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https://api.github.com/repos/huggingface/datasets/issues/3307 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3307/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3307/comments | https://api.github.com/repos/huggingface/datasets/issues/3307/events | https://github.com/huggingface/datasets/pull/3307 | 1,059,226,297 | PR_kwDODunzps4uzlWa | 3,307 | Add IndoNLI dataset | {
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"@lhoestq thanks for the review! I've modified the labels to follow other NLI datasets.\r\nPlease review my change and let me know if I miss anything."
] | 1,637,441,163,000 | 1,637,851,908,000 | 1,637,851,908,000 | CONTRIBUTOR | null | This PR adds IndoNLI dataset, from https://aclanthology.org/2021.emnlp-main.821/ | {
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https://api.github.com/repos/huggingface/datasets/issues/3305 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3305/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3305/comments | https://api.github.com/repos/huggingface/datasets/issues/3305/events | https://github.com/huggingface/datasets/pull/3305 | 1,059,161,000 | PR_kwDODunzps4uzZWv | 3,305 | asserts replaced with exception for ``fingerprint.py``, ``search.py``, ``arrow_writer.py`` and ``metric.py`` | {
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Fixes exception for ``fingerprint.py``, ``search.py``, ``arrow_writer.py`` and ``metric.py`` and modified tests | {
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https://api.github.com/repos/huggingface/datasets/issues/3304 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3304/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3304/comments | https://api.github.com/repos/huggingface/datasets/issues/3304/events | https://github.com/huggingface/datasets/issues/3304 | 1,059,130,494 | I_kwDODunzps4_IQx- | 3,304 | Dataset object has no attribute `to_tf_dataset` | {
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"The issue is due to the older version of transformers and datasets. It has been resolved by upgrading their versions.\r\n\r\n```\r\n# upgrade transformers and datasets to latest versions\r\n!pip install --upgrade transformers\r\n!pip install --upgrade datasets\r\n```\r\n\r\nRegards!"
] | 1,637,409,839,000 | 1,637,478,445,000 | 1,637,478,445,000 | NONE | null | I am following HuggingFace Course. I am at Fine-tuning a model.
Link: https://huggingface.co/course/chapter3/2?fw=tf
I use tokenize_function and `map` as mentioned in the course to process data.
`# define a tokenize function`
`def Tokenize_function(example):`
` return tokenizer(example['sentence'], truncation=True)`
`# tokenize entire data`
`tokenized_data = raw_data.map(Tokenize_function, batched=True)`
I get Dataset object at this point. When I try converting this to a TF dataset object as mentioned in the course, it throws the following error.
`# convert to TF dataset`
`train_data = tokenized_data["train"].to_tf_dataset( `
` columns = ['attention_mask', 'input_ids', 'token_type_ids'], `
` label_cols = ['label'], `
` shuffle = True, `
` collate_fn = data_collator, `
` batch_size = 8 `
`)`
Output:
`---------------------------------------------------------------------------`
`AttributeError Traceback (most recent call last)`
`/tmp/ipykernel_42/103099799.py in <module>`
` 1 # convert to TF dataset`
`----> 2 train_data = tokenized_data["train"].to_tf_dataset( \`
` 3 columns = ['attention_mask', 'input_ids', 'token_type_ids'], \`
` 4 label_cols = ['label'], \`
` 5 shuffle = True, \`
`AttributeError: 'Dataset' object has no attribute 'to_tf_dataset'`
When I look for `dir(tokenized_data["train"])`, there is no method or attribute in the name of `to_tf_dataset`.
Why do I get this error? And how to clear this?
Please help me. | {
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https://api.github.com/repos/huggingface/datasets/issues/3303 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3303/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3303/comments | https://api.github.com/repos/huggingface/datasets/issues/3303/events | https://github.com/huggingface/datasets/issues/3303 | 1,059,129,732 | I_kwDODunzps4_IQmE | 3,303 | DataCollatorWithPadding: TypeError | {
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"\r\n> \r\n> Input:\r\n> \r\n> ```\r\n> tokenizer = AutoTokenizer.from_pretrained(checkpoint)\r\n> data_collator = DataCollatorWithPadding(tokenizer=tokenizer, return_tensors=\"tf\")\r\n> ```\r\n> \r\n> Output:\r\n> \r\n> ```\r\n> TypeError Traceback (most recent call last)\r\n> /tmp/ipykernel_42/1563280798.py in <module>\r\n> 1 checkpoint = 'bert-base-uncased'\r\n> 2 tokenizer = AutoTokenizer.from_pretrained(checkpoint)\r\n> ----> 3 data_collator = DataCollatorWithPadding(tokenizer=tokenizer, return_tensors=\"pt\")\r\n> TypeError: __init__() got an unexpected keyword argument 'return_tensors'\r\n> ```\r\n> \r\n\r\nThe issue is due to the older version of transformers and datasets. It has been resolved by upgrading their versions.\r\n\r\n`# upgrade transformers and datasets to latest versions`\r\n`!pip install --upgrade transformers`\r\n`!pip install --upgrade datasets`\r\n\r\nCheers!"
] | 1,637,409,595,000 | 1,637,478,337,000 | 1,637,478,337,000 | NONE | null | Hi,
I am following the HuggingFace course. I am now at Fine-tuning [https://huggingface.co/course/chapter3/3?fw=tf](https://huggingface.co/course/chapter3/3?fw=tf). When I set up `DataCollatorWithPadding` as following I got an error while trying to reproduce the course code in Kaggle. This error occurs with either a CPU-only-device or a GPU-device.
Input:
```checkpoint = 'bert-base-uncased'
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
data_collator = DataCollatorWithPadding(tokenizer=tokenizer, return_tensors="tf")
```
Output:
```---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/tmp/ipykernel_42/1563280798.py in <module>
1 checkpoint = 'bert-base-uncased'
2 tokenizer = AutoTokenizer.from_pretrained(checkpoint)
----> 3 data_collator = DataCollatorWithPadding(tokenizer=tokenizer, return_tensors="pt")
TypeError: __init__() got an unexpected keyword argument 'return_tensors'
```
When I call `help` method, it too confirms that there is no argument `return_tensors`.
Input:
```
help(DataCollatorWithPadding.__init__)
```
Output:
```
Help on function __init__ in module transformers.data.data_collator:
__init__(self, tokenizer: transformers.tokenization_utils_base.PreTrainedTokenizerBase, padding: Union[bool, str, transformers.file_utils.PaddingStrategy] = True, max_length: Union[int, NoneType] = None, pad_to_multiple_of: Union[int, NoneType] = None) -> None
```
But, the source file *[Data Collator - docs](https://huggingface.co/transformers/main_classes/data_collator.html#datacollatorwithpadding)* says that there is such an argument. By default, it returns Pytorch tensors while I need TF tensors.
Where do I miss?
Please help me. | {
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https://api.github.com/repos/huggingface/datasets/issues/3302 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3302/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3302/comments | https://api.github.com/repos/huggingface/datasets/issues/3302/events | https://github.com/huggingface/datasets/pull/3302 | 1,058,907,168 | PR_kwDODunzps4uynjc | 3,302 | fix old_val typo in f-string | {
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} | [] | closed | false | null | [] | null | [] | 1,637,355,068,000 | 1,637,878,483,000 | 1,637,600,659,000 | CONTRIBUTOR | null |
This PR is to correct a typo in #3277 that @Carlosbogo revieled in a comment.
Related closed issue : #3257
Sorry about that π
. | {
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https://api.github.com/repos/huggingface/datasets/issues/3301 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3301/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3301/comments | https://api.github.com/repos/huggingface/datasets/issues/3301/events | https://github.com/huggingface/datasets/pull/3301 | 1,058,718,957 | PR_kwDODunzps4uyA9o | 3,301 | Add wikipedia tags | {
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I also added the missing languages code in our language codes list.
This should also fix the code snippet that is presented on the Hub to load the dataset: fix https://github.com/huggingface/datasets/issues/3292 | {
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https://api.github.com/repos/huggingface/datasets/issues/3296 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3296/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3296/comments | https://api.github.com/repos/huggingface/datasets/issues/3296/events | https://github.com/huggingface/datasets/pull/3296 | 1,057,970,638 | PR_kwDODunzps4uvlQz | 3,296 | Fix temporary dataset_path creation for URIs related to remote fs | {
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"Hi ! Thanks for the fix :) \r\n\r\nI think this should be `extract_path_from_uri` 's responsibility to strip the extra `/` from a badly formatted path like `hdfs:///absolute/path` (or raise an error). Do you think you can simply do the changes in `extract_path_from_uri` ? This way this fix will be available for all the other parts of the lib that need to extract the inner path from an URI of a remote filesystem\r\n\r\nThen we can also keep your test cases but simply apply them to `extract_path_from_uri` instead",
"Hi @lhoestq! No problem! Thanks for your interest! :)\r\n\r\nI think stripping the 3rd `/` in `hdfs:///absolute/path` inside `extract_path_from_uri` is not the solution. When I provide `hdfs:///absolute/path` to `extract_path_from_uri` we want `/absolute/path` to be returned, as it does now (at least in the case of URIs with `hdfs` schemas, for `s3` is different as it should start with a bucket name).\r\n\r\nThe problem comes in line 1041 in the original code below:\r\n\r\nhttps://github.com/huggingface/datasets/blob/42f6b1d18a4a1b6009b6e62d115491be16dfca22/src/datasets/arrow_dataset.py#L1038-L1042\r\n\r\nLets assume the following parameters for line 1041 after `extract_path_from_uri` has removed the `hdfs` schema part and the `://` from `hdfs:///absolute/path`, and `get_temporary_cache_files_directory()` returns `/tmp/a1b2b3c4`, as it is shown below: \r\n\r\n```python\r\nsrc_dataset_path = '/absolute/path'\r\ntmp_dir = '/tmp/a1b2b3c4'\r\ndataset_path = Path(tmp_dir, src_dataset_path)\r\n```\r\n\r\nAfter passing those paths to the `Path` object, `dataset_path` contains only `/absolute/path`; that is, it has lost the temporary directory path. This is because, when two (or more) absolute paths are passed to the `Path` function, only the last one is taken. However, if the contents of those variables are:\r\n\r\n```python\r\nsrc_dataset_path = 'relative/path'\r\ntmp_dir = '/tmp/a1b2b3c4'\r\ndataset_path = Path(tmp_dir, src_dataset_path)\r\n```\r\n\r\nthen `dataset_path` contains `/tmp/a1b2b3c4/relative/path` as expected.\r\n\r\nAbsolute paths are allowed in hdfs URIs, so that's why I added the extra function `build_local_temp_path` in the PR; so in case the second argument is an absolute path, it still will create the correct absolute path by concatenating the temp dir and the path passed by converting it to a relative path (and it also works for windows paths too.) It also allows to add the tests, checking that the main combinations are ok.\r\n\r\nI've checked all the places where the result of `extract_path_from_uri` is used, and as far as I've seen this is the only place where it is concatenated with another possible absolute path, so no need to add `build_local_temp_path` anywhere else. \r\n"
] | 1,637,278,365,000 | 1,638,787,504,000 | 1,638,787,504,000 | CONTRIBUTOR | null | This aims to close #3295 | {
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"Hi ! Good catch and thanks for opening a PR :)\r\n\r\nI just responded in your PR"
] | 1,637,277,842,000 | 1,638,787,504,000 | 1,638,787,504,000 | CONTRIBUTOR | null | ## Describe the bug
When trying to build a temporary dataset path from a remote URI in this block of code:
https://github.com/huggingface/datasets/blob/42f6b1d18a4a1b6009b6e62d115491be16dfca22/src/datasets/arrow_dataset.py#L1038-L1042
the result is not the expected when passing an absolute path in an URI like `hdfs:///absolute/path`.
## Steps to reproduce the bug
```python
dataset_path = "hdfs:///absolute/path"
src_dataset_path = extract_path_from_uri(dataset_path)
tmp_dir = get_temporary_cache_files_directory()
dataset_path = Path(tmp_dir, src_dataset_path)
print(dataset_path)
```
## Expected results
With the code above, we would expect a value in `dataset_path` similar to:
`/tmp/tmpnwxyvao5/absolute/path`
## Actual results
However, we get a `dataset_path` value like:
`/absolute/path`
This is because this line here: https://github.com/huggingface/datasets/blob/42f6b1d18a4a1b6009b6e62d115491be16dfca22/src/datasets/arrow_dataset.py#L1041
returns the last absolute path when two absolute paths (the one in `tmp_dir` and the one extracted from the URI in `src_dataset_path`) are passed as arguments.
## Environment info
- `datasets` version: 1.13.3
- Platform: Linux-3.10.0-1160.15.2.el7.x86_64-x86_64-with-glibc2.33
- Python version: 3.9.7
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3293 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3293/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3293/comments | https://api.github.com/repos/huggingface/datasets/issues/3293/events | https://github.com/huggingface/datasets/pull/3293 | 1,057,004,431 | PR_kwDODunzps4uslLN | 3,293 | Pin version exclusion for Markdown | {
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Related to #3289, #3286. | {
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"Hi ! Indeed it looks like the code snippet on the Hugging face Hub doesn't show the second parameter\r\n\r\n![image](https://user-images.githubusercontent.com/42851186/142649237-45ba55c5-1a64-4c30-8692-2c8120572f92.png)\r\n\r\nThanks for reporting, I'm taking a look\r\n"
] | 1,637,214,078,000 | 1,637,340,569,000 | 1,637,340,569,000 | NONE | null | ## Describe the bug
I am following the instruction for loading the wikipedia dataset using datasets. However getting the below error.
## Steps to reproduce the bug
from datasets import load_dataset
dataset = load_dataset("wikipedia")
```
## Expected results
A clear and concise description of the expected results.
## Actual results
~/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/datasets/builder.py in _create_builder_config(self, name, custom_features, **config_kwargs)
339 "Config name is missing."
340 "\nPlease pick one among the available configs: %s" % list(self.builder_configs.keys())
--> 341 + "\nExample of usage:\n\t`{}`".format(example_of_usage)
342 )
343 builder_config = self.BUILDER_CONFIGS[0]
ValueError: Config name is missing.
Please pick one among the available configs: ['20200501.aa', '20200501.ab', '20200501.ace', '20200501.ady', '20200501.af', '20200501.ak', '20200501.als', '20200501.am', '20200501.an', '20200501.ang', '20200501.ar', '20200501.arc', '20200501.arz', '20200501.as', '20200501.ast', '20200501.atj', '20200501.av', '20200501.ay', '20200501.az', '20200501.azb', '20200501.ba', '20200501.bar', '20200501.bat-smg', '20200501.bcl', '20200501.be', '20200501.be-x-old', '20200501.bg', '20200501.bh', '20200501.bi', '20200501.bjn', '20200501.bm', '20200501.bn', '20200501.bo', '20200501.bpy', '20200501.br', '20200501.bs', '20200501.bug', '20200501.bxr', '20200501.ca', '20200501.cbk-zam', '20200501.cdo', '20200501.ce', '20200501.ceb', '20200501.ch', '20200501.cho', '20200501.chr', '20200501.chy', '20200501.ckb', '20200501.co', '20200501.cr', '20200501.crh', '20200501.cs', '20200501.csb', '20200501.cu', '20200501.cv', '20200501.cy', '20200501.da', '20200501.de', '20200501.din', '20200501.diq', '20200501.dsb', '20200501.dty', '20200501.dv', '20200501.dz', '20200501.ee', '20200501.el', '20200501.eml', '20200501.en', '20200501.eo', '20200501.es', '20200501.et', '20200501.eu', '20200501.ext', '20200501.fa', '20200501.ff', '20200501.fi', '20200501.fiu-vro', '20200501.fj', '20200501.fo', '20200501.fr', '20200501.frp', '20200501.frr', '20200501.fur', '20200501.fy', '20200501.ga', '20200501.gag', '20200501.gan', '20200501.gd', '20200501.gl', '20200501.glk', '20200501.gn', '20200501.gom', '20200501.gor', '20200501.got', '20200501.gu', '20200501.gv', '20200501.ha', '20200501.hak', '20200501.haw', '20200501.he', '20200501.hi', '20200501.hif', '20200501.ho', '20200501.hr', '20200501.hsb', '20200501.ht', '20200501.hu', '20200501.hy', '20200501.ia', '20200501.id', '20200501.ie', '20200501.ig', '20200501.ii', '20200501.ik', '20200501.ilo', '20200501.inh', '20200501.io', '20200501.is', '20200501.it', '20200501.iu', '20200501.ja', '20200501.jam', '20200501.jbo', '20200501.jv', '20200501.ka', '20200501.kaa', '20200501.kab', '20200501.kbd', '20200501.kbp', '20200501.kg', '20200501.ki', '20200501.kj', '20200501.kk', '20200501.kl', '20200501.km', '20200501.kn', '20200501.ko', '20200501.koi', '20200501.krc', '20200501.ks', '20200501.ksh', '20200501.ku', '20200501.kv', '20200501.kw', '20200501.ky', '20200501.la', '20200501.lad', '20200501.lb', '20200501.lbe', '20200501.lez', '20200501.lfn', '20200501.lg', '20200501.li', '20200501.lij', '20200501.lmo', '20200501.ln', '20200501.lo', '20200501.lrc', '20200501.lt', '20200501.ltg', '20200501.lv', '20200501.mai', '20200501.map-bms', '20200501.mdf', '20200501.mg', '20200501.mh', '20200501.mhr', '20200501.mi', '20200501.min', '20200501.mk', '20200501.ml', '20200501.mn', '20200501.mr', '20200501.mrj', '20200501.ms', '20200501.mt', '20200501.mus', '20200501.mwl', '20200501.my', '20200501.myv', '20200501.mzn', '20200501.na', '20200501.nah', '20200501.nap', '20200501.nds', '20200501.nds-nl', '20200501.ne', '20200501.new', '20200501.ng', '20200501.nl', '20200501.nn', '20200501.no', '20200501.nov', '20200501.nrm', '20200501.nso', '20200501.nv', '20200501.ny', '20200501.oc', '20200501.olo', '20200501.om', '20200501.or', '20200501.os', '20200501.pa', '20200501.pag', '20200501.pam', '20200501.pap', '20200501.pcd', '20200501.pdc', '20200501.pfl', '20200501.pi', '20200501.pih', '20200501.pl', '20200501.pms', '20200501.pnb', '20200501.pnt', '20200501.ps', '20200501.pt', '20200501.qu', '20200501.rm', '20200501.rmy', '20200501.rn', '20200501.ro', '20200501.roa-rup', '20200501.roa-tara', '20200501.ru', '20200501.rue', '20200501.rw', '20200501.sa', '20200501.sah', '20200501.sat', '20200501.sc', '20200501.scn', '20200501.sco', '20200501.sd', '20200501.se', '20200501.sg', '20200501.sh', '20200501.si', '20200501.simple', '20200501.sk', '20200501.sl', '20200501.sm', '20200501.sn', '20200501.so', '20200501.sq', '20200501.sr', '20200501.srn', '20200501.ss', '20200501.st', '20200501.stq', '20200501.su', '20200501.sv', '20200501.sw', '20200501.szl', '20200501.ta', '20200501.tcy', '20200501.te', '20200501.tet', '20200501.tg', '20200501.th', '20200501.ti', '20200501.tk', '20200501.tl', '20200501.tn', '20200501.to', '20200501.tpi', '20200501.tr', '20200501.ts', '20200501.tt', '20200501.tum', '20200501.tw', '20200501.ty', '20200501.tyv', '20200501.udm', '20200501.ug', '20200501.uk', '20200501.ur', '20200501.uz', '20200501.ve', '20200501.vec', '20200501.vep', '20200501.vi', '20200501.vls', '20200501.vo', '20200501.wa', '20200501.war', '20200501.wo', '20200501.wuu', '20200501.xal', '20200501.xh', '20200501.xmf', '20200501.yi', '20200501.yo', '20200501.za', '20200501.zea', '20200501.zh', '20200501.zh-classical', '20200501.zh-min-nan', '20200501.zh-yue', '20200501.zu']
Example of usage:
`load_dataset('wikipedia', '20200501.aa')`
I think the other parameter is missing in the load_dataset function that is not shown in the instruction. | {
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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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"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(['file', 'audio', 'text', 'speaker_id', 'chapter_id', 'id'])\r\n\r\nIn [5]: item[\"file\"]\r\nOut[5]: '374-180298-0000.flac'\r\n\r\nIn [6]: item[\"audio\"].keys()\r\nOut[6]: dict_keys(['path', 'array', 'sampling_rate'])\r\n\r\nIn [7]: item[\"audio\"][\"sampling_rate\"]\r\nOut[7]: 16000\r\n\r\nIn [8]: item[\"audio\"][\"path\"]\r\nOut[8]: '374-180298-0000.flac'\r\n\r\nIn [9]: item[\"audio\"][\"array\"].shape\r\nOut[9]: (232480,)\r\n```",
"Oh cool ! I think this might have come from an issue with my local `soundfile` installation then",
"I'll do `multilingual_librispeech` in a separate PR since it requires the data to be in another format (in particular separate the train/dev/test splits in different files)"
] | 1,637,171,021,000 | 1,637,334,538,000 | 1,637,334,537,000 | MEMBER | null | <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/3289 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3289/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3289/comments | https://api.github.com/repos/huggingface/datasets/issues/3289/events | https://github.com/huggingface/datasets/pull/3289 | 1,056,323,715 | PR_kwDODunzps4uqf79 | 3,289 | Unpin markdown for build_docs now that it's fixed | {
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https://api.github.com/repos/huggingface/datasets/issues/3288 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3288/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3288/comments | https://api.github.com/repos/huggingface/datasets/issues/3288/events | https://github.com/huggingface/datasets/pull/3288 | 1,056,145,703 | PR_kwDODunzps4up6S5 | 3,288 | Allow datasets with indices table when concatenating along axis=1 | {
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} | [] | closed | false | null | [] | null | [] | 1,637,156,488,000 | 1,637,163,672,000 | 1,637,163,671,000 | CONTRIBUTOR | null | Calls `flatten_indices` on the datasets with indices table in `concatenate_datasets` to fix issues when concatenating along `axis=1`.
cc @lhoestq: I decided to flatten all the datasets instead of flattening all the datasets except the largest one in the end. The latter approach fails on the following example:
```python
a = Dataset.from_dict({"a": [10, 20, 30, 40]})
b = Dataset.from_dict({"b": [10, 20, 30, 40, 50, 60]}) # largest dataset
a = a.select([1, 2, 3])
b = b.select([1, 2, 3])
concatenate_datasets([a, b], axis=1) # fails at line concat_tables(...) because the real length of b's data is 6 and a's length is 3 after flattening (was 4 before flattening)
```
Also, it requires additional re-ordering of indices to prepare them for working with the indices table of the largest dataset. IMO not worth when we save only one `flatten_indices` call. (feel free to check the code of that approach at https://github.com/huggingface/datasets/commit/6acd10481c70950dcfdbfd2bab0bf0c74ad80bcb if you are interested)
Fixes #3273
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https://api.github.com/repos/huggingface/datasets/issues/3287 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3287/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3287/comments | https://api.github.com/repos/huggingface/datasets/issues/3287/events | https://github.com/huggingface/datasets/pull/3287 | 1,056,079,724 | PR_kwDODunzps4upsWR | 3,287 | Add The Pile dataset and PubMed Central subset | {
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} | [] | closed | false | null | [] | null | [] | 1,637,152,558,000 | 1,638,372,548,000 | 1,638,372,547,000 | MEMBER | null | Add:
- The complete final version of The Pile dataset: "all" config
- PubMed Central subset of The Pile: "pubmed_central" config
Close #1675, close bigscience-workshop/data_tooling#74.
CC: @StellaAthena, @lewtun | {
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https://api.github.com/repos/huggingface/datasets/issues/3286 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3286/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3286/comments | https://api.github.com/repos/huggingface/datasets/issues/3286/events | https://github.com/huggingface/datasets/pull/3286 | 1,056,008,586 | PR_kwDODunzps4updTK | 3,286 | Fix build_docs CI | {
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https://api.github.com/repos/huggingface/datasets/issues/3281 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3281/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3281/comments | https://api.github.com/repos/huggingface/datasets/issues/3281/events | https://github.com/huggingface/datasets/pull/3281 | 1,055,018,876 | PR_kwDODunzps4umWZE | 3,281 | [Datasets] Improve Covost 2 | {
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} | [] | closed | false | null | [] | null | [] | 1,637,076,739,000 | 1,637,232,266,000 | 1,637,232,244,000 | MEMBER | null | It's currently quite confusing to understand the manual data download instruction of Covost and not very user-friendly.
Currenty the user has to:
1. Go on Common Voice website
2. Find the correct dataset which is **not** mentioned in the error message
3. Download it
4. Untar it
5. Create a language id folder (why? this folder does not exist in the `.tar` downloaded file)
6. pass the folder containing the created language id folder
This PR improves this to:
1. Go on Common Voice website
2. Find the correct dataset which **is** mentioned in the error message
3. Download it
4. Untar it
5. pass the untared folder
**Note**: This PR is not at all time-critical | {
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} | [] | closed | false | null | [] | null | [] | 1,637,062,072,000 | 1,637,164,408,000 | 1,637,069,670,000 | MEMBER | null | Each document is a full book, so the default arrow writer batch size of 10,000 is too big, and it can fill up RAM quickly before flushing the first batch on disk. I changed its batch size to 256 to use maximum 100MB of memory
Fix #3167. | {
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https://api.github.com/repos/huggingface/datasets/issues/3279 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3279/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3279/comments | https://api.github.com/repos/huggingface/datasets/issues/3279/events | https://github.com/huggingface/datasets/pull/3279 | 1,054,711,852 | PR_kwDODunzps4ulVHe | 3,279 | Minor Typo Fix - Precision to Recall | {
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https://api.github.com/repos/huggingface/datasets/issues/3278 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3278/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3278/comments | https://api.github.com/repos/huggingface/datasets/issues/3278/events | https://github.com/huggingface/datasets/pull/3278 | 1,054,249,463 | PR_kwDODunzps4uj2EQ | 3,278 | Proposed update to the documentation for WER | {
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Because of the possibility of insertions, the numerator in the WER formula can be larger than N, so the value of WER can be greater than 1.0:
```
>>> from datasets import load_metric
>>> metric = load_metric("wer")
>>> metric.compute(predictions=["hello how are you"], references=["hello"])
3.0
```
and similarly from the underlying jiwer module's `wer` function:
```
>>> from jiwer import wer
>>> wer("hello", "hello how are you")
3.0
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3277 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3277/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3277/comments | https://api.github.com/repos/huggingface/datasets/issues/3277/events | https://github.com/huggingface/datasets/pull/3277 | 1,054,122,656 | PR_kwDODunzps4ujk11 | 3,277 | f-string formatting | {
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"Hello @lhoestq, ```make style``` is applied as asked. :)"
] | 1,637,012,225,000 | 1,637,354,408,000 | 1,637,165,918,000 | CONTRIBUTOR | null | **Fix #3257**
Replaced _.format()_ and _%_ by f-strings in the following modules :
- [x] **tests**
- [x] **metrics**
- [x] **benchmarks**
- [x] **utils**
- [x] **templates**
- [x] **src/Datasets/\*.py**
Modules in **_src/Datasets/_**:
- [x] **commands**
- [x] **features**
- [x] **formatting**
- [x] **io**
- [x] **tasks**
- [x] **utils**
Module **datasets** will not be edited as asked by @mariosasko
-A correction of the first PR (#3267)-
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https://api.github.com/repos/huggingface/datasets/issues/3276 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3276/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3276/comments | https://api.github.com/repos/huggingface/datasets/issues/3276/events | https://github.com/huggingface/datasets/pull/3276 | 1,053,793,063 | PR_kwDODunzps4uihih | 3,276 | Update KILT metadata JSON | {
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https://api.github.com/repos/huggingface/datasets/issues/3275 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3275/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3275/comments | https://api.github.com/repos/huggingface/datasets/issues/3275/events | https://github.com/huggingface/datasets/pull/3275 | 1,053,698,898 | PR_kwDODunzps4uiN9t | 3,275 | Force data files extraction if download_mode='force_redownload' | {
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} | [] | closed | false | null | [] | null | [] | 1,636,984,824,000 | 1,636,987,523,000 | 1,636,987,523,000 | CONTRIBUTOR | null | Avoids weird issues when redownloading a dataset due to cached data not being fully updated.
With this change, issues #3122 and https://github.com/huggingface/datasets/issues/2956 (not a fix, but a workaround) can be fixed as follows:
```python
dset = load_dataset(..., download_mode="force_redownload")
``` | {
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"The CI fail are caused by some missing sections or tags, which is unrelated to this PR. Merging !"
] | 1,636,984,234,000 | 1,636,987,435,000 | 1,636,987,434,000 | MEMBER | null | As reported in https://github.com/huggingface/datasets/issues/3188 some contact information are not displayed correctly.
This PR fixes this for CoNLL-2002 and some other datasets with the same issue | {
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] | closed | false | null | [] | null | [] | 1,636,975,634,000 | 1,637,163,671,000 | 1,637,163,671,000 | CONTRIBUTOR | null | Currently, there is a bug when concatenating datasets along `axis=1` if more than one dataset has the `_indices` attribute defined. In that scenario, all indices mappings except the first one get ignored.
A minimal reproducible example:
```python
>>> from datasets import Dataset, concatenate_datasets
>>> a = Dataset.from_dict({"a": [30, 20, 10]})
>>> b = Dataset.from_dict({"b": [2, 1, 3]})
>>> d = concatenate_datasets([a.sort("a"), b.sort("b")], axis=1)
>>> print(d[:3]) # expected: {'a': [10, 20, 30], 'b': [1, 2, 3]}
{'a': [10, 20, 30], 'b': [3, 1, 2]}
```
I've noticed the bug while working on #3195. | {
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To fix this I replaced `open` with our `xopen` functoin that is compatible with remote files in audio.py
cc @albertvillanova @mariosasko | {
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https://api.github.com/repos/huggingface/datasets/issues/3270 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3270/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3270/comments | https://api.github.com/repos/huggingface/datasets/issues/3270/events | https://github.com/huggingface/datasets/pull/3270 | 1,053,465,662 | PR_kwDODunzps4uhcxm | 3,270 | Add os.listdir for streaming | {
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https://api.github.com/repos/huggingface/datasets/issues/3267 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3267/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3267/comments | https://api.github.com/repos/huggingface/datasets/issues/3267/events | https://github.com/huggingface/datasets/pull/3267 | 1,052,750,084 | PR_kwDODunzps4ufQzB | 3,267 | Replacing .format() and % by f-strings | {
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"Hi ! It looks like most of your changes are just `black` changes. All those changes are not necessary. In particular if you want to use `black`, please use the `make style` command instead. It runs `black` with additional parameters and you shouldn't end up with that many changes\r\n\r\nFeel free to open a new PR that doesn't include all the unnecessary `black` changes that you have on your branch :)",
"> Hi ! It looks like most of your changes are just `black` changes. All those changes are not necessary. In particular if you want to use `black`, please use the `make style` command instead. It runs `black` with additional parameters and you shouldn't end up with that many changes\r\n> \r\n> Feel free to open a new PR that doesn't include all the unnecessary `black` changes that you have on your branch :)\r\n\r\nThank you for your answer :) , I will open a new PR with the correct changes.",
"Hi @lhoestq, I submitted 3 commits in a new PR (#3277) where I did not apply black.\r\n\r\nI can apply the ```make style``` command if asked.",
"Cool thanks ! Yes feel free to make sure you have `black==21.4b0` and run `make style`"
] | 1,636,830,722,000 | 1,637,096,426,000 | 1,637,074,543,000 | CONTRIBUTOR | null | **Fix #3257**
Replaced _.format()_ and _%_ by f-strings in the following modules :
- [x] **tests**
- [x] **metrics**
- [x] **benchmarks**
- [x] **utils**
- [x] **templates**
Will follow in the next PR the modules left :
- [ ] **src**
Module **datasets** will not be edited as asked by @mariosasko
PS : black and isort applied to files
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https://api.github.com/repos/huggingface/datasets/issues/3266 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3266/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3266/comments | https://api.github.com/repos/huggingface/datasets/issues/3266/events | https://github.com/huggingface/datasets/pull/3266 | 1,052,700,155 | PR_kwDODunzps4ufH94 | 3,266 | Fix URLs for WikiAuto Manual, jeopardy and definite_pronoun_resolution | {
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"There seems to be problems with datasets metadata, of which I dont have access to. I think one of the datasets is from reddit. Can anyone help?",
"Hello @LashaO , I think the errors were caused by `_DATA_FILES` in `definite_pronoun_resolution.py`. Here are details of the test error.\r\n```\r\nself = BuilderConfig(name='plain_text', version=1.0.0, data_dir=None, data_files={'train': 'train.c.txt', 'test': 'test.c.txt'}, description='Plain text import of the Definite Pronoun Resolution Dataset.')\r\n\r\n def __post_init__(self):\r\n # The config name is used to name the cache directory.\r\n invalid_windows_characters = r\"<>:/\\|?*\"\r\n for invalid_char in invalid_windows_characters:\r\n if invalid_char in self.name:\r\n raise InvalidConfigName(\r\n f\"Bad characters from black list '{invalid_windows_characters}' found in '{self.name}'. \"\r\n f\"They could create issues when creating a directory for this config on Windows filesystem.\"\r\n )\r\n if self.data_files is not None and not isinstance(self.data_files, DataFilesDict):\r\n> raise ValueError(f\"Expected a DataFilesDict in data_files but got {self.data_files}\")\r\nE ValueError: Expected a DataFilesDict in data_files but got {'train': 'train.c.txt', 'test': 'test.c.txt'}\r\n```",
"Hi ! Thanks for the fixes :)\r\n\r\nInstead of uploading the `definite_pronoun_resolution` data files in this PR, maybe we can just update the URL ?\r\nThe old url was http://www.hlt.utdallas.edu/~vince/data/emnlp12/train.c.txt, but now it's https://www.hlt.utdallas.edu/~vince/data/emnlp12/train.c.txt (https instead of http)",
"Actually the bad certificate creates an issue with the download\r\n```python\r\nimport datasets \r\ndatasets.DownloadManager().download(\"https://www.hlt.utdallas.edu/~vince/data/emnlp12/train.c.txt\")\r\n# raises: ConnectionError: Couldn't reach https://www.hlt.utdallas.edu/~vince/data/emnlp12/train.c.txt\r\n```\r\n\r\nLet me see if I can fix that",
"I uploaded them to these URLs, feel free to use them instead of having the text files here in the PR :)\r\nhttps://s3.amazonaws.com/datasets.huggingface.co/definite_pronoun_resolution/train.c.txt\r\nhttps://s3.amazonaws.com/datasets.huggingface.co/definite_pronoun_resolution/test.c.txt",
"Thank you for the tips! Having a busy week so anyone willing to commit the suggestions is welcome. Else, I will try to get back to this in a while.",
"@LashaO Thanks for working on this. Yes, I'll take over as we already have a request to fix the URL of the Jeopardy! dataset in a separate issue.",
"~~Still have to fix the error in the dummy data test of the WikiAuto dataset (so please don't merge).~~ Done! Ready for merging.",
"Thank you, Mario!",
"The CI failure is only related to missing tags in the dataset cards, merging :)"
] | 1,636,815,694,000 | 1,638,789,391,000 | 1,638,789,391,000 | CONTRIBUTOR | null | [#3264](https://github.com/huggingface/datasets/issues/3264) | {
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"Using `dataset = load_dataset(\"kilt_tasks\", \"wow\", ignore_verifications=True)` may fix it, but I do not think it is a elegant solution.",
"Hi @slyviacassell, thanks for reporting.\r\n\r\nYes, there is an issue with the checksum verification. I'm fixing it.\r\n\r\nAnd as you pointed out, in the meantime, you can circumvent the problem by passing `ignore_verifications=True`. "
] | 1,636,805,057,000 | 1,637,061,833,000 | 1,637,061,718,000 | NONE | null | ## Describe the bug
Checksum failed when downloads kilt_tasks_wow. See error output for details.
## Steps to reproduce the bug
```python
import datasets
datasets.load_datasets('kilt_tasks','wow')
```
## Expected results
Download successful
## Actual results
```
Downloading and preparing dataset kilt_tasks/wow (download: 72.07 MiB, generated: 61.82 MiB, post-processed: Unknown size, total: 133.89 MiB) to /root/.cache/huggingface/datasets/kilt_tasks/wow/1.0.0/57dc8b2431e76637e0c6ef79689ca4af61ed3a330e2e0cd62c8971465a35db3a...
100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 3/3 [00:00<00:00, 5121.25it/s]
100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 3/3 [00:00<00:00, 1527.42it/s]
Traceback (most recent call last):
File "kilt_wow.py", line 30, in <module>
main()
File "kilt_wow.py", line 27, in main
train, dev, test = dataset.generate_k_shot_data(k=32, seed=seed, path="../data/")
File "/workspace/projects/CrossFit/tasks/fewshot_gym_dataset.py", line 79, in generate_k_shot_data
dataset = self.load_dataset()
File "kilt_wow.py", line 21, in load_dataset
return datasets.load_dataset('kilt_tasks','wow')
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 679, in _download_and_prepare
verify_checksums(
File "/opt/conda/lib/python3.8/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:
['http://dl.fbaipublicfiles.com/KILT/wow-train-kilt.jsonl', 'http://dl.fbaipublicfiles.com/KILT/wow-dev-kilt.jsonl']
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-4.15.0-161-generic-x86_64-with-glibc2.10
- Python version: 3.8.3
- PyArrow version: 4.0.1
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- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). | {
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https://api.github.com/repos/huggingface/datasets/issues/3262 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3262/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3262/comments | https://api.github.com/repos/huggingface/datasets/issues/3262/events | https://github.com/huggingface/datasets/pull/3262 | 1,052,455,082 | PR_kwDODunzps4uej4t | 3,262 | asserts replaced with exception for image classification task, csv, json | {
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https://api.github.com/repos/huggingface/datasets/issues/3260 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3260/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3260/comments | https://api.github.com/repos/huggingface/datasets/issues/3260/events | https://github.com/huggingface/datasets/pull/3260 | 1,052,247,373 | PR_kwDODunzps4ueCIU | 3,260 | Fix ConnectionError in Scielo dataset | {
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"The CI error is unrelated to the change."
] | 1,636,740,157,000 | 1,637,086,697,000 | 1,637,085,322,000 | CONTRIBUTOR | null | This PR:
* allows 403 status code in HEAD requests to S3 buckets to fix the connection error in the Scielo dataset (instead of `url`, uses `response.url` to check the URL of the final endpoint)
* makes the Scielo dataset streamable
Fixes #3255. | {
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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!"
] | 1,636,737,418,000 | 1,637,255,973,000 | 1,637,255,973,000 | CONTRIBUTOR | null | 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/3257 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3257/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3257/comments | https://api.github.com/repos/huggingface/datasets/issues/3257/events | https://github.com/huggingface/datasets/issues/3257 | 1,052,118,365 | I_kwDODunzps4-tg1d | 3,257 | Use f-strings for string formatting | {
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"Hi, I would be glad to help with this. Is there anyone else working on it?",
"Hi, I would be glad to work on this too.",
"#self-assign",
"Hi @Carlosbogo,\r\n\r\nwould you be interested in replacing the `.format` and `%` syntax with f-strings in the modules in the `datasets` directory since @Mehdi2402 has opened a PR that does that for all the other directories?",
"Oh I see. I will be glad to help with the `datasets` directory then."
] | 1,636,732,935,000 | 1,637,165,918,000 | 1,637,165,918,000 | CONTRIBUTOR | null | f-strings offer better readability/performance than `str.format` and `%`, so we should use them in all places in our codebase unless there is good reason to keep the older syntax.
> **NOTE FOR CONTRIBUTORS**: To avoid large PRs and possible merge conflicts, do 1-3 modules per PR. Also, feel free to ignore the files located under `datasets/*`. | {
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https://api.github.com/repos/huggingface/datasets/issues/3256 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3256/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3256/comments | https://api.github.com/repos/huggingface/datasets/issues/3256/events | https://github.com/huggingface/datasets/pull/3256 | 1,052,000,613 | PR_kwDODunzps4udTqg | 3,256 | asserts replaced by exception for text classification task with test. | {
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"Haha it looks like you got the chance of being reviewed twice at the same time and got the same suggestion twice x)\r\nAnyway it's all good now so we can merge !",
"Thanks for the feedback. "
] | 1,636,725,936,000 | 1,636,729,773,000 | 1,636,729,172,000 | CONTRIBUTOR | null | I have replaced only a single assert in text_classification.py along with a unit test to verify an exception is raised based on https://github.com/huggingface/datasets/issues/3171 .
I would like to first understand the code contribution workflow. So keeping the change to a single file rather than making too many changes. Once this gets approved, I will look into the rest.
Thanks. | {
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https://api.github.com/repos/huggingface/datasets/issues/3255 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3255/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3255/comments | https://api.github.com/repos/huggingface/datasets/issues/3255/events | https://github.com/huggingface/datasets/issues/3255 | 1,051,783,129 | I_kwDODunzps4-sO_Z | 3,255 | SciELO dataset ConnectionError | {
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] | null | [] | 1,636,711,034,000 | 1,637,085,322,000 | 1,637,085,322,000 | NONE | null | ## Describe the bug
I get `ConnectionError` when I am trying to load the SciELO dataset.
When I try the URL with `requests` I get:
```
>>> requests.head("https://ndownloader.figstatic.com/files/14019287")
<Response [302]>
```
And as far as I understand redirections in `datasets` are not supported for downloads.
https://github.com/huggingface/datasets/blob/807341d0db0728073ab605c812c67f927d148f38/datasets/scielo/scielo.py#L45
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("scielo", "en-es")
```
## Expected results
Download SciELO dataset and load Dataset object
## Actual results
```
Downloading and preparing dataset scielo/en-es (download: 21.90 MiB, generated: 68.45 MiB, post-processed: Unknown size, total: 90.35 MiB) to /Users/test/.cache/huggingface/datasets/scielo/en-es/1.0.0/7e05d55a20257efeb9925ff5de65bd4884fc6ddb6d765f1ea3e8860449d90e0e...
Traceback (most recent call last):
File "scielo.py", line 3, in <module>
dataset = load_dataset("scielo", "en-es")
File "../lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "../lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "../lib/python3.8/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/Users/test/.cache/huggingface/modules/datasets_modules/datasets/scielo/7e05d55a20257efeb9925ff5de65bd4884fc6ddb6d765f1ea3e8860449d90e0e/scielo.py", line 77, in _split_generators
data_dir = dl_manager.download_and_extract(_URLS[self.config.name])
File "../lib/python3.8/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "../lib/python3.8/site-packages/datasets/utils/download_manager.py", line 196, in download
downloaded_path_or_paths = map_nested(
File "../lib/python3.8/site-packages/datasets/utils/py_utils.py", line 206, in map_nested
return function(data_struct)
File "../lib/python3.8/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "../lib/python3.8/site-packages/datasets/utils/file_utils.py", line 295, in cached_path
output_path = get_from_cache(
File "../lib/python3.8/site-packages/datasets/utils/file_utils.py", line 594, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://ndownloader.figstatic.com/files/14019287
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.12
- PyArrow version: 6.0.0
| {
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https://api.github.com/repos/huggingface/datasets/issues/3254 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3254/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3254/comments | https://api.github.com/repos/huggingface/datasets/issues/3254/events | https://github.com/huggingface/datasets/pull/3254 | 1,051,351,172 | PR_kwDODunzps4ubPwR | 3,254 | Update xcopa dataset (fix checksum issues + add translated data) | {
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"The CI failures are unrelated to the changes (missing fields in the readme and the CER metric error fixed in #3252)."
] | 1,636,663,893,000 | 1,636,713,058,000 | 1,636,713,057,000 | CONTRIBUTOR | null | This PR updates the checksums (as reported [here](https://discuss.huggingface.co/t/how-to-load-dataset-locally/11601/2)) of the `xcopa` dataset. Additionally, it adds new configs that hold the translated data of the original set of configs. This data was not available at the time of adding this dataset to the lib. | {
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https://api.github.com/repos/huggingface/datasets/issues/3252 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3252/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3252/comments | https://api.github.com/repos/huggingface/datasets/issues/3252/events | https://github.com/huggingface/datasets/pull/3252 | 1,051,124,749 | PR_kwDODunzps4uagoy | 3,252 | Fix failing CER metric test in CI after update | {
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} | [] | closed | false | null | [] | null | [] | 1,636,646,236,000 | 1,636,726,004,000 | 1,636,726,003,000 | CONTRIBUTOR | null | Fixes the [failing CER metric test](https://app.circleci.com/pipelines/github/huggingface/datasets/8644/workflows/79816553-fa2f-4756-b022-d5937f00bf7b/jobs/53298) in CI by adding support for `jiwer==2.3.0`, which was released yesterday. Also, I verified that all the tests in `metrics/cer/test_cer.py` pass after the change, so the results should be the same irrespective of the `jiwer` version. | {
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https://api.github.com/repos/huggingface/datasets/issues/3249 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3249/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3249/comments | https://api.github.com/repos/huggingface/datasets/issues/3249/events | https://github.com/huggingface/datasets/pull/3249 | 1,050,193,138 | PR_kwDODunzps4uXeea | 3,249 | Fix streaming for id_newspapers_2018 | {
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} | [] | closed | false | null | [] | null | [] | 1,636,570,530,000 | 1,636,725,692,000 | 1,636,725,691,000 | MEMBER | null | To be compatible with streaming, this dataset must use `dl_manager.iter_archive` since the data are in a .tgz file | {
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https://api.github.com/repos/huggingface/datasets/issues/3248 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3248/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3248/comments | https://api.github.com/repos/huggingface/datasets/issues/3248/events | https://github.com/huggingface/datasets/pull/3248 | 1,050,171,082 | PR_kwDODunzps4uXZzU | 3,248 | Stream from Google Drive and other hosts | {
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"I just tried some datasets and noticed that `spider` is not working for some reason (the compression type is not recognized), resulting in FileNotFoundError. I can take a look tomorrow",
"I'm fixing the remaining files based on TAR archives",
"THANKS A LOT"
] | 1,636,569,152,000 | 1,638,288,223,000 | 1,636,737,491,000 | MEMBER | null | Streaming from Google Drive is a bit more challenging than the other host we've been supporting:
- the download URL must be updated to add the confirm token obtained by HEAD request
- it requires to use cookies to keep the connection alive
- the URL doesn't tell any information about whether the file is compressed or not
Therefore I did two things:
- I added a step for URL and headers/cookies preparation in the StreamingDownloadManager
- I added automatic compression type inference by reading the [magic number](https://en.wikipedia.org/wiki/List_of_file_signatures)
This allows to do do fancy things like
```python
from datasets.utils.streaming_download_manager import StreamingDownloadManager, xopen, xjoin, xglob
# zip file containing a train.tsv file
url = "https://drive.google.com/uc?export=download&id=1k92sUfpHxKq8PXWRr7Y5aNHXwOCNUmqh"
extracted = StreamingDownloadManager().download_and_extract(url)
for inner_file in xglob(xjoin(extracted, "*.tsv")):
with xopen(inner_file) as f:
# streaming starts here
for line in f:
print(line)
```
This should make around 80 datasets streamable. It concerns those hosted on Google Drive but also any dataset for which the URL doesn't give any information about compression. Here is the full list:
```
amazon_polarity, ami, arabic_billion_words, ascent_kb, asset, big_patent, billsum, capes, cmrc2018, cnn_dailymail,
code_x_glue_cc_code_completion_token, code_x_glue_cc_code_refinement, code_x_glue_cc_code_to_code_trans,
code_x_glue_tt_text_to_text, conll2002, craigslist_bargains, dbpedia_14, docred, ehealth_kd, emo, euronews, germeval_14,
gigaword, grail_qa, great_code, has_part, head_qa, health_fact, hope_edi, id_newspapers_2018,
igbo_english_machine_translation, irc_disentangle, jfleg, jnlpba, journalists_questions, kor_ner, linnaeus, med_hop, mrqa,
mt_eng_vietnamese, multi_news, norwegian_ner, offcombr, offenseval_dravidian, para_pat, peoples_daily_ner, pn_summary,
poleval2019_mt, pubmed_qa, qangaroo, reddit_tifu, refresd, ro_sts_parallel, russian_super_glue, samsum, sberquad, scielo,
search_qa, species_800, spider, squad_adversarial, tamilmixsentiment, tashkeela, ted_talks_iwslt, trec, turk, turkish_ner,
twi_text_c3, universal_morphologies, web_of_science, weibo_ner, wiki_bio, wiki_hop, wiki_lingua, wiki_summary, wili_2018,
wisesight1000, wnut_17, yahoo_answers_topics, yelp_review_full, yoruba_text_c3
```
Some of them may not work if the host doesn't support HTTP range requests for example
Fix https://github.com/huggingface/datasets/issues/2742
Fix https://github.com/huggingface/datasets/issues/3188 | {
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https://api.github.com/repos/huggingface/datasets/issues/3246 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3246/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3246/comments | https://api.github.com/repos/huggingface/datasets/issues/3246/events | https://github.com/huggingface/datasets/pull/3246 | 1,049,662,746 | PR_kwDODunzps4uVvaW | 3,246 | [tiny] fix typo in stream docs | {
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https://api.github.com/repos/huggingface/datasets/issues/3245 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3245/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3245/comments | https://api.github.com/repos/huggingface/datasets/issues/3245/events | https://github.com/huggingface/datasets/pull/3245 | 1,048,726,062 | PR_kwDODunzps4uSqqq | 3,245 | Fix load_from_disk temporary directory | {
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} | [] | closed | false | null | [] | null | [] | 1,636,470,915,000 | 1,636,471,852,000 | 1,636,471,851,000 | MEMBER | null | `load_from_disk` uses `tempfile.TemporaryDirectory()` instead of our `get_temporary_cache_files_directory()` function. This can cause the temporary directory to be deleted before the dataset object is garbage collected.
In practice, it prevents anyone from using methods like `shuffle` on a dataset loaded this way, because it can't write the shuffled indices in a directory that doesn't exist anymore.
In this PR I switch to using `get_temporary_cache_files_directory()` and I update the tests.
cc @mariosasko since you worked on `get_temporary_cache_files_directory()` | {
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https://api.github.com/repos/huggingface/datasets/issues/3244 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3244/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3244/comments | https://api.github.com/repos/huggingface/datasets/issues/3244/events | https://github.com/huggingface/datasets/pull/3244 | 1,048,675,741 | PR_kwDODunzps4uSgG5 | 3,244 | Fix filter method for batched=True | {
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https://api.github.com/repos/huggingface/datasets/issues/3243 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3243/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3243/comments | https://api.github.com/repos/huggingface/datasets/issues/3243/events | https://github.com/huggingface/datasets/pull/3243 | 1,048,630,754 | PR_kwDODunzps4uSWtB | 3,243 | Remove redundant isort module placement | {
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https://api.github.com/repos/huggingface/datasets/issues/3241 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3241/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3241/comments | https://api.github.com/repos/huggingface/datasets/issues/3241/events | https://github.com/huggingface/datasets/pull/3241 | 1,048,461,852 | PR_kwDODunzps4uRzHa | 3,241 | Swap descriptions of v1 and raw-v1 configs of WikiText dataset and fix metadata | {
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https://api.github.com/repos/huggingface/datasets/issues/3238 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3238/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3238/comments | https://api.github.com/repos/huggingface/datasets/issues/3238/events | https://github.com/huggingface/datasets/issues/3238 | 1,048,226,086 | I_kwDODunzps4-eqkm | 3,238 | Reuters21578 Couldn't reach | {
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"Hi ! The URL works fine on my side today, could you try again ?",
"thank you @lhoestq \r\nit works"
] | 1,636,438,136,000 | 1,636,588,977,000 | 1,636,588,977,000 | NONE | null | ``## Adding a Dataset
- **Name:** *Reuters21578*
- **Description:** *ConnectionError: Couldn't reach https://kdd.ics.uci.edu/databases/reuters21578/reuters21578.tar.gz*
- **Data:** *https://huggingface.co/datasets/reuters21578*
`from datasets import load_dataset`
`dataset = load_dataset("reuters21578", 'ModLewis')`
ConnectionError: Couldn't reach https://kdd.ics.uci.edu/databases/reuters21578/reuters21578.tar.gz
And I try to request the link as follow:
`import requests`
`requests.head('https://kdd.ics.uci.edu/databases/reuters21578/reuters21578.tar.gz')`
SSLError: HTTPSConnectionPool(host='kdd.ics.uci.edu', port=443): Max retries exceeded with url: /databases/reuters21578/reuters21578.tar.gz (Caused by SSLError(SSLError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:852)'),))
This problem likes #575
What should I do ?
| {
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https://api.github.com/repos/huggingface/datasets/issues/3237 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3237/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3237/comments | https://api.github.com/repos/huggingface/datasets/issues/3237/events | https://github.com/huggingface/datasets/issues/3237 | 1,048,165,525 | I_kwDODunzps4-ebyV | 3,237 | wikitext description wrong | {
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"Hi @hongyuanmei, thanks for reporting.\r\n\r\nI'm fixing it."
] | 1,636,430,812,000 | 1,636,465,768,000 | 1,636,465,768,000 | NONE | null | ## Describe the bug
Descriptions of the wikitext datasests are wrong.
## Steps to reproduce the bug
Please see: https://github.com/huggingface/datasets/blob/f6dcafce996f39b6a4bbe3a9833287346f4a4b68/datasets/wikitext/wikitext.py#L50
## Expected results
The descriptions for raw-v1 and v1 should be switched. | {
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"Hi @eladsegal, thanks for reporting.\r\n\r\nI am sorry, but I can't reproduce the bug:\r\n```\r\nIn [1]: from datasets import load_dataset\r\n\r\nIn [2]: ds = load_dataset(\"qasper\")\r\nDownloading: 5.11kB [00:00, ?B/s]\r\nDownloading and preparing dataset qasper/qasper (download: 9.88 MiB, generated: 35.11 MiB, post-processed: Unknown size, total: 44.99 MiB) to .cache\\qasper\\qasper\\0.1.0\\b99154d2a15aa54bfc669f82b2eda715a2e342e81023d39613b0e2920fdb3ad8...\r\nDataset qasper downloaded and prepared to .cache\\qasper\\qasper\\0.1.0\\b99154d2a15aa54bfc669f82b2eda715a2e342e81023d39613b0e2920fdb3ad8. Subsequent calls will reuse this data.\r\n100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 2/2 [00:00<?, ?it/s]\r\n\r\nIn [3]: ds\r\nOut[3]:\r\nDatasetDict({\r\n train: Dataset({\r\n features: ['id', 'title', 'abstract', 'full_text', 'qas'],\r\n num_rows: 888\r\n })\r\n validation: Dataset({\r\n features: ['id', 'title', 'abstract', 'full_text', 'qas'],\r\n num_rows: 281\r\n })\r\n})\r\n``` \r\n\r\nThis makes me suspect that the origin of the problem might be the cache: I didn't have this dataset in my cache, although I guess you already had it, before the code change introduced by #3110.\r\n\r\n@lhoestq might it be possible that the code change introduced by #3110 makes \"inaccessible\" all previously cached TAR-based datasets?\r\n- Before the caching system downloaded and extracted the tar dataset\r\n- Now it only downloads the tar dataset (no extraction is done)",
"I can't reproduce either in my environment (macos, python 3.7).\r\n\r\nIn your case it generates zero examples. This can only happen if the extraction of the TAR archive doesn't output the right filenames. Indeed if the `qasper` script can't find the right file to load, it's currently ignored and it returns zero examples. This case was not even considered when #3110 was developed since we considered the file names to be deterministic - and not depend on your environment.\r\n\r\nTherefore here is my hypothesis:\r\n- either the cache is corrupted somehow with an empty TAR archive\r\n- OR I suspect that the issue comes from python 3.8\r\n",
"I just tried again on python 3.8 and I was able to reproduce the issue. Let me work on a fix",
"Ok I found the issue. It's not related to python 3.8 in itself though. This issue happens because your local installation of `datasets` is outdated compared to the changes to datasets in #3110\r\n\r\nTo fix this you just have to pull the latest changes from `master` :)\r\n\r\nLet me know if that helps !\r\n\r\n--------------\r\n\r\nHere are more details about my investigation:\r\n\r\nIt's possible to reproduce this issue if you use `datasets<=1.15.1` or before b6469baa22c174b3906c631802a7016fedea6780 and if you load the dataset after revision b6469baa22c174b3906c631802a7016fedea6780. This is because `dl_manager.iter_archive` had issues at that time (and it was not used anywhere anyway).\r\n\r\nIn particular it was returning the absolute path to extracted files instead of the relative path of the file inside the archive. This was an issue because `dl_manager.iter_archive` isn't supposed to extract the TAR archive. Instead, it iterates over all the files inside the archive, without creating a directory with the extracted content.\r\n\r\nTherefore if you want to use the datasets on `master`, make sure that you have an up-to-date local installation of `datasets` as well, or you may face incompatibilities like this.",
"Thanks!\r\nBut what about code that is already using older version of datasets? \r\nThe reason I encountered this issue was that suddenly one of my repos with version 1.12.1 started getting 0 examples.\r\nI handled it by adding `revision` to `load_dataset`, but I guess it would still be an issue for other users who doesn't know this.",
"Hi, in 1.12.1 it uses the dataset scripts from that time, not the one on master.\r\n\r\nIt only uses the datasets from master if you installed `datasets` from source, or if the dataset isn't available in your local version (in this case it shows a warning and it loads from master).\r\n",
"OK, I understand the issue a bit better now.\r\nI see I wasn't on 1.12.1, but on 1.12.1.dev0 and since it is a dev version it uses master.\r\nSo users that use an old dev version must specify revision or else they'll encounter this problem.\r\n\r\nBTW, when I opened the issue I installed the latest master version with\r\n```\r\npip install git+git://github.com/huggingface/datasets@master#egg=datasets\r\n```\r\nand also used `download_mode=\"force_redownload\"`, and it still returned 0 examples.\r\nNow I deleted all of the cache and ran the code again, and it worked.\r\nI'm not sure what exactly happened here, but looks like it was due to a mix of an unofficial version and its cache.\r\n\r\nThanks again!"
] | 1,636,414,186,000 | 1,636,476,365,000 | 1,636,476,347,000 | CONTRIBUTOR | null | ## Describe the bug
Loading of datasets changed in https://github.com/huggingface/datasets/pull/3110 returns no examples:
```python
DatasetDict({
train: Dataset({
features: ['id', 'title', 'abstract', 'full_text', 'qas'],
num_rows: 0
})
validation: Dataset({
features: ['id', 'title', 'abstract', 'full_text', 'qas'],
num_rows: 0
})
})
```
## Steps to reproduce the bug
Load any of the datasets that were changed in https://github.com/huggingface/datasets/pull/3110:
```python
from datasets import load_dataset
load_dataset("qasper")
# The problem only started with the commit of #3110
load_dataset("qasper", revision="b6469baa22c174b3906c631802a7016fedea6780")
```
## Expected results
```python
DatasetDict({
train: Dataset({
features: ['id', 'title', 'abstract', 'full_text', 'qas'],
num_rows: 888
})
validation: Dataset({
features: ['id', 'title', 'abstract', 'full_text', 'qas'],
num_rows: 281
})
})
```
Which can be received when specifying revision of the commit before https://github.com/huggingface/datasets/pull/3110:
```python
from datasets import load_dataset
load_dataset("qasper", revision="acfe2abda1ca79f0ce5c1896aa83b4b78af76b7d")
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.2.dev0 (master)
- Python version: 3.8.10
- PyArrow version: 3.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3235 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3235/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3235/comments | https://api.github.com/repos/huggingface/datasets/issues/3235/events | https://github.com/huggingface/datasets/pull/3235 | 1,047,808,263 | PR_kwDODunzps4uPr9Z | 3,235 | Addd options to use updated bleurt checkpoints | {
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Updated checkpoints are described in https://github.com/google-research/bleurt/blob/master/checkpoints.md#the-recommended-checkpoint-bleurt-20
This change won't affect the default behavior of metrics/bleurt. It only adds option to load newer checkpoints as
`datasets.load_metric('bleurt', 'bleurt-20')`
`bluert-20` generates scores roughly between 0 and 1, which wasn't the case for the previous checkpoints. | {
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"That's good to have a way to disable this easily :)\r\nI just find it a bit unfortunate that users would have to experience the error once and then do `DISABLE_PYARROW_TYPES_OPTIMIZATION=1`. Do you know if there's a way to simply fallback on disabling it automatically when it fails ?",
"@lhoestq Actually, I agree a fallback makes more sense. The current approach is not very practical indeed and would require a mention in the docs.\r\n",
"Replaced the env variable with a fallback!",
"Hmm if the fallback automatically happens without the user knowing it, then I don't think we really need to mention it. But if you really wanted to, I think the [Improve performance](https://huggingface.co/docs/datasets/cache.html#improve-performance) section would be a great place for it! ",
"Yea I think this could just end up in a note that says that `datasets` automatically picks the most optimized integer precision for your tokenized text data to save you disk space. Maybe later if we have a page on text processing we can add this note, but for now I agree it doesn't fit well into the doc.\r\n\r\nIn particular in the \"Improve performance\" section we mention what users can do to speed up their computations, while this behavior is just some internal feature that users don't have control over anyway."
] | 1,636,387,827,000 | 1,636,545,869,000 | 1,636,545,868,000 | CONTRIBUTOR | null | Adds a new variable, `DISABLE_PYARROW_TYPES_OPTIMIZATION`, to `config.py` for easier control of the Arrow type optimization.
Fix #2206 | {
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"Hi ! On my side the URL is working fine, could you try again ?",
"> Hi ! On my side the URL is working fine, could you try again ?\r\n\r\nI try it again and cannot download the file (might because of my location). Could you please provide another download link(such as google drive)? :>",
"I don't know other download links - this is the one provided by the authors of the dataset. Maybe you can try downloading from another location ? There are several solutions: a VPN, a remote VM or Google Colab for example.",
"> I don't know other download links - this is the one provided by the authors of the dataset. Maybe you can try downloading from another location ? There are several solutions: a VPN, a remote VM or Google Colab for example.\r\n\r\n:> ok. Thanks for your reply."
] | 1,636,372,734,000 | 1,636,470,436,000 | 1,636,470,436,000 | NONE | null | ## Describe the bug
The download Link of the Xsum dataset provided in the repository is [Link](http://bollin.inf.ed.ac.uk/public/direct/XSUM-EMNLP18-Summary-Data-Original.tar.gz). It seems not able to download.
## Steps to reproduce the bug
```python
load_dataset('xsum')
```
## Actual results
``` python
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://bollin.inf.ed.ac.uk/public/direct/XSUM-EMNLP18-Summary-Data-Original.tar.gz
```
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Therefore, the fixture `hf_token` will be called only once (and from the same worker).
Related to: #3200.
Fix #3219. | {
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"I also added the missing `pretty_name` tag in the dataset card to fix the CI"
] | 1,636,358,764,000 | 1,636,454,918,000 | 1,636,454,458,000 | CONTRIBUTOR | null | Even though it is possible to manually get the tagset list with
```python
dset.features[field_name].feature.names
```
I think it is useful to have an overview of the used tagset on the dataset card. This is particularly useful in light of the **dataset viewer**: the tags are encoded, so it is not immediately obvious what they are for a given sample. Adding a label-int mapping should make it easier for visitors to get a grasp of what they mean.
From user-experience perspective, I would urge the full tagsets to always be available in the README's but I understand that that would take a lot of work, probably. Perhaps it can be automated?
closes #3189 | {
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https://api.github.com/repos/huggingface/datasets/issues/3229 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3229/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3229/comments | https://api.github.com/repos/huggingface/datasets/issues/3229/events | https://github.com/huggingface/datasets/pull/3229 | 1,046,706,425 | PR_kwDODunzps4uMKsx | 3,229 | Fix URL in CITATION file | {
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} | [] | closed | false | null | [] | null | [] | 1,636,279,475,000 | 1,636,279,486,000 | 1,636,279,485,000 | MEMBER | null | Currently the BibTeX citation parsed from the CITATION file has wrong URL (it shows the repo URL instead of the proceedings paper URL):
```
@inproceedings{Lhoest_Datasets_A_Community_2021,
author = {Lhoest, Quentin and Villanova del Moral, Albert and von Platen, Patrick and Wolf, Thomas and Šaőko, Mario and Jernite, Yacine and Thakur, Abhishek and Tunstall, Lewis and Patil, Suraj and Drame, Mariama and Chaumond, Julien and Plu, Julien and Davison, Joe and Brandeis, Simon and Sanh, Victor and Le Scao, Teven and Canwen Xu, Kevin and Patry, Nicolas and Liu, Steven and McMillan-Major, Angelina and Schmid, Philipp and Gugger, Sylvain and Raw, Nathan and Lesage, Sylvain and Lozhkov, Anton and Carrigan, Matthew and Matussière, Théo and von Werra, Leandro and Debut, Lysandre and Bekman, Stas and Delangue, Clément},
booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
month = {11},
pages = {175--184},
publisher = {Association for Computational Linguistics},
title = {{Datasets: A Community Library for Natural Language Processing}},
url = {https://github.com/huggingface/datasets},
year = {2021}
}
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3228 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3228/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3228/comments | https://api.github.com/repos/huggingface/datasets/issues/3228/events | https://github.com/huggingface/datasets/pull/3228 | 1,046,702,143 | PR_kwDODunzps4uMJ58 | 3,228 | Add CITATION file | {
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https://api.github.com/repos/huggingface/datasets/issues/3227 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3227/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3227/comments | https://api.github.com/repos/huggingface/datasets/issues/3227/events | https://github.com/huggingface/datasets/issues/3227 | 1,046,667,845 | I_kwDODunzps4-YuJF | 3,227 | Error in `Json(datasets.ArrowBasedBuilder)` class | {
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"I have additionally identified the source of the error, being that [this condition](https://github.com/huggingface/datasets/blob/fc46bba66ba4f432cc10501c16a677112e13984c/src/datasets/packaged_modules/json/json.py#L124-L126) in the file\r\n`python3.8/site-packages/datasets/packaged_modules/json/json.py` is not being entered correctly:\r\n```python\r\n if (\r\n isinstance(e, pa.ArrowInvalid)\r\n and \"straddling\" not in str(e)\r\n or block_size > len(batch)\r\n ):\r\n```\r\n\r\nFrom what I can tell, in my case the block_size simply needs to be increased, but the error message does not contain \"straddling\" so the condition does trigger correctly and we fail to reach [the line to increase block_size](https://github.com/huggingface/datasets/blob/fc46bba66ba4f432cc10501c16a677112e13984c/src/datasets/packaged_modules/json/json.py#L135).\r\n\r\nChanging the condition above to simply\r\n```python\r\n if (\r\n block_size > len(batch)\r\n ):\r\n```\r\n\r\nFixes the error for me. I'm happy to create a PR containing this fix if the developers deem the other conditions unnecessary.",
"Hi ! I think the issue comes from the fact that your JSON file is not a valid JSON Lines file.\r\nEach example should be on one single line.\r\n\r\nCan you try fixing the format to have one line per example and try again ?",
":open_mouth: you're right, that did it! I just put everything on a single line (my file only has a single example) and that fixed the error. Thank you so much!"
] | 1,636,264,232,000 | 1,636,484,955,000 | 1,636,484,955,000 | NONE | null | ## Describe the bug
When a json file contains a `text` field that is larger than the block_size, the JSON dataset builder fails.
## Steps to reproduce the bug
Create a folder that contains the following:
```
.
βββ testdata
βΒ Β βββ mydata.json
βββ test.py
```
Please download [this file](https://github.com/huggingface/datasets/files/7491797/mydata.txt) as `mydata.json`. (The error does not occur in JSON files with shorter text, but it is reproducible when the text is long as in the file I provide)
:exclamation: :exclamation: GitHub doesn't allow me to upload JSON so this file is a TXT, and you should rename it to `.json`!
`test.py` simply contains:
```python
from datasets import load_dataset
my_dataset = load_dataset("testdata")
```
To reproduce the error, simply run
```
python test.py
```
## Expected results
The data should load correctly without error.
## Actual results
The dataset builder fails with:
```
Using custom data configuration testdata-d490389b8ab4fd82
Downloading and preparing dataset json/testdata to /home/junshern.chan/.cache/huggingface/datasets/json/testdata-d490389b8ab4fd82/0.0.0/3333a8af0db9764dfcff43a42ff26228f0f2e267f0d8a0a294452d188beadb34...
100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1/1 [00:00<00:00, 2264.74it/s]
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1/1 [00:00<00:00, 447.01it/s]
Failed to read file '/home/junshern.chan/hf-json-bug/testdata/mydata.json' with error <class 'pyarrow.lib.ArrowInvalid'>: JSON parse error: Missing a name for object member. in row 0
Traceback (most recent call last):
File "test.py", line 28, in <module>
my_dataset = load_dataset("testdata")
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/datasets/builder.py", line 697, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/datasets/builder.py", line 1156, in _prepare_split
for key, table in utils.tqdm(
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/tqdm/std.py", line 1168, in __iter__
for obj in iterable:
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/datasets/packaged_modules/json/json.py", line 146, in _generate_tables
raise ValueError(
ValueError: Not able to read records in the JSON file at /home/junshern.chan/hf-json-bug/testdata/mydata.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['text']. Select the correct one and provide it as `field='XXX'` to the dataset loading method.
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-5.8.0-63-generic-x86_64-with-glibc2.17
- Python version: 3.8.12
- PyArrow version: 6.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3226 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3226/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3226/comments | https://api.github.com/repos/huggingface/datasets/issues/3226/events | https://github.com/huggingface/datasets/pull/3226 | 1,046,584,518 | PR_kwDODunzps4uL0ma | 3,226 | Fix paper BibTeX citation with proceedings reference | {
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https://api.github.com/repos/huggingface/datasets/issues/3225 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3225/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3225/comments | https://api.github.com/repos/huggingface/datasets/issues/3225/events | https://github.com/huggingface/datasets/pull/3225 | 1,046,530,493 | PR_kwDODunzps4uLrB3 | 3,225 | Update tatoeba to v2021-07-22 | {
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"How about this? @lhoestq @abhishekkrthakur ",
"Hi ! I think it would be nice if people could still be able to load the old version.\r\nMaybe this can be a parameter ? For example to load the old version they could do\r\n```python\r\nload_dataset(\"tatoeba\", lang1=\"en\", lang2=\"mr\", date=\"v2020-11-09\")\r\n```\r\n\r\nIf it sounds good to you, we can add this parameter to the TatoebaConfig:\r\n```python\r\nclass TatoebaConfig(datasets.BuilderConfig):\r\n def __init__(self, *args, lang1=None, lang2=None, date=\"v2021-07-22\", **kwargs):\r\n self.date = date\r\n```\r\nand then pass the date to the URL\r\n```python\r\n_BASE_URL = \"https://object.pouta.csc.fi/OPUS-Tatoeba/{}/moses/{}-{}.txt.zip\"\r\n```\r\n```python\r\n def _base_url(lang1, lang2, date):\r\n return _BASE_URL.format(date, lang1, lang2)\r\n```\r\n\r\nWhat do you think ?",
"`_DATE = \"v\" + \"-\".join(s.zfill(2) for s in _VERSION.split(\".\"))` seems rather tricky but works well. How about this? @lhoestq \r\n",
"The CI is only failing because of the missing sections in the dataset card, and because of an issue with the CER metric that is unrelated to this PR"
] | 1,636,211,671,000 | 1,636,715,593,000 | 1,636,715,593,000 | CONTRIBUTOR | null | Tatoeba's latest version is v2021-07-22 | {
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https://api.github.com/repos/huggingface/datasets/issues/3223 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3223/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3223/comments | https://api.github.com/repos/huggingface/datasets/issues/3223/events | https://github.com/huggingface/datasets/pull/3223 | 1,046,445,507 | PR_kwDODunzps4uLb1E | 3,223 | Update BibTeX entry | {
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https://api.github.com/repos/huggingface/datasets/issues/3222 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3222/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3222/comments | https://api.github.com/repos/huggingface/datasets/issues/3222/events | https://github.com/huggingface/datasets/pull/3222 | 1,046,299,725 | PR_kwDODunzps4uK_uG | 3,222 | Add docs for audio processing | {
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"Nice ! love it this way. I guess you can set this PR to \"ready for review\" ?",
"I guess we can merge this one now :)"
] | 1,636,153,679,000 | 1,637,771,528,000 | 1,637,768,152,000 | CONTRIBUTOR | null | This PR adds documentation for the `Audio` feature. It describes:
- The difference between loading `path` and `audio`, as well as use-cases/best practices for each of them.
- Resampling audio files with `cast_column`, and then calling `ds[0]["audio"]` to automatically decode and resample to the desired sampling rate.
- Resampling with `map`.
Preview [here](https://52969-250213286-gh.circle-artifacts.com/0/docs/_build/html/audio_process.html), let me know if I'm missing anything! | {
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https://api.github.com/repos/huggingface/datasets/issues/3221 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3221/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3221/comments | https://api.github.com/repos/huggingface/datasets/issues/3221/events | https://github.com/huggingface/datasets/pull/3221 | 1,045,890,512 | PR_kwDODunzps4uJp4Z | 3,221 | Resolve data_files by split name | {
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"Really cool!\r\nWhen splitting by folder, what do we use for validation set (\"valid\", \"validation\" or both)?",
"> When splitting by folder, what do we use for validation set (\"valid\", \"validation\" or both)?\r\n\r\nBoth are fine :) As soon as it has \"valid\" in it",
"Merging for now, if you have comments about the documentation we can address them in subsequent PRs :)",
"Thanks for the comments @stevhliu :) I just opened https://github.com/huggingface/datasets/pull/3233 to take them into account"
] | 1,636,121,255,000 | 1,636,379,540,000 | 1,636,134,598,000 | MEMBER | null | As discussed in https://github.com/huggingface/datasets/issues/3027 we should automatically infer what file is supposed to go to what split automatically, based on filenames.
I added the support for different kinds of patterns, for both dataset repositories and local directories:
```
Input structure:
my_dataset_repository/
βββ README.md
βββ dataset.csv
Output patterns:
{"train": ["*"]}
```
```
Input structure:
my_dataset_repository/
βββ README.md
βββ train.csv
βββ test.csv
my_dataset_repository/
βββ README.md
βββ data/
βββ train.csv
βββ test.csv
my_dataset_repository/
βββ README.md
βββ train_0.csv
βββ train_1.csv
βββ train_2.csv
βββ train_3.csv
βββ test_0.csv
βββ test_1.csv
Output patterns:
{"train": ["*train*"], "test": ["*test*"]}
```
```
Input structure:
my_dataset_repository/
βββ README.md
βββ data/
βββ train/
β βββ shard_0.csv
β βββ shard_1.csv
β βββ shard_2.csv
β βββ shard_3.csv
βββ test/
βββ shard_0.csv
βββ shard_1.csv
Output patterns:
{"train": ["*train*/*", "*train*/**/*"], "test": ["*test*/*", "*test*/**/*"]}
```
and also this pattern that allows to have custom split names, and that is the structure used by #3098 for `push_to_hub` (cc @LysandreJik ):
```
Input structure:
my_dataset_repository/
βββ README.md
βββ data/
βββ train-00000-of-00003.csv
βββ train-00001-of-00003.csv
βββ train-00002-of-00003.csv
βββ test-00000-of-00001.csv
βββ random-00000-of-00003.csv
βββ random-00001-of-00003.csv
βββ random-00002-of-00003.csv
Output patterns:
{
"train": ["data/train-[0-9][0-9][0-9][0-9][0-9]-of-[0-9][0-9][0-9][0-9][0-9].*"],
"test": ["data/test-[0-9][0-9][0-9][0-9][0-9]-of-[0-9][0-9][0-9][0-9][0-9].*"],
"random": ["data/random-[0-9][0-9][0-9][0-9][0-9]-of-[0-9][0-9][0-9][0-9][0-9].*"],
}
```
You can check the documentation about structuring your repository [here](https://52640-250213286-gh.circle-artifacts.com/0/docs/_build/html/repository_structure.html). cc @stevhliu
Fix https://github.com/huggingface/datasets/issues/3027
Fix https://github.com/huggingface/datasets/issues/3212
In the future we can also add support for dataset configurations. | {
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https://api.github.com/repos/huggingface/datasets/issues/3219 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3219/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3219/comments | https://api.github.com/repos/huggingface/datasets/issues/3219/events | https://github.com/huggingface/datasets/issues/3219 | 1,045,095,000 | I_kwDODunzps4-SuJY | 3,219 | Eventual Invalid Token Error at setup of private datasets | {
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] | null | [] | 1,636,051,845,000 | 1,636,377,786,000 | 1,636,361,983,000 | MEMBER | null | ## Describe the bug
From time to time, there appear Invalid Token errors with private datasets:
- https://app.circleci.com/pipelines/github/huggingface/datasets/8520/workflows/d44629f2-4749-40f8-a657-50931d0b3434/jobs/52534
```
____________ ERROR at setup of test_load_streaming_private_dataset _____________
ValueError: Invalid token passed!
____ ERROR at setup of test_load_streaming_private_dataset_with_zipped_data ____
ValueError: Invalid token passed!
=========================== short test summary info ============================
ERROR tests/test_load.py::test_load_streaming_private_dataset - ValueError: I...
ERROR tests/test_load.py::test_load_streaming_private_dataset_with_zipped_data
```
- https://app.circleci.com/pipelines/github/huggingface/datasets/8557/workflows/a8383181-ba6d-4487-9d0a-f750b6dcb936/jobs/52763
```
____ ERROR at setup of test_load_streaming_private_dataset_with_zipped_data ____
[gw1] linux -- Python 3.6.15 /home/circleci/.pyenv/versions/3.6.15/bin/python3.6
hf_api = <huggingface_hub.hf_api.HfApi object at 0x7f4899bab908>
hf_token = 'vgNbyuaLNEBuGbgCEtSBCOcPjZnngJufHkTaZvHwkXKGkHpjBPwmLQuJVXRxBuaRzNlGjlMpYRPbthfHPFWXaaEDTLiqTTecYENxukRYVAAdpeApIUPxcgsowadkTkPj'
zip_csv_path = PosixPath('/tmp/pytest-of-circleci/pytest-0/popen-gw1/data16/dataset.csv.zip')
@pytest.fixture(scope="session")
def hf_private_dataset_repo_zipped_txt_data_(hf_api: HfApi, hf_token, zip_csv_path):
repo_name = "repo_zipped_txt_data-{}".format(int(time.time() * 10e3))
hf_api.create_repo(token=hf_token, name=repo_name, repo_type="dataset", private=True)
repo_id = f"{USER}/{repo_name}"
hf_api.upload_file(
token=hf_token,
path_or_fileobj=str(zip_csv_path),
path_in_repo="data.zip",
repo_id=repo_id,
> repo_type="dataset",
)
tests/hub_fixtures.py:68:
...
ValueError: Invalid token passed!
=========================== short test summary info ============================
ERROR tests/test_load.py::test_load_streaming_private_dataset_with_zipped_data
```
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https://api.github.com/repos/huggingface/datasets/issues/3218 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3218/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3218/comments | https://api.github.com/repos/huggingface/datasets/issues/3218/events | https://github.com/huggingface/datasets/pull/3218 | 1,045,032,313 | PR_kwDODunzps4uG2UA | 3,218 | Fix code quality in riddle_sense dataset | {
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Fix #3217. | {
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"To give more context: https://github.com/psf/black/issues/318. `black` doesn't treat this as a bug, but `flake8` does. \r\n"
] | 1,636,047,632,000 | 1,636,048,202,000 | 1,636,048,202,000 | MEMBER | null | ## Describe the bug
```
datasets/riddle_sense/riddle_sense.py:36:21: W291 trailing whitespace
``` | {
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- https://github.com/tensorflow/tensorflow/commit/c1867f3bfdd1042f694df7a9870be51ba80543cb
- https://pypi.org/project/tensorflow/2.6.2/
with the patch:
- tensorflow/tensorflow#52927
we can remove the temporary fix we introduced in:
- #3208
Fix #3209. | {
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"@stevhliu Accepted both suggestions, thanks for the review!"
] | 1,636,046,521,000 | 1,636,052,138,000 | 1,636,052,137,000 | CONTRIBUTOR | null | I added a little more description about `to_tf_dataset` compared to just setting the format | {
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"This will be fixed by https://github.com/huggingface/datasets/pull/3221"
] | 1,636,024,111,000 | 1,636,134,598,000 | 1,636,134,598,000 | CONTRIBUTOR | null | When loading a dataset that consists of several files (e.g. `my_data/data_001.json`, `my_data/data_002.json` etc.) they are not loaded in order when using `load_dataset("my_data")`.
This could lead to counter-intuitive results if, for example, the data files are sorted by date or similar since they would appear in different order in the `Dataset`.
The straightforward solution is to sort the list of files alphabetically before loading them.
cc @lhoestq
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} | [] | closed | false | null | [] | null | [] | 1,636,023,126,000 | 1,636,024,101,000 | 1,636,024,100,000 | MEMBER | null | Currently the `disable_nullable` parameter is not consistent across all dataset transforms. For example it is `False` in `map` but `True` in `flatten_indices`.
This creates unexpected behaviors like this
```python
from datasets import Dataset, concatenate_datasets
d1 = Dataset.from_dict({"a": [0, 1, 2, 3]})
d2 = d1.filter(lambda x: x["a"] < 2).flatten_indices()
d1.data.schema == d2.data.schema # False
```
This can cause issues when concatenating datasets for example.
For consistency I set `disable_nullable` to `False` in `flatten_indices` and I fixed some docstrings
cc @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/3209 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3209/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3209/comments | https://api.github.com/repos/huggingface/datasets/issues/3209/events | https://github.com/huggingface/datasets/issues/3209 | 1,044,505,771 | I_kwDODunzps4-QeSr | 3,209 | Unpin keras once TF fixes its release | {
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- #3208 | {
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] | null | [] | 1,636,016,651,000 | 1,636,018,254,000 | 1,636,018,254,000 | MEMBER | null | ## Describe the bug
Release of TensorFlow 2.7.0 contains an incompatibility with Keras. See:
- keras-team/keras#15579
This breaks our CI test suite: https://app.circleci.com/pipelines/github/huggingface/datasets/8493/workflows/055c7ae2-43bc-49b4-9f11-8fc71f35a25c/jobs/52363
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"Hi @BramVanroy, thanks for your PR.\r\n\r\nThere was a bug in TensorFlow/Keras. We have made a temporary fix in master branch. Please, merge master into your PR branch, so that the CI tests pass.\r\n\r\n```\r\ngit checkout registry\r\ngit fetch upstream master\r\ngit merge upstream/master\r\n```",
"@albertvillanova Done. Although new tests will need to be added. I am looking for some feedback on my initial proposal in this PR. Reviews and ideas welcome!",
"Hi ! Thanks for diving into this :)\r\n\r\nWith this approach you get the right hash when doing `Hasher.hash(nlp)` but if you try to hash an object that has `nlp` as one of its attributes for example you will get different hashes every time.\r\n\r\nThis is because `Hasher.hash` is not recursive itself. Indeed what happens when you try to hash an object is that:\r\n1. it is dumped with our custom `dill` pickler (which is recursive)\r\n2. the bytes of the dump are hashed\r\n\r\nTo fix this we must integrate the custom hashing as a custom pickler dumping instead.\r\n\r\nNote that we're only using the `pickler.dumps` method and not `pickler.loads` since we only use it to get hashes, so it doesn't matter if `loads` doesn't reconstruct the object exactly. What's important it only to capture all the necessary information that defines how the object transforms the data (here `nlp.to_bytes()` determines how the spacy pipeline transforms the text).\r\n\r\nOur pickler already has a registry and you can register new dump functions with:\r\n```python\r\nimport dill\r\nimport spacy\r\nfrom datasets.utils.py_utils import pklregister\r\n\r\n@pklregister(spacy.Language)\r\ndef _save_spacy_language(pickler, nlp):\r\n pickler.save_reduce(...) # I think we can use nlp.to_bytes() here\r\n dill._dill.log.info(...)\r\n```\r\n\r\nYou can find some examples of custom dump functions in `py_utils.py`",
"Ah, darn it. Completely missed that register. Time wasted, unfortunately. \r\n\r\nTo better understand what you mean, I figured I'd try the basis of your snippet and I've noticed quite an annoying side-effect of how the pickle dispatch table seems to work. It explicitly uses an object's [`type()`](https://github.com/python/cpython/blob/87032cfa3dc975d7442fd57dea2c6a56d31c911a/Lib/pickle.py#L557-L558), which makes sense for pickling some (primitive) types it is not ideal for more complex ones, I think. `Hasher.hash` has the same issue as far as I can tell.\r\n\r\nhttps://github.com/huggingface/datasets/blob/d21ce54f2c2782f854f975eb1dc2be6f923b4314/src/datasets/fingerprint.py#L187-L191\r\n\r\nThis is very restrictive, and won't work for subclasses. In the case of spaCy, for instance, we register `Language`, but `nlp` is an instance of `English`, which is a _subclass_ of `Language`. These are different types, and so they will not match in the dispatch table. Maybe this is more general approach to cover such cases? Something like this is a start but too broad, but ideally a hierarchy is constructed and traversed of all classes in the table and the lowest class is selected to ensure that the most specific class function is dispatched.\r\n\r\n```python\r\n def hash(cls, value: Any) -> str:\r\n # Try to match the exact type\r\n if type(value) in cls.dispatch:\r\n return cls.dispatch[type(value)](cls, value)\r\n\r\n # Try to match instance (superclass)\r\n for type_cls, func in cls.dispatch.items():\r\n if isinstance(value, type_cls):\r\n return cls.dispatch[type_cls](cls, value)\r\n\r\n return cls.hash_default(value)\r\n```\r\n\r\nThis does not solve the problem for pickling, though. That is quite unfortunate IMO because that implies that users always have to specify the most specific class, which is not always obvious. (For instance, `spacy.load`'s signature returns `Language`, but as said before a subclass might be returned.)\r\n\r\nSecond, I am trying to understand `save_reduce` but I can find very little documentation about it, only the source code which is quite cryptic. Can you explain it a bit? The required arguments are not very clear to me and there is no docstring.\r\n\r\n```python\r\n def save_reduce(self, func, args, state=None, listitems=None, dictitems=None, obj=None):\r\n```",
"Here is an example illustrating the problem with sub-classes.\r\n\r\n```python\r\nimport spacy\r\n\r\nfrom spacy import Language\r\nfrom spacy.lang.en import English\r\n\r\nfrom datasets.utils.py_utils import Pickler, pklregister\r\n\r\n# Only useful in the registry (matching with `nlp`)\r\n# if you swap it out for very specific `English`\r\n@pklregister(English)\r\ndef hash_spacy_language(pickler, nlp):\r\n pass\r\n\r\n\r\ndef main():\r\n print(Pickler.dispatch)\r\n nlp = spacy.load(\"en_core_web_sm\")\r\n print(f\"NLP type {type(nlp)} in dispatch table? \", type(nlp) in Pickler.dispatch)\r\n\r\n\r\nif __name__ == '__main__':\r\n main()\r\n```",
"Indeed that's not ideal.\r\nMaybe we could integrate all the subclasses directly in `datasets`. That's simple to do but the catch is that if users have new subclasses of `Language` it won't work.\r\n\r\nOtherwise we can see how to make the API simpler for users by allowing subclasses\r\n```python\r\n# if you swap it out for very specific `English`\r\n@pklregister(Language, allow_subclasses=True)\r\ndef hash_spacy_language(pickler, nlp):\r\n pass\r\n```\r\n\r\nHere is an idea how to make this work, let me know what you think:\r\n\r\nWhen `Pickler.dumps` is called, it uses `Pickler.save_global` which is a method that is going to be called recursively on all the objects. We can customize this part, and make it work as we want when it encounters a subclass of `Language`.\r\n\r\nFor example when it encounters a subclass of `Language`, we can dynamically register the hashing function for the subclass (`English` for example) in `Pickler.save_global`, right before calling the actual `dill.Pickler.save_global(self, obj, name=name)`:\r\n```python\r\npklregister(type(obj))(hash_function_registered_for_parent_class)\r\ndill.Pickler.save_global(self, obj, name=name)\r\n```\r\n\r\nIn practice that means we can have an additional dispatch dictionary (similar to `Pickler.dispatch`) to store the hashing functions when `allow_subclasses=True`, and use this dictionary in `Pickler.save_global` to check if we need to use a hashing function registered with `allow_subclasses=True` and get `hash_function_registered_for_parent_class`.",
"If I understood you correctly, I do not think that that is enough because you are only doing this for a type and its direct parent class. You could do this for all superclasses (so traverse all ancestors and find the registered function for the first that is encountered). I can work on that, if you agree. The one thing that I am not sure about is how you want to create the secondary dispatch table. An empty dict as class variable in Pickler? (It doesn't have to be a true dispatcher, I think.)\r\n\r\nI do not think that dynamic registration is the ideal situation (it feels a bit hacky). An alternative would be to subclass Pickle and Dill to make sure that instead of just type() checking in the dispatch table also superclasses are considered. But that is probably overkill.",
"> You could do this for all superclasses (so traverse all ancestors and find the registered function for the first that is encountered)\r\n\r\nThat makes sense indeed !\r\n\r\n> The one thing that I am not sure about is how you want to create the secondary dispatch table. An empty dict as class variable in Pickler? (It doesn't have to be a true dispatcher, I think.)\r\n\r\nSure, let's try to not use too complicated stuff\r\n\r\n> I do not think that dynamic registration is the ideal situation (it feels a bit hacky). An alternative would be to subclass Pickle and Dill to make sure that instead of just type() checking in the dispatch table also superclasses are considered. But that is probably overkill.\r\n\r\nIndeed that would feel less hacky, but maybe it's too complex just for this. I feel like this part of the library is already hard to understand when you're not familiar with pickle. IMO having only a few changes that are simpler to understand is better than having a rewrite of `dill`'s core code.\r\n\r\nThanks a lot for your insights, it looks like we're going to have something that works well and that unlocks some nice flexibility for users :) Feel free to ping me anytime if I can help on this",
"Sure, thanks for brainstorming! I'll try to work on it this weekend. Will also revert the current changes in this PR and rename it. ",
"It seems like this is going in the right direction :). \r\n\r\n@BramVanroy Just one small suggestion for future contributions: instead of using `WIP` in the PR title, you can create a draft PR if you're still working on it.",
"Maybe I should just create a new (draft) PR then, seeing that I'll have to rename and revert the changes anyway? I'll link to this PR so that the discussion is at least referenced.",
"I can convert this PR to a draft PR. Let me know what would you prefer.",
"I think reverting my previous commits would make for a dirty (or confusing) commit history, so I'll just create a new one. Thanks."
] | 1,635,981,942,000 | 1,636,115,891,000 | 1,636,115,884,000 | CONTRIBUTOR | null | Inspired by the discussion on hashing in https://github.com/huggingface/datasets/issues/3178#issuecomment-959016329, @lhoestq suggested that it would be neat to allow users more control over the hashing process. Specifically, it would be great if users can specify specific hashing functions depending on the **class** of the object.
As an example, we found in the linked topic that loaded spaCy models (`Language` objects) have different hashes when `dump`'d, but their byte representation with `Language.to_bytes()` _is_ deterministic. It would therefore be great if we could specify that for `Language` objects, the hasher should hash the objects `to_bytes()` return value instead of the object itself.
This PR adds a new, but tiny, dependency to manage the registry, namely [`catalogue`](https://github.com/explosion/catalogue).
Two files have been changed (apart from the added dependency in `setup.py`) and one file has been added.
**utils.registry** (added)
This file defines our custom Registry and builds a registry called "hashers". A Registry is basically dictionary from names (str) to functions. A function can be added to the registry by a decorator, e.g.
```python
@hashers.register(spacy.Language)
def hash_spacy_language(nlp):
return Hasher.hash(nlp.to_bytes())
```
You'll notice that `spacy.Language` is not a string, even though the registry holds a str->func mapping. To accomplish this with classes in a dynamic way, catalogue.Registry needed to be subclassed and modified as `DatasetsRegistry`. All methods that use a name as an input are now modified so that classes are deterministically converted in strings in such a way that we can later retrieve the actual class from the string (below).
**utils.py_utils** (modified)
Added two functions to deal with classes and their qualified names, that is, their full descriptive name including the module. On the one hand it allows us to retrieve a string from a given class, e.g. given `Module` class, return `torch.nn.Module` str. Conversly, a function is added to convert such a full qualified name into a class. For instance, given the string `torch.nn.Module`, return the `Module` class. These straightforward methods allow us to interchangeably use classes and strings without any needed user interaction - they can just register a class, and behind the scenes `DatasetsRegistry` converts these to deterministic strings.
**fingerprint** (modified)
Updated Hasher.hash so that if the object to hash is an instance of a class in the registry, the registered function is used to hash the object instead of the default behavior. To do so we iterate over the registry `hashers` and convert its keys (strings) into classes, and then we can use `isinstance`.
```python
# Check if the current object is an instance that is
# applicable to the user-defined hashers. If so, hash
# with the user-defined function
for full_module_name, func in hashers.get_all().items():
registered_cls = get_cls_from_qualname(full_module_name)
if isinstance(value, registered_cls):
return func(value)
```
**Putting it all together**
To test this, you can try the following example with spaCy. First install spaCy from source and checkout a specific commit.
```shell
git clone https://github.com/explosion/spaCy.git
cd spaCy/
git checkout cab9209c3dfcd1b75dfe5657f10e52c4d847a3cf
cd ..
git clone https://github.com/BramVanroy/datasets.git
cd datasets
git checkout registry
pip install -e .
pip install ../spaCy
spacy download en_core_web_sm
```
Now you can run the following script. By default it will use the custom hasher function for the Language object. You can enable the default behavior by commenting out `@hashers.register...`.
```python
import spacy
from datasets.fingerprint import Hasher
from datasets.utils.registry import hashers
# Register a function so that when the Hasher encounters a spacy.Language object
# it uses this custom function to hash instead of the default
@hashers.register(spacy.Language)
def hash_spacy_language(nlp):
return Hasher.hash(nlp.to_bytes())
def main():
print(hashers.get_all())
nlp = spacy.load("en_core_web_sm")
dump1 = Hasher.hash(nlp)
nlp = spacy.load("en_core_web_sm")
dump2 = Hasher.hash(nlp)
print(dump1)
# succeeds when using the registered custom function
# fails if using the default
assert dump1 == dump2
if __name__ == '__main__':
main()
```
To do
====
- The above is just a proof-of-concept. I am open to changes/suggestions
- Tests still need to be written
- We should consider whether we can make `DatasetsRegistry` very restrictive and ONLY allowing classes. That would make testing easier - otherwise we also need to test for other sorts of objects.
- Maybe the `hashers` definition is better suited in `fingerprint`?
- Documentation/examples need to be updated
- Not sure why the logger is not working in `hash()`
- `get_cls_from_qualname` might need a fail-safe: is it possible for a full_qualname to not have a module, and if so how do we deal with that?
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"@songfeng cc",
"Hi @sivasankalpp, thanks for your PR.\r\n\r\nThere was a bug in TensorFlow/Keras. We have made a temporary fix in our master branch. Please, merge master into your PR branch, so that the CI tests pass.\r\n\r\n```\r\ngit checkout multidoc2dial\r\ngit fetch upstream master\r\ngit merge upstream/master\r\n```",
"Hi @albertvillanova, I have merged master into my PR branch. All tests are passing. \r\nPlease take a look when you get a chance, thanks! \r\n",
"Thanks for your feedback @lhoestq. We addressed your comments in the latest commit. Let us know if everything looks okay :) "
] | 1,635,972,511,000 | 1,637,775,169,000 | 1,637,772,908,000 | CONTRIBUTOR | null | This PR adds the MultiDoc2Dial dataset introduced in this [paper](https://arxiv.org/pdf/2109.12595v1.pdf ) | {
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"@mariosasko @lhoestq Could you give me an update on how to load the dataset after the fix?\r\nThanks.",
"Hi @arda-vianai,\r\n\r\nfirst, you can try:\r\n```python\r\nimport datasets\r\ndataset = datasets.load_dataset('tuple_ie', 'all', revision=\"master\")\r\n```\r\nIf this doesn't work, your version of `datasets` is missing some features that are required to run the dataset script, so install the master version with the following command:\r\n```\r\npip install git+https://github.com/huggingface/datasets.git\r\n```\r\nand then:\r\n```python\r\nimport datasets\r\ndataset = datasets.load_dataset('tuple_ie', 'all')\r\n```\r\nshould work (even without `revision`).",
"@mariosasko \r\nThanks, it is working now. I actually did that before but I didn't restart the kernel. I restarted it and it works now. My bad!!!\r\nMany thanks and great job!\r\n-arda"
] | 1,635,951,415,000 | 1,636,127,475,000 | 1,636,121,765,000 | NONE | null | Hi,
`dataset = datasets.load_dataset('tuple_ie', 'all')`
returns a FileNotFound error. Is the data not available?
Many thanks.
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"Actually it looks like the old URL is still working, and it's also the one that is mentioned in https://github.com/alexandrainst/danlp/blob/master/docs/docs/datasets.md\r\n\r\nWhat makes you think we should use the new URL ?",
"@lhoestq Sorry! I might have jumped to conclusions a bit too fast here... \r\n\r\nI was working in Google Colab and got an error that it was unable to use the URL. I then forked the project, updated the URL, ran it locally and it worked. I therefore assumed that my URL update fixed the issue, however, I see now that it might rather be a Google Colab issue... \r\n\r\nStill - this seems to be the official URL for downloading the dataset, and I think that it will be most beneficial to use. :-) ",
"It looks like they're using these new urls for their new datasets. Maybe let's change to the new URL in case the old one stops working at one point. Thanks"
] | 1,635,944,113,000 | 1,636,031,676,000 | 1,636,026,403,000 | CONTRIBUTOR | null | It seems that DaNLP has updated their download URLs and it therefore also needs to be updated in here... | {
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https://api.github.com/repos/huggingface/datasets/issues/3200 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3200/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3200/comments | https://api.github.com/repos/huggingface/datasets/issues/3200/events | https://github.com/huggingface/datasets/pull/3200 | 1,042,887,291 | PR_kwDODunzps4uAZLu | 3,200 | Catch token invalid error in CI | {
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I modified the fixture in the test that uses staging to ignore this error | {
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https://api.github.com/repos/huggingface/datasets/issues/3199 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3199/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3199/comments | https://api.github.com/repos/huggingface/datasets/issues/3199/events | https://github.com/huggingface/datasets/pull/3199 | 1,042,860,935 | PR_kwDODunzps4uAVzQ | 3,199 | Bump huggingface_hub | {
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It was supposed to be part of 1.15.0 but I'm adding it for 1.15.1 | {
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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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} | [] | closed | false | null | [] | null | [] | 1,635,868,553,000 | 1,635,880,344,000 | 1,635,880,343,000 | MEMBER | null | 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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* automatically calls `flatten_indices` where needed: in `unique` and `save_to_disk` to avoid saving the indices file
* adds descriptions to the map calls
Fix #3040 | {
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https://api.github.com/repos/huggingface/datasets/issues/3193 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3193/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3193/comments | https://api.github.com/repos/huggingface/datasets/issues/3193/events | https://github.com/huggingface/datasets/issues/3193 | 1,041,971,117 | I_kwDODunzps4-Gzet | 3,193 | Update link to datasets-tagging app | {
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] | null | [] | 1,635,838,799,000 | 1,636,367,782,000 | 1,636,367,782,000 | MEMBER | null | Once datasets-tagging has been transferred to Spaces:
- huggingface/datasets-tagging#22
We should update the link in Datasets. | {
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https://api.github.com/repos/huggingface/datasets/issues/3190 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3190/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3190/comments | https://api.github.com/repos/huggingface/datasets/issues/3190/events | https://github.com/huggingface/datasets/issues/3190 | 1,041,153,631 | I_kwDODunzps4-Dr5f | 3,190 | combination of shuffle and filter results in a bug | {
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"name": "bug",
"color": "d73a4a",
"default": true,
"description": "Something isn't working"
}
] | closed | false | null | [] | null | [
"I cannot reproduce this on master and pyarrow==4.0.1.\r\n",
"Hi ! There was a regression in `datasets` 1.12 that introduced this bug. It has been fixed in #3019 in 1.13\r\n\r\nCan you try to update `datasets` and try again ?",
"Thanks a lot, fixes with 1.13"
] | 1,635,772,049,000 | 1,635,850,249,000 | 1,635,850,249,000 | CONTRIBUTOR | null | ## Describe the bug
Hi,
I would like to shuffle a dataset, then filter it based on each existing label. however, the combination of `filter`, `shuffle` seems to results in a bug. In the minimal example below, as you see in the filtered results, the filtered labels are not unique, meaning filter has not worked. Any suggestions as a temporary fix is appreciated @lhoestq.
Thanks.
Best regards
Rabeeh
## Steps to reproduce the bug
```python
import numpy as np
import datasets
datasets = datasets.load_dataset('super_glue', 'rte', script_version="master")
shuffled_data = datasets["train"].shuffle(seed=42)
for label in range(2):
print("label ", label)
data = shuffled_data.filter(lambda example: int(example['label']) == label)
print("length ", len(data), np.unique(data['label']))
```
## Expected results
Filtering per label, should only return the data with that specific label.
## Actual results
As you can see, filtered data per label, has still two labels of [0, 1]
```
label 0
length 1249 [0 1]
label 1
length 1241 [0 1]
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.1
- Platform: linux
- Python version: 3.7.11
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3189 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3189/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3189/comments | https://api.github.com/repos/huggingface/datasets/issues/3189/events | https://github.com/huggingface/datasets/issues/3189 | 1,041,044,986 | I_kwDODunzps4-DRX6 | 3,189 | conll2003 incorrect label explanation | {
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] | closed | false | null | [] | null | [
"Hi @BramVanroy,\r\n\r\nsince these fields are of type `ClassLabel` (you can check this with `dset.features`), you can inspect the possible values with:\r\n```python\r\ndset.features[field_name].feature.names # .feature because it's a sequence of labels\r\n```\r\n\r\nand to find the mapping between names and integers, use: \r\n```python\r\ndset.features[field_name].feature.int2str(value_or_values_list) # map integer value to string value\r\n# or\r\ndset.features[field_name].feature.str2int(value_or_values_list) # map string value to integer value\r\n```\r\n\r\n"
] | 1,635,764,610,000 | 1,636,454,458,000 | 1,636,454,458,000 | CONTRIBUTOR | null | In the [conll2003](https://huggingface.co/datasets/conll2003#data-fields) README, the labels are described as follows
> - `id`: a `string` feature.
> - `tokens`: a `list` of `string` features.
> - `pos_tags`: a `list` of classification labels, with possible values including `"` (0), `''` (1), `#` (2), `$` (3), `(` (4).
> - `chunk_tags`: a `list` of classification labels, with possible values including `O` (0), `B-ADJP` (1), `I-ADJP` (2), `B-ADVP` (3), `I-ADVP` (4).
> - `ner_tags`: a `list` of classification labels, with possible values including `O` (0), `B-PER` (1), `I-PER` (2), `B-ORG` (3), `I-ORG` (4) `B-LOC` (5), `I-LOC` (6) `B-MISC` (7), `I-MISC` (8).
First of all, it would be great if we can get a list of ALL possible pos_tags.
Second, the chunk tags labels cannot be correct. The description says the values go from 0 to 4 whereas the data shows values from at least 11 to 21 and 0.
EDIT: not really a bug, sorry for mistagging. | {
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https://api.github.com/repos/huggingface/datasets/issues/3188 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3188/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3188/comments | https://api.github.com/repos/huggingface/datasets/issues/3188/events | https://github.com/huggingface/datasets/issues/3188 | 1,040,980,712 | I_kwDODunzps4-DBro | 3,188 | conll2002 issues | {
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"name": "dataset-viewer",
"color": "E5583E",
"default": false,
"description": "Related to the dataset viewer on huggingface.co"
}
] | closed | false | null | [] | null | [
"Hi ! Thanks for reporting :)\r\n\r\nThis is related to https://github.com/huggingface/datasets/issues/2742, I'm working on it. It should fix the viewer for around 80 datasets.\r\n",
"Ah, hadn't seen that sorry.\r\n\r\nThe scrambled \"point of contact\" is a separate issue though, I think.",
"@lhoestq The \"point of contact\" is still an issue.",
"It will be fixed in https://github.com/huggingface/datasets/pull/3274, thanks"
] | 1,635,760,164,000 | 1,636,984,259,000 | 1,636,737,491,000 | CONTRIBUTOR | null | **Link:** https://huggingface.co/datasets/conll2002
The dataset viewer throws a server error when trying to preview the dataset.
```
Message: Extraction protocol 'train' for file at 'https://raw.githubusercontent.com/teropa/nlp/master/resources/corpora/conll2002/esp.train' is not implemented yet
```
In addition, the "point of contact" has encoding issues and does not work when clicked.
Am I the one who added this dataset ? No, @lhoestq did | {
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https://api.github.com/repos/huggingface/datasets/issues/3187 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3187/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3187/comments | https://api.github.com/repos/huggingface/datasets/issues/3187/events | https://github.com/huggingface/datasets/pull/3187 | 1,040,412,869 | PR_kwDODunzps4t44Ab | 3,187 | Add ChrF(++) (as implemented in sacrebleu) | {
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} | [] | closed | false | null | [] | null | [] | 1,635,670,438,000 | 1,635,864,650,000 | 1,635,863,486,000 | CONTRIBUTOR | null | Similar to my [PR for TER](https://github.com/huggingface/datasets/pull/3153), it feels only right to also include ChrF and friends. These are present in Sacrebleu and are therefore very similar to implement as TER and sacrebleu. I tested the implementation with sacrebleu's tests to verify. You can try this below for yourself
```python
import datasets
EPSILON = 1e-4
chrf = datasets.load_metric(r"path\to\datasets\metrics\chrf")
test_cases = [
(["abcdefg"], ["hijklmnop"], 0.0),
(["a"], ["b"], 0.0),
([""], ["b"], 0.0),
([""], ["ref"], 0.0),
([""], ["reference"], 0.0),
(["aa"], ["ab"], 8.3333),
(["a", "b"], ["a", "c"], 8.3333),
(["a"], ["a"], 16.6667),
(["a b c"], ["a b c"], 50.0),
(["a b c"], ["abc"], 50.0),
([" risk assessment must be made of those who are qualified and expertise in the sector - these are the scientists ."],
["risk assessment has to be undertaken by those who are qualified and expert in that area - that is the scientists ."], 63.361730),
([" Die Beziehung zwischen Obama und Netanjahu ist nicht gerade freundlich. "],
["Das VerhΓ€ltnis zwischen Obama und Netanyahu ist nicht gerade freundschaftlich."], 64.1302698),
(["Niemand hat die Absicht, eine Mauer zu errichten"], ["Niemand hat die Absicht, eine Mauer zu errichten"], 100.0),
]
for hyp, ref, score in test_cases:
# Note the reference transformation which is different from scarebleu's input format
results = chrf.compute(predictions=hyp, references=[[r] for r in ref],
char_order=6, word_order=0, beta=3, eps_smoothing=True)
if abs(score - results["score"]) > EPSILON:
print(f"expected {score}, got {results['score']} for {hyp} - {ref}")
test_cases_effective_order = [
(["a"], ["a"], 100.0),
([""], ["reference"], 0.0),
(["a b c"], ["a b c"], 100.0),
(["a b c"], ["abc"], 100.0),
([""], ["c"], 0.0),
(["a", "b"], ["a", "c"], 50.0),
(["aa"], ["ab"], 25.0),
]
for hyp, ref, score in test_cases_effective_order:
# Note the reference transformation which is different from scarebleu's input format
results = chrf.compute(predictions=hyp, references=[[r] for r in ref],
char_order=6, word_order=0, beta=3, eps_smoothing=False)
if abs(score - results["score"]) > EPSILON:
print(f"expected {score}, got {results['score']} for {hyp} - {ref}")
test_cases_keep_whitespace = [
(
["Die Beziehung zwischen Obama und Netanjahu ist nicht gerade freundlich."],
["Das VerhΓ€ltnis zwischen Obama und Netanyahu ist nicht gerade freundschaftlich."],
67.3481606,
),
(
["risk assessment must be made of those who are qualified and expertise in the sector - these are the scientists ."],
["risk assessment has to be undertaken by those who are qualified and expert in that area - that is the scientists ."],
65.2414427,
),
]
for hyp, ref, score in test_cases_keep_whitespace:
# Note the reference transformation which is different from scarebleu's input format
results = chrf.compute(predictions=hyp, references=[[r] for r in ref],
char_order=6, word_order=0, beta=3,
whitespace=True)
if abs(score - results["score"]) > EPSILON:
print(f"expected {score}, got {results['score']} for {hyp} - {ref}")
predictions = ["The relationship between Obama and Netanyahu is not exactly friendly."]
references = [["The ties between Obama and Netanyahu are not particularly friendly."]]
print(chrf.compute(predictions=predictions, references=references))
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3184 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3184/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3184/comments | https://api.github.com/repos/huggingface/datasets/issues/3184/events | https://github.com/huggingface/datasets/pull/3184 | 1,040,114,102 | PR_kwDODunzps4t4J61 | 3,184 | RONEC v2 | {
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"@lhoestq Thanks for the review. I totally understand what you are saying. Normally, I would definitely agree with you, but in this particular case, the quality of v1 is poor, and the dataset itself is small (at the time we created v1 it was the only RO NER dataset, and its size was limited by the available resources). \r\n\r\nThis is why we worked to build a larger one, with much better inter-annotator agreement. Fact is, models trained on v1 will be of very low quality and I would not recommend to anybody to use/do that. That's why I'd strongly suggest we replace v1 with v2, and kindof make v1 vanish :) \r\n\r\nWhat do you think? If you insist on having v1 accessible, I'll add the required code. Thanks!\r\n\r\n",
"Ok I see ! I think it's fine then, no need to re-add V1"
] | 1,635,591,003,000 | 1,635,868,943,000 | 1,635,868,942,000 | CONTRIBUTOR | null | Hi, as we've recently finished with the new RONEC (Romanian Named Entity Corpus), we'd like to update the dataset here as well. It's actually essential as links to V1 are no longer valid.
In reality we'd like to replace completely v1, as v2 is a full re-annotation of v1 with additional data (up to 2x size vs v1).
I've run the make style and all the dummy and real data test, and they passed.
I hope it's okay to merge the new RONEC v2 in the datasets.
Thanks! | {
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https://api.github.com/repos/huggingface/datasets/issues/3183 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3183/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3183/comments | https://api.github.com/repos/huggingface/datasets/issues/3183/events | https://github.com/huggingface/datasets/pull/3183 | 1,039,761,120 | PR_kwDODunzps4t3Dag | 3,183 | Add missing docstring to DownloadConfig | {
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https://api.github.com/repos/huggingface/datasets/issues/3182 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3182/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3182/comments | https://api.github.com/repos/huggingface/datasets/issues/3182/events | https://github.com/huggingface/datasets/pull/3182 | 1,039,739,606 | PR_kwDODunzps4t2-9J | 3,182 | Don't memoize strings when hashing since two identical strings may have different python ids | {
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"This change slows down the hash computation a little bit but from my tests it doesn't look too impactful. So I think it's fine to merge this."
] | 1,635,524,777,000 | 1,635,845,738,000 | 1,635,845,737,000 | MEMBER | null | When hashing an object that has several times the same string, the hashing could return a different hash if the identical strings share the same python `id()` or not.
Here is an example code that shows how the issue can affect the caching:
```python
import json
import pyarrow as pa
from datasets.features import Features
from datasets.fingerprint import Hasher
schema = pa.schema([pa.field("some_string", pa.string()), pa.field("another_string", pa.string())])
features_from_schema = Features.from_arrow_schema(schema)
Hasher.hash(features_from_schema) # dffa9dca9a73fd8c
features_dict = json.loads('{"some_string": {"dtype": "string", "id": null, "_type": "Value"}, "another_string": {"dtype": "string", "id": null, "_type": "Value"}}')
features_from_json = Features.from_dict(features_dict)
Hasher.hash(features_from_json) # 3812e76b15e6420e
features_from_schema == features_from_json # True
```
This is because in `features_dict`, some strings like "dtype" are repeated but don't share the same id, contrary to the ones in `features_from_schema`.
I fixed that by disabling memoization for strings.
This could be optimized in the future by implementing a smarter memoization with a special handling for strings. | {
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https://api.github.com/repos/huggingface/datasets/issues/3180 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3180/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3180/comments | https://api.github.com/repos/huggingface/datasets/issues/3180/events | https://github.com/huggingface/datasets/pull/3180 | 1,039,641,316 | PR_kwDODunzps4t2qQn | 3,180 | fix label mapping | {
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"heck, test failings. moving to draft. will come back to this later today hopefully",
"Thanks for fixing this :)\r\nI just updated the dataset_infos.json and added the missing `pretty_name` tag to the dataset card",
"thank you @lhoestq! running around as always it felt through as a lower priority..."
] | 1,635,518,544,000 | 1,635,860,467,000 | 1,635,849,432,000 | MEMBER | null | Fixing label mapping for hlgd.
0 correponds to same event and 1 corresponds to different event
<img width="642" alt="Capture dβeΜcran 2021-10-29 aΜ 10 39 58 AM" src="https://user-images.githubusercontent.com/16107619/139454810-1f225e3d-ad48-44a8-b8b1-9205c9533839.png">
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"The issue is that the datasets are malformed. Not a bug with the datasets library"
] | 1,635,514,247,000 | 1,635,514,521,000 | 1,635,514,521,000 | CONTRIBUTOR | null | ## Describe the bug
After https://github.com/huggingface/datasets/pull/3159, we can get the config name of "Check/region_1", which is "Check___region_1".
But now we cannot load the dataset (not sure it's related to the above PR though). It's the case for all the similar datasets, listed in https://github.com/huggingface/datasets-preview-backend/issues/78
## Steps to reproduce the bug
```python
>>> from datasets import get_dataset_config_names
>>> get_dataset_config_names("Check/region_1")
['Check___region_1']
>>> load_dataset("Check/region_1")
Using custom data configuration Check___region_1-d2b3bc48f11c9be2
Downloading and preparing dataset json/Check___region_1 to /home/slesage/.cache/huggingface/datasets/json/Check___region_1-d2b3bc48f11c9be2/0.0.0/c2d554c3377ea79c7664b93dc65d0803b45e3279000f993c7bfd18937fd7f426...
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1/1 [00:00<00:00, 4443.12it/s]
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1/1 [00:00<00:00, 1277.19it/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/builder.py", line 697, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1159, in _prepare_split
writer.write_table(table)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 442, in write_table
pa_table = pa.Table.from_arrays([pa_table[name] for name in self._schema.names], schema=self._schema)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 442, in <listcomp>
pa_table = pa.Table.from_arrays([pa_table[name] for name in self._schema.names], schema=self._schema)
File "pyarrow/table.pxi", line 1249, in pyarrow.lib.Table.__getitem__
File "pyarrow/table.pxi", line 1825, in pyarrow.lib.Table.column
File "pyarrow/table.pxi", line 1800, in pyarrow.lib.Table._ensure_integer_index
KeyError: 'Field "builder_name" does not exist in table schema'
```
Loading in streaming mode also returns something strange:
```python
>>> list(load_dataset("Check/region_1", streaming=True, split="train"))
Using custom data configuration Check___region_1-d2b3bc48f11c9be2
[{'builder_name': None, 'citation': '', 'config_name': None, 'dataset_size': None, 'description': '', 'download_checksums': None, 'download_size': None, 'features': {'speech': {'feature': {'dtype': 'float64', 'id': None, '_type': 'Value'}, 'length': -1, 'id': None, '_type': 'Sequence'}, 'sampling_rate': {'dtype': 'int64', 'id': None, '_type': 'Value'}, 'label': {'dtype': 'string', 'id': None, '_type': 'Value'}}, 'homepage': '', 'license': '', 'post_processed': None, 'post_processing_size': None, 'size_in_bytes': None, 'splits': None, 'supervised_keys': None, 'task_templates': None, 'version': None}, {'_data_files': [{'filename': 'dataset.arrow'}], '_fingerprint': 'f1702bb5533c549c', '_format_columns': ['speech', 'sampling_rate', 'label'], '_format_kwargs': {}, '_format_type': None, '_indexes': {}, '_indices_data_files': None, '_output_all_columns': False, '_split': None}]
```
## Expected results
The dataset should be loaded
## Actual results
An error occurs
## Environment info
- `datasets` version: 1.14.1.dev0
- Platform: Linux-5.11.0-1020-aws-x86_64-with-glibc2.31
- Python version: 3.9.6
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3176 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3176/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3176/comments | https://api.github.com/repos/huggingface/datasets/issues/3176/events | https://github.com/huggingface/datasets/pull/3176 | 1,039,068,312 | PR_kwDODunzps4t00xS | 3,176 | OpenSLR dataset: update generate_examples to properly extract data for SLR83 | {
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"Also fix #3125."
] | 1,635,469,167,000 | 1,636,042,845,000 | 1,635,501,849,000 | CONTRIBUTOR | null | Fixed #3168.
The SLR38 indices are CSV files and there wasn't any code in openslr.py to process these files properly. The end result was an empty table.
I've added code to properly process these CSV files. | {
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https://api.github.com/repos/huggingface/datasets/issues/3175 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3175/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3175/comments | https://api.github.com/repos/huggingface/datasets/issues/3175/events | https://github.com/huggingface/datasets/pull/3175 | 1,038,945,271 | PR_kwDODunzps4t0bXw | 3,175 | Add docs for `to_tf_dataset` | {
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"This looks great, thank you!",
"Thanks !\r\n\r\nFor some reason the new GIF is 6MB, which is a bit heavy for an image on a website. The previous one was around 200KB though which is perfect. For a good experience we usually expect images to be less than 500KB - otherwise for users with poor connection it takes too long to load. Could you try to reduce its size ? Than I think we can merge :)"
] | 1,635,454,522,000 | 1,635,953,976,000 | 1,635,934,043,000 | CONTRIBUTOR | null | This PR adds some documentation for new features released in v1.13.0, with the main addition being `to_tf_dataset`:
- Show how to use `to_tf_dataset` in the tutorial, and move `set_format(type='tensorflow'...)` to the Process section (let me know if I'm missing anything @Rocketknight1 π
).
- Add an example for loading dataset from multiple zipped CSV files to the Load section.
- Add an example for removing columns for an `IterableDataset`.
- Add graphic for visualizing streaming. | {
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https://api.github.com/repos/huggingface/datasets/issues/3174 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3174/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3174/comments | https://api.github.com/repos/huggingface/datasets/issues/3174/events | https://github.com/huggingface/datasets/pull/3174 | 1,038,427,245 | PR_kwDODunzps4tyuQ_ | 3,174 | Asserts replaced by exceptions (huggingface#3171) | {
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"Your first PR went smoothly, well done!\r\nYou are welcome to continue contributing to this project.\r\nGrΓ cies, @joseporiolayats! π "
] | 1,635,422,145,000 | 1,636,180,532,000 | 1,635,512,923,000 | CONTRIBUTOR | null | I've replaced two asserts with their proper exceptions following the guidelines described in issue #3171 by following the contributing guidelines.
PS: This is one of my first PRs, hoping I don't break anything! | {
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https://api.github.com/repos/huggingface/datasets/issues/3173 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3173/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3173/comments | https://api.github.com/repos/huggingface/datasets/issues/3173/events | https://github.com/huggingface/datasets/pull/3173 | 1,038,404,300 | PR_kwDODunzps4typcA | 3,173 | Fix issue with filelock filename being too long on encrypted filesystems | {
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Fix #2924
cc: @lmmx | {
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https://api.github.com/repos/huggingface/datasets/issues/3172 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3172/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3172/comments | https://api.github.com/repos/huggingface/datasets/issues/3172/events | https://github.com/huggingface/datasets/issues/3172 | 1,038,351,587 | I_kwDODunzps494_zj | 3,172 | `SystemError 15` thrown in `Dataset.__del__` when using `Dataset.map()` with `num_proc>1` | {
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"NB: even if the error is raised, the dataset is successfully cached. So restarting the script after every `map()` allows to ultimately run the whole preprocessing. But this prevents to realistically run the code over multiple nodes.",
"Hi,\r\n\r\nIt's not easy to debug the problem without the script. I may be wrong since I'm not very familiar with PyTorch Lightning, but shouldn't you preprocess the data in the `prepare_data` function of `LightningDataModule` and not in the `setup` function.\r\nAs you can't modify the module state in `prepare_data` (according to the docs), use the `cache_file_name` argument in `Dataset.map` there, and reload the processed data in `setup` with `Dataset.from_file(cache_file_name)`. If `num_proc>1`, check the docs on the `suffix_template` argument of `Dataset.map` to get an idea what the final `cache_file_names` are going to be.\r\n\r\nLet me know if this helps.",
"Hi @mariosasko, thank you for the hint, that helped me to move forward with that issue. \r\n\r\nI did a major refactoring of my project to disentangle my `LightningDataModule` and `Dataset`. Just FYI, it looks like:\r\n\r\n```python\r\nclass Builder():\r\n def __call__() -> DatasetDict:\r\n # load and preprocess the data\r\n return dataset\r\n\r\nclass DataModule(LightningDataModule):\r\n def prepare_data():\r\n self.builder()\r\n def setup():\r\n self.dataset = self.builder()\r\n```\r\n\r\nUnfortunately, the entanglement between `LightningDataModule` and `Dataset` was not the issue.\r\n\r\nThe culprit was `hydra` and a slight adjustment of the structure of my project solved this issue. The problematic project structure was:\r\n\r\n```\r\nsrc/\r\n | - cli.py\r\n | - training/\r\n | -experiment.py\r\n\r\n# code in experiment.py\r\ndef run_experiment(config):\r\n # preprocess data and run\r\n \r\n# code in cli.py\r\n@hydra.main(...)\r\ndef run(config):\r\n return run_experiment(config)\r\n```\r\n\r\nMoving `run()` from `clip.py` to `training.experiment.py` solved the issue with `SystemError 15`. No idea why. \r\n\r\nEven if the traceback was referring to `Dataset.__del__`, the problem does not seem to be primarily related to `datasets`, so I will close this issue. Thank you for your help!"
] | 1,635,416,940,000 | 1,635,938,872,000 | 1,635,938,770,000 | NONE | null | ## Describe the bug
I use `datasets.map` to preprocess some data in my application. The error `SystemError 15` is thrown at the end of the execution of `Dataset.map()` (only with `num_proc>1`. Traceback included bellow.
The exception is raised only when the code runs within a specific context. Despite ~10h spent investigating this issue, I have failed to isolate the bug, so let me describe my setup.
In my project, `Dataset` is wrapped into a `LightningDataModule` and the data is preprocessed when calling `LightningDataModule.setup()`. Calling `.setup()` in an isolated script works fine (even when wrapped with `hydra.main()`). However, when calling `.setup()` within the experiment script (depends on `pytorch_lightning`), the script crashes and `SystemError 15`.
I could avoid throwing this error by modifying ` Dataset.__del__()` (see bellow), but I believe this only moves the problem somewhere else. I am completely stuck with this issue, any hint would be welcome.
```python
class Dataset()
...
def __del__(self):
if hasattr(self, "_data"):
_ = self._data # <- ugly trick that allows avoiding the issue.
del self._data
if hasattr(self, "_indices"):
del self._indices
```
## Steps to reproduce the bug
```python
# Unfortunately I couldn't isolate the bug.
```
## Expected results
Calling `Dataset.map()` without throwing an exception. Or at least raising a more detailed exception/traceback.
## Actual results
```
Exception ignored in: <function Dataset.__del__ at 0x7f7cec179160>βββββββββββββββββββββββββββββββββββββββββββββββββββ| 5/5 [00:05<00:00, 1.17ba/s]
Traceback (most recent call last):
File ".../python3.8/site-packages/datasets/arrow_dataset.py", line 906, in __del__
del self._data
File ".../python3.8/site-packages/ray/worker.py", line 1033, in sigterm_handler
sys.exit(signum)
SystemExit: 15
```
## Environment info
Tested on 2 environments:
**Environment 1.**
- `datasets` version: 1.14.0
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.8
- PyArrow version: 6.0.0
**Environment 2.**
- `datasets` version: 1.14.0
- Platform: Linux-4.18.0-305.19.1.el8_4.x86_64-x86_64-with-glibc2.28
- Python version: 3.9.7
- PyArrow version: 6.0.0
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This PR fixes the problem with the different ordering of the example keys across different Python sessions caused by the `zip_dict` call in `Features.decode_example`. | {
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