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https://api.github.com/repos/huggingface/datasets/issues/2966 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2966/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2966/comments | https://api.github.com/repos/huggingface/datasets/issues/2966/events | https://github.com/huggingface/datasets/pull/2966 | 1,007,142,233 | PR_kwDODunzps4sRRMs | 2,966 | Upload greek-legal-code dataset | {
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"@albertvillanova @lhoestq thank you very much for reviewing! :hugs: \r\n\r\nI 've pushed some updates/changes as requested."
] | 2021-09-25T16:52:15Z | 2021-10-13T13:37:30Z | 2021-10-13T13:37:30Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3924 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3924/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3924/comments | https://api.github.com/repos/huggingface/datasets/issues/3924/events | https://github.com/huggingface/datasets/pull/3924 | 1,169,805,813 | PR_kwDODunzps40eED5 | 3,924 | Document cases for github datasets | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3924). All of your documentation changes will be reflected on that endpoint.",
"Yay!"
] | 2022-03-15T15:10:10Z | 2022-04-05T18:33:15Z | 2022-03-15T15:41:23Z | MEMBER | null | 0 | {
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} | In general we recommend adding the new dataset under a username or organization in the Hugging Face Hub at [hf.co/datasets](hf.co/datasets), but users can still add a dataset on github in some cases.
I added a paragraph in the documentation to explain in which cases it can make more sense to open a PR on github:
- when you need the dataset to be reviewed
- when you need long-term maintenance from the HF team
- when there’s no clear org name / namespace that you can put the dataset under | {
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https://api.github.com/repos/huggingface/datasets/issues/5880 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5880/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5880/comments | https://api.github.com/repos/huggingface/datasets/issues/5880/events | https://github.com/huggingface/datasets/issues/5880 | 1,719,090,101 | I_kwDODunzps5mdzu1 | 5,880 | load_dataset from s3 file system through streaming can't not iterate data | {
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"This sounds related to #5281.\r\n\r\nCan you try passing `storage_options=s3_client.storage_options` instead passing it to `use_auth_token=` ?",
"I tried `storage_options` before, but it doesn't work, I checked our source code and I found that we even didn't pass this parameter to the following process. if I use... | 2023-05-22T07:40:27Z | 2023-05-26T12:52:08Z | null | CONTRIBUTOR | null | null | null | ### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-45b5-ac68-4e7c664c2ed0">
<img width="1144" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/76872af3-8b3c-42ff-9f55-528c920a7af1">
we can change 4 lines to fix this bug, you can check whether it is ok for us.
<img width="941" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/5a22155a-ece7-496c-8506-047e5c235cd3">
### Steps to reproduce the bug
1. storage a file in you s3 file system
2. use load_dataset to read it through streaming
3. iterate it
### Expected behavior
can iterate it successfully
### Environment info
- `datasets` version: 2.12.0
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.16
- Huggingface_hub version: 0.14.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.1
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https://api.github.com/repos/huggingface/datasets/issues/4853 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4853/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4853/comments | https://api.github.com/repos/huggingface/datasets/issues/4853/events | https://github.com/huggingface/datasets/pull/4853 | 1,339,456,490 | PR_kwDODunzps49NFNL | 4,853 | Fix bug and checksums in exams dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-15T20:17:57Z | 2022-08-16T06:43:57Z | 2022-08-16T06:29:06Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3926 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3926/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3926/comments | https://api.github.com/repos/huggingface/datasets/issues/3926/events | https://github.com/huggingface/datasets/pull/3926 | 1,169,945,052 | PR_kwDODunzps40ehVP | 3,926 | Doc maintenance | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3926). All of your documentation changes will be reflected on that endpoint."
] | 2022-03-15T17:00:46Z | 2022-03-15T19:27:15Z | 2022-03-15T19:27:12Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5713 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5713/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5713/comments | https://api.github.com/repos/huggingface/datasets/issues/5713/events | https://github.com/huggingface/datasets/issues/5713 | 1,657,141,251 | I_kwDODunzps5ixfgD | 5,713 | ArrowNotImplementedError when loading dataset from the hub | {
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"Hi Julien ! This sounds related to https://github.com/huggingface/datasets/issues/5695 - TL;DR: you need to have shards smaller than 2GB to avoid this issue\r\n\r\nThe number of rows per shard is computed using an estimated size of the full dataset, which can sometimes lead to shards bigger than `max_shard_size`. ... | 2023-04-06T10:27:22Z | 2023-04-06T13:06:22Z | 2023-04-06T13:06:21Z | CONTRIBUTOR | null | null | null | ### Describe the bug
Hello,
I have created a dataset by using the image loader. Once the dataset is created I try to download it and I get the error:
```
Traceback (most recent call last):
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-packages/datasets/builder.py", line 1860, in _prepare_split_single
for _, table in generator:
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-packages/datasets/packaged_modules/parquet/parquet.py", line 69, in _generate_tables
for batch_idx, record_batch in enumerate(
File "pyarrow/_parquet.pyx", line 1323, in iter_batches
File "pyarrow/error.pxi", line 121, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Nested data conversions not implemented for chunked array outputs
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-packages/datasets/load.py", line 1791, in load_dataset
builder_instance.download_and_prepare(
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-packages/datasets/builder.py", line 891, in download_and_prepare
self._download_and_prepare(
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-packages/datasets/builder.py", line 986, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-packages/datasets/builder.py", line 1748, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-packages/datasets/builder.py", line 1893, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.builder.DatasetGenerationError: An error occurred while generating the dataset
```
### Steps to reproduce the bug
Create the dataset and push it to the hub:
```python
from datasets import load_dataset
dataset = load_dataset("imagefolder", data_dir="/path/to/dataset")
dataset.push_to_hub("org/dataset-name", private=True, max_shard_size="1GB")
```
Then use it:
```python
from datasets import load_dataset
dataset = load_dataset("org/dataset-name")
```
### Expected behavior
To properly download and use the pushed dataset.
Something else to note is that I specified to have shards of 1GB max, but at the end, for the train set, it is an almost 7GB single file that is pushed.
### Environment info
- `datasets` version: 2.11.0
- Platform: Linux-5.15.90.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
- Python version: 3.10.10
- Huggingface_hub version: 0.13.3
- PyArrow version: 11.0.0
- Pandas version: 2.0.0 | {
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"Thanks for reporting @beyondguo.\r\n\r\nIndeed, we generate this dataset from this raw data file URL: https://data.deepai.org/conll2003.zip\r\nAnd that URL only contains the English version.",
"The German data requires payment\r\n\r\nThe [original task page](https://www.clips.uantwerpen.be/conll2003/ner/) states... | 2022-04-27T00:53:52Z | 2023-07-25T15:10:15Z | 2023-07-25T15:10:15Z | NONE | null | null | null | 
But on huggingface datasets:
Where is the German data? | {
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https://api.github.com/repos/huggingface/datasets/issues/1460 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1460/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1460/comments | https://api.github.com/repos/huggingface/datasets/issues/1460/events | https://github.com/huggingface/datasets/pull/1460 | 761,349,149 | MDExOlB1bGxSZXF1ZXN0NTM2MDI3NzYy | 1,460 | add Bengali Hate Speech dataset | {
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"@lhoestq I think you might want to look at the dataset, and the first data instances mentioned in the README.md is very much offensive. Though this dataset is based on hate speech but I found the dataset heavily disturbing as Bengali is my native language.",
"Hi @tanmoyio indeed you're right.\r\nWe should *at le... | 2020-12-10T15:40:55Z | 2021-09-17T16:54:53Z | 2021-01-04T14:08:29Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3534 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3534/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3534/comments | https://api.github.com/repos/huggingface/datasets/issues/3534/events | https://github.com/huggingface/datasets/pull/3534 | 1,094,352,449 | PR_kwDODunzps4wj3LE | 3,534 | Update wiki_dpr README.md | {
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} | Some infos of wiki_dpr were missing as noted in https://github.com/huggingface/datasets/issues/3510, I added them and updated the tags and the examples
Close #3510. | {
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https://api.github.com/repos/huggingface/datasets/issues/6003 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6003/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6003/comments | https://api.github.com/repos/huggingface/datasets/issues/6003/events | https://github.com/huggingface/datasets/issues/6003 | 1,786,554,110 | I_kwDODunzps5qfKb- | 6,003 | interleave_datasets & DataCollatorForLanguageModeling having a conflict ? | {
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} | [] | open | false | null | [] | null | [] | 2023-07-03T17:15:31Z | 2023-07-03T17:15:31Z | null | NONE | null | null | null | ### Describe the bug
Hi everyone :)
I have two local & custom datasets (1 "sentence" per line) which I split along the 95/5 lines for pre-training a Bert model. I use a modified version of `run_mlm.py` in order to be able to make use of `interleave_dataset`:
- `tokenize()` runs fine
- `group_text()` runs fine
Everytime, on step 19, I get
```pytb
File "env/lib/python3.9/site-packages/transformers/data/data_collator.py", line 779, in torch_mask_tokens
inputs[indices_random] = random_words[indices_random]
RuntimeError: Index put requires the source and destination dtypes match, got Float for the destination and Long for the source.
```
I tried:
- training without interleave on dataset 1, it runs
- training without interleave on dataset 2, it runs
- training without `.to_iterable_dataset()`, it hangs then crash
- training without group_text() and padding to max_length seemed to fix the issue, but who knows if this was just because it was an issue that would come much later in terms of steps.
I might have coded something wrong, but I don't get what
### Steps to reproduce the bug
I have this function:
```py
def build_dataset(path: str, percent: str):
dataset = load_dataset(
"text",
data_files={"train": [path]},
split=f"train[{percent}]"
)
dataset = dataset.map(
lambda examples: tokenize(examples["text"]),
batched=True,
num_proc=num_proc,
)
dataset = dataset.map(
group_texts,
batched=True,
num_proc=num_proc,
desc=f"Grouping texts in chunks of {tokenizer.max_seq_length}",
remove_columns=["text"]
)
print(len(dataset))
return dataset.to_iterable_dataset()
```
I hardcoded group_text:
```py
def group_texts(examples):
# Concatenate all texts.
concatenated_examples = {k: list(chain(*examples[k])) for k in examples.keys()}
total_length = len(concatenated_examples[list(examples.keys())[0]])
# We drop the small remainder, and if the total_length < max_seq_length we exclude this batch and return an empty dict.
# We could add padding if the model supported it instead of this drop, you can customize this part to your needs.
total_length = (total_length // 512) * 512
# Split by chunks of max_len.
result = {
k: [t[i: i + 512] for i in range(0, total_length, 512)]
for k, t in concatenated_examples.items()
}
# result = {k: [el for el in elements if el] for k, elements in result.items()}
return result
```
And then I build datasets using the following code:
```py
train1 = build_dataset("d1.txt", ":95%")
train2 = build_dataset("d2.txt", ":95%")
dev1 = build_dataset("d1.txt", "95%:")
dev2 = build_dataset("d2.txt", "95%:")
```
and finally I run
```py
train_dataset = interleave_datasets(
[train1, train2],
probabilities=[0.8, 0.2],
seed=42
)
eval_dataset = interleave_datasets(
[dev1, dev2],
probabilities=[0.8, 0.2],
seed=42
)
```
Then I run the training part which remains mostly untouched:
> CUDA_VISIBLE_DEVICES=1 python custom_dataset.py --model_type bert --per_device_train_batch_size 32 --do_train --output_dir /var/mlm/training-bert/model --max_seq_length 512 --save_steps 10000 --save_total_limit 3 --auto_find_batch_size --logging_dir ./logs-bert --learning_rate 0.0001 --do_train --num_train_epochs 25 --warmup_steps 10000 --max_step 45000 --fp16
### Expected behavior
The model should then train normally, but fails every time at the same step (19).
printing the variables at `inputs[indices_random] = random_words[indices_random]` shows a magnificient empty tensor (, 32) [if I remember well]
### Environment info
transformers[torch] 4.30.2
Ubuntu
A100 0 CUDA 12
Driver Version: 525.116.04 | {
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https://api.github.com/repos/huggingface/datasets/issues/3290 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3290/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3290/comments | https://api.github.com/repos/huggingface/datasets/issues/3290/events | https://github.com/huggingface/datasets/pull/3290 | 1,056,414,856 | PR_kwDODunzps4uqzcv | 3,290 | Make several audio datasets streamable | {
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} | [] | closed | false | null | [] | null | [
"Reading FLAC (for `librispeech_asr`) works OK for me (`soundfile` version: `0.10.3`):\r\n```python\r\nIn [2]: ds = load_dataset(\"datasets/librispeech_asr/librispeech_asr.py\", \"clean\", streaming=True, split=\"train.100\")\r\n\r\nIn [3]: item = next(iter(ds))\r\n\r\nIn [4]: item.keys()\r\nOut[4]: dict_keys(['fil... | 2021-11-17T17:43:41Z | 2022-02-01T21:00:52Z | 2021-11-19T15:08:57Z | MEMBER | null | 0 | {
"diff_url": "https://github.com/huggingface/datasets/pull/3290.diff",
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/3290"
} | <s>Needs https://github.com/huggingface/datasets/pull/3129 to be merged first</s>
Make those audio datasets streamable:
- [x] common_voice
- [x] openslr
- [x] vivos
- [x] librispeech_asr <s>(still has some issues to read FLAC)</s> *actually it's ok*
- [ ] <s>multilingual_librispeech (yet to be converted)</S> *TODO in a separate PR* | {
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https://api.github.com/repos/huggingface/datasets/issues/5722 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5722/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5722/comments | https://api.github.com/repos/huggingface/datasets/issues/5722/events | https://github.com/huggingface/datasets/issues/5722 | 1,659,837,510 | I_kwDODunzps5i7xxG | 5,722 | Distributed Training Error on Customized Dataset | {
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"Hmm the error doesn't seem related to data loading.\r\n\r\nRegarding `split_dataset_by_node`: it's generally used to split an iterable dataset (e.g. when streaming) in pytorch DDP. It's not needed if you use a regular dataset since the pytorch DataLoader already assigns a subset of the dataset indices to each node... | 2023-04-09T11:04:59Z | 2023-07-24T14:50:46Z | 2023-07-24T14:50:46Z | NONE | null | null | null | Hi guys, recently I tried to use `datasets` to train a dual encoder.
I finish my own datasets according to the nice [tutorial](https://huggingface.co/docs/datasets/v2.11.0/en/dataset_script)
Here are my code:
```python
class RetrivalDataset(datasets.GeneratorBasedBuilder):
"""CrossEncoder dataset."""
BUILDER_CONFIGS = [RetrivalConfig(name="DuReader")]
# DEFAULT_CONFIG_NAME = "DuReader"
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features(
{
"id": datasets.Value("string"),
"question": datasets.Value("string"),
"documents": Sequence(datasets.Value("string")),
}
),
supervised_keys=None,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
train_file = self.config.data_dir + self.config.train_file
valid_file = self.config.data_dir + self.config.valid_file
logger.info(f"Training on {self.config.train_file}")
logger.info(f"Evaluating on {self.config.valid_file}")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN, gen_kwargs={"file_path": train_file}
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION, gen_kwargs={"file_path": valid_file}
),
]
def _generate_examples(self, file_path):
with jsonlines.open(file_path, "r") as f:
for record in f:
label = record["label"]
question = record["question"]
# dual encoder
all_documents = record["all_documents"]
positive_paragraph = all_documents.pop(label)
all_documents = [positive_paragraph] + all_documents
u_id = "{}_#_{}".format(
md5_hash(question + "".join(all_documents)),
"".join(random.sample(string.ascii_letters + string.digits, 7)),
)
item = {
"question": question,
"documents": all_documents,
"id": u_id,
}
yield u_id, item
```
It works well on single GPU, but got errors as follows when used DDP:
```python
Detected mismatch between collectives on ranks. Rank 1 is running collective: CollectiveFingerPrint(OpType=BARRIER), but Rank 0 is running collective: CollectiveFingerPrint(OpType=ALLGATHER_COALESCED)
```
Here are my train script on a two A100 mechine:
```bash
export TORCH_DISTRIBUTED_DEBUG=DETAIL
export TORCH_SHOW_CPP_STACKTRACES=1
export NCCL_DEBUG=INFO
export NCCL_DEBUG_SUBSYS=INIT,COLL,ENV
nohup torchrun --nproc_per_node 2 train.py experiments/de-big.json >logs/de-big.log 2>&1&
```
I am not sure if this error below related to my dataset code when use DDP. And I notice the PR(#5369 ), but I don't know when and where should I used the function(`split_dataset_by_node`) .
@lhoestq hope you could help me?
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https://api.github.com/repos/huggingface/datasets/issues/2487 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2487/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2487/comments | https://api.github.com/repos/huggingface/datasets/issues/2487/events | https://github.com/huggingface/datasets/pull/2487 | 919,452,407 | MDExOlB1bGxSZXF1ZXN0NjY4Nzc5Mjk0 | 2,487 | Set configurable extracted datasets path | {
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"Let me push a small fix... 😉 ",
"Thanks !"
] | 2021-06-12T05:47:29Z | 2021-06-14T09:30:17Z | 2021-06-14T09:02:56Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5547 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5547/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5547/comments | https://api.github.com/repos/huggingface/datasets/issues/5547/events | https://github.com/huggingface/datasets/pull/5547 | 1,590,468,200 | PR_kwDODunzps5KRmcf | 5,547 | Add JAX device selection when formatting | {
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"The code below was throwing a warning:\r\n\r\n```python\r\nclass JaxFormatter(Formatter[Mapping, \"jax.Array\", Mapping]):\r\n def __init__(self, features=None, device=None, **jnp_array_kwargs):\r\n super().__init__(features=features)\r\n import jax\r\n from jaxlib.xla_extension import Devi... | 2023-02-18T20:57:40Z | 2023-02-21T16:10:55Z | 2023-02-21T16:04:03Z | CONTRIBUTOR | null | 0 | {
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} | ## What's in this PR?
After exploring for a while the JAX integration in 🤗`datasets`, I found out that, even though JAX prioritizes the TPU and GPU as the default device when available, the `JaxFormatter` doesn't let you specify the device where you want to place the `jax.Array`s in case you don't want to rely on JAX's default array placement.
So on, I've included the `device` param in `JaxFormatter` but there are some things to take into consideration:
* A formatted `Dataset` is copied with `copy.deepcopy` which means that if one adds the param `device` in `JaxFormatter` as a `jaxlib.xla_extension.Device`, it "fails" because that object cannot be serialized (instead of serializing the param adds a random hash instead). That's the reason why I added a function `_map_devices_to_str` to basically create a mapping of strings to `jaxlib.xla_extension.Device`s so that `self.device` is a string and not a `jaxlib.xla_extension.Device`.
* To create a `jax.Array` in a device you need to either create it in the default device and then move it to the desired device with `jax.device_put` or directly create it in the device you want with `jax.default_device()` context manager.
* JAX will create an array by default in `jax.devices()[0]`
More information on JAX device management is available at https://jax.readthedocs.io/en/latest/faq.html#controlling-data-and-computation-placement-on-devices
## What's missing in this PR?
I've tested it both locally in CPU (Mac M2 and Mac M1, as no GPU support for Mac yet), and in GPU and TPU in Google Colab, let me know if you want me to provide you the Notebook for the latter.
But I did not implement any integration test as I wanted to get your feedback first. | {
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https://api.github.com/repos/huggingface/datasets/issues/5234 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5234/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5234/comments | https://api.github.com/repos/huggingface/datasets/issues/5234/events | https://github.com/huggingface/datasets/pull/5234 | 1,447,999,062 | PR_kwDODunzps5C1diq | 5,234 | fix: dataset path should be absolute | {
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"Good catch thanks ! Have you tried to use the absolue path in `MemoryMappedTable.__init__` in `table.py`?\r\n\r\nI think it can fix issues with relative paths at more levels than just fixing it `load_from_disk`. If it works I think it would be a more robust fix to this issue",
"@lhoestq right, that actually fixe... | 2022-11-14T12:47:40Z | 2022-12-07T23:49:22Z | 2022-12-07T23:46:34Z | CONTRIBUTOR | null | 0 | {
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} | cache_file_name depends on dataset's path.
A simple way where this could cause a problem:
```
import os
import datasets
def add_prefix(example):
example["text"] = "Review: " + example["text"]
return example
ds = datasets.load_from_disk("a/relative/path")
os.chdir("/tmp")
ds_1 = ds.map(add_prefix)
```
while it may feel that the `chdir` is quite constructed, there are many scenarios when the current working dir can/will change... | {
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"caching issue, seems to work again.."
] | 2021-03-04T14:18:55Z | 2021-03-04T14:31:07Z | 2021-03-04T14:31:07Z | NONE | null | null | null | ~\.cache\huggingface\modules\datasets_modules\datasets\wmt14\43e717d978d2261502b0194999583acb874ba73b0f4aed0ada2889d1bb00f36e\wmt_utils.py in _split_generators(self, dl_manager)
758 # Extract manually downloaded files.
759 manual_files = dl_manager.extract(manual_paths_dict)
--> 760 extraction_map = dict(downloaded_files, **manual_files)
761
762 for language in self.config.language_pair:
TypeError: type object argument after ** must be a mapping, not list | {
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https://api.github.com/repos/huggingface/datasets/issues/4652 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4652/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4652/comments | https://api.github.com/repos/huggingface/datasets/issues/4652/events | https://github.com/huggingface/datasets/issues/4652 | 1,296,697,498 | I_kwDODunzps5NSgia | 4,652 | Add Sentence Compression Dataset | {
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"uploaded dataset [here](https://huggingface.co/datasets/embedding-data/sentence-compression)."
] | 2022-07-07T02:13:46Z | 2022-07-14T02:11:48Z | 2022-07-14T02:11:48Z | NONE | null | null | null | ## Adding a Dataset
- **Name:** *Sentence Compression*
- **Description:** *Large corpus of uncompressed and compressed sentences from news articles.*
- **Paper:** *https://www.aclweb.org/anthology/D13-1155/*
- **Data:** *https://github.com/google-research-datasets/sentence-compression/tree/master/data*
- **Motivation:** *Dataset for training and evaluating models of conversational response*
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https://api.github.com/repos/huggingface/datasets/issues/4840 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4840/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4840/comments | https://api.github.com/repos/huggingface/datasets/issues/4840/events | https://github.com/huggingface/datasets/issues/4840 | 1,337,342,672 | I_kwDODunzps5PtjrQ | 4,840 | Dataset Viewer issue for darragh/demo_data_raw3 | {
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"do you have an idea of why it can occur @huggingface/datasets? The dataset consists of a single parquet file.",
"Thanks for reporting @severo.\r\n\r\nI'm not able to reproduce that error. I get instead:\r\n```\r\nFileNotFoundError: [Errno 2] No such file or directory: 'orix/data/ChiSig/唐合乐-9-3.jpg'\r\n```\r\n\r\... | 2022-08-12T15:22:58Z | 2022-09-08T07:55:44Z | null | CONTRIBUTOR | null | null | null | ### Link
https://huggingface.co/datasets/darragh/demo_data_raw3
### Description
```
Exception: ValueError
Message: Arrow type extension<arrow.py_extension_type<pyarrow.lib.UnknownExtensionType>> does not have a datasets dtype equivalent.
```
reported by @NielsRogge
### Owner
No | {
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https://api.github.com/repos/huggingface/datasets/issues/2841 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2841/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2841/comments | https://api.github.com/repos/huggingface/datasets/issues/2841/events | https://github.com/huggingface/datasets/issues/2841 | 980,497,321 | MDU6SXNzdWU5ODA0OTczMjE= | 2,841 | Adding GLUECoS Hinglish and Spanglish code-switching bemchmark | {
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"Hi @yjernite I am interested in adding this dataset. \r\nIn the repo they have also added a code mixed MT task from English to Hinglish [here](https://github.com/microsoft/GLUECoS#code-mixed-machine-translation-task). I think this could be a good dataset addition in itself and then I can add the rest of the GLUECo... | 2021-08-26T17:47:39Z | 2021-10-20T18:41:20Z | null | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** GLUECoS
- **Description:** a Microsoft Benchmark to evaluate code-switching for only two language pairs but a variety of tasks
- **Paper:** https://aclanthology.org/2020.acl-main.329/
- **Data:** https://github.com/microsoft/GLUECoS
- **Motivation:** We currently only have [one other](https://huggingface.co/datasets/lince) dataset for code-switching
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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"Very cool! Do you have a link to the code that you're using to eagerly fetch the data? Would also be interested in hacking around something here for pre-fetching iterable datasets",
"I ended up just switching back to the pytorch dataloader and using it's multiprocessing functionality to handle this :(. I'm just ... | 2023-05-20T15:25:40Z | 2023-06-01T17:40:00Z | null | NONE | null | null | null | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk space setting as well as quick iteration where you're iterating though different accelerator environments (e.x changing ec2 instances quickly to figure out batch/sec for a particular architecture).
Currently, using the IterableDataset results in accelerators becoming basically useless due to the massive bottleneck induced by the dataset lazy loading/transform/mapping.
I've considered two alternatives:
PyTorch dataloader that handles this. However, I'm using jax, and I believe this is a piece of functionality that should live in the stream class.
Replicating the "num_workers" part of the PyTorch DataLoader to eagerly load batches and apply the transform so Arrow caching will automatically cache results and make them accessible.
### Your contribution
I may or may not have time to do this. Currently, I've written the basic multiprocessor approach to handle the eager DataLoader for my own use case with code that's not integrated to datasets. I'd definitely see this as being the default over the regular Dataset for most people given that they wouldn't have to wait on the datasets while also not worrying about performance. | {
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https://api.github.com/repos/huggingface/datasets/issues/5314 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5314/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5314/comments | https://api.github.com/repos/huggingface/datasets/issues/5314/events | https://github.com/huggingface/datasets/issues/5314 | 1,469,685,118 | I_kwDODunzps5XmZ1- | 5,314 | Datasets: classification_report() got an unexpected keyword argument 'suffix' | {
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"This seems similar to https://github.com/huggingface/datasets/issues/2512 Can you try to update seqeval ? ",
"@JonathanAlis also note that the metrics are deprecated in our `datasets` library.\r\n\r\nPlease, use the new library 🤗 Evaluate instead: https://huggingface.co/docs/evaluate"
] | 2022-11-30T14:01:03Z | 2023-07-21T14:40:31Z | 2023-07-21T14:40:31Z | NONE | null | null | null | https://github.com/huggingface/datasets/blob/main/metrics/seqeval/seqeval.py
> import datasets
predictions = [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]
references = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]
seqeval = datasets.load_metric("seqeval")
results = seqeval.compute(predictions=predictions, references=references)
print(list(results.keys()))
print(results["overall_f1"])
print(results["PER"]["f1"])
It raises the error:
> TypeError: classification_report() got an unexpected keyword argument 'suffix'
For context, versions on my pip list -v
> datasets 1.12.1
seqeval 1.2.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/5344 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5344/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5344/comments | https://api.github.com/repos/huggingface/datasets/issues/5344/events | https://github.com/huggingface/datasets/pull/5344 | 1,485,628,319 | PR_kwDODunzps5E2BPN | 5,344 | Clean up Dataset and DatasetDict | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-12-09T00:02:08Z | 2022-12-13T00:56:07Z | 2022-12-13T00:53:02Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4643 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4643/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4643/comments | https://api.github.com/repos/huggingface/datasets/issues/4643/events | https://github.com/huggingface/datasets/pull/4643 | 1,295,852,650 | PR_kwDODunzps468Cqk | 4,643 | Rename master to main | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"All the mentions I found on google were simple URLs that will be redirected, so it's fine. I also checked the spaces and we should be good:\r\n- dalle-mini used to install the master branch but [it's no longer the case](https://huggi... | 2022-07-06T13:34:30Z | 2022-07-06T15:36:46Z | 2022-07-06T15:25:08Z | MEMBER | null | 0 | {
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} | This PR renames mentions of "master" by "main" in the code base for several cases:
- set the default dataset script version to "main" if the local installation of `datasets` is a dev installation
- update URLs to this github repository to use "main"
- update the DVC benchmark
- update the github workflows
- update docstrings
- update tests to compare the changes in dataset cards against "main"
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https://api.github.com/repos/huggingface/datasets/issues/5526 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5526/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5526/comments | https://api.github.com/repos/huggingface/datasets/issues/5526/events | https://github.com/huggingface/datasets/pull/5526 | 1,580,488,133 | PR_kwDODunzps5JwVol | 5,526 | Allow loading/saving of FAISS index using fsspec | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks for the quick review! I updated the code with your suggestion",
"Thanks for the quick review @albertvillanova! I updated the code with your suggestions",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n... | 2023-02-10T23:37:14Z | 2023-03-27T15:26:46Z | 2023-03-27T15:18:20Z | CONTRIBUTOR | null | 0 | {
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} | Fixes #5428
Allow loading/saving of FAISS index using fsspec:
1. Simply use BufferedIOWriter/Reader to Read/Write indices on fsspec stream.
2. Needed `mockfs` in the test, so I took it out of the `TestCase`. Let me know if that makes sense.
I can work on the documentation once the code changes are approved.
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https://api.github.com/repos/huggingface/datasets/issues/3224 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3224/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3224/comments | https://api.github.com/repos/huggingface/datasets/issues/3224/events | https://github.com/huggingface/datasets/pull/3224 | 1,046,495,831 | PR_kwDODunzps4uLk2q | 3,224 | User-pickling with dynamic sub-classing | {
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"@lhoestq Feel free to have a look. The implementation is slightly different from what you suggested. I have opted to overwrite `save` instead of meddling with `save_global`. `save_global` is called very late down in dill/pickle so it is hard to control for what is happening there. I might be wrong. Pickling is mor... | 2021-11-06T12:08:24Z | 2022-07-06T15:19:48Z | null | CONTRIBUTOR | null | 1 | {
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} | This is a continuation of the now closed PR in https://github.com/huggingface/datasets/pull/3206. The discussion there has shaped a new approach to do this.
In this PR, behavior of `pklregister` and `Pickler` is extended. Earlier, users were already able to register custom pickle functions. That is useful if they have objects that are not easily picklable with default methods. When one registers a custom function to a type, an object of that type will be pickled with the given function by `Pickler` which looks up the type in its `dispatch` table. The downside of this method, and of `pickle` in general, is that it is limited to direct type-matching and does not allow sub-classes. In many, default, cases that is not an issue. But when you are using external libraries where classes (e.g. parsers, models) are sub-classed this is not ideal.
```python
from datasets.fingerprint import Hasher
from datasets.utils.py_utils import pklregister
class BaseParser:
pass
class EnglishParser(BaseParser):
pass
@pklregister(BaseParser)
def custom_pkl_func(pickler, obj):
print(f"Called the custom pickle function for type {type(obj)}!")
# do something with the obj and ultimately save with the pickler
base = BaseParser()
en = EnglishParser()
# Hasher.hash uses the Pickler behind the scenes
# `custom_pkl_func` called for base
Hasher.hash(base)
# `custom_pkl_func` not called for en :-(
Hasher.hash(en)
```
In the example above we'd want to sub-class `EnglishParser` to be handled in the same way as its super-class `BaseParser`. This PR solves that by allowing for a keyword-argument `allow_subclasses` in `pklregister` (default: `False`).
```python
@pklregister(BaseParser, allow_subclasses=True)
```
When this option is enabled, we not only save the function in `Pickler.dispatch` but also save it in a custom table `Pickler.subclass_dispatch` **which allows us to dynamically add sub-classes of that class to the real dispatch table**. Then, if we want to pickle an object `obj` with `Pickler.dump()` (which ultimately will call `Pickler.save()`) we _first_ check whether any of the object's super-classes exist in `Pickler.sublcass_dispatch` and get the related custom pickle function. If we find one, we add the type of `obj` alongside the function to `Pickler.dispatch`. All of this happens at the start of the call to `Pickler.save()`. _Only then_ dill.Pickler's `save` will be called, which in turn will call `pickle._Pickler.save` which handles everything. Here, the `Pickler.dispatch` table will be used to look up custom pickler functions - and it now also includes the function for `obj`, which was copied from its super-class, which we added at the very start of our custom `Pickler.save()`.
For edge cases and, especially, for testing, a contextmanager class `TempPickleRegistry` is included that resets the pickle registry on exit to its previous state.
```python
with TempPickleRegistry():
@pklregister(MyObjClass)
def pickle_registry_test_false(pickler, obj):
pickler.save(obj.fancy_method())
some_obj = MyObjClass()
dumps(some_obj)
# `MyObjClass` is in Pickler.dispatch
# ... `MyObjClass` is _not_ in Pickler.dispatch anymore
```
closes https://github.com/huggingface/datasets/issues/3178
To Do
====
- [x] Write tests
- [ ] Write documentation/examples? | {
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] | open | false | null | [] | null | [] | 2022-03-09T16:12:25Z | 2022-03-09T16:33:42Z | null | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
Align to DCAT metadata to describe datasets
**Describe the solution you'd like**
Reuse terms and structure from DCAT in the metadata file, ideally generate a json-ld file dcat compliant
**Describe alternatives you've considered**
**Additional context**
DCAT is a W3C standard extended in Europe with DCAT-AP, an example is data.europa.eu publishing datasets metadata in DCAT-AP
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https://api.github.com/repos/huggingface/datasets/issues/3197 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3197/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3197/comments | https://api.github.com/repos/huggingface/datasets/issues/3197/events | https://github.com/huggingface/datasets/pull/3197 | 1,042,541,127 | PR_kwDODunzps4t_cry | 3,197 | Fix optimized encoding for arrays | {
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} | Hi !
#3124 introduced a regression that made the benchmarks CI fail because of a bad array comparison when checking the first encoded element. This PR fixes this by making sure that encoding is applied on all sequence types except lists.
cc @eladsegal fyi (no big deal) | {
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"We already have a ClassLabel type that does this kind of mapping between the label ids (integers) and actual label values (strings).\r\n\r\nI wonder if actually we should use the DictionaryType from Arrow and the Categorical type from pandas for the `datasets` ClassLabel feature type.\r\nCurrently ClassLabel corre... | 2021-02-18T19:46:05Z | 2021-02-23T14:38:50Z | null | CONTRIBUTOR | null | null | null | ```
from datasets import Dataset
import pandas as pd
import pyarrow
df = pd.DataFrame(pd.Series(["a", "b", "c", "a"], dtype="category"))
pyarrow.Table.from_pandas(df)
Dataset.from_pandas(df)
# Throws NotImplementedError
# TODO(thom) this will need access to the dictionary as well (for labels). I.e. to the py_table
```
I'm curious if https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L796 could be built out in a way similar to `Sequence`?
e.g. a `Map` class (or whatever name the maintainers might prefer) that can accept:
```
index_type = generate_from_arrow_type(pa_type.index_type)
value_type = generate_from_arrow_type(pa_type.value_type)
```
and then additional code points to modify:
- FeatureType: https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L694
- A branch to handle Map in get_nested_type: https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L719
- I don't quite understand what `encode_nested_example` does but perhaps a branch there? https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L755
- Similarly, I don't quite understand why `Sequence` is used this way in `generate_from_dict`, but perhaps a branch here? https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L775
I couldn't find other usages of `Sequence` outside of defining specific datasets, so I'm not sure if that's a comprehensive set of touchpoints. | {
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https://api.github.com/repos/huggingface/datasets/issues/6279 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6279/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6279/comments | https://api.github.com/repos/huggingface/datasets/issues/6279/events | https://github.com/huggingface/datasets/issues/6279 | 1,928,028,226 | I_kwDODunzps5y62BC | 6,279 | Batched IterableDataset | {
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"This is exactly what I was looking for. It would also be very useful for me :-)"
] | 2023-10-05T11:12:49Z | 2023-10-05T11:50:28Z | null | NONE | null | null | null | ### Feature request
Hi,
could you add an implementation of a batched `IterableDataset`. It already support an option to do batch iteration via `.iter(batch_size=...)` but this cannot be used in combination with a torch `DataLoader` since it just returns an iterator.
### Motivation
The current implementation loads each element of a batch individually which can be very slow in cases of a big batch_size. I did some experiments [here](https://discuss.huggingface.co/t/slow-dataloader-with-big-batch-size/57224) and using a batched iteration would speed up data loading significantly.
### Your contribution
N/A | {
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https://api.github.com/repos/huggingface/datasets/issues/2286 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2286/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2286/comments | https://api.github.com/repos/huggingface/datasets/issues/2286/events | https://github.com/huggingface/datasets/pull/2286 | 871,032,393 | MDExOlB1bGxSZXF1ZXN0NjI2MTE5MTE2 | 2,286 | Fix metadata validation with config names | {
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} | I noticed in https://github.com/huggingface/datasets/pull/2280 that the metadata validator doesn't parse the tags in the readme properly when then contain the tags per config. | {
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https://api.github.com/repos/huggingface/datasets/issues/1744 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1744/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1744/comments | https://api.github.com/repos/huggingface/datasets/issues/1744/events | https://github.com/huggingface/datasets/pull/1744 | 787,649,811 | MDExOlB1bGxSZXF1ZXN0NTU2MzA0MjU4 | 1,744 | Add missing "brief" entries to reuters | {
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"@lhoestq I ran `make style` but CI code quality still failing and I don't have access to logs",
"It's also likely that due to the previous placement of the field initialization, much of the data about topics etc was simply wrong and carried over from previous entries. Model scores seem to improve significantly w... | 2021-01-17T07:58:49Z | 2021-01-18T11:26:09Z | 2021-01-18T11:26:09Z | CONTRIBUTOR | null | 0 | {
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} | This brings the number of examples for ModApte to match the stated `Training set (9,603 docs)...Test Set (3,299 docs)` | {
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https://api.github.com/repos/huggingface/datasets/issues/1994 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1994/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1994/comments | https://api.github.com/repos/huggingface/datasets/issues/1994/events | https://github.com/huggingface/datasets/issues/1994 | 822,871,238 | MDU6SXNzdWU4MjI4NzEyMzg= | 1,994 | not being able to get wikipedia es language | {
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"@lhoestq I really appreciate if you could help me providiing processed datasets, I do not really have access to enough resources to run the apache-beam and need to run the codes on these datasets. Only en/de/fr currently works, but I need all the languages more or less. thanks ",
"Hi @dorost1234, I think I can ... | 2021-03-05T08:31:48Z | 2021-03-11T20:46:21Z | null | NONE | null | null | null | Hi
I am trying to run a code with wikipedia of config 20200501.es, getting:
Traceback (most recent call last):
File "run_mlm_t5.py", line 608, in <module>
main()
File "run_mlm_t5.py", line 359, in main
datasets = load_dataset(data_args.dataset_name, data_args.dataset_config_name)
File "/dara/libs/anaconda3/envs/success432/lib/python3.7/site-packages/datasets-1.2.1-py3.7.egg/datasets/load.py", line 612, in load_dataset
ignore_verifications=ignore_verifications,
File "/dara/libs/anaconda3/envs/success432/lib/python3.7/site-packages/datasets-1.2.1-py3.7.egg/datasets/builder.py", line 527, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/dara/libs/anaconda3/envs/success432/lib/python3.7/site-packages/datasets-1.2.1-py3.7.egg/datasets/builder.py", line 1050, in _download_and_prepare
"\n\t`{}`".format(usage_example)
datasets.builder.MissingBeamOptions: Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided in `load_dataset` or in the builder arguments. For big datasets it has to run on large-scale data processing tools like Dataflow, Spark, etc. More information about Apache Beam runners at https://beam.apache.org/documentation/runners/capability-matrix/
If you really want to run it locally because you feel like the Dataset is small enough, you can use the local beam runner called `DirectRunner` (you may run out of memory).
Example of usage:
`load_dataset('wikipedia', '20200501.es', beam_runner='DirectRunner')`
thanks @lhoestq for any suggestion/help | {
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https://api.github.com/repos/huggingface/datasets/issues/5042 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5042/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5042/comments | https://api.github.com/repos/huggingface/datasets/issues/5042/events | https://github.com/huggingface/datasets/pull/5042 | 1,390,762,877 | PR_kwDODunzps4_2eqa | 5,042 | Update swiss judgment prediction | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-29T12:10:02Z | 2022-09-30T07:14:00Z | 2022-09-29T14:32:02Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2067 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2067/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2067/comments | https://api.github.com/repos/huggingface/datasets/issues/2067/events | https://github.com/huggingface/datasets/issues/2067 | 833,559,940 | MDU6SXNzdWU4MzM1NTk5NDA= | 2,067 | Multiprocessing windows error | {
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"Hi ! Thanks for reporting.\r\nThis looks like a bug, could you try to provide a minimal code example that reproduces the issue ? This would be very helpful !\r\n\r\nOtherwise I can try to run the wav2vec2 code above on my side but probably not this week..",
"```\r\nfrom datasets import load_dataset\r\n\r\ndatase... | 2021-03-17T09:12:28Z | 2021-08-04T17:59:08Z | 2021-08-04T17:59:08Z | CONTRIBUTOR | null | null | null | As described here https://huggingface.co/blog/fine-tune-xlsr-wav2vec2
When using the num_proc argument on windows the whole Python environment crashes and hanging in loop.
For example at the map_to_array part.
An error occures because the cache file already exists and windows throws and error. After this the log crashes into an loop | {
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https://api.github.com/repos/huggingface/datasets/issues/2615 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2615/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2615/comments | https://api.github.com/repos/huggingface/datasets/issues/2615/events | https://github.com/huggingface/datasets/issues/2615 | 940,794,339 | MDU6SXNzdWU5NDA3OTQzMzk= | 2,615 | Jsonlines export error | {
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"Thanks for reporting @TevenLeScao! I'm having a look...",
"(not sure what just happened on the assignations sorry)",
"For some reason this happens (both `datasets` version are on master) only on Python 3.6 and not Python 3.8.",
"@TevenLeScao we are using `pandas` to serialize the dataset to JSON Lines. So it... | 2021-07-09T14:02:05Z | 2021-07-09T15:29:07Z | 2021-07-09T15:28:33Z | CONTRIBUTOR | null | null | null | ## Describe the bug
When exporting large datasets in jsonlines (c4 in my case) the created file has an error every 9999 lines: the 9999th and 10000th are concatenated, thus breaking the jsonlines format. This sounds like it is related to batching, which is by 10000 by default
## Steps to reproduce the bug
This what I'm running:
in python:
```
from datasets import load_dataset
ptb = load_dataset("ptb_text_only")
ptb["train"].to_json("ptb.jsonl")
```
then out of python:
```
head -10000 ptb.jsonl
```
## Expected results
Properly separated lines
## Actual results
The last line is a concatenation of two lines
## Environment info
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- `datasets` version: 1.9.1.dev0
- Platform: Linux-5.4.0-1046-gcp-x86_64-with-Ubuntu-18.04-bionic
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"Thanks @albertvillanova for your great suggestions! I just pushed a new commit with the necessary fixes. For some reason, the test `test_metric_common` failed for `meteor` metric, which doesn't have any connection to this PR, so I'm trying to rebase and see if it helps.",
"Hi @Hazoom,\r\n\r\nYou were right: the ... | 2021-09-19T13:11:24Z | 2021-09-24T10:39:55Z | 2021-09-24T10:39:54Z | NONE | null | 0 | {
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} | This PR adds the SEDE dataset for the task of realistic Text-to-SQL, following the instructions of how to add a database and a dataset card.
Please see our paper for more details: https://arxiv.org/abs/2106.05006 | {
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L
## Expected L
A clear and concise lmll
Specify the actual results or traceback.
## Environment info
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- Platform:
- Python version:
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"Thanks for reviewing and merging!"
] | 2021-01-05T11:47:27Z | 2021-01-06T10:27:12Z | 2021-01-06T09:31:10Z | CONTRIBUTOR | null | 0 | {
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} | Update README.md of covid-tweets-japanese added by PR https://github.com/huggingface/datasets/pull/1367 and https://github.com/huggingface/datasets/pull/1402.
- Update "Data Splits" to be more precise that no information is provided for now.
- old: [More Information Needed]
- new: No information about data splits is provided for now.
- The automatic generation of links seemed not working properly, so I added a space before and after the URL to make the links work correctly. | {
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"@lhoestq Thank you for the review. I have made all the changes you mentioned. PTAL! "
] | 2020-12-13T05:16:37Z | 2020-12-21T14:39:49Z | 2020-12-21T14:39:49Z | CONTRIBUTOR | null | 0 | {
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} | This PR adds the Igbo Monolingual dataset.
Data: https://github.com/IgnatiusEzeani/IGBONLP/tree/master/ig_monoling
Paper: https://arxiv.org/abs/2004.00648 | {
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https://api.github.com/repos/huggingface/datasets/issues/2043 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2043/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2043/comments | https://api.github.com/repos/huggingface/datasets/issues/2043/events | https://github.com/huggingface/datasets/pull/2043 | 830,279,098 | MDExOlB1bGxSZXF1ZXN0NTkxODE1ODAz | 2,043 | Support pickle protocol for dataset splits defined as ReadInstruction | {
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"@lhoestq But we don't perform conversion to a `NamedSplit` if `_split` is not a string which means it **will** be a `ReadInstruction` after reloading.",
"Yes right ! I read it wrong.\r\nPerfect then"
] | 2021-03-12T16:35:11Z | 2021-03-16T14:25:38Z | 2021-03-16T14:05:05Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6229 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6229/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6229/comments | https://api.github.com/repos/huggingface/datasets/issues/6229/events | https://github.com/huggingface/datasets/issues/6229 | 1,889,050,954 | I_kwDODunzps5wmKFK | 6,229 | Apply inference on all images in the dataset | {
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"From what I see, `MMSegInferencer` supports NumPy arrays, so replace the line `image_path = example['image']` with `image_path = np.array(example['image'])` to fix the issue (`example[\"image\"]` is a `PIL.Image` object). ",
"> From what I see, `MMSegInferencer` supports NumPy arrays, so replace the line `image_... | 2023-09-10T08:36:12Z | 2023-09-20T16:11:53Z | 2023-09-20T16:11:52Z | NONE | null | null | null | ### Describe the bug
```
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
Cell In[14], line 11
9 for idx, example in enumerate(dataset['train']):
10 image_path = example['image']
---> 11 mask_image = process_image(image_path)
12 mask_image.save(f"mask_{idx}.png")
Cell In[14], line 4, in process_image(image_path)
2 def process_image(image_path):
3 print("Processing image:", image_path)
----> 4 result = inferencer(image_path)['predictions']
5 mask = np.where(result == 12, 255, 0).astype('uint8')
6 return Image.fromarray(mask)
File /usr/local/lib/python3.10/dist-packages/mmseg/apis/mmseg_inferencer.py:183, in MMSegInferencer.__call__(self, inputs, return_datasamples, batch_size, show, wait_time, out_dir, img_out_dir, pred_out_dir, **kwargs)
180 pred_out_dir = ''
181 img_out_dir = ''
--> 183 return super().__call__(
184 inputs=inputs,
185 return_datasamples=return_datasamples,
186 batch_size=batch_size,
187 show=show,
188 wait_time=wait_time,
189 img_out_dir=img_out_dir,
190 pred_out_dir=pred_out_dir,
191 **kwargs)
File /usr/local/lib/python3.10/dist-packages/mmengine/infer/infer.py:221, in BaseInferencer.__call__(self, inputs, return_datasamples, batch_size, **kwargs)
218 inputs = self.preprocess(
219 ori_inputs, batch_size=batch_size, **preprocess_kwargs)
220 preds = []
--> 221 for data in (track(inputs, description='Inference')
222 if self.show_progress else inputs):
223 preds.extend(self.forward(data, **forward_kwargs))
224 visualization = self.visualize(
225 ori_inputs, preds,
226 **visualize_kwargs) # type: ignore # noqa: E501
File /usr/local/lib/python3.10/dist-packages/rich/progress.py:168, in track(sequence, description, total, auto_refresh, console, transient, get_time, refresh_per_second, style, complete_style, finished_style, pulse_style, update_period, disable, show_speed)
157 progress = Progress(
158 *columns,
159 auto_refresh=auto_refresh,
(...)
164 disable=disable,
165 )
167 with progress:
--> 168 yield from progress.track(
169 sequence, total=total, description=description, update_period=update_period
170 )
File /usr/local/lib/python3.10/dist-packages/rich/progress.py:1210, in Progress.track(self, sequence, total, task_id, description, update_period)
1208 if self.live.auto_refresh:
1209 with _TrackThread(self, task_id, update_period) as track_thread:
-> 1210 for value in sequence:
1211 yield value
1212 track_thread.completed += 1
File /usr/local/lib/python3.10/dist-packages/mmengine/infer/infer.py:291, in BaseInferencer.preprocess(self, inputs, batch_size, **kwargs)
266 """Process the inputs into a model-feedable format.
267
268 Customize your preprocess by overriding this method. Preprocess should
(...)
287 Any: Data processed by the ``pipeline`` and ``collate_fn``.
288 """
289 chunked_data = self._get_chunk_data(
290 map(self.pipeline, inputs), batch_size)
--> 291 yield from map(self.collate_fn, chunked_data)
File /usr/local/lib/python3.10/dist-packages/mmengine/infer/infer.py:588, in BaseInferencer._get_chunk_data(self, inputs, chunk_size)
586 chunk_data = []
587 for _ in range(chunk_size):
--> 588 processed_data = next(inputs_iter)
589 chunk_data.append(processed_data)
590 yield chunk_data
File /usr/local/lib/python3.10/dist-packages/mmcv/transforms/base.py:12, in BaseTransform.__call__(self, results)
9 def __call__(self,
10 results: Dict) -> Optional[Union[Dict, Tuple[List, List]]]:
---> 12 return self.transform(results)
File /usr/local/lib/python3.10/dist-packages/mmcv/transforms/wrappers.py:88, in Compose.transform(self, results)
79 """Call function to apply transforms sequentially.
80
81 Args:
(...)
85 dict or None: Transformed results.
86 """
87 for t in self.transforms:
---> 88 results = t(results) # type: ignore
89 if results is None:
90 return None
File /usr/local/lib/python3.10/dist-packages/mmcv/transforms/base.py:12, in BaseTransform.__call__(self, results)
9 def __call__(self,
10 results: Dict) -> Optional[Union[Dict, Tuple[List, List]]]:
---> 12 return self.transform(results)
File /usr/local/lib/python3.10/dist-packages/mmseg/datasets/transforms/loading.py:496, in InferencerLoader.transform(self, single_input)
494 inputs = single_input
495 else:
--> 496 raise NotImplementedError
498 if 'img' in inputs:
499 return self.from_ndarray(inputs)
NotImplementedError:
````
### Steps to reproduce the bug
```
from datasets import load_dataset
dataset = load_dataset('Andyrasika/cat_kingdom')
dataset
from mmseg.apis import MMSegInferencer
checkpoint_name = 'segformer_mit-b5_8xb2-160k_ade20k-640x640'
inferencer = MMSegInferencer(model=checkpoint_name)
# Define a function to apply the code to each image in the dataset
def process_image(image_path):
print("Processing image:", image_path)
result = inferencer(image_path)['predictions']
mask = np.where(result == 12, 255, 0).astype('uint8')
return Image.fromarray(mask)
# Process and save masks for each image in the dataset
for idx, example in enumerate(dataset['train']):
image_path = example['image']
mask_image = process_image(image_path)
mask_image.save(f"mask_{idx}.png")
```
### Expected behavior
create a separate column with masks in the dataset and further shows as a separate column in hub
### Environment info
jupyter notebook RTX 3090 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Did you run the `datasets-cli` command before merging to make sure you generate all the examples ?"
] | 2022-04-20T14:04:36Z | 2022-05-11T13:39:06Z | 2022-04-20T15:52:49Z | MEMBER | null | 0 | {
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} | Support streaming cnn_dailymail dataset.
Fix #3969.
CC: @severo | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-09-06T23:17:24Z | 2023-10-03T14:18:41Z | 2023-09-07T15:39:09Z | CONTRIBUTOR | null | 0 | {
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} | There is a typo in the section of the documentation dedicated to creating an audio dataset. The Dataset is incorrectly suffixed with a `Config`
https://huggingface.co/datasets/indonesian-nlp/librivox-indonesia/blob/main/librivox-indonesia.py#L59 | {
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"Additionally, I've deleted the points that are not very relevant for this repo (I guess the deleted points originate from the transformers repo). With this change, running `datasets-cli` is identical to copy-pasting the code from `bug_report.md`, but is more elegant because it doesn't require launching the REPL an... | 2021-05-04T18:55:11Z | 2021-05-10T16:36:51Z | 2021-05-10T16:36:50Z | CONTRIBUTOR | null | 0 | {
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} | This PR:
* replaces the code from the `bug_report.md` that was used to get relevant system info with a dedicated command (a more elegant approach than copy-pasting the code IMO)
* removes the `download` command (copied from the transformers repo?)
* adds missing help messages to the cli commands
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https://api.github.com/repos/huggingface/datasets/issues/3609 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3609/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3609/comments | https://api.github.com/repos/huggingface/datasets/issues/3609/events | https://github.com/huggingface/datasets/pull/3609 | 1,109,579,112 | PR_kwDODunzps4xVrsG | 3,609 | Fixes to pubmed dataset download function | {
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"Hi ! I think we can simply add a new configuration for the 2022 data instead of replacing them.\r\nYou can add the new configuration here:\r\n```python\r\n BUILDER_CONFIGS = [\r\n datasets.BuilderConfig(name=\"2021\", description=\"The 2021 annual record\", version=datasets.Version(\"1.0.0\")),\r\n ... | 2022-01-20T17:31:35Z | 2022-03-03T16:18:52Z | 2022-03-03T14:23:35Z | NONE | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3417 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3417/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3417/comments | https://api.github.com/repos/huggingface/datasets/issues/3417/events | https://github.com/huggingface/datasets/pull/3417 | 1,076,943,343 | PR_kwDODunzps4vrwd7 | 3,417 | Fix type of bridge field in QED | {
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} | Use `Value("string")` instead of `Value("bool")` for the feature type of the `"bridge"` field in the QED dataset. If the value is `False`, set to `None`.
The following paragraph in the QED repo explains the purpose of this field:
>Each annotation in referential_equalities is a pair of spans, the question_reference and the sentence_reference, corresponding to an entity mention in the question and the selected_sentence respectively. As described in the paper, sentence_references can be "bridged in", in which case they do not correspond with any actual span in the selected_sentence. Hence, sentence_reference spans contain an additional field, bridge, which is a prepositional phrase when a reference is bridged, and is False otherwise. Prepositional phrases serve to link bridged references to an anchoring phrase in the selected_sentence. In the case a sentence_reference is bridged, the start and end, as well as the span string, map to such an anchoring phrase in the selected_sentence.
Fix #3346
cc @VictorSanh | {
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"Hi,\r\n\r\nif you inspect the raw data, you can find there are 946 occurrences of `-DOCSTART- -X- -X- O` in the train split and `14041 + 946 = 14987`, which is exactly the number of sentences the authors report. `-DOCSTART-` is a special line that acts as a boundary between two different documents and is filtered ... | 2021-03-04T04:41:34Z | 2022-10-05T13:13:26Z | 2022-10-05T13:13:26Z | NONE | null | null | null | Thanks for the dataset sharing! But when I use conll-2003, I meet some questions.
The statistics of conll-2003 in this repo is :
\#train 14041 \#dev 3250 \#test 3453
While the official statistics is:
\#train 14987 \#dev 3466 \#test 3684
Wish for your reply~ | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-14T17:15:17Z | 2022-06-14T17:35:13Z | 2022-06-14T17:25:45Z | MEMBER | null | 0 | {
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} | Use the commit sha in the data files URLs of the imagenet-1k download script, in case we want to restructure the data files in the future. For example we may split it into many more shards for better paralellism.
cc @mariosasko | {
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https://api.github.com/repos/huggingface/datasets/issues/3968 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3968/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3968/comments | https://api.github.com/repos/huggingface/datasets/issues/3968/events | https://github.com/huggingface/datasets/issues/3968 | 1,174,193,962 | I_kwDODunzps5F_Mcq | 3,968 | Cannot preview 'indonesian-nlp/eli5_id' dataset | {
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"Hi @cahya-wirawan, thanks for reporting.\r\n\r\nYour dataset is working OK in streaming mode:\r\n```python\r\nIn [1]: from datasets import load_dataset\r\n ...: ds = load_dataset(\"indonesian-nlp/eli5_id\", split=\"train\", streaming=True)\r\n ...: item = next(iter(ds))\r\n ...: item\r\nUsing custom data con... | 2022-03-19T06:54:09Z | 2022-03-24T16:34:24Z | 2022-03-24T16:34:24Z | CONTRIBUTOR | null | null | null | ## Dataset viewer issue for '*indonesian-nlp/eli5_id*'
**Link:** https://huggingface.co/datasets/indonesian-nlp/eli5_id
I can not see the dataset preview.
```
Server Error
Status code: 400
Exception: Status400Error
Message: Not found. Maybe the cache is missing, or maybe the dataset does not exist.
```
Am I the one who added this dataset ? Yes
| {
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https://api.github.com/repos/huggingface/datasets/issues/1976 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1976/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1976/comments | https://api.github.com/repos/huggingface/datasets/issues/1976/events | https://github.com/huggingface/datasets/pull/1976 | 820,228,538 | MDExOlB1bGxSZXF1ZXN0NTgzMjA3NDI4 | 1,976 | Add datasets full offline mode with HF_DATASETS_OFFLINE | {
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} | Add the HF_DATASETS_OFFLINE environment variable for users who want to use `datasets` offline without having to wait for the network timeouts/retries to happen. This was requested in https://github.com/huggingface/datasets/issues/1939
cc @stas00 | {
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https://api.github.com/repos/huggingface/datasets/issues/2376 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2376/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2376/comments | https://api.github.com/repos/huggingface/datasets/issues/2376/events | https://github.com/huggingface/datasets/pull/2376 | 894,852,264 | MDExOlB1bGxSZXF1ZXN0NjQ3MTU1NDE4 | 2,376 | Improve task api code quality | {
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"Looks good thanks, what do you think @lewtun ?",
"thanks for including the lazy `ClassLabel` class @mariosasko ! from my side this LGTM!"
] | 2021-05-18T23:13:40Z | 2021-06-02T20:39:57Z | 2021-05-25T15:30:54Z | CONTRIBUTOR | null | 0 | {
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} | Improves the code quality of the `TaskTemplate` dataclasses.
Changes:
* replaces `return NotImplemented` with raise `NotImplementedError`
* replaces `sorted` with `len` in the uniqueness check
* defines `label2id` and `id2label` in the `TextClassification` template as properties
* replaces the `object.__setattr__(self, attr, value)` syntax with (IMO nicer) `self.__dict__[attr] = value` | {
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} | Currently some files can't be read with the default parameters of the JSON lines reader.
For example this one:
https://huggingface.co/datasets/thomwolf/codeparrot/resolve/main/file-000000000006.json.gz
raises a pyarrow error:
```python
ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)
```
The block size that is used is the default one by pyarrow (related to this [jira issue](https://issues.apache.org/jira/browse/ARROW-9612)).
To fix this issue I changed the block_size to increase automatically if there is a straddling issue when parsing a batch of json lines.
By default the value is `chunksize // 32` in order to leverage multithreading, and it doubles every time a straddling issue occurs. The block_size is then reset for each file.
cc @thomwolf @albertvillanova | {
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https://api.github.com/repos/huggingface/datasets/issues/2579 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2579/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2579/comments | https://api.github.com/repos/huggingface/datasets/issues/2579/events | https://github.com/huggingface/datasets/pull/2579 | 935,486,894 | MDExOlB1bGxSZXF1ZXN0NjgyMzkyNjYx | 2,579 | Fix BibTeX entry | {
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} | Add missing contributor to BibTeX entry.
cc: @abhishekkrthakur @thomwolf | {
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https://api.github.com/repos/huggingface/datasets/issues/4839 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4839/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4839/comments | https://api.github.com/repos/huggingface/datasets/issues/4839/events | https://github.com/huggingface/datasets/issues/4839 | 1,337,206,377 | I_kwDODunzps5PtCZp | 4,839 | ImageFolder dataset builder does not read the validation data set if it is named as "val" | {
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"#take"
] | 2022-08-12T13:26:00Z | 2022-08-30T10:14:55Z | 2022-08-30T10:14:55Z | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
Currently, the `'imagefolder'` data set builder in [`load_dataset()`](https://github.com/huggingface/datasets/blob/2.4.0/src/datasets/load.py#L1541] ) only [supports](https://github.com/huggingface/datasets/blob/6c609a322da994de149b2c938f19439bca99408e/src/datasets/data_files.py#L31) the following names as the validation data set directory name: `["validation", "valid", "dev"]`. When the validation directory is named as `'val'`, the Data set will not have a validation split. I expected this to be a trivial task but ended up spending a lot of time before knowing that only the above names are supported.
Here's a minimal example of `val` not being recognized:
```python
import os
import numpy as np
import cv2
from datasets import load_dataset
# creating a dummy data set with the following structure:
# ROOT
# | -- train
# | ---- class_1
# | ---- class_2
# | -- val
# | ---- class_1
# | ---- class_2
ROOT = "data"
for which in ["train", "val"]:
for class_name in ["class_1", "class_2"]:
dir_name = os.path.join(ROOT, which, class_name)
if not os.path.exists(dir_name):
os.makedirs(dir_name)
for i in range(10):
cv2.imwrite(
os.path.join(dir_name, f"{i}.png"),
np.random.random((224, 224))
)
# trying to create a data set
dataset = load_dataset(
"imagefolder",
data_dir=ROOT
)
>> dataset
DatasetDict({
train: Dataset({
features: ['image', 'label'],
num_rows: 20
})
})
# ^ note how the dataset only has a 'train' subset
```
**Describe the solution you'd like**
The suggestion is to include `"val"` to [that list ](https://github.com/huggingface/datasets/blob/6c609a322da994de149b2c938f19439bca99408e/src/datasets/data_files.py#L31) as that's a commonly used phrase to name the validation directory.
Also, In the documentation, explicitly mention that only such directory names are supported as train/val/test directories to avoid confusion.
**Describe alternatives you've considered**
In the documentation, explicitly mention that only such directory names are supported as train/val/test directories without adding `val` to the above list.
**Additional context**
A question asked in the forum: [
Loading an imagenet-style image dataset with train/val directories](https://discuss.huggingface.co/t/loading-an-imagenet-style-image-dataset-with-train-val-directories/21554) | {
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https://api.github.com/repos/huggingface/datasets/issues/5261 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5261/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5261/comments | https://api.github.com/repos/huggingface/datasets/issues/5261/events | https://github.com/huggingface/datasets/issues/5261 | 1,454,647,861 | I_kwDODunzps5WtCo1 | 5,261 | Add PubTables-1M | {
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"cc @albertvillanova the author would like to add this dataset to the hub: https://github.com/microsoft/table-transformer/issues/68#issuecomment-1319114621. Could you help him out?"
] | 2022-11-18T07:56:36Z | 2022-11-18T08:02:18Z | null | CONTRIBUTOR | null | null | null | ### Name
PubTables-1M
### Paper
https://openaccess.thecvf.com/content/CVPR2022/html/Smock_PubTables-1M_Towards_Comprehensive_Table_Extraction_From_Unstructured_Documents_CVPR_2022_paper.html
### Data
https://github.com/microsoft/table-transformer
### Motivation
Table Transformer is now available in 🤗 Transformer, and it was trained on PubTables-1M. It's a large dataset for table extraction and structure recognition in unstructured documents. | {
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https://api.github.com/repos/huggingface/datasets/issues/2352 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2352/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2352/comments | https://api.github.com/repos/huggingface/datasets/issues/2352/events | https://github.com/huggingface/datasets/pull/2352 | 889,810,100 | MDExOlB1bGxSZXF1ZXN0NjQyOTI4NTgz | 2,352 | Set to_json default to JSON lines | {
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"This is perfect, @albertvillanova - thank you! Tested it to work.\r\n\r\nMight it be a good idea to document the args to `to_json`?\r\n\r\nand also even a very basic progress bar? took 10min for 8M large records for `openwebtext` so perhaps some indication of it's being alive every min or so?",
"@lhoestq I added... | 2021-05-12T08:19:25Z | 2021-05-21T09:01:14Z | 2021-05-21T09:01:13Z | MEMBER | null | 0 | {
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} | With this PR, the method `Dataset.to_json`:
- is added to the docs
- defaults to JSON lines | {
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https://api.github.com/repos/huggingface/datasets/issues/5586 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5586/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5586/comments | https://api.github.com/repos/huggingface/datasets/issues/5586/events | https://github.com/huggingface/datasets/issues/5586 | 1,602,961,544 | I_kwDODunzps5fi0CI | 5,586 | .sort() is broken when used after .filter(), only in 2.10.0 | {
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"Thanks for reporting and thanks @mariosasko for fixing ! We just did a patch release `2.10.1` with the fix"
] | 2023-02-28T12:18:09Z | 2023-02-28T18:17:26Z | 2023-02-28T17:21:59Z | NONE | null | null | null | ### Describe the bug
Hi, thank you for your support!
It seems like the addition of multiple key sort (#5502) in 2.10.0 broke the `.sort()` method.
After filtering a dataset with `.filter()`, the `.sort()` seems to refer to the query_table index of the previous unfiltered dataset, resulting in an IndexError.
This only happens with the 2.10.0 release.
### Steps to reproduce the bug
```Python
from datasets import load_dataset
# dataset with length of 1104
ds = load_dataset('glue', 'ax')['test']
ds = ds.filter(lambda x: x['idx'] > 1100)
ds.sort('premise')
print('Done')
```
File "/home/dongkeun/datasets_test/test.py", line 5, in <module>
ds.sort('premise')
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 528, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/fingerprint.py", line 511, in wrapper
out = func(dataset, *args, **kwargs)
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3959, in sort
sort_table = query_table(
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 588, in query_table
_check_valid_index_key(key, size)
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 537, in _check_valid_index_key
_check_valid_index_key(max(key), size=size)
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 531, in _check_valid_index_key
raise IndexError(f"Invalid key: {key} is out of bounds for size {size}")
IndexError: Invalid key: 1103 is out of bounds for size 3
### Expected behavior
It should sort the dataset and print "Done". Which it does on 2.9.0.
### Environment info
- `datasets` version: 2.10.0
- Platform: Linux-5.15.0-41-generic-x86_64-with-glibc2.31
- Python version: 3.9.16
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/1508 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1508/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1508/comments | https://api.github.com/repos/huggingface/datasets/issues/1508/events | https://github.com/huggingface/datasets/pull/1508 | 763,908,724 | MDExOlB1bGxSZXF1ZXN0NTM4MjEyODUy | 1,508 | Fix namedsplit docs | {
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"Hii please follow me",
"Thanks @mariosasko!"
] | 2020-12-12T14:43:38Z | 2021-03-11T02:18:39Z | 2020-12-15T12:57:48Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3583 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3583/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3583/comments | https://api.github.com/repos/huggingface/datasets/issues/3583/events | https://github.com/huggingface/datasets/issues/3583 | 1,105,195,144 | I_kwDODunzps5B3_CI | 3,583 | Add The Medical Segmentation Decathlon Dataset | {
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"Hello! I have recently been involved with a medical image segmentation project myself and was going through the `The Medical Segmentation Decathlon Dataset` as well. \r\nI haven't yet had experience adding datasets to this repository yet but would love to get started. Should I take this issue?\r\nIf yes, I've got ... | 2022-01-16T21:42:25Z | 2022-03-18T10:44:42Z | null | NONE | null | null | null | ## Adding a Dataset
- **Name:** *The Medical Segmentation Decathlon Dataset*
- **Description:** The underlying data set was designed to explore the axis of difficulties typically encountered when dealing with medical images, such as small data sets, unbalanced labels, multi-site data, and small objects.
- **Paper:** [link to the dataset paper if available](https://arxiv.org/abs/2106.05735)
- **Data:** http://medicaldecathlon.com/
- **Motivation:** Hugging Face seeks to democratize ML for society. One of the growing niches within ML is the ML + Medicine community. Key data sets will help increase the supply of HF resources for starting an initial community.
(cc @osanseviero @abidlabs )
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/2010 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2010/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2010/comments | https://api.github.com/repos/huggingface/datasets/issues/2010/events | https://github.com/huggingface/datasets/issues/2010 | 825,567,635 | MDU6SXNzdWU4MjU1Njc2MzU= | 2,010 | Local testing fails | {
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"I'm not able to reproduce on my side.\r\nCan you provide the full stacktrace please ?\r\nWhat version of `python` and `dill` do you have ? Which OS are you using ?",
"```\r\nco_filename = '<ipython-input-2-e0383a102aae>', returned_obj = [0]\r\n ... | 2021-03-09T09:01:38Z | 2021-03-09T14:06:03Z | 2021-03-09T14:06:03Z | CONTRIBUTOR | null | null | null | I'm following the CI setup as described in
https://github.com/huggingface/datasets/blob/8eee4fa9e133fe873a7993ba746d32ca2b687551/.circleci/config.yml#L16-L19
in a new conda environment, at commit https://github.com/huggingface/datasets/commit/4de6dbf84e93dad97e1000120d6628c88954e5d4
and getting
```
FAILED tests/test_caching.py::RecurseDumpTest::test_dump_ipython_function - TypeError: an integer is required (got type bytes)
1 failed, 2321 passed, 5109 skipped, 10 warnings in 124.32s (0:02:04)
```
Seems like a discrepancy with CI, perhaps a lib version that's not controlled?
Tried with `pyarrow=={1.0.0,0.17.1,2.0.0}` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-08T12:03:42Z | 2022-06-08T12:36:24Z | 2022-06-08T12:27:13Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5648 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5648/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5648/comments | https://api.github.com/repos/huggingface/datasets/issues/5648/events | https://github.com/huggingface/datasets/issues/5648 | 1,629,253,719 | I_kwDODunzps5hHHBX | 5,648 | flatten_indices doesn't work with pandas format | {
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"Thanks for reporting! This can be fixed by setting the format to `arrow` in `flatten_indices` and restoring the original format after the flattening. I'm working on a PR that reduces the number of the `flatten_indices` calls in our codebase and makes `flatten_indices` a no-op when a dataset does not have an indice... | 2023-03-17T12:44:25Z | 2023-03-21T13:12:03Z | null | NONE | null | null | null | ### Describe the bug
Hi,
I noticed that `flatten_indices` throws an error when the batch format is `pandas`. This is probably due to the fact that flatten_indices uses map internally which doesn't accept dataframes as the transformation function output
### Steps to reproduce the bug
tabular_data = pd.DataFrame(np.random.randn(10,10))
tabular_data = datasets.arrow_dataset.Dataset.from_pandas(tabular_data)
tabular_data.with_format("pandas").select([0,1,2,3]).flatten_indices()
### Expected behavior
No error thrown
### Environment info
- `datasets` version: 2.10.1
- Python version: 3.9.5
- PyArrow version: 11.0.0
- Pandas version: 1.4.1 | {
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In this I made the ETag requests parallel using multithreading. There is also a tqdm progress bar that shows up if there are more than 16 data files. | {
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https://api.github.com/repos/huggingface/datasets/issues/3822 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3822/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3822/comments | https://api.github.com/repos/huggingface/datasets/issues/3822/events | https://github.com/huggingface/datasets/issues/3822 | 1,159,395,728 | I_kwDODunzps5FGvmQ | 3,822 | Add Biwi Kinect Head Pose Database | {
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"Official dataset location : https://icu.ee.ethz.ch/research/datsets.html\r\nIn the \"Biwi Kinect Head Pose Database\" section, I do not find any information regarding \"Downloading the dataset.\" . Do we mail the authors regarding this ?\r\n\r\nI found the dataset on Kaggle : [Link](https://www.kaggle.com/kmader/b... | 2022-03-04T08:48:39Z | 2022-06-01T13:00:47Z | 2022-06-01T13:00:47Z | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** Biwi Kinect Head Pose Database
- **Description:** Over 15K images of 20 people recorded with a Kinect while turning their heads around freely. For each frame, depth and rgb images are provided, together with ground in the form of the 3D location of the head and its rotation angles.
- **Data:** [*link to the Github repository or current dataset location*](https://icu.ee.ethz.ch/research/datsets.html)
- **Motivation:** Useful pose estimation 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/3587 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3587/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3587/comments | https://api.github.com/repos/huggingface/datasets/issues/3587/events | https://github.com/huggingface/datasets/issues/3587 | 1,106,719,182 | I_kwDODunzps5B9zHO | 3,587 | No module named 'fsspec.archive' | {
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] | closed | false | null | [] | null | [] | 2022-01-18T10:17:01Z | 2022-08-11T09:57:54Z | 2022-01-18T10:33:10Z | NONE | null | null | null | ## Describe the bug
Cannot import datasets after installation.
## Steps to reproduce the bug
```shell
$ python
Python 3.9.7 (default, Sep 16 2021, 13:09:58)
[GCC 7.5.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import datasets
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/shuchen/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/__init__.py", line 34, in <module>
from .arrow_dataset import Dataset, concatenate_datasets
File "/home/shuchen/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 61, in <module>
from .arrow_writer import ArrowWriter, OptimizedTypedSequence
File "/home/shuchen/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/arrow_writer.py", line 28, in <module>
from .features import (
File "/home/shuchen/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/features/__init__.py", line 2, in <module>
from .audio import Audio
File "/home/shuchen/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/features/audio.py", line 7, in <module>
from ..utils.streaming_download_manager import xopen
File "/home/shuchen/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/utils/streaming_download_manager.py", line 18, in <module>
from ..filesystems import COMPRESSION_FILESYSTEMS
File "/home/shuchen/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/filesystems/__init__.py", line 6, in <module>
from . import compression
File "/home/shuchen/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/filesystems/compression.py", line 5, in <module>
from fsspec.archive import AbstractArchiveFileSystem
ModuleNotFoundError: No module named 'fsspec.archive'
```
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https://api.github.com/repos/huggingface/datasets/issues/4830 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4830/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4830/comments | https://api.github.com/repos/huggingface/datasets/issues/4830/events | https://github.com/huggingface/datasets/pull/4830 | 1,336,177,937 | PR_kwDODunzps49Cdro | 4,830 | Fix task tags in dataset cards | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The non-passing tests are caused by other missing information in the dataset cards."
] | 2022-08-11T16:06:06Z | 2022-08-11T16:37:27Z | 2022-08-11T16:23:00Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2743 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2743/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2743/comments | https://api.github.com/repos/huggingface/datasets/issues/2743/events | https://github.com/huggingface/datasets/issues/2743 | 958,119,251 | MDU6SXNzdWU5NTgxMTkyNTE= | 2,743 | Dataset JSON is incorrect | {
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"As discussed, the metadata JSON files must be regenerated because the keys were nor properly generated and they will not be read by the builder:\r\n> Indeed there is some problem/bug while reading the datasets_info.json file: there is a mismatch with the config.name keys in the file...\r\nIn the meanwhile, in orde... | 2021-08-02T13:01:26Z | 2021-08-03T10:06:57Z | 2021-08-03T09:25:33Z | CONTRIBUTOR | null | null | null | ## Describe the bug
The JSON file generated for https://github.com/huggingface/datasets/blob/573f3d35081cee239d1b962878206e9abe6cde91/datasets/journalists_questions/journalists_questions.py is https://github.com/huggingface/datasets/blob/573f3d35081cee239d1b962878206e9abe6cde91/datasets/journalists_questions/dataset_infos.json.
The only config should be `plain_text`, but the first key in the JSON is `journalists_questions` (the dataset id) instead.
```json
{
"journalists_questions": {
"description": "The journalists_questions corpus (version 1.0) is a collection of 10K human-written Arabic\ntweets manually labeled for question identification over Arabic tweets posted by journalists.\n",
...
```
## Steps to reproduce the bug
Look at the files.
## Expected results
The first key should be `plain_text`:
```json
{
"plain_text": {
"description": "The journalists_questions corpus (version 1.0) is a collection of 10K human-written Arabic\ntweets manually labeled for question identification over Arabic tweets posted by journalists.\n",
...
```
## Actual results
```json
{
"journalists_questions": {
"description": "The journalists_questions corpus (version 1.0) is a collection of 10K human-written Arabic\ntweets manually labeled for question identification over Arabic tweets posted by journalists.\n",
...
```
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https://api.github.com/repos/huggingface/datasets/issues/4443 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4443/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4443/comments | https://api.github.com/repos/huggingface/datasets/issues/4443/events | https://github.com/huggingface/datasets/issues/4443 | 1,259,606,334 | I_kwDODunzps5LFBE- | 4,443 | Dataset Viewer issue for openclimatefix/nimrod-uk-1km | {
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"If I understand correctly, this is due to the key `split` missing in the line https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km/blob/main/nimrod-uk-1km.py#L41 of the script.\r\nMaybe @albertvillanova could confirm.",
"I'm having a look.",
"Indeed there are several issues in this dataset loading scri... | 2022-06-03T08:17:16Z | 2023-09-25T12:15:08Z | null | NONE | null | null | null | ### Link
_No response_
### Description
_No response_
### Owner
_No response_ | {
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https://api.github.com/repos/huggingface/datasets/issues/6046 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6046/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6046/comments | https://api.github.com/repos/huggingface/datasets/issues/6046/events | https://github.com/huggingface/datasets/issues/6046 | 1,808,154,414 | I_kwDODunzps5rxj8u | 6,046 | Support proxy and user-agent in fsspec calls | {
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"hii @lhoestq can you assign this issue to me?\r\n",
"You can reply \"#self-assign\" to this issue to automatically get assigned to it :)\r\nLet me know if you have any questions or if I can help",
"#2289 ",
"Actually i am quite new to figure it out how everything goes and done \r\n\r\n> You can reply \"#self... | 2023-07-17T16:39:26Z | 2023-10-09T13:49:14Z | null | MEMBER | null | null | null | Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage_options`.
Though ideally the `HfFileSystem` could support passing at least the proxies | {
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https://api.github.com/repos/huggingface/datasets/issues/5230 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5230/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5230/comments | https://api.github.com/repos/huggingface/datasets/issues/5230/events | https://github.com/huggingface/datasets/issues/5230 | 1,445,507,580 | I_kwDODunzps5WKLH8 | 5,230 | dataclasses error when importing the library in python 3.11 | {
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"I opened [this issue](https://github.com/python/cpython/issues/99401).\r\nPython's maintainers say that the issue is caused by [this change](https://docs.python.org/3.11/whatsnew/3.11.html#dataclasses).\r\nI believe adding a `__hash__` method to `datasets.utils.version.Version` should solve (at least partially) th... | 2022-11-11T13:53:49Z | 2023-05-25T04:37:05Z | 2022-11-14T15:27:37Z | NONE | null | null | null | ### Describe the bug
When I import datasets using python 3.11 the dataclasses standard library raises the following error:
`ValueError: mutable default <class 'datasets.utils.version.Version'> for field version is not allowed: use default_factory`
When I tried to import the library using the following jupyter notebook:
```
%%bash
# create python 3.11 conda env
conda create --yes --quiet -n myenv -c conda-forge python=3.11
# activate is
source activate myenv
# install pyarrow
/opt/conda/envs/myenv/bin/python -m pip install --quiet --extra-index-url https://pypi.fury.io/arrow-nightlies/ \
--prefer-binary --pre pyarrow
# install datasets
/opt/conda/envs/myenv/bin/python -m pip install --quiet datasets
```
```
# create a python file that only imports datasets
with open("import_datasets.py", 'w') as f:
f.write("import datasets")
# run it with the env
!/opt/conda/envs/myenv/bin/python import_datasets.py
```
I get the following error:
```
Traceback (most recent call last):
File "/kaggle/working/import_datasets.py", line 1, in <module>
import datasets
File "/opt/conda/envs/myenv/lib/python3.11/site-packages/datasets/__init__.py", line 45, in <module>
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
File "/opt/conda/envs/myenv/lib/python3.11/site-packages/datasets/builder.py", line 91, in <module>
@dataclass
^^^^^^^^^
File "/opt/conda/envs/myenv/lib/python3.11/dataclasses.py", line 1221, in dataclass
return wrap(cls)
^^^^^^^^^
File "/opt/conda/envs/myenv/lib/python3.11/dataclasses.py", line 1211, in wrap
return _process_class(cls, init, repr, eq, order, unsafe_hash,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/conda/envs/myenv/lib/python3.11/dataclasses.py", line 959, in _process_class
cls_fields.append(_get_field(cls, name, type, kw_only))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/conda/envs/myenv/lib/python3.11/dataclasses.py", line 816, in _get_field
raise ValueError(f'mutable default {type(f.default)} for field '
ValueError: mutable default <class 'datasets.utils.version.Version'> for field version is not allowed: use default_factory
```
This is probably due to one of the following changes in the [dataclasses standard library](https://docs.python.org/3/library/dataclasses.html) in version 3.11:
1. Changed in version 3.11: Instead of looking for and disallowing objects of type list, dict, or set, unhashable objects are now not allowed as default values. Unhashability is used to approximate mutability.
2. fields may optionally specify a default value, using normal Python syntax:
```
@dataclass
class C:
a: int # 'a' has no default value
b: int = 0 # assign a default value for 'b'
In this example, both a and b will be included in the added __init__() method, which will be defined as:
def __init__(self, a: int, b: int = 0):
```
3. Changed in version 3.11: If a field name is already included in the __slots__ of a base class, it will not be included in the generated __slots__ to prevent [overriding them](https://docs.python.org/3/reference/datamodel.html#datamodel-note-slots). Therefore, do not use __slots__ to retrieve the field names of a dataclass. Use [fields()](https://docs.python.org/3/library/dataclasses.html#dataclasses.fields) instead. To be able to determine inherited slots, base class __slots__ may be any iterable, but not an iterator.
4. weakref_slot: If true (the default is False), add a slot named “__weakref__”, which is required to make an instance weakref-able. It is an error to specify weakref_slot=True without also specifying slots=True.
[TypeError](https://docs.python.org/3/library/exceptions.html#TypeError) will be raised if a field without a default value follows a field with a default value. This is true whether this occurs in a single class, or as a result of class inheritance.
### Steps to reproduce the bug
Steps to reproduce the behavior:
1. go to [the notebook in kaggle](https://www.kaggle.com/yonikremer/repreducing-issue)
2. rub both of the cells
### Expected behavior
I'm expecting no issues.
This error should not occur.
### Environment info
kaggle kernels, with default settings:
pin to original environment, no accelerator. | {
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https://api.github.com/repos/huggingface/datasets/issues/2838 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2838/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2838/comments | https://api.github.com/repos/huggingface/datasets/issues/2838/events | https://github.com/huggingface/datasets/pull/2838 | 980,067,186 | MDExOlB1bGxSZXF1ZXN0NzIwMzcxMDk5 | 2,838 | Add error_bad_chunk to the JSON loader | {
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"Somebody reported the following error message which I think this is related to the goal of this PR:\r\n```Python\r\n03/24/2022 02:19:45 - INFO - __main__ - Step 5637: {'lr': 0.00018773333333333333, 'samples': 360768, 'batch_offset': 5637, 'completed_steps': 704, 'loss/train': 4.473083972930908, 'tokens/s': 6692.61... | 2021-08-26T10:07:32Z | 2023-09-25T09:06:42Z | null | MEMBER | null | 1 | {
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} | Add the `error_bad_chunk` parameter to the JSON loader.
Setting `error_bad_chunk=False` allows to skip an unparsable chunk of JSON data without raising an error.
Additional note:
In case of an unparsable JSON chunk, the JSON loader no longer tries to load the full JSON (which could take a lot of time in streaming mode) to get the JSON fields that the user may have forgotten to pass. Ex : for squad-like data, the user has to pass `field="data"` to tell the loader to get the list of examples from this field.
TODO: update docs
cc @lvwerra | {
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https://api.github.com/repos/huggingface/datasets/issues/3846 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3846/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3846/comments | https://api.github.com/repos/huggingface/datasets/issues/3846/events | https://github.com/huggingface/datasets/pull/3846 | 1,161,810,226 | PR_kwDODunzps40D-uh | 3,846 | Update faiss device docstring | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3846). All of your documentation changes will be reflected on that endpoint."
] | 2022-03-07T19:06:59Z | 2022-03-07T19:21:23Z | 2022-03-07T19:21:22Z | MEMBER | null | 0 | {
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} | Following https://github.com/huggingface/datasets/pull/3721 I updated the docstring of the `device` argument of the FAISS related methods of `Dataset` | {
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https://api.github.com/repos/huggingface/datasets/issues/5496 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5496/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5496/comments | https://api.github.com/repos/huggingface/datasets/issues/5496/events | https://github.com/huggingface/datasets/issues/5496 | 1,567,301,765 | I_kwDODunzps5dayCF | 5,496 | Add a `reduce` method | {
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"Hi! Sure, feel free to open a PR, so we can see the API you have in mind.",
"I would like to give it a go! #self-assign",
"Closing as `Dataset.map` can be used instead (see https://github.com/huggingface/datasets/pull/5533#issuecomment-1440571658 and https://github.com/huggingface/datasets/pull/5533#issuecomme... | 2023-02-02T04:30:22Z | 2023-07-21T14:24:32Z | 2023-07-21T14:24:32Z | NONE | null | null | null | ### Feature request
Right now the `Dataset` class implements `map()` and `filter()`, but leaves out the third functional idiom popular among Python users: `reduce`.
### Motivation
A `reduce` method is often useful when calculating dataset statistics, for example, the occurrence of a particular n-gram or the average line length of a code dataset.
### Your contribution
I haven't contributed to `datasets` before, but I don't expect this will be too difficult, since the implementation will closely follow that of `map` and `filter`. I could have a crack over the weekend. | {
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https://api.github.com/repos/huggingface/datasets/issues/6045 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6045/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6045/comments | https://api.github.com/repos/huggingface/datasets/issues/6045/events | https://github.com/huggingface/datasets/pull/6045 | 1,808,072,270 | PR_kwDODunzps5Vr-r1 | 6,045 | Check if column names match in Parquet loader only when config `features` are specified | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-07-17T15:50:15Z | 2023-07-24T14:45:56Z | 2023-07-24T14:35:03Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3259 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3259/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3259/comments | https://api.github.com/repos/huggingface/datasets/issues/3259/events | https://github.com/huggingface/datasets/pull/3259 | 1,052,189,775 | PR_kwDODunzps4ud5W3 | 3,259 | Updating details of IRC disentanglement data | {
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"Thank you for the cleanup!"
] | 2021-11-12T17:16:58Z | 2021-11-18T17:19:33Z | 2021-11-18T17:19:33Z | CONTRIBUTOR | null | 0 | {
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} | I was pleasantly surprised to find that someone had already added my dataset to the huggingface library, but some details were missing or incorrect. This PR fixes the documentation. | {
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https://api.github.com/repos/huggingface/datasets/issues/1874 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1874/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1874/comments | https://api.github.com/repos/huggingface/datasets/issues/1874/events | https://github.com/huggingface/datasets/pull/1874 | 807,786,094 | MDExOlB1bGxSZXF1ZXN0NTcyOTYzMjAy | 1,874 | Adding Europarl Bilingual dataset | {
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"is there a way to check errors without subscribing to CircleCI? Because they want access to private repositories when logging.",
"I think you need to be logged in to check the errors unfortunately. Feel free to create an account with bitbucket maybe if you don't want it to access your private github repos",
"I... | 2021-02-13T17:02:04Z | 2021-03-04T10:38:22Z | 2021-03-04T10:38:22Z | CONTRIBUTOR | null | 0 | {
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} | Implementation of Europarl bilingual dataset from described [here](https://opus.nlpl.eu/Europarl.php).
This dataset allows to use every language pair detailed in the original dataset. The loading script manages also the small errors contained in the original dataset (in very rare cases (1 over 10M) there are some keys that references to inexistent sentences).
I chose to follow the the style of a similar dataset available in this repository: `multi_para_crawl`.
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https://api.github.com/repos/huggingface/datasets/issues/1273 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1273/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1273/comments | https://api.github.com/repos/huggingface/datasets/issues/1273/events | https://github.com/huggingface/datasets/pull/1273 | 758,935,768 | MDExOlB1bGxSZXF1ZXN0NTM0MDE4MjQ2 | 1,273 | Created wiki_movies dataset. | {
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"looks like your PR includes changes about many other files than the ones for wiki_movies\r\n\r\nCan you create another branch and another PR please ?",
"I'm happy to. What's the best way to do that (sorry, I'm new to PRs etc.)?",
"Sure !\r\n\r\nFirst please save your new dataset files somewhere.\r\nThen you ca... | 2020-12-07T23:38:54Z | 2020-12-14T13:56:49Z | 2020-12-14T13:56:49Z | CONTRIBUTOR | null | 0 | {
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} | First PR (ever). Hopefully this movies dataset is useful to others! | {
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https://api.github.com/repos/huggingface/datasets/issues/5466 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5466/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5466/comments | https://api.github.com/repos/huggingface/datasets/issues/5466/events | https://github.com/huggingface/datasets/pull/5466 | 1,557,584,845 | PR_kwDODunzps5Ij-z1 | 5,466 | remove pathlib.Path with URIs | {
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"Thanks !\r\n`os.path.join` will use a backslash `\\` on windows which will also fail. You can use this instead in `load_from_disk`:\r\n```python\r\nfrom .filesystems import is_remote_filesystem\r\n\r\nis_local = not is_remote_filesystem(fs)\r\npath_join = os.path.join if is_local else posixpath.join\r\n```",
"Th... | 2023-01-26T03:25:45Z | 2023-01-26T17:08:57Z | 2023-01-26T16:59:11Z | CONTRIBUTOR | null | 0 | {
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} | Pathlib will convert "//" to "/" which causes retry errors when downloading from cloud storage | {
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https://api.github.com/repos/huggingface/datasets/issues/1275 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1275/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1275/comments | https://api.github.com/repos/huggingface/datasets/issues/1275/events | https://github.com/huggingface/datasets/pull/1275 | 758,958,066 | MDExOlB1bGxSZXF1ZXN0NTM0MDM2NjIw | 1,275 | Yoruba GV NER added | {
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"Thank you. Okay, I will add the dataset card."
] | 2020-12-08T00:31:38Z | 2020-12-08T23:25:28Z | 2020-12-08T23:25:28Z | CONTRIBUTOR | null | 0 | {
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} | I just added Yoruba GV NER dataset from this paper https://www.aclweb.org/anthology/2020.lrec-1.335/ | {
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https://api.github.com/repos/huggingface/datasets/issues/1901 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1901/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1901/comments | https://api.github.com/repos/huggingface/datasets/issues/1901/events | https://github.com/huggingface/datasets/pull/1901 | 810,845,605 | MDExOlB1bGxSZXF1ZXN0NTc1NDY5MDUy | 1,901 | Fix OPUS dataset download errors | {
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} | Replace http to https.
https://github.com/huggingface/datasets/issues/854
https://discuss.huggingface.co/t/cannot-download-wmt16/2081
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https://api.github.com/repos/huggingface/datasets/issues/2839 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2839/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2839/comments | https://api.github.com/repos/huggingface/datasets/issues/2839/events | https://github.com/huggingface/datasets/issues/2839 | 980,271,715 | MDU6SXNzdWU5ODAyNzE3MTU= | 2,839 | OpenWebText: NonMatchingSplitsSizesError | {
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"Thanks for reporting, I'm updating the verifications metadata",
"I just regenerated the verifications metadata and noticed that nothing changed: the data file is fine (the checksum didn't change), and the number of examples is still 8013769. Not sure how you managed to get 7982430 examples.\r\n\r\nCan you try to... | 2021-08-26T13:50:26Z | 2021-09-21T14:12:40Z | 2021-09-21T14:09:43Z | CONTRIBUTOR | null | null | null | ## Describe the bug
When downloading `openwebtext`, I'm getting:
```
datasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=39769494896, num_examples=8013769, dataset_name='openwebtext'), 'recorded': SplitInfo(name='train', num_bytes=39611023912, num_examples=7982430, dataset_name='openwebtext')}]
```
I suspect that the file we download from has changed since the size doesn't look like to match with documentation
`Downloading: 0%| | 0.00/12.9G [00:00<?, ?B/s]` This suggest the total size is 12.9GB, whereas the one documented mentions `Size of downloaded dataset files: 12283.35 MB`.
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset("openwebtext", download_mode="force_redownload")
```
## Expected results
Loading is successful
## Actual results
Loading throws above error.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.10.2
- Platform: linux (Redhat version 8.1)
- Python version: 3.8
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/5305 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5305/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5305/comments | https://api.github.com/repos/huggingface/datasets/issues/5305/events | https://github.com/huggingface/datasets/issues/5305 | 1,465,627,826 | I_kwDODunzps5XW7Sy | 5,305 | Dataset joelito/mc4_legal does not work with multiple files | {
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"Thanks for reporting @JoelNiklaus.\r\n\r\nPlease note that since we moved all dataset loading scripts to the Hub, the issues and pull requests relative to specific datasets are directly handled on the Hub, in their Community tab. I'm transferring this issue there: https://huggingface.co/datasets/joelito/mc4_legal/... | 2022-11-28T00:16:16Z | 2022-11-28T07:22:42Z | 2022-11-28T07:22:42Z | CONTRIBUTOR | null | null | null | ### Describe the bug
The dataset https://huggingface.co/datasets/joelito/mc4_legal works for languages like bg with a single data file, but not for languages with multiple files like de. It shows zero rows for the de dataset.
joelniklaus@Joels-MacBook-Pro ~/N/P/C/L/p/m/mc4_legal (main) [1]> python test_mc4_legal.py (debug)
Found cached dataset mc4_legal (/Users/joelniklaus/.cache/huggingface/datasets/mc4_legal/de/0.0.0/fb6952a097180f8c936e2a7605525ff670354a344fc1a2c70107684d3f7cb02f)
Dataset({
features: ['index', 'url', 'timestamp', 'matches', 'text'],
num_rows: 0
})
joelniklaus@Joels-MacBook-Pro ~/N/P/C/L/p/m/mc4_legal (main)> python test_mc4_legal.py (debug)
Downloading and preparing dataset mc4_legal/bg to /Users/joelniklaus/.cache/huggingface/datasets/mc4_legal/bg/0.0.0/fb6952a097180f8c936e2a7605525ff670354a344fc1a2c70107684d3f7cb02f...
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1240.55it/s]
Dataset mc4_legal downloaded and prepared to /Users/joelniklaus/.cache/huggingface/datasets/mc4_legal/bg/0.0.0/fb6952a097180f8c936e2a7605525ff670354a344fc1a2c70107684d3f7cb02f. Subsequent calls will reuse this data.
Dataset({
features: ['index', 'url', 'timestamp', 'matches', 'text'],
num_rows: 204
})
### Steps to reproduce the bug
import datasets
from datasets import load_dataset, get_dataset_config_names
language = "bg"
test = load_dataset("joelito/mc4_legal", language, split='train')
### Expected behavior
It should display the correct number of rows for the de dataset which should be a large number (thousands or more).
### Environment info
Package Version
------------------------ --------------
absl-py 1.3.0
aiohttp 3.8.1
aiosignal 1.2.0
astunparse 1.6.3
async-timeout 4.0.2
attrs 22.1.0
beautifulsoup4 4.11.1
blinker 1.4
blis 0.7.8
Bottleneck 1.3.4
brotlipy 0.7.0
cachetools 5.2.0
catalogue 2.0.7
certifi 2022.5.18.1
cffi 1.15.1
chardet 4.0.0
charset-normalizer 2.1.0
click 8.0.4
conllu 4.5.2
cryptography 38.0.1
cymem 2.0.6
datasets 2.6.1
dill 0.3.5.1
docker-pycreds 0.4.0
fasttext 0.9.2
fasttext-langdetect 1.0.3
filelock 3.0.12
flatbuffers 20210226132247
frozenlist 1.3.0
fsspec 2022.5.0
gast 0.4.0
gcloud 0.18.3
gitdb 4.0.9
GitPython 3.1.27
google-auth 2.9.0
google-auth-oauthlib 0.4.6
google-pasta 0.2.0
googleapis-common-protos 1.57.0
grpcio 1.47.0
h5py 3.7.0
httplib2 0.21.0
huggingface-hub 0.8.1
idna 3.4
importlib-metadata 4.12.0
Jinja2 3.1.2
joblib 1.0.1
keras 2.9.0
Keras-Preprocessing 1.1.2
langcodes 3.3.0
lxml 4.9.1
Markdown 3.3.7
MarkupSafe 2.1.1
mkl-fft 1.3.1
mkl-random 1.2.2
mkl-service 2.4.0
multidict 6.0.2
multiprocess 0.70.13
murmurhash 1.0.7
numexpr 2.8.1
numpy 1.22.3
oauth2client 4.1.3
oauthlib 3.2.1
opt-einsum 3.3.0
packaging 21.3
pandas 1.4.2
pathtools 0.1.2
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pip 21.1.2
preshed 3.0.6
promise 2.3
protobuf 4.21.9
psutil 5.9.1
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pyasn1 0.4.8
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regex 2021.4.4
requests 2.28.1
requests-oauthlib 1.3.1
responses 0.18.0
rsa 4.8
sacremoses 0.0.45
scikit-learn 1.1.1
scipy 1.8.1
sentencepiece 0.1.96
sentry-sdk 1.6.0
setproctitle 1.2.3
setuptools 65.5.0
shortuuid 1.0.9
six 1.16.0
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tensorboard-plugin-wit 1.8.1
tensorflow 2.9.1
tensorflow-estimator 2.9.0
termcolor 2.1.0
thinc 8.0.17
threadpoolctl 3.1.0
tokenizers 0.12.1
torch 1.13.0
tqdm 4.64.0
transformers 4.20.1
typer 0.4.1
typing-extensions 4.3.0
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https://api.github.com/repos/huggingface/datasets/issues/2465 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2465/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2465/comments | https://api.github.com/repos/huggingface/datasets/issues/2465/events | https://github.com/huggingface/datasets/pull/2465 | 915,525,071 | MDExOlB1bGxSZXF1ZXN0NjY1MzMxMDMz | 2,465 | adding masahaner dataset | {
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"Thank you for the review. ",
"Thanks a lot for the corrections and comments. \r\n\r\nI have resolved point 2. The make style still throws some errors, please see below\r\n\r\nblack --line-length 119 --target-version py36 tests src benchmarks datasets/**/*.py metrics\r\n/bin/sh: 1: black: not found\r\nMakefile:13... | 2021-06-08T21:20:25Z | 2021-06-14T14:59:05Z | 2021-06-14T14:59:05Z | CONTRIBUTOR | null | 0 | {
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} | Adding Masakhane dataset https://github.com/masakhane-io/masakhane-ner
@lhoestq , can you please review | {
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https://api.github.com/repos/huggingface/datasets/issues/3820 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3820/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3820/comments | https://api.github.com/repos/huggingface/datasets/issues/3820/events | https://github.com/huggingface/datasets/issues/3820 | 1,159,106,603 | I_kwDODunzps5FFpAr | 3,820 | `pubmed_qa` checksum mismatch | {
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"descript... | closed | false | null | [] | null | [
"Hi @jon-tow, thanks for reporting.\r\n\r\nThis issue was already reported and its root cause is a change in the Google Drive service. See:\r\n- #3786 \r\n\r\nWe have already fixed it. See:\r\n- #3787 \r\n\r\nWe are planning to make a patch release today.\r\n\r\nIn the meantime, you can get this fix by installing o... | 2022-03-04T00:28:08Z | 2022-03-04T09:42:32Z | 2022-03-04T09:42:32Z | CONTRIBUTOR | null | null | null | ## Describe the bug
Loading [`pubmed_qa`](https://huggingface.co/datasets/pubmed_qa) results in a mismatched checksum error.
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import datasets
try:
datasets.load_dataset("pubmed_qa", "pqa_labeled")
except Exception as e:
print(e)
try:
datasets.load_dataset("pubmed_qa", "pqa_unlabeled")
except Exception as e:
print(e)
try:
datasets.load_dataset("pubmed_qa", "pqa_artificial")
except Exception as e:
print(e)
```
## Expected results
Successful download.
## Actual results
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.9/site-packages/datasets/load.py", line 1702, in load_dataset
builder_instance.download_and_prepare(
File "/usr/local/lib/python3.9/site-packages/datasets/builder.py", line 594, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.9/site-packages/datasets/builder.py", line 665, in _download_and_prepare
verify_checksums(
File "/usr/local/lib/python3.9/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=1RsGLINVce-0GsDkCLDuLZmoLuzfmoCuQ', 'https://drive.google.com/uc?export=download&id=15v1x6aQDlZymaHGP7cZJZZYFfeJt2NdS']
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: macOS
- Python version: 3.8.1
- PyArrow version: 3.0.0
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https://api.github.com/repos/huggingface/datasets/issues/4587 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4587/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4587/comments | https://api.github.com/repos/huggingface/datasets/issues/4587/events | https://github.com/huggingface/datasets/pull/4587 | 1,287,291,494 | PR_kwDODunzps46flzR | 4,587 | Validate new_fingerprint passed by user | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-28T12:46:21Z | 2022-06-28T14:11:57Z | 2022-06-28T14:00:44Z | MEMBER | null | 0 | {
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However the fingerprint is used to name cache files so we need to make sure it doesn't contain bad characters as mentioned in https://github.com/huggingface/datasets/issues/1718, and that it's not too long | {
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https://api.github.com/repos/huggingface/datasets/issues/4144 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4144/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4144/comments | https://api.github.com/repos/huggingface/datasets/issues/4144/events | https://github.com/huggingface/datasets/pull/4144 | 1,200,016,983 | PR_kwDODunzps42ARmu | 4,144 | Fix splits in local packaged modules, local datasets without script and hub datasets without script | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks !\r\nI'm in favor of this change, even though it's a breaking change:\r\n\r\nif you had a dataset\r\n```\r\ndata/\r\n train.csv\r\n test.csv\r\n```\r\n\r\nthen running this code would now return both train and test splits:\r... | 2022-04-11T13:57:33Z | 2022-04-29T09:12:14Z | 2022-04-28T21:02:45Z | CONTRIBUTOR | null | 0 | {
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} | fixes #4150
I suggest to infer splits structure from files when `data_dir` is passed with `get_patterns_locally`, analogous to what's done in `LocalDatasetModuleFactoryWithoutScript` with `self.path`, instead of generating files with `data_dir/**` patterns and putting them all into a single default (train) split.
I would also suggest to align `HubDatasetModuleFactoryWithoutScript` and `LocalDatasetModuleFactoryWithoutScript` with this logic (remove `data_files = os.path.join(data_dir, "**")`). It's not reflected in the current code now as I'd like to discuss it cause I might be unaware of some use cases. @lhoestq @mariosasko @albertvillanova WDYT? | {
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https://api.github.com/repos/huggingface/datasets/issues/2787 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2787/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2787/comments | https://api.github.com/repos/huggingface/datasets/issues/2787/events | https://github.com/huggingface/datasets/issues/2787 | 967,018,406 | MDU6SXNzdWU5NjcwMTg0MDY= | 2,787 | ConnectionError: Couldn't reach https://raw.githubusercontent.com | {
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"the bug code locate in ：\r\n if data_args.task_name is not None:\r\n # Downloading and loading a dataset from the hub.\r\n datasets = load_dataset(\"glue\", data_args.task_name, cache_dir=model_args.cache_dir)",
"Hi @jinec,\r\n\r\nFrom time to time we get this kind of `ConnectionError` coming fr... | 2021-08-11T16:19:01Z | 2023-10-03T12:39:25Z | 2021-08-18T15:09:18Z | NONE | null | null | null | Hello,
I am trying to run run_glue.py and it gives me this error -
Traceback (most recent call last):
File "E:/BERT/pytorch_hugging/transformers/examples/pytorch/text-classification/run_glue.py", line 546, in <module>
main()
File "E:/BERT/pytorch_hugging/transformers/examples/pytorch/text-classification/run_glue.py", line 250, in main
datasets = load_dataset("glue", data_args.task_name, cache_dir=model_args.cache_dir)
File "C:\install\Anaconda3\envs\huggingface\lib\site-packages\datasets\load.py", line 718, in load_dataset
use_auth_token=use_auth_token,
File "C:\install\Anaconda3\envs\huggingface\lib\site-packages\datasets\load.py", line 320, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "C:\install\Anaconda3\envs\huggingface\lib\site-packages\datasets\utils\file_utils.py", line 291, in cached_path
use_auth_token=download_config.use_auth_token,
File "C:\install\Anaconda3\envs\huggingface\lib\site-packages\datasets\utils\file_utils.py", line 623, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.7.0/datasets/glue/glue.py
Trying to do python run_glue.py --model_name_or_path
bert-base-cased
--task_name
mrpc
--do_train
--do_eval
--max_seq_length
128
--per_device_train_batch_size
32
--learning_rate
2e-5
--num_train_epochs
3
--output_dir
./tmp/mrpc/
Is this something on my end? From what I can tell, this was re-fixeded by @fullyz a few months ago.
Thank you!
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https://api.github.com/repos/huggingface/datasets/issues/5117 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5117/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5117/comments | https://api.github.com/repos/huggingface/datasets/issues/5117/events | https://github.com/huggingface/datasets/issues/5117 | 1,409,571,346 | I_kwDODunzps5UBFoS | 5,117 | Progress bars have color red and never completed to 100% | {
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"... | null | [
"Hi @echatzikyriakidis, thanks for submitting the issue.\r\nWhich shell are you using exactly? I tried to run the command you sent, but I don't see colors at all 🧐\r\n\r\nI tried from bash and zsh as well.",
"Hi @david1542 ,\r\n\r\nI use Google Colab.\r\n",
"Got it. I [created a PR](https://github.com/huggingf... | 2022-10-14T16:12:30Z | 2022-10-23T12:58:41Z | 2022-10-23T12:58:41Z | NONE | null | null | null | ## Describe the bug
Progress bars after transformative operations turn in red and never be completed to 100%
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset('rotten_tomatoes', split='test').filter(lambda o: True)
```
## Expected results
Progress bar should be 100% and green
## Actual results
Progress bar turn in red and never completed to 100%
## Environment info
- `datasets` version: 2.6.1
- Platform: Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.14
- PyArrow version: 6.0.1
- Pandas version: 1.3.5 | {
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https://api.github.com/repos/huggingface/datasets/issues/1863 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1863/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1863/comments | https://api.github.com/repos/huggingface/datasets/issues/1863/events | https://github.com/huggingface/datasets/issues/1863 | 806,171,311 | MDU6SXNzdWU4MDYxNzEzMTE= | 1,863 | Add WikiCREM | {
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"Hi @NielsRogge I would like to work on this dataset.\r\n\r\nThanks!",
"Hi @udapy, are you working on this?"
] | 2021-02-11T08:16:00Z | 2021-03-07T07:27:13Z | null | CONTRIBUTOR | null | null | null | ## Adding a Dataset
- **Name:** WikiCREM
- **Description:** A large unsupervised corpus for coreference resolution.
- **Paper:** https://arxiv.org/abs/1905.06290
- **Github repo:**: https://github.com/vid-koci/bert-commonsense
- **Data:** https://ora.ox.ac.uk/objects/uuid:c83e94bb-7584-41a1-aef9-85b0e764d9e3
- **Motivation:** Coreference resolution, common sense reasoning
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/3900 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3900/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3900/comments | https://api.github.com/repos/huggingface/datasets/issues/3900/events | https://github.com/huggingface/datasets/pull/3900 | 1,167,224,903 | PR_kwDODunzps40VxRh | 3,900 | Add MetaShift dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"@lhoestq Please could you review this when you get time. Thank you.",
"Thanks a lot for your inputs @mariosasko .\r\n> Maybe we can add the generated meta-graphs to the card as images (with attributions)?\r\n\r\nYes. We can do this... | 2022-03-12T08:44:18Z | 2022-04-01T16:59:48Z | 2022-04-01T15:16:30Z | CONTRIBUTOR | null | 0 | {
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} | This PR adds the MetaShift dataset.
Dataset Request : Add MetaShift dataset [#3813](https://github.com/huggingface/datasets/issues/3813)
@lhoestq As discussed,
- I have copied the preprocessing script and modified it as required to not create new directories and folders and instead yield the images.
- I do the preprocessing in _split_generators to get the required data which is then passed to _generate_examples.
- Beyond the generated MetaShift dataset, the original preprocess script also generates the meta-graphs for each class, I have currently not included this part. [ Ref : [Link](https://github.com/Weixin-Liang/MetaShift#generate-full-metashift) ]
- There is a Bonus section, the authors share. I have currently not included this part. [ Ref : [Link](https://github.com/Weixin-Liang/MetaShift#bonus-generate-the-metashift-attributes-dataset-subsets-defined-by-subject-attributes) ]
- I had a basic test script which downloaded the dataset and tested the basic functionality. Things seems fine.
For real data, I performed the following test :
```
RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_metashift
============================================== test session starts ===============================================
platform linux -- Python 3.7.11, pytest-7.0.1, pluggy-1.0.0
rootdir: ./datasets
plugins: hydra-core-1.1.1, datadir-1.3.1, forked-1.4.0, xdist-2.5.0
collected 1 item
tests/test_dataset_common.py . [100%]
========================================= 1 passed in 4821.25s (1:20:21) =========================================
```
- I couldn't get the dummy dataset. Need some inputs here.
Error as follows :
```
Using custom data configuration default
Dataset metashift with config None seems to already open files in the method `_split_generators(...)`. You might consider to instead only open files in the method `_generate_examples(...)` instead. If this is not possible the dummy data has to be created with less guidance. Make sure you create the file dummy_data/full-candidate-subsets.pkl.
for split in generator_splits:
UnboundLocalError: local variable 'generator_splits' referenced before assignment
```
To-Do :
- [x] Currently I am using the default _SELECTED_CLASSES. I need to use config option here as suggested
- [x] Complete fields in the Dataset Card.
- [x] Tagging the dataset using the Datasets Tagging app.
Need your help and suggestions for improvement. Thank you
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https://api.github.com/repos/huggingface/datasets/issues/6189 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6189/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6189/comments | https://api.github.com/repos/huggingface/datasets/issues/6189/events | https://github.com/huggingface/datasets/pull/6189 | 1,871,569,855 | PR_kwDODunzps5ZB8Z9 | 6,189 | Don't alter input in Features.from_dict | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-08-29T12:29:47Z | 2023-08-29T13:04:59Z | 2023-08-29T12:52:48Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4056 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4056/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4056/comments | https://api.github.com/repos/huggingface/datasets/issues/4056/events | https://github.com/huggingface/datasets/issues/4056 | 1,185,155,775 | I_kwDODunzps5GpAq_ | 4,056 | Unexpected behavior of _TempDirWithCustomCleanup | {
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"Hi ! Would setting TMPDIR at the beginning of your python script/session work ? I mean, even before importing transformers, datasets, etc. and using them ? I think this would be the most robust solution given any library that uses `tempfile`. I don't think we aim to support environment variables to be changed at r... | 2022-03-29T16:58:22Z | 2022-03-30T15:08:04Z | null | NONE | null | null | null | ## Describe the bug
This is not 100% a bug in `datasets`, but behavior that surprised me and I think this could be made more robust on the `datasets`side.
When using `datasets.disable_caching()`, cache files are written to a temporary directory. This directory should be based on the environment variable TMPDIR. I want to set TMPDIR at runtime using os.ENVIRON["TMPDIR"] = something, but depending on other imported modules this can fail to take effect.
## Steps to reproduce the bug
`_TempDirWithCustomCleanup` relies on `tempfile` to generate a path to a temporary directory. However, `tempfile` generates the path only once. This can be a problem when trying to set TMPDIR at runtime whenever other code imports `tempfile` first and does something unexpected.
For example (after too much trial and error) I found out that a different part of the code base I work with defines a class `PatchedDataCollatorForLanguageModeling(transformers.DataCollatorForLanguageModeling)` based on a `transformers` class. This import is enough to trigger `tempfile` to generate `tempfile` to generate a temporary path and leading to the wrong path being cached in `tempfile.tempdir`.
## Suggestion:
I could file this also as bug with `transformers`, but I think fixing this on the datasets would be much more robust:
Datasets could recompute the temporary path once (technically possible via `tempfile._get_default_tempdir` or resetting
the global variable `tempfile.tmpdir` to None) before setting its own global `_TEMP_DIR_FOR_TEMP_CACHE_FILES`.
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https://api.github.com/repos/huggingface/datasets/issues/3085 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3085/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3085/comments | https://api.github.com/repos/huggingface/datasets/issues/3085/events | https://github.com/huggingface/datasets/pull/3085 | 1,026,467,384 | PR_kwDODunzps4tNFza | 3,085 | Fixes to `to_tf_dataset` | {
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"Hi ! Can you give some details about why you need these changes ?",
"Hey, sorry, I should have explained! I've been getting a lot of `VisibleDeprecationWarning` from Numpy, due to an issue in the formatter, see #3084 . This is a temporary workaround (since I'm using these methods in the upcoming course) until I ... | 2021-10-14T14:25:56Z | 2021-10-21T15:05:29Z | 2021-10-21T15:05:28Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2849 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2849/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2849/comments | https://api.github.com/repos/huggingface/datasets/issues/2849/events | https://github.com/huggingface/datasets/issues/2849 | 982,631,420 | MDU6SXNzdWU5ODI2MzE0MjA= | 2,849 | Add Open Catalyst Project Dataset | {
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- **Name:** Open Catalyst 2020 (OC20) Dataset
- **Website:** https://opencatalystproject.org/
- **Data:** https://github.com/Open-Catalyst-Project/ocp/blob/master/DATASET.md
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/3319 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3319/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3319/comments | https://api.github.com/repos/huggingface/datasets/issues/3319/events | https://github.com/huggingface/datasets/pull/3319 | 1,062,749,654 | PR_kwDODunzps4u-xdv | 3,319 | Add push_to_hub docs | {
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"Looks good to me! :)\r\n\r\nMaybe we can mention that users can also set the `private` argument if they want to keep their dataset private? It would lead nicely into the next section on Privacy.",
"Thanks for your comments, I fixed the capitalization for consistency and added an passage to mention the `private` ... | 2021-11-24T18:21:11Z | 2021-11-25T14:47:46Z | 2021-11-25T14:47:46Z | MEMBER | null | 0 | {
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} | Since #3098 it's now possible to upload a dataset on the Hub directly from python using the `push_to_hub` method.
I just added a section in the "Upload a dataset to the Hub" tutorial.
I kept the section quite simple but let me know if it sounds good to you @LysandreJik @stevhliu :) | {
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https://api.github.com/repos/huggingface/datasets/issues/2184 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2184/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2184/comments | https://api.github.com/repos/huggingface/datasets/issues/2184/events | https://github.com/huggingface/datasets/pull/2184 | 852,597,258 | MDExOlB1bGxSZXF1ZXN0NjEwODIxMTc0 | 2,184 | Implementation of class_encode_column | {
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"Made the required changes @lhoestq , sorry it took so much time!"
] | 2021-04-07T16:47:43Z | 2021-04-16T11:44:37Z | 2021-04-16T11:26:59Z | CONTRIBUTOR | null | 0 | {
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I'm happy to discuss the API and internals! | {
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https://api.github.com/repos/huggingface/datasets/issues/6102 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6102/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6102/comments | https://api.github.com/repos/huggingface/datasets/issues/6102/events | https://github.com/huggingface/datasets/pull/6102 | 1,828,494,896 | PR_kwDODunzps5WwyGy | 6,102 | Release 2.14.2 | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-07-31T06:27:47Z | 2023-07-31T06:48:09Z | 2023-07-31T06:32:58Z | MEMBER | null | 0 | {
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