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https://api.github.com/repos/huggingface/datasets/issues/4311 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4311/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4311/comments | https://api.github.com/repos/huggingface/datasets/issues/4311/events | https://github.com/huggingface/datasets/pull/4311 | 1,231,369,438 | PR_kwDODunzps43ln8- | 4,311 | [Imagefolder] Docs + Don't infer labels from file names when there are metadata + Error messages when metadata and images aren't linked correctly | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Merging this one since mario is off, I took care of adding some tests to make sure everything is fine. Will do the release after it"
] | 1,652,197,935,000 | 1,652,203,182,000 | 1,652,202,707,000 | MEMBER | null | false | {
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} | I updated the `docs/source/image_process.mdx` documentation and added an example for image captioning and object detection using `ImageFolder`.
While doing so I also improved a few aspects:
- we don't need to infer labels from file names when there are metadata - they can just be in the metadata if necessary
- raise informative error messages when metadata and images aren't linked correctly:
- when an image is missing a metadata file
- when a metadata file is missing an image
I added some tests for these changes as well
cc @mariosasko | {
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https://api.github.com/repos/huggingface/datasets/issues/4310 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4310/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4310/comments | https://api.github.com/repos/huggingface/datasets/issues/4310/events | https://github.com/huggingface/datasets/issues/4310 | 1,231,319,815 | I_kwDODunzps5JZHMH | 4,310 | Loading dataset with streaming: '_io.BufferedReader' object has no attribute 'loc' | {
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] | open | false | null | [] | null | [] | 1,652,195,573,000 | 1,652,195,573,000 | null | NONE | null | null | null | ## Describe the bug
Loading a datasets with `load_dataset` and `streaming=True` returns `AttributeError: '_io.BufferedReader' object has no attribute 'loc'`. Notice that loading with `streaming=False` works fine.
In the following steps we load parquet files but the same happens with pickle files. The problem seems to come from `fsspec` lib, I put in the environment info also `s3fs` and `fsspec` versions since I'm loading from an s3 bucket.
## Steps to reproduce the bug
```python
from datasets import load_dataset
# path is the path to parquet files
data_files = {"train": path + "meta_train.parquet.gzip", "test": path + "meta_test.parquet.gzip"}
dataset = load_dataset("parquet", data_files=data_files, streaming=True)
```
## Expected results
A dataset object `datasets.dataset_dict.DatasetDict`
## Actual results
```
AttributeError Traceback (most recent call last)
<command-562086> in <module>
11
12 data_files = {"train": path + "meta_train.parquet.gzip", "test": path + "meta_test.parquet.gzip"}
---> 13 dataset = load_dataset("parquet", data_files=data_files, streaming=True)
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)
1679 if streaming:
1680 extend_dataset_builder_for_streaming(builder_instance, use_auth_token=use_auth_token)
-> 1681 return builder_instance.as_streaming_dataset(
1682 split=split,
1683 use_auth_token=use_auth_token,
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/builder.py in as_streaming_dataset(self, split, base_path, use_auth_token)
904 )
905 self._check_manual_download(dl_manager)
--> 906 splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}
907 # By default, return all splits
908 if split is None:
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/packaged_modules/parquet/parquet.py in _split_generators(self, dl_manager)
30 if not self.config.data_files:
31 raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
---> 32 data_files = dl_manager.download_and_extract(self.config.data_files)
33 if isinstance(data_files, (str, list, tuple)):
34 files = data_files
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in download_and_extract(self, url_or_urls)
798
799 def download_and_extract(self, url_or_urls):
--> 800 return self.extract(self.download(url_or_urls))
801
802 def iter_archive(self, urlpath_or_buf: Union[str, io.BufferedReader]) -> Iterable[Tuple]:
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in extract(self, path_or_paths)
776
777 def extract(self, path_or_paths):
--> 778 urlpaths = map_nested(self._extract, path_or_paths, map_tuple=True)
779 return urlpaths
780
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, types, disable_tqdm, desc)
312 num_proc = 1
313 if num_proc <= 1 or len(iterable) <= num_proc:
--> 314 mapped = [
315 _single_map_nested((function, obj, types, None, True, None))
316 for obj in logging.tqdm(iterable, disable=disable_tqdm, desc=desc)
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in <listcomp>(.0)
313 if num_proc <= 1 or len(iterable) <= num_proc:
314 mapped = [
--> 315 _single_map_nested((function, obj, types, None, True, None))
316 for obj in logging.tqdm(iterable, disable=disable_tqdm, desc=desc)
317 ]
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in _single_map_nested(args)
267 return {k: _single_map_nested((function, v, types, None, True, None)) for k, v in pbar}
268 else:
--> 269 mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]
270 if isinstance(data_struct, list):
271 return mapped
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in <listcomp>(.0)
267 return {k: _single_map_nested((function, v, types, None, True, None)) for k, v in pbar}
268 else:
--> 269 mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]
270 if isinstance(data_struct, list):
271 return mapped
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/py_utils.py in _single_map_nested(args)
249 # Singleton first to spare some computation
250 if not isinstance(data_struct, dict) and not isinstance(data_struct, types):
--> 251 return function(data_struct)
252
253 # Reduce logging to keep things readable in multiprocessing with tqdm
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _extract(self, urlpath)
781 def _extract(self, urlpath: str) -> str:
782 urlpath = str(urlpath)
--> 783 protocol = _get_extraction_protocol(urlpath, use_auth_token=self.download_config.use_auth_token)
784 if protocol is None:
785 # no extraction
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _get_extraction_protocol(urlpath, use_auth_token)
371 urlpath, kwargs = urlpath, {}
372 with fsspec.open(urlpath, **kwargs) as f:
--> 373 return _get_extraction_protocol_with_magic_number(f)
374
375
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _get_extraction_protocol_with_magic_number(f)
335 def _get_extraction_protocol_with_magic_number(f) -> Optional[str]:
336 """read the magic number from a file-like object and return the compression protocol"""
--> 337 prev_loc = f.loc
338 magic_number = f.read(MAGIC_NUMBER_MAX_LENGTH)
339 f.seek(prev_loc)
/local_disk0/.ephemeral_nfs/envs/pythonEnv-a7e72260-221c-472b-85f4-bec801aee66d/lib/python3.8/site-packages/fsspec/implementations/local.py in __getattr__(self, item)
337
338 def __getattr__(self, item):
--> 339 return getattr(self.f, item)
340
341 def __enter__(self):
AttributeError: '_io.BufferedReader' object has no attribute 'loc'
```
## Environment info
- `datasets` version: 2.1.0
- Platform: Linux-5.4.0-1071-aws-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 8.0.0
- Pandas version: 1.4.2
- `fsspec` version: 2021.08.1
- `s3fs` version: 2021.08.1 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4309). All of your documentation changes will be reflected on that endpoint.",
"```python\r\nfrom datasets import load_dataset\r\n\r\nds = load_dataset('./datasets/tedlium', 'release1', cache_dir='/home/sanchitgandhi/cache')\r\n```\r\n\r\n```\r\nDownloading and preparing dataset tedlium/release1 to /home/sanchitgandhi/cache/tedlium/release1/1.0.1/5a9fcb97b4b52d5a1c9dc7bde4b1d5994cd89c4a3425ea36c789bf6096fee4f0...\r\nTraceback (most recent call last):\r\n File \"<string>\", line 1, in <module>\r\n File \"/home/sanchit_huggingface_co/datasets/src/datasets/load.py\", line 1703, in load_dataset\r\n builder_instance.download_and_prepare(\r\n File \"/home/sanchit_huggingface_co/datasets/src/datasets/builder.py\", line 605, in download_and_prepare\r\n self._download_and_prepare(\r\n File \"/home/sanchit_huggingface_co/datasets/src/datasets/builder.py\", line 1240, in _download_and_prepare\r\n raise MissingBeamOptions(\r\ndatasets.builder.MissingBeamOptions: Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided in `load_dataset` or in the builder arguments. For big datasets it has to run on large-scale data processing tools like Dataflow, Spark, etc. More information about Apache Beam runners at https://beam.apache.org/documentation/runners/capability-matrix/\r\nIf you really want to run it locally because you feel like the Dataset is small enough, you can use the local beam runner called `DirectRunner` (you may run out of memory). \r\nExample of usage: \r\n `load_dataset('tedlium', 'release1', beam_runner='DirectRunner')`\r\n```\r\nSpecifying the `beam_runner='DirectRunner'` works:\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nds = load_dataset('./datasets/tedlium', 'release1', cache_dir='/home/sanchitgandhi/cache', beam_runner='DirectRunner')\r\n```"
] | 1,652,191,967,000 | 1,652,200,645,000 | null | CONTRIBUTOR | null | false | {
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} | Adds the TED-LIUM dataset https://www.tensorflow.org/datasets/catalog/tedlium#tedliumrelease3
TODO:
- [x] Port `tedium.py` from TF datasets using `convert_dataset.sh` script
- [ ] Make `load_dataset` work
- [ ] Run `datasets-cli` command to generate `dataset_infos.json`
- [ ] Create dummy data for continuous testing
- [ ] Dummy data tests
- [ ] Real data tests
- [ ] Create the metadata JSON
- [ ] Close PR and add directly to the Hub under LIUM org | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,652,189,659,000 | 1,652,191,430,000 | 1,652,190,954,000 | MEMBER | null | false | {
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} | Add the packaged builders configurations to the docs reference is useful to show the list of all parameters one can use when loading data in many formats: CSV, JSON, etc. | {
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https://api.github.com/repos/huggingface/datasets/issues/4306 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4306/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4306/comments | https://api.github.com/repos/huggingface/datasets/issues/4306/events | https://github.com/huggingface/datasets/issues/4306 | 1,231,137,204 | I_kwDODunzps5JYam0 | 4,306 | `load_dataset` does not work with certain filename. | {
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"Never mind. It is because of the caching of datasets..."
] | 1,652,188,444,000 | 1,652,209,116,000 | 1,652,209,089,000 | NONE | null | null | null | ## Describe the bug
This is a weird bug that took me some time to find out.
I have a JSON dataset that I want to load with `load_dataset` like this:
```
data_files = dict(train="train.json.zip", val="val.json.zip")
dataset = load_dataset("json", data_files=data_files, field="data")
```
## Expected results
No error.
## Actual results
The val file is loaded as expected, but the train file throws JSON decoding error:
```
╭──────────────────────────── Traceback (most recent call last) ────────────────────────────╮
│ <ipython-input-74-97947e92c100>:5 in <module> │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/site-packages/datasets/load.py:1687 in │
│ load_dataset │
│ │
│ 1684 │ try_from_hf_gcs = path not in _PACKAGED_DATASETS_MODULES │
│ 1685 │ │
│ 1686 │ # Download and prepare data │
│ ❱ 1687 │ builder_instance.download_and_prepare( │
│ 1688 │ │ download_config=download_config, │
│ 1689 │ │ download_mode=download_mode, │
│ 1690 │ │ ignore_verifications=ignore_verifications, │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/site-packages/datasets/builder.py:605 in │
│ download_and_prepare │
│ │
│ 602 │ │ │ │ │ │ except ConnectionError: │
│ 603 │ │ │ │ │ │ │ logger.warning("HF google storage unreachable. Downloa │
│ 604 │ │ │ │ │ if not downloaded_from_gcs: │
│ ❱ 605 │ │ │ │ │ │ self._download_and_prepare( │
│ 606 │ │ │ │ │ │ │ dl_manager=dl_manager, verify_infos=verify_infos, **do │
│ 607 │ │ │ │ │ │ ) │
│ 608 │ │ │ │ │ # Sync info │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/site-packages/datasets/builder.py:694 in │
│ _download_and_prepare │
│ │
│ 691 │ │ │ │
│ 692 │ │ │ try: │
│ 693 │ │ │ │ # Prepare split will record examples associated to the split │
│ ❱ 694 │ │ │ │ self._prepare_split(split_generator, **prepare_split_kwargs) │
│ 695 │ │ │ except OSError as e: │
│ 696 │ │ │ │ raise OSError( │
│ 697 │ │ │ │ │ "Cannot find data file. " │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/site-packages/datasets/builder.py:1151 in │
│ _prepare_split │
│ │
│ 1148 │ │ │
│ 1149 │ │ generator = self._generate_tables(**split_generator.gen_kwargs) │
│ 1150 │ │ with ArrowWriter(features=self.info.features, path=fpath) as writer: │
│ ❱ 1151 │ │ │ for key, table in logging.tqdm( │
│ 1152 │ │ │ │ generator, unit=" tables", leave=False, disable=True # not loggin │
│ 1153 │ │ │ ): │
│ 1154 │ │ │ │ writer.write_table(table) │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/site-packages/tqdm/notebook.py:257 in │
│ __iter__ │
│ │
│ 254 │ │
│ 255 │ def __iter__(self): │
│ 256 │ │ try: │
│ ❱ 257 │ │ │ for obj in super(tqdm_notebook, self).__iter__(): │
│ 258 │ │ │ │ # return super(tqdm...) will not catch exception │
│ 259 │ │ │ │ yield obj │
│ 260 │ │ # NB: except ... [ as ...] breaks IPython async KeyboardInterrupt │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/site-packages/tqdm/std.py:1183 in │
│ __iter__ │
│ │
│ 1180 │ │ # If the bar is disabled, then just walk the iterable │
│ 1181 │ │ # (note: keep this check outside the loop for performance) │
│ 1182 │ │ if self.disable: │
│ ❱ 1183 │ │ │ for obj in iterable: │
│ 1184 │ │ │ │ yield obj │
│ 1185 │ │ │ return │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/site-packages/datasets/packaged_modules/j │
│ son/json.py:90 in _generate_tables │
│ │
│ 87 │ │ │ # If the file is one json object and if we need to look at the list of │
│ 88 │ │ │ if self.config.field is not None: │
│ 89 │ │ │ │ with open(file, encoding="utf-8") as f: │
│ ❱ 90 │ │ │ │ │ dataset = json.load(f) │
│ 91 │ │ │ │ │
│ 92 │ │ │ │ # We keep only the field we are interested in │
│ 93 │ │ │ │ dataset = dataset[self.config.field] │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/json/__init__.py:293 in load │
│ │
│ 290 │ To use a custom ``JSONDecoder`` subclass, specify it with the ``cls`` │
│ 291 │ kwarg; otherwise ``JSONDecoder`` is used. │
│ 292 │ """ │
│ ❱ 293 │ return loads(fp.read(), │
│ 294 │ │ cls=cls, object_hook=object_hook, │
│ 295 │ │ parse_float=parse_float, parse_int=parse_int, │
│ 296 │ │ parse_constant=parse_constant, object_pairs_hook=object_pairs_hook, **kw) │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/json/__init__.py:357 in loads │
│ │
│ 354 │ if (cls is None and object_hook is None and │
│ 355 │ │ │ parse_int is None and parse_float is None and │
│ 356 │ │ │ parse_constant is None and object_pairs_hook is None and not kw): │
│ ❱ 357 │ │ return _default_decoder.decode(s) │
│ 358 │ if cls is None: │
│ 359 │ │ cls = JSONDecoder │
│ 360 │ if object_hook is not None: │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/json/decoder.py:337 in decode │
│ │
│ 334 │ │ containing a JSON document). │
│ 335 │ │ │
│ 336 │ │ """ │
│ ❱ 337 │ │ obj, end = self.raw_decode(s, idx=_w(s, 0).end()) │
│ 338 │ │ end = _w(s, end).end() │
│ 339 │ │ if end != len(s): │
│ 340 │ │ │ raise JSONDecodeError("Extra data", s, end) │
│ │
│ /home/tiankang/software/anaconda3/lib/python3.8/json/decoder.py:353 in raw_decode │
│ │
│ 350 │ │ │
│ 351 │ │ """ │
│ 352 │ │ try: │
│ ❱ 353 │ │ │ obj, end = self.scan_once(s, idx) │
│ 354 │ │ except StopIteration as err: │
│ 355 │ │ │ raise JSONDecodeError("Expecting value", s, err.value) from None │
│ 356 │ │ return obj, end │
╰───────────────────────────────────────────────────────────────────────────────────────────╯
JSONDecodeError: Unterminated string starting at: line 85 column 20 (char 60051)
```
However, when I rename the `train.json.zip` to other names (like `training.json.zip`, or even to `train.json`), everything works fine; when I unzip the file to `train.json`, it works as well.
## Environment info
```
- `datasets` version: 2.1.0
- Platform: Linux-4.4.0-131-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyArrow version: 7.0.0
- Pandas version: 1.4.2
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4305 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4305/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4305/comments | https://api.github.com/repos/huggingface/datasets/issues/4305/events | https://github.com/huggingface/datasets/pull/4305 | 1,231,099,934 | PR_kwDODunzps43kt4P | 4,305 | Fixes FrugalScore | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4305). All of your documentation changes will be reflected on that endpoint."
] | 1,652,186,646,000 | 1,652,187,343,000 | null | CONTRIBUTOR | null | false | {
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} | There are two minor modifications in this PR:
1) `predictions` and `references` are swapped. Basically Frugalscore is commutative, however some tiny differences can occur if we swap the references and the predictions. I decided to swap them just to obtain the exact results as reported in the paper.
2) I switched to dynamic padding that was was used in the training, forcing the padding to `max_length` introduces errors for some reason that I ignore.
@lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/4304 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4304/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4304/comments | https://api.github.com/repos/huggingface/datasets/issues/4304/events | https://github.com/huggingface/datasets/issues/4304 | 1,231,047,051 | I_kwDODunzps5JYEmL | 4,304 | Language code search does direct matches | {
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"Thanks for reporting ! I forwarded the issue to the front-end team :)\r\n\r\nWill keep you posted !\r\n\r\nI also changed the tagging app to suggest two letters code for now."
] | 1,652,183,956,000 | 1,652,186,322,000 | null | NONE | null | null | null | ## Describe the bug
Hi. Searching for bcp47 tags that are just the language prefix (e.g. `sq` or `da`) excludes datasets that have added extra information in their language metadata (e.g. `sq-AL` or `da-bornholm`). The example codes given in the [tagging app](https://huggingface.co/spaces/huggingface/datasets-tagging) encourages addition of the additional codes ("_expected format is BCP47 tags separated for ';' e.g. 'en-US;fr-FR'_") but this would lead to those datasets being hidden in datasets search.
## Steps to reproduce the bug
1. Add a dataset using a variant tag (e.g. [`sq-AL`](https://huggingface.co/datasets?languages=languages:sq-AL))
2. Look for datasets using the full code
3. Note that they're missing when just the language is searched for (e.g. [`sq`](https://huggingface.co/datasets?languages=languages:sq))
Some datasets are already affected by this - e.g. `AmazonScience/massive` is listed under `sq-AL` but not `sq`.
One workaround is for dataset creators to add an additional root language tag to dataset YAML metadata, but it's unclear how to communicate this. It might be possible to index the search on `languagecode.split('-')[0]` but I wanted to float this issue before trying to write any code :)
## Expected results
Datasets using longer bcp47 tags also appear under searches for just the language code; e.g. Quebecois datasets (`fr-CA`) would come up when looking for French datasets with no region specification (`fr`), or US English (`en-US`) datasets would come up when searching for English datasets (`en`).
## Actual results
The language codes seem to be directly string matched, excluding datasets with specific language tags from non-specific searches.
## Environment info
(web app) | {
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https://api.github.com/repos/huggingface/datasets/issues/4303 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4303/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4303/comments | https://api.github.com/repos/huggingface/datasets/issues/4303/events | https://github.com/huggingface/datasets/pull/4303 | 1,230,867,728 | PR_kwDODunzps43j8cH | 4,303 | Fix: Add missing comma | {
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https://api.github.com/repos/huggingface/datasets/issues/4302 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4302/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4302/comments | https://api.github.com/repos/huggingface/datasets/issues/4302/events | https://github.com/huggingface/datasets/pull/4302 | 1,230,651,117 | PR_kwDODunzps43jPE5 | 4,302 | Remove hacking license tags when mirroring datasets on the Hub | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4302). All of your documentation changes will be reflected on that endpoint.",
"The Hub doesn't allow these characters in the YAML tags, and git push fails if you want to push a dataset card containing these characters."
] | 1,652,161,966,000 | 1,652,204,850,000 | null | MEMBER | null | false | {
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I guess this hacking is no longer necessary:
- it is not applied to community datasets
- all canonical datasets are validated by maintainers before being merged: CI + maintainers make sure license tags are the right ones
Fix #4298. | {
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https://api.github.com/repos/huggingface/datasets/issues/4301 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4301/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4301/comments | https://api.github.com/repos/huggingface/datasets/issues/4301/events | https://github.com/huggingface/datasets/pull/4301 | 1,230,401,256 | PR_kwDODunzps43idlE | 4,301 | Add ImageNet-Sketch dataset | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4301). All of your documentation changes will be reflected on that endpoint."
] | 1,652,139,525,000 | 1,652,211,471,000 | null | CONTRIBUTOR | null | false | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4300). All of your documentation changes will be reflected on that endpoint."
] | 1,652,131,826,000 | 1,652,132,501,000 | null | MEMBER | null | false | {
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} | This PR adds API code examples for loading methods, let me know if I've missed any important parameters we should showcase :)
I was a bit confused about `inspect_dataset` and `inspect_metric`. The `path` parameter says it will accept a dataset identifier from the Hub. But when I try the identifier `rotten_tomatoes`, it gives me:
```py
from datasets import inspect_dataset
inspect_dataset('rotten_tomatoes', local_path='/content/rotten_tomatoes')
FileNotFoundError: Couldn't find a dataset script at /content/rotten_tomatoes/rotten_tomatoes.py or any data file in the same directory.
```
Does the user need to have an existing copy of `rotten_tomatoes.py` on their local drive (in which case, it seems like the same option as the first option in `path`)? | {
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https://api.github.com/repos/huggingface/datasets/issues/4299 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4299/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4299/comments | https://api.github.com/repos/huggingface/datasets/issues/4299/events | https://github.com/huggingface/datasets/pull/4299 | 1,230,236,782 | PR_kwDODunzps43h5RP | 4,299 | Remove manual download from imagenet-1k | {
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"we'll add the same server-side metadata validation system as for hf.co/models soon-ish\r\n\r\n(you can check on hf.co/models that licenses are \"clean\")"
] | 1,652,104,292,000 | 1,652,204,645,000 | null | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
When browsing datasets, the Licenses tag cloud (bottom left of e.g. https://huggingface.co/datasets) has multiple variants of the same license. This means the options exclude datasets arbitrarily, giving users artificially low recall. The cause of the dupes is probably due to a bit of variation in metadata.
**Describe the solution you'd like**
I'd like the licenses in metadata to follow the same standard as much as possible, to remove this problem. I'd like to go ahead and normalise the dataset metadata to follow the format & values given in [src/datasets/utils/resources/licenses.json](https://github.com/huggingface/datasets/blob/master/src/datasets/utils/resources/licenses.json) .
**Describe alternatives you've considered**
None
**Additional context**
None
**Priority**
Low
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https://api.github.com/repos/huggingface/datasets/issues/4297 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4297/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4297/comments | https://api.github.com/repos/huggingface/datasets/issues/4297/events | https://github.com/huggingface/datasets/issues/4297 | 1,229,735,498 | I_kwDODunzps5JTEZK | 4,297 | Datasets YAML tagging space is down | {
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"@lhoestq @albertvillanova `update-task-list` branch does not exist anymore, should point to `main` now i guess",
"Thanks for reporting, fixing it now",
"It's up again :)"
] | 1,652,103,905,000 | 1,652,107,465,000 | 1,652,107,465,000 | NONE | null | null | null | ## Describe the bug
The neat hf spaces app for generating YAML tags for dataset `README.md`s is down
## Steps to reproduce the bug
1. Visit https://huggingface.co/spaces/huggingface/datasets-tagging
## Expected results
There'll be a HF spaces web app for generating dataset metadata YAML
## Actual results
There's an error message; here's the step where it breaks:
```
Step 18/29 : RUN pip install -r requirements.txt
---> Running in e88bfe7e7e0c
Defaulting to user installation because normal site-packages is not writeable
Collecting git+https://github.com/huggingface/datasets.git@update-task-list (from -r requirements.txt (line 4))
Cloning https://github.com/huggingface/datasets.git (to revision update-task-list) to /tmp/pip-req-build-bm8t0r0k
Running command git clone --filter=blob:none --quiet https://github.com/huggingface/datasets.git /tmp/pip-req-build-bm8t0r0k
WARNING: Did not find branch or tag 'update-task-list', assuming revision or ref.
Running command git checkout -q update-task-list
error: pathspec 'update-task-list' did not match any file(s) known to git
error: subprocess-exited-with-error
× git checkout -q update-task-list did not run successfully.
│ exit code: 1
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
error: subprocess-exited-with-error
× git checkout -q update-task-list did not run successfully.
│ exit code: 1
╰─> See above for output.
```
## Environment info
- Platform: Linux / Brave
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"_The documentation is not available anymore as the PR was closed or merged._"
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```
TypeError: _download_and_prepare() got an unexpected keyword argument 'save_infos'
``` | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4293). All of your documentation changes will be reflected on that endpoint."
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4292). All of your documentation changes will be reflected on that endpoint."
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"Hi @leondz, thanks for reporting.\r\n\r\nIndeed, the dataset viewer relies on the dataset being streamable (passing `streaming=True` to `load_dataset`). Whereas most of the datastes are streamable out of the box (thanks to our implementation of streaming), there are still some exceptions.\r\n\r\nIn particular, in your case, that is due to the data file being TAR. This format is not streamable out of the box (it does not allow random access to the archived files), but we use a trick to allow streaming: using `dl_manager.iter_archive`.\r\n\r\nLet me know if you need some help: I could push a commit to your repo with the fix.",
"Ah, right! The preview is working now, but this explanation is good to know, thank you. I'll prefer formats with random file access supported in datasets.utils.extract in future, and try out this fix for the tarfiles :)"
] | 1,651,838,607,000 | 1,652,084,758,000 | 1,652,084,758,000 | NONE | null | null | null | ### Link
https://huggingface.co/datasets/strombergnlp/ipm_nel/viewer/ipm_nel/train
### Description
The viewer is blank. I tried my best to emulate a dataset with a working viewer, but this one just doesn't seem to want to come up. What did I miss?
### Owner
Yes | {
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"So I managed to solve this by adding a missing `import faiss` in the `@staticmethod` defined in https://github.com/huggingface/datasets/blob/f51b6994db27ea69261ef919fb7775928f9ec10b/src/datasets/search.py#L305, triggered from https://github.com/huggingface/datasets/blob/f51b6994db27ea69261ef919fb7775928f9ec10b/src/datasets/search.py#L249 when trying to `ds_with_embeddings.add_faiss_index(column='embeddings', device=0)` with the code above.\r\n\r\nAs it seems that the `@staticmethod` doesn't recognize the `import faiss` defined in https://github.com/huggingface/datasets/blob/f51b6994db27ea69261ef919fb7775928f9ec10b/src/datasets/search.py#L261, so whenever the value of `device` is not None in https://github.com/huggingface/datasets/blob/71f76e0bdeaddadedc4f9c8d15cfff5a36d62f66/src/datasets/search.py#L438, that exception is triggered.\r\n\r\nSo on, adding `import faiss` inside https://github.com/huggingface/datasets/blob/71f76e0bdeaddadedc4f9c8d15cfff5a36d62f66/src/datasets/search.py#L305 right after the check of `device`'s value, solves the issue and lets you calculate the indices in GPU.\r\n\r\nI'll add the code in a PR linked to this issue in case you want to merge it!",
"Adding here the complete error traceback!\r\n\r\n```\r\nTraceback (most recent call last):\r\n File \"/home/alvarobartt/lol.py\", line 12, in <module>\r\n ds_with_embeddings.add_faiss_index(column='embeddings', device=0) # default `device=None`\r\n File \"/home/alvarobartt/.local/lib/python3.9/site-packages/datasets/arrow_dataset.py\", line 3656, in add_faiss_index\r\n super().add_faiss_index(\r\n File \"/home/alvarobartt/.local/lib/python3.9/site-packages/datasets/search.py\", line 478, in add_faiss_index\r\n faiss_index.add_vectors(self, column=column, train_size=train_size, faiss_verbose=True)\r\n File \"/home/alvarobartt/.local/lib/python3.9/site-packages/datasets/search.py\", line 281, in add_vectors\r\n self.faiss_index = self._faiss_index_to_device(index, self.device)\r\n File \"/home/alvarobartt/.local/lib/python3.9/site-packages/datasets/search.py\", line 327, in _faiss_index_to_device\r\n faiss_res = faiss.StandardGpuResources()\r\nNameError: name 'faiss' is not defined\r\n```",
"Closed as https://github.com/huggingface/datasets/pull/4288 already merged! :hugs:"
] | 1,651,763,385,000 | 1,652,190,799,000 | 1,652,190,799,000 | CONTRIBUTOR | null | null | null | ## Describe the bug
When using `datasets` to calculate the FAISS indices of a dataset, the exception `NameError: name 'faiss' is not defined` is triggered when trying to calculate those on a device (GPU), so `.add_faiss_index(..., device=0)` fails with that exception.
All that assuming that `datasets` is properly installed and `faiss-gpu` too, as well as all the CUDA drivers required.
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
from transformers import DPRContextEncoder, DPRContextEncoderTokenizer
import torch
torch.set_grad_enabled(False)
ctx_encoder = DPRContextEncoder.from_pretrained("facebook/dpr-ctx_encoder-single-nq-base")
ctx_tokenizer = DPRContextEncoderTokenizer.from_pretrained("facebook/dpr-ctx_encoder-single-nq-base")
from datasets import load_dataset
ds = load_dataset('crime_and_punish', split='train[:100]')
ds_with_embeddings = ds.map(lambda example: {'embeddings': ctx_encoder(**ctx_tokenizer(example["line"], return_tensors="pt"))[0][0].numpy()})
ds_with_embeddings.add_faiss_index(column='embeddings', device=0) # default `device=None`
```
## Expected results
A new column named `embeddings` in the dataset that we're adding the index to.
## Actual results
An exception is triggered with the following message `NameError: name 'faiss' is not defined`.
## Environment info
- `datasets` version: 2.1.0
- Platform: Linux-5.13.0-1022-azure-x86_64-with-glibc2.31
- Python version: 3.9.12
- PyArrow version: 7.0.0
- Pandas version: 1.4.2
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,651,761,260,000 | 1,652,184,604,000 | 1,652,184,158,000 | CONTRIBUTOR | null | false | {
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} | This language is present in [Wikimedia's WIT](https://huggingface.co/datasets/wikimedia/wit_base) dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/4285 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4285/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4285/comments | https://api.github.com/repos/huggingface/datasets/issues/4285/events | https://github.com/huggingface/datasets/pull/4285 | 1,226,374,831 | PR_kwDODunzps43VtEa | 4,285 | Update LexGLUE README.md | {
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] | 1,651,739,810,000 | 1,651,757,944,000 | 1,651,757,615,000 | CONTRIBUTOR | null | false | {
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https://api.github.com/repos/huggingface/datasets/issues/4284 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4284/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4284/comments | https://api.github.com/repos/huggingface/datasets/issues/4284/events | https://github.com/huggingface/datasets/issues/4284 | 1,226,200,727 | I_kwDODunzps5JFlaX | 4,284 | Issues in processing very large datasets | {
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"Hi ! `datasets` doesn't load the dataset in memory. Instead it uses memory mapping to load your dataset from your disk (it is stored as arrow files). Do you know at what point you have RAM issues exactly ?\r\n\r\nHow big are your graph_data_train dictionaries btw ?"
] | 1,651,726,869,000 | 1,652,184,923,000 | null | NONE | null | null | null | ## Describe the bug
I'm trying to add a feature called "subgraph" to CNN/DM dataset (modifications on run_summarization.py of Huggingface Transformers script) --- I'm not quite sure if I'm doing it the right way, though--- but the main problem appears when the training starts where the error ` [OSError: [Errno 12] Cannot allocate memory]` appears. I suppose this problem roots in RAM issues and how the dataset is loaded during training, but I have no clue of what I can do to fix it. Observing the dataset's cache directory, I see that it takes ~600GB of memory and that's why I believe special care is needed when loading it into the memory.
Here are my modifications to `run_summarization.py` code.
```
# loading pre-computed dictionary where keys are 'id' of article and values are corresponding subgraph
graph_data_train = get_graph_data('train')
graph_data_validation = get_graph_data('val')
...
...
with training_args.main_process_first(desc="train dataset map pre-processing"):
train_dataset = train_dataset.map(
preprocess_function_train,
batched=True,
num_proc=data_args.preprocessing_num_workers,
remove_columns=column_names,
load_from_cache_file=not data_args.overwrite_cache,
desc="Running tokenizer on train dataset",
)
```
And here is the modified preprocessed function:
```
def preprocess_function_train(examples):
inputs, targets, sub_graphs, ids = [], [], [], []
for i in range(len(examples[text_column])):
if examples[text_column][i] is not None and examples[summary_column][i] is not None:
# if examples['doc_id'][i] in graph_data.keys():
inputs.append(examples[text_column][i])
targets.append(examples[summary_column][i])
sub_graphs.append(graph_data_train[examples['id'][i]])
ids.append(examples['id'][i])
inputs = [prefix + inp for inp in inputs]
model_inputs = tokenizer(inputs, max_length=data_args.max_source_length, padding=padding, truncation=True,
sub_graphs=sub_graphs, ids=ids)
# Setup the tokenizer for targets
with tokenizer.as_target_tokenizer():
labels = tokenizer(targets, max_length=max_target_length, padding=padding, truncation=True)
# If we are padding here, replace all tokenizer.pad_token_id in the labels by -100 when we want to ignore
# padding in the loss.
if padding == "max_length" and data_args.ignore_pad_token_for_loss:
labels["input_ids"] = [
[(l if l != tokenizer.pad_token_id else -100) for l in label] for label in labels["input_ids"]
]
model_inputs["labels"] = labels["input_ids"]
return model_inputs
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.1.0
- Platform: Linux Ubuntu
- Python version: 3.6
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/4283 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4283/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4283/comments | https://api.github.com/repos/huggingface/datasets/issues/4283/events | https://github.com/huggingface/datasets/pull/4283 | 1,225,686,988 | PR_kwDODunzps43Tnxo | 4,283 | Fix filesystem docstring | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,651,686,162,000 | 1,651,854,722,000 | 1,651,818,137,000 | MEMBER | null | false | {
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} | This PR untangles the `S3FileSystem` docstring so the [parameters](https://huggingface.co/docs/datasets/master/en/package_reference/main_classes#parameters) are properly displayed. | {
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https://api.github.com/repos/huggingface/datasets/issues/4282 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4282/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4282/comments | https://api.github.com/repos/huggingface/datasets/issues/4282/events | https://github.com/huggingface/datasets/pull/4282 | 1,225,616,545 | PR_kwDODunzps43TZYL | 4,282 | Don't do unnecessary list type casting to avoid replacing None values by empty lists | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Quick question about the message in the warning. You say \"will be fixed in a future major version\" but don't you mean \"will raise an error in a future major version\"?",
"Right ! Good catch, thanks, I updated the message to say \"will raise an error in a future major version\""
] | 1,651,682,221,000 | 1,651,833,838,000 | 1,651,833,420,000 | MEMBER | null | false | {
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} | In certain cases, `None` values are replaced by empty lists when casting feature types.
It happens every time you cast an array of nested lists like [None, [0, 1, 2, 3]] to a different type (to change the integer precision for example). In this case you'd get [[], [0, 1, 2, 3]] for example. This issue comes from PyArrow, see the discussion in https://github.com/huggingface/datasets/issues/3676
This issue also happens when no type casting is needed, because casting is supposed to be a no-op in this case. But as https://github.com/huggingface/datasets/issues/3676 shown, it's not the case and `None` are replaced by empty lists even if we cast to the exact same type.
In this PR I just workaround this bug in the case where no type casting is needed. In particular, I only call `pa.ListArray.from_arrays` only when necessary.
I also added a warning when some `None` are effectively replaced by empty lists. I wanted to raise an error in this case, but maybe we should wait a major update to do so
This PR fixes this particular case, that is occurring in `run_qa.py` in `transformers`:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# before:
# b
# 0 [None, [0]]
# 1 [[], [0]]
# 2 [[], [0]]
# 3 [[], [0]]
#
# now:
# b
# 0 [None, [0]]
# 1 [None, [0]]
# 2 [None, [0]]
# 3 [None, [0]]
```
cc @sgugger | {
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https://api.github.com/repos/huggingface/datasets/issues/4281 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4281/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4281/comments | https://api.github.com/repos/huggingface/datasets/issues/4281/events | https://github.com/huggingface/datasets/pull/4281 | 1,225,556,939 | PR_kwDODunzps43TNBm | 4,281 | Remove a copy-paste sentence in dataset cards | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The non-passing tests have nothing to do with this PR."
] | 1,651,678,915,000 | 1,651,826,283,000 | 1,651,689,196,000 | MEMBER | null | false | {
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} | Remove the following copy-paste sentence from dataset cards:
```
We show detailed information for up to 5 configurations of the dataset.
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4280 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4280/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4280/comments | https://api.github.com/repos/huggingface/datasets/issues/4280/events | https://github.com/huggingface/datasets/pull/4280 | 1,225,446,844 | PR_kwDODunzps43S2xg | 4,280 | Add missing features to commonsense_qa dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"@albertvillanova it adds question_concept and id which is great. I suppose we'll talk about staying true to the format on another PR. ",
"Yes, let's merge this PR as it is: it adds missing features.\r\n\r\nA subsequent PR may address the request on changing the dataset feature structure."
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https://api.github.com/repos/huggingface/datasets/issues/4279 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4279/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4279/comments | https://api.github.com/repos/huggingface/datasets/issues/4279/events | https://github.com/huggingface/datasets/pull/4279 | 1,225,300,273 | PR_kwDODunzps43SXw5 | 4,279 | Update minimal PyArrow version warning | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Let's merge this PR as it is: it adds missing features.\r\n\r\nA subsequent PR may address the request on changing the data feature structure."
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"_The documentation is not available anymore as the PR was closed or merged._",
"Hmm, not sure why the Windows tests are failing with:\r\n\r\n```\r\nDid not find path entry C:\\tools\\miniconda3\\bin\r\nC:\\tools\\miniconda3\\envs\\py37\\python.exe: No module named pytest\r\n```\r\n\r\nEdit: running the CI again fixed the problem 🙃 ",
"> One last nit and we can merge then\r\n\r\nThanks, done!"
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} | This PR extends the `Dataset.align_labels_with_mapping()` method to support alignment of label mappings between datasets and models for token classification (e.g. NER).
Example of usage:
```python
from datasets import load_dataset
ner_ds = load_dataset("conll2003", split="train")
# returns [3, 0, 7, 0, 0, 0, 7, 0, 0]
ner_ds[0]["ner_tags"]
# hypothetical model mapping with O <--> B-LOC
label2id = {
"B-LOC": "0",
"B-MISC": "7",
"B-ORG": "3",
"B-PER": "1",
"I-LOC": "6",
"I-MISC": "8",
"I-ORG": "4",
"I-PER": "2",
"O": "5"
}
ner_aligned_ds = ner_ds.align_labels_with_mapping(label2id, "ner_tags")
# returns [3, 5, 7, 5, 5, 5, 7, 5, 5]
ner_aligned_ds[0]["ner_tags"]
```
Context: we need this in AutoTrain to automatically align datasets / models during evaluation. cc @abhishekkrthakur | {
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"Thanks for reporting, @vblagoje.\r\n\r\nIndeed, I noticed some of these issues while reviewing this PR:\r\n- #4259 \r\n\r\nThis is in my TODO list. ",
"Ok, awesome @albertvillanova How about #4275 ?",
"On the other hand, I am not sure if we should always preserve the original nested structure. I think we should also consider other factors as convenience or consistency.\r\n\r\nFor example, other datasets also flatten \"question.stem\" into \"question\":\r\n- ai2_arc:\r\n ```python\r\n question = data[\"question\"][\"stem\"]\r\n choices = data[\"question\"][\"choices\"]\r\n text_choices = [choice[\"text\"] for choice in choices]\r\n label_choices = [choice[\"label\"] for choice in choices]\r\n yield id_, {\r\n \"id\": id_,\r\n \"answerKey\": answerkey,\r\n \"question\": question,\r\n \"choices\": {\"text\": text_choices, \"label\": label_choices},\r\n }\r\n ```\r\n- commonsense_qa:\r\n ```python\r\n question = data[\"question\"]\r\n stem = question[\"stem\"]\r\n yield id_, {\r\n \"answerKey\": answerkey,\r\n \"question\": stem,\r\n \"choices\": {\"label\": labels, \"text\": texts},\r\n }\r\n ```\r\n- cos_e:\r\n ```python\r\n \"question\": cqa[\"question\"][\"stem\"],\r\n ```\r\n- qasc\r\n- quartz\r\n- wiqa\r\n\r\nExceptions:\r\n- exams\r\n\r\nI think we should agree on a CONVENIENT format for QA and use always CONSISTENTLY the same.",
"@albertvillanova I agree that we should be consistent. In the last month, I have come across tons of code that deals with OpenBookQA and CommonSenseQA and all of that code relies on the original data format structure. We can't expect users to adopt HF Datasets if we arbitrarily change the structure of the format just because we think something makes more sense. I am in that position now (downloading original data rather than using HF Datasets) and undoubtedly it hinders HF Datasets' widespread use and adoption. Missing fields like in the case of #4275 is definitely bad and not even up for a discussion IMHO! cc @lhoestq ",
"I'm opening a PR that adds the missing fields.\r\n\r\nLet's agree on the feature structure: @lhoestq @mariosasko @polinaeterna ",
"IMO we should always try to preserve the original structure unless there is a good reason not to (and I don't see one in this case).",
"I agree with @mariosasko . The transition to the original format could be done in one PR for the next minor release, clearly documenting all dataset changes just as @albertvillanova outlined them above and perhaps even providing a per dataset util method to convert the new valid format to the old for backward compatibility. Users who relied on the old format will update their code with either the util method for a quick fix or slightly more elaborate for the new. ",
"I don't have a strong opinion on this, besides the fact that whatever decision we agree on, should be applied to all datasets.\r\n\r\nThere is always the tension between:\r\n- preserving each dataset original structure (which has the advantage of not forcing users to learn other structure for the same dataset),\r\n- and on the other hand performing some king of standardization/harmonization depending on the task (this has the advantage that once learnt, the same structure applies to all datasets; this has been done for e.g. POS tagging: all datasets have been adapted to a certain \"standard\" structure).\r\n - Another advantage: datasets can easily be interchanged (or joined) to be used by the same model\r\n\r\nRecently, in the BigScience BioMedical hackathon, they adopted a different approach:\r\n- they implement a \"source\" config, respecting the original structure as much as possible\r\n- they implement additional config for each task, with a \"standard\" nested structure per task, which is most useful for users.",
"@albertvillanova, thanks for the detailed answer and the new perspectives. I understand the friction for the best design approach much better now. Ultimately, it is essential to include all the missing fields and the correct data first. Whatever approach is determined to be optimal is important but not as crucial once all the data is there, and users can create lambda functions to create whatever structure serves them best. "
] | 1,651,643,512,000 | 1,652,013,223,000 | null | CONTRIBUTOR | null | null | null | ## Describe the bug
OpenBookQA implementation is inconsistent with the original dataset.
We need to:
1. The dataset field [question][stem] is flattened into question_stem. Unflatten it to match the original format.
2. Add missing additional fields:
- 'fact1': row['fact1'],
- 'humanScore': row['humanScore'],
- 'clarity': row['clarity'],
- 'turkIdAnonymized': row['turkIdAnonymized']
3. Ensure the structure and every data item in the original OpenBookQA matches our OpenBookQA version.
## Expected results
The structure and every data item in the original OpenBookQA matches our OpenBookQA version.
## Actual results
TBD
## Environment info
- `datasets` version: 2.1.0
- Platform: macOS-10.15.7-x86_64-i386-64bit
- Python version: 3.8.13
- PyArrow version: 7.0.0
- Pandas version: 1.4.2 | {
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"Thanks for reporting, @vblagoje.\r\n\r\nI'm opening a PR to address this. "
] | 1,651,642,739,000 | 1,651,664,478,000 | null | CONTRIBUTOR | null | null | null | ## Describe the bug
In short, CommonSenseQA implementation is inconsistent with the original dataset.
More precisely, we need to:
1. Add the dataset matching "id" field. The current dataset, instead, regenerates monotonically increasing id.
2. The [“question”][“stem”] field is flattened into "question". We should match the original dataset and unflatten it
3. Add the missing "question_concept" field in the question tree node
4. Anything else? Go over the data structure of the newly repaired CommonSenseQA and make sure it matches the original
## Expected results
Every data item of the CommonSenseQA should structurally and data-wise match the original CommonSenseQA dataset.
## Actual results
TBD
## Environment info
- `datasets` version: 2.1.0
- Platform: macOS-10.15.7-x86_64-i386-64bit
- Python version: 3.8.13
- PyArrow version: 7.0.0
- Pandas version: 1.4.2 | {
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"> This PR fixes #4271.\r\n\r\nThings have not changed when searching \"tqdm\" in the Dataset document. The second result still performs as \"Enable\".",
"Hi @jiangwy99, the fix will appear on the `main` version of the docs:\r\n\r\n\r\n",
"Fixed now, thanks."
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] | 1,651,599,896,000 | 1,651,647,515,000 | 1,651,647,515,000 | NONE | null | null | null | ## Describe the bug
in the docs of V2.1.0 datasets.disable_progress_bar, we should replace "enable" with "disable". | {
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"It would help a lot to be able to preview the dataset - I'd like to see if the pronunciations are in the dataset, eg. for [\"word\"](https://en.wiktionary.org/wiki/word),\r\n\r\nPronunciation\r\n([Received Pronunciation](https://en.wikipedia.org/wiki/Received_Pronunciation)) [IPA](https://en.wiktionary.org/wiki/Wiktionary:International_Phonetic_Alphabet)([key](https://en.wiktionary.org/wiki/Appendix:English_pronunciation)): /wɜːd/\r\n([General American](https://en.wikipedia.org/wiki/General_American)) [enPR](https://en.wiktionary.org/wiki/Appendix:English_pronunciation): wûrd, [IPA](https://en.wiktionary.org/wiki/Wiktionary:International_Phonetic_Alphabet)([key](https://en.wiktionary.org/wiki/Appendix:English_pronunciation)): /wɝd/",
"Hi @i-am-neo, thanks for reporting.\r\n\r\nNormally this dataset should be private and not accessible for public use. @cakiki, @lvwerra, any reason why is it public? I see many other Wikimedia datasets are also public.\r\n\r\nAlso note that last commit \"Add metadata\" (https://huggingface.co/datasets/bigscience-catalogue-lm-data/lm_en_wiktionary_filtered/commit/dc2f458dab50e00f35c94efb3cd4009996858609) introduced buggy data files (`data/file-01.jsonl.gz.lock`, `data/file-01.jsonl.gz.lock.lock`). The same bug appears in other datasets as well.\r\n\r\n@i-am-neo, please note that in the near future we are planning to make public all datasets used for the BigScience project (at least all of them whose license allows to do that). Once public, they will be accessible for all the NLP community.",
"Ah this must be a bug introduced at creation time since the repos were created programmatically; I'll go ahead and make them private; sorry about that!",
"All datasets are private now. \r\n\r\nRe:that bug I think we're currently avoiding it by avoiding verifications. (i.e. `ignore_verifications=True`)",
"Thanks a lot, @cakiki.\r\n\r\n@i-am-neo, I'm closing this issue for now because the dataset is not publicly available yet. Just stay tuned, as we will soon release all the BigScience open-license datasets. ",
"Thanks for letting me know, @albertvillanova @cakiki.\r\nAny chance of having a subset alpha version in the meantime? \r\nI only need two dicts out of wiktionary: 1) phoneme(as key): word, and 2) word(as key): its phonemes.\r\n\r\nWould like to use it for a mini-poc [Robust ASR](https://github.com/huggingface/transformers/issues/13162#issuecomment-1096881290) decoding, cc @patrickvonplaten. \r\n\r\n(Patrick, possible to email you so as not to litter github with comments? I have some observations after experiments training hubert on some YT AMI-like data (11.44% wer). Also wonder if a robust ASR is on your/HG's roadmap). Thanks!",
"Hey @i-am-neo,\r\n\r\nCool to hear that you're working on Robust ASR! Feel free to drop me a mail :-)",
"@i-am-neo This particular subset of the dataset was taken from the [CirrusSearch dumps](https://dumps.wikimedia.org/other/cirrussearch/current/)\r\nYou're specifically after the [enwiktionary-20220425-cirrussearch-content.json.gz](https://dumps.wikimedia.org/other/cirrussearch/current/enwiktionary-20220425-cirrussearch-content.json.gz) file",
"thanks @cakiki ! <del>I could access the gz file yesterday (but neglected to tuck it away somewhere safe), and today the link is throwing a 404. Can you help? </del> Never mind, got it!",
"thanks @patrickvonplaten. will do - getting my observations together."
] | 1,651,523,665,000 | 1,651,852,410,000 | 1,651,577,028,000 | NONE | null | null | null | ## Describe the bug
Error generated when attempting to download dataset
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("bigscience-catalogue-lm-data/lm_en_wiktionary_filtered")
```
## Expected results
A clear and concise description of the expected results.
## Actual results
```
ExpectedMoreDownloadedFiles Traceback (most recent call last)
[<ipython-input-62-4ac5cf959477>](https://localhost:8080/#) in <module>()
1 from datasets import load_dataset
2
----> 3 dataset = load_dataset("bigscience-catalogue-lm-data/lm_en_wiktionary_filtered")
3 frames
[/usr/local/lib/python3.7/dist-packages/datasets/utils/info_utils.py](https://localhost:8080/#) in verify_checksums(expected_checksums, recorded_checksums, verification_name)
31 return
32 if len(set(expected_checksums) - set(recorded_checksums)) > 0:
---> 33 raise ExpectedMoreDownloadedFiles(str(set(expected_checksums) - set(recorded_checksums)))
34 if len(set(recorded_checksums) - set(expected_checksums)) > 0:
35 raise UnexpectedDownloadedFile(str(set(recorded_checksums) - set(expected_checksums)))
ExpectedMoreDownloadedFiles: {'/home/leandro/catalogue_data/datasets/lm_en_wiktionary_filtered/data/file-01.jsonl.gz', '/home/leandro/catalogue_data/datasets/lm_en_wiktionary_filtered/data/file-01.jsonl.gz.lock'}
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/4267 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4267/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4267/comments | https://api.github.com/repos/huggingface/datasets/issues/4267/events | https://github.com/huggingface/datasets/pull/4267 | 1,223,214,275 | PR_kwDODunzps43LzOR | 4,267 | Replace data URL in SAMSum dataset within the same repository | {
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"_The documentation is not available anymore as the PR was closed or merged._"
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,651,510,771,000 | 1,651,740,440,000 | 1,651,740,009,000 | CONTRIBUTOR | null | false | {
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} | Adds the HF Speech Bench to Librispeech Dataset Card in place of the Papers With Code Leaderboard. Should improve usage and visibility of this leaderboard! Wondering whether this can also be done for [Common Voice 7](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) and [8](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0) through someone with permissions?
cc @patrickvonplaten: more leaderboard promotion! | {
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https://api.github.com/repos/huggingface/datasets/issues/4263 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4263/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4263/comments | https://api.github.com/repos/huggingface/datasets/issues/4263/events | https://github.com/huggingface/datasets/pull/4263 | 1,222,723,083 | PR_kwDODunzps43KLnD | 4,263 | Rename imagenet2012 -> imagenet-1k | {
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"> Later we can add imagenet-21k as a new dataset if we want.\r\n\r\nisn't it what models refer to as `imagenet` already?",
"> isn't it what models refer to as imagenet already?\r\n\r\nI wasn't sure, but it looks like it indeed. Therefore having a dataset `imagenet` for ImageNet 21k makes sense actually.\r\n\r\nEDIT: actually not all `imagenet` tag refer to ImageNet 21k - we will need to correct some of them",
"_The documentation is not available anymore as the PR was closed or merged._",
"should we remove the repo mirror on the hub side or will you do it?"
] | 1,651,487,181,000 | 1,651,513,846,000 | 1,651,509,177,000 | MEMBER | null | false | {
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} | On the Hugging Face Hub, users refer to imagenet2012 (from #4178 ) as imagenet-1k in their model tags.
To correctly link models to imagenet, we should rename this dataset `imagenet-1k`.
Later we can add `imagenet-21k` as a new dataset if we want.
Once this one is merged we can delete the `imagenet2012` dataset repository on the Hub.
EDIT: to complete the rationale on why we should name it `imagenet-1k`:
If users specifically added the tag `imagenet-1k` , then it could be for two reasons (not sure which one is predominant), either they
- wanted to make it explicit that it’s not 21k -> the distinction is important for the community
- or they have been following this convention from other models -> the convention implicitly exists already | {
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https://api.github.com/repos/huggingface/datasets/issues/4262 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4262/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4262/comments | https://api.github.com/repos/huggingface/datasets/issues/4262/events | https://github.com/huggingface/datasets/pull/4262 | 1,222,130,749 | PR_kwDODunzps43IOye | 4,262 | Add YAML tags to Dataset Card rotten tomatoes | {
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"_The documentation is not available anymore as the PR was closed or merged._"
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