwargs):
File "/llm/.env/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3480, in _map_single
writer.write_batch(batch)
File "/llm/.env/lib/python3.9/site-packages/datasets/arrow_writer.py", line 556, in write_batch
pa_table = pa.Table.from_arrays(arrays, schema=schema)
File "pyarrow/table.pxi", line 3798, in pyarrow.lib.Table.from_arrays
File "pyarrow/table.pxi", line 2962, in pyarrow.lib.Table.validate
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 1 named input_ids expected length 394 but got length 447
```
The lambda function I have provided is correctly chopping up long text so it wraps around (and because of this 394 samples become 447 after wrap around) but the dataset `map` function does not like it.
### Motivation
please see above
### Your contribution
I'm afraid I don't have much knowledge to help | null | {
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} | _Originally [posted](https://huggingface.slack.com/archives/C02V51Q3800/p1675443873878489?thread_ts=1675418893.373479&cid=C02V51Q3800) on Slack_
Considering all this, perhaps for Datasets 3.0, we can do the following:
* [ ] have `continuous=True` by default in `.shard` (requested in the survey and makes more sense for us since it doesn't create an indices mapping)
* [x] allow calling `save_to_disk` on "unflattened" datasets
* [ ] remove "hidden" expensive calls in `save_to_disk`, `unique`, `concatenate_datasets`, etc. For instance, instead of silently calling `flatten_indices` where it's needed, it's probably better to be explicit (considering how expensive these ops can be) and raise an error instead | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4598 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4598/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4598/comments | https://api.github.com/repos/huggingface/datasets/issues/4598/events | https://github.com/huggingface/datasets/pull/4598 | 1,288,774,514 | PR_kwDODunzps46kfOS | 4,598 | Host financial_phrasebank data on the Hub | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-29T13:59:31Z | 2022-07-01T09:41:14Z | 2022-07-01T09:29:36Z | MEMBER | null | null | null |
Fix #4597. | {
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https://api.github.com/repos/huggingface/datasets/issues/6091 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6091/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6091/comments | https://api.github.com/repos/huggingface/datasets/issues/6091/events | https://github.com/huggingface/datasets/pull/6091 | 1,826,086,487 | PR_kwDODunzps5Wov9Q | 6,091 | Bump fsspec from 2021.11.1 to 2022.3.0 | {
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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... | 2023-07-28T09:37:15Z | 2023-07-28T10:16:11Z | 2023-07-28T10:07:02Z | COLLABORATOR | null | null | null | Fix https://github.com/huggingface/datasets/issues/6087
(Colab installs 2023.6.0, so we should be good) | {
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https://api.github.com/repos/huggingface/datasets/issues/7461 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7461/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7461/comments | https://api.github.com/repos/huggingface/datasets/issues/7461/events | https://github.com/huggingface/datasets/issues/7461 | 2,925,608,123 | I_kwDODunzps6uYTy7 | 7,461 | List of images behave differently on IterableDataset and Dataset | {
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"Hi ! Can you try with `datasets` ^3.4 released recently ? on my side it works with IterableDataset on the recent version :)\n\n```python\nIn [20]: def train_iterable_gen():\n ...: images = np.array(load_image(\"https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg\")... | 2025-03-17T15:59:23Z | 2025-03-18T08:57:17Z | 2025-03-18T08:57:16Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
This code:
```python
def train_iterable_gen():
images = np.array(load_image("https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg").resize((128, 128)))
yield {
"images": np.expand_dims(images, axis=0),
"messages": [
{
"role": "user",
"content": [{"type": "image", "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" }]
},
{
"role": "assistant",
"content": [{"type": "text", "text": "duck" }]
}
]
}
train_ds = Dataset.from_generator(train_iterable_gen,
features=Features({
'images': [datasets.Image(mode=None, decode=True, id=None)],
'messages': [{'content': [{'text': datasets.Value(dtype='string', id=None), 'type': datasets.Value(dtype='string', id=None) }], 'role': datasets.Value(dtype='string', id=None)}]
} )
)
```
works as I'd expect; if I iterate the dataset then the `images` column returns a `List[PIL.Image.Image]`, i.e. `'images': [<PIL.PngImagePlugin.PngImageFile image mode=RGB size=128x128 at 0x77EFB7EF4680>]`.
But if I change `Dataset` to `IterableDataset`, the `images` column changes into `'images': [{'path': None, 'bytes': ..]`
### Steps to reproduce the bug
The code above +
```python
def load_image(url):
response = requests.get(url)
image = Image.open(io.BytesIO(response.content))
return image
```
I'm feeding it to SFTTrainer
### Expected behavior
Dataset and IterableDataset would behave the same
### Environment info
```yaml
requires-python = ">=3.12"
dependencies = [
"av>=14.1.0",
"boto3>=1.36.7",
"datasets>=3.3.2",
"docker>=7.1.0",
"google-cloud-storage>=2.19.0",
"grpcio>=1.70.0",
"grpcio-tools>=1.70.0",
"moviepy>=2.1.2",
"open-clip-torch>=2.31.0",
"opencv-python>=4.11.0.86; sys_platform == 'darwin'",
"opencv-python-headless>=4.11.0.86; sys_platform == 'linux'",
"pandas>=2.2.3",
"pillow>=10.4.0",
"plotly>=6.0.0",
"py-spy>=0.4.0",
"pydantic>=2.10.6",
"pydantic-settings>=2.7.1",
"pymysql>=1.1.1",
"ray[data,default,serve,train,tune]>=2.43.0",
"torch>=2.6.0",
"torchmetrics>=1.6.1",
"torchvision>=0.21.0",
"transformers[torch]@git+https://github.com/huggingface/transformers",
"wandb>=0.19.4",
# https://github.com/Dao-AILab/flash-attention/issues/833
"flash-attn @ https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.3/flash_attn-2.7.3+cu12torch2.6cxx11abiFALSE-cp312-cp312-linux_x86_64.whl; sys_platform == 'linux'",
"trl@https://github.com/huggingface/trl.git",
"peft>=0.14.0",
]
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6297 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6297/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6297/comments | https://api.github.com/repos/huggingface/datasets/issues/6297/events | https://github.com/huggingface/datasets/pull/6297 | 1,938,752,707 | PR_kwDODunzps5ckXBa | 6,297 | Fix ArrayXD cast | {
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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... | 2023-10-11T21:14:59Z | 2023-10-13T13:54:00Z | 2023-10-13T13:45:30Z | COLLABORATOR | null | null | null | Fix #6291 | {
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https://api.github.com/repos/huggingface/datasets/issues/6990 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6990/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6990/comments | https://api.github.com/repos/huggingface/datasets/issues/6990/events | https://github.com/huggingface/datasets/issues/6990 | 2,366,660,785 | I_kwDODunzps6NEGCx | 6,990 | Problematic rank after calling `split_dataset_by_node` twice | {
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"ah yes good catch ! feel free to open a PR with your suggested fix"
] | 2024-06-21T14:25:26Z | 2024-06-25T16:19:19Z | 2024-06-25T16:19:19Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
I'm trying to split `IterableDataset` by `split_dataset_by_node`.
But when doing split on a already split dataset, the resulting `rank` is greater than `world_size`.
### Steps to reproduce the bug
Here is the minimal code for reproduction:
```py
>>> from datasets import load_dataset
>>> from datasets.distributed import split_dataset_by_node
>>> dataset = load_dataset('fla-hub/slimpajama-test', split='train', streaming=True)
>>> dataset = split_dataset_by_node(dataset, 1, 32)
>>> dataset._distributed
DistributedConfig(rank=1, world_size=32)
>>> dataset = split_dataset_by_node(dataset, 1, 15)
>>> dataset._distributed
DistributedConfig(rank=481, world_size=480)
```
As you can see, the second rank 481 > 480, which is problematic.
### Expected behavior
I think this error comes from this line @lhoestq
https://github.com/huggingface/datasets/blob/a6ccf944e42c1a84de81bf326accab9999b86c90/src/datasets/iterable_dataset.py#L2943-L2944
We may need to obtain the rank first. Then the above code gives
```py
>>> dataset._distributed
DistributedConfig(rank=16, world_size=480)
```
### Environment info
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https://api.github.com/repos/huggingface/datasets/issues/6850 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6850/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6850/comments | https://api.github.com/repos/huggingface/datasets/issues/6850/events | https://github.com/huggingface/datasets/issues/6850 | 2,269,500,624 | I_kwDODunzps6HRdTQ | 6,850 | Problem loading voxpopuli dataset | {
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"Version 2.18 works without problem.",
"@Namangarg110 @mohsen-goodarzi The bug appears because the number of urls is less than 16 and the algorithm is meant to work on the previously created mode for a single url as stated on line 314: https://github.com/huggingface/datasets/blob/1bf8a46cc7b096d5c547ea3794f6a4b6... | 2024-04-29T16:46:51Z | 2024-05-06T09:25:54Z | 2024-05-06T09:25:54Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
```
Exception has occurred: FileNotFoundError
Couldn't find file at https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/{'en': 'data/en/asr_train.tsv'}
```
Error in logic for link url creation. The link should be https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/en/asr_train.tsv
Basically there should be links directly under ```metadata["train"]```, not under ```metadata["train"][self.config.languages[0]]```
same for audio urls
### Steps to reproduce the bug
```
from datasets import load_dataset
dataset = load_dataset("facebook/voxpopuli","en")
```
### Expected behavior
Dataset should be loaded successfully.
### Environment info
- `datasets` version: 2.19.0
- Platform: Linux-5.15.0-1041-aws-x86_64-with-glibc2.31
- Python version: 3.10.13
- `huggingface_hub` version: 0.22.2
- PyArrow version: 16.0.0
- Pandas version: 2.2.0
- `fsspec` version: 2023.12.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6412 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6412/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6412/comments | https://api.github.com/repos/huggingface/datasets/issues/6412/events | https://github.com/huggingface/datasets/issues/6412 | 1,992,401,594 | I_kwDODunzps52waK6 | 6,412 | User token is printed out! | {
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"Indeed, this is not a good practice. I've opened a PR that removes the token value from the (deprecation) warning."
] | 2023-11-14T10:01:34Z | 2023-11-14T22:19:46Z | 2023-11-14T22:19:46Z | NONE | null | null | {
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https://github.com/huggingface/datasets/blob/12ebe695b4748c5a26e08b44ed51955f74f5801d/src/datasets/load.py#L2091 | {
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https://api.github.com/repos/huggingface/datasets/issues/7264 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7264/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7264/comments | https://api.github.com/repos/huggingface/datasets/issues/7264/events | https://github.com/huggingface/datasets/pull/7264 | 2,624,047,640 | PR_kwDODunzps6AYfwL | 7,264 | fix docs relative links | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7264). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2024-10-30T13:07:34Z | 2024-10-30T13:10:13Z | 2024-10-30T13:09:02Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7023 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7023/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7023/comments | https://api.github.com/repos/huggingface/datasets/issues/7023/events | https://github.com/huggingface/datasets/pull/7023 | 2,388,090,424 | PR_kwDODunzps50TDot | 7,023 | Remove dead code for pyarrow < 15.0.0 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7023). 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>... | 2024-07-03T09:05:03Z | 2024-07-03T09:24:46Z | 2024-07-03T09:17:35Z | MEMBER | null | null | null | Remove dead code for pyarrow < 15.0.0.
Code is dead since the merge of:
- #6892
Fix #7022. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7474). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"Thanks ! can you run `make style` to fix code formatting ? then we can merge",
"@lhoe... | 2025-03-25T03:08:04Z | 2025-04-16T00:11:06Z | 2025-04-15T16:07:55Z | CONTRIBUTOR | null | null | null | This PR remove conditions for Python < 3.9. | {
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https://api.github.com/repos/huggingface/datasets/issues/5522 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5522/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5522/comments | https://api.github.com/repos/huggingface/datasets/issues/5522/events | https://github.com/huggingface/datasets/pull/5522 | 1,580,183,124 | PR_kwDODunzps5JvTVp | 5,522 | Minor changes in JAX-formatting docstrings & type-hints | {
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"P.S. For more context, I'm currently exploring the integration of 🤗`datasets` with JAX, so in case you need any help or want me to try something specific just let me know! (`jnp.asarray`/`jnp.array(..., copy=False)` still no zero-copy 😭)",
"_The documentation is not available anymore as the PR was closed or me... | 2023-02-10T19:05:00Z | 2023-02-15T14:48:27Z | 2023-02-15T13:19:06Z | MEMBER | null | null | null | Hi to whoever is reading this! 🤗
## What's in this PR?
I was exploring the code regarding the `JaxFormatter` implemented in 🤗`datasets`, and found some things that IMO could be changed. Those are mainly regarding the docstrings and the type-hints based on `jax`'s 0.4.1 release where `jax.Array` was introduced as the default type for JAX-arrays (instead of `jnp.DeviceArray`, `jnp.SharedDeviceArray`, and `jnp.GlobalDeviceArray`). Even though `isinstance(..., jax.Array)` also works with lower versions such as e.g. `0.3.25`.
More information about the latter at [`jax` v0.4.1 - Release Notes](https://github.com/google/jax/releases/tag/jax-v0.4.1) and [jax.Array migration - JAX documentation](https://jax.readthedocs.io/en/latest/jax_array_migration.html).
## What's missing?
* Do you want me to write an entry in the documentation on how to use 🤗`datasets` with JAX as https://huggingface.co/docs/datasets/use_with_pytorch with PyTorch?
* Do we need to actually include `pyarrow` under the `TYPE_CHECKING` when needed? I just did it for JAX, but if we are OK with that, I can do that with the rest of the formatters, just LMK.
* Should the License header be included in `datasets.formatting.np_formatter`? If so, do I include the one from 2020 e.g. https://github.com/huggingface/datasets/blob/b065547654efa0ec633cf373ac1512884c68b2e1/src/datasets/formatting/tf_formatter.py#L1-L13
* Is there any reason why `jnp.array` is being used instead of `jnp.asarray`? There's no difference between both, just that `jnp.asarray` has `copy=False` as default, even though `numpy` to `jax.numpy` conversion is not zero-copy, but just asking :) | {
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https://api.github.com/repos/huggingface/datasets/issues/6238 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6238/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6238/comments | https://api.github.com/repos/huggingface/datasets/issues/6238/events | https://github.com/huggingface/datasets/issues/6238 | 1,895,207,828 | I_kwDODunzps5w9pOU | 6,238 | `dataset.filter` ALWAYS removes the first item from the dataset when using batched=True | {
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"`filter` treats the function's output as a (selection) mask - `True` keeps the sample, and `False` drops it. In your case, `bool(0)` evaluates to `False`, so dropping the first sample is the correct behavior.",
"Oh gosh! 🤦 I totally misunderstood the API! My apologies!"
] | 2023-09-13T20:20:37Z | 2023-09-17T07:05:07Z | 2023-09-17T07:05:07Z | NONE | null | null | {
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} | ### Describe the bug
If you call batched=True when calling `filter`, the first item is _always_ filtered out, regardless of the filter condition.
### Steps to reproduce the bug
Here's a minimal example:
```python
def filter_batch_always_true(batch, indices):
print("First index being passed into this filter function: ", indices[0])
return indices # Keep all indices
data = {"value": list(range(10))}
dataset = Dataset.from_dict(data)
filtered_dataset = dataset.filter(filter_batch_always_true, with_indices=True, batched=True)
print("Length of original dataset: ", len(dataset))
print("Length of filtered_dataset: ", len(filtered_dataset))
print("Is equal to original? ", len(filtered_dataset) == len(dataset))
print("First item of filtered dataset: ", filtered_dataset[0])
print("Last item of filtered dataset: ", filtered_dataset[-1])
```
prints:
```
First index being passed into this filter function: 0
Length of original dataset: 10
Length of filtered_dataset: 9
Is equal to original? False
First item of filtered dataset: {'value': 1}
Last item of filtered dataset: {'value': 9}
```
### Expected behavior
Filter should respect the filter condition.
### Environment info
- `datasets` version: 2.14.4
- Platform: macOS-13.5-arm64-arm-64bit
- Python version: 3.9.18
- Huggingface_hub version: 0.17.1
- PyArrow version: 10.0.1
- Pandas version: 2.0.2
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https://api.github.com/repos/huggingface/datasets/issues/6397 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6397/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6397/comments | https://api.github.com/repos/huggingface/datasets/issues/6397/events | https://github.com/huggingface/datasets/issues/6397 | 1,987,622,152 | I_kwDODunzps52eLUI | 6,397 | Raise a different exception for inexisting dataset vs files without known extension | {
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} | See https://github.com/huggingface/datasets-server/issues/2082#issuecomment-1805716557
We have the same error for:
- https://huggingface.co/datasets/severo/a_dataset_that_does_not_exist: a dataset that does not exist
- https://huggingface.co/datasets/severo/test_files_without_extension: a dataset with files without a known extension
```
>>> import datasets
>>> datasets.get_dataset_config_names('severo/a_dataset_that_does_not_exist')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1508, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at /home/slesage/hf/datasets-server/services/worker/severo/a_dataset_that_does_not_exist/a_dataset_that_does_not_exist.py or any data file in the same directory. Couldn't find 'severo/a_dataset_that_does_not_exist' on the Hugging Face Hub either: FileNotFoundError: Dataset 'severo/a_dataset_that_does_not_exist' doesn't exist on the Hub. If the repo is private or gated, make sure to log in with `huggingface-cli login`.
>>> datasets.get_dataset_config_names('severo/test_files_without_extension')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1508, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at /home/slesage/hf/datasets-server/services/worker/severo/test_files_without_extension/test_files_without_extension.py or any data file in the same directory. Couldn't find 'severo/test_files_without_extension' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in severo/test_files_without_extension.
```
To differentiate, we must parse the error message (only the end is different). We should have a different exception for these two errors. | {
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https://api.github.com/repos/huggingface/datasets/issues/6932 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6932/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6932/comments | https://api.github.com/repos/huggingface/datasets/issues/6932/events | https://github.com/huggingface/datasets/pull/6932 | 2,324,729,267 | PR_kwDODunzps5w9d7w | 6,932 | Update dataset_dict.py | {
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"thanks !",
"<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_bat... | 2024-05-30T05:22:35Z | 2024-06-04T12:56:20Z | 2024-06-04T12:50:13Z | CONTRIBUTOR | null | null | null | shape returns (number of rows, number of columns) | {
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https://api.github.com/repos/huggingface/datasets/issues/5341 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5341/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5341/comments | https://api.github.com/repos/huggingface/datasets/issues/5341/events | https://github.com/huggingface/datasets/pull/5341 | 1,484,376,644 | PR_kwDODunzps5Exohx | 5,341 | Remove tasks.json | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-12-08T11:04:35Z | 2022-12-09T12:26:21Z | 2022-12-09T12:23:20Z | MEMBER | null | null | null | After discussions in https://github.com/huggingface/datasets/pull/5335 we should remove this file that is not used anymore. We should update https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts instead. | {
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https://api.github.com/repos/huggingface/datasets/issues/5266 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5266/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5266/comments | https://api.github.com/repos/huggingface/datasets/issues/5266/events | https://github.com/huggingface/datasets/pull/5266 | 1,455,281,310 | PR_kwDODunzps5DN9BT | 5,266 | Specify arguments as keywords in librosa.reshape to avoid future errors | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-11-18T14:58:47Z | 2022-11-21T15:45:02Z | 2022-11-21T15:41:57Z | CONTRIBUTOR | null | null | null | Fixes a warning and future deprecation from `librosa.reshape`:
```
FutureWarning: Pass orig_sr=16000, target_sr=48000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6979 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6979/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6979/comments | https://api.github.com/repos/huggingface/datasets/issues/6979/events | https://github.com/huggingface/datasets/issues/6979 | 2,360,175,363 | I_kwDODunzps6MrWsD | 6,979 | How can I load partial parquet files only? | {
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"Hello,\r\n\r\nHave you tried loading the dataset in streaming mode? [Documentation](https://huggingface.co/docs/datasets/v2.20.0/stream)\r\n\r\nThis way you wouldn't have to load it all. Also, let's be nice to Parquet, it's a really nice technology and we don't need to be mean :)",
"I have downloaded part of it,... | 2024-06-18T15:44:16Z | 2024-06-21T17:09:32Z | 2024-06-21T13:32:50Z | NONE | null | null | {
"completed": 0,
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} | I have a HUGE dataset about 14TB, I unable to download all parquet all. I just take about 100 from it.
dataset = load_dataset("xx/", data_files="data/train-001*-of-00314.parquet")
How can I just using 000 - 100 from a 00314 from all partially?
I search whole net didn't found a solution, **this is stupid if they didn't support it, and I swear I wont using stupid parquet any more**
| {
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https://api.github.com/repos/huggingface/datasets/issues/6527 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6527/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6527/comments | https://api.github.com/repos/huggingface/datasets/issues/6527/events | https://github.com/huggingface/datasets/pull/6527 | 2,053,966,748 | PR_kwDODunzps5ip2vd | 6,527 | Release: 2.16.0 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6527). 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>... | 2023-12-22T13:59:56Z | 2023-12-22T14:24:12Z | 2023-12-22T14:17:55Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7357 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7357/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7357/comments | https://api.github.com/repos/huggingface/datasets/issues/7357/events | https://github.com/huggingface/datasets/issues/7357 | 2,770,456,127 | I_kwDODunzps6lIc4_ | 7,357 | Python process aborded with GIL issue when using image dataset | {
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} | [] | open | false | null | [] | null | [
"The issue seems to come from `pyarrow`, I opened an issue on their side at https://github.com/apache/arrow/issues/45214"
] | 2025-01-06T11:29:30Z | 2025-03-08T15:59:36Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
The issue is visible only with the latest `datasets==3.2.0`.
When using image dataset the Python process gets aborted right before the exit with the following error:
```
Fatal Python error: PyGILState_Release: thread state 0x7fa1f409ade0 must be current when releasing
Python runtime state: finalizing (tstate=0x0000000000ad2958)
Thread 0x00007fa33d157740 (most recent call first):
<no Python frame>
Extension modules: numpy.core._multiarray_umath, numpy.core._multiarray_tests, numpy.linalg._umath_linalg, numpy.fft._pocketfft_internal, numpy.random._common, numpy.random.bit_generator, numpy.random._boun
ded_integers, numpy.random._mt19937, numpy.random.mtrand, numpy.random._philox, numpy.random._pcg64, numpy.random._sfc64, numpy.random._generator, pyarrow.lib, pandas._libs.tslibs.ccalendar, pandas._libs.ts
libs.np_datetime, pandas._libs.tslibs.dtypes, pandas._libs.tslibs.base, pandas._libs.tslibs.nattype, pandas._libs.tslibs.timezones, pandas._libs.tslibs.fields, pandas._libs.tslibs.timedeltas, pandas._libs.t
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reprocessing._target_encoder_fast, sklearn.metrics._dist_metrics, sklearn.metrics._pairwise_distances_reduction._datasets_pair, sklearn.utils._cython_blas, sklearn.metrics._pairwise_distances_reduction._bas
e, sklearn.metrics._pairwise_distances_reduction._middle_term_computer, sklearn.utils._heap, sklearn.utils._sorting, sklearn.metrics._pairwise_distances_reduction._argkmin, sklearn.metrics._pairwise_distanc
es_reduction._argkmin_classmode, sklearn.utils._vector_sentinel, sklearn.metrics._pairwise_distances_reduction._radius_neighbors, sklearn.metrics._pairwise_distances_reduction._radius_neighbors_classmode, s
klearn.metrics._pairwise_fast, PIL._imagingft, google._upb._message, h5py._errors, h5py.defs, h5py._objects, h5py.h5, h5py.utils, h5py.h5t, h5py.h5s, h5py.h5ac, h5py.h5p, h5py.h5r, h5py._proxy, h5py._conv,
h5py.h5z, h5py.h5a, h5py.h5d, h5py.h5ds, h5py.h5g, h5py.h5i, h5py.h5o, h5py.h5f, h5py.h5fd, h5py.h5pl, h5py.h5l, h5py._selector, _cffi_backend, pyarrow._parquet, pyarrow._fs, pyarrow._azurefs, pyarrow._hdfs
, pyarrow._gcsfs, pyarrow._s3fs, multidict._multidict, propcache._helpers_c, yarl._quoting_c, aiohttp._helpers, aiohttp._http_writer, aiohttp._http_parser, aiohttp._websocket, frozenlist._frozenlist, xxhash
._xxhash, pyarrow._json, pyarrow._acero, pyarrow._csv, pyarrow._dataset, pyarrow._dataset_orc, pyarrow._parquet_encryption, pyarrow._dataset_parquet_encryption, pyarrow._dataset_parquet, regex._regex, scipy
.io.matlab._mio_utils, scipy.io.matlab._streams, scipy.io.matlab._mio5_utils, PIL._imagingmath, PIL._webp (total: 236)
Aborted (core dumped)
```an
### Steps to reproduce the bug
Install `datasets==3.2.0`
Run the following script:
```python
import datasets
DATASET_NAME = "phiyodr/InpaintCOCO"
NUM_SAMPLES = 10
def preprocess_fn(example):
return {
"prompts": example["inpaint_caption"],
"images": example["coco_image"],
"masks": example["mask"],
}
default_dataset = datasets.load_dataset(
DATASET_NAME, split="test", streaming=True
).filter(lambda example: example["inpaint_caption"] != "").take(NUM_SAMPLES)
test_data = default_dataset.map(
lambda x: preprocess_fn(x), remove_columns=default_dataset.column_names
)
for data in test_data:
print(data["prompts"])
``
### Expected behavior
The script should not hang or crash.
### Environment info
- `datasets` version: 3.2.0
- Platform: Linux-5.15.0-50-generic-x86_64-with-glibc2.31
- Python version: 3.11.0
- `huggingface_hub` version: 0.25.1
- PyArrow version: 17.0.0
- Pandas version: 2.2.3
- `fsspec` version: 2024.2.0 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4977 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4977/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4977/comments | https://api.github.com/repos/huggingface/datasets/issues/4977/events | https://github.com/huggingface/datasets/issues/4977 | 1,372,962,157 | I_kwDODunzps5R1b1t | 4,977 | Providing dataset size | {
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"description": "New feature or request",
"id": 1935892871,
"name": "enhancement",
"node_id": "MDU6TGFiZWwxOTM1ODkyODcx",
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"Hi @sashavor, thanks for your suggestion.\r\n\r\nUntil now we have the CLI command \r\n```\r\ndatasets-cli test datasets/<your-dataset-folder> --save_infos --all_configs\r\n```\r\nthat generates the `dataset_infos.json` with the size of the downloaded dataset, among other information.\r\n\r\nWe are currently in th... | 2022-09-14T13:09:27Z | 2022-09-15T16:03:58Z | null | CONTRIBUTOR | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | **Is your feature request related to a problem? Please describe.**
Especially for big datasets like [LAION](https://huggingface.co/datasets/laion/laion2B-en/), it's hard to know exactly the downloaded size (because there are many files and you don't have their exact size when downloaded).
**Describe the solution you'd like**
Auto-populating the downloaded dataset size on the dataset page would be really useful, including that of each split (when there are some).
**Describe alternatives you've considered**
People should be adding this to dataset cards, but I don't think that is systematically the case :slightly_smiling_face:
**Additional context**
Mentioned to @lhoestq
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https://api.github.com/repos/huggingface/datasets/issues/6708 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6708/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6708/comments | https://api.github.com/repos/huggingface/datasets/issues/6708/events | https://github.com/huggingface/datasets/pull/6708 | 2,164,158,579 | PR_kwDODunzps5oczmi | 6,708 | Release: 2.18.0 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6708). 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>... | 2024-03-01T20:52:17Z | 2024-03-01T21:03:01Z | 2024-03-01T20:56:50Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6722 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6722/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6722/comments | https://api.github.com/repos/huggingface/datasets/issues/6722/events | https://github.com/huggingface/datasets/pull/6722 | 2,174,332,127 | PR_kwDODunzps5o_ch0 | 6,722 | Add details in docstring | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6722). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2024-03-07T17:02:07Z | 2024-03-07T17:21:10Z | 2024-03-07T17:21:08Z | COLLABORATOR | null | null | null | see https://github.com/huggingface/datasets-server/pull/2554#discussion_r1516516867 | {
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https://api.github.com/repos/huggingface/datasets/issues/6208 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6208/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6208/comments | https://api.github.com/repos/huggingface/datasets/issues/6208/events | https://github.com/huggingface/datasets/pull/6208 | 1,879,572,646 | PR_kwDODunzps5ZcnpJ | 6,208 | Do not filter out .zip extensions from no-script datasets | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-09-04T06:07:12Z | 2023-09-04T09:22:19Z | 2023-09-04T09:13:32Z | MEMBER | null | null | null | This PR is a hotfix of:
- #6207
That PR introduced the filtering out of `.zip` extensions. This PR reverts that.
Hot fix #6207.
Maybe we should do patch releases: the bug was introduced in 2.13.1.
CC: @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/5846 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5846/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5846/comments | https://api.github.com/repos/huggingface/datasets/issues/5846/events | https://github.com/huggingface/datasets/issues/5846 | 1,706,289,290 | I_kwDODunzps5ls-iK | 5,846 | load_dataset('bigcode/the-stack-dedup', streaming=True) very slow! | {
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"This is due to the slow resolution of the data files: https://github.com/huggingface/datasets/issues/5537.\r\n\r\nWe plan to switch to `huggingface_hub`'s `HfFileSystem` soon to make the resolution faster (will be up to 20x faster once we merge https://github.com/huggingface/huggingface_hub/pull/1443)\r\n\r\n",
... | 2023-05-11T17:58:57Z | 2024-04-08T12:53:17Z | 2024-04-05T12:28:58Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Running
```
import datasets
ds = datasets.load_dataset('bigcode/the-stack-dedup', streaming=True)
```
takes about 2.5 minutes!
I would expect this to be near instantaneous. With other datasets, the runtime is one or two seconds.
### Environment info
- `datasets` version: 2.11.0
- Platform: macOS-13.3.1-arm64-arm-64bit
- Python version: 3.10.10
- Huggingface_hub version: 0.13.4
- PyArrow version: 11.0.0
- Pandas version: 2.0.0 | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-10-25T18:21:08Z | 2023-10-26T17:19:49Z | 2023-10-26T17:10:27Z | CONTRIBUTOR | null | null | null | The current example isn't working because it can't find `labels` inside the Dataset object. So I've added an extra step to the process. Tested and working in Colab. | {
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https://api.github.com/repos/huggingface/datasets/issues/5233 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5233/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5233/comments | https://api.github.com/repos/huggingface/datasets/issues/5233/events | https://github.com/huggingface/datasets/pull/5233 | 1,447,906,868 | PR_kwDODunzps5C1JVh | 5,233 | Fix shards in IterableDataset.from_generator | {
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] | 2022-12-08T00:17:53Z | 2022-12-08T19:33:14Z | 2022-12-08T19:30:10Z | MEMBER | null | null | null | This PR cleans up the docstrings for `DatasetInfo` and about half of the methods in `Dataset`. | {
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I also fixed a warning message by not using format_type= in with_format() | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6963). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"ci failures are r-unrelated to this PR, merging",
"<details>\n<summary>Show benchmark... | 2024-06-10T15:51:56Z | 2024-06-28T09:53:11Z | 2024-06-28T09:46:52Z | MEMBER | null | null | null | reported in https://discuss.huggingface.co/t/speeding-up-streaming-of-large-datasets-fineweb/90714/6 when training using a streaming a dataloader
cc @Wauplin it looks like the retries from `hfh` are not always enough. In this PR I let `datasets` do additional retries (that users can configure in `datasets.config`) since I couldn't find an easy way to increase the max_retries for `hfh` users in general. | {
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https://api.github.com/repos/huggingface/datasets/issues/4621 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4621/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4621/comments | https://api.github.com/repos/huggingface/datasets/issues/4621/events | https://github.com/huggingface/datasets/issues/4621 | 1,293,030,128 | I_kwDODunzps5NEhLw | 4,621 | ImageFolder raises an error with parameters drop_metadata=True and drop_labels=False when metadata.jsonl is present | {
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"following_url": "https://api.github.com/users/polinaeterna/following{/other_use... | null | [] | 2022-07-04T11:21:44Z | 2022-07-15T14:24:24Z | 2022-07-15T14:24:24Z | CONTRIBUTOR | null | null | {
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} | ## Describe the bug
If you pass `drop_metadata=True` and `drop_labels=False` when a `data_dir` contains at least one `matadata.jsonl` file, you will get a KeyError. This is probably not a very useful case but we shouldn't get an error anyway. Asking users to move metadata files manually outside `data_dir` or pass features manually (when there is a tool that can infer them automatically) don't look like a good idea to me either.
## Steps to reproduce the bug
### Clone an example dataset from the Hub
```bash
git clone https://huggingface.co/datasets/nateraw/test-imagefolder-metadata
```
### Try to load it
```python
from datasets import load_dataset
ds = load_dataset("test-imagefolder-metadata", drop_metadata=True, drop_labels=False)
```
or even just
```python
ds = load_dataset("test-imagefolder-metadata", drop_metadata=True)
```
as `drop_labels=False` is a default value.
## Expected results
A DatasetDict object with two features: `"image"` and `"label"`.
## Actual results
```
Traceback (most recent call last):
File "/home/polina/workspace/datasets/debug.py", line 18, in <module>
ds = load_dataset(
File "/home/polina/workspace/datasets/src/datasets/load.py", line 1732, in load_dataset
builder_instance.download_and_prepare(
File "/home/polina/workspace/datasets/src/datasets/builder.py", line 704, in download_and_prepare
self._download_and_prepare(
File "/home/polina/workspace/datasets/src/datasets/builder.py", line 1227, in _download_and_prepare
super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos)
File "/home/polina/workspace/datasets/src/datasets/builder.py", line 793, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/polina/workspace/datasets/src/datasets/builder.py", line 1218, in _prepare_split
example = self.info.features.encode_example(record)
File "/home/polina/workspace/datasets/src/datasets/features/features.py", line 1596, in encode_example
return encode_nested_example(self, example)
File "/home/polina/workspace/datasets/src/datasets/features/features.py", line 1165, in encode_nested_example
{
File "/home/polina/workspace/datasets/src/datasets/features/features.py", line 1165, in <dictcomp>
{
File "/home/polina/workspace/datasets/src/datasets/utils/py_utils.py", line 249, in zip_dict
yield key, tuple(d[key] for d in dicts)
File "/home/polina/workspace/datasets/src/datasets/utils/py_utils.py", line 249, in <genexpr>
yield key, tuple(d[key] for d in dicts)
KeyError: 'label'
```
## Environment info
`datasets` master branch
- `datasets` version: 2.3.3.dev0
- Platform: Linux-5.14.0-1042-oem-x86_64-with-glibc2.17
- Python version: 3.8.12
- PyArrow version: 6.0.1
- Pandas version: 1.4.1
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https://api.github.com/repos/huggingface/datasets/issues/5949 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5949/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5949/comments | https://api.github.com/repos/huggingface/datasets/issues/5949/events | https://github.com/huggingface/datasets/pull/5949 | 1,754,843,717 | PR_kwDODunzps5S4oPC | 5,949 | Replace metadata utils with `huggingface_hub`'s RepoCard API | {
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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... | 2023-06-13T13:03:19Z | 2023-06-27T16:47:51Z | 2023-06-27T16:38:32Z | COLLABORATOR | null | null | null | Use `huggingface_hub`'s RepoCard API instead of `DatasetMetadata` for modifying the card's YAML, and deprecate `datasets.utils.metadata` and `datasets.utils.readme`.
After removing these modules, we can also delete `datasets.utils.resources` since the moon landing repo now stores its own version of these resources for the metadata UI.
PS: this change requires bumping `huggingface_hub` to 0.13.0 (Transformers requires 0.14.0, so should be ok) | {
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https://api.github.com/repos/huggingface/datasets/issues/6656 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6656/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6656/comments | https://api.github.com/repos/huggingface/datasets/issues/6656/events | https://github.com/huggingface/datasets/issues/6656 | 2,127,338,377 | I_kwDODunzps5-zJuJ | 6,656 | Error when loading a big local json file | {
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"I get similar when dealing with a large jsonl file (6k lines), \r\n\r\n> TypeError: Couldn't cast array of type timestamp[us] to null\r\n\r\nYet when I split it into 1k lines, files, load_dataset works fine!\r\n\r\nhttps://github.com/huggingface/course/issues/692\r\n\r\n",
"What's the proposed solution? :-)"
] | 2024-02-09T15:14:21Z | 2024-11-29T10:06:57Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
When trying to load big json files from a local directory, `load_dataset` throws the following error
```
Traceback (most recent call last):
File "/miniconda3/envs/conda-env/lib/python3.10/site-packages/datasets/builder.py", line 1989, in _prepare_split_single
writer.write_table(table)
File "miniconda3/envs/conda-env/lib/python3.10/site-packages/datasets/arrow_writer.py", line 573, in write_table
pa_table = pa_table.combine_chunks()
File "pyarrow/table.pxi", line 3638, in pyarrow.lib.Table.combine_chunks
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: offset overflow while concatenating arrays
```
### Steps to reproduce the bug
1. Download a big file, e.g. `https://dl.fbaipublicfiles.com/dpr/data/retriever/biencoder-nq-train.json.gz`
2. Load it like `data = load_dataset("json", data_files=["nq-train.json"], split="train")`
```python
from datasets import load_dataset
data = load_dataset("json", data_files=["nq-train.json"], split="train")
```
A similarly formatted but smaller file, e.g. e.g. `https://dl.fbaipublicfiles.com/dpr/data/retriever/biencoder-nq-dev.json.gz` is loaded without issues
```python
from datasets import load_dataset
data = load_dataset("json", data_files=["nq-dev.json"], split="train")
```
### Expected behavior
It should load normally
### Environment info
- `datasets` version: 2.16.1
- Platform: Linux-5.18.10-76051810-generic-x86_64-with-glibc2.31
- Python version: 3.10.13
- `huggingface_hub` version: 0.20.3
- PyArrow version: 15.0.0
- Pandas version: 2.2.0
- `fsspec` version: 2023.10.0 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6692 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6692/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6692/comments | https://api.github.com/repos/huggingface/datasets/issues/6692/events | https://github.com/huggingface/datasets/pull/6692 | 2,152,270,987 | PR_kwDODunzps5n0XN1 | 6,692 | Enhancement: Enable loading TSV files in load_dataset() | {
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"Hi @harsh1504660,\r\n\r\nThanks for your work, but this functionality already exists. See my comment in the corresponding issue: https://github.com/huggingface/datasets/issues/6691#issuecomment-1963449923\r\n\r\nNext time you would like to contribute, I would suggest you take on an issue that is previously validat... | 2024-02-24T11:38:59Z | 2024-02-26T15:33:50Z | 2024-02-26T07:14:03Z | NONE | null | null | null | Fix #6691 | {
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https://api.github.com/repos/huggingface/datasets/issues/4779 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4779/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4779/comments | https://api.github.com/repos/huggingface/datasets/issues/4779/events | https://github.com/huggingface/datasets/issues/4779 | 1,325,997,225 | I_kwDODunzps5PCRyp | 4,779 | Loading natural_questions requires apache_beam even with existing preprocessed data | {
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"completed": 0,
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} | ## Describe the bug
When loading "natural_questions", the package "apache_beam" is required:
```
ImportError: To be able to use natural_questions, you need to install the following dependency: apache_beam.
Please install it using 'pip install apache_beam' for instance'
```
This requirement is unnecessary, once there exists preprocessed data and the script just needs to download it.
## Steps to reproduce the bug
```python
load_dataset("natural_questions", "dev", split="validation", revision="main")
```
## Expected results
No ImportError raised.
## Actual results
```
ImportError Traceback (most recent call last)
[<ipython-input-3-c938e7c05d02>](https://localhost:8080/#) in <module>()
----> 1 from datasets import load_dataset; ds = load_dataset("natural_questions", "dev", split="validation", revision="main")
[/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, **config_kwargs)
1732 revision=revision,
1733 use_auth_token=use_auth_token,
-> 1734 **config_kwargs,
1735 )
1736
[/usr/local/lib/python3.7/dist-packages/datasets/load.py](https://localhost:8080/#) in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, **config_kwargs)
1504 download_mode=download_mode,
1505 data_dir=data_dir,
-> 1506 data_files=data_files,
1507 )
1508
[/usr/local/lib/python3.7/dist-packages/datasets/load.py](https://localhost:8080/#) in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)
1245 f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}"
1246 ) from None
-> 1247 raise e1 from None
1248 else:
1249 raise FileNotFoundError(
[/usr/local/lib/python3.7/dist-packages/datasets/load.py](https://localhost:8080/#) in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)
1180 download_config=download_config,
1181 download_mode=download_mode,
-> 1182 dynamic_modules_path=dynamic_modules_path,
1183 ).get_module()
1184 elif path.count("/") == 1: # community dataset on the Hub
[/usr/local/lib/python3.7/dist-packages/datasets/load.py](https://localhost:8080/#) in get_module(self)
490 base_path=hf_github_url(path=self.name, name="", revision=revision),
491 imports=imports,
--> 492 download_config=self.download_config,
493 )
494 additional_files = [(config.DATASETDICT_INFOS_FILENAME, dataset_infos_path)] if dataset_infos_path else []
[/usr/local/lib/python3.7/dist-packages/datasets/load.py](https://localhost:8080/#) in _download_additional_modules(name, base_path, imports, download_config)
214 _them_str = "them" if len(needs_to_be_installed) > 1 else "it"
215 raise ImportError(
--> 216 f"To be able to use {name}, you need to install the following {_depencencies_str}: "
217 f"{', '.join(needs_to_be_installed)}.\nPlease install {_them_str} using 'pip install "
218 f"{' '.join(needs_to_be_installed.values())}' for instance'"
ImportError: To be able to use natural_questions, you need to install the following dependency: apache_beam.
Please install it using 'pip install apache_beam' for instance'
```
## Environment info
Colab notebook.
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https://api.github.com/repos/huggingface/datasets/issues/7452 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7452/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7452/comments | https://api.github.com/repos/huggingface/datasets/issues/7452/events | https://github.com/huggingface/datasets/pull/7452 | 2,920,354,783 | PR_kwDODunzps6Orhw4 | 7,452 | minor docs changes | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7452). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-03-14T14:14:04Z | 2025-03-14T14:16:38Z | 2025-03-14T14:14:20Z | MEMBER | null | null | null | before the release | {
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https://api.github.com/repos/huggingface/datasets/issues/6554 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6554/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6554/comments | https://api.github.com/repos/huggingface/datasets/issues/6554/events | https://github.com/huggingface/datasets/issues/6554 | 2,063,839,916 | I_kwDODunzps57A7Ks | 6,554 | Parquet exports are used even if revision is passed | {
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"I don't think this bug is a thing ? Do you have some code that leads to this issue ?"
] | 2024-01-03T11:32:26Z | 2024-02-02T10:35:29Z | 2024-02-02T10:35:29Z | MEMBER | null | null | {
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I think this is a regression. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-12T18:08:24Z | 2022-09-13T13:51:08Z | 2022-09-13T13:48:45Z | COLLABORATOR | null | null | null | Currently, if the `input_columns` list in `Dataset.map` is specified, the columns not in that list are dropped after the `map` transform.
This makes the behavior inconsistent with `IterableDataset.map`.
(It seems this issue was introduced by mistake in https://github.com/huggingface/datasets/pull/2246)
Fix https://github.com/huggingface/datasets/issues/4858 | {
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https://api.github.com/repos/huggingface/datasets/issues/7535 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7535/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7535/comments | https://api.github.com/repos/huggingface/datasets/issues/7535/events | https://github.com/huggingface/datasets/pull/7535 | 3,018,289,872 | PR_kwDODunzps6T0lm3 | 7,535 | Change dill version in requirements | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7535). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-04-24T19:44:28Z | 2025-04-25T09:31:44Z | null | NONE | null | null | null | Change dill version to >=0.3.9,<0.4.5 and check for errors | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6534 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6534/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6534/comments | https://api.github.com/repos/huggingface/datasets/issues/6534/events | https://github.com/huggingface/datasets/issues/6534 | 2,056,002,548 | I_kwDODunzps56jBv0 | 6,534 | How to configure multiple folders in the same zip package | {
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"@albertvillanova"
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train floder and test floder in data.zip | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5054 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5054/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5054/comments | https://api.github.com/repos/huggingface/datasets/issues/5054/events | https://github.com/huggingface/datasets/pull/5054 | 1,394,152,728 | PR_kwDODunzps5ABnd3 | 5,054 | Fix license/citation information of squadshifts dataset card | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-10-03T05:19:13Z | 2022-10-03T09:26:49Z | 2022-10-03T09:24:30Z | MEMBER | null | null | null | This PR fixes the license/citation information of squadshifts dataset card, once the dataset owners have responded to our request for information:
- https://github.com/modestyachts/squadshifts-website/issues/1
Additionally, we have updated the mention in their website to our `datasets` library (they were referring old name `nlp`):
- https://github.com/modestyachts/squadshifts-website/pull/2#event-7500953009 | {
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https://api.github.com/repos/huggingface/datasets/issues/6447 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6447/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6447/comments | https://api.github.com/repos/huggingface/datasets/issues/6447/events | https://github.com/huggingface/datasets/issues/6447 | 2,008,195,298 | I_kwDODunzps53sqDi | 6,447 | Support one dataset loader per config when using YAML | {
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} | ### Feature request
See https://huggingface.co/datasets/datasets-examples/doc-unsupported-1
I would like to use CSV loader for the "csv" config, JSONL loader for the "jsonl" config, etc.
### Motivation
It would be more flexible for the users
### Your contribution
No specific contribution | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5895 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5895/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5895/comments | https://api.github.com/repos/huggingface/datasets/issues/5895/events | https://github.com/huggingface/datasets/issues/5895 | 1,725,467,252 | I_kwDODunzps5m2Ip0 | 5,895 | The dir name and split strings are confused when loading ArmelR/stack-exchange-instruction dataset | {
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"Thanks for reporting, @DongHande.\r\n\r\nI think the issue is caused by the metadata in the dataset card: in the header of the `README.md`, they state that the dataset has 4 splits (\"finetune\", \"reward\", \"rl\", \"evaluation\"). \r\n```yaml\r\n splits:\r\n - name: finetune\r\n num_bytes: 6674567576\r\... | 2023-05-25T09:39:06Z | 2023-05-29T02:32:12Z | 2023-05-29T02:32:12Z | NONE | null | null | {
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} | ### Describe the bug
When I load the ArmelR/stack-exchange-instruction dataset, I encounter a bug that may be raised by confusing the dir name string and the split string about the dataset.
When I use the script "datasets.load_dataset('ArmelR/stack-exchange-instruction', data_dir="data/finetune", split="train", use_auth_token=True)", it fails. But it succeeds when I add the "streaming = True" parameter.
The website of the dataset is https://huggingface.co/datasets/ArmelR/stack-exchange-instruction/ .
The traceback logs are as below:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/load.py", line 1797, in load_dataset
builder_instance.download_and_prepare(
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/builder.py", line 890, in download_and_prepare
self._download_and_prepare(
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/builder.py", line 985, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/builder.py", line 1706, in _prepare_split
split_info = self.info.splits[split_generator.name]
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/splits.py", line 530, in __getitem__
instructions = make_file_instructions(
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/arrow_reader.py", line 112, in make_file_instructions
name2filenames = {
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/arrow_reader.py", line 113, in <dictcomp>
info.name: filenames_for_dataset_split(
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/naming.py", line 70, in filenames_for_dataset_split
prefix = filename_prefix_for_split(dataset_name, split)
File "/home/xxx/miniconda3/envs/code/lib/python3.9/site-packages/datasets/naming.py", line 54, in filename_prefix_for_split
if os.path.basename(name) != name:
File "/home/xxx/miniconda3/envs/code/lib/python3.9/posixpath.py", line 142, in basename
p = os.fspath(p)
TypeError: expected str, bytes or os.PathLike object, not NoneType
### Steps to reproduce the bug
1. import datasets library function: ```from datasets import load_dataset```
2. load dataset: ```ds=load_dataset('ArmelR/stack-exchange-instruction', data_dir="data/finetune", split="train", use_auth_token=True)```
### Expected behavior
The dataset can be loaded successfully without the streaming setting.
### Environment info
Linux,
python=3.9
datasets=2.12.0 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-10-06T01:39:35Z | 2022-10-07T14:35:43Z | 2022-10-07T14:33:10Z | CONTRIBUTOR | null | null | null | Closes #5074
Replaces `AssertionError` in the following files with more descriptive exceptions:
- `src/datasets/arrow_reader.py`
- `src/datasets/builder.py`
- `src/datasets/utils/version.py`
The issue listed more files that needed to be fixed, but the rest of them were contained in the top-level `datasets` directory, which was removed when #4974 was merged | {
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https://api.github.com/repos/huggingface/datasets/issues/7478 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7478/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7478/comments | https://api.github.com/repos/huggingface/datasets/issues/7478/events | https://github.com/huggingface/datasets/pull/7478 | 2,948,993,461 | PR_kwDODunzps6QLPe3 | 7,478 | update fsspec 2025.3.0 | {
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"Sorry for tagging you @lhoestq but since you merged the linked PR, I wondered if you might be able to help me get this triaged so it can be reviewed/rejected etc. 🙏🏼 ",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7478). All of your documentation changes will be reflec... | 2025-03-26T09:53:05Z | 2025-03-28T19:15:54Z | 2025-03-28T15:51:55Z | CONTRIBUTOR | null | null | null | It appears there have been two releases of fsspec since this dependency was last updated, it would be great if Datasets could be updated so that it didn't hold back the usage of newer fsspec versions in consuming projects.
PR based on https://github.com/huggingface/datasets/pull/7352 | {
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https://api.github.com/repos/huggingface/datasets/issues/5750 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5750/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5750/comments | https://api.github.com/repos/huggingface/datasets/issues/5750/events | https://github.com/huggingface/datasets/issues/5750 | 1,668,289,067 | I_kwDODunzps5jcBIr | 5,750 | Fail to create datasets from a generator when using Google Big Query | {
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"`from_generator` expects a generator function, not a generator object, so this should work:\r\n```python\r\nfrom datasets import Dataset\r\nfrom google.cloud import bigquery\r\n\r\nclient = bigquery.Client()\r\n\r\ndef gen()\r\n # Perform a query.\r\n QUERY = (\r\n 'SELECT name FROM `bigquery-public-d... | 2023-04-14T13:50:59Z | 2023-04-17T12:20:43Z | 2023-04-17T12:20:43Z | NONE | null | null | {
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} | ### Describe the bug
Creating a dataset from a generator using `Dataset.from_generator()` fails if the generator is the [Google Big Query Python client](https://cloud.google.com/python/docs/reference/bigquery/latest). The problem is that the Big Query client is not pickable. And the function `create_config_id` tries to get a hash of the generator by pickling it. So the following error is generated:
```
_pickle.PicklingError: Pickling client objects is explicitly not supported.
Clients have non-trivial state that is local and unpickleable.
```
### Steps to reproduce the bug
1. Install the big query client and datasets `pip install google-cloud-bigquery datasets`
2. Run the following code:
```py
from datasets import Dataset
from google.cloud import bigquery
client = bigquery.Client()
# Perform a query.
QUERY = (
'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` '
'WHERE state = "TX" '
'LIMIT 100')
query_job = client.query(QUERY) # API request
rows = query_job.result() # Waits for query to finish
ds = Dataset.from_generator(rows)
for r in ds:
print(r)
```
### Expected behavior
Two options:
1. Ignore the pickle errors when computing the hash
2. Provide a scape hutch so that we can avoid calculating the hash for the generator. For example, allowing to provide a hash from the user.
### Environment info
python 3.9
google-cloud-bigquery 3.9.0
datasets 2.11.0
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https://api.github.com/repos/huggingface/datasets/issues/4945 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4945/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4945/comments | https://api.github.com/repos/huggingface/datasets/issues/4945/events | https://github.com/huggingface/datasets/issues/4945 | 1,364,691,096 | I_kwDODunzps5RV4iY | 4,945 | Push to hub can push splits that do not respect the regex | {
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"completed": 0,
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} | ## Describe the bug
The `push_to_hub` method can push splits that do not respect the regex check that is used for downloads. Therefore, splits may be pushed but never re-used, which can be painful if the split was done after runtime preprocessing.
## Steps to reproduce the bug
```python
>>> from datasets import Dataset, DatasetDict, load_dataset
>>> d = Dataset.from_dict({'x': [1,2,3], 'y': [1,2,3]})
>>> di = DatasetDict()
>>> di['identifier-with-column'] = d
>>> di.push_to_hub('open-source-metrics/test')
Pushing split identifier-with-column to the Hub.
Pushing dataset shards to the dataset hub: 100%|██████████| 1/1 [00:04<00:00, 4.40s/it]
```
Loading it afterwards:
```python
>>> load_dataset('open-source-metrics/test')
Downloading: 100%|██████████| 610/610 [00:00<00:00, 432kB/s]
Using custom data configuration open-source-metrics--test-28b63ec7cde80488
Downloading and preparing dataset None/None (download: 950 bytes, generated: 48 bytes, post-processed: Unknown size, total: 998 bytes) to /home/lysandre/.cache/huggingface/datasets/open-source-metrics___parquet/open-source-metrics--test-28b63ec7cde80488/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec...
Downloading data files: 0%| | 0/1 [00:00<?, ?it/s]
Downloading data: 100%|██████████| 950/950 [00:00<00:00, 1.01MB/s]
Downloading data files: 100%|██████████| 1/1 [00:01<00:00, 1.48s/it]
Extracting data files: 100%|██████████| 1/1 [00:00<00:00, 2291.97it/s]
Traceback (most recent call last):
File "/home/lysandre/.pyenv/versions/3.10.6/lib/python3.10/code.py", line 90, in runcode
exec(code, self.locals)
File "<input>", line 1, in <module>
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/load.py", line 1746, in load_dataset
builder_instance.download_and_prepare(
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/builder.py", line 704, in download_and_prepare
self._download_and_prepare(
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/builder.py", line 771, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/packaged_modules/parquet/parquet.py", line 48, in _split_generators
splits.append(datasets.SplitGenerator(name=split_name, gen_kwargs={"files": files}))
File "<string>", line 5, in __init__
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/splits.py", line 599, in __post_init__
NamedSplit(self.name) # check that it's a valid split name
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/splits.py", line 346, in __init__
raise ValueError(f"Split name should match '{_split_re}' but got '{split_name}'.")
ValueError: Split name should match '^\w+(\.\w+)*$' but got 'identifier-with-column'.
```
## Expected results
I would expect `push_to_hub` to stop me in my tracks if trying to upload a split that will not be working afterwards.
## Actual results
See above
## Environment info
- `datasets` version: 2.4.0
- Platform: Linux-5.15.64-1-lts-x86_64-with-glibc2.36
- Python version: 3.10.6
- PyArrow version: 9.0.0
- Pandas version: 1.4.4
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https://api.github.com/repos/huggingface/datasets/issues/7243 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7243/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7243/comments | https://api.github.com/repos/huggingface/datasets/issues/7243/events | https://github.com/huggingface/datasets/issues/7243 | 2,602,853,172 | I_kwDODunzps6bJGM0 | 7,243 | ArrayXD with None as leading dim incompatible with DatasetCardData | {
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"It looks like `CardData` in `huggingface_hub` removes None values where it shouldn't. Indeed it calls `_remove_none` on the return of `to_dict()`:\r\n\r\n```python\r\n def to_dict(self) -> Dict[str, Any]:\r\n \"\"\"Converts CardData to a dict.\r\n\r\n Returns:\r\n `dict`: CardData repre... | 2024-10-21T15:08:13Z | 2024-10-22T14:18:10Z | null | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
Creating a dataset with ArrayXD features leads to errors when downloading from hub due to DatasetCardData removing the Nones
@lhoestq
### Steps to reproduce the bug
```python
import numpy as np
from datasets import Array2D, Dataset, Features, load_dataset
def examples_generator():
for i in range(4):
yield {
"array_1d": np.zeros((10,1), dtype="uint16"),
"array_2d": np.zeros((10, 1), dtype="uint16"),
}
features = Features(array_1d=Array2D((None,1), "uint16"), array_2d=Array2D((None, 1), "uint16"))
dataset = Dataset.from_generator(examples_generator, features=features)
dataset.push_to_hub("alex-hh/test_array_1d2d")
ds = load_dataset("alex-hh/test_array_1d2d")
```
Source of error appears to be DatasetCardData.to_dict invoking DatasetCardData._remove_none
```python
from huggingface_hub import DatasetCardData
from datasets.info import DatasetInfosDict
dataset_card_data = DatasetCardData()
DatasetInfosDict({"default": dataset.info.copy()}).to_dataset_card_data(dataset_card_data)
print(dataset_card_data.to_dict()) # removes Nones in shape
```
### Expected behavior
Should be possible to load datasets saved with shape None in leading dimension
### Environment info
3.0.2 and latest huggingface_hub | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5744 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5744/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5744/comments | https://api.github.com/repos/huggingface/datasets/issues/5744/events | https://github.com/huggingface/datasets/issues/5744 | 1,667,076,620 | I_kwDODunzps5jXZIM | 5,744 | [BUG] With Pandas 2.0.0, `load_dataset` raises `TypeError: read_csv() got an unexpected keyword argument 'mangle_dupe_cols'` | {
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"Thanks for reporting, @keyboardAnt.\r\n\r\nWe haven't noticed any crash in our CI tests. Could you please indicate specifically the `load_dataset` command that crashes in your side, so that we can reproduce it?",
"This has been fixed in `datasets` 2.11",
"I am still getting this bug with the latest pandas and ... | 2023-04-13T20:21:28Z | 2024-04-09T16:13:59Z | 2023-07-06T17:01:59Z | NONE | null | null | {
"completed": 0,
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} | The `load_dataset` function with Pandas `1.5.3` has no issue (just a FutureWarning) but crashes with Pandas `2.0.0`.
For your convenience, I opened a draft Pull Request to fix it quickly: https://github.com/huggingface/datasets/pull/5745
---
* The FutureWarning mentioned above:
```
FutureWarning: the 'mangle_dupe_cols' keyword is deprecated and will be removed in a future version. Please take steps to stop the use of 'mangle_dupe_cols'
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6525 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6525/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6525/comments | https://api.github.com/repos/huggingface/datasets/issues/6525/events | https://github.com/huggingface/datasets/pull/6525 | 2,053,119,357 | PR_kwDODunzps5im-lL | 6,525 | BBox type | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6525). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"closing in favor of other ideas that would not involve any typing"
] | 2023-12-21T22:13:27Z | 2024-01-11T06:34:51Z | 2023-12-21T22:39:27Z | MEMBER | null | null | null | see [internal discussion](https://huggingface.slack.com/archives/C02EK7C3SHW/p1703097195609209)
Draft to get some feedback on a possible `BBox` feature type that can be used to get object detection bounding boxes data in one format or another.
```python
>>> from datasets import load_dataset, BBox
>>> ds = load_dataset("svhn", "full_numbers", split="train")
>>> ds[0]
{
'image': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=107x46 at 0x126409BE0>,
'digits': {'bbox': [[38, 1, 21, 40], [57, 3, 16, 40]], 'label': [4, 6]}
}
>>> ds = ds.rename_column("digits", "annotations").cast_column("annotations", BBox(format="coco"))
>>> ds[0]
{
'image': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=107x46 at 0x147730070>,
'annotations': [{'bbox': [38, 1, 21, 40], 'category_id': 4}, {'bbox': [57, 3, 16, 40], 'category_id': 6}]
}
```
note that it's a type for a list of bounding boxes, not just one - which would be needed to switch from a format to another using type casting. | {
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https://api.github.com/repos/huggingface/datasets/issues/4777 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4777/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4777/comments | https://api.github.com/repos/huggingface/datasets/issues/4777/events | https://github.com/huggingface/datasets/pull/4777 | 1,324,548,784 | PR_kwDODunzps48cByL | 4,777 | Require torchaudio<0.12.0 to avoid RuntimeError | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-01T14:50:50Z | 2022-08-02T17:35:14Z | 2022-08-02T17:21:39Z | MEMBER | null | null | null | Related to:
- https://github.com/huggingface/transformers/issues/18379
Fix partially #4776. | {
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https://api.github.com/repos/huggingface/datasets/issues/6522 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6522/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6522/comments | https://api.github.com/repos/huggingface/datasets/issues/6522/events | https://github.com/huggingface/datasets/issues/6522 | 2,052,332,528 | I_kwDODunzps56VBvw | 6,522 | Loading HF Hub Dataset (private org repo) fails to load all features | {
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} | [] | open | false | null | [] | null | [] | 2023-12-21T12:26:35Z | 2023-12-21T13:24:31Z | null | NONE | null | null | {
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} | ### Describe the bug
When pushing a `Dataset` with multiple `Features` (`input`, `output`, `tags`) to Huggingface Hub (private org repo), and later downloading the `Dataset`, only `input` and `output` load - I believe the expected behavior is for all `Features` to be loaded by default?
### Steps to reproduce the bug
Pushing the data. `data_concat` is a `list` of `dict`s.
```python
for datum in data_concat:
datum_tags = {d["key"]: d["value"] for d in datum["tags"]}
split_fraction = # some logic that generates a train/test split number
if split_faction < test_fraction:
data_test.append(datum)
else:
data_train.append(datum)
dataset = DatasetDict(
{
"train": Dataset.from_list(data_train),
"test": Dataset.from_list(data_test),
"full": Dataset.from_list(data_concat),
},
)
dataset_shuffled = dataset.shuffle(seed=shuffle_seed)
dataset_shuffled.push_to_hub(
repo_id=hf_repo_id,
private=True,
config_name=m,
revision=revision,
token=hf_token,
)
```
Loading it later:
```python
dataset = datasets.load_dataset(
path=hf_repo_id,
name=name,
token=hf_token,
)
```
Produces:
```
DatasetDict({
train: Dataset({
features: ['input', 'output'],
num_rows: <obfuscated>
})
test: Dataset({
features: ['input', 'output'],
num_rows: <obfuscated>
})
full: Dataset({
features: ['input', 'output'],
num_rows: <obfuscated>
})
})
```
### Expected behavior
The expected result is below:
```
DatasetDict({
train: Dataset({
features: ['input', 'output', 'tags'],
num_rows: <obfuscated>
})
test: Dataset({
features: ['input', 'output', 'tags'],
num_rows: <obfuscated>
})
full: Dataset({
features: ['input', 'output', 'tags'],
num_rows: <obfuscated>
})
})
```
My workaround is as follows:
```python
dsinfo = datasets.get_dataset_config_info(
path=data_files,
config_name=data_config,
token=hf_token,
)
allfeatures = dsinfo.features.copy()
if "tags" not in allfeatures:
allfeatures["tags"] = [{"key": Value(dtype="string", id=None), "value": Value(dtype="string", id=None)}]
dataset = datasets.load_dataset(
path=data_files,
name=data_config,
features=allfeatures,
token=hf_token,
)
```
Interestingly enough (and perhaps a related bug?), if I don't add the `tags` to `allfeatures` above (i.e. only loading `input` and `output`), it throws an error when executing `load_dataset`:
```
ValueError: Couldn't cast
tags: list<element: struct<key: string, value: string>>
child 0, element: struct<key: string, value: string>
child 0, key: string
child 1, value: string
input: <obfuscated>
output: <obfuscated>
-- schema metadata --
huggingface: '{"info": {"features": {"tags": [{"key": {"dtype": "string",' + 532
to
{'input': <obfuscated>, 'output': <obfuscated>
because column names don't match
```
Traceback for this:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/bt/github/core/.venv/lib/python3.11/site-packages/datasets/load.py", line 2152, in load_dataset
builder_instance.download_and_prepare(
File "/Users/bt/github/core/.venv/lib/python3.11/site-packages/datasets/builder.py", line 948, in download_and_prepare
self._download_and_prepare(
File "/Users/bt/github/core/.venv/lib/python3.11/site-packages/datasets/builder.py", line 1043, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/Users/bt/github/core/.venv/lib/python3.11/site-packages/datasets/builder.py", line 1805, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/Users/bt/github/core/.venv/lib/python3.11/site-packages/datasets/builder.py", line 1950, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.builder.DatasetGenerationError: An error occurred while generating the dataset
```
### Environment info
- `datasets` version: 2.15.0
- Platform: macOS-14.0-arm64-arm-64bit
- Python version: 3.11.5
- `huggingface_hub` version: 0.19.4
- PyArrow version: 14.0.1
- Pandas version: 2.1.4
- `fsspec` version: 2023.10.0 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4763 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4763/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4763/comments | https://api.github.com/repos/huggingface/datasets/issues/4763/events | https://github.com/huggingface/datasets/pull/4763 | 1,321,295,876 | PR_kwDODunzps48RMKi | 4,763 | More rigorous shape inference in to_tf_dataset | {
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} | [] | closed | false | null | [] | null | [
"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-28T18:04:15Z | 2022-09-08T19:17:54Z | 2022-09-08T19:15:41Z | MEMBER | null | null | null | `tf.data` needs to know the shape of tensors emitted from a `tf.data.Dataset`. Although `None` dimensions are possible, overusing them can cause problems - Keras uses the dataset tensor spec at compile-time, and so saying that a dimension is `None` when it's actually constant can hurt performance, or even cause training to fail for dimensions that are needed to determine the shape of weight tensors!
The compromise I used here was to sample several batches from the underlying dataset and apply the `collate_fn` to them, and then to see which dimensions were "empirically variable". There's an obvious problem here, though - if you sample 10 batches and they all have the same shape on a certain dimension, there's still a small chance that the 11th batch will be different, and Keras will throw an error if a dataset tries to emit a tensor whose shape doesn't match the spec.
I encountered this bug in practice once or twice for datasets that were mostly-but-not-totally constant on a given dimension, and I still don't have a perfect solution, but this PR should greatly reduce the risk. It samples many more batches, and also samples very small batches (size 2) - this increases the variability, making it more likely that a few outlier samples will be detected.
Ideally, of course, we'd determine the full output shape analytically, but that's surprisingly tricky when the `collate_fn` can be any arbitrary Python code! | {
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https://api.github.com/repos/huggingface/datasets/issues/7062 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7062/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7062/comments | https://api.github.com/repos/huggingface/datasets/issues/7062/events | https://github.com/huggingface/datasets/pull/7062 | 2,424,467,484 | PR_kwDODunzps52LUPR | 7,062 | Avoid calling http_head for non-HTTP URLs | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7062). 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>... | 2024-07-23T07:25:09Z | 2024-07-23T14:28:27Z | 2024-07-23T14:21:08Z | MEMBER | null | null | null | Avoid calling `http_head` for non-HTTP URLs, by adding and `else` statement.
Currently, it makes an unnecessary HTTP call (which adds latency) for non-HTTP protocols, like FTP, S3,...
I discovered this while working in an unrelated issue. | {
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https://api.github.com/repos/huggingface/datasets/issues/5865 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5865/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5865/comments | https://api.github.com/repos/huggingface/datasets/issues/5865/events | https://github.com/huggingface/datasets/pull/5865 | 1,710,455,738 | PR_kwDODunzps5QiHnw | 5,865 | Deprecate task api | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"If it's easy to keep supporting it we can keep it no ? There are many datasets on the hub that implement the tasks templates in dataset scripts and it's maybe easier to keep task templates than opening PRs to those datasets.",
"do ... | 2023-05-15T16:48:24Z | 2023-07-10T12:33:59Z | 2023-07-10T12:24:01Z | COLLABORATOR | null | null | null | The task API is not well adopted in the ecosystem, so this PR deprecates it. The `train_eval_index` is a newer, more flexible solution that should be used instead (I think?).
These are the projects that still use the task API :
* the image classification example in Transformers: [here](https://github.com/huggingface/transformers/blob/8f76dc8e5aaad58f2df7748b6d6970376f315a9a/examples/pytorch/image-classification/run_image_classification_no_trainer.py#L262) and [here](https://github.com/huggingface/transformers/blob/8f76dc8e5aaad58f2df7748b6d6970376f315a9a/examples/tensorflow/image-classification/run_image_classification.py#L277)
* autotrain: [here](https://github.com/huggingface/autotrain-backend/blob/455e274004b56f9377d64db4ab03671508fcc4cd/zeus/zeus/run/utils.py#L666)
* api-inference-community: [here](https://github.com/huggingface/api-inference-community/blob/fb8fb29d577a5bf01c82944db745489a6d6ed3d4/manage.py#L64) (but the rest of the code does not call the `resolve_dataset` function)
So we need to update these files after the merge.
cc @lewtun | {
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https://api.github.com/repos/huggingface/datasets/issues/6497 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6497/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6497/comments | https://api.github.com/repos/huggingface/datasets/issues/6497/events | https://github.com/huggingface/datasets/issues/6497 | 2,041,994,274 | I_kwDODunzps55tlwi | 6,497 | Support setting a default config name in push_to_hub | {
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https://api.github.com/repos/huggingface/datasets/issues/6718 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6718/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6718/comments | https://api.github.com/repos/huggingface/datasets/issues/6718/events | https://github.com/huggingface/datasets/pull/6718 | 2,169,468,488 | PR_kwDODunzps5ouwwE | 6,718 | Fix concurrent script loading with force_redownload | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6718). 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>... | 2024-03-05T15:04:20Z | 2024-03-07T14:05:53Z | 2024-03-07T13:58:04Z | MEMBER | null | null | null | I added `lock_importable_file` in `get_dataset_builder_class` and `extend_dataset_builder_for_streaming` to fix the issue, and I also added a test
cc @clefourrier | {
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https://api.github.com/repos/huggingface/datasets/issues/5114 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5114/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5114/comments | https://api.github.com/repos/huggingface/datasets/issues/5114/events | https://github.com/huggingface/datasets/issues/5114 | 1,409,236,738 | I_kwDODunzps5T_z8C | 5,114 | load_from_disk with remote filesystem fails due to a wrong temporary local folder path | {
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"Hi Hubert! Could you please probably create a publicly available `gs://` dataset link? I think this would be easier for others to directly start to debug.",
"What seems to work is to change the line to:\r\n```\r\nfs.download(src_dataset_path, dataset_path.parent.as_posix(), recursive=True)\r\n```"
] | 2022-10-14T11:54:53Z | 2022-11-19T07:13:10Z | null | CONTRIBUTOR | null | null | {
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} | ## Describe the bug
The function load_from_disk fails when using a remote filesystem because of a wrong temporary path generation in the load_from_disk method of arrow_dataset.py:
```python
if is_remote_filesystem(fs):
src_dataset_path = extract_path_from_uri(dataset_path)
dataset_path = Dataset._build_local_temp_path(src_dataset_path)
fs.download(src_dataset_path, dataset_path.as_posix(), recursive=True)
```
If _dataset_path_ is `gs://speech/mydataset/train`, then _src_dataset_path_ will be `speech/mydataset/train` and _dataset_path_ will be something like `/var/folders/9s/gf0b/T/tmp6t/speech/mydataset/train`
Then, after downloading the **folder** _src_dataset_path_, you will get a path like `/var/folders/9s/gf0b/T/tmp6t/speech/mydataset/train/train/state.json` (notice we have train twice)
Instead of downloading the remote folder we should be downloading all the files in the folder for the path to be right:
```python
fs.download(os.path.join(src_dataset_path,*), dataset_path.as_posix(), recursive=True)
```
## Steps to reproduce the bug
```python
fs = gcsfs.GCSFileSystem(**storage_options)
dataset = load_from_disk("common_voice_processed") # loading local dataset previously saved locally, works fine
dataset.save_to_disk(output_dir, fs=fs) #works fine
dataset = load_from_disk(output_dir, fs=fs) # crashes
```
## Expected results
The dataset is loaded
## Actual results
FileNotFoundError: [Errno 2] No such file or directory: '/var/folders/9s/gf0b9jz15d517yrf7m3nvlxr0000gn/T/tmp6t5e221_/speech/datasets/tests/common_voice_processed/train/state.json'
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: datasets-2.6.1.dev0
- Platform: mac os monterey 12.5.1
- Python version: 3.8.13
- PyArrow version:pyarrow==9.0.0
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https://api.github.com/repos/huggingface/datasets/issues/7402 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7402/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7402/comments | https://api.github.com/repos/huggingface/datasets/issues/7402/events | https://github.com/huggingface/datasets/pull/7402 | 2,855,880,858 | PR_kwDODunzps6LW8G3 | 7,402 | Fix a typo in arrow_dataset.py | {
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} | [] | closed | false | null | [] | null | [] | 2025-02-16T04:52:02Z | 2025-02-20T17:29:28Z | 2025-02-20T17:29:28Z | CONTRIBUTOR | null | null | null | "in the feature" should be "in the future" | {
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https://api.github.com/repos/huggingface/datasets/issues/4812 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4812/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4812/comments | https://api.github.com/repos/huggingface/datasets/issues/4812/events | https://github.com/huggingface/datasets/pull/4812 | 1,333,051,730 | PR_kwDODunzps484Fzq | 4,812 | Fix bug in function validate_type for Python >= 3.9 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-09T10:32:42Z | 2022-08-12T13:41:23Z | 2022-08-12T13:27:04Z | MEMBER | null | null | null | Fix `validate_type` function, so that it uses `get_origin` instead. This makes the function forward compatible.
This fixes #4811 because:
```python
In [4]: typing.Optional[str]
Out[4]: typing.Optional[str]
In [5]: get_origin(typing.Optional[str])
Out[5]: typing.Union
```
Fix #4811. | {
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https://api.github.com/repos/huggingface/datasets/issues/6011 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6011/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6011/comments | https://api.github.com/repos/huggingface/datasets/issues/6011/events | https://github.com/huggingface/datasets/issues/6011 | 1,795,296,568 | I_kwDODunzps5rAg04 | 6,011 | Documentation: wiki_dpr Dataset has no metric_type for Faiss Index | {
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"Hi! You can do `ds.get_index(\"embeddings\").faiss_index.metric_type` to get the metric type and then match the result with the FAISS metric [enum](https://github.com/facebookresearch/faiss/blob/43d86e30736ede853c384b24667fc3ab897d6ba9/faiss/MetricType.h#L22-L36) (should be L2).",
"Ah! Thank you for pointing thi... | 2023-07-09T08:30:19Z | 2023-07-11T03:02:36Z | 2023-07-11T03:02:36Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
After loading `wiki_dpr` using:
```py
ds = load_dataset(path='wiki_dpr', name='psgs_w100.multiset.compressed', split='train')
print(ds.get_index("embeddings").metric_type) # prints nothing because the value is None
```
the index does not have a defined `metric_type`. This is an issue because I do not know how the `scores` are being computed for `get_nearest_examples()`.
### Steps to reproduce the bug
System: Python 3.9.16, Transformers 4.30.2, WSL
After loading `wiki_dpr` using:
```py
ds = load_dataset(path='wiki_dpr', name='psgs_w100.multiset.compressed', split='train')
print(ds.get_index("embeddings").metric_type) # prints nothing because the value is None
```
the index does not have a defined `metric_type`. This is an issue because I do not know how the `scores` are being computed for `get_nearest_examples()`.
```py
from transformers import DPRQuestionEncoder, DPRContextEncoder, DPRQuestionEncoderTokenizer, DPRContextEncoderTokenizer
tokenizer = DPRQuestionEncoderTokenizer.from_pretrained("facebook/dpr-question_encoder-multiset-base")
encoder = DPRQuestionEncoder.from_pretrained("facebook/dpr-question_encoder-multiset-base")
def encode_question(query, tokenizer=tokenizer, encoder=encoder):
inputs = tokenizer(query, return_tensors='pt')
question_embedding = encoder(**inputs)[0].detach().numpy()
return question_embedding
def get_knn(query, k=5, tokenizer=tokenizer, encoder=encoder, verbose=False):
enc_question = encode_question(query, tokenizer, encoder)
topk_results = ds.get_nearest_examples(index_name='embeddings',
query=enc_question,
k=k)
a = torch.tensor(enc_question[0]).reshape(768)
b = torch.tensor(topk_results.examples['embeddings'][0])
print(a.shape, b.shape)
print(torch.dot(a, b))
print((a-b).pow(2).sum())
return topk_results
```
The [FAISS documentation](https://github.com/facebookresearch/faiss/wiki/MetricType-and-distances) suggests the metric is usually L2 distance (without the square root) or the inner product. I compute both for the sample query:
```py
query = """ it catapulted into popular culture along with a line of action figures and other toys by Bandai.[2] By 2001, the media franchise had generated over $6 billion in toy sales.
Despite initial criticism that its action violence targeted child audiences, the franchise has been commercially successful."""
get_knn(query,k=5)
```
Here, I get dot product of 80.6020 and L2 distance of 77.6616 and
```py
NearestExamplesResults(scores=array([76.20431 , 75.312416, 74.945404, 74.866394, 74.68506 ],
dtype=float32), examples={'id': ['3081096', '2004811', '8908258', '9594124', '286575'], 'text': ['actors, resulting in the "Power Rangers" franchise which has continued since then into sequel TV series (with "Power Rangers Beast Morphers" set to premiere in 2019), comic books, video games, and three feature films, with a further cinematic universe planned. Following from the success of "Power Rangers", Saban acquired the rights to more of Toei\'s library, creating "VR Troopers" and "Big Bad Beetleborgs" from several Metal Hero Series shows and "Masked Rider" from Kamen Rider Series footage. DIC Entertainment joined this boom by acquiring the rights to "Gridman the Hyper Agent" and turning it into "Superhuman Samurai Syber-Squad". In 2002,',
```
Doing `k=1` indicates the higher the outputted number, the better the match, so the metric should not be L2 distance. However, my manually computed inner product (80.6) has a discrepancy with the reported (76.2). Perhaps, this has to do with me using the `compressed` embeddings?
### Expected behavior
```py
ds = load_dataset(path='wiki_dpr', name='psgs_w100.multiset.compressed', split='train')
print(ds.get_index("embeddings").metric_type) # METRIC_INNER_PRODUCT
```
### Environment info
- `datasets` version: 2.12.0
- Platform: Linux-4.18.0-477.13.1.el8_8.x86_64-x86_64-with-glibc2.28
- Python version: 3.9.16
- Huggingface_hub version: 0.14.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/5583 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5583/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5583/comments | https://api.github.com/repos/huggingface/datasets/issues/5583/events | https://github.com/huggingface/datasets/pull/5583 | 1,601,583,625 | PR_kwDODunzps5K2mIz | 5,583 | Do no write index by default when exporting a dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-02-27T17:04:46Z | 2023-02-28T13:52:15Z | 2023-02-28T13:44:04Z | COLLABORATOR | null | null | null | Ensures all the writers that use Pandas for conversion (JSON, CSV, SQL) do not export `index` by default (https://github.com/huggingface/datasets/pull/5490 only did this for CSV) | {
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https://api.github.com/repos/huggingface/datasets/issues/6598 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6598/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6598/comments | https://api.github.com/repos/huggingface/datasets/issues/6598/events | https://github.com/huggingface/datasets/issues/6598 | 2,084,236,605 | I_kwDODunzps58Ou09 | 6,598 | Unexpected keyword argument 'hf' when downloading CSV dataset from S3 | {
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"I am facing similar issue while reading a csv file from s3. Wondering if somebody has found a workaround. ",
"same thing happened to other formats like parquet",
"I am facing similar issue while reading a parquet file from s3.\r\ni try with every version between 2.14 to 2.16.1 but it dosen't work ",
"Re-def... | 2024-01-16T15:16:01Z | 2025-01-31T15:35:33Z | 2024-07-23T14:30:10Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
I receive this error message when using `load_dataset` with "csv" path and `dataset_files=s3://...`:
```
TypeError: Session.__init__() got an unexpected keyword argument 'hf'
```
I found a similar issue here: https://stackoverflow.com/questions/77596258/aws-issue-load-dataset-from-s3-fails-with-unexpected-keyword-argument-error-in
Full stacktrace:
```
.../site-packages/datasets/load.py:2549: in load_dataset
builder_instance.download_and_prepare(
.../site-packages/datasets/builder.py:1005: in download_and_prepare
self._download_and_prepare(
.../site-packages/datasets/builder.py:1078: in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
.../site-packages/datasets/packaged_modules/csv/csv.py:147: in _split_generators
data_files = dl_manager.download_and_extract(self.config.data_files)
.../site-packages/datasets/download/download_manager.py:562: in download_and_extract
return self.extract(self.download(url_or_urls))
.../site-packages/datasets/download/download_manager.py:426: in download
downloaded_path_or_paths = map_nested(
.../site-packages/datasets/utils/py_utils.py:466: in map_nested
mapped = [
.../site-packages/datasets/utils/py_utils.py:467: in <listcomp>
_single_map_nested((function, obj, types, None, True, None))
.../site-packages/datasets/utils/py_utils.py:387: in _single_map_nested
mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]
.../site-packages/datasets/utils/py_utils.py:387: in <listcomp>
mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]
.../site-packages/datasets/utils/py_utils.py:370: in _single_map_nested
return function(data_struct)
.../site-packages/datasets/download/download_manager.py:451: in _download
out = cached_path(url_or_filename, download_config=download_config)
.../site-packages/datasets/utils/file_utils.py:188: in cached_path
output_path = get_from_cache(
...1/site-packages/datasets/utils/file_utils.py:511: in get_from_cache
response = fsspec_head(url, storage_options=storage_options)
.../site-packages/datasets/utils/file_utils.py:316: in fsspec_head
fs, _, paths = fsspec.get_fs_token_paths(url, storage_options=storage_options)
.../site-packages/fsspec/core.py:622: in get_fs_token_paths
fs = filesystem(protocol, **inkwargs)
.../site-packages/fsspec/registry.py:290: in filesystem
return cls(**storage_options)
.../site-packages/fsspec/spec.py:79: in __call__
obj = super().__call__(*args, **kwargs)
.../site-packages/s3fs/core.py:187: in __init__
self.s3 = self.connect()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <s3fs.core.S3FileSystem object at 0x1500a1310>, refresh = True
def connect(self, refresh=True):
"""
Establish S3 connection object.
Parameters
----------
refresh : bool
Whether to create new session/client, even if a previous one with
the same parameters already exists. If False (default), an
existing one will be used if possible
"""
if refresh is False:
# back compat: we store whole FS instance now
return self.s3
anon, key, secret, kwargs, ckwargs, token, ssl = (
self.anon, self.key, self.secret, self.kwargs,
self.client_kwargs, self.token, self.use_ssl)
if not self.passed_in_session:
> self.session = botocore.session.Session(**self.kwargs)
E TypeError: Session.__init__() got an unexpected keyword argument 'hf'
```
### Steps to reproduce the bug
1. Assuming a valid CSV file located at `s3://bucket/data.csv`
2. Run the below code:
```
storage_options = {
"key": "...",
"secret": "...",
"client_kwargs": {
"endpoint_url": "...",
}
}
load_dataset("csv", data_files="s3://bucket/data.csv", storage_options=storage_options)
```
Encountered in version `2.16.1` but also reproduced in `2.16.0` and `2.15.0`.
Note: I encountered this in a unit test using a `moto` mock for S3, however since the error occurs before the session is instantiated, it should not be the issue.
### Expected behavior
No exception is raised, the boto3 session is created successfully, and the CSV file is downloaded successfully and returned as a dataset.
===
After some research I found that `DownloadConfig` has a `__post_init__` method that always forces this value to be set in its `storage_options`, even though in case of an S3 location the storage options get passed on to the S3 Session which does not expect this parameter. I assume this parameter is needed when reading from the huggingface hub and should not be set in this context.
Unfortunately there is nothing the user can do to work around it. Even if you manually do something like:
```
download_config = DownloadConfig()
del download_config.storage_options["hf"]
load_dataset("csv", data_files="s3://bucket/data.csv", download_config=download_config)
```
the library will still reinsert this parameter when `download_config = self.download_config.copy()` in line 418 of `download_manager.py` (`DownloadManager.download`).
Therefore `load_dataset` currently cannot be used to read a dataset in CSV format from an S3 location.
### Environment info
- `datasets` version: 2.16.1
- Platform: macOS-14.2.1-arm64-arm-64bit
- Python version: 3.11.7
- `huggingface_hub` version: 0.20.2
- PyArrow version: 14.0.2
- Pandas version: 2.1.4
- `fsspec` version: 2023.10.0
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https://api.github.com/repos/huggingface/datasets/issues/6640 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6640/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6640/comments | https://api.github.com/repos/huggingface/datasets/issues/6640/events | https://github.com/huggingface/datasets/issues/6640 | 2,115,864,531 | I_kwDODunzps5-HYfT | 6,640 | Sign Language Support | {
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] | open | false | null | [] | null | [] | 2024-02-02T21:54:51Z | 2024-02-02T21:54:51Z | null | NONE | null | null | {
"completed": 0,
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} | ### Feature request
Currently, there are only several Sign Language labels, I would like to propose adding all the Signed Languages as new labels which are described in this ISO standard: https://www.evertype.com/standards/iso639/sign-language.html
### Motivation
Datasets currently only have labels for several signed languages. There are more signed languages in the world. Furthermore, some signed languages that have a lot of online data cannot be found because of this reason (for instance, German Sign Language, and there is no German Sign Language label on huggingface datasets even though there are a lot of readily available sign language datasets exist for German Sign Language, which are used very frequently in Sign Language Processing papers, and models.)
### Your contribution
I can submit a PR for this as well, adding the ISO codes and languages to the labels in datasets. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7445 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7445/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7445/comments | https://api.github.com/repos/huggingface/datasets/issues/7445/events | https://github.com/huggingface/datasets/pull/7445 | 2,911,507,923 | PR_kwDODunzps6ONygU | 7,445 | Fix small bugs with async map | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7445). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-03-11T18:30:57Z | 2025-03-13T10:38:03Z | 2025-03-13T10:37:58Z | MEMBER | null | null | null | helpful for the next PR to enable parallel image/audio/video decoding and make multimodal datasets go brr (e.g. for lerobot)
- fix with_indices
- fix resuming with save_state_dict() / load_state_dict() - omg that wasn't easy
- remove unnecessary decoding in map() to enable parallelism in FormattedExampleIterable later
small bonus: keeping features in batch() | {
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https://api.github.com/repos/huggingface/datasets/issues/6531 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6531/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6531/comments | https://api.github.com/repos/huggingface/datasets/issues/6531/events | https://github.com/huggingface/datasets/pull/6531 | 2,055,201,605 | PR_kwDODunzps5it5Sm | 6,531 | Add polars compatibility | {
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} | [] | closed | false | null | [] | null | [
"Hi ! thanks for adding polars support :)\r\n\r\nYou added from_polars in arrow_dataset.py but not to_polars, is this on purpose ?\r\n\r\nAlso no need to touch table.py imo, which is for arrow-only logic (tables are just wrappers of pyarrow.Table with the exact same methods + optimization to existing methods + sepa... | 2023-12-24T20:03:23Z | 2024-03-08T19:29:25Z | 2024-03-08T15:22:58Z | CONTRIBUTOR | null | null | null | Hey there,
I've just finished adding support to convert and format to `polars.DataFrame`. This was in response to the open issue about integrating Polars [#3334](https://github.com/huggingface/datasets/issues/3334). Datasets can be switched to Polars format via `Dataset.set_format("polars")`. I've also included `to_polars` and `from_polars`. All polars functions are checked via config.POLARS_AVAILABLE.
A few notes:
This only supports `DataFrames` and not `LazyFrames`. This probably could be integrated fairly easily via `is_lazy` args in `set_format`, and `to_polars`.
Let me know your feedbacks. | {
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https://api.github.com/repos/huggingface/datasets/issues/5111 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5111/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5111/comments | https://api.github.com/repos/huggingface/datasets/issues/5111/events | https://github.com/huggingface/datasets/issues/5111 | 1,408,143,170 | I_kwDODunzps5T7o9C | 5,111 | map and filter not working properly in multiprocessing with the new release 2.6.0 | {
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"Same bug exists with `num_proc=1` on colab. `3.7.14 (default, Sep 8 2022, 00:06:44) [GCC 7.5.0]` ",
"Thanks for reporting, @loubnabnl and for the additional information, @PartiallyTyped.\r\n\r\nHowever, I'm not able to reproduce this issue, neither locally nor on Colab:\r\n```\r\nDataset({\r\n features: ['re... | 2022-10-13T17:00:55Z | 2022-10-17T08:26:59Z | 2022-10-14T14:59:59Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
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} | ## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc` in filter for it to work properly. This doesn't happen with `datasets` version 2.5.2
In the code below the data is filtered differently when we increase `num_proc` used in `map` although the datsets before and after mapping have identical elements.
## Steps to reproduce the bug
```python
import datasets
from datasets import load_dataset
def preprocess(example):
return example
ds = load_dataset("codeparrot/codeparrot-clean-valid", split="train").select([i for i in range(10)])
ds1 = ds.map(preprocess, num_proc=2)
ds2 = ds.map(preprocess)
# the datasets elements are the same
for i in range(len(ds1)):
assert ds1[i]==ds2[i]
print(f'Target column before filtering {ds1["autogenerated"]}')
print(f'Target column before filtering {ds2["autogenerated"]}')
print(f"datasets version {datasets.__version__}")
ds_filtered_1 = ds1.filter(lambda x: not x["autogenerated"])
ds_filtered_2 = ds2.filter(lambda x: not x["autogenerated"])
# all elements in Target column are false so they should all be kept, but for ds2 only the first 5=num_samples/num_proc are kept
print(ds_filtered_1)
print(ds_filtered_2)
```
```
Target column before filtering [False, False, False, False, False, False, False, False, False, False]
Target column before filtering [False, False, False, False, False, False, False, False, False, False]
Dataset({
features: ['repo_name', 'path', 'copies', 'size', 'content', 'license', 'hash', 'line_mean', 'line_max', 'alpha_frac', 'autogenerated'],
num_rows: 5
})
Dataset({
features: ['repo_name', 'path', 'copies', 'size', 'content', 'license', 'hash', 'line_mean', 'line_max', 'alpha_frac', 'autogenerated'],
num_rows: 10
})
```
## Expected results
Increasing `num_proc` in mapping shouldn't alter filtering. With the previous version 2.5.2 this doesn't happen
## Actual results
Filtering doesn't work properly when we increase `num_proc` in mapping but not when calling `filter`
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.6.0
- Platform: Linux-4.19.0-22-cloud-amd64-x86_64-with-glibc2.28
- Python version: 3.9.13
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https://api.github.com/repos/huggingface/datasets/issues/4637 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4637/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4637/comments | https://api.github.com/repos/huggingface/datasets/issues/4637/events | https://github.com/huggingface/datasets/issues/4637 | 1,294,818,236 | I_kwDODunzps5NLVu8 | 4,637 | The "all" split breaks streaming | {
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"Thanks for reporting @cakiki.\r\n\r\nYes, this is a bug. We are investigating it.",
"@albertvillanova Nice! Let me know if it's something I can fix my self; would love to contribtue!",
"@cakiki I was working on this but if you would like to contribute, go ahead. I will close my PR. ;)\r\n\r\nFor the moment I j... | 2022-07-05T21:56:49Z | 2022-07-15T13:59:30Z | null | CONTRIBUTOR | null | null | {
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} | ## Describe the bug
Not sure if this is a bug or just the way streaming works, but setting `streaming=True` did not work when setting `split="all"`
## Steps to reproduce the bug
The following works:
```python
ds = load_dataset('super_glue', 'wsc.fixed', split='all')
```
The following throws `ValueError: Bad split: all. Available splits: ['train', 'validation', 'test']`:
```python
ds = load_dataset('super_glue', 'wsc.fixed', split='all', streaming=True)
```
## Expected results
An iterator over all splits.
## Actual results
I had to do the following to achieve the desired result:
```python
from itertools import chain
ds = load_dataset('super_glue', 'wsc.fixed', streaming=True)
it = chain.from_iterable(ds.values())
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.2
- Platform: Linux-4.15.0-176-generic-x86_64-with-glibc2.31
- Python version: 3.10.5
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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https://api.github.com/repos/huggingface/datasets/issues/6716 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6716/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6716/comments | https://api.github.com/repos/huggingface/datasets/issues/6716/events | https://github.com/huggingface/datasets/issues/6716 | 2,168,706,558 | I_kwDODunzps6BQ9X- | 6,716 | Non-deterministic `Dataset.builder_name` value | {
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"When `rotten_tomatoes` is printed out, the following warning message is also printed out:\r\n\r\n```\r\nYou can avoid this message in future by passing the argument `trust_remote_code=True`.\r\nPassing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`.\r\n```... | 2024-03-05T09:23:21Z | 2024-03-19T07:58:14Z | 2024-03-19T07:58:14Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I'm not sure if this is a bug, but `print(ds.builder_name)` in the following code sometimes prints out `rotten_tomatoes` instead of `parquet`:
```python
import datasets
for _ in range(100):
ds = datasets.load_dataset("rotten_tomatoes", split="train")
print(ds.builder_name) # prints out "rotten_tomatoes" sometimes instead of "parquet"
```
Output:
```
...
parquet
parquet
parquet
rotten_tomatoes
parquet
parquet
parquet
...
```
Here's a reproduction using GitHub Actions:
https://github.com/mlflow/mlflow/actions/runs/8153247984/job/22284263613?pr=11329#step:12:241
One of our tests is flaky because `builder_name` is not deterministic.
### Steps to reproduce the bug
1. Run the code above.
### Expected behavior
Always prints out `parquet`?
### Environment info
```
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 2.18.0
- Platform: Linux-6.5.0-1015-azure-x86_64-with-glibc2.34
- Python version: 3.8.18
- `huggingface_hub` version: 0.21.3
- PyArrow version: 15.0.0
- Pandas version: 2.0.3
- `fsspec` version: 2024.2.0
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6172 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6172/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6172/comments | https://api.github.com/repos/huggingface/datasets/issues/6172/events | https://github.com/huggingface/datasets/issues/6172 | 1,863,318,027 | I_kwDODunzps5vD_oL | 6,172 | Make Dataset streaming queries retryable | {
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"Hi! The streaming mode also retries requests - `datasets.config.STREAMING_READ_MAX_RETRIES` (20 sec by default) controls the number of retries and `datasets.config.STREAMING_READ_RETRY_INTERVAL` (5 sec) the sleep time between retries.\r\n\r\n> At step 1800 I got a 504 HTTP status code error from Huggingface hub fo... | 2023-08-23T13:15:38Z | 2023-11-06T13:54:16Z | null | NONE | null | null | {
"completed": 0,
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} | ### Feature request
Streaming datasets, as intended, do not load the entire dataset in memory or disk. However, while querying the next data chunk from the remote, sometimes it is possible that the service is down or there might be other issues that may cause the query to fail. In such a scenario, it would be nice to make these queries retryable (perhaps with a backoff strategy).
### Motivation
I was working on a model and the model checkpoints after every 1000 steps. At step 1800 I got a 504 HTTP status code error from Huggingface hub for my pytorch `dataloader`. Given the size of my model and data, it took around 2 hours to reach 1800 steps and now it will take about an hour to recover the lost 800. It would be better to get a retryable querying strategy.
### Your contribution
It would be better if someone having experience in this area takes this up as this would require some testing. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7299 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7299/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7299/comments | https://api.github.com/repos/huggingface/datasets/issues/7299/events | https://github.com/huggingface/datasets/issues/7299 | 2,695,378,251 | I_kwDODunzps6gqDVL | 7,299 | Efficient Image Augmentation in Hugging Face Datasets | {
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} | ### Describe the bug
I'm using the Hugging Face datasets library to load images in batch and would like to apply a torchvision transform to solve the inconsistent image sizes in the dataset and apply some on the fly image augmentation. I can just think about using the collate_fn, but seems quite inefficient.
I'm new to the Hugging Face datasets library, I didn't find nothing in the documentation or the issues here on github.
Is there an existing way to add image transformations directly to the dataset loading pipeline?
### Steps to reproduce the bug
from datasets import load_dataset
from torch.utils.data import DataLoader
```python
def collate_fn(batch):
images = [item['image'] for item in batch]
texts = [item['text'] for item in batch]
return {
'images': images,
'texts': texts
}
dataset = load_dataset("Yuki20/pokemon_caption", split="train")
dataloader = DataLoader(dataset, batch_size=4, collate_fn=collate_fn)
# Output shows varying image sizes:
# [(1280, 1280), (431, 431), (789, 789), (769, 769)]
```
### Expected behavior
I'm looking for a way to resize images on-the-fly when loading the dataset, similar to PyTorch's Dataset.__getitem__ functionality. This would be more efficient than handling resizing in the collate_fn.
### Environment info
- `datasets` version: 3.1.0
- Platform: Linux-6.5.0-41-generic-x86_64-with-glibc2.35
- Python version: 3.11.10
- `huggingface_hub` version: 0.26.2
- PyArrow version: 18.0.0
- Pandas version: 2.2.3
- `fsspec` version: 2024.9.0
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https://api.github.com/repos/huggingface/datasets/issues/4980 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4980/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4980/comments | https://api.github.com/repos/huggingface/datasets/issues/4980/events | https://github.com/huggingface/datasets/issues/4980 | 1,374,868,083 | I_kwDODunzps5R8tJz | 4,980 | Make `pyarrow` optional | {
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"The whole datasets library is pretty much a wrapper to pyarrow (just take a look at some of the source for a Dataset) https://github.com/huggingface/datasets/blob/51aef08ad7053c0bfe8f9a961207b26df15850d3/src/datasets/arrow_dataset.py#L639 \r\n\r\nI think removing the pyarrow dependency would involve a complete rew... | 2022-09-15T17:38:03Z | 2022-09-16T17:23:47Z | 2022-09-16T17:23:47Z | NONE | null | null | {
"completed": 0,
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} | **Is your feature request related to a problem? Please describe.**
Is `pyarrow` really needed for every dataset?
**Describe the solution you'd like**
It is made optional.
**Describe alternatives you've considered**
Likely, no.
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https://api.github.com/repos/huggingface/datasets/issues/5931 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5931/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5931/comments | https://api.github.com/repos/huggingface/datasets/issues/5931/events | https://github.com/huggingface/datasets/issues/5931 | 1,745,408,784 | I_kwDODunzps5oCNMQ | 5,931 | `datasets.map` not reusing cached copy by default | {
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"This can happen when a map transform cannot be hashed deterministically (e.g., an object referenced by the transform changes its state after the first call - an issue with fast tokenizers). The solution is to provide `cache_file_name` in the `map` call to check this file for the cached result instead of relying on... | 2023-06-07T09:03:33Z | 2023-06-21T16:15:40Z | 2023-06-21T16:15:40Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
When I load the dataset from local directory, it's cached copy is picked up after first time. However, for `map` operation, the operation is applied again and cached copy is not picked up. Is there any way to pick cached copy instead of processing it again? The only solution I could think of was to use `save_to_disk` after my last transform and then use that in my DataLoader pipeline. Are there any other solutions for the same?
One more thing, my dataset is occupying 6GB storage memory after I use `map`, is there any way I can reduce that memory usage?
### Steps to reproduce the bug
```
# make sure that dataset decodes audio with correct sampling rate
dataset_sampling_rate = next(iter(self.raw_datasets.values())).features["audio"].sampling_rate
if dataset_sampling_rate != self.feature_extractor.sampling_rate:
self.raw_datasets = self.raw_datasets.cast_column(
"audio", datasets.features.Audio(sampling_rate=self.feature_extractor.sampling_rate)
)
vectorized_datasets = self.raw_datasets.map(
self.prepare_dataset,
remove_columns=next(iter(self.raw_datasets.values())).column_names,
num_proc=self.num_workers,
desc="preprocess datasets",
)
# filter data that is longer than max_input_length
self.vectorized_datasets = vectorized_datasets.filter(
self.is_audio_in_length_range,
num_proc=self.num_workers,
input_columns=["input_length"],
)
def prepare_dataset(self, batch):
# load audio
sample = batch["audio"]
inputs = self.feature_extractor(sample["array"], sampling_rate=sample["sampling_rate"])
batch["input_values"] = inputs.input_values[0]
batch["input_length"] = len(batch["input_values"])
batch["labels"] = self.tokenizer(batch["target_text"]).input_ids
return batch
```
### Expected behavior
`map` to use cached copy and if possible an alternative technique to reduce memory usage after using `map`
### Environment info
- `datasets` version: 2.12.0
- Platform: Linux-3.10.0-1160.71.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.8.16
- Huggingface_hub version: 0.15.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.2
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https://api.github.com/repos/huggingface/datasets/issues/6306 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6306/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6306/comments | https://api.github.com/repos/huggingface/datasets/issues/6306/events | https://github.com/huggingface/datasets/issues/6306 | 1,946,363,452 | I_kwDODunzps50AyY8 | 6,306 | pyinstaller : OSError: could not get source code | {
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"more information：\r\n``` \r\nFile \"text2vec\\__init__.py\", line 8, in <module>\r\nFile \"<frozen importlib._bootstrap>\", line 1027, in _find_and_load\r\nFile \"<frozen importlib._bootstrap>\", line 1006, in _find_and_load_unlocked\r\nFile \"<frozen importlib._bootstrap>\", line 688, in _load_unlocked\r\nFile \"... | 2023-10-17T01:41:51Z | 2023-11-02T07:24:51Z | 2023-10-18T14:03:42Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I ran a package with pyinstaller and got the following error：
### Steps to reproduce the bug
```
...
File "datasets\__init__.py", line 52, in <module>
File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
File "PyInstaller\loader\pyimod02_importers.py", line 499, in exec_module
File "datasets\inspect.py", line 30, in <module>
File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
File "PyInstaller\loader\pyimod02_importers.py", line 499, in exec_module
File "datasets\load.py", line 58, in <module>
File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
File "PyInstaller\loader\pyimod02_importers.py", line 499, in exec_module
File "datasets\packaged_modules\__init__.py", line 31, in <module>
File "inspect.py", line 1147, in getsource
File "inspect.py", line 1129, in getsourcelines
File "inspect.py", line 958, in findsource
OSError: could not get source code
```
### Expected behavior
I have looked up the relevant information, but I can't find a suitable reason
### Environment info
```python
python 3.10
datasets 2.14.4
pyinstaller 5.6.2
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4603 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4603/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4603/comments | https://api.github.com/repos/huggingface/datasets/issues/4603/events | https://github.com/huggingface/datasets/issues/4603 | 1,289,963,331 | I_kwDODunzps5M40dD | 4,603 | CI fails recurrently and randomly on Windows | {
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} | As reported by @lhoestq,
The windows CI is currently flaky: some dependencies like `aiobotocore`, `multiprocess` and `seqeval` sometimes fail to install.
In particular it seems that building the wheels fail. Here is an example of logs:
```
Building wheel for seqeval (setup.py): started
Running command 'C:\tools\miniconda3\envs\py37\python.exe' -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\circleci\\AppData\\Local\\Temp\\pip-install-h55pfgbv\\seqeval_d6cdb9d23ff6490b98b6c4bcaecb516e\\setup.py'"'"'; __file__='"'"'C:\\Users\\circleci\\AppData\\Local\\Temp\\pip-install-h55pfgbv\\seqeval_d6cdb9d23ff6490b98b6c4bcaecb516e\\setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(__file__) if os.path.exists(__file__) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' bdist_wheel -d 'C:\Users\circleci\AppData\Local\Temp\pip-wheel-x3cc8ym6'
No parent package detected, impossible to derive `name`
running bdist_wheel
running build
running build_py
package init file 'seqeval\__init__.py' not found (or not a regular file)
package init file 'seqeval\metrics\__init__.py' not found (or not a regular file)
C:\tools\miniconda3\envs\py37\lib\site-packages\setuptools\command\install.py:37: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.
setuptools.SetuptoolsDeprecationWarning,
installing to build\bdist.win-amd64\wheel
running install
running install_lib
warning: install_lib: 'build\lib' does not exist -- no Python modules to install
running install_egg_info
running egg_info
creating UNKNOWN.egg-info
writing UNKNOWN.egg-info\PKG-INFO
writing dependency_links to UNKNOWN.egg-info\dependency_links.txt
writing top-level names to UNKNOWN.egg-info\top_level.txt
writing manifest file 'UNKNOWN.egg-info\SOURCES.txt'
reading manifest file 'UNKNOWN.egg-info\SOURCES.txt'
writing manifest file 'UNKNOWN.egg-info\SOURCES.txt'
Copying UNKNOWN.egg-info to build\bdist.win-amd64\wheel\.\UNKNOWN-0.0.0-py3.7.egg-info
running install_scripts
creating build\bdist.win-amd64\wheel\UNKNOWN-0.0.0.dist-info\WHEEL
creating 'C:\Users\circleci\AppData\Local\Temp\pip-wheel-x3cc8ym6\UNKNOWN-0.0.0-py3-none-any.whl' and adding 'build\bdist.win-amd64\wheel' to it
adding 'UNKNOWN-0.0.0.dist-info/METADATA'
adding 'UNKNOWN-0.0.0.dist-info/WHEEL'
adding 'UNKNOWN-0.0.0.dist-info/top_level.txt'
adding 'UNKNOWN-0.0.0.dist-info/RECORD'
removing build\bdist.win-amd64\wheel
Building wheel for seqeval (setup.py): finished with status 'done'
Created wheel for seqeval: filename=UNKNOWN-0.0.0-py3-none-any.whl size=963 sha256=67eb93a6e1ff4796c5882a13f9fa25bb0d3d103796e2525f9cecf3b2ef26d4b1
Stored in directory: c:\users\circleci\appdata\local\pip\cache\wheels\05\96\ee\7cac4e74f3b19e3158dce26a20a1c86b3533c43ec72a549fd7
WARNING: Built wheel for seqeval is invalid: Wheel has unexpected file name: expected 'seqeval', got 'UNKNOWN'
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6150 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6150/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6150/comments | https://api.github.com/repos/huggingface/datasets/issues/6150/events | https://github.com/huggingface/datasets/issues/6150 | 1,850,740,456 | I_kwDODunzps5uUA7o | 6,150 | Allow dataset implement .take | {
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"```\r\n dataset = IterableDataset(dataset) if type(dataset) != IterableDataset else dataset # to force dataset.take(batch_size) to work in non-streaming mode\r\n ```\r\n",
"hf discuss: https://discuss.huggingface.co/t/how-does-one-make-dataset-take-512-work-with-streaming-false-with-hugging-face-data-set/5... | 2023-08-15T00:17:51Z | 2023-08-17T13:49:37Z | null | NONE | null | null | {
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} | ### Feature request
I want to do:
```
dataset.take(512)
```
but it only works with streaming = True
### Motivation
uniform interface to data sets. Really surprising the above only works with streaming = True.
### Your contribution
Should be trivial to copy paste the IterableDataset .take to use the local path in the data (when streaming = False) | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5613 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5613/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5613/comments | https://api.github.com/repos/huggingface/datasets/issues/5613/events | https://github.com/huggingface/datasets/issues/5613 | 1,611,875,473 | I_kwDODunzps5gE0SR | 5,613 | Version mismatch with multiprocess and dill on Python 3.10 | {
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"Sorry, I just found https://github.com/apache/beam/issues/24458. It seems this issue is being worked on. ",
"Reopening, since I think the docs should inform the user of this problem. For example, [this page](https://huggingface.co/docs/datasets/installation) says \r\n> Datasets is tested on Python 3.7+.\r\n\r\nb... | 2023-03-06T17:14:41Z | 2024-04-05T20:13:52Z | null | NONE | null | null | {
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} | ### Describe the bug
Grabbing the latest version of `datasets` and `apache-beam` with `poetry` using Python 3.10 gives a crash at runtime. The crash is
```
File "/Users/adpauls/sc/git/DSI-transformers/data/NQ/create_NQ_train_vali.py", line 1, in <module>
import datasets
File "/Users/adpauls/Library/Caches/pypoetry/virtualenvs/yyy-oPbZ7mKM-py3.10/lib/python3.10/site-packages/datasets/__init__.py", line 43, in <module>
from .arrow_dataset import Dataset
File "/Users/adpauls/Library/Caches/pypoetry/virtualenvs/yyy-oPbZ7mKM-py3.10/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 65, in <module>
from .arrow_reader import ArrowReader
File "/Users/adpauls/Library/Caches/pypoetry/virtualenvs/yyy-oPbZ7mKM-py3.10/lib/python3.10/site-packages/datasets/arrow_reader.py", line 30, in <module>
from .download.download_config import DownloadConfig
File "/Users/adpauls/Library/Caches/pypoetry/virtualenvs/yyy-oPbZ7mKM-py3.10/lib/python3.10/site-packages/datasets/download/__init__.py", line 9, in <module>
from .download_manager import DownloadManager, DownloadMode
File "/Users/adpauls/Library/Caches/pypoetry/virtualenvs/yyy-oPbZ7mKM-py3.10/lib/python3.10/site-packages/datasets/download/download_manager.py", line 35, in <module>
from ..utils.py_utils import NestedDataStructure, map_nested, size_str
File "/Users/adpauls/Library/Caches/pypoetry/virtualenvs/yyy-oPbZ7mKM-py3.10/lib/python3.10/site-packages/datasets/utils/py_utils.py", line 40, in <module>
import multiprocess.pool
File "/Users/adpauls/Library/Caches/pypoetry/virtualenvs/yyy-oPbZ7mKM-py3.10/lib/python3.10/site-packages/multiprocess/pool.py", line 609, in <module>
class ThreadPool(Pool):
File "/Users/adpauls/Library/Caches/pypoetry/virtualenvs/yyy-oPbZ7mKM-py3.10/lib/python3.10/site-packages/multiprocess/pool.py", line 611, in ThreadPool
from .dummy import Process
File "/Users/adpauls/Library/Caches/pypoetry/virtualenvs/yyy-oPbZ7mKM-py3.10/lib/python3.10/site-packages/multiprocess/dummy/__init__.py", line 87, in <module>
class Condition(threading._Condition):
AttributeError: module 'threading' has no attribute '_Condition'. Did you mean: 'Condition'?
```
I think this is a bad interaction of versions from `dill`, `multiprocess`, `apache-beam`, and `threading` from the Python (3.10) standard lib. Upgrading `multiprocess` to a version that does not crash like this is not possible because `apache-beam` pins `dill` to and old version:
```
Because multiprocess (0.70.10) depends on dill (>=0.3.2)
and apache-beam (2.45.0) depends on dill (>=0.3.1.1,<0.3.2), multiprocess (0.70.10) is incompatible with apache-beam (2.45.0).
And because no versions of apache-beam match >2.45.0,<3.0.0, multiprocess (0.70.10) is incompatible with apache-beam (>=2.45.0,<3.0.0).
So, because yyy depends on both apache-beam (^2.45.0) and multiprocess (0.70.10), version solving failed.
```
Perhaps it is not right to file a bug here, but I'm not totally sure whose fault it is. And in any case, this is an immediate blocker to using `datasets` out of the box.
Possibly related to https://github.com/huggingface/datasets/issues/5232.
### Steps to reproduce the bug
Steps to reproduce:
1. Make a poetry project with this configuration
```
[tool.poetry]
name = "yyy"
version = "0.1.0"
description = ""
authors = ["Adam Pauls <adpauls@gmail.com>"]
readme = "README.md"
packages = [{ include = "xxx" }]
[tool.poetry.dependencies]
python = ">=3.10,<3.11"
datasets = "^2.10.1"
apache-beam = "^2.45.0"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
```
2. `poetry install`.
3. `poetry run python -c "import datasets"`.
### Expected behavior
Script runs.
### Environment info
Python 3.10. Here are the versions installed by `poetry`:
```
•• Installing frozenlist (1.3.3)
• Installing idna (3.4)
• Installing multidict (6.0.4)
• Installing aiosignal (1.3.1)
• Installing async-timeout (4.0.2)
• Installing attrs (22.2.0)
• Installing certifi (2022.12.7)
• Installing charset-normalizer (3.1.0)
• Installing six (1.16.0)
• Installing urllib3 (1.26.14)
• Installing yarl (1.8.2)
• Installing aiohttp (3.8.4)
• Installing dill (0.3.1.1)
• Installing docopt (0.6.2)
• Installing filelock (3.9.0)
• Installing numpy (1.22.4)
• Installing pyparsing (3.0.9)
• Installing protobuf (3.19.4)
• Installing packaging (23.0)
• Installing python-dateutil (2.8.2)
• Installing pytz (2022.7.1)
• Installing pyyaml (6.0)
• Installing requests (2.28.2)
• Installing tqdm (4.65.0)
• Installing typing-extensions (4.5.0)
• Installing cloudpickle (2.2.1)
• Installing crcmod (1.7)
• Installing fastavro (1.7.2)
• Installing fasteners (0.18)
• Installing fsspec (2023.3.0)
• Installing grpcio (1.51.3)
• Installing hdfs (2.7.0)
• Installing httplib2 (0.20.4)
• Installing huggingface-hub (0.12.1)
• Installing multiprocess (0.70.9)
• Installing objsize (0.6.1)
• Installing orjson (3.8.7)
• Installing pandas (1.5.3)
• Installing proto-plus (1.22.2)
• Installing pyarrow (9.0.0)
• Installing pydot (1.4.2)
• Installing pymongo (3.13.0)
• Installing regex (2022.10.31)
• Installing responses (0.18.0)
• Installing xxhash (3.2.0)
• Installing zstandard (0.20.0)
• Installing apache-beam (2.45.0)
• Installing datasets (2.10.1)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5117 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5117/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5117/comments | https://api.github.com/repos/huggingface/datasets/issues/5117/events | https://github.com/huggingface/datasets/issues/5117 | 1,409,571,346 | I_kwDODunzps5UBFoS | 5,117 | Progress bars have color red and never completed to 100% | {
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"... | null | [
"Hi @echatzikyriakidis, thanks for submitting the issue.\r\nWhich shell are you using exactly? I tried to run the command you sent, but I don't see colors at all 🧐\r\n\r\nI tried from bash and zsh as well.",
"Hi @david1542 ,\r\n\r\nI use Google Colab.\r\n",
"Got it. I [created a PR](https://github.com/huggingf... | 2022-10-14T16:12:30Z | 2024-06-19T19:03:42Z | 2022-10-23T12:58:41Z | NONE | null | null | {
"completed": 0,
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} | ## Describe the bug
Progress bars after transformative operations turn in red and never be completed to 100%
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset('rotten_tomatoes', split='test').filter(lambda o: True)
```
## Expected results
Progress bar should be 100% and green
## Actual results
Progress bar turn in red and never completed to 100%
## Environment info
- `datasets` version: 2.6.1
- Platform: Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.14
- PyArrow version: 6.0.1
- Pandas version: 1.3.5 | {
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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... | 2023-07-17T15:50:15Z | 2023-07-24T14:45:56Z | 2023-07-24T14:35:03Z | COLLABORATOR | null | null | null | Fix #6039 | {
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https://api.github.com/repos/huggingface/datasets/issues/7224 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7224/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7224/comments | https://api.github.com/repos/huggingface/datasets/issues/7224/events | https://github.com/huggingface/datasets/pull/7224 | 2,583,233,980 | PR_kwDODunzps5-bLNR | 7,224 | fallback to default feature casting in case custom features not available during dataset loading | {
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} | [] | open | false | null | [] | null | [] | 2024-10-12T16:13:56Z | 2024-10-12T16:13:56Z | null | CONTRIBUTOR | null | null | null | a fix for #7223 in case datasets is happy to support this kind of extensibility! seems cool / powerful for allowing sharing of datasets with potentially different feature types | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7337 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7337/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7337/comments | https://api.github.com/repos/huggingface/datasets/issues/7337/events | https://github.com/huggingface/datasets/issues/7337 | 2,744,877,569 | I_kwDODunzps6jm4IB | 7,337 | One or several metadata.jsonl were found, but not in the same directory or in a parent directory of | {
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"Hmmm I double checked in the source code and I found a contradiction: in the current implementation the metadata file is ignored if it's not in the same archive as the zip image somehow:\r\n\r\nhttps://github.com/huggingface/datasets/blob/caa705e8bf4bedf1a956f48b545283b2ca14170a/src/datasets/packaged_modules/folde... | 2024-12-17T12:58:43Z | 2025-01-03T15:28:13Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
ImageFolder with metadata.jsonl error. I downloaded liuhaotian/LLaVA-CC3M-Pretrain-595K locally from Hugging Face. According to the tutorial in https://huggingface.co/docs/datasets/image_dataset#image-captioning, only put images.zip and metadata.jsonl containing information in the same folder. However, after loading, an error was reported: One or several metadata.jsonl were found, but not in the same directory or in a parent directory of.
The data in my jsonl file is as follows:
> {"id": "GCC_train_002448550", "file_name": "GCC_train_002448550.jpg", "conversations": [{"from": "human", "value": "<image>\nProvide a brief description of the given image."}, {"from": "gpt", "value": "a view of a city , where the flyover was proposed to reduce the increasing traffic on thursday ."}]}
### Steps to reproduce the bug
from datasets import load_dataset
image = load_dataset("imagefolder",data_dir='data/opensource_data')
### Expected behavior
success
### Environment info
datasets==3.2.0 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5223 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5223/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5223/comments | https://api.github.com/repos/huggingface/datasets/issues/5223/events | https://github.com/huggingface/datasets/pull/5223 | 1,442,610,658 | PR_kwDODunzps5CjT9Z | 5,223 | Add SQL guide | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5223). All of your documentation changes will be reflected on that endpoint.",
"I think we may want more content on this page that's not SQL related. Some of that content probably already lives in the main `load` docs page, but... | 2022-11-09T19:10:27Z | 2022-11-15T17:40:25Z | 2022-11-15T17:40:21Z | MEMBER | null | null | null | This PR adapts @nateraw's awesome SQL notebook as a guide for the docs! | {
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