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https://api.github.com/repos/huggingface/datasets/issues/5533 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5533/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5533/comments | https://api.github.com/repos/huggingface/datasets/issues/5533/events | https://github.com/huggingface/datasets/pull/5533 | 1,585,885,871 | PR_kwDODunzps5KCR5I | 5,533 | Add reduce function | [] | closed | false | null | 19 | 2023-02-15T13:44:01Z | 2023-02-28T14:46:13Z | 2023-02-28T14:46:12Z | null | This PR closes #5496 .
I tried to imitate the `reduce`-method from `functools`, i.e. the function input must be a binary operation. I assume that the input type has an empty element, i.e. `input_type()` is defined, as the acumulant is instantiated as this object - im not sure that is this a reasonable assumption?
If `batched= True` the reduction of each shard is _not_ returned, but the reduction of the entire dataset. I was unsure wether this was an intuitive API, or it would make more sense to return the reduction of each shard? | {
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"I agree that it would be a good idea to introduce a `combiner` argument in another PR.\r\n\r\nI did take quite a lot of inspiration from the implementation of `map`, but it did not seem obvious how to resuse `map` for the implementation. Do you have any suggestions, i could give a try?\r\n\r\nThose were exactly m... |
https://api.github.com/repos/huggingface/datasets/issues/374 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/374/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/374/comments | https://api.github.com/repos/huggingface/datasets/issues/374/events | https://github.com/huggingface/datasets/pull/374 | 654,895,066 | MDExOlB1bGxSZXF1ZXN0NDQ3NTMxMzUy | 374 | Add dataset post processing for faiss indexes | [] | closed | false | null | 2 | 2020-07-10T16:25:59Z | 2020-07-13T13:44:03Z | 2020-07-13T13:44:01Z | null | # Post processing of datasets for faiss indexes
Now that we can have datasets with embeddings (see `wiki_pr` for example), we can allow users to load the dataset + get the Faiss index that comes with it to do nearest neighbors queries.
## Implementation proposition
- Faiss indexes have to be added to the `nlp.Dataset` object, and therefore it's in a different scope that what are doing the `_split_generators` and `_generate_examples` methods of `nlp.DatasetBuilder`. Therefore I added a new method for post processing of the `nlp.Dataset` object called `_post_process` (name could change)
- The role of `_post_process` is to apply dataset transforms (filter/map etc.) or indexing functions (add_faiss_index) to modify/enrich the `nlp.Dataset` object. It is not part of the `download_and_prepare` process (that is focused on arrow files creation) so the post processing is run inside the `as_dataset` method.
- `_post_process` can generate new files (cached files from dataset transforms or serialized faiss indexes) and their names are defined by `_post_processing_resources`
- as we know what are the post processing resources, we can download them automatically from google storage instead of computing them if they're available (as we do for arrow files)
I'd happy to discuss these choices !
## The `wiki_dpr` index
It takes 1h20 and ~7GB of memory to compute. The final index is 1.42GB and takes ~1.5GB of memory.
This is pretty cool given that a naive flat index would take 170GB of memory to store the 21M vectors of dim 768.
I couldn't use directly the Faiss `index_factory` as I needed to set the metric to inner product.
## Example of usage
```python
import nlp
dset = nlp.load_dataset(
"wiki_dpr",
"psgs_w100_with_nq_embeddings",
split="train",
with_index=True
)
print(len(dset), dset.list_indexes()) # (21015300, ['embeddings'])
```
(it also works with the dataset configuration without the embeddings because I added the index file in google storage for this one too)
## Demo
You can also check a demo on google colab that shows how to use it with the DPRQuestionEncoder from transformers:
https://colab.research.google.com/drive/1FakNU8W5EPMcWff7iP1H6REg3XSS0YLp?usp=sharing
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"I changed the `wiki_dpr` script to ignore the last 24 examples for now. Hopefully we'll have the full version soon.\r\nThe datasets_infos.json and the data on GCS are updated.\r\n\r\nAnd I also added a check to make sure we don't have post processing resources in sub-directories.",
"I added a dummy config that c... |
https://api.github.com/repos/huggingface/datasets/issues/3283 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3283/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3283/comments | https://api.github.com/repos/huggingface/datasets/issues/3283/events | https://github.com/huggingface/datasets/issues/3283 | 1,055,495,874 | I_kwDODunzps4-6ZbC | 3,283 | Add Speech Commands dataset | [
{
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"description": "Requesting to add a new dataset",
"id": 2067376369,
"name": "dataset request",
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"url": "https://api.github.com/repos/huggingface/datasets/labels/dataset%20request"
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"color": "d93f0b",... | closed | false | null | 1 | 2021-11-16T22:39:56Z | 2021-12-10T10:30:15Z | 2021-12-10T10:30:15Z | null | ## Adding a Dataset
- **Name:** Speech commands
- **Description:** A Dataset for Limited-Vocabulary Speech Recognition
- **Paper:** https://arxiv.org/abs/1804.03209
- **Data:** https://www.tensorflow.org/datasets/catalog/speech_commands, Available:
http://download.tensorflow.org/data/speech_commands_v0.02.tar.gz
- **Motivation:** Nice dataset for audio classification training
cc @anton-l
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| {
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https://api.github.com/repos/huggingface/datasets/issues/6019 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6019/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6019/comments | https://api.github.com/repos/huggingface/datasets/issues/6019/events | https://github.com/huggingface/datasets/pull/6019 | 1,799,532,822 | PR_kwDODunzps5VPAlD | 6,019 | Improve logging | [] | closed | false | null | 13 | 2023-07-11T18:30:23Z | 2023-07-12T19:34:14Z | 2023-07-12T17:19:28Z | null | Adds the StreamHandler (as `hfh` and `transformers` do) to the library's logger to log INFO messages and logs the messages about "loading a cached result" (and some other warnings) as INFO
(Also removes the `leave=False` arg in the progress bars to be consistent with `hfh` and `transformers` - progress bars serve as an indicator that a result is not cached, so it makes more sense not to delete them)
Fix #2832, fix https://github.com/huggingface/datasets/issues/1948, fix https://github.com/huggingface/datasets/issues/5444 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/1044 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1044/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1044/comments | https://api.github.com/repos/huggingface/datasets/issues/1044/events | https://github.com/huggingface/datasets/pull/1044 | 756,111,647 | MDExOlB1bGxSZXF1ZXN0NTMxNzA5MTg0 | 1,044 | Add AMTTL Chinese Word Segmentation Dataset | [] | closed | false | null | 0 | 2020-12-03T11:27:52Z | 2020-12-03T17:13:14Z | 2020-12-03T17:13:13Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2142 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2142/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2142/comments | https://api.github.com/repos/huggingface/datasets/issues/2142/events | https://github.com/huggingface/datasets/pull/2142 | 843,919,420 | MDExOlB1bGxSZXF1ZXN0NjAzMjQwMzUy | 2,142 | Gem V1.1 | [] | closed | false | null | 0 | 2021-03-29T23:47:02Z | 2021-03-30T00:10:02Z | 2021-03-30T00:10:02Z | null | This branch updates the GEM benchmark to its 1.1 version which includes:
- challenge sets for most tasks
- detokenized TurkCorpus to match the rest of the text simplification subtasks
- fixed inputs for TurkCorpus and ASSET test sets
- 18 languages in WikiLingua
cc @sebastianGehrmann | {
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https://api.github.com/repos/huggingface/datasets/issues/5193 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5193/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5193/comments | https://api.github.com/repos/huggingface/datasets/issues/5193/events | https://github.com/huggingface/datasets/issues/5193 | 1,433,883,780 | I_kwDODunzps5Vd1SE | 5,193 | "One or several metadata. were found, but not in the same directory or in a parent directory" | [] | closed | false | null | 5 | 2022-11-02T22:46:25Z | 2022-11-03T13:39:16Z | 2022-11-03T13:35:44Z | null | ### Describe the bug
When loading my own dataset, on loading it I get an error.
Here is my dataset link: https://huggingface.co/datasets/corentinm7/MyoQuant-SDH-Data
And the error after loading with:
```python
from datasets import load_dataset
load_dataset("corentinm7/MyoQuant-SDH-Data")
```
```python
Downloading readme: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3.34k/3.34k [00:00<00:00, 4.45MB/s]
Using custom data configuration SDH_16k-53e7301a92ab0025
Downloading and preparing dataset None/SDH_16k to /home/corentin/.cache/huggingface/datasets/corentinm7___imagefolder/SDH_16k-53e7301a92ab0025/0.0.0/37fbb85cc714a338bea574ac6c7d0b5be5aff46c1862c1989b20e0771199e93f...
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3.28M/3.28M [00:00<00:00, 4.31MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:01<00:00, 1.75s/it]
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1.13G/1.13G [00:15<00:00, 74.3MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:16<00:00, 16.09s/it]
Extracting data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:13<00:00, 13.16s/it]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/load.py", line 1742, in load_dataset
builder_instance.download_and_prepare(
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/builder.py", line 814, in download_and_prepare
self._download_and_prepare(
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1423, in _download_and_prepare
super()._download_and_prepare(
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/builder.py", line 905, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1374, in _prepare_split
for key, record in logging.tqdm(
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/tqdm/std.py", line 1195, in __iter__
for obj in iterable:
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 394, in _generate_examples
raise ValueError(
ValueError: One or several metadata. were found, but not in the same directory or in a parent directory of /home/corentin/.cache/huggingface/datasets/downloads/extracted/60c4aa8d4da3065bb3d310de4373dffd73bd4dc331aedcb4ee867febe4fdb7cd/validation/sick/2_CG_SDH_TAM_Bin1cKO_ko_pla_4_1640.tif.
```
However the test command is working fine. ```datasets-cli test hugging_face_play/ds_test/SDH_16k.py --save_info --all_configs --force_redownload```
```
Using custom data configuration SDH_16k
Testing builder 'SDH_16k' (1/1)
Downloading and preparing dataset sdh_16k/SDH_16k to /home/corentin/.cache/huggingface/datasets/sdh_16k/SDH_16k/1.0.0/21b584239a638aeeda33cba1ac2ca4869d48e4b4f20fb22274d5a5ddc487659d...
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1.13G/1.13G [00:14<00:00, 76.5MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:15<00:00, 15.66s/it]
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3.28M/3.28M [00:02<00:00, 1.44MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:03<00:00, 3.21s/it]
Downloading data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11586.48it/s]
Extracting data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:13<00:00, 13.42s/it]
Dataset sdh_16k downloaded and prepared to /home/corentin/.cache/huggingface/datasets/sdh_16k/SDH_16k/1.0.0/21b584239a638aeeda33cba1ac2ca4869d48e4b4f20fb22274d5a5ddc487659d. Subsequent calls will reuse this data.
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 605.27it/s]
Dataset card saved at hugging_face_play/ds_test/README.md
Test successful.
```
### Steps to reproduce the bug
Simply run on python
```python
from datasets import load_dataset
load_dataset("corentinm7/MyoQuant-SDH-Data")
```
### Expected behavior
As the test command worked, this error should not appear
### Environment info
- `datasets` version: 2.6.1
- Platform: Linux-5.10.16.3-microsoft-standard-WSL2-x86_64-with-glibc2.31
- Python version: 3.10.6
- PyArrow version: 10.0.0
- Pandas version: 1.5.1
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"Also unrelated but still: https://huggingface.co/docs/datasets/image_dataset#generate-the-dataset\r\n```If your loading script passed the test, you should now have a dataset_infos.json file in your dataset folder.```\r\nIt's not the case anymore as it's now in the readme.md, it was confusing to me",
"And here is... |
https://api.github.com/repos/huggingface/datasets/issues/5336 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5336/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5336/comments | https://api.github.com/repos/huggingface/datasets/issues/5336/events | https://github.com/huggingface/datasets/pull/5336 | 1,479,649,900 | PR_kwDODunzps5Egzed | 5,336 | Set `IterableDataset.map` param `batch_size` typing as optional | [] | closed | false | null | 3 | 2022-12-06T17:08:10Z | 2022-12-07T14:14:56Z | 2022-12-07T14:06:27Z | null | This PR solves #5325
~Indeed we're using the typing for optional values as `Union[type, None]` as it's similar to how Python 3.10 handles optional values as `type | None`, instead of using `Optional[type]`.~
~Do we want to start using `Union[type, None]` for type-hinting optional values or just keep on using `Optional`?~ -> Keeping `Optional` still for consistency with the rest of the code in `datasets`
Also we now allow `batch_size` to be `None` for `IterableDataset.map` and `IterableDataset.filter`e.g. `MappedExamplesIterable` as `map` is internally instantiating those and propagating the `batch_size` param so if it can be `None` for `map` it should also do so for `MappedExamplesIterable`, as well as for `FilteredExamplesIterable` when calling `IterableDataset.filter`.
## TODOs
- [x] Add integration tests
- [x] Handle scenario where `batched=True` and `batch_size=None` or `batch_size<=0` | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5336). All of your documentation changes will be reflected on that endpoint.",
"Hi @mariosasko, @lhoestq I was wondering whether we should include `batched` as a `pytest.mark` param for the functions testing `IterableDataset.ma... |
https://api.github.com/repos/huggingface/datasets/issues/4471 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4471/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4471/comments | https://api.github.com/repos/huggingface/datasets/issues/4471/events | https://github.com/huggingface/datasets/issues/4471 | 1,267,475,268 | I_kwDODunzps5LjCNE | 4,471 | CI error with repo lhoestq/_dummy | [
{
"color": "d73a4a",
"default": true,
"description": "Something isn't working",
"id": 1935892857,
"name": "bug",
"node_id": "MDU6TGFiZWwxOTM1ODkyODU3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
}
] | closed | false | null | 1 | 2022-06-10T12:26:06Z | 2022-06-10T13:24:53Z | 2022-06-10T13:24:53Z | null | ## Describe the bug
CI is failing because of repo "lhoestq/_dummy". See: https://app.circleci.com/pipelines/github/huggingface/datasets/12461/workflows/1b040b45-9578-4ab9-8c44-c643c4eb8691/jobs/74269
```
requests.exceptions.HTTPError: 401 Client Error: Unauthorized for url: https://huggingface.co/api/datasets/lhoestq/_dummy?full=true
```
The repo seems to no longer exist: https://huggingface.co/api/datasets/lhoestq/_dummy
```
error: "Repository not found"
```
CC: @lhoestq | {
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"fixed by https://github.com/huggingface/datasets/pull/4472"
] |
https://api.github.com/repos/huggingface/datasets/issues/2070 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2070/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2070/comments | https://api.github.com/repos/huggingface/datasets/issues/2070/events | https://github.com/huggingface/datasets/issues/2070 | 833,799,035 | MDU6SXNzdWU4MzM3OTkwMzU= | 2,070 | ArrowInvalid issue for squad v2 dataset | [] | closed | false | null | 1 | 2021-03-17T13:51:49Z | 2021-08-04T17:57:16Z | 2021-08-04T17:57:16Z | null | Hello, I am using the huggingface official question answering example notebook (https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/question_answering.ipynb).
In the prepare_validation_features function, I made some modifications to tokenize a new set of quesions with the original contexts and save them in three different list called candidate_input_dis, candidate_attetion_mask and candidate_token_type_ids. When I try to run the next cell for dataset.map, I got the following error:
`ArrowInvalid: Column 1 named candidate_attention_mask expected length 1180 but got length 1178`
My code is as follows:
```
def generate_candidate_questions(examples):
val_questions = examples["question"]
candididate_questions = random.sample(datasets["train"]["question"], len(val_questions))
candididate_questions = [x[:max_length] for x in candididate_questions]
return candididate_questions
def prepare_validation_features(examples, use_mixing=False):
pad_on_right = tokenizer.padding_side == "right"
tokenized_examples = tokenizer(
examples["question" if pad_on_right else "context"],
examples["context" if pad_on_right else "question"],
truncation="only_second" if pad_on_right else "only_first",
max_length=max_length,
stride=doc_stride,
return_overflowing_tokens=True,
return_offsets_mapping=True,
padding="max_length",
)
if use_mixing:
candidate_questions = generate_candidate_questions(examples)
tokenized_candidates = tokenizer(
candidate_questions if pad_on_right else examples["context"],
examples["context"] if pad_on_right else candidate_questions,
truncation="only_second" if pad_on_right else "only_first",
max_length=max_length,
stride=doc_stride,
return_overflowing_tokens=True,
return_offsets_mapping=True,
padding="max_length",
)
sample_mapping = tokenized_examples.pop("overflow_to_sample_mapping")
tokenized_examples["example_id"] = []
if use_mixing:
tokenized_examples["candidate_input_ids"] = tokenized_candidates["input_ids"]
tokenized_examples["candidate_attention_mask"] = tokenized_candidates["attention_mask"]
tokenized_examples["candidate_token_type_ids"] = tokenized_candidates["token_type_ids"]
for i in range(len(tokenized_examples["input_ids"])):
sequence_ids = tokenized_examples.sequence_ids(i)
context_index = 1 if pad_on_right else 0
sample_index = sample_mapping[i]
tokenized_examples["example_id"].append(examples["id"][sample_index])
tokenized_examples["offset_mapping"][i] = [
(o if sequence_ids[k] == context_index else None)
for k, o in enumerate(tokenized_examples["offset_mapping"][i])
]
return tokenized_examples
validation_features = datasets["validation"].map(
lambda xs: prepare_validation_features(xs, True),
batched=True,
remove_columns=datasets["validation"].column_names
)
```
I guess this might happen because of the batched=True. I see similar issues in this repo related to arrow table length mismatch error, but in their cases, the numbers vary a lot. In my case, this error always happens when the expected length and unexpected length are very close. Thanks for the help! | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2070/timeline | null | completed | null | null | false | [
"Hi ! This error happens when you use `map` in batched mode and then your function doesn't return the same number of values per column.\r\n\r\nIndeed since you're using `map` in batched mode, `prepare_validation_features` must take a batch as input (i.e. a dictionary of multiple rows of the dataset), and return a b... |
https://api.github.com/repos/huggingface/datasets/issues/3082 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3082/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3082/comments | https://api.github.com/repos/huggingface/datasets/issues/3082/events | https://github.com/huggingface/datasets/pull/3082 | 1,026,388,994 | PR_kwDODunzps4tM2BV | 3,082 | Fix error related to huggingface_hub timeout parameter | [] | closed | false | null | 0 | 2021-10-14T13:17:47Z | 2021-10-14T14:39:52Z | 2021-10-14T14:39:51Z | null | The `huggingface_hub` package added the parameter `timeout` from version 0.0.19.
This PR bumps this minimal version.
Fix #3080. | {
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https://api.github.com/repos/huggingface/datasets/issues/6043 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6043/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6043/comments | https://api.github.com/repos/huggingface/datasets/issues/6043/events | https://github.com/huggingface/datasets/issues/6043 | 1,807,771,750 | I_kwDODunzps5rwGhm | 6,043 | Compression kwargs have no effect when saving datasets as csv | [] | open | false | null | 3 | 2023-07-17T13:19:21Z | 2023-07-22T17:34:18Z | null | null | ### Describe the bug
Attempting to save a dataset as a compressed csv file, the compression kwargs provided to `.to_csv()` that get piped to panda's `pandas.DataFrame.to_csv` do not have any effect - resulting in the dataset not getting compressed.
A warning is raised if explicitly providing a `compression` kwarg, but no warnings are raised if relying on the defaults. This can lead to datasets secretly not getting compressed for users expecting the behaviour to match panda's `.to_csv()`, where the compression format is automatically inferred from the destination path suffix.
### Steps to reproduce the bug
```python
# dataset is not compressed (but at least a warning is emitted)
import datasets
dataset = datasets.load_dataset("rotten_tomatoes", split="train")
dataset.to_csv("uncompressed.csv")
print(os.path.getsize("uncompressed.csv")) # 1008607
dataset.to_csv("compressed.csv.gz", compression={'method': 'gzip', 'compresslevel': 1, 'mtime': 1})
print(os.path.getsize("compressed.csv.gz")) # 1008607
```
```shell
>>>
RuntimeWarning: compression has no effect when passing a non-binary object as input.
csv_str = batch.to_pandas().to_csv(
```
```python
# dataset is not compressed and no warnings are emitted
dataset.to_csv("compressed.csv.gz")
print(os.path.getsize("compressed.csv.gz")) # 1008607
# compare with
dataset.to_pandas().to_csv("pandas.csv.gz")
print(os.path.getsize("pandas.csv.gz")) # 418561
```
---
I think that this is because behind the scenes `pandas.DataFrame.to_csv` is always called with a buf-like `path_or_buf`, but users that are providing a path-like to `datasets.Dataset.to_csv` are likely not to expect / know that - leading to a mismatch in their understanding of the expected behaviour of the `compression` kwarg.
### Expected behavior
The dataset to be saved as a compressed csv file when providing a `compression` kwarg, or when relying on the default `compression='infer'`
### Environment info
`datasets == 2.13.1`
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"Hello @exs-avianello, I have reproduced the bug successfully and have understood the problem. But I am confused regarding this part of the statement, \"`pandas.DataFrame.to_csv` is always called with a buf-like `path_or_buf`\".\r\n\r\nCan you please elaborate on it?\r\n\r\nThanks!",
"Hi @aryanxk02 ! Sure, what I... |
https://api.github.com/repos/huggingface/datasets/issues/3149 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3149/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3149/comments | https://api.github.com/repos/huggingface/datasets/issues/3149/events | https://github.com/huggingface/datasets/pull/3149 | 1,033,747,625 | PR_kwDODunzps4tjuUt | 3,149 | Add CMU Hinglish DoG Dataset for MT | [] | closed | false | null | 2 | 2021-10-22T16:17:25Z | 2021-11-15T11:36:42Z | 2021-11-15T10:27:45Z | null | Address part of #2841
Added the CMU Hinglish DoG Dataset as in GLUECoS. Added it as a seperate dataset as unlike other tasks of GLUE CoS this can't be evaluated for a BERT like model.
Consists of parallel dataset between Hinglish (Hindi-English) and English, can be used for Machine Translation between the two.
The data processing part is inspired from the GLUECoS repo [here](https://github.com/microsoft/GLUECoS/blob/7fdc51653e37a32aee17505c47b7d1da364fa77e/Data/Preprocess_Scripts/preprocess_mt_en_hi.py)
The dummy data part is not working properly, it shows
``` UnboundLocalError: local variable 'generator_splits' referenced before assignment ```
when I run without ``--auto_generate``.
Please let me know how I can fix that.
Thanks | {
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"Hi @lhoestq, thanks a lot for the help. I have moved the part as suggested. \r\nAlthough still while running the dummy data script, I face this issue\r\n\r\n```\r\nTraceback (most recent call last):\r\n File \"/home/ishan/anaconda3/bin/datasets-cli\", line 8, in <module>\r\n sys.exit(main())\r\n File \"/home/... |
https://api.github.com/repos/huggingface/datasets/issues/314 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/314/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/314/comments | https://api.github.com/repos/huggingface/datasets/issues/314/events | https://github.com/huggingface/datasets/pull/314 | 645,461,174 | MDExOlB1bGxSZXF1ZXN0NDM5OTM4MTMw | 314 | Fixed singlular very minor spelling error | [] | closed | false | null | 1 | 2020-06-25T10:45:59Z | 2020-06-26T08:46:41Z | 2020-06-25T12:43:59Z | null | An instance of "independantly" was changed to "independently". That's all. | {
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"Thank you BatJeti! The storm-joker, aka the typo, finally got caught!"
] |
https://api.github.com/repos/huggingface/datasets/issues/5073 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5073/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5073/comments | https://api.github.com/repos/huggingface/datasets/issues/5073/events | https://github.com/huggingface/datasets/pull/5073 | 1,397,832,183 | PR_kwDODunzps5AN3Gn | 5,073 | Restore saved format state in `load_from_disk` | [] | closed | false | null | 1 | 2022-10-05T13:51:47Z | 2022-10-11T16:55:07Z | 2022-10-11T16:49:23Z | null | Hello! @mariosasko
This pull request relates to issue #5050 and intends to add the format to datasets loaded from disk.
All I did was add a set_format in the Dataset.load_from_disk, as DatasetDict.load_from_disk relies on the first.
I don't know if I should add a test and where, so let me know if I should and I can work on that as well!
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/4201 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4201/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4201/comments | https://api.github.com/repos/huggingface/datasets/issues/4201/events | https://github.com/huggingface/datasets/pull/4201 | 1,212,086,420 | PR_kwDODunzps42nIRm | 4,201 | Update GH template for dataset viewer issues | [] | closed | false | null | 2 | 2022-04-22T09:34:44Z | 2022-05-06T08:38:43Z | 2022-04-26T08:45:55Z | null | Update template to use new issue forms instead.
With this PR we can check if this new feature is useful for us.
Once validated, we can update the other templates.
CC: @severo | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"You can see rendering at: https://github.com/huggingface/datasets/blob/6b48fedbdafe12a42c7b6edcecc32820af1a4822/.github/ISSUE_TEMPLATE/dataset-viewer.yml"
] |
https://api.github.com/repos/huggingface/datasets/issues/3781 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3781/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3781/comments | https://api.github.com/repos/huggingface/datasets/issues/3781/events | https://github.com/huggingface/datasets/pull/3781 | 1,148,599,680 | PR_kwDODunzps4zXr_O | 3,781 | Reddit dataset card additions | [] | closed | false | null | 1 | 2022-02-23T21:29:16Z | 2022-02-28T18:00:40Z | 2022-02-28T11:21:14Z | null | The changes proposed are based on the "TL;DR: Mining Reddit to Learn Automatic Summarization" paper & https://zenodo.org/record/1043504#.YhaKHpbQC38
It is a Reddit dataset indeed, but the name given to the dataset by the authors is Webis-TLDR-17 (corpus), so perhaps it should be modified as well.
The task at which the dataset is aimed is abstractive summarization.
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"Hello! I added the tags and created a PR. Just to note, regarding the paperswithcode_id tag, that currently has the value \"reddit\"; the dataset described as reddit in paperswithcode is https://paperswithcode.com/dataset/reddit and it isn't the Webis-tldr-17. I could not find Webis-tldr-17 in paperswithcode neith... |
https://api.github.com/repos/huggingface/datasets/issues/3425 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3425/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3425/comments | https://api.github.com/repos/huggingface/datasets/issues/3425/events | https://github.com/huggingface/datasets/issues/3425 | 1,078,598,140 | I_kwDODunzps5AShn8 | 3,425 | Getting configs names takes too long | [
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] | open | false | null | 3 | 2021-12-13T14:27:57Z | 2021-12-13T14:53:33Z | null | null |
## Steps to reproduce the bug
```python
from datasets import get_dataset_config_names
get_dataset_config_names("allenai/c4")
```
## Expected results
I would expect to get the answer quickly, at least in less than 10s
## Actual results
It takes about 45s on my environment
## Environment info
- `datasets` version: 1.16.1
- Platform: Linux-5.11.0-1022-aws-x86_64-with-glibc2.31
- Python version: 3.9.6
- PyArrow version: 4.0.1 | {
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"maybe related to https://github.com/huggingface/datasets/issues/2859\r\n",
"It looks like it's currently calling `HfFileSystem.ls()` ~8 times at the root and for each subdirectory:\r\n- \"\"\r\n- \"en.noblocklist\"\r\n- \"en.noclean\"\r\n- \"en\"\r\n- \"multilingual\"\r\n- \"realnewslike\"\r\n\r\nCurrently `ls` ... |
https://api.github.com/repos/huggingface/datasets/issues/5052 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5052/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5052/comments | https://api.github.com/repos/huggingface/datasets/issues/5052/events | https://github.com/huggingface/datasets/pull/5052 | 1,393,076,765 | PR_kwDODunzps4_-PZw | 5,052 | added from_generator method to IterableDataset class. | [] | closed | false | null | 3 | 2022-09-30T22:14:05Z | 2022-10-05T12:51:48Z | 2022-10-05T12:10:48Z | null | Hello,
This resolves issues #4988.
I added a method `from_generator` to class `IterableDataset`.
I modified the `read` method of input stream generator to also return Iterable_dataset.
| {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I added a test and moved the `streaming` param from `read` to `__init_`. Then, I also decided to update the `read` method of the rest of the packaged modules to account for this param. \r\n\r\n@hamid-vakilzadeh Are you OK with these ... |
https://api.github.com/repos/huggingface/datasets/issues/4680 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4680/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4680/comments | https://api.github.com/repos/huggingface/datasets/issues/4680/events | https://github.com/huggingface/datasets/issues/4680 | 1,304,534,770 | I_kwDODunzps5NwZ7y | 4,680 | Dataset Viewer issue for codeparrot/xlcost-text-to-code | [] | closed | false | null | 5 | 2022-07-14T09:45:50Z | 2022-07-18T16:37:00Z | 2022-07-18T16:04:36Z | null | ### Link
https://huggingface.co/datasets/codeparrot/xlcost-text-to-code
### Description
Error
```
Server Error
Status code: 400
Exception: TypeError
Message: 'NoneType' object is not iterable
```
Before I did a minor change in the dataset script (removing some comments), the viewer was working but not properely, it wasn't showing the dataset subsets. But the data can be loaded successfully.
Thanks!
### Owner
Yes | {
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"There seems to be an issue with the `C++-snippet-level` config:\r\n\r\n```python\r\n>>> from datasets import get_dataset_split_names\r\n>>> get_dataset_split_names(\"codeparrot/xlcost-text-to-code\", \"C++-snippet-level\")\r\nTraceback (most recent call last):\r\n File \"/home/slesage/hf/datasets-server/services/... |
https://api.github.com/repos/huggingface/datasets/issues/3767 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3767/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3767/comments | https://api.github.com/repos/huggingface/datasets/issues/3767/events | https://github.com/huggingface/datasets/pull/3767 | 1,146,036,648 | PR_kwDODunzps4zPahh | 3,767 | Expose method and fix param | [] | closed | false | null | 0 | 2022-02-21T16:57:47Z | 2022-02-22T08:35:03Z | 2022-02-22T08:35:02Z | null | A fix + expose a new method, following https://github.com/huggingface/datasets/pull/3670 | {
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https://api.github.com/repos/huggingface/datasets/issues/465 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/465/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/465/comments | https://api.github.com/repos/huggingface/datasets/issues/465/events | https://github.com/huggingface/datasets/pull/465 | 669,889,779 | MDExOlB1bGxSZXF1ZXN0NDYwMjEwODYw | 465 | Keep features after transform | [] | closed | false | null | 3 | 2020-07-31T14:43:21Z | 2020-07-31T18:27:33Z | 2020-07-31T18:27:32Z | null | When applying a transform like `map`, some features were lost (and inferred features were used).
It was the case for ClassLabel, Translation, etc.
To fix that, I did some modifications in the `ArrowWriter`:
- added the `update_features` parameter. When it's `True`, then the features specified by the user (if any) can be updated with inferred features if their type don't match. `map` transform sets `update_features=True` when writing to cache file or buffer. Features won't change by default in `map`.
- added the `with_metadata` parameter. If `True`, the `features` (after update) will be written inside the metadata of the schema in this format:
```
{
"huggingface": {"features" : <serialized Features exactly like dataset_info.json>}
}
```
Then, once a dataset is instantiated without info/features, these metadata are used to set the features of the dataset. | {
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"One note on features inference:\r\n\r\nif an arrow type is `struct of items` where each item is a `list`, then we return a `dict` in which each item is a `Sequence`.\r\nIt means that we don't use the Sequence <-> dict swap when we infer features.\r\n\r\nIt's fine because the swap is generally used in dataset scrip... |
https://api.github.com/repos/huggingface/datasets/issues/1216 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1216/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1216/comments | https://api.github.com/repos/huggingface/datasets/issues/1216/events | https://github.com/huggingface/datasets/pull/1216 | 758,005,982 | MDExOlB1bGxSZXF1ZXN0NTMzMjU0ODE2 | 1,216 | Add limit | [] | closed | false | null | 1 | 2020-12-06T19:46:18Z | 2020-12-08T07:52:11Z | 2020-12-08T07:52:11Z | null | This PR adds [LiMiT](https://github.com/ilmgut/limit_dataset), a dataset for literal motion classification/extraction by [Manotas et al., 2020](https://www.aclweb.org/anthology/2020.findings-emnlp.88.pdf). | {
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"My bad, didn't see this on the open dataset list. Closing this since it overlaps with PR#1256"
] |
https://api.github.com/repos/huggingface/datasets/issues/28 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/28/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/28/comments | https://api.github.com/repos/huggingface/datasets/issues/28/events | https://github.com/huggingface/datasets/pull/28 | 610,241,907 | MDExOlB1bGxSZXF1ZXN0NDExNzE5MTQy | 28 | [Circle ci] Adds circle ci config | [] | closed | false | null | 0 | 2020-04-30T17:03:35Z | 2020-04-30T19:51:09Z | 2020-04-30T19:51:08Z | null | @thomwolf can you take a look and set up circle ci on:
https://app.circleci.com/projects/project-dashboard/github/huggingface
I think for `nlp` only admins can set it up, which I guess is you :-) | {
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https://api.github.com/repos/huggingface/datasets/issues/4939 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4939/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4939/comments | https://api.github.com/repos/huggingface/datasets/issues/4939/events | https://github.com/huggingface/datasets/pull/4939 | 1,363,468,679 | PR_kwDODunzps4-cw4A | 4,939 | Fix NonMatchingChecksumError in adv_glue dataset | [] | closed | false | null | 1 | 2022-09-06T15:31:16Z | 2022-09-06T17:42:10Z | 2022-09-06T17:39:16Z | null | Fix issue reported on the Hub: https://huggingface.co/datasets/adv_glue/discussions/1 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/3291 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3291/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3291/comments | https://api.github.com/repos/huggingface/datasets/issues/3291/events | https://github.com/huggingface/datasets/pull/3291 | 1,056,689,876 | PR_kwDODunzps4urikR | 3,291 | Use f-strings in the dataset scripts | [] | closed | false | null | 0 | 2021-11-17T22:20:19Z | 2021-11-22T16:40:16Z | 2021-11-22T16:40:16Z | null | Uses f-strings to format the .py files in the dataset folder | {
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https://api.github.com/repos/huggingface/datasets/issues/4911 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4911/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4911/comments | https://api.github.com/repos/huggingface/datasets/issues/4911/events | https://github.com/huggingface/datasets/issues/4911 | 1,354,426,978 | I_kwDODunzps5Quupi | 4,911 | [Tests] Ensure `datasets` supports renamed repositories | [
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] | open | false | null | 1 | 2022-08-29T14:46:14Z | 2022-08-29T15:31:03Z | null | null | On https://hf.co/datasets you can rename a dataset (or sometimes move it to another user/org). The website handles redirections correctly and AFAIK `datasets` does as well.
However it would be nice to have an integration test to make sure we don't break support for renamed datasets.
To implement this we can use the /api/repos/move endpoint on hub-ci to rename/move a repo (it is documented at https://huggingface.co/docs/hub/api) | {
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"You could also switch to using `huggingface_hub` more directly, where such a guarantee is already tested =)\r\n\r\ncc @Wauplin "
] |
https://api.github.com/repos/huggingface/datasets/issues/5835 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5835/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5835/comments | https://api.github.com/repos/huggingface/datasets/issues/5835/events | https://github.com/huggingface/datasets/pull/5835 | 1,702,522,620 | PR_kwDODunzps5QHquR | 5,835 | Always set nullable fields in the writer | [] | closed | false | null | 4 | 2023-05-09T18:16:59Z | 2023-05-23T16:10:29Z | 2023-05-19T13:04:30Z | null | This fixes loading of e.g. parquet data with non-nullable fields.
Indeed `datasets.Features` doesn't support non-nullable fields, which can lead to data not concatenable due to arrow schema mismatch. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/463 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/463/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/463/comments | https://api.github.com/repos/huggingface/datasets/issues/463/events | https://github.com/huggingface/datasets/pull/463 | 669,735,455 | MDExOlB1bGxSZXF1ZXN0NDYwMDcyNjQ1 | 463 | Add dataset/mlsum | [] | closed | false | null | 3 | 2020-07-31T11:50:52Z | 2020-08-24T14:54:42Z | 2020-08-24T14:54:42Z | null | New pull request that should correct the previous errors.
The load_real_data stills fails because it is looking for a default dataset URL that does not exists, this does not happen when loading the dataset with load_dataset | {
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"I think the problem is related to `wiki_dpr` dataset which is making the circle CI failed as you can see:\r\n```\r\nFAILED tests/test_dataset_common.py::AWSDatasetTest::test_load_dataset_wiki_dpr\r\nFAILED tests/test_hf_gcp.py::TestDatasetOnHfGcp::test_script_synced_with_s3_wiki_dpr/dummy_psgs_w100_no_embeddings\r... |
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 | [] | closed | false | null | 3 | 2023-02-27T17:04:46Z | 2023-02-28T13:52:15Z | 2023-02-28T13:44:04Z | 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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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/1556 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1556/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1556/comments | https://api.github.com/repos/huggingface/datasets/issues/1556/events | https://github.com/huggingface/datasets/pull/1556 | 765,689,730 | MDExOlB1bGxSZXF1ZXN0NTM5MDM2OTYz | 1,556 | add bswac | [] | closed | false | null | 1 | 2020-12-13T22:55:35Z | 2020-12-18T15:14:28Z | 2020-12-18T15:14:27Z | null | {
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"merging since the CI is fixed on master"
] | |
https://api.github.com/repos/huggingface/datasets/issues/696 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/696/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/696/comments | https://api.github.com/repos/huggingface/datasets/issues/696/events | https://github.com/huggingface/datasets/pull/696 | 712,942,977 | MDExOlB1bGxSZXF1ZXN0NDk2MzQzMjEy | 696 | Elasticsearch index docs | [] | closed | false | null | 0 | 2020-10-01T15:18:58Z | 2020-10-02T07:48:19Z | 2020-10-02T07:48:18Z | null | I added the docs for ES indexes.
I also added a `load_elasticsearch_index` method to load an index that has already been built.
I checked the tests for the ES index and we have tests that mock ElasticSearch.
I think this is good for now but at some point it would be cool to have an end-to-end test with a real ES running. | {
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https://api.github.com/repos/huggingface/datasets/issues/3003 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3003/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3003/comments | https://api.github.com/repos/huggingface/datasets/issues/3003/events | https://github.com/huggingface/datasets/pull/3003 | 1,014,137,933 | PR_kwDODunzps4smExP | 3,003 | common_language: Fix license in README.md | [] | closed | false | null | 0 | 2021-10-02T18:47:37Z | 2021-10-04T09:27:01Z | 2021-10-04T09:27:01Z | null | ...it's correct elsewhere | {
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https://api.github.com/repos/huggingface/datasets/issues/289 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/289/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/289/comments | https://api.github.com/repos/huggingface/datasets/issues/289/events | https://github.com/huggingface/datasets/pull/289 | 641,934,194 | MDExOlB1bGxSZXF1ZXN0NDM3MDc0MTM3 | 289 | update xsum | [] | closed | false | null | 3 | 2020-06-19T12:28:32Z | 2020-06-22T13:27:26Z | 2020-06-22T07:20:07Z | null | This PR makes the following update to the xsum dataset:
- Manual download is not required anymore
- dataset can be loaded as follow: `nlp.load_dataset('xsum')`
**Important**
Instead of using on outdated url to download the data: "https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum-TRAINING-DEV-TEST-SPLIT-90-5-5.json"
a more up-to-date url stored here: https://s3.amazonaws.com/datasets.huggingface.co/summarization/xsum.tar.gz is used
, so that the user does not need to manually download the data anymore.
There might be slight breaking changes here for xsum. | {
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"Looks cool!\r\n@mariamabarham can you add a detailed description here what exactly is changed and how the user can load xsum now?",
"And a rebase should solve the conflicts",
"This is a super useful PR :-) @sshleifer - maybe you can take a look at the updated version of xsum if you can use it for your use case... |
https://api.github.com/repos/huggingface/datasets/issues/2742 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2742/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2742/comments | https://api.github.com/repos/huggingface/datasets/issues/2742/events | https://github.com/huggingface/datasets/issues/2742 | 958,114,064 | MDU6SXNzdWU5NTgxMTQwNjQ= | 2,742 | Improve detection of streamable file types | [
{
"color": "a2eeef",
"default": true,
"description": "New feature or request",
"id": 1935892871,
"name": "enhancement",
"node_id": "MDU6TGFiZWwxOTM1ODkyODcx",
"url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement"
},
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"default": fals... | closed | false | null | 1 | 2021-08-02T12:55:09Z | 2021-11-12T17:18:10Z | 2021-11-12T17:18:10Z | null | **Is your feature request related to a problem? Please describe.**
```python
from datasets import load_dataset_builder
from datasets.utils.streaming_download_manager import StreamingDownloadManager
builder = load_dataset_builder("journalists_questions", name="plain_text")
builder._split_generators(StreamingDownloadManager(base_path=builder.base_path))
```
raises
```
NotImplementedError: Extraction protocol for file at https://drive.google.com/uc?export=download&id=1CBrh-9OrSpKmPQBxTK_ji6mq6WTN_U9U is not implemented yet
```
But the file at https://drive.google.com/uc?export=download&id=1CBrh-9OrSpKmPQBxTK_ji6mq6WTN_U9U is a text file and it can be streamed:
```bash
curl --header "Range: bytes=0-100" -L https://drive.google.com/uc\?export\=download\&id\=1CBrh-9OrSpKmPQBxTK_ji6mq6WTN_U9U
506938088174940160 yes 1
302221719412830209 yes 1
289761704907268096 yes 1
513820885032378369 yes %
```
Yet, it's wrongly categorized as a file type that cannot be streamed because the test is currently based on 1. the presence of a file extension at the end of the URL (here: no extension), and 2. the inclusion of this extension in a list of supported formats.
**Describe the solution you'd like**
In the case of an URL (instead of a local path), ask for the MIME type, and decide on that value? Note that it would not work in that case, because the value of `content_type` is `text/html; charset=UTF-8`.
**Describe alternatives you've considered**
Add a variable in the dataset script to set the data format by hand.
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"maybe we should rather attempt to download a `Range` from the server and see if it works?"
] |
https://api.github.com/repos/huggingface/datasets/issues/1454 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1454/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1454/comments | https://api.github.com/repos/huggingface/datasets/issues/1454/events | https://github.com/huggingface/datasets/pull/1454 | 761,199,862 | MDExOlB1bGxSZXF1ZXN0NTM1OTAxNjk4 | 1,454 | Add kinnews_kirnews | [] | closed | false | null | 1 | 2020-12-10T12:29:08Z | 2020-12-17T18:34:16Z | 2020-12-17T18:34:16Z | null | Add kinnews and kirnews | {
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"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/1329 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1329/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1329/comments | https://api.github.com/repos/huggingface/datasets/issues/1329/events | https://github.com/huggingface/datasets/pull/1329 | 759,654,174 | MDExOlB1bGxSZXF1ZXN0NTM0NjIxNzg0 | 1,329 | Add yoruba ner corpus | [] | closed | false | null | 0 | 2020-12-08T17:54:00Z | 2020-12-08T23:11:12Z | 2020-12-08T23:11:12Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4326 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4326/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4326/comments | https://api.github.com/repos/huggingface/datasets/issues/4326/events | https://github.com/huggingface/datasets/pull/4326 | 1,233,818,489 | PR_kwDODunzps43tjWy | 4,326 | Fix type hint and documentation for `new_fingerprint` | [] | closed | false | null | 1 | 2022-05-12T11:05:08Z | 2022-06-01T13:04:45Z | 2022-06-01T12:56:18Z | null | Currently, there are no type hints nor `Optional` for the argument `new_fingerprint` in several methods of `datasets.arrow_dataset.Dataset`.
There was some documentation missing as well.
Note that pylance is happy with the type hints, but pyright does not detect that `new_fingerprint` is set within the decorator.
The modifications in this PR are fine since here https://github.com/huggingface/datasets/blob/aa743886221d76afb409d263e1b136e7a71fe2b4/src/datasets/fingerprint.py#L446-L454
for the non-inplace case we make sure to auto-generate a new fingerprint (as indicated in the doc). | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/393 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/393/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/393/comments | https://api.github.com/repos/huggingface/datasets/issues/393/events | https://github.com/huggingface/datasets/pull/393 | 657,330,911 | MDExOlB1bGxSZXF1ZXN0NDQ5NDY1MTAz | 393 | Fix extracted files directory for the DownloadManager | [] | closed | false | null | 0 | 2020-07-15T12:59:55Z | 2020-07-17T17:02:16Z | 2020-07-17T17:02:14Z | null | The cache dir was often cluttered by extracted files because of the download manager.
For downloaded files, we are using the `downloads` directory to make things easier to navigate, but extracted files were still placed at the root of the cache directory. To fix that I changed the directory for extracted files to cache_dir/downloads/extracted. | {
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https://api.github.com/repos/huggingface/datasets/issues/3575 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3575/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3575/comments | https://api.github.com/repos/huggingface/datasets/issues/3575/events | https://github.com/huggingface/datasets/pull/3575 | 1,101,947,955 | PR_kwDODunzps4w8Usm | 3,575 | Add Arrow type casting to struct for Image and Audio + Support nested casting | [] | closed | false | null | 9 | 2022-01-13T15:36:59Z | 2022-11-29T11:14:16Z | 2022-01-21T13:22:27Z | null | ## Intro
1. Currently, it's not possible to have nested features containing Audio or Image.
2. Moreover one can keep an Arrow array as a StringArray to store paths to images, but such arrays can't be directly concatenated to another image array if it's stored an another Arrow type (typically, a StructType).
3. Allowing several Arrow types for a single HF feature type also leads to bugs like this one #3497
4. Issues like #3247 are quite frequent and happen when Arrow fails to reorder StructArrays.
5. Casting Audio feature type is blocking preparation for the ASR task template: https://github.com/huggingface/datasets/pull/3364
All those issues are linked together by the fact that:
- we are limited by the Arrow type casting which is lacking features for nested types.
- and especially for Audio and Image: they are not robust enough for concatenation and feature inference.
## Proposed solution
To fix 1 and 4 I implemented nested array type casting (which is missing in PyArrow).
To fix 2, 3 and 5 while having a simple implementation for nested array type casting, I changed the storage type of Audio and Image to always be a StructType. Also casting from StringType is directly implemented via a new function `cast_storage` that is defined individually for Audio and Image. I also added nested decoding.
## Implementation details
### I. Better Arrow data type casting for nested data structures
I implemented new functions `array_cast` and `table_cast` that do the exact same as `pyarrow.Array.cast` or `pyarrow.Table.cast` but support nested struct casting and array re-ordering.
These functions can be used on PyArrow objects, and are already integrated in our own `datasets.table.Table.cast` functions. So one can do `my_dataset.data.cast(pyarrow_schema_with_custom_hf_types)` directly.
### II. New image and audio extension types with custom casting
I used PyArrow extension types to be able to define what casting is allowed or not. For example both StringType->ImageExtensionType and StructType->ImageExtensionType are allowed, via the `cast_storage` method.
I factorized all the PyArrow + Pandas extension stuff in the `base_extension.py` file. This aims at separating the front-facing API code of `datasets` from the Arrow back-end which requires advanced knowledge.
### III. Nested feature decoding
I added a new function `decode_nested_example` to decode image and audio data in nested data structures. For optimization's sake, this function is only called if a column has at least one feature that requires decoding.
## Alternative considered
The casting to struct type could have been done directly with python objects using some Audio and Image methods, but bringing arrow data to python objects is expensive. The Audio and Image types could also have been able to convert the arrow data directly, but this is not convenient to use when casting a full Arrow Table with nested fields. Therefore I decided to keep the Arrow data casting logic in Arrow extension types.
## Future work
This work can be used to allow the ArrayND feature types to be nested too (see issue #887)
## TODO
- [x] fix current tests
- [x] add new tests
- [x] docstrings/comments | {
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"Regarding the tests I'm just missing the FixedSizeListType type casting for ListArray objects, will to it tomorrow as well as adding new tests + docstrings\r\n\r\nand also adding soundfile in the CI",
"While writing some tests I noticed that the ExtensionArray can't be directly concatenated - maybe we can get ri... |
https://api.github.com/repos/huggingface/datasets/issues/1435 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1435/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1435/comments | https://api.github.com/repos/huggingface/datasets/issues/1435/events | https://github.com/huggingface/datasets/pull/1435 | 760,867,325 | MDExOlB1bGxSZXF1ZXN0NTM1NjIwODE4 | 1,435 | Add FreebaseQA dataset | [] | closed | false | null | 12 | 2020-12-10T04:03:27Z | 2021-02-05T09:47:30Z | 2021-02-05T09:47:30Z | null | This PR adds the FreebaseQA dataset: A Trivia-type QA Data Set over the Freebase Knowledge Graph
Repo: https://github.com/kelvin-jiang/FreebaseQA
Paper: https://www.aclweb.org/anthology/N19-1028.pdf
## TODO: create dummy data
Error encountered when running `python datasets-cli dummy_data datasets/freebase_qa --auto_generate`
```
f"Couldn't parse columns {list(json_data.keys())}. "
ValueError: Couldn't parse columns ['Dataset', 'Version', 'Questions']. Maybe specify which json field must be used to read the data with --json_field <my_field>.
```
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"@yjernite @lhoestq Any suggestions on how to get the dummy data generator to recognize the columns? The structure of the json is:\r\n```\r\n{\r\n \"Dataset\": \"FreebaseQA-eval\", \r\n \"Version\": \"1.0\", \r\n \"Questions\": [\r\n {\r\n \"Question-ID\": \"FreebaseQA-eval-0\", \r\n \"RawQuestion\"... |
https://api.github.com/repos/huggingface/datasets/issues/5013 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5013/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5013/comments | https://api.github.com/repos/huggingface/datasets/issues/5013/events | https://github.com/huggingface/datasets/issues/5013 | 1,383,415,971 | I_kwDODunzps5SdUCj | 5,013 | would huggingface like publish cpp binding for datasets package ? | [
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] | closed | false | null | 5 | 2022-09-23T07:42:49Z | 2023-02-24T16:20:57Z | 2023-02-24T16:20:57Z | null | HI:
I use cpp env libtorch, I like use hugggingface ,but huggingface not cpp binding, would you like publish cpp binding for it.
thanks | {
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"Hi ! Can you share more information about your use case ? How could it help you to have cpp bindings versus using the python libraries ?",
"> Hi ! Can you share more information about your use case ? How could it help you to have cpp bindings versus using the python libraries ?\r\n\r\nfor example ,the huggingfac... |
https://api.github.com/repos/huggingface/datasets/issues/4731 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4731/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4731/comments | https://api.github.com/repos/huggingface/datasets/issues/4731/events | https://github.com/huggingface/datasets/pull/4731 | 1,313,773,348 | PR_kwDODunzps474dlZ | 4,731 | docs: ✏️ fix TranslationVariableLanguages example | [] | closed | false | null | 1 | 2022-07-21T20:35:41Z | 2022-07-22T07:01:00Z | 2022-07-22T06:48:42Z | null | null | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/5742 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5742/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5742/comments | https://api.github.com/repos/huggingface/datasets/issues/5742/events | https://github.com/huggingface/datasets/pull/5742 | 1,666,209,738 | PR_kwDODunzps5OOH-W | 5,742 | Warning specifying future change in to_tf_dataset behaviour | [] | closed | false | null | 2 | 2023-04-13T11:10:00Z | 2023-04-21T13:18:14Z | 2023-04-21T13:11:09Z | null | Warning specifying future changes happening to `to_tf_dataset` behaviour when #5602 is merged in | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/4740 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4740/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4740/comments | https://api.github.com/repos/huggingface/datasets/issues/4740/events | https://github.com/huggingface/datasets/pull/4740 | 1,316,478,007 | PR_kwDODunzps48BX5l | 4,740 | Fix multiprocessing in map_nested | [] | closed | false | null | 3 | 2022-07-25T08:44:19Z | 2022-07-28T10:53:23Z | 2022-07-28T10:40:31Z | null | As previously discussed:
Before, multiprocessing was not used in `map_nested` if `num_proc` was greater than or equal to `len(iterable)`.
- Multiprocessing was not used e.g. when passing `num_proc=20` but having 19 files to download
- As by default, `DownloadManager` sets `num_proc=16`, before multiprocessing was only used when `len(iterable)>16` by default
Now, if `num_proc` is greater than or equal to ``len(iterable)``, `num_proc` is set to ``len(iterable)`` and multiprocessing is used.
- We pass the variable `parallel_min_length=16`, so that multiprocessing is only used if at least 16 files to be downloaded
- ~As by default, `DownloadManager` sets `num_proc=16`, now multiprocessing is used when `len(iterable)>1` by default~
See discussion below.
~After having had to fix some tests (87602ac), I am wondering:~
- ~do we want to have multiprocessing by default?~
- ~please note that `DownloadManager.download` sets `num_proc=16` by default~
- ~or would it be better to ask the user to set it explicitly if they want multiprocessing (and default to `num_proc=1`)?~
Fix #4636.
CC: @nateraw | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"@lhoestq as a workaround to preserve previous behavior, the parameter `multiprocessing_min_length=16` is passed from `download` to `map_nested`, so that multiprocessing is only used if at least 16 files to be downloaded.\r\n\r\nNote ... |
https://api.github.com/repos/huggingface/datasets/issues/4878 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4878/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4878/comments | https://api.github.com/repos/huggingface/datasets/issues/4878/events | https://github.com/huggingface/datasets/issues/4878 | 1,348,270,141 | I_kwDODunzps5QXPg9 | 4,878 | [not really a bug] `identical_ok` is deprecated in huggingface-hub's `upload_file` | [
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"default":... | closed | false | null | 1 | 2022-08-23T17:09:55Z | 2022-09-13T14:00:06Z | 2022-09-13T14:00:05Z | null | In the huggingface-hub dependency, the `identical_ok` argument has no effect in `upload_file` (and it will be removed soon)
See
https://github.com/huggingface/huggingface_hub/blob/43499582b19df1ed081a5b2bd7a364e9cacdc91d/src/huggingface_hub/hf_api.py#L2164-L2169
It's used here:
https://github.com/huggingface/datasets/blob/fcfcc951a73efbc677f9def9a8707d0af93d5890/src/datasets/dataset_dict.py#L1373-L1381
https://github.com/huggingface/datasets/blob/fdcb8b144ce3ef241410281e125bd03e87b8caa1/src/datasets/arrow_dataset.py#L4354-L4362
https://github.com/huggingface/datasets/blob/fdcb8b144ce3ef241410281e125bd03e87b8caa1/src/datasets/arrow_dataset.py#L4197-L4213
We should remove it.
Maybe the third code sample has an unexpected behavior since it uses the non-default value `identical_ok = False`, but the argument is ignored. | {
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"Resolved via https://github.com/huggingface/datasets/pull/4937."
] |
https://api.github.com/repos/huggingface/datasets/issues/3854 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3854/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3854/comments | https://api.github.com/repos/huggingface/datasets/issues/3854/events | https://github.com/huggingface/datasets/issues/3854 | 1,162,434,199 | I_kwDODunzps5FSVaX | 3,854 | load only England English dataset from common voice english dataset | [
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] | closed | false | null | 1 | 2022-03-08T09:40:52Z | 2022-03-09T08:13:33Z | 2022-03-09T08:13:33Z | null | training_data = load_dataset("common_voice", "en",split='train[:250]+validation[:250]')
testing_data = load_dataset("common_voice", "en", split="test[:200]")
I'm trying to load only 8% of the English common voice data with accent == "England English." Can somebody assist me with this?
**Typical Voice Accent Proportions:**
- 24% United States English
- 8% England English
- 5% India and South Asia (India, Pakistan, Sri Lanka)
- 3% Australian English
- 3% Canadian English
- 2% Scottish English
- 1% Irish English
- 1% Southern African (South Africa, Zimbabwe, Namibia)
- 1% New Zealand English
Can we replicate this for Age as well?
**Age proportions of the common voice:-**
- 24% 19 - 29
- 14% 30 - 39
- 10% 40 - 49
- 6% < 19
- 4% 50 - 59
- 4% 60 - 69
- 1% 70 – 79 | {
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"Hi @amanjaiswal777,\r\n\r\nFirst note that the dataset you are trying to load is deprecated: it was the Common Voice dataset release as of Dec 2020.\r\n\r\nCurrently, Common Voice dataset releases are directly hosted on the Hub, under the Mozilla Foundation organization: https://huggingface.co/mozilla-foundation\r... |
https://api.github.com/repos/huggingface/datasets/issues/198 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/198/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/198/comments | https://api.github.com/repos/huggingface/datasets/issues/198/events | https://github.com/huggingface/datasets/issues/198 | 625,200,627 | MDU6SXNzdWU2MjUyMDA2Mjc= | 198 | Index outside of table length | [] | closed | false | null | 2 | 2020-05-26T21:09:40Z | 2020-05-26T22:43:49Z | 2020-05-26T22:43:49Z | null | The offset input box warns of numbers larger than a limit (like 2000) but then the errors start at a smaller value than that limit (like 1955).
> ValueError: Index (2000) outside of table length (2000).
> Traceback:
> File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/ScriptRunner.py", line 322, in _run_script
> exec(code, module.__dict__)
> File "/home/sasha/nlp_viewer/run.py", line 116, in <module>
> v = d[item][k]
> File "/home/sasha/.local/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 338, in __getitem__
> output_all_columns=self._output_all_columns,
> File "/home/sasha/.local/lib/python3.7/site-packages/nlp/arrow_dataset.py", line 290, in _getitem
> raise ValueError(f"Index ({key}) outside of table length ({self._data.num_rows}).") | {
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"Sounds like something related to the nlp viewer @srush ",
"Fixed. "
] |
https://api.github.com/repos/huggingface/datasets/issues/3626 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3626/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3626/comments | https://api.github.com/repos/huggingface/datasets/issues/3626/events | https://github.com/huggingface/datasets/issues/3626 | 1,113,534,436 | I_kwDODunzps5CXy_k | 3,626 | The Pile cannot connect to host | [
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] | closed | false | null | 0 | 2022-01-25T07:43:33Z | 2022-02-14T08:40:58Z | 2022-02-14T08:40:58Z | null | ## Describe the bug
The Pile had issues with their previous host server and have mirrored its content to another server.
The new URL server should be updated.
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https://api.github.com/repos/huggingface/datasets/issues/2211 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2211/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2211/comments | https://api.github.com/repos/huggingface/datasets/issues/2211/events | https://github.com/huggingface/datasets/issues/2211 | 855,988,410 | MDU6SXNzdWU4NTU5ODg0MTA= | 2,211 | Getting checksum error when trying to load lc_quad dataset | [] | closed | false | null | 2 | 2021-04-12T13:38:58Z | 2021-04-14T13:42:25Z | 2021-04-14T13:42:25Z | null | I'm having issues loading the [lc_quad](https://huggingface.co/datasets/fquad) dataset by running:
```Python
lc_quad = load_dataset("lc_quad")
```
which is giving me the following error:
```
Using custom data configuration default
Downloading and preparing dataset lc_quad/default (download: 3.69 MiB, generated: 19.77 MiB, post-processed: Unknown size, total: 23.46 MiB) to /root/.cache/huggingface/datasets/lc_quad/default/2.0.0/5a98fe174603f5dec6df07edf1c2b4d2317210d2ad61f5a393839bca4d64e5a7...
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback (most recent call last)
<ipython-input-42-404ace83f73c> in <module>()
----> 1 lc_quad = load_dataset("lc_quad")
3 frames
/usr/local/lib/python3.7/dist-packages/datasets/utils/info_utils.py in verify_checksums(expected_checksums, recorded_checksums, verification_name)
37 if len(bad_urls) > 0:
38 error_msg = "Checksums didn't match" + for_verification_name + ":\n"
---> 39 raise NonMatchingChecksumError(error_msg + str(bad_urls))
40 logger.info("All the checksums matched successfully" + for_verification_name)
41
NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://github.com/AskNowQA/LC-QuAD2.0/archive/master.zip']
```
Does anyone know why this could be and how I fix it? | {
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"Hi,\r\n\r\nI've already opened a PR with the fix. If you are in a hurry, just build the project from source and run:\r\n```bash\r\ndatasets-cli test datasets/lc_quad --save_infos --all_configs --ignore_verifications\r\n```\r\n\r\n",
"Ah sorry, I tried searching but couldn't find any related PR. \r\n\r\nThank you... |
https://api.github.com/repos/huggingface/datasets/issues/6026 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6026/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6026/comments | https://api.github.com/repos/huggingface/datasets/issues/6026/events | https://github.com/huggingface/datasets/pull/6026 | 1,802,929,222 | PR_kwDODunzps5VanI8 | 6,026 | Fix style with ruff 0.0.278 | [] | closed | false | null | 3 | 2023-07-13T12:34:24Z | 2023-07-13T12:46:26Z | 2023-07-13T12:37:01Z | null | null | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6026). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... |
https://api.github.com/repos/huggingface/datasets/issues/5134 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5134/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5134/comments | https://api.github.com/repos/huggingface/datasets/issues/5134/events | https://github.com/huggingface/datasets/issues/5134 | 1,413,623,687 | I_kwDODunzps5UQi-H | 5,134 | Raise ImportError instead of OSError if required extraction library is not installed | [
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"default": true... | closed | false | null | 2 | 2022-10-18T17:53:46Z | 2022-10-25T15:56:59Z | 2022-10-25T15:56:59Z | null | According to the official Python docs, `OSError` should be thrown in the following situations:
> This exception is raised when a system function returns a system-related error, including I/O failures such as “file not found” or “disk full” (not for illegal argument types or other incidental errors).
Hence, it makes more sense to raise `ImportError` instead of `OSError` when the required extraction/decompression library is not installed. | {
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"hey ,i would like to work on this issue . Please assign it to me.",
"hey @mariosasko , i made a pr for this issue. Could you please review it.\r\nAlso i found multiple `OSError` in `extract.py` file which i thought could be replaced too but wasn't sure about them.\r\nPlease do tell if that also needs to be done.... |
https://api.github.com/repos/huggingface/datasets/issues/3608 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3608/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3608/comments | https://api.github.com/repos/huggingface/datasets/issues/3608/events | https://github.com/huggingface/datasets/issues/3608 | 1,109,310,981 | I_kwDODunzps5CHr4F | 3,608 | Add support for continuous metrics (RMSE, MAE) | [
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"default": true... | closed | false | null | 3 | 2022-01-20T13:35:36Z | 2022-03-09T17:18:20Z | 2022-03-09T17:18:20Z | null | **Is your feature request related to a problem? Please describe.**
I am uploading our dataset and models for the "Constructing interval measures" method we've developed, which uses item response theory to convert multiple discrete labels into a continuous spectrum for hate speech. Once we have this outcome our NLP models conduct regression rather than classification, so binary metrics are not relevant. The only continuous metrics available at https://huggingface.co/metrics are pearson & spearman correlation, which don't ensure that the prediction is on the same scale as the outcome.
**Describe the solution you'd like**
I would like to be able to tag our models on the Hub with the following metrics:
- RMSE
- MAE
**Describe alternatives you've considered**
I don't know if there are any alternatives.
**Additional context**
Our preprint is available here: https://arxiv.org/abs/2009.10277 . We are making it available for use in Jigsaw's Toxic Severity Rating Kaggle competition: https://www.kaggle.com/c/jigsaw-toxic-severity-rating/overview . I have our first model uploaded to the Hub at https://huggingface.co/ucberkeley-dlab/hate-measure-roberta-large
Thanks,
Chris
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"Hey @ck37 \r\n\r\nYou can always use a custom metric as explained [in this guide from HF](https://huggingface.co/docs/datasets/master/loading_metrics.html#using-a-custom-metric-script).\r\n\r\nIf this issue needs to be contributed to (for enhancing the metric API) I think [this link](https://scikit-learn.org/stabl... |
https://api.github.com/repos/huggingface/datasets/issues/2970 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2970/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2970/comments | https://api.github.com/repos/huggingface/datasets/issues/2970/events | https://github.com/huggingface/datasets/issues/2970 | 1,007,340,089 | I_kwDODunzps48Cso5 | 2,970 | Magnet’s | [
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] | closed | false | null | 0 | 2021-09-26T09:50:29Z | 2021-09-26T10:38:59Z | 2021-09-26T10:38:59Z | null | ## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). | {
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https://api.github.com/repos/huggingface/datasets/issues/719 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/719/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/719/comments | https://api.github.com/repos/huggingface/datasets/issues/719/events | https://github.com/huggingface/datasets/pull/719 | 716,492,263 | MDExOlB1bGxSZXF1ZXN0NDk5MjE5Mjg2 | 719 | Fix train_test_split output format | [] | closed | false | null | 0 | 2020-10-07T12:39:01Z | 2020-10-07T13:38:08Z | 2020-10-07T13:38:06Z | null | There was an issue in the `transmit_format` wrapper that returned bad formats when using train_test_split.
This was due to `column_names` being handled as a List[str] instead of Dict[str, List[str]] when the dataset transform (train_test_split) returns a DatasetDict (one set of column names per split).
This should fix @timothyjlaurent 's issue in #620 and fix #676
I added tests for `transmit_format` so that it doesn't happen again | {
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https://api.github.com/repos/huggingface/datasets/issues/5284 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5284/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5284/comments | https://api.github.com/repos/huggingface/datasets/issues/5284/events | https://github.com/huggingface/datasets/issues/5284 | 1,461,519,733 | I_kwDODunzps5XHQV1 | 5,284 | Features of IterableDataset set to None by remove column | [
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"descrip... | closed | false | null | 18 | 2022-11-23T10:54:59Z | 2023-02-02T09:05:51Z | 2022-11-28T12:53:24Z | null | ### Describe the bug
The `remove_column` method of the IterableDataset sets the dataset features to None.
### Steps to reproduce the bug
```python
from datasets import Audio, load_dataset
# load LS in streaming mode
dataset = load_dataset("librispeech_asr", "clean", split="validation", streaming=True)
# check original features
print("Original features: ", dataset.features.keys())
# define features to remove: we KEEP audio and text
COLUMNS_TO_REMOVE = ['chapter_id', 'speaker_id', 'file', 'id']
dataset = dataset.remove_columns(COLUMNS_TO_REMOVE)
# check processed features, uh-oh!
print("Processed features: ", dataset.features)
# streaming the first audio sample still works
print("First sample:", next(iter(ds)))
```
**Print Output:**
```
Original features: dict_keys(['file', 'audio', 'text', 'speaker_id', 'chapter_id', 'id'])
Processed features: None
First sample: {'audio': {'path': '2277-149896-0000.flac', 'array': array([ 0.00186157, 0.0005188 , 0.00024414, ..., -0.00097656,
-0.00109863, -0.00146484]), 'sampling_rate': 16000}, 'text': "HE WAS IN A FEVERED STATE OF MIND OWING TO THE BLIGHT HIS WIFE'S ACTION THREATENED TO CAST UPON HIS ENTIRE FUTURE"}
```
### Expected behavior
The features should be those **not** removed by the `remove_column` method, i.e. audio and text.
### Environment info
- `datasets` version: 2.7.1
- Platform: Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.15
- PyArrow version: 9.0.0
- Pandas version: 1.3.5
(Running on Google Colab for a blog post: https://colab.research.google.com/drive/1ySCQREPZEl4msLfxb79pYYOWjUZhkr9y#scrollTo=8pRDGiVmH2ml)
cc @polinaeterna @lhoestq | {
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"Related to https://github.com/huggingface/datasets/issues/5245",
"#self-assign",
"Thanks @lhoestq and @alvarobartt!\r\n\r\nThis would be extremely helpful to have working for the Whisper fine-tuning event - we're **only** training using streaming mode, so it'll be quite important to have this feature working t... |
https://api.github.com/repos/huggingface/datasets/issues/5146 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5146/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5146/comments | https://api.github.com/repos/huggingface/datasets/issues/5146/events | https://github.com/huggingface/datasets/pull/5146 | 1,418,331,282 | PR_kwDODunzps5BSUWW | 5,146 | Delete duplicate issue template file | [] | closed | false | null | 1 | 2022-10-21T13:18:46Z | 2022-10-21T13:52:30Z | 2022-10-21T13:50:04Z | null | A conflict between two PRs:
- #5116
- #5136
was not properly resolved, resulting in a duplicate issue template.
This PR removes the duplicate template. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/64 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/64/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/64/comments | https://api.github.com/repos/huggingface/datasets/issues/64/events | https://github.com/huggingface/datasets/pull/64 | 614,737,057 | MDExOlB1bGxSZXF1ZXN0NDE1MjMwMjYy | 64 | [Datasets] Make master ready for datasets adding | [] | closed | false | null | 0 | 2020-05-08T13:17:00Z | 2020-05-08T13:17:31Z | 2020-05-08T13:17:30Z | null | Add all relevant files so that datasets can now be added on master | {
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https://api.github.com/repos/huggingface/datasets/issues/756 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/756/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/756/comments | https://api.github.com/repos/huggingface/datasets/issues/756/events | https://github.com/huggingface/datasets/pull/756 | 728,211,373 | MDExOlB1bGxSZXF1ZXN0NTA4OTYwNTc3 | 756 | Start community-provided dataset docs | [] | closed | false | null | 1 | 2020-10-23T13:17:41Z | 2020-10-26T12:55:20Z | 2020-10-26T12:55:19Z | null | Continuation of #736 with clean fork.
#### Old description
This is what I did to get the pseudo-labels updated. Not sure if it generalizes, but I figured I would write it down. It was pretty easy because all I had to do was make properly formatted directories and change URLs.
In slack @thomwolf called it a user-namespace dataset, but the docs call it community dataset.
I think the first naming is clearer, but I didn't address that here.
I didn't add metadata, will try that. | {
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"Oh, really cool @sshleifer!"
] |
https://api.github.com/repos/huggingface/datasets/issues/1347 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1347/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1347/comments | https://api.github.com/repos/huggingface/datasets/issues/1347/events | https://github.com/huggingface/datasets/pull/1347 | 759,845,231 | MDExOlB1bGxSZXF1ZXN0NTM0Nzc3NjQ0 | 1,347 | Add spanish billion words corpus | [] | closed | false | null | 4 | 2020-12-08T22:51:38Z | 2020-12-11T11:26:39Z | 2020-12-11T11:15:28Z | null | Add an unannotated Spanish corpus of nearly 1.5 billion words, compiled from different resources from the web. | {
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"Thank you for your feedback! I've reduced the dummy data size to 2KB.\r\n\r\nI had to rebase to fix `RemoteDatasetTest` fails, sorry about the 80 commits. \r\nI could create a new clean PR if you prefer.",
"I have seen that in similar cases you have suggested to other contributors to create another branch and an... |
https://api.github.com/repos/huggingface/datasets/issues/2986 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2986/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2986/comments | https://api.github.com/repos/huggingface/datasets/issues/2986/events | https://github.com/huggingface/datasets/pull/2986 | 1,010,792,783 | PR_kwDODunzps4scSHR | 2,986 | Refac module factory + avoid etag requests for hub datasets | [] | closed | false | null | 6 | 2021-09-29T10:42:00Z | 2021-10-11T11:05:53Z | 2021-10-11T11:05:52Z | null | ## Refactor the module factory
When trying to extend the `data_files` logic to avoid doing unnecessary ETag requests, I noticed that the module preparation mechanism needed a refactor:
- the function was 600 lines long
- it was not readable
- it contained many different cases that made it complex to maintain
- it was hard to properly test it
- it was hard to extend without breaking anything
The module preparation mechanism is in charge of taking the name of a dataset or a metric given by the user (ex: "squad", "accuracy", "lhoestq/test", "path/to/my/script.py", "path/to/my/data/directory", "json", "csv") and return a module (possibly downloaded from the Hub) that contains the dataset builder or the metric class to use.
### Implementation details
I decided to separate all these use cases into different dataset/metric module factories.
First, the metric module factories:
- **CanonicalMetricModuleFactory**: "accuracy", "rouge", ...
- **LocalMetricModuleFactory**: "path/to/my/metric.py"
Then, the dataset module factories:
- **CanonicalDatasetModuleFactory**: "squad", "glue", ...
- **CommunityDatasetModuleFactoryWithScript**: "lhoestq/test"
- **CommunityDatasetModuleFactoryWithoutScript**: "lhoestq/demo1"
- **PackagedDatasetModuleFactory**: "json", "csv", ...
- **LocalDatasetModuleFactoryWithScript**: "path/to/my/script.py"
- **LocalDatasetModuleFactoryWithoutScript**: "path/to/my/data/directory"
And finally, additional factories when users have no internet:
- **CachedDatasetModuleFactory**
- **CachedMetricModuleFactory**
### Breaking changes
One thing is that I still don't know at what extent we want to keep backward compatibility for `prepare_module`. For now I just kept it (except I removed two parameters) just in case, but it's not used anywhere anymore.
## Avoid etag requests for hub datasets
To do this I added a class `DataFilesDict` that can be hashed to define the cache directory of the dataset.
It contains the usual data files formatted as `{"train": ["train.txt"]}` for example.
But each list of file is a `DataFilesList` that also has a `origin_metadata` attribute that contains metadata about the origin of each file:
- for URLs: it stores the ETags of the files
- for local files: it stores the last modification data
- for files from a Hugging Face repository on the Hub: it stores the pattern (`*`, `*.csv`, "train.txt", etc.) and the commit sha of the repository (so there're no ETag requests !)
This way if any file changes, the hash of the `DataFilesDict` changes too !
You can instantiate a `DataFilesDict` by using patterns for local/remote files or files in a HF repository:
- for local/remote files: `DataFilesDict.from_local_or_remote(patterns)`
- for files in a HF repository: `DataFilesDict.from_hf_repo(patterns, dataset_info)`
Fix #2859
## TODO
Fix the latest test:
- [x] fix the call to dataset_info in offline mode (related to https://github.com/huggingface/huggingface_hub/issues/372)
Add some more tests:
- [x] test all the factories
- [x] test the new data files logic
Other:
- [x] docstrings
- [x] comments | {
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"> One thing is that I still don't know at what extent we want to keep backward compatibility for prepare_module. For now I just kept it (except I removed two parameters) just in case, but it's not used anywhere anymore.\r\n\r\nFYI, various other projects currently use it, thus clearly a major version would be requ... |
https://api.github.com/repos/huggingface/datasets/issues/5617 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5617/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5617/comments | https://api.github.com/repos/huggingface/datasets/issues/5617/events | https://github.com/huggingface/datasets/pull/5617 | 1,612,947,422 | PR_kwDODunzps5LcvI- | 5,617 | Fix CI by temporarily pinning fsspec < 2023.3.0 | [] | closed | false | null | 2 | 2023-03-07T08:18:20Z | 2023-03-07T08:44:55Z | 2023-03-07T08:37:28Z | null | As a hotfix for our CI, temporarily pin `fsspec`:
Fix #5616.
Until root cause is fixed, see:
- #5614 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/3564 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3564/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3564/comments | https://api.github.com/repos/huggingface/datasets/issues/3564/events | https://github.com/huggingface/datasets/pull/3564 | 1,099,214,403 | PR_kwDODunzps4wzSOL | 3,564 | Add the KMWP & DKTC dataset. | [] | closed | false | null | 3 | 2022-01-11T14:14:08Z | 2022-01-12T15:33:49Z | 2022-01-12T15:33:28Z | null | Add the DKTC dataset.
- https://github.com/tunib-ai/DKTC | {
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"I reflect your review. cc. @lhoestq ",
"Ah sorry, I missed KMWP comment, wait.",
"I request 2 new pull requests. #3569 #3570"
] |
https://api.github.com/repos/huggingface/datasets/issues/5053 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5053/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5053/comments | https://api.github.com/repos/huggingface/datasets/issues/5053/events | https://github.com/huggingface/datasets/issues/5053 | 1,393,739,882 | I_kwDODunzps5TEshq | 5,053 | Intermittent JSON parse error when streaming the Pile | [
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] | open | false | null | 3 | 2022-10-02T11:56:46Z | 2022-10-04T17:59:03Z | null | null | ## Describe the bug
I have an intermittent error when streaming the Pile, where I get a JSON parse error which causes my program to crash.
This is intermittent - when I rerun the program with the same random seed it does not crash in the same way. The exact point this happens also varied - it happened to me 11B tokens and 4 days into a training run, and now just happened 2 minutes into one, but I can't reliably reproduce it.
I'm using a remote machine with 8 A6000 GPUs via runpod.io
## Expected results
I have a DataLoader which can iterate through the whole Pile
## Actual results
Stack trace:
```
Failed to read file 'zstd://12.jsonl::https://the-eye.eu/public/AI/pile/train/12.jsonl.zst' with error <class 'pyarrow.lib.ArrowInvalid'>: JSON parse error: Invalid value. in row 0
```
I'm currently using HuggingFace accelerate, which also gave me the following stack trace, but I've also experienced this problem intermittently when using DataParallel, so I don't think it's to do with parallelisation
```
Traceback (most recent call last):
File "ddp_script.py", line 1258, in <module>
main()
File "ddp_script.py", line 1143, in main
for c, batch in tqdm.tqdm(enumerate(data_iter)):
File "/opt/conda/lib/python3.7/site-packages/tqdm/std.py", line 1195, in __iter__
for obj in iterable:
File "/opt/conda/lib/python3.7/site-packages/accelerate/data_loader.py", line 503, in __iter__
next_batch, next_batch_info, next_skip = self._fetch_batches(main_iterator)
File "/opt/conda/lib/python3.7/site-packages/accelerate/data_loader.py", line 454, in _fetch_batches
broadcast_object_list(batch_info)
File "/opt/conda/lib/python3.7/site-packages/accelerate/utils/operations.py", line 333, in broadcast_object_list
torch.distributed.broadcast_object_list(object_list, src=from_process)
File "/opt/conda/lib/python3.7/site-packages/torch/distributed/distributed_c10d.py", line 1900, in broadcast_object_list
object_list[i] = _tensor_to_object(obj_view, obj_size)
File "/opt/conda/lib/python3.7/site-packages/torch/distributed/distributed_c10d.py", line 1571, in _tensor_to_object
return _unpickler(io.BytesIO(buf)).load()
_pickle.UnpicklingError: invalid load key, '@'.
```
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset(
cfg["dataset_name"], streaming=True, split="train")
dataset = dataset.remove_columns("meta")
dataset = dataset.map(tokenize_and_concatenate, batched=True)
dataset = dataset.with_format(type="torch")
train_data_loader = DataLoader(
dataset, batch_size=cfg["batch_size"], num_workers=3)
for batch in train_data_loader:
continue
```
`tokenize_and_concatenate` is a custom tokenization function I defined on the GPT-NeoX tokenizer to tokenize the text, separated by endoftext tokens, and reshape to have length batch_size, I don't think this is related to tokenization:
```
import numpy as np
import einops
import torch
def tokenize_and_concatenate(examples):
texts = examples["text"]
full_text = tokenizer.eos_token.join(texts)
div = 20
length = len(full_text) // div
text_list = [full_text[i * length: (i + 1) * length]
for i in range(div)]
tokens = tokenizer(text_list, return_tensors="np", padding=True)[
"input_ids"
].flatten()
tokens = tokens[tokens != tokenizer.pad_token_id]
n = len(tokens)
curr_batch_size = n // (seq_len - 1)
tokens = tokens[: (seq_len - 1) * curr_batch_size]
tokens = einops.rearrange(
tokens,
"(batch_size seq) -> batch_size seq",
batch_size=curr_batch_size,
seq=seq_len - 1,
)
prefix = np.ones((curr_batch_size, 1), dtype=np.int64) * \
tokenizer.bos_token_id
return {
"text": np.concatenate([prefix, tokens], axis=1)
}
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.4.0
- Platform: Linux-5.4.0-105-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.13
- PyArrow version: 9.0.0
- Pandas version: 1.3.5
ZStandard data:
Version: 0.18.0
Summary: Zstandard bindings for Python
Home-page: https://github.com/indygreg/python-zstandard
Author: Gregory Szorc
Author-email: gregory.szorc@gmail.com
License: BSD
Location: /opt/conda/lib/python3.7/site-packages
Requires:
Required-by: | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5053/timeline | null | null | null | null | false | [
"Maybe #2838 can help. In this PR we allow to skip bad chunks of JSON data to not crash the training\r\n\r\nDid you have warning messages before the error ?\r\n\r\nsomething like this maybe ?\r\n```\r\n03/24/2022 02:19:46 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host... |
https://api.github.com/repos/huggingface/datasets/issues/3314 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3314/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3314/comments | https://api.github.com/repos/huggingface/datasets/issues/3314/events | https://github.com/huggingface/datasets/pull/3314 | 1,061,448,227 | PR_kwDODunzps4u6mdX | 3,314 | Adding arg to pass process rank to `map` | [] | closed | false | null | 1 | 2021-11-23T15:55:21Z | 2021-11-24T11:54:13Z | 2021-11-24T11:54:13Z | null | This PR adds a `with_rank` argument to `map` that gives the user the possibility to pass the rank of each process to their function. This is mostly designed for multi-GPU map (each process can be sent to a different device thanks to the rank). I've also added tests. I'm putting the PR up so you can check the code, I'll add a multi-GPU example to the doc (+ write a bit in the doc for the new arg) | {
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"Some commits seem to be there twice (made the mistake of rebasing because I wasn't sure whether the doc had changed), is this an issue @lhoestq ?"
] |
https://api.github.com/repos/huggingface/datasets/issues/4744 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4744/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4744/comments | https://api.github.com/repos/huggingface/datasets/issues/4744/events | https://github.com/huggingface/datasets/issues/4744 | 1,317,822,345 | I_kwDODunzps5OjF-J | 4,744 | Remove instructions to generate dummy data from our docs | [
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] | closed | false | null | 2 | 2022-07-26T07:32:58Z | 2022-08-02T23:50:30Z | 2022-08-02T23:50:30Z | null | In our docs, we indicate to generate the dummy data: https://huggingface.co/docs/datasets/dataset_script#testing-data-and-checksum-metadata
However:
- dummy data makes sense only for datasets in our GitHub repo: so that we can test their loading with our CI
- for datasets on the Hub:
- they do not pass any CI test requiring dummy data
- there are no instructions on how they can test their dataset locally using the dummy data
- the generation of the dummy data assumes our GitHub directory structure:
- the dummy data will be generated under `./datasets/<dataset_name>/dummy` even if locally there is no `./datasets` directory (which is the usual case). See issue:
- #4742
CC: @stevhliu | {
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"Note that for me personally, conceptually all the dummy data (even for \"canonical\" datasets) should be superseded by `datasets-server`, which performs some kind of CI/CD of datasets (including the canonical ones)",
"I totally agree: next step should be rethinking if dummy data makes sense for canonical dataset... |
https://api.github.com/repos/huggingface/datasets/issues/5872 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5872/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5872/comments | https://api.github.com/repos/huggingface/datasets/issues/5872/events | https://github.com/huggingface/datasets/pull/5872 | 1,713,174,662 | PR_kwDODunzps5QrQ5o | 5,872 | Fix infer module for uppercase extensions | [] | closed | false | null | 2 | 2023-05-17T05:56:45Z | 2023-05-17T14:26:59Z | 2023-05-17T14:19:18Z | null | Fix the `infer_module_for_data_files` and `infer_module_for_data_files_in_archives` functions when passed a data file name with uppercase extension, e.g. `filename.TXT`.
Before, `None` module was returned. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/2952 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2952/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2952/comments | https://api.github.com/repos/huggingface/datasets/issues/2952/events | https://github.com/huggingface/datasets/pull/2952 | 1,002,704,096 | PR_kwDODunzps4sDU8S | 2,952 | Fix missing conda deps | [] | closed | false | null | 0 | 2021-09-21T15:23:01Z | 2021-09-22T04:39:59Z | 2021-09-21T15:30:44Z | null | `aiohttp` was added as a dependency in #2662 but was missing for the conda build, which causes the 1.12.0 and 1.12.1 to fail.
Fix #2932. | {
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https://api.github.com/repos/huggingface/datasets/issues/602 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/602/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/602/comments | https://api.github.com/repos/huggingface/datasets/issues/602/events | https://github.com/huggingface/datasets/pull/602 | 697,636,605 | MDExOlB1bGxSZXF1ZXN0NDgzNTU3NDM0 | 602 | apply offset to indices in multiprocessed map | [] | closed | false | null | 0 | 2020-09-10T08:54:30Z | 2020-09-10T11:03:39Z | 2020-09-10T11:03:37Z | null | Fix #597
I fixed the indices by applying an offset.
I added the case to our tests to make sure it doesn't happen again.
I also added the message proposed by @thomwolf in #597
```python
>>> d.select(range(10)).map(fn, with_indices=True, batched=True, num_proc=2, load_from_cache_file=False)
Done writing 10 indices in 80 bytes .
Testing the mapped function outputs
[0, 1]
Testing finished, running the mapping function on the dataset
Done writing 5 indices in 41 bytes .
Done writing 5 indices in 41 bytes .
Spawning 2 processes
[0, 1, 2, 3, 4]
[5, 6, 7, 8, 9]
#0: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 377.90ba/s]
#1: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 378.92ba/s]
Concatenating 2 shards from multiprocessing
# Dataset(features: {'label': ClassLabel(num_classes=2, names=['neg', 'pos'], names_file=None, id=None), 'text': Value(dtype='string', id=None)}, num_rows: 10)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4922 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4922/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4922/comments | https://api.github.com/repos/huggingface/datasets/issues/4922/events | https://github.com/huggingface/datasets/issues/4922 | 1,357,684,018 | I_kwDODunzps5Q7J0y | 4,922 | I/O error on Google Colab in streaming mode | [
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] | closed | false | null | 0 | 2022-08-31T18:08:26Z | 2022-08-31T18:15:48Z | 2022-08-31T18:15:48Z | null | ## Describe the bug
When trying to load a streaming dataset in Google Colab the loading fails with an I/O error
## Steps to reproduce the bug
```python
import datasets
from datasets import load_dataset
hf_ds = load_dataset(path='wmt19', name='cs-en', streaming=True, split=datasets.Split.VALIDATION)
list(hf_ds.take(5))
```
## Expected results
It should load five data points
## Actual results
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
[<ipython-input-13-7b5b8b1e7e58>](https://localhost:8080/#) in <module>
2 from datasets import load_dataset
3 hf_ds = load_dataset(path='wmt19', name='cs-en', streaming=True, split=datasets.Split.VALIDATION)
----> 4 list(hf_ds.take(5))
6 frames
[/usr/local/lib/python3.7/dist-packages/datasets/iterable_dataset.py](https://localhost:8080/#) in __iter__(self)
716
717 def __iter__(self):
--> 718 for key, example in self._iter():
719 if self.features:
720 # `IterableDataset` automatically fills missing columns with None.
[/usr/local/lib/python3.7/dist-packages/datasets/iterable_dataset.py](https://localhost:8080/#) in _iter(self)
706 else:
707 ex_iterable = self._ex_iterable
--> 708 yield from ex_iterable
709
710 def _iter_shard(self, shard_idx: int):
[/usr/local/lib/python3.7/dist-packages/datasets/iterable_dataset.py](https://localhost:8080/#) in __iter__(self)
582
583 def __iter__(self):
--> 584 yield from islice(self.ex_iterable, self.n)
585
586 def shuffle_data_sources(self, generator: np.random.Generator) -> "TakeExamplesIterable":
[/usr/local/lib/python3.7/dist-packages/datasets/iterable_dataset.py](https://localhost:8080/#) in __iter__(self)
110
111 def __iter__(self):
--> 112 yield from self.generate_examples_fn(**self.kwargs)
113
114 def shuffle_data_sources(self, generator: np.random.Generator) -> "ExamplesIterable":
[~/.cache/huggingface/modules/datasets_modules/datasets/wmt19/aeadcbe9f1cbf9969e603239d33d3e43670cf250c1158edf74f5f6e74d4f21d0/wmt_utils.py](https://localhost:8080/#) in _generate_examples(self, split_subsets, extraction_map, with_translation)
845 raise ValueError("Invalid number of files: %d" % len(files))
846
--> 847 for sub_key, ex in sub_generator(*sub_generator_args):
848 if not all(ex.values()):
849 continue
[~/.cache/huggingface/modules/datasets_modules/datasets/wmt19/aeadcbe9f1cbf9969e603239d33d3e43670cf250c1158edf74f5f6e74d4f21d0/wmt_utils.py](https://localhost:8080/#) in _parse_parallel_sentences(f1, f2, filename1, filename2)
923 l2_sentences, l2 = parse_file(f2_i, filename2)
924
--> 925 for line_id, (s1, s2) in enumerate(zip(l1_sentences, l2_sentences)):
926 key = f"{f_id}/{line_id}"
927 yield key, {l1: s1, l2: s2}
[~/.cache/huggingface/modules/datasets_modules/datasets/wmt19/aeadcbe9f1cbf9969e603239d33d3e43670cf250c1158edf74f5f6e74d4f21d0/wmt_utils.py](https://localhost:8080/#) in gen()
895
896 def gen():
--> 897 with open(path, encoding="utf-8") as f:
898 for line in f:
899 seg_match = re.match(seg_re, line)
ValueError: I/O operation on closed file.
```
## Environment info
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 2.4.0
- Platform: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 9.0.0. (the same error happened with PyArrow version 6.0.0)
- Pandas version: 1.3.5
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https://api.github.com/repos/huggingface/datasets/issues/3368 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3368/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3368/comments | https://api.github.com/repos/huggingface/datasets/issues/3368/events | https://github.com/huggingface/datasets/pull/3368 | 1,069,403,624 | PR_kwDODunzps4vTObo | 3,368 | Fix dict source_datasets tagset validator | [] | closed | false | null | 0 | 2021-12-02T10:52:20Z | 2021-12-02T15:48:38Z | 2021-12-02T15:48:37Z | null | Currently, the `source_datasets` tag validation does not support passing a dict with configuration keys.
This PR:
- Extends `tagset_validator` to support regex tags
- Uses `tagset_validator` to validate dict `source_datasets` | {
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https://api.github.com/repos/huggingface/datasets/issues/2256 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2256/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2256/comments | https://api.github.com/repos/huggingface/datasets/issues/2256/events | https://github.com/huggingface/datasets/issues/2256 | 866,708,609 | MDU6SXNzdWU4NjY3MDg2MDk= | 2,256 | Running `datase.map` with `num_proc > 1` uses a lot of memory | [
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] | closed | false | null | 2 | 2021-04-24T09:56:20Z | 2021-04-26T17:12:15Z | 2021-04-26T17:12:15Z | null | ## Describe the bug
Running `datase.map` with `num_proc > 1` leads to a tremendous memory usage that requires swapping on disk and it becomes very slow.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dstc8_datset = load_dataset("roskoN/dstc8-reddit-corpus", keep_in_memory=False)
def _prepare_sample(batch):
return {"input_ids": list(), "attention_mask": list()}
for split_name, dataset_split in list(dstc8_datset.items()):
print(f"Processing {split_name}")
encoded_dataset_split = dataset_split.map(
function=_prepare_sample,
batched=True,
num_proc=4,
remove_columns=dataset_split.column_names,
batch_size=10,
writer_batch_size=10,
keep_in_memory=False,
)
print(encoded_dataset_split)
path = f"./data/encoded_{split_name}"
encoded_dataset_split.save_to_disk(path)
```
## Expected results
Memory usage should stay within reasonable boundaries.
## Actual results
This is htop-output from running the provided script.
## Versions
```
- Datasets: 1.6.0
- Python: 3.8.8 (default, Apr 13 2021, 19:58:26)
[GCC 7.3.0]
- Platform: Linux-4.19.128-microsoft-standard-x86_64-with-glibc2.10
```
Running on WSL2
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"Thanks for reporting ! We are working on this and we'll do a patch release very soon.",
"We did a patch release to fix this issue.\r\nIt should be fixed in the new version 1.6.1\r\n\r\nThanks again for reporting and for the details :)"
] |
https://api.github.com/repos/huggingface/datasets/issues/3556 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3556/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3556/comments | https://api.github.com/repos/huggingface/datasets/issues/3556/events | https://github.com/huggingface/datasets/pull/3556 | 1,097,907,724 | PR_kwDODunzps4wvALx | 3,556 | Preserve encoding/decoding with features in `Iterable.map` call | [] | closed | false | null | 0 | 2022-01-10T13:32:20Z | 2022-01-18T19:54:08Z | 2022-01-18T19:54:07Z | null | As described in https://github.com/huggingface/datasets/issues/3505#issuecomment-1004755657, this PR uses a generator expression to encode/decode examples with `features` (which are set to None in `map`) before applying a map transform.
Fix #3505 | {
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https://api.github.com/repos/huggingface/datasets/issues/2405 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2405/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2405/comments | https://api.github.com/repos/huggingface/datasets/issues/2405/events | https://github.com/huggingface/datasets/pull/2405 | 901,227,658 | MDExOlB1bGxSZXF1ZXN0NjUyNzA2OTk1 | 2,405 | Add dataset tags | [] | closed | false | null | 1 | 2021-05-25T18:57:29Z | 2021-05-26T16:54:16Z | 2021-05-26T16:40:07Z | null | The dataset tags were provided by Peter Clark following the guide. | {
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"Thanks!"
] |
https://api.github.com/repos/huggingface/datasets/issues/2760 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2760/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2760/comments | https://api.github.com/repos/huggingface/datasets/issues/2760/events | https://github.com/huggingface/datasets/issues/2760 | 961,372,667 | MDU6SXNzdWU5NjEzNzI2Njc= | 2,760 | Add Nuswide dataset | [
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},
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"color": "bfdadc",... | open | false | null | 0 | 2021-08-05T03:00:41Z | 2021-12-08T12:06:23Z | null | null | ## Adding a Dataset
- **Name:** *NUSWIDE*
- **Description:** *[A Real-World Web Image Dataset from National University of Singapore](https://lms.comp.nus.edu.sg/wp-content/uploads/2019/research/nuswide/NUS-WIDE.html)*
- **Paper:** *[here](https://lms.comp.nus.edu.sg/wp-content/uploads/2019/research/nuswide/nuswide-civr2009.pdf)*
- **Data:** *[here](https://github.com/wenting-zhao/nuswide)*
- **Motivation:** *This dataset is a benchmark in the Text Retrieval task.*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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https://api.github.com/repos/huggingface/datasets/issues/3677 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3677/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3677/comments | https://api.github.com/repos/huggingface/datasets/issues/3677/events | https://github.com/huggingface/datasets/issues/3677 | 1,123,192,866 | I_kwDODunzps5C8pAi | 3,677 | Discovery cannot be streamed anymore | [
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] | closed | false | null | 2 | 2022-02-03T15:02:03Z | 2022-02-10T16:51:24Z | 2022-02-10T16:51:24Z | null | ## Describe the bug
A clear and concise description of what the bug is.
## Steps to reproduce the bug
```python
from datasets import load_dataset
iterable_dataset = load_dataset("discovery", name="discovery", split="train", streaming=True)
list(iterable_dataset.take(1))
```
## Expected results
The first row of the train split.
## Actual results
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 365, in __iter__
for key, example in self._iter():
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 362, in _iter
yield from ex_iterable
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 272, in __iter__
yield from islice(self.ex_iterable, self.n)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 79, in __iter__
yield from self.generate_examples_fn(**self.kwargs)
File "/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/discovery/542fab7a9ddc1d9726160355f7baa06a1ccc44c40bc8e12c09e9bc743aca43a2/discovery.py", line 333, in _generate_examples
with open(data_file, encoding="utf8") as f:
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 64, in wrapper
return function(*args, use_auth_token=use_auth_token, **kwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/utils/streaming_download_manager.py", line 369, in xopen
file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/core.py", line 456, in open
return open_files(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/core.py", line 288, in open_files
fs, fs_token, paths = get_fs_token_paths(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/core.py", line 611, in get_fs_token_paths
fs = filesystem(protocol, **inkwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 253, in filesystem
return cls(**storage_options)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 68, in __call__
obj = super().__call__(*args, **kwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 57, in __init__
self.zip = zipfile.ZipFile(self.fo)
File "/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/zipfile.py", line 1257, in __init__
self._RealGetContents()
File "/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/zipfile.py", line 1320, in _RealGetContents
endrec = _EndRecData(fp)
File "/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/zipfile.py", line 263, in _EndRecData
fpin.seek(0, 2)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 676, in seek
raise ValueError("Cannot seek streaming HTTP file")
ValueError: Cannot seek streaming HTTP file
```
## Environment info
- `datasets` version: 1.18.3
- Platform: Linux-5.11.0-1027-aws-x86_64-with-glibc2.31
- Python version: 3.9.6
- PyArrow version: 6.0.1
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"Seems like a regression from https://github.com/huggingface/datasets/pull/2843\r\n\r\nOr maybe it's an issue with the hosting. I don't think so, though, because https://www.dropbox.com/s/aox84z90nyyuikz/discovery.zip seems to work as expected\r\n\r\n",
"Hi @severo, thanks for reporting.\r\n\r\nSome servers do no... |
https://api.github.com/repos/huggingface/datasets/issues/4542 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4542/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4542/comments | https://api.github.com/repos/huggingface/datasets/issues/4542/events | https://github.com/huggingface/datasets/issues/4542 | 1,280,269,445 | I_kwDODunzps5MT1yF | 4,542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | [
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] | open | false | null | 48 | 2022-06-22T14:42:00Z | 2022-10-11T08:45:45Z | null | null | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_io` we could have something similar for `to_tf_dataset` if we provide sharded Feather files: https://www.tensorflow.org/io/api_docs/python/tfio/arrow/ArrowFeatherDataset
Feather is a format almost equivalent to the Arrow IPC Stream format we're using in `datasets`: Feather V2 is equivalent to Arrow IPC File format, which is an extension of the stream format (it has an extra footer). Therefore we could store datasets as Feather instead of Arrow IPC Stream format without breaking the whole library.
Here are a few points to explore
- [ ] check the performance of ArrowFeatherDataset in tf.data
- [ ] check what would change if we were to switch to Feather if needed, in particular check that those are fine: memory mapping, typing, writing, reading to python objects, etc.
We would also need to implement sharding when loading a dataset (this will be done anyway for #546)
cc @Rocketknight1 @gante feel free to comment in case I missed anything !
I'll share some files and scripts, so that we can benchmark performance of Feather files with tf.data | {
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"This has so much potential to be great! Also I think you tagged some poor random dude on the internet whose name is also Joao, lol, edited that for you! ",
"cc @sayakpaul here too, since he was interested in our new approaches to converting datasets!",
"Noted and I will look into the thread in detail tomorrow ... |
https://api.github.com/repos/huggingface/datasets/issues/3123 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3123/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3123/comments | https://api.github.com/repos/huggingface/datasets/issues/3123/events | https://github.com/huggingface/datasets/issues/3123 | 1,031,793,207 | I_kwDODunzps49f-o3 | 3,123 | Segmentation fault when loading datasets from file | [
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] | closed | false | null | 2 | 2021-10-20T20:16:11Z | 2021-11-02T14:57:07Z | 2021-11-02T14:57:07Z | null | ## Describe the bug
Custom dataset loading sometimes segfaults and kills the process if chunks contain a variety of features/
## Steps to reproduce the bug
Download an example file:
```
wget https://gist.githubusercontent.com/TevenLeScao/11e2184394b3fa47d693de2550942c6b/raw/4232704d08fbfcaf93e5b51def9e5051507651ad/tiny_kelm.jsonl
```
Then in Python:
```
import datasets
tiny_kelm = datasets.load_dataset("json", data_files="tiny_kelm.jsonl", chunksize=100000)
```
## Expected results
a `tiny_kelm` functional dataset
## Actual results
☠️ `Segmentation fault (core dumped)` ☠️
## Environment info
- `datasets` version: 1.14.0
- Platform: Linux-5.11.0-38-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
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"Hi ! I created an issue on Arrow's JIRA after making a minimum reproducible example\r\n\r\nhttps://issues.apache.org/jira/browse/ARROW-14439\r\n\r\n```python\r\nimport io\r\n\r\nimport pyarrow.json as paj\r\n\r\nbatch = b'{\"a\": [], \"b\": 1}\\n{\"b\": 1}'\r\nblock_size = 12\r\n\r\npaj.read_json(\r\n io.BytesI... |
https://api.github.com/repos/huggingface/datasets/issues/1016 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1016/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1016/comments | https://api.github.com/repos/huggingface/datasets/issues/1016/events | https://github.com/huggingface/datasets/pull/1016 | 755,521,862 | MDExOlB1bGxSZXF1ZXN0NTMxMjE3MjM3 | 1,016 | Add CLINC150 dataset | [] | closed | false | null | 0 | 2020-12-02T18:44:30Z | 2020-12-03T10:32:04Z | 2020-12-03T10:32:04Z | null | Added CLINC150 Dataset. The link to the dataset can be found [here](https://github.com/clinc/oos-eval) and the paper can be found [here](https://www.aclweb.org/anthology/D19-1131.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | {
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https://api.github.com/repos/huggingface/datasets/issues/1193 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1193/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1193/comments | https://api.github.com/repos/huggingface/datasets/issues/1193/events | https://github.com/huggingface/datasets/pull/1193 | 757,840,830 | MDExOlB1bGxSZXF1ZXN0NTMzMTM1NDAy | 1,193 | add taskmaster-1 | [] | closed | false | null | 0 | 2020-12-06T04:09:57Z | 2020-12-07T15:23:24Z | 2020-12-07T15:08:39Z | null | Adding Taskmaster-1 dataset
https://github.com/google-research-datasets/Taskmaster/tree/master/TM-1-2019 | {
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https://api.github.com/repos/huggingface/datasets/issues/2324 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2324/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2324/comments | https://api.github.com/repos/huggingface/datasets/issues/2324/events | https://github.com/huggingface/datasets/pull/2324 | 876,602,064 | MDExOlB1bGxSZXF1ZXN0NjMwNzE1NTQz | 2,324 | Create Audio feature | [] | closed | false | {
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} | 30 | 2021-05-05T15:55:22Z | 2021-10-13T10:26:33Z | 2021-10-13T10:26:33Z | null | Create `Audio` feature to handle raw audio files.
Some decisions to be further discussed:
- I have chosen `soundfile` as the audio library; another interesting library is `librosa`, but this requires `soundfile` (see [here](https://github.com/librosa/librosa/blob/main/setup.cfg#L53)). If we require some more advanced functionalities, we could eventually switch the library.
- I have implemented the audio feature as an extra: `pip install datasets[audio]`. For the moment, the typical datasets user uses only text datasets, and there is no need for them for additional package requirements for audio/image if they do not need them.
- For tests, I require audio dependencies (so that all audio functionalities are checked with our CI test suite); I exclude Linux platforms, which require an additional library to be installed with the distribution package manager
- I also require `pytest-datadir`, which allow to have (audio) data files for tests
- The audio data contain: array and sample_rate.
- The array is reshaped as 1D array (expected input for `Wav2Vec2`).
Note that to install `soundfile` on Linux, you need to install `libsndfile` using your distribution’s package manager, for example `sudo apt-get install libsndfile1`.
## Requirements Specification
- Access example with audio loading and resampling:
```python
ds[0]["audio"]
```
- Map with audio loading & resampling:
```python
def preprocess(batch):
batch["input_values"] = processor(batch["audio"]).input_values
return batch
ds = ds.map(preprocess)
```
- Map without audio loading and resampling:
```python
def preprocess(batch):
batch["labels"] = processor(batch["target_text"]).input_values
return batch
ds = ds.map(preprocess)
```
- Additional requirement specification (see https://github.com/huggingface/datasets/pull/2324#pullrequestreview-768864998): Cast audio column to change sampling sate:
```python
ds = ds.cast_column("audio", Audio(sampling_rate=16_000))
``` | {
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"For optimal storage, it would be better to:\r\n- store only the audio file path in the cache Arrow file\r\n- perform decoding of the audio file (into audio array and sample rate) on the fly, while loading the dataset from cache (or by adding a convenient `load_audio` function)",
"Thanks a lot @lhoestq for your h... |
https://api.github.com/repos/huggingface/datasets/issues/2833 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2833/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2833/comments | https://api.github.com/repos/huggingface/datasets/issues/2833/events | https://github.com/huggingface/datasets/issues/2833 | 978,296,140 | MDU6SXNzdWU5NzgyOTYxNDA= | 2,833 | IndexError when accessing first element of a Dataset if first RecordBatch is empty | [] | closed | false | null | 0 | 2021-08-24T16:49:20Z | 2021-08-24T17:21:17Z | 2021-08-24T17:21:17Z | null | The computation of the offsets of the underlying Table of a Dataset has some issues if the first RecordBatch is empty.
```python
from datasets import Dataset
import pyarrow as pa
pa_table = pa.Table.from_pydict({"a": [1]})
pa_table2 = pa.Table.from_pydict({"a": []}, schema=pa_table.schema)
ds_table = pa.concat_tables([pa_table2, pa_table])
dataset = Dataset(ds_table)
print([len(b) for b in dataset.data._batches])
# [0, 1]
print(dataset.data._offsets)
# [0 0 1] (should be [0, 1])
dataset[0]
```
raises
```python
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/datasets/table.py in _interpolation_search(arr, x)
90 else:
91 i, j = i, k
---> 92 raise IndexError(f"Invalid query '{x}' for size {arr[-1] if len(arr) else 'none'}.")
93
94
IndexError: Invalid query '0' for size 1.
```
This can be fixed by ignoring empty batches when computing `table._batches` and `table._offsets`
cc @SaulLu | {
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https://api.github.com/repos/huggingface/datasets/issues/343 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/343/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/343/comments | https://api.github.com/repos/huggingface/datasets/issues/343/events | https://github.com/huggingface/datasets/pull/343 | 651,419,630 | MDExOlB1bGxSZXF1ZXN0NDQ0Njc4NDEw | 343 | Fix nested tensorflow format | [] | closed | false | null | 0 | 2020-07-06T10:13:45Z | 2020-07-06T13:11:52Z | 2020-07-06T13:11:51Z | null | In #339 and #337 we are thinking about adding a way to export datasets to tfrecords.
However I noticed that it was not possible to do `dset.set_format("tensorflow")` on datasets with nested features like `squad`. I fixed that using a nested map operations to convert features to `tf.ragged.constant`.
I also added tests on the `set_format` function. | {
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https://api.github.com/repos/huggingface/datasets/issues/1033 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1033/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1033/comments | https://api.github.com/repos/huggingface/datasets/issues/1033/events | https://github.com/huggingface/datasets/pull/1033 | 755,921,927 | MDExOlB1bGxSZXF1ZXN0NTMxNTUxNzYw | 1,033 | Add support for ".txm" format | [] | closed | false | null | 5 | 2020-12-03T06:52:08Z | 2021-02-21T19:47:11Z | 2021-02-21T19:47:11Z | null | In dummy data generation, add support for XML-like ".txm" file format.
Also support filenames with additional compression extension: ".txm.gz". | {
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"Neat! Looks like you need a rebase and then should be good to go :) ",
"Done, @yjernite, @lhoestq.",
"If you agree, we could merge this.",
"Hi ! yes sure :) can you just merge master into this branch before we merge ?",
"Done @lhoestq "
] |
https://api.github.com/repos/huggingface/datasets/issues/5926 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5926/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5926/comments | https://api.github.com/repos/huggingface/datasets/issues/5926/events | https://github.com/huggingface/datasets/issues/5926 | 1,743,922,028 | I_kwDODunzps5n8iNs | 5,926 | Uncaught exception when generating the splits from a dataset that miss data | [] | open | false | null | 1 | 2023-06-06T13:51:01Z | 2023-06-07T07:53:16Z | null | null | ### Describe the bug
Dataset https://huggingface.co/datasets/blog_authorship_corpus has an issue with its hosting platform, since https://drive.google.com/u/0/uc?id=1cGy4RNDV87ZHEXbiozABr9gsSrZpPaPz&export=download returns 404 error.
But when trying to generate the split names, we get an exception which is now correctly caught.
Seen originally in https://github.com/huggingface/datasets-server/blob/adbdcd6710ffed4e2eb2e4cd905b5e0dff530a15/services/worker/src/worker/job_runners/config/parquet_and_info.py#L435
### Steps to reproduce the bug
```python
>>> from datasets import StreamingDownloadManager, load_dataset_builder
>>> builder = load_dataset_builder(path="blog_authorship_corpus")
Downloading builder script: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5.60k/5.60k [00:00<00:00, 23.1MB/s]
Downloading metadata: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2.81k/2.81k [00:00<00:00, 14.7MB/s]
Downloading readme: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7.30k/7.30k [00:00<00:00, 30.8MB/s]
>>> dl_manager = StreamingDownloadManager(base_path=builder.base_path)
>>> builder._split_generators(dl_manager)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/blog_authorship_corpus/6f5d78241afd8313111956f877a57db7a0e9fc6718255dc85df0928197feb683/blog_authorship_corpus.py", line 79, in _split_generators
data = dl_manager.download_and_extract(_DATA_URL)
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1087, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1039, in extract
urlpaths = map_nested(self._extract, url_or_urls, map_tuple=True)
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 435, in map_nested
return function(data_struct)
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1044, in _extract
protocol = _get_extraction_protocol(urlpath, use_auth_token=self.download_config.use_auth_token)
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 433, in _get_extraction_protocol
with fsspec.open(urlpath, **kwargs) as f:
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 439, in open
return open_files(
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 194, in __getitem__
out = super().__getitem__(item)
IndexError: list index out of range
```
### Expected behavior
We should have an Exception raised by the datasets library.
### Environment info
- `datasets` version: 2.12.0
- Platform: Linux-5.19.0-1026-aws-x86_64-with-glibc2.35
- Python version: 3.9.15
- Huggingface_hub version: 0.15.1
- PyArrow version: 11.0.0
- Pandas version: 2.0.2 | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5926/timeline | null | null | null | null | false | [
"Thanks for reporting, @severo.\r\n\r\nThis is a known issue with `fsspec`:\r\n- #5862\r\n- https://github.com/fsspec/filesystem_spec/issues/1265"
] |
https://api.github.com/repos/huggingface/datasets/issues/1753 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1753/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1753/comments | https://api.github.com/repos/huggingface/datasets/issues/1753/events | https://github.com/huggingface/datasets/pull/1753 | 789,867,685 | MDExOlB1bGxSZXF1ZXN0NTU4MTQ3Njkx | 1,753 | fix comet citations | [] | closed | false | null | 0 | 2021-01-20T10:52:38Z | 2021-01-20T14:39:30Z | 2021-01-20T14:39:30Z | null | I realized COMET citations were not showing in the hugging face metrics page:
<img width="814" alt="Screenshot 2021-01-20 at 09 48 44" src="https://user-images.githubusercontent.com/17256847/105164848-8b9da900-5b0d-11eb-9e20-a38f559d2037.png">
This pull request is intended to fix that.
Thanks! | {
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https://api.github.com/repos/huggingface/datasets/issues/1877 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1877/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1877/comments | https://api.github.com/repos/huggingface/datasets/issues/1877/events | https://github.com/huggingface/datasets/issues/1877 | 808,462,272 | MDU6SXNzdWU4MDg0NjIyNzI= | 1,877 | Allow concatenation of both in-memory and on-disk datasets | [] | closed | false | null | 6 | 2021-02-15T11:39:46Z | 2021-03-26T16:51:58Z | 2021-03-26T16:51:58Z | null | This is a prerequisite for the addition of the `add_item` feature (see #1870).
Currently there is one assumption that we would need to change: a dataset is either fully in memory (dataset._data_files is empty), or the dataset can be reloaded from disk (using the dataset._data_files).
This assumption is used for pickling for example:
- in-memory dataset can just be pickled/unpickled in-memory
- on-disk dataset can be unloaded to only keep the filepaths when pickling, and then reloaded from the disk when unpickling
Maybe let's have a design that allows a Dataset to have a Table that can be rebuilt from heterogenous sources like in-memory tables or on-disk tables ? This could also be further extended in the future
One idea would be to define a list of sources and each source implements a way to reload its corresponding pyarrow Table.
Then the dataset would be the concatenation of all these tables.
Depending on the source type, the serialization using pickle would be different. In-memory data would be copied while on-disk data would simply be replaced by the path to these data.
If you have some ideas you would like to share about the design/API feel free to do so :)
cc @albertvillanova | {
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"I started working on this. My idea is to first add the pyarrow Table wrappers InMemoryTable and MemoryMappedTable that both implement what's necessary regarding copy/pickle. Then have another wrapper that takes the concatenation of InMemoryTable/MemoryMappedTable objects.\r\n\r\nWhat's important here is that conca... |
https://api.github.com/repos/huggingface/datasets/issues/5510 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5510/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5510/comments | https://api.github.com/repos/huggingface/datasets/issues/5510/events | https://github.com/huggingface/datasets/pull/5510 | 1,575,191,549 | PR_kwDODunzps5JehbR | 5,510 | Milvus integration for search | [] | open | false | null | 5 | 2023-02-07T23:30:26Z | 2023-02-24T16:45:09Z | null | null | Signed-off-by: Filip Haltmayer <filip.haltmayer@zilliz.com> | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5510). All of your documentation changes will be reflected on that endpoint.",
"To the maintainer, sorry about the repeated run requests for formatting. Missed the `make style` outlined in contributing guidelines. ",
"Anythin... |
https://api.github.com/repos/huggingface/datasets/issues/402 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/402/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/402/comments | https://api.github.com/repos/huggingface/datasets/issues/402/events | https://github.com/huggingface/datasets/pull/402 | 658,001,288 | MDExOlB1bGxSZXF1ZXN0NDUwMDI2NTE0 | 402 | Search qa | [] | closed | false | null | 0 | 2020-07-16T09:00:10Z | 2020-07-16T14:27:00Z | 2020-07-16T14:26:59Z | null | add SearchQA dataset
#336 | {
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https://api.github.com/repos/huggingface/datasets/issues/5738 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5738/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5738/comments | https://api.github.com/repos/huggingface/datasets/issues/5738/events | https://github.com/huggingface/datasets/issues/5738 | 1,663,477,690 | I_kwDODunzps5jJqe6 | 5,738 | load_dataset("text","dataset.txt") loads the wrong dataset! | [] | closed | false | null | 1 | 2023-04-12T01:07:46Z | 2023-04-19T12:08:27Z | 2023-04-19T12:08:27Z | null | ### Describe the bug
I am trying to load my own custom text dataset using the load_dataset function. My dataset is a bunch of ordered text, think along the lines of shakespeare plays. However, after I load the dataset and I inspect it, the dataset is a table with a bunch of latitude and longitude values! What in the world??
### Steps to reproduce the bug
my_dataset = load_dataset("text","TextFile.txt")
my_dataset
### Expected behavior
I expected the dataset to contain the actual data from the text document that I used.
### Environment info
Google Colab | {
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"You need to provide a text file as `data_files`, not as a configuration:\r\n\r\n```python\r\nmy_dataset = load_dataset(\"text\", data_files=\"TextFile.txt\")\r\n```\r\n\r\nOtherwise, since `data_files` is `None`, it picks up Colab's sample datasets from the `content` dir."
] |
https://api.github.com/repos/huggingface/datasets/issues/375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/375/comments | https://api.github.com/repos/huggingface/datasets/issues/375/events | https://github.com/huggingface/datasets/issues/375 | 655,023,307 | MDU6SXNzdWU2NTUwMjMzMDc= | 375 | TypeError when computing bertscore | [] | closed | false | null | 2 | 2020-07-10T20:37:44Z | 2022-06-01T15:15:59Z | 2022-06-01T15:15:59Z | null | Hi,
I installed nlp 0.3.0 via pip, and my python version is 3.7.
When I tried to compute bertscore with the code:
```
import nlp
bertscore = nlp.load_metric('bertscore')
# load hyps and refs
...
print (bertscore.compute(hyps, refs, lang='en'))
```
I got the following error.
```
Traceback (most recent call last):
File "bert_score_evaluate.py", line 16, in <module>
print (bertscore.compute(hyps, refs, lang='en'))
File "/home/willywsm/anaconda3/envs/torcher/lib/python3.7/site-packages/nlp/metric.py", line 200, in compute
output = self._compute(predictions=predictions, references=references, **metrics_kwargs)
File "/home/willywsm/anaconda3/envs/torcher/lib/python3.7/site-packages/nlp/metrics/bertscore/fb176889831bf0ce995ed197edc94b2e9a83f647a869bb8c9477dbb2d04d0f08/bertscore.py", line 105, in _compute
hashcode = bert_score.utils.get_hash(model_type, num_layers, idf, rescale_with_baseline)
TypeError: get_hash() takes 3 positional arguments but 4 were given
```
It seems like there is something wrong with get_hash() function? | {
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"I am not able to reproduce this issue on my side.\r\nCould you give us more details about the inputs you used ?\r\n\r\nI do get another error though:\r\n```\r\n~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/bert_score/utils.py in bert_cos_score_idf(model, refs, hyps, tokenizer, idf_dict, verbose, batch_siz... |
https://api.github.com/repos/huggingface/datasets/issues/3725 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3725/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3725/comments | https://api.github.com/repos/huggingface/datasets/issues/3725/events | https://github.com/huggingface/datasets/pull/3725 | 1,138,835,625 | PR_kwDODunzps4y3bOG | 3,725 | Pin pandas to avoid bug in streaming mode | [] | closed | false | null | 0 | 2022-02-15T15:21:00Z | 2022-02-15T15:52:38Z | 2022-02-15T15:52:37Z | null | Temporarily pin pandas version to avoid bug in streaming mode (patching no longer works).
Related to #3724. | {
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https://api.github.com/repos/huggingface/datasets/issues/2076 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2076/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2076/comments | https://api.github.com/repos/huggingface/datasets/issues/2076/events | https://github.com/huggingface/datasets/issues/2076 | 834,445,296 | MDU6SXNzdWU4MzQ0NDUyOTY= | 2,076 | Issue: Dataset download error | [
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] | open | false | null | 7 | 2021-03-18T06:36:06Z | 2021-03-22T11:52:31Z | null | null | The download link in `iwslt2017.py` file does not seem to work anymore.
For example, `FileNotFoundError: Couldn't find file at https://wit3.fbk.eu/archive/2017-01-trnted/texts/zh/en/zh-en.tgz`
Would be nice if we could modify it script and use the new downloadable link? | {
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"Hi @XuhuiZhou, thanks for reporting this issue. \r\n\r\nIndeed, the old links are no longer valid (404 Not Found error), and the script must be updated with the new links to Google Drive.",
"It would be nice to update the urls indeed !\r\n\r\nTo do this, you just need to replace the urls in `iwslt2017.py` and th... |
https://api.github.com/repos/huggingface/datasets/issues/2085 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2085/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2085/comments | https://api.github.com/repos/huggingface/datasets/issues/2085/events | https://github.com/huggingface/datasets/pull/2085 | 835,870,994 | MDExOlB1bGxSZXF1ZXN0NTk2NDYyOTc2 | 2,085 | Fix max_wait_time in requests | [] | closed | false | null | 0 | 2021-03-19T11:22:26Z | 2021-03-23T15:36:38Z | 2021-03-23T15:36:37Z | null | it was handled as a min time, not max cc @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/5624 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5624/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5624/comments | https://api.github.com/repos/huggingface/datasets/issues/5624/events | https://github.com/huggingface/datasets/issues/5624 | 1,617,400,192 | I_kwDODunzps5gZ5GA | 5,624 | glue datasets returning -1 for test split | [] | closed | false | null | 1 | 2023-03-09T14:47:18Z | 2023-03-09T16:49:29Z | 2023-03-09T16:49:29Z | null | ### Describe the bug
Downloading any dataset from GLUE has -1 as class labels for test split. Train and validation have regular 0/1 class labels. This is also present in the dataset card online.
### Steps to reproduce the bug
```
dataset = load_dataset("glue", "sst2")
for d in dataset:
# prints out -1
print(d["label"]
```
### Expected behavior
Expected behavior should be 0/1 instead of -1.
### Environment info
- `datasets` version: 2.4.0
- Platform: Linux-5.15.0-46-generic-x86_64-with-glibc2.17
- Python version: 3.8.16
- PyArrow version: 8.0.0
- Pandas version: 1.5.3
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"Hi @lithafnium, thanks for reporting.\r\n\r\nPlease note that you can use the \"Community\" tab in the corresponding dataset page to start any discussion: https://huggingface.co/datasets/glue/discussions\r\n\r\nIndeed this issue was already raised there (https://huggingface.co/datasets/glue/discussions/5) and answ... |
https://api.github.com/repos/huggingface/datasets/issues/2124 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2124/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2124/comments | https://api.github.com/repos/huggingface/datasets/issues/2124/events | https://github.com/huggingface/datasets/issues/2124 | 842,627,729 | MDU6SXNzdWU4NDI2Mjc3Mjk= | 2,124 | Adding ScaNN library to do MIPS? | [] | open | false | null | 1 | 2021-03-28T00:07:00Z | 2021-03-29T13:23:43Z | null | null | @lhoestq Hi I am thinking of adding this new google library to do the MIPS similar to **add_faiss_idex**. As the paper suggests, it is really fast when it comes to retrieving the nearest neighbors.
https://github.com/google-research/google-research/tree/master/scann
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"I haven't played with it (yet) but it sounds really cool !\r\n"
] |
https://api.github.com/repos/huggingface/datasets/issues/1841 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1841/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1841/comments | https://api.github.com/repos/huggingface/datasets/issues/1841/events | https://github.com/huggingface/datasets/issues/1841 | 803,561,123 | MDU6SXNzdWU4MDM1NjExMjM= | 1,841 | Add ljspeech | [
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"color": "d93f0b",... | closed | false | null | 0 | 2021-02-08T13:22:26Z | 2021-03-15T05:59:02Z | 2021-03-15T05:59:02Z | null | ## Adding a Dataset
- **Name:** *ljspeech*
- **Description:** *This is a public domain speech dataset consisting of 13,100 short audio clips of a single speaker reading passages from 7 non-fiction books. A transcription is provided for each clip. Clips vary in length from 1 to 10 seconds and have a total length of approximately 24 hours.
The texts were published between 1884 and 1964, and are in the public domain. The audio was recorded in 2016-17 by the LibriVox project and is also in the public domain.)*
- **Paper:** *Homepage*: https://keithito.com/LJ-Speech-Dataset/
- **Data:** *https://keithito.com/LJ-Speech-Dataset/*
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/datasets/catalog/ljspeech
If interested in tackling this issue, feel free to tag @patrickvonplaten
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| {
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https://api.github.com/repos/huggingface/datasets/issues/798 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/798/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/798/comments | https://api.github.com/repos/huggingface/datasets/issues/798/events | https://github.com/huggingface/datasets/issues/798 | 735,518,805 | MDU6SXNzdWU3MzU1MTg4MDU= | 798 | Cannot load TREC dataset: ConnectionError | [
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] | closed | false | null | 9 | 2020-11-03T17:45:22Z | 2022-02-14T15:34:22Z | 2022-02-14T15:34:22Z | null | ## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here. | {
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"Hi ! Indeed there's an issue with those links.\r\nWe should probably use the target urls of the redirections instead",
"Hi, the same issue here, could you tell me how to download it through datasets? thanks ",
"Same issue. ",
"Actually it's already fixed on the master branch since #740 \r\nI'll do the 1.1.3 ... |
https://api.github.com/repos/huggingface/datasets/issues/2248 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2248/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2248/comments | https://api.github.com/repos/huggingface/datasets/issues/2248/events | https://github.com/huggingface/datasets/pull/2248 | 864,853,447 | MDExOlB1bGxSZXF1ZXN0NjIxMDEyNzg5 | 2,248 | Implement Dataset to JSON | [
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} | 0 | 2021-04-22T11:46:51Z | 2021-04-27T15:29:21Z | 2021-04-27T15:29:20Z | null | Implement `Dataset.to_json`. | {
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https://api.github.com/repos/huggingface/datasets/issues/3791 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3791/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3791/comments | https://api.github.com/repos/huggingface/datasets/issues/3791/events | https://github.com/huggingface/datasets/pull/3791 | 1,150,733,475 | PR_kwDODunzps4zevU2 | 3,791 | Add `data_dir` to `data_files` resolution and misc improvements to HfFileSystem | [] | closed | false | null | 0 | 2022-02-25T18:26:35Z | 2022-03-01T13:10:43Z | 2022-03-01T13:10:42Z | null | As discussed in https://github.com/huggingface/datasets/pull/2830#issuecomment-1048989764, this PR adds a QOL improvement to easily reference the files inside a directory in `load_dataset` using the `data_dir` param (very handy for ImageFolder because it avoids globbing, but also useful for the other loaders). Additionally, it fixes the issue with `HfFileSystem.isdir`, which would previously always return `False`, and aligns the path-handling logic in `HfFileSystem` with `fsspec.GitHubFileSystem`. | {
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