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https://api.github.com/repos/huggingface/datasets/issues/3454 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3454/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3454/comments | https://api.github.com/repos/huggingface/datasets/issues/3454/events | https://github.com/huggingface/datasets/pull/3454 | 1,084,519,107 | PR_kwDODunzps4wENam | 3,454 | Fix iter_archive generator | {
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- Adds tests to DownloadManager and StreamingDownloadManager `iter_archive` for both path and file inputs
- Fixes bugs in `iter_archive` introduced in:
- #3443
Fix #3453. | {
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] | null | [] | "2021-12-20T08:46:18" | "2021-12-20T10:04:59" | "2021-12-20T10:04:59" | MEMBER | null | ## Describe the bug
After the merge of:
- #3443
the method `iter_archive` throws a ValueError:
```
ValueError: read of closed file
```
## Steps to reproduce the bug
```python
for path, file in dl_manager.iter_archive(archive_path):
pass
```
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https://api.github.com/repos/huggingface/datasets/issues/3452 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3452/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3452/comments | https://api.github.com/repos/huggingface/datasets/issues/3452/events | https://github.com/huggingface/datasets/issues/3452 | 1,083,803,178 | I_kwDODunzps5AmYYq | 3,452 | why the stratify option is omitted from test_train_split function? | {
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"Hi ! It's simply not added yet :)\r\n\r\nIf someone wants to contribute to add the `stratify` parameter I'd be happy to give some pointers.\r\n\r\nIn the meantime, I guess you can use `sklearn` or other tools to do a stratified train/test split over the **indices** of your dataset and then do\r\n```\r\ntrain_dataset = dataset.select(train_indices)\r\ntest_dataset = dataset.select(test_indices)\r\n```",
"Hi @lhoestq I would like to add `stratify` parameter, can you give me some pointers for adding the same ?",
"Hi ! Sure :)\r\n\r\nThe `train_test_split` method is defined here: \r\n\r\nhttps://github.com/huggingface/datasets/blob/dc62232fa1b3bcfe2fbddcb721f2d141f8908943/src/datasets/arrow_dataset.py#L3253-L3253\r\n\r\nand inside `train_test_split ` we need to create the right `train_indices` and `test_indices` that are passed here to `.select()`:\r\n\r\nhttps://github.com/huggingface/datasets/blob/dc62232fa1b3bcfe2fbddcb721f2d141f8908943/src/datasets/arrow_dataset.py#L3450-L3464\r\n\r\nFor example if your dataset is like\r\n| | label |\r\n|---:|--------:|\r\n| 0 | 1 |\r\n| 1 | 1 |\r\n| 2 | 0 |\r\n| 3 | 0 |\r\n\r\nand the user passes `stratify=dataset[\"label\"]`, then you should get indices that look like this\r\n```\r\ntrain_indices = [0, 2]\r\ntest_indices = [1, 3]\r\n```\r\n\r\nthese indices will be passed to `.select` to return the stratified train and test splits :)\r\n\r\nFeel free to รฎng me if you have any question !",
"@lhoestq \r\nI just added the implementation for `stratify` option here #4322 "
] | "2021-12-18T10:37:47" | "2022-05-25T20:43:51" | "2022-05-25T20:43:51" | NONE | null | why the stratify option is omitted from test_train_split function?
is there any other way implement the stratify option while splitting the dataset? as it is important point to be considered while splitting the dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/3451 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3451/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3451/comments | https://api.github.com/repos/huggingface/datasets/issues/3451/events | https://github.com/huggingface/datasets/pull/3451 | 1,083,459,137 | PR_kwDODunzps4wA5LP | 3,451 | [Staging] Update dataset repos automatically on the Hub | {
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Related to https://github.com/huggingface/datasets/issues/3341
The script runs on each commit on `master`. It checks the datasets that were changed, and it pushes the changes to the corresponding repositories on the Hub.
If there's a new dataset, then a new repository is created.
If the commit is a new release of `datasets`, it also pushes the tag to all the repositories. | {
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https://api.github.com/repos/huggingface/datasets/issues/3448 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3448/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3448/comments | https://api.github.com/repos/huggingface/datasets/issues/3448/events | https://github.com/huggingface/datasets/issues/3448 | 1,083,231,080 | I_kwDODunzps5AkMto | 3,448 | JSONDecodeError with HuggingFace dataset viewer | {
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"Hi ! I think the issue comes from the dataset_infos.json file: it has the \"flat\" field twice.\r\n\r\nCan you try deleting this file and regenerating it please ?",
"Thanks! That fixed that, but now I am getting:\r\nServer Error\r\nStatus code: 400\r\nException: KeyError\r\nMessage: 'feature'\r\n\r\nI checked the dataset_infos.json and pubmed_neg.py script, I don't use 'feature' anywhere as a key. Is the dataset viewer expecting that I do?",
"It seems that the `feature` key is missing from some feature type definition in your dataset_infos.json:\r\n```json\r\n\t\t\t\"tokens\": {\r\n\t\t\t\t\"dtype\": \"list\",\r\n\t\t\t\t\"id\": null,\r\n\t\t\t\t\"_type\": \"Sequence\"\r\n\t\t\t},\r\n\t\t\t\"tags\": {\r\n\t\t\t\t\"dtype\": \"list\",\r\n\t\t\t\t\"id\": null,\r\n\t\t\t\t\"_type\": \"Sequence\"\r\n\t\t\t}\r\n```\r\nThey should be\r\n```json\r\n\t\t\t\"tokens\": {\r\n\t\t\t\t\"dtype\": \"list\",\r\n\t\t\t\t\"id\": null,\r\n\t\t\t\t\"_type\": \"Sequence\"\r\n \"feature\": {\"dtype\": \"string\", \"id\": null, \"_type\": \"Value\"}\r\n\t\t\t},\r\n\t\t\t\"tags\": {\r\n\t\t\t\t\"dtype\": \"list\",\r\n\t\t\t\t\"id\": null,\r\n\t\t\t\t\"_type\": \"Sequence\",\r\n \"feature\": {\"num_classes\": 5, \"names\": [\"-\", \"S\", \"H\", \"N\", \"C\"], \"names_file\": null, \"id\": null, \"_type\": \"ClassLabel\"}\r\n\t\t\t}\r\n```\r\n\r\nNote that you can generate the dataset_infos.json automatically to avoid mistakes:\r\n```bash\r\ndatasets-cli test ./path/to/dataset --save_infos\r\n```"
] | "2021-12-17T12:52:41" | "2022-02-24T09:10:26" | "2022-02-24T09:10:26" | NONE | null | ## Dataset viewer issue for 'pubmed_neg'
**Link:** https://huggingface.co/datasets/IGESML/pubmed_neg
I am getting the error:
Status code: 400
Exception: JSONDecodeError
Message: Expecting property name enclosed in double quotes: line 61 column 2 (char 1202)
I have checked all files - I am not using single quotes anywhere. Not sure what is causing this issue.
Am I the one who added this dataset ? Yes
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"Hi ! Indeed it says \"downloading and preparing\" but in your case it didn't need to download anything since you used local files (it would have thrown an error otherwise). I think we can improve the logging to make it clearer in this case",
"@lhoestq Thank you for explaining. I am sorry but I was not clear about my intention. I didn't want to kill internet traffic; I wanted to kill all write activity. In other words, you can imagine that my storage has only read access but crashes on write.\r\n\r\nWhen run_clm.py is invoked with the same parameters, the hash in the cache directory \"datacache/trainpy.v2/json/default-471372bed4b51b53/0.0.0/...\" doesn't change, and my job can load cached data properly. This is great.\r\n\r\nUnfortunately, when params change (which happens sometimes), the hash changes and the old cache is invalid. datasets builder would create a new cache directory with the new hash and create JSON builder there, even though every JSON builder is the same. I didn't find a way to avoid such behavior.\r\n\r\nThis problem can be resolved when using datasets.map() for tokenizing and grouping text. This function allows me to specify output filenames with --cache_file_names, so that the cached files are always valid.\r\n\r\nThis is the code that I used to freeze cache filenames for tokenization. I wish I could do the same to datasets.load_dataset()\r\n```\r\n tokenized_datasets = raw_datasets.map(\r\n tokenize_function,\r\n batched=True,\r\n num_proc=data_args.preprocessing_num_workers,\r\n remove_columns=column_names,\r\n load_from_cache_file=not data_args.overwrite_cache,\r\n desc=\"Running tokenizer on dataset\",\r\n cache_file_names={k: os.path.join(model_args.cache_dir, f'{k}-tokenized') for k in raw_datasets},\r\n )\r\n```",
"Hi ! `load_dataset` may re-generate your dataset if some parameters changed indeed. If you want to freeze a dataset loaded with `load_dataset`, I think the best solution is just to save it somewhere on your disk with `.save_to_disk(my_dataset_dir)` and reload it with `load_from_disk(my_dataset_dir)`. This way you will be able to reload the dataset without having to run `load_dataset`"
] | "2021-12-16T18:51:13" | "2022-02-17T14:16:27" | "2022-02-17T14:16:27" | NONE | null | ## Describe the bug
According to https://huggingface.co/docs/datasets/loading_datasets.html#loading-a-dataset-builder, setting HF_DATASETS_OFFLINE to 1 should make datasets to "run in full offline mode". It didn't work for me. At the very beginning, datasets still tried to download "custom data configuration" for JSON, despite I have run the program once and cached all data into the same --cache_dir.
"Downloading" is not an issue when running with local disk, but crashes often with cloud storage because (1) multiply GPU processes try to access the same file, AND (2) FileLocker fails to synchronize all processes, due to storage throttling. 99% of times, when the main process releases FileLocker, the file is not actually ready for access in cloud storage and thus triggers "FileNotFound" errors for all other processes. Well, another way to resolve the problem is to investigate super reliable cloud storage, but that's out of scope here.
## Steps to reproduce the bug
```
export HF_DATASETS_OFFLINE=1
python run_clm.py --model_name_or_path=models/gpt-j-6B --train_file=trainpy.v2.train.json --validation_file=trainpy.v2.eval.json --cache_dir=datacache/trainpy.v2
```
## Expected results
datasets should stop all "downloading" behavior but reuse the cached JSON configuration. I think the problem here is part of the cache directory path, "default-471372bed4b51b53", is randomly generated, and it could change if some parameters changed. And I didn't find a way to use a fixed path to ensure datasets to reuse cached data every time.
## Actual results
The logging shows datasets are still downloading into "datacache/trainpy.v2/json/default-471372bed4b51b53/0.0.0/c2d554c3377ea79c7664b93dc65d0803b45e3279000f993c7bfd18937fd7f426".
```
12/16/2021 10:25:59 - WARNING - datasets.builder - Using custom data configuration default-471372bed4b51b53
12/16/2021 10:25:59 - INFO - datasets.builder - Generating dataset json (datacache/trainpy.v2/json/default-471372bed4b51b53/0.0.0/c2d554c3377ea79c7664b93dc65d0803b45e3279000f993c7bfd18937fd7f426)
Downloading and preparing dataset json/default to datacache/trainpy.v2/json/default-471372bed4b51b53/0.0.0/c2d554c3377ea79c7664b93dc65d0803b45e3279000f993c7bfd18937fd7f426...
100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 2/2 [00:00<00:00, 17623.13it/s]
12/16/2021 10:25:59 - INFO - datasets.utils.download_manager - Downloading took 0.0 min
12/16/2021 10:26:00 - INFO - datasets.utils.download_manager - Checksum Computation took 0.0 min
100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 2/2 [00:00<00:00, 1206.99it/s]
12/16/2021 10:26:00 - INFO - datasets.utils.info_utils - Unable to verify checksums.
12/16/2021 10:26:00 - INFO - datasets.builder - Generating split train
12/16/2021 10:26:01 - INFO - datasets.builder - Generating split validation
12/16/2021 10:26:02 - INFO - datasets.utils.info_utils - Unable to verify splits sizes.
Dataset json downloaded and prepared to datacache/trainpy.v2/json/default-471372bed4b51b53/0.0.0/c2d554c3377ea79c7664b93dc65d0803b45e3279000f993c7bfd18937fd7f426. Subsequent calls will reuse this data.
100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 2/2 [00:00<00:00, 53.54it/s]
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.1
- Platform: Linux
- Python version: 3.8.10
- PyArrow version: 6.0.1
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"Hi ! What's your question ?"
] | "2021-12-16T15:57:00" | "2022-01-03T10:09:00" | "2022-01-03T10:09:00" | NONE | null | ## Dataset viewer issue for '*name of the dataset*'
**Link:** *link to the dataset viewer page*
*short description of the issue*
Am I the one who added this dataset ? Yes-No
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https://api.github.com/repos/huggingface/datasets/issues/3443 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3443/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3443/comments | https://api.github.com/repos/huggingface/datasets/issues/3443/events | https://github.com/huggingface/datasets/pull/3443 | 1,082,052,833 | PR_kwDODunzps4v8QDX | 3,443 | Extend iter_archive to support file object input | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-16T10:59:14" | "2021-12-17T17:53:03" | "2021-12-17T17:53:02" | MEMBER | null | This PR adds support to passing a file object to `[Streaming]DownloadManager.iter_archive`.
With this feature, we can iterate over a tar file inside another tar file. | {
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https://api.github.com/repos/huggingface/datasets/issues/3442 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3442/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3442/comments | https://api.github.com/repos/huggingface/datasets/issues/3442/events | https://github.com/huggingface/datasets/pull/3442 | 1,081,862,747 | PR_kwDODunzps4v7oBZ | 3,442 | Extend text to support yielding lines, paragraphs or documents | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-16T07:33:17" | "2021-12-20T16:59:10" | "2021-12-20T16:39:18" | MEMBER | null | Add `config.row` option to `text` module to allow yielding lines (default, current case), paragraphs or documents.
Feel free to comment on the name of the config parameter `row`:
- Currently, the docs state datasets are made of rows and columns
- Other names I considered: `example`, `item` | {
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https://api.github.com/repos/huggingface/datasets/issues/3440 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3440/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3440/comments | https://api.github.com/repos/huggingface/datasets/issues/3440/events | https://github.com/huggingface/datasets/issues/3440 | 1,081,528,426 | I_kwDODunzps5AdtBq | 3,440 | datasets keeps reading from cached files, although I disabled it | {
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"Hi ! What version of `datasets` are you using ? Can you also provide the logs you get before it raises the error ?"
] | "2021-12-15T21:26:22" | "2022-02-24T09:12:22" | "2022-02-24T09:12:22" | NONE | null | ## Describe the bug
Hi,
I am trying to avoid dataset library using cached files, I get the following bug when this tried to read the cached files. I tried to do the followings:
```
from datasets import set_caching_enabled
set_caching_enabled(False)
```
also force redownlaod:
```
download_mode='force_redownload'
```
but none worked so far, this is on a cluster and on some of the machines this reads from the cached files, I really appreciate any idea on how to fully remove caching @lhoestq
many thanks
```
File "run_clm.py", line 496, in <module>
main()
File "run_clm.py", line 419, in main
train_result = trainer.train(resume_from_checkpoint=checkpoint)
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 943, in train
self._maybe_log_save_evaluate(tr_loss, model, trial, epoch, ignore_keys_for_eval)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/transformers/trainer.py", line 1445, in _maybe_log_save_evaluate
metrics = self.evaluate(ignore_keys=ignore_keys_for_eval)
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 172, in evaluate
output = self.eval_loop(
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 241, in eval_loop
metrics = self.compute_pet_metrics(eval_datasets, model, self.extra_info[metric_key_prefix], task=task)
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 268, in compute_pet_metrics
centroids = self._compute_per_token_train_centroids(model, task=task)
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 353, in _compute_per_token_train_centroids
data = get_label_samples(self.get_per_task_train_dataset(task), label)
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 350, in get_label_samples
return dataset.filter(lambda example: int(example['labels']) == label)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 470, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/fingerprint.py", line 406, in wrapper
out = func(self, *args, **kwargs)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2519, in filter
indices = self.map(
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2036, in map
return self._map_single(
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 503, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 470, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/fingerprint.py", line 406, in wrapper
out = func(self, *args, **kwargs)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2248, in _map_single
return Dataset.from_file(cache_file_name, info=info, split=self.split)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 654, in from_file
return cls(
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 593, in __init__
self.info.features = self.info.features.reorder_fields_as(inferred_features)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/features/features.py", line 1092, in reorder_fields_as
return Features(recursive_reorder(self, other))
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/features/features.py", line 1081, in recursive_reorder
raise ValueError(f"Keys mismatch: between {source} and {target}" + stack_position)
ValueError: Keys mismatch: between {'indices': Value(dtype='uint64', id=None)} and {'candidates_ids': Sequence(feature=Value(dtype='null', id=None), length=-1, id=None), 'labels': Value(dtype='int64', id=None), 'attention_mask': Sequence(feature=Value(dtype='int8', id=None), length=-1, id=None), 'input_ids': Sequence(feature=Value(dtype='int32', id=None), length=-1, id=None), 'extra_fields': {}, 'task': Value(dtype='string', id=None)}
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- Platform: linux
- Python version: 3.8.12
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3439 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3439/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3439/comments | https://api.github.com/repos/huggingface/datasets/issues/3439/events | https://github.com/huggingface/datasets/pull/3439 | 1,081,389,723 | PR_kwDODunzps4v6Hxs | 3,439 | Add `cast_column` to `IterableDataset` | {
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cc: @patrickvonplaten | {
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https://api.github.com/repos/huggingface/datasets/issues/3438 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3438/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3438/comments | https://api.github.com/repos/huggingface/datasets/issues/3438/events | https://github.com/huggingface/datasets/pull/3438 | 1,081,302,203 | PR_kwDODunzps4v52Va | 3,438 | Update supported versions of Python in setup.py | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-15T17:30:12" | "2021-12-20T14:22:13" | "2021-12-20T14:22:12" | CONTRIBUTOR | null | Update the list of supported versions of Python in `setup.py` to keep the PyPI project description updated. | {
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https://api.github.com/repos/huggingface/datasets/issues/3437 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3437/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3437/comments | https://api.github.com/repos/huggingface/datasets/issues/3437/events | https://github.com/huggingface/datasets/pull/3437 | 1,081,247,889 | PR_kwDODunzps4v5qzI | 3,437 | Update BLEURT hyperlink | {
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https://api.github.com/repos/huggingface/datasets/issues/3436 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3436/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3436/comments | https://api.github.com/repos/huggingface/datasets/issues/3436/events | https://github.com/huggingface/datasets/pull/3436 | 1,081,068,139 | PR_kwDODunzps4v5FE3 | 3,436 | Add the OneStopQa dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/3435 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3435/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3435/comments | https://api.github.com/repos/huggingface/datasets/issues/3435/events | https://github.com/huggingface/datasets/pull/3435 | 1,081,043,756 | PR_kwDODunzps4v4_-0 | 3,435 | Improve Wikipedia Loading Script | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-15T13:30:06" | "2022-03-04T08:16:00" | "2022-03-04T08:16:00" | CONTRIBUTOR | null | * More structured approach to detecting redirects
* Remove redundant template filter code (covered by strip_code)
* Add language-specific lists of additional media namespace aliases for filtering
* Add language-specific lists of category namespace aliases for new link text cleaning step
* Remove magic words (parser directions like __TOC__ that occasionally occur in text)
Fix #3400
With support from @albertvillanova
CC @yjernite | {
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"This dataset is now available on the Hub here: https://huggingface.co/datasets/MLCommons/peoples_speech"
] | "2021-12-15T11:21:21" | "2023-02-28T16:22:29" | "2023-02-28T16:22:28" | CONTRIBUTOR | null | ## Adding a Dataset
- **Name:** The People's Speech
- **Description:** a massive English-language dataset of audio transcriptions of full sentences.
- **Paper:** https://openreview.net/pdf?id=R8CwidgJ0yT
- **Data:** https://mlcommons.org/en/peoples-speech/
- **Motivation:** With over 30,000 hours of speech, this dataset is the largest and most diverse freely available English speech recognition corpus today.
[The article](https://thegradient.pub/new-datasets-to-democratize-speech-recognition-technology-2/) which may be useful when working on the dataset.
cc: @anton-l
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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https://api.github.com/repos/huggingface/datasets/issues/3433 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3433/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3433/comments | https://api.github.com/repos/huggingface/datasets/issues/3433/events | https://github.com/huggingface/datasets/issues/3433 | 1,080,910,724 | I_kwDODunzps5AbWOE | 3,433 | Add Multilingual Spoken Words dataset | {
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- **Name:** Multilingual Spoken Words
- **Description:** Multilingual Spoken Words Corpus is a large and growing audio dataset of spoken words in 50 languages for academic research and commercial applications in keyword spotting and spoken term search, licensed under CC-BY 4.0. The dataset contains more than 340,000 keywords, totaling 23.4 million 1-second spoken examples (over 6,000 hours).
Read more: https://mlcommons.org/en/news/spoken-words-blog/
- **Paper:** https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/file/fe131d7f5a6b38b23cc967316c13dae2-Paper-round2.pdf
- **Data:** https://mlcommons.org/en/multilingual-spoken-words/
- **Motivation:**
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/3432 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3432/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3432/comments | https://api.github.com/repos/huggingface/datasets/issues/3432/events | https://github.com/huggingface/datasets/pull/3432 | 1,079,910,769 | PR_kwDODunzps4v1NGS | 3,432 | Correctly indent builder config in dataset script docs | {
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https://api.github.com/repos/huggingface/datasets/issues/3431 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3431/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3431/comments | https://api.github.com/repos/huggingface/datasets/issues/3431/events | https://github.com/huggingface/datasets/issues/3431 | 1,079,866,083 | I_kwDODunzps5AXXLj | 3,431 | Unable to resolve any data file after loading once | {
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"Hi ! `load_dataset` accepts as input either a local dataset directory or a dataset name from the Hugging Face Hub.\r\n\r\nSo here you are getting this error the second time because it tries to load the local `wiki_dpr` directory, instead of `wiki_dpr` from the Hub. It doesn't work since it's a **cache** directory, not a **dataset** directory in itself.\r\n\r\nTo fix that you can use another cache directory like `cache_dir=\"/data2/whr/lzy/open_domain_data/retrieval/cache\"`",
"thx a lot"
] | "2021-12-14T15:02:15" | "2022-12-11T10:53:04" | "2022-02-24T09:13:52" | NONE | null | when I rerun my program, it occurs this error
" Unable to resolve any data file that matches '['**train*']' at /data2/whr/lzy/open_domain_data/retrieval/wiki_dpr with any supported extension ['csv', 'tsv', 'json', 'jsonl', 'parquet', 'txt', 'zip']", so how could i deal with this problem?
thx.
And below is my code .
| {
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https://api.github.com/repos/huggingface/datasets/issues/3430 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3430/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3430/comments | https://api.github.com/repos/huggingface/datasets/issues/3430/events | https://github.com/huggingface/datasets/pull/3430 | 1,079,811,124 | PR_kwDODunzps4v033w | 3,430 | Make decoding of Audio and Image feature optional | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-14T14:15:08" | "2022-01-25T18:57:52" | "2022-01-25T18:57:52" | CONTRIBUTOR | null | Add the `decode` argument (`True` by default) to the `Audio` and the `Image` feature to make it possible to toggle on/off decoding of these features.
Even though we've discussed that on Slack, I'm not removing the `_storage_dtype` argument of the Audio feature in this PR to avoid breaking the Audio feature tests. | {
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https://api.github.com/repos/huggingface/datasets/issues/3429 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3429/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3429/comments | https://api.github.com/repos/huggingface/datasets/issues/3429/events | https://github.com/huggingface/datasets/pull/3429 | 1,078,902,390 | PR_kwDODunzps4vx1gp | 3,429 | Make cast cacheable (again) on Windows | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-13T19:32:02" | "2021-12-14T14:39:51" | "2021-12-14T14:39:50" | CONTRIBUTOR | null | `cast` currently emits the following warning when called on Windows:
```
Parameter 'function'=<function Dataset.cast.<locals>.<lambda> at 0x000001C930571EA0> of the transform datasets.arrow_dataset.Dataset._map_single couldn't be hashed properly, a random hash was used instead. Make sure your transforms and parameters are serializable with pickle or dill for the dataset fingerprinting
and caching to work. If you reuse this transform, the caching mechanism will consider it to be different
from the previous calls and recompute everything. This warning is only showed once. Subsequent hashing failures won't be showed.
```
It seems like the issue stems from the `config.PYARROW_VERSION` object not being serializable on Windows (tested with `dumps(lambda: config.PYARROW_VERSION)`), so I'm fixing this by capturing `config.PYARROW_VERSION.major` before the lambda definition. | {
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https://api.github.com/repos/huggingface/datasets/issues/3428 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3428/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3428/comments | https://api.github.com/repos/huggingface/datasets/issues/3428/events | https://github.com/huggingface/datasets/pull/3428 | 1,078,863,468 | PR_kwDODunzps4vxtNT | 3,428 | Clean squad dummy data | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-13T18:46:29" | "2021-12-13T18:57:50" | "2021-12-13T18:57:50" | MEMBER | null | Some unused files were remaining, this PR removes them. We just need to keep the dummy_data.zip file | {
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https://api.github.com/repos/huggingface/datasets/issues/3427 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3427/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3427/comments | https://api.github.com/repos/huggingface/datasets/issues/3427/events | https://github.com/huggingface/datasets/pull/3427 | 1,078,782,159 | PR_kwDODunzps4vxb_y | 3,427 | Add The Pile Enron Emails subset | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-13T17:14:16" | "2021-12-14T17:30:59" | "2021-12-14T17:30:57" | MEMBER | null | Add:
- Enron Emails subset of The Pile: "enron_emails" config
Close bigscience-workshop/data_tooling#310.
CC: @StellaAthena | {
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https://api.github.com/repos/huggingface/datasets/issues/3426 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3426/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3426/comments | https://api.github.com/repos/huggingface/datasets/issues/3426/events | https://github.com/huggingface/datasets/pull/3426 | 1,078,670,031 | PR_kwDODunzps4vxEN5 | 3,426 | Update disaster_response_messages download urls (+ add validation split) | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-13T15:30:12" | "2021-12-14T14:38:30" | "2021-12-14T14:38:29" | CONTRIBUTOR | null | Fixes #3240, fixes #3416 | {
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https://api.github.com/repos/huggingface/datasets/issues/3424 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3424/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3424/comments | https://api.github.com/repos/huggingface/datasets/issues/3424/events | https://github.com/huggingface/datasets/pull/3424 | 1,078,543,625 | PR_kwDODunzps4vwpNt | 3,424 | Add RedCaps dataset | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-13T13:38:13" | "2022-01-12T14:13:16" | "2022-01-12T14:13:15" | CONTRIBUTOR | null | Add the RedCaps dataset. I'm not adding the generated `dataset_infos.json` file for now due to its size (11 MB).
TODOs:
- [x] dummy data
- [x] dataset card
Close #3316 | {
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https://api.github.com/repos/huggingface/datasets/issues/3423 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3423/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3423/comments | https://api.github.com/repos/huggingface/datasets/issues/3423/events | https://github.com/huggingface/datasets/issues/3423 | 1,078,049,638 | I_kwDODunzps5AQbtm | 3,423 | data duplicate when setting num_works > 1 with streaming data | {
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"Hi ! Thanks for reporting :)\r\n\r\nWhen using a PyTorch's data loader with `num_workers>1` and an iterable dataset, each worker streams the exact same data by default, resulting in duplicate data when iterating using the data loader.\r\n\r\nWe can probably fix this in `datasets` by checking `torch.utils.data.get_worker_info()` which gives the worker id if it happens.",
"> Hi ! Thanks for reporting :)\r\n> \r\n> When using a PyTorch's data loader with `num_workers>1` and an iterable dataset, each worker streams the exact same data by default, resulting in duplicate data when iterating using the data loader.\r\n> \r\n> We can probably fix this in `datasets` by checking `torch.utils.data.get_worker_info()` which gives the worker id if it happens.\r\nHi ! Thanks for reply\r\n\r\nDo u have some plans to fix the problem?\r\n",
"Isnโt that somehow a bug on PyTorch side? (Just asking because this behavior seems quite general and maybe not what would be intended)",
"From PyTorch's documentation [here](https://pytorch.org/docs/stable/data.html#dataset-types):\r\n\r\n> When using an IterableDataset with multi-process data loading. The same dataset object is replicated on each worker process, and thus the replicas must be configured differently to avoid duplicated data. See [IterableDataset](https://pytorch.org/docs/stable/data.html#torch.utils.data.IterableDataset) documentations for how to achieve this.\r\n\r\nIt looks like an intended behavior from PyTorch\r\n\r\nAs suggested in the [docstring of the IterableDataset class](https://pytorch.org/docs/stable/data.html#torch.utils.data.IterableDataset), we could pass a `worker_init_fn` to the DataLoader to fix this. It could be called `streaming_worker_init_fn` for example.\r\n\r\nHowever, while this solution works, I'm worried that many users simply don't know about this parameter and just start their training with duplicate data without knowing it. That's why I'm more in favor of integrating the check on the worker id directly in `datasets` in our implementation of `IterableDataset.__iter__`.",
"Fixed by https://github.com/huggingface/datasets/pull/4375",
"> Fixed by #4375\r\n\r\nThanks!",
"Hi there @lhoestq @cloudyuyuyu \r\nI met that problem recently, and #4375 is really useful because I finally found out I am training with duplicate data.\r\nHowever, in multi-GPU training, I'm using DDP mode and IterableDataset, which still yields duplicate data for each progress. And this is dangerous because users maybe not realize this behavior.",
"If the worker_info.id is unique per process it should work fine, could you check that they're unique ?\r\n\r\nThe code to get the worker_info in each worker is `torch.utils.data.get_worker_info()`",
"test.py\r\n```python\r\nimport json\r\nimport os\r\n\r\nimport torch\r\nfrom torch.utils.data import IterableDataset, DataLoader\r\nfrom transformers import PreTrainedTokenizer, TrainingArguments\r\n\r\nfrom common.arguments import DataTrainingArguments, ModelArguments\r\n\r\n\r\nclass MyIterableDataset(IterableDataset):\r\n def __iter__(self):\r\n worker_info = torch.utils.data.get_worker_info()\r\n print(worker_info)\r\n return iter(range(3))\r\n\r\n\r\nif __name__ == '__main__':\r\n dataset = MyIterableDataset()\r\n dataloader = DataLoader(dataset, num_workers=1)\r\n for i in dataloader:\r\n print(i)\r\n\r\n```\r\n\r\n\r\n```sh\r\n$ python3 -m torch.distributed.launch \\\r\n --nproc_per_node=2 test.py\r\nWorkerInfo(id=0, num_workers=1, seed=5545685212307804959, dataset=<__main__.MyIterableDataset object at 0x7f92648cf6a0>)\r\nWorkerInfo(id=0, num_workers=1, seed=3174108029709729025, dataset=<__main__.MyIterableDataset object at 0x7f19ab961670>)\r\ntensor([0])\r\ntensor([1])\r\ntensor([2])\r\ntensor([0])\r\ntensor([1])\r\ntensor([2])\r\n```\r\n\r\n@lhoestq they are not unique",
"It looks like a bug from pytorch no ? How can we know which data should go in which process when using DDP ?\r\n\r\nI guess we need to check `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` as well. Not fan of the design here tbh, but that's how it is",
"> It looks like a bug from pytorch no ? How can we know which data should go in which process when using DDP ?\r\n> \r\n> I guess we need to check `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` as well. Not fan of the design here tbh, but that's how it is\r\n\r\nMaybe we should document it?",
"Never mind. After reading the code, `IterableDatasetShard` has solved this problem.",
"I'm re-opening this one since I think it should be supported by `datasets` natively",
"hmm actually let me open a new issue on DDP - original post was for single node"
] | "2021-12-13T03:43:17" | "2022-12-14T16:04:22" | "2022-12-14T16:04:22" | NONE | null | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from torch.utils.data import DataLoader
from tqdm import tqdm
import shutil
NUM_OF_USER = 1000000
NUM_OF_ACTION = 50000
NUM_OF_SEQUENCE = 10000
NUM_OF_FILES = 32
NUM_OF_WORKERS = 16
if __name__ == "__main__":
shutil.rmtree("./dataset")
for i in range(NUM_OF_FILES):
sequence_data = pd.DataFrame(
{
"imei": np.random.randint(1, NUM_OF_USER, size=NUM_OF_SEQUENCE),
"sequence": np.random.randint(1, NUM_OF_ACTION, size=NUM_OF_SEQUENCE)
}
)
if not os.path.exists("./dataset"):
os.makedirs("./dataset")
sequence_data.to_csv(f"./dataset/sequence_data_{i}.csv",
index=False)
dataset = load_dataset("csv",
data_files=[os.path.join("./dataset",file) for file in os.listdir("./dataset") if file.endswith(".csv")],
split="train",
streaming=True).with_format("torch")
data_loader = DataLoader(dataset,
batch_size=1024,
num_workers=NUM_OF_WORKERS)
result = pd.DataFrame()
for i, batch in tqdm(enumerate(data_loader)):
result = pd.concat([result,
pd.DataFrame(batch)],
axis=0)
result.to_csv(f"num_work_{NUM_OF_WORKERS}.csv", index=False)
```
## Expected results
data do not duplicate
## Actual results
data duplicate NUM_OF_WORKERS = 16
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:datasets==1.14.0
- Platform:transformers==4.11.3
- Python version:3.8
- PyArrow version:
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"Hi ! I wasn't able to reproduce your error.\r\n\r\nCan you try to clear your cache at `~/.cache/huggingface/modules` and try again ?"
] | "2021-12-13T02:49:51" | "2022-01-07T14:06:47" | "2022-01-07T14:06:47" | NONE | null | ## Describe the bug
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1371, in load_metric
metric = metric_cls(
TypeError: 'NoneType' object is not callable
## Steps to reproduce the bug
```python
metric = load_metric("glue", "sst2")
```
## Environment info
- `datasets` version: 1.16.1
- Platform: Linux-4.15.0-161-generic-x86_64-with-glibc2.10
- Python version: 3.8.3
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3420 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3420/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3420/comments | https://api.github.com/repos/huggingface/datasets/issues/3420/events | https://github.com/huggingface/datasets/pull/3420 | 1,077,913,468 | PR_kwDODunzps4vukyD | 3,420 | Add eli5_category dataset | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-12T21:30:45" | "2021-12-14T17:53:03" | "2021-12-14T17:53:02" | CONTRIBUTOR | null | This pull request adds a categorized Long-form question answering dataset `ELI5_Category`. It's a new variant of the [ELI5](https://huggingface.co/datasets/eli5) dataset that uses the Reddit tags to alleviate the training/validation overlapping in the origin ELI5 dataset.
A [report](https://celeritasml.netlify.app/posts/2021-12-01-eli5c/)(Section 2) on this dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/3418 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3418/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3418/comments | https://api.github.com/repos/huggingface/datasets/issues/3418/events | https://github.com/huggingface/datasets/pull/3418 | 1,077,053,296 | PR_kwDODunzps4vsHMK | 3,418 | Add Wikisource dataset | {
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Fix #3399.
CC: @geohci, @yjernite | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-10T15:07:21" | "2021-12-14T14:39:06" | "2021-12-14T14:39:05" | CONTRIBUTOR | null | Use `Value("string")` instead of `Value("bool")` for the feature type of the `"bridge"` field in the QED dataset. If the value is `False`, set to `None`.
The following paragraph in the QED repo explains the purpose of this field:
>Each annotation in referential_equalities is a pair of spans, the question_reference and the sentence_reference, corresponding to an entity mention in the question and the selected_sentence respectively. As described in the paper, sentence_references can be "bridged in", in which case they do not correspond with any actual span in the selected_sentence. Hence, sentence_reference spans contain an additional field, bridge, which is a prepositional phrase when a reference is bridged, and is False otherwise. Prepositional phrases serve to link bridged references to an anchoring phrase in the selected_sentence. In the case a sentence_reference is bridged, the start and end, as well as the span string, map to such an anchoring phrase in the selected_sentence.
Fix #3346
cc @VictorSanh | {
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"Hi, thanks for reporting! This is a duplicate of https://github.com/huggingface/datasets/issues/3240. We are working on a fix.\r\n\r\n"
] | "2021-12-10T13:49:17" | "2021-12-14T14:38:29" | "2021-12-14T14:38:29" | NONE | null | ## Dataset viewer issue for '* disaster_response_messages*'
**Link:** https://huggingface.co/datasets/disaster_response_messages
Dataset unavailable. Link dead: https://datasets.appen.com/appen_datasets/disaster_response_data/disaster_response_messages_training.csv
Am I the one who added this dataset ?No
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https://api.github.com/repos/huggingface/datasets/issues/3415 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3415/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3415/comments | https://api.github.com/repos/huggingface/datasets/issues/3415/events | https://github.com/huggingface/datasets/issues/3415 | 1,076,472,534 | I_kwDODunzps5AKarW | 3,415 | Non-deterministic tests: CI tests randomly fail | {
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"I think it might come from two different issues:\r\n1. Google Drive is an unreliable host, mainly because of quota limitations\r\n2. the staging environment can sometimes raise some errors\r\n\r\nFor Google Drive tests we could set up some retries with backup URLs if necessary I guess.\r\nFor staging on the other hand, I guess we can investigate what causes this and discuss with the back-end team",
"Closed by:\r\n- #3982"
] | "2021-12-10T06:08:59" | "2022-03-31T16:38:51" | "2022-03-31T16:38:51" | MEMBER | null | ## Describe the bug
Some CI tests fail randomly.
1. In https://github.com/huggingface/datasets/pull/3375/commits/c10275fe36085601cb7bdb9daee9a8f1fc734f48, there were 3 failing tests, only on Linux:
```
=========================== short test summary info ============================
FAILED tests/test_streaming_download_manager.py::test_streaming_dl_manager_get_extraction_protocol[https://drive.google.com/uc?export=download&id=1k92sUfpHxKq8PXWRr7Y5aNHXwOCNUmqh-zip]
FAILED tests/test_streaming_download_manager.py::test_streaming_gg_drive - Fi...
FAILED tests/test_streaming_download_manager.py::test_streaming_gg_drive_zipped
= 3 failed, 3553 passed, 2950 skipped, 2 xfailed, 1 xpassed, 125 warnings in 192.79s (0:03:12) =
```
2. After re-running the CI (without any change in the code) in https://github.com/huggingface/datasets/pull/3375/commits/57bfe1f342cd3c59d2510b992d5f06a0761eb147, there was only 1 failing test (one on Linux and a different one on Windows):
- On Linux:
```
=========================== short test summary info ============================
FAILED tests/test_streaming_download_manager.py::test_streaming_gg_drive_zipped
= 1 failed, 3555 passed, 2950 skipped, 2 xfailed, 1 xpassed, 125 warnings in 199.76s (0:03:19) =
```
- On Windows:
```
=========================== short test summary info ===========================
FAILED tests/test_load.py::test_load_dataset_builder_for_community_dataset_without_script
= 1 failed, 3551 passed, 2954 skipped, 2 xfailed, 1 xpassed, 121 warnings in 478.58s (0:07:58) =
```
The test `tests/test_streaming_download_manager.py::test_streaming_gg_drive_zipped` passes locally.
3. After re-running again the CI (without any change in the code) in https://github.com/huggingface/datasets/pull/3375/commits/39f32f2119cf91b86867216bb5c356c586503c6a, ALL the tests passed.
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https://api.github.com/repos/huggingface/datasets/issues/3414 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3414/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3414/comments | https://api.github.com/repos/huggingface/datasets/issues/3414/events | https://github.com/huggingface/datasets/pull/3414 | 1,076,028,998 | PR_kwDODunzps4voyaq | 3,414 | Skip None encoding (line deleted by accident in #3195) | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-09T21:17:33" | "2021-12-10T11:00:03" | "2021-12-10T11:00:02" | CONTRIBUTOR | null | Return the line deleted by accident in #3195 while [resolving merge conflicts](https://github.com/huggingface/datasets/pull/3195/commits/8b0ed15be08559056b817836a07d47acda0c4510).
Fix #3181 (finally :))
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https://api.github.com/repos/huggingface/datasets/issues/3413 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3413/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3413/comments | https://api.github.com/repos/huggingface/datasets/issues/3413/events | https://github.com/huggingface/datasets/pull/3413 | 1,075,854,325 | PR_kwDODunzps4voNZv | 3,413 | Add WIDER FACE dataset | {
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TODOs:
* [x] dataset card
* [x] dummy data | {
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https://api.github.com/repos/huggingface/datasets/issues/3412 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3412/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3412/comments | https://api.github.com/repos/huggingface/datasets/issues/3412/events | https://github.com/huggingface/datasets/pull/3412 | 1,075,846,368 | PR_kwDODunzps4voLs4 | 3,412 | Fix flaky test again for s3 serialization | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-09T17:54:41" | "2021-12-09T18:00:52" | "2021-12-09T18:00:52" | MEMBER | null | Following https://github.com/huggingface/datasets/pull/3388 that wasn't enough (see CI error [here](https://app.circleci.com/pipelines/github/huggingface/datasets/9080/workflows/b971fb27-ff20-4220-9416-c19acdfdf6f4/jobs/55985)) | {
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https://api.github.com/repos/huggingface/datasets/issues/3410 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3410/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3410/comments | https://api.github.com/repos/huggingface/datasets/issues/3410/events | https://github.com/huggingface/datasets/pull/3410 | 1,075,815,415 | PR_kwDODunzps4voFG7 | 3,410 | Fix dependencies conflicts in Windows CI after conda update to 4.11 | {
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https://api.github.com/repos/huggingface/datasets/issues/3409 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3409/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3409/comments | https://api.github.com/repos/huggingface/datasets/issues/3409/events | https://github.com/huggingface/datasets/pull/3409 | 1,075,684,593 | PR_kwDODunzps4vnpU0 | 3,409 | Pass new_fingerprint in multiprocessing | {
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Currently one can pass `new_fingerprint` to `.map()` to use a custom fingerprint instead of the one computed by hashing the map transform. However it's ignored if `num_proc>1`.
In this PR I fixed that by passing `new_fingerprint` to `._map_single()` when `num_proc>1`.
More specifically, `new_fingerprint` with a suffix based on the process `rank` is passed, so that each process has a different `new_fingerprint`
cc @TevenLeScao @vlievin | {
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"Fixed, thanks\r\n<img width=\"661\" alt=\"Capture dโeฬcran 2021-12-22 aฬ 12 02 30\" src=\"https://user-images.githubusercontent.com/1676121/147082881-cf700e8d-0511-4431-b214-d6cf8137db10.png\">\r\n"
] | "2021-12-09T14:34:02" | "2021-12-22T11:02:53" | "2021-12-22T11:02:53" | MEMBER | null | ## Dataset viewer issue for '*name of the dataset*'
**Link:** *link to the dataset viewer page*
*short description of the issue*
When creating an empty dataset repo, the Dataset Preview provides a helpful message that no files were found. There is a tiny typo in that message: "ressource" should be "resource"
Am I the one who added this dataset ?
N/A
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https://api.github.com/repos/huggingface/datasets/issues/3407 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3407/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3407/comments | https://api.github.com/repos/huggingface/datasets/issues/3407/events | https://github.com/huggingface/datasets/pull/3407 | 1,074,502,225 | PR_kwDODunzps4vjyrB | 3,407 | Use max number of data files to infer module | {
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This PR fixes the issue of taking too long when hundred of data files present.
Please, feel free to agree on both numbers:
```
# Datasets without script
DATA_FILES_MAX_NUMBER = 10
ARCHIVED_DATA_FILES_MAX_NUMBER = 5
```
Fix #3404. | {
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Fix #3405. | {
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] | null | [] | "2021-12-08T12:32:15" | "2021-12-08T13:03:29" | "2021-12-08T13:03:29" | MEMBER | null | ## Describe the bug
When a zipped file contains archived files within a directory, the function `infer_module_for_data_files_in_archives` does not work.
It only works for files located in the root directory of the ZIP file.
## Steps to reproduce the bug
```python
infer_module_for_data_files_in_archives(["path/to/zip/file.zip"], False)
``` | {
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When hundreds of ZIP files are present in a dataset, format inference takes too long.
See: https://github.com/bigscience-workshop/data_tooling/issues/232#issuecomment-986685497
**Describe the solution you'd like**
Iterate over a maximum number of files.
CC: @lhoestq
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"Hi ! Can you try updating `fsspec` ? The minimum version is `2021.05.0`",
"hey @lhoestq. I'm using `fsspec-2021.11.1` but still getting that error.",
"Maybe this discussion can help:\r\n\r\nhttps://github.com/fsspec/filesystem_spec/issues/597#issuecomment-958646964",
"Thanks @lhoestq. Downgrading `fsspec and s3fs` to `2021.10` fixed this issue!"
] | "2021-12-07T17:57:59" | "2021-12-17T07:00:35" | "2021-12-17T07:00:35" | CONTRIBUTOR | null | ## Describe the bug
Cannot seem to import datasets when running run_summarizer.py script on a VM set up on ovhcloud
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
No error
## Actual results
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/conda/lib/python3.7/site-packages/datasets/__init__.py", line 34, in <module>
from .arrow_dataset import Dataset, concatenate_datasets
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 48, in <module>
from .arrow_writer import ArrowWriter, OptimizedTypedSequence
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_writer.py", line 27, in <module>
from .features import (
File "/opt/conda/lib/python3.7/site-packages/datasets/features/__init__.py", line 2, in <module>
from .audio import Audio
File "/opt/conda/lib/python3.7/site-packages/datasets/features/audio.py", line 8, in <module>
from ..utils.streaming_download_manager import xopen
File "/opt/conda/lib/python3.7/site-packages/datasets/utils/streaming_download_manager.py", line 16, in <module>
from ..filesystems import COMPRESSION_FILESYSTEMS
File "/opt/conda/lib/python3.7/site-packages/datasets/filesystems/__init__.py", line 13, in <module>
from .s3filesystem import S3FileSystem # noqa: F401
File "/opt/conda/lib/python3.7/site-packages/datasets/filesystems/s3filesystem.py", line 1, in <module>
import s3fs
File "/opt/conda/lib/python3.7/site-packages/s3fs/__init__.py", line 1, in <module>
from .core import S3FileSystem, S3File
File "/opt/conda/lib/python3.7/site-packages/s3fs/core.py", line 11, in <module>
from fsspec.asyn import AsyncFileSystem, sync, sync_wrapper, maybe_sync
ImportError: cannot import name 'maybe_sync' from 'fsspec.asyn' (/opt/conda/lib/python3.7/site-packages/fsspec/asyn.py)
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.0
- Platform: OVH Cloud Tesla V100 Machine
- Python version: 3.7.9
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3400 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3400/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3400/comments | https://api.github.com/repos/huggingface/datasets/issues/3400/events | https://github.com/huggingface/datasets/issues/3400 | 1,073,600,382 | I_kwDODunzps4__dd- | 3,400 | Improve Wikipedia loading script | {
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"Thanks! See https://public.paws.wmcloud.org/User:Isaac_(WMF)/HuggingFace%20Wikipedia%20Processing.ipynb for more implementation details / some data around the overhead induced by adding the extra preprocessing steps (stripping link prefixes and magic words)",
"Closed by:\r\n- #3435"
] | "2021-12-07T17:29:25" | "2022-03-22T16:52:28" | "2022-03-22T16:52:28" | MEMBER | null | As reported by @geohci, the "wikipedia" processing/loading script could be improved by some additional small suggested processing functions:
- _extract_content(filepath):
- Replace .startswith("#redirect") with more structured approach: if elem.find(f"./{namespace}redirect") is None: continue
- _parse_and_clean_wikicode(raw_content, parser):
- Remove rm_template from cleaning -- this is redundant with .strip_code() from mwparserformhell
- Build a language-specific list of namespace prefixes to filter out per below get_namespace_prefixes
- Optional: strip prefixes like categories -- e.g., Category:Towns in Tianjin becomes Towns in Tianjin
- Optional: strip magic words
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https://api.github.com/repos/huggingface/datasets/issues/3398 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3398/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3398/comments | https://api.github.com/repos/huggingface/datasets/issues/3398/events | https://github.com/huggingface/datasets/issues/3398 | 1,073,590,384 | I_kwDODunzps4__bBw | 3,398 | Add URL field to Wikimedia dataset instances: wikipedia,... | {
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"@geohci, I think the field \"url\" does not appear in the Wikimedia dumps. Therefore I guess we should generate it, using the \"title\" field and making some transformation of it (replacing spaces with underscores) and prepending the domain (created using the language)?",
"Indeed:\r\n\r\n> To re-distribute text on Wikipedia in any form, provide credit to the authors either by including a) a [hyperlink](https://en.wikipedia.org/wiki/Hyperlink) (where possible) or [URL](https://en.wikipedia.org/wiki/URL) to the page or pages you are re-using, b) a hyperlink (where possible) or URL to an alternative, stable online copy which is freely accessible, which conforms with the license, and which provides credit to the authors in a manner equivalent to the credit given on this website, or c) a list of all authors. (Any list of authors may be filtered to exclude very small or irrelevant contributions.) This applies to text developed by the Wikipedia community. Text from external sources may attach additional attribution requirements to the work, which should be indicated on an article's face or on its talk page. For example, a page may have a banner or other notation indicating that some or all of its content was originally published somewhere else. Where such notations are visible in the page itself, they should generally be preserved by re-users.\r\n\r\nsource: https://en.wikipedia.org/wiki/Wikipedia:Copyrights\r\n\r\nI guess it's fine to add the URL field - it can be constructed easily from the title page IIRC.",
"yep, sorry forgot that that wasn't already in the dumps. specifically `f\"https://{language}.wikipedia.org/wiki/{title.replace(' ', '_')}` should do it",
"Thanks @geohci.\r\n\r\nI had already been looking for information about the conversion from title to URL and I found that apart from replacing blanks with underscores, some other special character must also be percent-encoded (e.g. `\"` to `%22`): https://meta.wikimedia.org/wiki/Help:URL\r\n\r\nTherefore, I have finally used `urllib.parse.quote` function. This additionally percent-encodes non-ASCII characters, but Wikimedia docs say these are equivalent:\r\n> For the other characters either the code or the character can be used in internal and external links, they are equivalent. The system does a conversion when needed.\r\n> [[%C3%80_propos_de_M%C3%A9ta]]\r\n> is rendered as [ร_propos_de_Mรฉta](https://meta.wikimedia.org/wiki/%C3%80_propos_de_M%C3%A9ta), almost like [ร propos de Mรฉta](https://meta.wikimedia.org/wiki/%C3%80_propos_de_M%C3%A9ta), which leads to this page on Meta with in the address bar the URL\r\n> [http://meta.wikipedia.org/wiki/%C3%80_propos_de_M%C3%A9ta](https://meta.wikipedia.org/wiki/%C3%80_propos_de_M%C3%A9ta)\r\n> while [http://meta.wikipedia.org/wiki/ร_propos_de_Mรฉta](https://meta.wikipedia.org/wiki/%C3%80_propos_de_M%C3%A9ta) leads to the same. ",
"Closed by:\r\n- #3789 "
] | "2021-12-07T17:17:27" | "2022-03-22T16:53:27" | "2022-03-22T16:53:27" | MEMBER | null | As reported by @geohci, in order to host pre-processed data in the Hub, we should add the full URL to data instances (new field "url"), so that we conform to proper attribution from license requirement. See, e.g.: https://fair-trec.github.io/docs/Fair_Ranking_2021_Participant_Instructions.pdf#subsection.3.2
This should be done for all pre-processed datasets under "wikimedia" org in the Hub: https://huggingface.co/wikimedia
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https://api.github.com/repos/huggingface/datasets/issues/3397 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3397/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3397/comments | https://api.github.com/repos/huggingface/datasets/issues/3397/events | https://github.com/huggingface/datasets/pull/3397 | 1,073,502,444 | PR_kwDODunzps4vgh1U | 3,397 | add BNL newspapers | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-07T15:43:21" | "2022-01-17T18:35:34" | "2022-01-17T18:35:34" | MEMBER | null | This pull request adds the BNL's [processed newspaper collections](https://data.bnl.lu/data/historical-newspapers/) as a dataset. This is partly done to support BigScience see: https://github.com/bigscience-workshop/data_tooling/issues/192.
The Datacard is more sparse than I would like but I plan to make a separate pull request to try and make this more complete at a later date.
I had to manually add the `dummy_data` but I believe I've done this correctly (the tests pass locally).
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"https://huggingface.co/datasets/projecte-aina/parlament_parla -> works (but we still have to show an audio player)\r\n\r\nhttps://huggingface.co/datasets/openslr -> another issue: `Message: [Errno 2] No such file or directory: '/home/hf/datasets-preview-backend/zip:/asr_javanese/data/00/00004fe6aa.flac'`",
"Done",
"https://huggingface.co/datasets/projecte-aina/parlament_parla/viewer/clean/train works\r\n\r\n<img width=\"1535\" alt=\"Capture dโeฬcran 2022-04-12 aฬ 13 58 47\" src=\"https://user-images.githubusercontent.com/1676121/162957855-cb3d9e2e-4b61-488c-99ca-8065cd8fe377.png\">\r\n",
"But https://huggingface.co/datasets/openslr/viewer does not work\r\n\r\n<img width=\"678\" alt=\"Capture dโeฬcran 2022-04-12 aฬ 13 59 46\" src=\"https://user-images.githubusercontent.com/1676121/162958013-e31ef2ae-f886-47b7-9f27-664ed3d4b5a1.png\">\r\n\r\nSame issue as #4126:\r\n\r\n```\r\nStatus code: 400\r\nException: TypeError\r\nMessage: __init__() got an unexpected keyword argument 'audio_column'\r\n```",
"Fixed:\r\n<img width=\"1561\" alt=\"Capture dโeฬcran 2022-04-25 aฬ 18 11 51\" src=\"https://user-images.githubusercontent.com/1676121/165129813-018ece9e-8b20-4544-844d-4e88148e738f.png\">\r\n"
] | "2021-12-07T15:11:36" | "2022-04-25T16:12:22" | "2022-04-25T16:12:01" | MEMBER | null | ## Dataset viewer issue for '*openslr*', '*projecte-aina/parlament_parla*'
**Link:** *https://huggingface.co/datasets/openslr*
**Link:** *https://huggingface.co/datasets/projecte-aina/parlament_parla*
Error:
```
Status code: 400
Exception: ImportError
Message: To support decoding audio files, please install 'librosa'.
```
Am I the one who added this dataset ? Yes-No
- openslr: No
- projecte-aina/parlament_parla: Yes
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https://api.github.com/repos/huggingface/datasets/issues/3394 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3394/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3394/comments | https://api.github.com/repos/huggingface/datasets/issues/3394/events | https://github.com/huggingface/datasets/issues/3394 | 1,073,396,308 | I_kwDODunzps4_-rpU | 3,394 | Preserve all feature types when saving a dataset on the Hub with `push_to_hub` | {
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"According to this [comment in the forum](https://discuss.huggingface.co/t/save-datasetdict-to-huggingface-hub/12075/8?u=lhoestq), using `push_to_hub` on a dataset with `ClassLabel` can also make the feature simply disappear when it's reloaded !",
"Maybe we can also fix https://github.com/huggingface/datasets/issues/3035 while working on this because, as pointed out in my initial post, `save_to_disk` also saves the `dataset_info.json` file."
] | "2021-12-07T14:08:30" | "2021-12-21T17:00:09" | "2021-12-21T17:00:09" | CONTRIBUTOR | null | Currently, if one of the dataset features is of type `ClassLabel`, saving the dataset with `push_to_hub` and reloading the dataset with `load_dataset` will return the feature of type `Value`. To fix this, we should do something similar to `save_to_disk` (which correctly preserves the types) and not only push the parquet files in `push_to_hub`, but also the dataset `info` (stored in a JSON file). | {
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https://api.github.com/repos/huggingface/datasets/issues/3392 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3392/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3392/comments | https://api.github.com/repos/huggingface/datasets/issues/3392/events | https://github.com/huggingface/datasets/issues/3392 | 1,073,073,408 | I_kwDODunzps4_9c0A | 3,392 | Dataset viewer issue for `dansbecker/hackernews_hiring_posts` | {
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"This issue was fixed by me calling `all_datasets.push_to_hub(\"hackernews_hiring_posts\")`.\r\n\r\nThe previous problems were from calling `all_datasets.save_to_disk` and then pushing with `my_repo.git_add` and `my_repo.push_to_hub`.\r\n"
] | "2021-12-07T08:41:01" | "2021-12-07T14:04:28" | "2021-12-07T14:04:28" | CONTRIBUTOR | null | ## Dataset viewer issue for `dansbecker/hackernews_hiring_posts`
**Link:** https://huggingface.co/datasets/dansbecker/hackernews_hiring_posts
*short description of the issue*
Dataset preview not showing for uploaded DatasetDict. See https://discuss.huggingface.co/t/dataset-preview-not-showing-for-uploaded-datasetdict/12603
Am I the one who added this dataset ?
No -> @dansbecker | {
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https://api.github.com/repos/huggingface/datasets/issues/3391 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3391/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3391/comments | https://api.github.com/repos/huggingface/datasets/issues/3391/events | https://github.com/huggingface/datasets/issues/3391 | 1,072,849,055 | I_kwDODunzps4_8mCf | 3,391 | method to select columns | {
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"duplicate of #2655"
] | "2021-12-07T02:44:19" | "2021-12-07T02:45:27" | "2021-12-07T02:45:27" | CONTRIBUTOR | null | **Is your feature request related to a problem? Please describe.**
* There is currently no way to select some columns of a dataset. In pandas, one can use `df[['col1', 'col2']]` to select columns, but in `datasets`, it results in error.
**Describe the solution you'd like**
* A new method that can be used to create a new dataset with only a list of specified columns.
**Describe alternatives you've considered**
`.remove_columns(self, columns: Union[str, List[str]], inverse: bool = False)`
Or
`.select(self, indices: Iterable = None, columns: List[str] = None)`
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https://api.github.com/repos/huggingface/datasets/issues/3390 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3390/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3390/comments | https://api.github.com/repos/huggingface/datasets/issues/3390/events | https://github.com/huggingface/datasets/issues/3390 | 1,072,462,456 | I_kwDODunzps4_7Hp4 | 3,390 | Loading dataset throws "KeyError: 'Field "builder_name" does not exist in table schema'" | {
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"Got solved it with push_to_hub, closing"
] | "2021-12-06T18:22:49" | "2021-12-06T20:22:05" | "2021-12-06T20:22:05" | NONE | null | ## Describe the bug
I have prepared dataset to datasets and now I am trying to load it back Finnish-NLP/voxpopuli_fi
I get "KeyError: 'Field "builder_name" does not exist in table schema'"
My dataset folder and files should be like @patrickvonplaten has here https://huggingface.co/datasets/flax-community/german-common-voice-processed
How my voxpopuli dataset looks like:
Part of the processing (path column is the absolute path to audio files)
```
def add_audio_column(example):
example['audio'] = example['path']
return example
voxpopuli = voxpopuli.map(add_audio_column)
voxpopuli.cast_column("audio", Audio())
voxpopuli["audio"] <-- to my knowledge this does load the local files and prepares those arrays
voxpopuli = voxpopuli.cast_column("audio", Audio(sampling_rate=16_000)) resampling 16kHz
```
I have then saved it to disk_
`voxpopuli.save_to_disk('/asr_disk/datasets_processed_new/voxpopuli')`
and made folder structure same as @patrickvonplaten
I also get same error while trying to load_dataset from his repo:
## Steps to reproduce the bug
```python
dataset = load_dataset("Finnish-NLP/voxpopuli_fi")
```
## Expected results
Dataset is loaded correctly and looks like in the first picture
## Actual results
Loading throws keyError:
KeyError: 'Field "builder_name" does not exist in table schema'
Resources I have been trying to follow:
https://huggingface.co/docs/datasets/audio_process.html
https://huggingface.co/docs/datasets/share_dataset.html
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.2.dev0
- Platform: Ubuntu 20.04.2 LTS
- Python version: 3.8.12
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3388 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3388/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3388/comments | https://api.github.com/repos/huggingface/datasets/issues/3388/events | https://github.com/huggingface/datasets/pull/3388 | 1,072,022,021 | PR_kwDODunzps4vbnyY | 3,388 | Fix flaky test of the temporary directory used by load_from_disk | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-06T11:09:31" | "2021-12-06T11:25:03" | "2021-12-06T11:24:49" | MEMBER | null | The test is flaky, here is an example of random CI failure:
https://github.com/huggingface/datasets/commit/73ed6615b4b3eb74d5311684f7b9e05cdb76c989
I fixed that by not checking the content of the random part of the temporary directory name | {
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https://api.github.com/repos/huggingface/datasets/issues/3387 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3387/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3387/comments | https://api.github.com/repos/huggingface/datasets/issues/3387/events | https://github.com/huggingface/datasets/pull/3387 | 1,071,836,456 | PR_kwDODunzps4vbAyC | 3,387 | Create Language Modeling task | {
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This can be useful for datasets which are not exclusively used for language modeling and have more than one column:
- for text classification datasets (with columns "review" and "rating", for example), the Language Modeling task can be used to specify the "text" column ("review" in this case).
TODO:
- [ ] Add the LanguageModeling task to all dataset scripts which can be used for language modeling | {
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https://api.github.com/repos/huggingface/datasets/issues/3386 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3386/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3386/comments | https://api.github.com/repos/huggingface/datasets/issues/3386/events | https://github.com/huggingface/datasets/pull/3386 | 1,071,813,141 | PR_kwDODunzps4va7-2 | 3,386 | Fix typos in dataset cards | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-06T07:20:40" | "2021-12-06T09:30:55" | "2021-12-06T09:30:54" | MEMBER | null | This PR:
- Fix typos in dataset cards
- Fix Papers With Code ID for:
- Bilingual Corpus of Arabic-English Parallel Tweets
- Tweets Hate Speech Detection
- Add pretty name tags | {
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https://api.github.com/repos/huggingface/datasets/issues/3384 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3384/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3384/comments | https://api.github.com/repos/huggingface/datasets/issues/3384/events | https://github.com/huggingface/datasets/pull/3384 | 1,071,594,165 | PR_kwDODunzps4vaNwL | 3,384 | Adding mMARCO dataset | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-05T23:59:11" | "2021-12-12T15:27:36" | "2021-12-12T15:27:36" | NONE | null | We are adding mMARCO dataset to HuggingFace datasets repo.
This way, all the languages covered in the translation are available in a easy way. | {
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https://api.github.com/repos/huggingface/datasets/issues/3383 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3383/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3383/comments | https://api.github.com/repos/huggingface/datasets/issues/3383/events | https://github.com/huggingface/datasets/pull/3383 | 1,071,551,884 | PR_kwDODunzps4vaFpm | 3,383 | add Georgian data in cc100. | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-05T20:38:09" | "2021-12-14T14:37:23" | "2021-12-14T14:37:22" | CONTRIBUTOR | null | update cc100 dataset to support loading Georgian (ka) data which is originally available in CC100 dataset source.
All tests are passed.
Dummy data generated.
metadata generated. | {
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https://api.github.com/repos/huggingface/datasets/issues/3382 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3382/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3382/comments | https://api.github.com/repos/huggingface/datasets/issues/3382/events | https://github.com/huggingface/datasets/pull/3382 | 1,071,293,299 | PR_kwDODunzps4vZT2K | 3,382 | #3337 Add typing overloads to Dataset.__getitem__ for mypy | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-04T20:54:49" | "2021-12-14T10:28:55" | "2021-12-14T10:28:55" | CONTRIBUTOR | null | Add typing overloads to Dataset.__getitem__ for mypy
Fixes #3337
**Iterable**
Iterable from `collections` cannot have a type, so you can't do `Iterable[int]` for example. `typing` has a Generic version that builds upon the one from `collections`.
**Flake8**
I had to add `# noqa: F811`, this is a bug from Flake8.
datasets uses flake8==3.7.9 which released in October 2019 if I update flake8 (4.0.1), I no longer get these errors, but I did not want to make the update without your approval. (It also triggers other errors like no args in f-strings.) | {
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https://api.github.com/repos/huggingface/datasets/issues/3381 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3381/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3381/comments | https://api.github.com/repos/huggingface/datasets/issues/3381/events | https://github.com/huggingface/datasets/issues/3381 | 1,071,283,879 | I_kwDODunzps4_2n6n | 3,381 | Unable to load audio_features from common_voice dataset | {
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"Hi ! Feel free to access `batch[\"audio\"][\"array\"]` and `batch[\"audio\"][\"sampling_rate\"]` instead\r\n\r\n`datasets` 1.16 introduced some changes in `common_voice` and now the `path` field is no longer a path to a local file (but rather the path to the file in the archive it's extracted from)",
"Thanks for the information. It works.",
"Cool ! Closing this issue then"
] | "2021-12-04T19:59:11" | "2021-12-06T17:52:42" | "2021-12-06T17:52:42" | NONE | null | ## Describe the bug
I am not able to load audio features from common_voice dataset
## Steps to reproduce the bug
```
from datasets import load_dataset
import torchaudio
test_dataset = load_dataset("common_voice", "hi", split="test[:2%]")
resampler = torchaudio.transforms.Resample(48_000, 16_000)
def speech_file_to_array_fn(batch):
speech_array, sampling_rate = torchaudio.load(batch["path"])
batch["speech"] = resampler(speech_array).squeeze().numpy()
return batch
test_dataset = test_dataset.map(speech_file_to_array_fn)
```
## Expected results
This piece of code should return test_dataset after loading audio features.
## Actual results
Reusing dataset common_voice (/home/jovyan/.cache/huggingface/datasets/common_voice/hi/6.1.0/b879a355caa529b11f2249400b61cadd0d9433f334d5c60f8c7216ccedfecfe1)
/opt/conda/lib/python3.7/site-packages/transformers/configuration_utils.py:341: UserWarning: Passing `gradient_checkpointing` to a config initialization is deprecated and will be removed in v5 Transformers. Using `model.gradient_checkpointing_enable()` instead, or if you are using the `Trainer` API, pass `gradient_checkpointing=True` in your `TrainingArguments`.
"Passing `gradient_checkpointing` to a config initialization is deprecated and will be removed in v5 "
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
0%| | 0/3 [00:00<?, ?ex/s]formats: can't open input file `common_voice_hi_23795358.mp3': No such file or directory
0%| | 0/3 [00:00<?, ?ex/s]
Traceback (most recent call last):
File "demo_file.py", line 23, in <module>
test_dataset = test_dataset.map(speech_file_to_array_fn)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2036, in map
desc=desc,
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 518, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 485, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/fingerprint.py", line 411, in wrapper
out = func(self, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2368, in _map_single
example = apply_function_on_filtered_inputs(example, i, offset=offset)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2277, in apply_function_on_filtered_inputs
processed_inputs = function(*fn_args, *additional_args, **fn_kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1978, in decorated
result = f(decorated_item, *args, **kwargs)
File "demo_file.py", line 19, in speech_file_to_array_fn
speech_array, sampling_rate = torchaudio.load(batch["path"])
File "/opt/conda/lib/python3.7/site-packages/torchaudio/backend/sox_io_backend.py", line 154, in load
filepath, frame_offset, num_frames, normalize, channels_first, format)
RuntimeError: Error loading audio file: failed to open file common_voice_hi_23795358.mp3
## Environment info
- `datasets` version: 1.16.1
- Platform: Linux-4.14.243 with-debian-bullseye-sid
- Python version: 3.7.9
- PyArrow version: 6.0.1
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} | [] | closed | false | null | [] | null | [] | "2021-12-04T09:18:33" | "2022-01-11T12:29:53" | "2022-01-11T12:29:53" | MEMBER | null | Thanks to all of you, `datasets` will pass 11.5k stars :star2: this week!
If you have a couple of minutes and want to participate in shaping the future of the ecosystem, please share your thoughts:
[**hf.co/oss-survey**](https://hf.co/oss-survey)
(please reply in the above feedback form rather than to this thread)
Thank you all on behalf of the HuggingFace team! ๐ค | {
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https://api.github.com/repos/huggingface/datasets/issues/3379 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3379/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3379/comments | https://api.github.com/repos/huggingface/datasets/issues/3379/events | https://github.com/huggingface/datasets/pull/3379 | 1,071,079,146 | PR_kwDODunzps4vYr7K | 3,379 | iter_archive on zipfiles with better compression type check | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-04T01:04:48" | "2023-01-24T13:00:19" | "2023-01-24T12:53:08" | CONTRIBUTOR | null | Hello @lhoestq , thank you for your detailed answer on previous PR !
I made this new PR because I misused git on the previous one #3347.
Related issue #3272.
# Comments :
* For extension check I used the `_get_extraction_protocol` function in **download_manager.py** with a slight change and called it `_get_extraction_protocol_local`:
**I removed this part :**
```python
elif path.endswith(".tar.gz") or path.endswith(".tgz"):
raise NotImplementedError(
f"Extraction protocol for TAR archives like '{urlpath}' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead."
)
```
**And also changed :**
```diff
- extension = path.split(".")[-1]
+ extension = "tar" if path.endswith(".tar.gz") else path.split(".")[-1]
```
The reason for this is a compression like **.tar.gz** will be considered a **.gz** which is handled with **zipfile**, though **tar.gz** can only be opened using **tarfile**.
Please tell me if there's anything to change.
# Tasks :
- [x] download_manager.py
- [x] streaming_download_manager.py | {
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- pubmed
- ubuntu_irc
- europarl
- hacker_news
- nih_exporter
Close bigscience-workshop/data_tooling#301.
CC: @StellaAthena | {
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I referred to this TFDS code: https://github.com/tensorflow/datasets/blob/2538a08c184d53b37bfcf52cc21dd382572a88f4/tensorflow_datasets/object_detection/coco.py
cc: @mariosasko | {
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- I have added the method `iter_files` to DownloadManager and StreamingDownloadManager
- I use this in modules: "csv", "json", "text"
- I test for CSV/JSONL/TXT zipped (and non-zipped) files, both in streaming and non-streaming modes
Fix #3373. | {
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"Seems like the issue still exists,:\r\n`Downloading and preparing dataset clue/chid (download: 127.15 MiB, generated: 259.71 MiB, post-processed: Unknown size, total: 386.86 MiB) to /mnt/cache/tanhaochen/.cache/huggingface/datasets/clue/chid/1.0.0/e55b490cb7809dcd8db31b9a87119f2e2ec87cdc060da8a9ac070b070ca3e379...\r\nTraceback (most recent call last):\r\n File \"/mnt/cache/tanhaochen/PromptCLUE/test_datasets.py\", line 3, in <module>\r\n cluewsc2020 = datasets.load_dataset(\"clue\",\"chid\")\r\n File \"/mnt/cache/tanhaochen/dependencies/datasets/src/datasets/load.py\", line 1667, in load_dataset\r\n builder_instance.download_and_prepare(\r\n File \"/mnt/cache/tanhaochen/dependencies/datasets/src/datasets/builder.py\", line 593, in download_and_prepare\r\n self._download_and_prepare(\r\n File \"/mnt/cache/tanhaochen/dependencies/datasets/src/datasets/builder.py\", line 663, in _download_and_prepare\r\n verify_checksums(\r\n File \"/mnt/cache/tanhaochen/dependencies/datasets/src/datasets/utils/info_utils.py\", line 40, in verify_checksums\r\n raise NonMatchingChecksumError(error_msg + str(bad_urls))\r\ndatasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:\r\n['https://storage.googleapis.com/cluebenchmark/tasks/chid_public.zip']\r\n`",
"Hi,\r\n\r\nthe fix hasn't been merged yet (it should be merged early next week)."
] | "2021-12-03T10:10:54" | "2021-12-08T14:14:41" | "2021-12-08T14:14:41" | NONE | null | Hi, it seems like there are updates in cluewsc2020, chid, c3 and tnews, since i could not load them due to the checksum error. | {
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] | null | [] | "2021-12-03T09:48:24" | "2021-12-16T18:03:31" | "2021-12-16T18:03:31" | MEMBER | null | Given a community ๐ค dataset repository containing only a zipped CSV file (only raw data, no loading script), I would like to load it in streaming mode without passing `data_files`:
```
ds_name = "bigscience-catalogue-data/vietnamese_poetry_from_fsoft_ai_lab"
ds = load_dataset(ds_name, split="train", streaming=True, use_auth_token=True)
item = next(iter(ds))
```
Currently, it gives a `FileNotFoundError` because there is no glob (no "\*" after "zip://": "zip://*") in the passed URL:
```
'zip://::https://huggingface.co/datasets/bigscience-catalogue-data/vietnamese_poetry_from_fsoft_ai_lab/resolve/e5d45f1bd9a8a798cc14f0a45ebc1ce91907c792/poems_dataset.zip'
```
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https://api.github.com/repos/huggingface/datasets/issues/3372 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3372/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3372/comments | https://api.github.com/repos/huggingface/datasets/issues/3372/events | https://github.com/huggingface/datasets/issues/3372 | 1,069,948,178 | I_kwDODunzps4_xh0S | 3,372 | [SEO improvement] Add Dataset Metadata to make datasets indexable | {
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] | closed | false | null | [] | null | [] | "2021-12-02T20:21:07" | "2022-03-18T09:36:48" | "2022-03-18T09:36:48" | CONTRIBUTOR | null | Some people who host datasets on github seem to include a table of metadata at the end of their README.md to make the dataset indexable by [Google Dataset Search](https://datasetsearch.research.google.com/) (See [here](https://github.com/google-research/google-research/tree/master/goemotions#dataset-metadata) and [here](https://github.com/cvdfoundation/google-landmark#dataset-metadata)). This could be a useful addition to canonical datasets; perhaps even community datasets.
I'll include a screenshot (as opposed to markdown) as an example so as not to have a github issue indexed as a dataset:
> 
**_PS: It might very well be the case that this is already covered by some other markdown magic I'm not aware of._**
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https://api.github.com/repos/huggingface/datasets/issues/3371 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3371/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3371/comments | https://api.github.com/repos/huggingface/datasets/issues/3371/events | https://github.com/huggingface/datasets/pull/3371 | 1,069,821,335 | PR_kwDODunzps4vUnbp | 3,371 | New: Americas NLI dataset | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-02T17:44:59" | "2021-12-08T13:58:12" | "2021-12-08T13:58:11" | CONTRIBUTOR | null | This PR adds the [Americas NLI](https://arxiv.org/abs/2104.08726) dataset, extension of XNLI to 10 low-resource indigenous languages spoken in the Americas: Ashaninka, Aymara, Bribri, Guarani, Nahuatl, Otomi, Quechua, Raramuri, Shipibo-Konibo, and Wixarika.
One odd thing (not sure) is that I had to set
`datasets-cli dummy_data ./datasets/americas_nli/ --auto_generate --n_lines 7500`
`n_lines` very large to successfully generate the dummy files for all the subsets. Happy to get some guidance here.
Otherwise, I hope everything is in order :)
e: missed a step, onto fixing the tests
e2: there you go -- hope it's ok to have added more languages with their ISO codes to `languages.json`, need those tests to pass :laughing: | {
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https://api.github.com/repos/huggingface/datasets/issues/3370 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3370/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3370/comments | https://api.github.com/repos/huggingface/datasets/issues/3370/events | https://github.com/huggingface/datasets/pull/3370 | 1,069,735,423 | PR_kwDODunzps4vUVA3 | 3,370 | Document a training loop for streaming dataset | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-02T16:17:00" | "2021-12-03T13:34:35" | "2021-12-03T13:34:34" | MEMBER | null | I added some docs about streaming dataset. In particular I added two subsections:
- one on how to use `map` for preprocessing
- one on how to use a streaming dataset in a pytorch training loop
cc @patrickvonplaten @stevhliu if you have some comments
cc @Rocketknight1 later we can add the one for TF and I might need your help ^^' | {
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"This requires implementing `cast_column` for iterable datasets, it could be a very nice addition !\r\n\r\n<s>It can also be useful to be able to disable the audio/image decoding for the dataset viewer (see PR https://github.com/huggingface/datasets/pull/3430) cc @severo </s>\r\nEDIT: actually following https://github.com/huggingface/datasets/issues/3145 the dataset viewer might not need it anymore",
"Just to clarify a bit. This feature is **always** needed when using the common voice dataset in streaming mode. So I think it's quite important"
] | "2021-12-02T14:04:57" | "2021-12-16T15:55:19" | "2021-12-16T15:55:19" | MEMBER | null | Many audio datasets like Common Voice always need to be resampled. This can very easily be done in non-streaming mode as follows:
```python
from datasets import load_dataset
ds = load_dataset("common_voice", "ab", split="test")
ds = ds.cast_column("audio", Audio(sampling_rate=16_000))
```
However in streaming mode it fails currently:
```python
from datasets import load_dataset
ds = load_dataset("common_voice", "ab", split="test", streaming=True)
ds = ds.cast_column("audio", Audio(sampling_rate=16_000))
```
with the following error:
```
AttributeError: 'IterableDataset' object has no attribute 'cast_column'
```
It would be great if we could add such a feature (I'm not 100% sure though how complex this would be) | {
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This PR:
- Extends `tagset_validator` to support regex tags
- Uses `tagset_validator` to validate dict `source_datasets` | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-02T08:02:27" | "2021-12-02T16:07:14" | "2021-12-02T16:07:13" | MEMBER | null | Fix typo in task tag:
- `other-stuctured-to-text` (before)
- `other-structured-to-text` (now) | {
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https://api.github.com/repos/huggingface/datasets/issues/3364 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3364/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3364/comments | https://api.github.com/repos/huggingface/datasets/issues/3364/events | https://github.com/huggingface/datasets/pull/3364 | 1,068,851,196 | PR_kwDODunzps4vRaxq | 3,364 | Use the Audio feature in the AutomaticSpeechRecognition template | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T20:42:26" | "2022-03-24T14:34:09" | "2022-03-24T14:34:08" | MEMBER | null | This updates the ASR template and all supported datasets to use the `Audio` feature | {
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https://api.github.com/repos/huggingface/datasets/issues/3363 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3363/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3363/comments | https://api.github.com/repos/huggingface/datasets/issues/3363/events | https://github.com/huggingface/datasets/pull/3363 | 1,068,824,340 | PR_kwDODunzps4vRVCl | 3,363 | Update URL of Jeopardy! dataset | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T20:08:10" | "2022-10-06T13:45:49" | "2021-12-03T12:35:01" | CONTRIBUTOR | null | Updates the URL of the Jeopardy! dataset.
Fix #3361 | {
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https://api.github.com/repos/huggingface/datasets/issues/3362 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3362/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3362/comments | https://api.github.com/repos/huggingface/datasets/issues/3362/events | https://github.com/huggingface/datasets/pull/3362 | 1,068,809,768 | PR_kwDODunzps4vRR2r | 3,362 | Adapt image datasets | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T19:52:01" | "2021-12-09T18:37:42" | "2021-12-09T18:37:41" | CONTRIBUTOR | null | This PR:
* adapts the ImageClassification template to use the new Image feature
* adapts the following datasets to use the new Image feature:
* beans (+ fixes streaming)
* cast_vs_dogs (+ fixes streaming)
* cifar10
* cifar100
* fashion_mnist
* mnist
* head_qa
cc @nateraw | {
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"Just a side note: duplicate #3264"
] | "2021-12-01T18:21:33" | "2021-12-11T12:50:23" | "2021-12-06T11:16:31" | CONTRIBUTOR | null | ## Describe the bug
http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz returns Access Denied now.
However, https://drive.google.com/file/d/0BwT5wj_P7BKXb2hfM3d2RHU1ckE/view?usp=sharing from the original Reddit post https://www.reddit.com/r/datasets/comments/1uyd0t/200000_jeopardy_questions_in_a_json_file/ may work.
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
```
```python
>>> from datasets import load_dataset
>>> load_dataset("jeopardy")
```
## Expected results
The download completes.
## Actual results
```shell
Downloading: 4.18kB [00:00, 1.60MB/s]
Downloading: 2.03kB [00:00, 1.04MB/s]
Using custom data configuration default
Downloading and preparing dataset jeopardy/default (download: 12.13 MiB, generated: 34.46 MiB, post-processed: Unknown size, total: 46.59 MiB) to /Users/mike/.cache/huggingface/datasets/jeopardy/default/0.1.0/25ee3e4a73755e637b8810f6493fd36e4523dea3ca8a540529d0a6e24c7f9810...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/load.py", line 1632, in load_dataset
use_auth_token=use_auth_token,
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/builder.py", line 608, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/Users/mike/.cache/huggingface/modules/datasets_modules/datasets/jeopardy/25ee3e4a73755e637b8810f6493fd36e4523dea3ca8a540529d0a6e24c7f9810/jeopardy.py", line 72, in _split_generators
filepath = dl_manager.download_and_extract(_DATA_URL)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 197, in download
download_func, url_or_urls, map_tuple=True, num_proc=download_config.num_proc, disable_tqdm=False
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 197, in map_nested
return function(data_struct)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 305, in cached_path
use_auth_token=download_config.use_auth_token,
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 594, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz
```
---
```shell
> curl http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz
```
```xml
<?xml version="1.0" encoding="UTF-8"?>
<Error><Code>AccessDenied</Code><Message>Access Denied</Message><RequestId>70Y9R36XNPEQXMGV</RequestId><HostId>G6F5AK4qo7JdaEdKGMtS0P6gdLPeFOdEfSEfvTOZEfk9km0/jAfp08QLfKSTFFj1oWIKoAoBehM=</HostId></Error>
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.14.0
- Platform: macOS Catalina 10.15.7
- Python version: 3.7.12
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3360 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3360/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3360/comments | https://api.github.com/repos/huggingface/datasets/issues/3360/events | https://github.com/huggingface/datasets/pull/3360 | 1,068,724,697 | PR_kwDODunzps4vQ_16 | 3,360 | Add The Pile USPTO subset | {
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- USPTO subset of The Pile: "uspto" config
Close bigscience-workshop/data_tooling#297.
CC: @StellaAthena | {
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https://api.github.com/repos/huggingface/datasets/issues/3359 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3359/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3359/comments | https://api.github.com/repos/huggingface/datasets/issues/3359/events | https://github.com/huggingface/datasets/pull/3359 | 1,068,638,213 | PR_kwDODunzps4vQtI0 | 3,359 | Add The Pile Free Law subset | {
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- Free Law subset of The Pile: "free_law" config
Close bigscience-workshop/data_tooling#75.
CC: @StellaAthena | {
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https://api.github.com/repos/huggingface/datasets/issues/3358 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3358/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3358/comments | https://api.github.com/repos/huggingface/datasets/issues/3358/events | https://github.com/huggingface/datasets/issues/3358 | 1,068,623,216 | I_kwDODunzps4_seVw | 3,358 | add new field, and get errors | {
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"Hi, \r\n\r\ncould you please post this question on our [Forum](https://discuss.huggingface.co/) as we keep issues for bugs and feature requests? ",
"> Hi,\r\n> \r\n> could you please post this question on our [Forum](https://discuss.huggingface.co/) as we keep issues for bugs and feature requests?\r\n\r\nok."
] | "2021-12-01T16:35:38" | "2021-12-02T02:26:22" | "2021-12-02T02:26:22" | NONE | null | after adding new field **tokenized_examples["example_id"]**, and get errors below,
I think it is due to changing data to tensor, and **tokenized_examples["example_id"]** is string list
**all fields**
```
***************** train_dataset 1: Dataset({
features: ['attention_mask', 'end_positions', 'example_id', 'input_ids', 'start_positions', 'token_type_ids'],
num_rows: 87714
})
```
**Errors**
```
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/transformers/tokenization_utils_base.py", line 705, in convert_to_tensors
tensor = as_tensor(value)
ValueError: too many dimensions 'str'
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3357 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3357/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3357/comments | https://api.github.com/repos/huggingface/datasets/issues/3357/events | https://github.com/huggingface/datasets/pull/3357 | 1,068,607,382 | PR_kwDODunzps4vQmcL | 3,357 | Update languages in aeslc dataset card | {
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] | closed | false | null | [] | null | [] | "2021-12-01T16:20:46" | "2022-09-23T13:16:49" | "2022-09-23T13:16:49" | CONTRIBUTOR | null | After having worked a bit with the dataset.
As far as I know, it is solely in English (en-US). There are only a few mails in Spanish, French or German (less than a dozen I would estimate). | {
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https://api.github.com/repos/huggingface/datasets/issues/3356 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3356/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3356/comments | https://api.github.com/repos/huggingface/datasets/issues/3356/events | https://github.com/huggingface/datasets/pull/3356 | 1,068,503,932 | PR_kwDODunzps4vQQLD | 3,356 | to_tf_dataset() refactor | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T14:54:30" | "2021-12-09T10:26:53" | "2021-12-09T10:26:53" | MEMBER | null | This is the promised cleanup to `to_tf_dataset()` now that the course is out of the way! The main changes are:
- A collator is always required (there was way too much hackiness making things like labels work without it)
- Lots of cleanup and a lot of code moved to `_get_output_signature`
- Should now handle it gracefully when the data collator adds unexpected columns | {
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https://api.github.com/repos/huggingface/datasets/issues/3355 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3355/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3355/comments | https://api.github.com/repos/huggingface/datasets/issues/3355/events | https://github.com/huggingface/datasets/pull/3355 | 1,068,468,573 | PR_kwDODunzps4vQIoy | 3,355 | Extend support for streaming datasets that use pd.read_excel | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T14:22:43" | "2021-12-17T07:24:19" | "2021-12-17T07:24:18" | MEMBER | null | This PR fixes error:
```
ValueError: Cannot seek streaming HTTP file
```
CC: @severo | {
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https://api.github.com/repos/huggingface/datasets/issues/3354 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3354/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3354/comments | https://api.github.com/repos/huggingface/datasets/issues/3354/events | https://github.com/huggingface/datasets/pull/3354 | 1,068,307,271 | PR_kwDODunzps4vPl9d | 3,354 | Remove duplicate name from dataset cards | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T11:45:40" | "2021-12-01T13:14:30" | "2021-12-01T13:14:29" | MEMBER | null | Remove duplicate name from dataset card for:
- ajgt_twitter_ar
- emotone_ar | {
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https://api.github.com/repos/huggingface/datasets/issues/3353 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3353/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3353/comments | https://api.github.com/repos/huggingface/datasets/issues/3353/events | https://github.com/huggingface/datasets/issues/3353 | 1,068,173,783 | I_kwDODunzps4_qwnX | 3,353 | add one field "example_id", but I can't see it in the "comput_loss" function | {
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"Hi ! Your function looks fine, I used to map `squad` locally and it indeed added the `example_id` field correctly.\r\n\r\nHowever I think that in the `compute_loss` method only a subset of the fields are available: the model inputs. Since `example_id` is not a model input (it's not passed as a parameter to the model), the data loader doesn't need to return it by default.\r\n\r\nHowever you can disable this behavior by setting `remove_unused_columns` to `False` to your training arguments. In this case in `compute_loss` you will get the full item with all the fields.\r\n\r\nNote that since the model doesn't take `example_id` as input, you will have to remove it from the inputs when `model(**inputs)` is called",
"Hi, I have set **args.remove_unused_columns=False** and **training_args.remove_unused_columns=False**, but the field doesn't been contained yet.\r\n```\r\ndef main():\r\n argp = HfArgumentParser(TrainingArguments)\r\n # The HfArgumentParser object collects command-line arguments into an object (and provides default values for unspecified arguments).\r\n # In particular, TrainingArguments has several keys that you'll need/want to specify (when you call run.py from the command line):\r\n # --do_train\r\n # When included, this argument tells the script to train a model.\r\n # See docstrings for \"--task\" and \"--dataset\" for how the training dataset is selected.\r\n # --do_eval\r\n # When included, this argument tells the script to evaluate the trained/loaded model on the validation split of the selected dataset.\r\n # --per_device_train_batch_size <int, default=8>\r\n # This is the training batch size.\r\n # If you're running on GPU, you should try to make this as large as you can without getting CUDA out-of-memory errors.\r\n # For reference, with --max_length=128 and the default ELECTRA-small model, a batch size of 32 should fit in 4gb of GPU memory.\r\n # --num_train_epochs <float, default=3.0>\r\n # How many passes to do through the training data.\r\n # --output_dir <path>\r\n # Where to put the trained model checkpoint(s) and any eval predictions.\r\n # *This argument is required*.\r\n\r\n argp.add_argument('--model', type=str,\r\n default='google/electra-small-discriminator',\r\n help=\"\"\"This argument specifies the base model to fine-tune.\r\n This should either be a HuggingFace model ID (see https://huggingface.co/models)\r\n or a path to a saved model checkpoint (a folder containing config.json and pytorch_model.bin).\"\"\")\r\n argp.add_argument('--task', type=str, choices=['nli', 'qa'], required=True,\r\n help=\"\"\"This argument specifies which task to train/evaluate on.\r\n Pass \"nli\" for natural language inference or \"qa\" for question answering.\r\n By default, \"nli\" will use the SNLI dataset, and \"qa\" will use the SQuAD dataset.\"\"\")\r\n argp.add_argument('--dataset', type=str, default=None,\r\n help=\"\"\"This argument overrides the default dataset used for the specified task.\"\"\")\r\n argp.add_argument('--max_length', type=int, default=128,\r\n help=\"\"\"This argument limits the maximum sequence length used during training/evaluation.\r\n Shorter sequence lengths need less memory and computation time, but some examples may end up getting truncated.\"\"\")\r\n argp.add_argument('--max_train_samples', type=int, default=None,\r\n help='Limit the number of examples to train on.')\r\n argp.add_argument('--max_eval_samples', type=int, default=None,\r\n help='Limit the number of examples to evaluate on.')\r\n\r\n argp.remove_unused_columns = False\r\n training_args, args = argp.parse_args_into_dataclasses()\r\n args.remove_unused_columns=False\r\n training_args.remove_unused_columns=False\r\n```\r\n\r\n\r\n```\r\n**************** train_dataset: Dataset({\r\n features: ['id', 'title', 'context', 'question', 'answers'],\r\n num_rows: 87599\r\n})\r\n\r\n\r\n**************** train_dataset_featurized: Dataset({\r\n features: ['attention_mask', 'end_positions', 'input_ids', 'start_positions', 'token_type_ids'],\r\n num_rows: 87714\r\n})\r\n```",
"Hi, I print the value, all are set to False, but don't work.\r\n```\r\n********************* training_args: TrainingArguments(\r\n_n_gpu=1,\r\nadafactor=False,\r\nadam_beta1=0.9,\r\nadam_beta2=0.999,\r\nadam_epsilon=1e-08,\r\ndataloader_drop_last=False,\r\ndataloader_num_workers=0,\r\ndataloader_pin_memory=True,\r\nddp_find_unused_parameters=None,\r\ndebug=[],\r\ndeepspeed=None,\r\ndisable_tqdm=False,\r\ndo_eval=False,\r\ndo_predict=False,\r\ndo_train=True,\r\neval_accumulation_steps=None,\r\neval_steps=None,\r\nevaluation_strategy=IntervalStrategy.NO,\r\nfp16=False,\r\nfp16_backend=auto,\r\nfp16_full_eval=False,\r\nfp16_opt_level=O1,\r\ngradient_accumulation_steps=1,\r\ngreater_is_better=None,\r\ngroup_by_length=False,\r\nignore_data_skip=False,\r\nlabel_names=None,\r\nlabel_smoothing_factor=0.0,\r\nlearning_rate=5e-05,\r\nlength_column_name=length,\r\nload_best_model_at_end=False,\r\nlocal_rank=-1,\r\nlog_level=-1,\r\nlog_level_replica=-1,\r\nlog_on_each_node=True,\r\nlogging_dir=./re_trained_model/runs/Dec01_14-15-08_399b9290604c,\r\nlogging_first_step=False,\r\nlogging_steps=500,\r\nlogging_strategy=IntervalStrategy.STEPS,\r\nlr_scheduler_type=SchedulerType.LINEAR,\r\nmax_grad_norm=1.0,\r\nmax_steps=-1,\r\nmetric_for_best_model=None,\r\nmp_parameters=,\r\nno_cuda=False,\r\nnum_train_epochs=3.0,\r\noutput_dir=./re_trained_model,\r\noverwrite_output_dir=False,\r\npast_index=-1,\r\nper_device_eval_batch_size=8,\r\nper_device_train_batch_size=8,\r\nprediction_loss_only=False,\r\npush_to_hub=False,\r\npush_to_hub_model_id=re_trained_model,\r\npush_to_hub_organization=None,\r\npush_to_hub_token=None,\r\nremove_unused_columns=False,\r\nreport_to=['tensorboard'],\r\nresume_from_checkpoint=None,\r\nrun_name=./re_trained_model,\r\nsave_on_each_node=False,\r\nsave_steps=500,\r\nsave_strategy=IntervalStrategy.STEPS,\r\nsave_total_limit=None,\r\nseed=42,\r\nsharded_ddp=[],\r\nskip_memory_metrics=True,\r\ntpu_metrics_debug=False,\r\ntpu_num_cores=None,\r\nuse_legacy_prediction_loop=False,\r\nwarmup_ratio=0.0,\r\nwarmup_steps=0,\r\nweight_decay=0.0,\r\n)\r\n```\r\n```\r\n********************* args: Namespace(dataset='squad', max_eval_samples=None, max_length=128, max_train_samples=None, model='google/electra-small-discriminator', remove_unused_columns=False, task='qa')\r\n2021-12-01 14:15:10,048 - WARNING - datasets.builder - Reusing dataset squad (/root/.cache/huggingface/datasets/squad/plain_text/1.0.0/d6ec3ceb99ca480ce37cdd35555d6cb2511d223b9150cce08a837ef62ffea453)\r\nSome weights of the model checkpoint at google/electra-small-discriminator were not used when initializing ElectraForQuestionAnswering: ['discriminator_predictions.dense_prediction.weight', 'discriminator_predictions.dense_prediction.bias', 'discriminator_predictions.dense.weight', 'discriminator_predictions.dense.bias']\r\n- This IS expected if you are initializing ElectraForQuestionAnswering from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\r\n- This IS NOT expected if you are initializing ElectraForQuestionAnswering from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\r\nSome weights of ElectraForQuestionAnswering were not initialized from the model checkpoint at google/electra-small-discriminator and are newly initialized: ['qa_outputs.bias', 'qa_outputs.weight']\r\nYou should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\r\nPreprocessing data... (this takes a little bit, should only happen once per dataset)\r\n```",
"Hmmm, it might be because the default data collator removes all the fields with `string` type:\r\n\r\nhttps://github.com/huggingface/transformers/blob/4c0dd199c8305903564c2edeae23d294edd4b321/src/transformers/data/data_collator.py#L107-L112\r\n\r\nI guess you also need a custom data collator that doesn't remove them.",
"can you give a tutorial about how to do this?",
"I overwrite **get_train_dataloader**, and remove **_remove_unused_columns**, but it doesn't work.\r\n\r\n```\r\n def get_train_dataloader(self) -> DataLoader:\r\n \"\"\"\r\n Returns the training :class:`~torch.utils.data.DataLoader`.\r\n\r\n Will use no sampler if :obj:`self.train_dataset` does not implement :obj:`__len__`, a random sampler (adapted\r\n to distributed training if necessary) otherwise.\r\n\r\n Subclass and override this method if you want to inject some custom behavior.\r\n \"\"\"\r\n if self.train_dataset is None:\r\n raise ValueError(\"Trainer: training requires a train_dataset.\")\r\n\r\n train_dataset = self.train_dataset\r\n # if is_datasets_available() and isinstance(train_dataset, datasets.Dataset):\r\n # train_dataset = self._remove_unused_columns(train_dataset, description=\"training\")\r\n\r\n if isinstance(train_dataset, torch.utils.data.IterableDataset):\r\n if self.args.world_size > 1:\r\n train_dataset = IterableDatasetShard(\r\n train_dataset,\r\n batch_size=self.args.train_batch_size,\r\n drop_last=self.args.dataloader_drop_last,\r\n num_processes=self.args.world_size,\r\n process_index=self.args.process_index,\r\n )\r\n\r\n return DataLoader(\r\n train_dataset,\r\n batch_size=self.args.train_batch_size,\r\n collate_fn=self.data_collator,\r\n num_workers=self.args.dataloader_num_workers,\r\n pin_memory=self.args.dataloader_pin_memory,\r\n )\r\n\r\n train_sampler = self._get_train_sampler()\r\n\r\n return DataLoader(\r\n train_dataset,\r\n batch_size=self.args.train_batch_size,\r\n sampler=train_sampler,\r\n collate_fn=self.data_collator,\r\n drop_last=self.args.dataloader_drop_last,\r\n num_workers=self.args.dataloader_num_workers,\r\n pin_memory=self.args.dataloader_pin_memory,\r\n )\r\n```",
"Hi, it works now, thank you.\r\n1. **args.remove_unused_columns=False** and **training_args.remove_unused_columns=False**\r\n2. overwrite **get_train_dataloader**, and remove **_remove_unused_columns**\r\n3. add new fields, and can be got in **inputs**. "
] | "2021-12-01T09:35:09" | "2021-12-01T16:02:39" | "2021-12-01T16:02:39" | NONE | null | Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
...,
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0]], device='cuda:0'), 'end_positions': tensor([ 25, 97, 93, 44, 25, 112, 109, 134], device='cuda:0'), 'input_ids': tensor([[ 101, 2054, 2390, ..., 0, 0, 0],
[ 101, 2054, 2515, ..., 0, 0, 0],
[ 101, 2054, 2106, ..., 0, 0, 0],
...,
[ 101, 2339, 2001, ..., 0, 0, 0],
[ 101, 2054, 2515, ..., 0, 0, 0],
[ 101, 2054, 2003, ..., 0, 0, 0]], device='cuda:0'), 'start_positions': tensor([ 20, 90, 89, 41, 25, 96, 106, 132], device='cuda:0'), 'token_type_ids': tensor([[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
...,
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0]], device='cuda:0')}
```
```
# This function preprocesses a question answering dataset, tokenizing the question and context text
# and finding the right offsets for the answer spans in the tokenized context (to use as labels).
# Adapted from https://github.com/huggingface/transformers/blob/master/examples/pytorch/question-answering/run_qa.py
def prepare_train_dataset_qa(examples, tokenizer, max_seq_length=None):
questions = [q.lstrip() for q in examples["question"]]
max_seq_length = tokenizer.model_max_length
# tokenize both questions and the corresponding context
# if the context length is longer than max_length, we split it to several
# chunks of max_length
tokenized_examples = tokenizer(
questions,
examples["context"],
truncation="only_second",
max_length=max_seq_length,
stride=min(max_seq_length // 2, 128),
return_overflowing_tokens=True,
return_offsets_mapping=True,
padding="max_length"
)
# Since one example might give us several features if it has a long context,
# we need a map from a feature to its corresponding example.
sample_mapping = tokenized_examples.pop("overflow_to_sample_mapping")
# The offset mappings will give us a map from token to character position
# in the original context. This will help us compute the start_positions
# and end_positions to get the final answer string.
offset_mapping = tokenized_examples.pop("offset_mapping")
tokenized_examples["start_positions"] = []
tokenized_examples["end_positions"] = []
tokenized_examples["example_id"] = []
for i, offsets in enumerate(offset_mapping):
input_ids = tokenized_examples["input_ids"][i]
# We will label features not containing the answer the index of the CLS token.
cls_index = input_ids.index(tokenizer.cls_token_id)
sequence_ids = tokenized_examples.sequence_ids(i)
# from the feature idx to sample idx
sample_index = sample_mapping[i]
# get the answer for a feature
answers = examples["answers"][sample_index]
tokenized_examples["example_id"].append(examples["id"][sample_index])
if len(answers["answer_start"]) == 0:
tokenized_examples["start_positions"].append(cls_index)
tokenized_examples["end_positions"].append(cls_index)
else:
# Start/end character index of the answer in the text.
start_char = answers["answer_start"][0]
end_char = start_char + len(answers["text"][0])
# Start token index of the current span in the text.
token_start_index = 0
while sequence_ids[token_start_index] != 1:
token_start_index += 1
# End token index of the current span in the text.
token_end_index = len(input_ids) - 1
while sequence_ids[token_end_index] != 1:
token_end_index -= 1
# Detect if the answer is out of the span (in which case this feature is labeled with the CLS index).
if not (offsets[token_start_index][0] <= start_char and
offsets[token_end_index][1] >= end_char):
tokenized_examples["start_positions"].append(cls_index)
tokenized_examples["end_positions"].append(cls_index)
else:
# Otherwise move the token_start_index and token_end_index to the two ends of the answer.
# Note: we could go after the last offset if the answer is the last word (edge case).
while token_start_index < len(offsets) and \
offsets[token_start_index][0] <= start_char:
token_start_index += 1
tokenized_examples["start_positions"].append(
token_start_index - 1)
while offsets[token_end_index][1] >= end_char:
token_end_index -= 1
tokenized_examples["end_positions"].append(token_end_index + 1)
return tokenized_examples
```
_Originally posted by @yanllearnn in https://github.com/huggingface/datasets/issues/3333#issuecomment-983457161_ | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T08:22:27" | "2021-12-01T10:49:02" | "2021-12-01T10:49:01" | MEMBER | null | Fix LABR dataset to make it streamable.
Related to: #3350. | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T08:13:17" | "2022-02-28T09:22:03" | "2021-12-28T15:05:08" | CONTRIBUTOR | null | Fixes #1837. | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T07:56:48" | "2021-12-01T08:15:01" | "2021-12-01T08:15:00" | MEMBER | null | This PR will fix streaming of datasets served with gzip content-encoding:
```
ClientPayloadError: 400, message='Can not decode content-encoding: gzip'
```
Fix #2918.
CC: @severo | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T01:37:51" | "2021-12-20T16:07:27" | "2021-12-20T16:07:27" | CONTRIBUTOR | null | fix for the remaining files https://github.com/huggingface/datasets/issues/3171 | {
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} | [] | closed | false | null | [] | null | [] | "2021-12-01T01:01:18" | "2021-12-07T16:06:57" | "2021-12-07T16:06:57" | CONTRIBUTOR | null | In order to properly locate downloaded ckpt files key name needs to match filename. Correcting change introduced in #3235 | {
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} | [] | closed | false | null | [] | null | [] | "2021-11-30T22:34:17" | "2021-12-04T00:22:22" | "2021-12-04T00:22:11" | CONTRIBUTOR | null | * In this PR, I added the option to iterate through zipfiles for `download_manager.py` only.
* Next PR will be the same applied to `streaming_download_manager.py`.
* Related issue #3272.
## Comments :
* There is no `.isreg()` equivalent in zipfile library to check if file is Regular so I used `.is_dir()` instead to skip directories.
* For now I got `streaming_download_manager.py` working for local zip files, but not for urls. I get the following error when I test it on an archive in google drive, so still working on it. `BlockSizeError: Got more bytes so far (>2112) than requested (22)`
## Tasks :
- [x] download_manager.py
- [ ] streaming_download_manager.py | {
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"Scratch that, probably the old and incompatible usage of dataset builder from promptsource.",
"Actually, re-opening this issue cause the error persists\r\n\r\n```python\r\n>>> load_dataset(\"qed\")\r\nDownloading and preparing dataset qed/qed (download: 13.43 MiB, generated: 9.70 MiB, post-processed: Unknown size, total: 23.14 MiB) to /home/victor_huggingface_co/.cache/huggingface/datasets/qed/qed/1.0.0/47d8b6f033393aa520a8402d4baf2d6bdc1b2fbde3dc156e595d2ef34caf7d75...\r\n100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 2/2 [00:00<00:00, 2228.64it/s]\r\nTraceback (most recent call last): \r\n File \"<stdin>\", line 1, in <module>\r\n File \"/home/victor_huggingface_co/miniconda3/envs/promptsource/lib/python3.7/site-packages/datasets/load.py\", line 1669, in load_dataset\r\n use_auth_token=use_auth_token,\r\n File \"/home/victor_huggingface_co/miniconda3/envs/promptsource/lib/python3.7/site-packages/datasets/builder.py\", line 594, in download_and_prepare\r\n dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs\r\n File \"/home/victor_huggingface_co/miniconda3/envs/promptsource/lib/python3.7/site-packages/datasets/builder.py\", line 681, in _download_and_prepare\r\n self._prepare_split(split_generator, **prepare_split_kwargs)\r\n File \"/home/victor_huggingface_co/miniconda3/envs/promptsource/lib/python3.7/site-packages/datasets/builder.py\", line 1083, in _prepare_split\r\n num_examples, num_bytes = writer.finalize()\r\n File \"/home/victor_huggingface_co/miniconda3/envs/promptsource/lib/python3.7/site-packages/datasets/arrow_writer.py\", line 468, in finalize\r\n self.write_examples_on_file()\r\n File \"/home/victor_huggingface_co/miniconda3/envs/promptsource/lib/python3.7/site-packages/datasets/arrow_writer.py\", line 339, in write_examples_on_file\r\n pa_array = pa.array(typed_sequence)\r\n File \"pyarrow/array.pxi\", line 229, in pyarrow.lib.array\r\n File \"pyarrow/array.pxi\", line 110, in pyarrow.lib._handle_arrow_array_protocol\r\n File \"/home/victor_huggingface_co/miniconda3/envs/promptsource/lib/python3.7/site-packages/datasets/arrow_writer.py\", line 125, in __arrow_array__\r\n out = pa.array(cast_to_python_objects(self.data, only_1d_for_numpy=True), type=type)\r\n File \"pyarrow/array.pxi\", line 315, in pyarrow.lib.array\r\n File \"pyarrow/array.pxi\", line 39, in pyarrow.lib._sequence_to_array\r\n File \"pyarrow/error.pxi\", line 143, in pyarrow.lib.pyarrow_internal_check_status\r\n File \"pyarrow/error.pxi\", line 99, in pyarrow.lib.check_status\r\npyarrow.lib.ArrowInvalid: Could not convert 'in' with type str: tried to convert to boolean\r\n```\r\n\r\nEnvironment (datasets and pyarrow):\r\n\r\n```bash\r\n(promptsource) victor_huggingface_co@victor-dev:~/promptsource$ datasets-cli env\r\n\r\nCopy-and-paste the text below in your GitHub issue.\r\n\r\n- `datasets` version: 1.16.1\r\n- Platform: Linux-5.0.0-1020-gcp-x86_64-with-debian-buster-sid\r\n- Python version: 3.7.11\r\n- PyArrow version: 6.0.1\r\n```\r\n```bash\r\n(promptsource) victor_huggingface_co@victor-dev:~/promptsource$ pip show pyarrow\r\nName: pyarrow\r\nVersion: 6.0.1\r\nSummary: Python library for Apache Arrow\r\nHome-page: https://arrow.apache.org/\r\nAuthor: \r\nAuthor-email: \r\nLicense: Apache License, Version 2.0\r\nLocation: /home/victor_huggingface_co/miniconda3/envs/promptsource/lib/python3.7/site-packages\r\nRequires: numpy\r\nRequired-by: streamlit, datasets\r\n```"
] | "2021-11-30T20:11:42" | "2021-12-14T14:39:05" | "2021-12-14T14:39:05" | CONTRIBUTOR | null | ## Describe the bug
Loading QED was fine until 1.15.0.
related: bigscience-workshop/promptsource#659, bigscience-workshop/promptsource#670
Not sure where the root cause is, but here are some candidates:
- #3158
- #3120
- #3196
- #2891
## Steps to reproduce the bug
```python
load_dataset("qed")
```
## Expected results
Loading completed.
## Actual results
```shell
ArrowInvalid: Could not convert in with type str: tried to convert to boolean
Traceback:
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/streamlit/script_runner.py", line 354, in _run_script
exec(code, module.__dict__)
File "/Users/s0s0cr3/Documents/GitHub/promptsource/promptsource/app.py", line 260, in <module>
dataset = get_dataset(dataset_key, str(conf_option.name) if conf_option else None)
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/streamlit/caching.py", line 543, in wrapped_func
return get_or_create_cached_value()
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/streamlit/caching.py", line 527, in get_or_create_cached_value
return_value = func(*args, **kwargs)
File "/Users/s0s0cr3/Documents/GitHub/promptsource/promptsource/utils.py", line 49, in get_dataset
builder_instance.download_and_prepare()
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/builder.py", line 697, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/builder.py", line 1106, in _prepare_split
num_examples, num_bytes = writer.finalize()
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/arrow_writer.py", line 456, in finalize
self.write_examples_on_file()
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/arrow_writer.py", line 325, in write_examples_on_file
pa_array = pa.array(typed_sequence)
File "pyarrow/array.pxi", line 222, in pyarrow.lib.array
File "pyarrow/array.pxi", line 110, in pyarrow.lib._handle_arrow_array_protocol
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/arrow_writer.py", line 121, in __arrow_array__
out = pa.array(cast_to_python_objects(self.data, only_1d_for_numpy=True), type=type)
File "pyarrow/array.pxi", line 305, in pyarrow.lib.array
File "pyarrow/array.pxi", line 39, in pyarrow.lib._sequence_to_array
File "pyarrow/error.pxi", line 122, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 84, in pyarrow.lib.check_status
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.0, 1.16.1
- Platform: macOS 1.15.7 or above
- Python version: 3.7.12 and 3.9
- PyArrow version: 3.0.0, 5.0.0, 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3345 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3345/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3345/comments | https://api.github.com/repos/huggingface/datasets/issues/3345/events | https://github.com/huggingface/datasets/issues/3345 | 1,067,622,951 | I_kwDODunzps4_oqIn | 3,345 | Failed to download species_800 from Google Drive zip file | {
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"Hi,\r\n\r\nthe dataset is downloaded normally on my machine. Maybe the URL was down at the time of your download. Could you try again?",
"> Hi,\r\n> \r\n> the dataset is downloaded normally on my machine. Maybe the URL was down at the time of your download. Could you try again?\r\n\r\nI have tried that many times with both load_dataset() and a browser almost simultaneously. The browser always works for me while load_dataset() fails.",
"@mariosasko \r\n> the dataset is downloaded normally on my machine. Maybe the URL was down at the time of your download. Could you try again?\r\n\r\nI've tried yet again just a moment ago. This time I realize that, the step `(... post-processed: Unknown size, total: 20.89 MiB) to /Users/mike/.cache/huggingface/datasets/species800/species_800/1.0.0/532167f0bb8fbc0d77d6d03c4fd642c8c55527b9c5f2b1da77f3d00b0e559976...` and the one after seem unstable. If I want to retry, I will have to delete it (and probably other cache lock files). It **_sometimes_** works.\r\n\r\nBut I didn't try `download_mode=\"force_redownload\"` yet.\r\n\r\nAnyway, I suppose this isn't really a pressing issue for the time being, so I'm going to close this. Thank you.\r\n\r\n"
] | "2021-11-30T20:00:28" | "2021-12-01T17:53:15" | "2021-12-01T17:53:15" | CONTRIBUTOR | null | ## Describe the bug
One can manually download the zip file on Google Drive, but `load_dataset()` cannot.
related: #3248
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
```
```python
>>> from datasets import load_dataset
>>> s800 = load_dataset("species_800")
```
## Expected results
species_800 downloaded.
## Actual results
```shell
Downloading: 5.68kB [00:00, 1.22MB/s]
Downloading: 2.70kB [00:00, 691kB/s]
Downloading and preparing dataset species800/species_800 (download: 17.36 MiB, generated: 3.53 MiB, post-processed: Unknown size, total: 20.89 MiB) to /Users/mike/.cache/huggingface/datasets/species800/species_800/1.0.0/532167f0bb8fbc0d77d6d03c4fd642c8c55527b9c5f2b1da77f3d00b0e559976...
0%| | 0/1 [00:00<?, ?it/s]Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/load.py", line 1632, in load_dataset
use_auth_token=use_auth_token,
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/builder.py", line 608, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/Users/mike/.cache/huggingface/modules/datasets_modules/datasets/species_800/532167f0bb8fbc0d77d6d03c4fd642c8c55527b9c5f2b1da77f3d00b0e559976/species_800.py", line 104, in _split_generators
downloaded_files = dl_manager.download_and_extract(urls_to_download)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 197, in download
download_func, url_or_urls, map_tuple=True, num_proc=download_config.num_proc, disable_tqdm=False
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 209, in map_nested
for obj in utils.tqdm(iterable, disable=disable_tqdm)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 209, in <listcomp>
for obj in utils.tqdm(iterable, disable=disable_tqdm)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 143, in _single_map_nested
return function(data_struct)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 305, in cached_path
use_auth_token=download_config.use_auth_token,
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/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://drive.google.com/u/0/uc?id=1OletxmPYNkz2ltOr9pyT0b0iBtUWxslh&export=download/
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.14,0 1.15.0, 1.16.1
- Platform: macOS Catalina 10.15.7
- Python version: 3.7.12
- PyArrow version: 6.0.1
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Let me know if I'm missing anything @lhoestq :) | {
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https://api.github.com/repos/huggingface/datasets/issues/3343 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3343/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3343/comments | https://api.github.com/repos/huggingface/datasets/issues/3343/events | https://github.com/huggingface/datasets/pull/3343 | 1,067,505,507 | PR_kwDODunzps4vM8yB | 3,343 | Better error message when download fails | {
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} | [] | closed | false | null | [] | null | [] | "2021-11-30T17:38:50" | "2021-12-01T11:27:59" | "2021-12-01T11:27:58" | MEMBER | null | From our discussions in https://github.com/huggingface/datasets/issues/3269 and https://github.com/huggingface/datasets/issues/3282 it would be nice to have better messages if a download fails.
In particular the error now shows:
- the error from the HEAD request if there's one
- otherwise the response code of the HEAD request
I also added an error to tell users to pass `use_auth_token` when the Hugging Face Hub returns 401 (Unauthorized).
While paying around with this I also fixed a minor issue with the `force_download` parameter that was not always taken into account | {
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https://api.github.com/repos/huggingface/datasets/issues/3342 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3342/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3342/comments | https://api.github.com/repos/huggingface/datasets/issues/3342/events | https://github.com/huggingface/datasets/pull/3342 | 1,067,481,390 | PR_kwDODunzps4vM3wh | 3,342 | Fix ASSET dataset data URLs | {
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} | [] | closed | false | null | [] | null | [] | "2021-11-30T17:13:30" | "2021-12-14T14:50:00" | "2021-12-14T14:50:00" | CONTRIBUTOR | null | Change the branch name "master" to "main" in the data URLs, since facebookresearch has changed that. | {
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"I created a GitHub project to keep track of what needs to be done:\r\nhttps://github.com/huggingface/datasets/projects/3\r\n\r\nI also store my code in a (private for now) repository at https://github.com/huggingface/mirror_canonical_datasets_on_hub",
"I understand that the datasets are mirrored on the Hub now, right? Might I close @lhoestq @SBrandeis?"
] | "2021-11-30T16:42:05" | "2022-01-26T14:47:37" | "2022-01-26T14:47:37" | CONTRIBUTOR | null | - [ ] create a repo on https://hf.co/datasets for every canonical dataset
- [ ] on every commit related to a dataset, update the hf.co repo
See https://github.com/huggingface/moon-landing/pull/1562
@SBrandeis: I let you edit this description if needed to precise the intent. | {
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https://api.github.com/repos/huggingface/datasets/issues/3340 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3340/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3340/comments | https://api.github.com/repos/huggingface/datasets/issues/3340/events | https://github.com/huggingface/datasets/pull/3340 | 1,067,292,636 | PR_kwDODunzps4vMP6Z | 3,340 | Fix JSON ClassLabel casting for integers | {
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} | [] | closed | false | null | [] | null | [] | "2021-11-30T14:19:54" | "2021-12-01T11:27:30" | "2021-12-01T11:27:30" | MEMBER | null | Loading a JSON dataset with ClassLabel feature types currently fails if the JSON data already has integers. Indeed currently it tries to convert the strings to integers without even checking if the data are not integers already.
For example this currently fails:
```python
from datasets import load_dataset, Features, ClassLabel
path = "data.json"
f = Features({"a": ClassLabel(names=["neg", "pos"])})
d = load_dataset("json", data_files=path, features=f)
```
data.json
```json
{"a": 0}
{"a": 1}
```
I fixed that by adding a line that checks the type of the JSON data before trying to convert them
cc @albertvillanova let me know if it sounds good to you | {
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