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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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- _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/3399 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3399/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3399/comments | https://api.github.com/repos/huggingface/datasets/issues/3399/events | https://github.com/huggingface/datasets/issues/3399 | 1,073,593,861 | I_kwDODunzps4__b4F | 3,399 | Add Wikisource dataset | {
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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | 2 | 2021-12-07 17:21:31+00:00 | 2024-10-09 16:11:27+00:00 | 2024-10-09 16:11:26+00:00 | MEMBER | null | null | null | null | ## Adding a Dataset
- **Name:** *wikisource*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** Additional high quality textual data, besides Wikipedia.
Add loading script as "canonical" dataset (as it is the case for ""wikipedia").
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
CC: @geohci, @yjernite | {
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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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This should be done for all pre-processed datasets under "wikimedia" org in the Hub: https://huggingface.co/wikimedia
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} | 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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**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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"gists... | null | 2 | 2021-12-07 14:08:30+00:00 | 2021-12-21 17:00:09+00:00 | 2021-12-21 17:00:09+00:00 | COLLABORATOR | null | null | null | 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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"color": "d93f0b",... | open | false | null | [] | null | 0 | 2021-12-07 10:37:02+00:00 | 2021-12-09 15:56:03+00:00 | NaT | NONE | null | null | null | null | ## Adding a Dataset
- **Name:** *Common Voice Belarusian Dataset*
- **Description:** *[commonvoice.mozilla.org/be](https://commonvoice.mozilla.org/be)*
- **Data:** *[commonvoice.mozilla.org/be/datasets](https://commonvoice.mozilla.org/be/datasets)*
- **Motivation:** *It has more than 7GB of data, so it will be great to have it in this package so anyone can try to train something for Belarusian language.*
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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**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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* 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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] | closed | false | null | [] | null | 1 | 2021-12-06 18:22:49+00:00 | 2021-12-06 20:22:05+00:00 | 2021-12-06 20:22:05+00:00 | NONE | null | null | null | 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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] | open | false | null | [] | null | 2 | 2021-12-06 14:06:11+00:00 | 2022-10-05 10:40:22+00:00 | NaT | CONTRIBUTOR | null | null | null | null | ## Adding a Dataset
- **Name:** EDGAR Database
- **Description:** https://www.sec.gov/edgar/about EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system, is the primary system for companies and others submitting documents under the Securities Act of 1933, the Securities Exchange Act of 1934, the Trust Indenture Act of 1939, and the Investment Company Act of 1940. Containing millions of company and individual filings, EDGAR benefits investors, corporations, and the U.S. economy overall by increasing the efficiency, transparency, and fairness of the securities markets. The system processes about 3,000 filings per day, serves up 3,000 terabytes of data to the public annually, and accommodates 40,000 new filers per year on average. EDGAR® and EDGARLink® are registered trademarks of the SEC.
- **Data:** https://www.sec.gov/os/accessing-edgar-data
- **Motivation:** Enabling and improving FSI (Financial Services Industry) datasets to increase ease of use
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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} | 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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} | Create Language Modeling task to be able to specify the input "text" column in a dataset.
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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} | 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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] | open | false | null | [] | null | 3 | 2021-12-06 05:20:54+00:00 | 2022-01-17 15:25:01+00:00 | NaT | CONTRIBUTOR | null | null | null | null | **Is your feature request related to a problem? Please describe.**
A `torch.utils.data.Dataset.__getitem__` operates on a single example.
But 🤗 `Datasets.with_transform` doesn't seem to allow non-batched transform.
**Describe the solution you'd like**
Have a `batched=True` argument in `Datasets.with_transform`
**Describe alternatives you've considered**
* Convert a non-batched transform function to batched one myself.
* Wrap a 🤗 Dataset with torch Dataset, and add a `__getitem__`. 🙄
* Have `lazy=False` in `Dataset.map`, and returns a `LazyDataset` if `lazy=True`. This way the same `map` interface can be used, and existing code can be updated with one argument change. | null | {
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This way, all the languages covered in the translation are available in a easy way. | {
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} | 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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} | [] | closed | false | null | [] | null | 2 | 2021-12-04 20:54:49+00:00 | 2021-12-14 10:28:55+00:00 | 2021-12-14 10:28:55+00:00 | CONTRIBUTOR | null | null | 0 | {
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} | 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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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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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! 🤗 | {
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} | 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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} | Add The Pile subsets:
- pubmed
- ubuntu_irc
- europarl
- hacker_news
- nih_exporter
Close bigscience-workshop/data_tooling#301.
CC: @StellaAthena | {
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} | This is a draft PR since I ran into few small problems.
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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} | Proposed solution:
- 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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... | null | 2 | 2021-12-03 10:10:54+00:00 | 2021-12-08 14:14:41+00:00 | 2021-12-08 14:14:41+00:00 | NONE | null | null | null | 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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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | 0 | 2021-12-03 09:48:24+00:00 | 2021-12-16 18:03:31+00:00 | 2021-12-16 18:03:31+00:00 | MEMBER | null | null | null | null | Given a community 🤗 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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] | closed | false | null | [] | null | 0 | 2021-12-02 20:21:07+00:00 | 2022-03-18 09:36:48+00:00 | 2022-03-18 09:36:48+00:00 | CONTRIBUTOR | null | null | null | 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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} | 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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} | 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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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | 2 | 2021-12-02 14:04:57+00:00 | 2021-12-16 15:55:19+00:00 | 2021-12-16 15:55:19+00:00 | CONTRIBUTOR | null | null | null | 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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- `other-stuctured-to-text` (before)
- `other-structured-to-text` (now) | {
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- [ ] #2526
- [x] #1842
- [ ] #1810
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
@VictorSanh feel free to add and sort by priority any interesting dataset. I have added the multimodal dataset requests which were already present as issues. | null | {
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] | closed | false | null | [] | null | 1 | 2021-12-02 06:58:20+00:00 | 2023-07-25 18:21:33+00:00 | 2023-07-25 18:21:32+00:00 | MEMBER | null | null | null | null | ## **Is your feature request related to a problem? Please describe.**
Currently, task tags are either exclusively related to text or speech processing:
- https://github.com/huggingface/datasets/blob/master/src/datasets/utils/resources/tasks.json
## **Describe the solution you'd like**
We should also add tasks related to:
- multimodality
- image
- video
CC: @VictorSanh @lewtun @lhoestq @merveenoyan @SBrandeis | {
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Fix #3361 | {
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} | 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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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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- USPTO subset of The Pile: "uspto" config
Close bigscience-workshop/data_tooling#297.
CC: @StellaAthena | {
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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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} | [] | closed | false | null | [] | null | 2 | 2021-12-01 16:35:38+00:00 | 2021-12-02 02:26:22+00:00 | 2021-12-02 02:26:22+00:00 | NONE | null | null | null | 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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} | 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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} | 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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} | This PR fixes error:
```
ValueError: Cannot seek streaming HTTP file
```
CC: @severo | {
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- ajgt_twitter_ar
- emotone_ar | {
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} | [] | closed | false | null | [] | null | 7 | 2021-12-01 09:35:09+00:00 | 2021-12-01 16:02:39+00:00 | 2021-12-01 16:02:39+00:00 | NONE | null | null | null | 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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Related to: #3350. | {
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} | 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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} | fix for the remaining files https://github.com/huggingface/datasets/issues/3171 | {
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} | * 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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... | null | 2 | 2021-11-30 20:11:42+00:00 | 2021-12-14 14:39:05+00:00 | 2021-12-14 14:39:05+00:00 | CONTRIBUTOR | null | null | null | 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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{
"color": "d73a4a",
"default": true,
"description": "Something isn't working",
"id": 1935892857,
"name": "bug",
"node_id": "MDU6TGFiZWwxOTM1ODkyODU3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
}
] | closed | false | null | [] | null | 3 | 2021-11-30 20:00:28+00:00 | 2021-12-01 17:53:15+00:00 | 2021-12-01 17:53:15+00:00 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/3344 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3344/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3344/comments | https://api.github.com/repos/huggingface/datasets/issues/3344/events | https://github.com/huggingface/datasets/pull/3344 | 1,067,567,603 | PR_kwDODunzps4vNJwd | 3,344 | Add ArrayXD docs | {
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} | [] | closed | false | null | [] | null | 0 | 2021-11-30 18:53:31+00:00 | 2021-12-01 20:16:03+00:00 | 2021-12-01 19:35:32+00:00 | MEMBER | null | null | 0 | {
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} | Documents support for dynamic first dimension in `ArrayXD` from #2891, and explain the `ArrayXD` feature in general.
Let me know if I'm missing anything @lhoestq :) | {
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} | 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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} | [] | closed | false | null | [] | null | 1 | 2021-11-30 17:13:30+00:00 | 2021-12-14 14:50:00+00:00 | 2021-12-14 14:50:00+00:00 | CONTRIBUTOR | null | null | 0 | {
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} | Change the branch name "master" to "main" in the data URLs, since facebookresearch has changed that. | {
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https://api.github.com/repos/huggingface/datasets/issues/3341 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3341/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3341/comments | https://api.github.com/repos/huggingface/datasets/issues/3341/events | https://github.com/huggingface/datasets/issues/3341 | 1,067,449,569 | I_kwDODunzps4_n_zh | 3,341 | Mirror the canonical datasets to the Hugging Face Hub | {
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- [ ] 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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} | 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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https://api.github.com/repos/huggingface/datasets/issues/3339 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3339/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3339/comments | https://api.github.com/repos/huggingface/datasets/issues/3339/events | https://github.com/huggingface/datasets/issues/3339 | 1,066,662,477 | I_kwDODunzps4_k_pN | 3,339 | to_tf_dataset fails on TPU | {
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] | open | false | null | [] | null | 5 | 2021-11-30 00:50:52+00:00 | 2021-12-02 14:21:27+00:00 | NaT | NONE | null | null | null | null | Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGouFxqD4OuWfnycW_1TaT276z?usp=sharing
## Expected results
dataset from `to_tf_dataset` works in `model.fit`
Right below the first error in the colab I use `tf.data.Dataset.from_tensor_slices` and `model.fit` works just fine. This is the desired outcome.
## Actual results
```
InternalError: 5 root error(s) found.
(0) INTERNAL: {{function_node __inference_train_function_30558}} failed to connect to all addresses
Additional GRPC error information from remote target /job:localhost/replica:0/task:0/device:CPU:0:
:{"created":"@1638231897.932218653","description":"Failed to pick subchannel","file":"third_party/grpc/src/core/ext/filters/client_channel/client_channel.cc","file_line":3151,"referenced_errors":[{"created":"@1638231897.932216754","description":"failed to connect to all addresses","file":"third_party/grpc/src/core/lib/transport/error_utils.cc","file_line":161,"grpc_status":14}]}
[[{{node StatefulPartitionedCall}}]]
[[MultiDeviceIteratorGetNextFromShard]]
Executing non-communication op <MultiDeviceIteratorGetNextFromShard> originally returned UnavailableError, and was replaced by InternalError to avoid invoking TF network error handling logic.
[[RemoteCall]]
[[IteratorGetNextAsOptional]]
[[tpu_compile_succeeded_assert/_14023832043698465348/_7/_439]]
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyArrow version: 3.0.0
- Tensorflow 2.7.0
- `transformers` 4.12.5
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https://api.github.com/repos/huggingface/datasets/issues/3338 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3338/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3338/comments | https://api.github.com/repos/huggingface/datasets/issues/3338/events | https://github.com/huggingface/datasets/pull/3338 | 1,066,371,235 | PR_kwDODunzps4vJRFM | 3,338 | [WIP] Add doctests for tutorials | {
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} | Opening a PR as discussed with @LysandreJik for some help with doctest issues. The goal is to add doctests for each of the tutorials in the documentation to make sure the code samples work as shown.
### Issues
A doctest has been added in the docstring of the `load_dataset_builder` function in `load.py` to handle variable outputs with the `ELLIPSIS` directive. When I run doctest on the `load_hub.rst` file, doctest should recognize the expected output from the docstring, and the corresponding code sample in `load_hub.rst` should pass. I am having the same issue with handling tracebacks in the `load_dataset` function.
From the docstring:
```
>>> dataset_builder.cache_dir #doctest: +ELLIPSIS
/Users/.../.cache/huggingface/datasets/imdb/plain_text/1.0.0/...
```
Test result:
```
Failed example:
dataset_builder.cache_dir
Expected:
/Users/.../.cache/huggingface/datasets/imdb/plain_text/1.0.0/...
Got:
/Users/steven/.cache/huggingface/datasets/imdb/plain_text/1.0.0/2fdd8b9bcadd6e7055e742a706876ba43f19faee861df134affd7a3f60fc38a1
```
I am able to get the doctest to pass by adding the doctest directives (`ELLIPSIS` and `NORMALIZE_WHITESPACE`) to the code samples in the `rst` file directly. But my understanding is that these directives should also work in the docstrings of the functions. I am running the test from the root of the directory:
```
python -m doctest -v docs/source/load_hub.rst
``` | {
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The newly added typing for Dataset.__getitem__ is Union[Dict, List]. This makes tools like mypy a bit awkward to use as we need to check the type manually. We could use type overloading to make this easier. [Documentation](https://docs.python.org/3/library/typing.html#typing.overload)
## Steps to reproduce the bug
Let's have a file `test.py`
```python
from typing import List, Dict, Any
from datasets import Dataset
ds = Dataset.from_dict({
'a': [1,2,3],
'b': ["1", "2", "3"]
})
one_colum: List[str] = ds['a']
some_index: Dict[Any, Any] = ds[1]
```
## Expected results
Running `mypy test.py` should not give any error.
## Actual results
```
test.py:10: error: Incompatible types in assignment (expression has type "Union[Dict[Any, Any], List[Any]]", variable has type "List[str]")
test.py:11: error: Incompatible types in assignment (expression has type "Union[Dict[Any, Any], List[Any]]", variable has type "Dict[Any, Any]")
Found 2 errors in 1 file (checked 1 source file)
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.13.3
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.8
- PyArrow version: 6.0.1
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} | Add support for multiple dynamic dimensions (e.g. `(None, None, 3)` for arbitrary sized images) and `to_pandas()` conversion for dynamic arrays.
TODOs:
* [ ] Cleaner code
* [ ] Formatting issues (if NumPy doesn't allow broadcasting even though dtype is np.object)
* [ ] Fix some issues with zero-dim tensors
* [ ] Tests
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] | closed | false | null | [] | null | 8 | 2021-11-29 12:31:54+00:00 | 2024-08-31 05:31:28+00:00 | 2024-08-31 05:31:27+00:00 | MEMBER | null | null | null | null | Check potential integration of the Polars library: https://github.com/pola-rs/polars
- Benchmark: https://h2oai.github.io/db-benchmark/
CC: @thomwolf @lewtun
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`!python3 run.py --do_train --task qa --dataset squad-retrain-data/train-v2.0.json --output_dir ./re_trained_model/`
change the dateset to load json by refering to https://huggingface.co/docs/datasets/loading.html
`dataset = datasets.load_dataset('json', data_files=args.dataset)`
Errors:
`Downloading and preparing dataset json/default (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/json/default-c1e124ad488911b8/0.0.0/45636811569ec4a6630521c18235dfbbab83b7ab572e3393c5ba68ccabe98264...
`
_Originally posted by @yanllearnn in https://github.com/huggingface/datasets/issues/730#issuecomment-981095050_ | {
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} | Fix the error message raised if `infered_module_name` is `None` in `CommunityDatasetModuleFactoryWithoutScript.get_module` and make `infer_module_for_data_files` more robust.
In the linked issue, `infer_module_for_data_files` returns `None` because `json` is the second most common extension due to the suffix ordering. Now, we go from the most common to the least common extension and try to map it or return `None`.
Fix #3331 | {
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] | closed | false | null | [] | null | 1 | 2021-11-28 08:54:05+00:00 | 2021-11-29 13:49:44+00:00 | 2021-11-29 13:34:14+00:00 | NONE | null | null | null | null | ## Describe the bug
I add a new question answering dataset to huggingface datasets manually. Here is the link: [luozhouyang/question-answering-datasets](https://huggingface.co/datasets/luozhouyang/question-answering-datasets)
But when I load the dataset, an error raised:
```bash
AttributeError: 'CommunityDatasetModuleFactoryWithoutScript' object has no attribute 'path'
```
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("luozhouyang/question-answering-datasets", data_files=["dureader_robust.train.json"])
```
## Expected results
Load dataset successfully without any error.
## Actual results
```bash
Traceback (most recent call last):
File "/mnt/home/zhouyang.lzy/github/naivenlp/naivenlp/tests/question_answering_tests/dataset_test.py", line 89, in test_load_dataset_with_hf
data_files=["dureader_robust.train.json"],
File "/mnt/home/zhouyang.lzy/.conda/envs/naivenlp/lib/python3.6/site-packages/datasets/load.py", line 1616, in load_dataset
**config_kwargs,
File "/mnt/home/zhouyang.lzy/.conda/envs/naivenlp/lib/python3.6/site-packages/datasets/load.py", line 1443, in load_dataset_builder
path, revision=revision, download_config=download_config, download_mode=download_mode, data_files=data_files
File "/mnt/home/zhouyang.lzy/.conda/envs/naivenlp/lib/python3.6/site-packages/datasets/load.py", line 1157, in dataset_module_factory
raise e1 from None
File "/mnt/home/zhouyang.lzy/.conda/envs/naivenlp/lib/python3.6/site-packages/datasets/load.py", line 1144, in dataset_module_factory
download_mode=download_mode,
File "/mnt/home/zhouyang.lzy/.conda/envs/naivenlp/lib/python3.6/site-packages/datasets/load.py", line 798, in get_module
raise FileNotFoundError(f"No data files or dataset script found in {self.path}")
AttributeError: 'CommunityDatasetModuleFactoryWithoutScript' object has no attribute 'path'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: linux
- Python version: 3.6.13
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3329 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3329/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3329/comments | https://api.github.com/repos/huggingface/datasets/issues/3329/events | https://github.com/huggingface/datasets/issues/3329 | 1,065,096,971 | I_kwDODunzps4_fBcL | 3,329 | Map function: Type error on iter #999 | {
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] | closed | false | null | [] | null | 4 | 2021-11-27 17:53:05+00:00 | 2021-11-29 20:40:15+00:00 | 2021-11-29 20:40:15+00:00 | NONE | null | null | null | null | ## Describe the bug
Using the map function, it throws a type error on iter #999
Here is the code I am calling:
```
dataset = datasets.load_dataset('squad')
dataset['validation'].map(text_numbers_to_int, input_columns=['context'], fn_kwargs={'column': 'context'})
```
text_numbers_to_int returns the input text with numbers replaced in the format {'context': text}
It happens at
`
File "C:\Users\lonek\anaconda3\envs\ai\Lib\site-packages\datasets\arrow_writer.py", line 289, in <listcomp>
[row[0][col] for row in self.current_examples], type=col_type, try_type=col_try_type, col=col
`
The issue is that the list comprehension expects self.current_examples to be type tuple(dict, str), but for some reason 26 out of 1000 of the sefl.current_examples are type tuple(str, str)
Here is an example of what self.current_examples should be
({'context': 'Super Bowl 50 was an...merals 50.'}, '')
Here is an example of what self.current_examples are when it throws the error:
('The Panthers used th... Marriott.', '')
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} | While working on a dataset, I got the error
```
TypeError: Provided `function` which is applied to all elements of table returns a `dict` of types {[type(x) for x in processed_inputs.values()]}. When using `batched=True`, make sure provided `function` returns a `dict` of types like `{allowed_batch_return_types}`.
```
This PR should fix the formatting of this error | {
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] | closed | false | null | [] | null | 1 | 2021-11-26 16:26:36+00:00 | 2021-11-26 16:44:11+00:00 | 2021-11-26 16:44:11+00:00 | CONTRIBUTOR | null | null | null | null | ## Describe the bug
Passing a correctly shaped Numpy-Array to get_nearest_examples leads to the Exception
"Shape of query is incorrect, it has to be either a 1D array or 2D (1, N)"
Probably the reason for this is a wrongly converted assertion.
1.15.1:
`assert len(query.shape) == 1 or (len(query.shape) == 2 and query.shape[0] == 1)`
1.16.1:
```
if len(query.shape) != 1 or (len(query.shape) == 2 and query.shape[0] != 1):
raise ValueError("Shape of query is incorrect, it has to be either a 1D array or 2D (1, N)")
```
## Steps to reproduce the bug
follow the steps described here: https://huggingface.co/course/chapter5/6?fw=tf
```python
question_embedding.shape # (1, 768)
scores, samples = embeddings_dataset.get_nearest_examples(
"embeddings", question_embedding, k=5 # Error
)
# "Shape of query is incorrect, it has to be either a 1D array or 2D (1, N)"
```
## Expected results
Should work without exception
## Actual results
Throws exception
## Environment info
- `datasets` version: 1.15.1
- Platform: Darwin-20.6.0-x86_64-i386-64bit
- Python version: 3.7.12
- PyArrow version: 6.0.
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} | In python 3.10 it's no longer possible to use `functools.wraps` on a method decorated with `classmethod`.
To fix this I inverted the order of the `inject_arrow_table_documentation` and `classmethod` decorators
Fix #3324 | {
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"gists... | null | 0 | 2021-11-26 16:06:14+00:00 | 2021-11-26 16:31:23+00:00 | 2021-11-26 16:31:23+00:00 | MEMBER | null | null | null | null | When importing `datasets` I'm getting this error in python 3.10:
```python
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/__init__.py", line 34, in <module>
from .arrow_dataset import Dataset, concatenate_datasets
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/arrow_dataset.py", line 47, in <module>
from .arrow_reader import ArrowReader
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/arrow_reader.py", line 33, in <module>
from .table import InMemoryTable, MemoryMappedTable, Table, concat_tables
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/table.py", line 334, in <module>
class InMemoryTable(TableBlock):
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/table.py", line 361, in InMemoryTable
def from_pandas(cls, *args, **kwargs):
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/table.py", line 24, in wrapper
out = wraps(arrow_table_method)(method)
File "/Users/quentinlhoest/.pyenv/versions/3.10.0/lib/python3.10/functools.py", line 61, in update_wrapper
wrapper.__wrapped__ = wrapped
AttributeError: readonly attribute
```
This makes the conda build fail.
I'm opening a PR to fix this and do a patch release 1.16.1 | {
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Fix #3320 | {
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It gives an error.
> FileNotFoundError: Couldn't find file at https://github.com/facebookresearch/LASER/raw/master/data/tatoeba/v1/tatoeba.rus-eng.rus
## Steps to reproduce the bug
```python
data=load_dataset("xtreme","tatoeba.rus", split="validation")
```
## Solution
The library tries to access the **master** branch. In the github repo of facebookresearch, it is in the **main** branch. | {
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} | Since #3098 it's now possible to upload a dataset on the Hub directly from python using the `push_to_hub` method.
I just added a section in the "Upload a dataset to the Hub" tutorial.
I kept the section quite simple but let me know if it sounds good to you @LysandreJik @stevhliu :) | {
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As I was filtering very large datasets I noticed the filter method doesn't have the desc parameter which is available in the map method. Why don't we add a desc parameter to the filter method both for consistency and it's nice to give some feedback to users during long operations on Datasets?
**Describe the solution you'd like**
Add desc parameter to Dataset filter method
**Describe alternatives you've considered**
N/A
**Additional context**
N/A
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https://api.github.com/repos/huggingface/datasets/issues/3316 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3316/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3316/comments | https://api.github.com/repos/huggingface/datasets/issues/3316/events | https://github.com/huggingface/datasets/issues/3316 | 1,062,185,822 | I_kwDODunzps4_T6te | 3,316 | Add RedCaps dataset | {
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... | null | 0 | 2021-11-24 09:23:02+00:00 | 2022-01-12 14:13:15+00:00 | 2022-01-12 14:13:15+00:00 | MEMBER | null | null | null | null | ## Adding a Dataset
- **Name:** RedCaps
- **Description:** Web-curated image-text data created by the people, for the people
- **Paper:** https://arxiv.org/abs/2111.11431
- **Data:** https://redcaps.xyz/
- **Motivation:** Multimodal image-text dataset: 12M+ Image-text pairs
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Proposed by @patil-suraj | {
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} | The main use case for this is to make dynamically generated private URLs (like the ones returned by CommonVoice API) compatible with the datasets' caching logic.
Usage example:
```python
import datasets
class CommonVoice(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo()
def _split_generators(self, dl_manager):
dl_manager.download_config.ignore_url_params = True
HUGE_URL = "https://mozilla-common-voice-datasets.s3.dualstack.us-west-2.amazonaws.com/cv-corpus-7.0-2021-07-21/cv-corpus-7.0-2021-07-21-ab.tar.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQ3GQRTO3IU5JYB5K%2F20211125%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20211125T131423Z&X-Amz-Expires=43200&X-Amz-Security-Token=FwoGZXIvYXdzEL7%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaDLsZw7Nj0d9h4rgheyKSBJJ6bxo1JdWLXAUhLMrUB8AXfhP8Ge4F8dtjwXmvGJgkIvdMT7P4YOEE1pS3mW8AyKsz7Z7IRVCIGQrOH1AbxGVVcDoCMMswXEOqL3nJFihKLf99%2F6l8iJVZdzftRUNgMhX5Hz0xSIL%2BzRDpH5nYa7C6YpEdOdW81CFVXybx7WUrX13wc8X4ZlUj7zrWcWf5p2VEIU5Utb7YHVi0Y5TQQiZSDoedQl0j4VmMuFkDzoobIO%2BvilgGeE2kIX0E62X423mEGNu4uQV5JsOuLAtv3GVlemsqEH3ZYrXDuxLmnvGj5HfMtySwI4vKv%2BlnnirD29o7hxvtidXiA8JMWhp93aP%2Fw7sod%2BPPbb5EqP%2B4Qb2GJ1myClOKcLEY0cqoy7XWm8NeVljLJojnFJVS5mNFBAzCCTJ%2FidxNsj8fflzkRoAzYaaPBuOTL1dgtZCdslK3FAuEvw0cik7P9A7IYiULV33otSHKMPcVfNHFsWQljs03gDztsIUWxaXvu6ck5vCcGULsHbfe6xoMPm2bR9jtKLONsslPcnzWIf7%2Fch2w%2F%2BjtTCd9IxaH4kytyJ6mIjpV%2FA%2F2h9qeDnDFsCphnMjAzPQn6tqCgTtPcyJ2b8c94ncgUnE4mepx%2FDa%2FanAEsrg9RPdmbdoPswzHn1IClh91IfSN74u95DZUxlPeZrHG5HxVCN3dKO6j%2Ft1xd20L0hEtazDdKOr8%2FYwGMirp8rp%2BII0pYOwQOrYHqH%2FREX2dRJctJtwE86Qj1eU8BAdXuFIkLC4NWXw%3D&X-Amz-Signature=1b8108d29b0e9c2bf6c7246e58ca8d5749a83de0704757ad8e8a44d78194691f&X-Amz-SignedHeaders=host"
dl_path = dl_manager.download_and_extract(HUGE_URL)
print(dl_path)
HUGE_URL += "&some_new_or_changed_param=12345"
dl_path = dl_manager.download_and_extract(HUGE_URL)
print(dl_path)
dl_manager = datasets.DownloadManager(dataset_name="common_voice")
CommonVoice()._split_generators(dl_manager)
```
Output:
```
/home/user/.cache/huggingface/datasets/downloads/6ef2a377398ff3309554be040caa78414e6562d623dbd0ce8fc262459a7f8ec6
/home/user/.cache/huggingface/datasets/downloads/6ef2a377398ff3309554be040caa78414e6562d623dbd0ce8fc262459a7f8ec6
``` | {
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} | [] | closed | false | null | [] | null | 1 | 2021-11-23 15:55:21+00:00 | 2021-11-24 11:54:13+00:00 | 2021-11-24 11:54:13+00:00 | CONTRIBUTOR | null | null | 0 | {
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} | This PR adds a `with_rank` argument to `map` that gives the user the possibility to pass the rank of each process to their function. This is mostly designed for multi-GPU map (each process can be sent to a different device thanks to the rank). I've also added tests. I'm putting the PR up so you can check the code, I'll add a multi-GPU example to the doc (+ write a bit in the doc for the new arg) | {
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TriviaQA Webpage at http://nlp.cs.washington.edu/triviaqa/ says they do not own the copyright to the data. However, Huggingface datasets at https://huggingface.co/datasets/trivia_qa mentions that the dataset is released under Apache License
Is the License Information on HuggingFace correct? | {
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} | [] | closed | false | null | [] | null | 6 | 2021-11-22 17:54:50+00:00 | 2021-12-02 16:10:29+00:00 | 2021-12-02 16:07:47+00:00 | MEMBER | null | null | 0 | {
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} | First of all thanks for the fantastic library/collection of datasets 🤗
This pull request adds a dataset of metadata from digitised (mostly 19th Century) books from the British Library The [data](https://bl.iro.bl.uk/concern/datasets/1e1ccb46-65b4-4481-b6f8-b8129d5da053) contains various metadata about the books. In addition, a subset of the data includes 'genre' information which can be used for supervised text classification tasks. I hope that this offers easier access to a dataset for doing text classification on GLAM (galleries, libraries, archives and museums) data.
I have tried to create three configurations that provide both an 'easy' version of the dataset if you want to use it for training a genre classification model and a more 'raw' version of the data for other potential use cases for the data. I am open to suggestions if this doesn't make sense.
Similarly, for some of the arrow datatypes, I have had to fall back to strings since there are missing values for some fields/rows but I may have missed a more elegant way of dealing with it. | {
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] | open | false | null | [] | null | 0 | 2021-11-22 16:58:33+00:00 | 2021-11-22 16:58:33+00:00 | NaT | CONTRIBUTOR | null | null | null | null | ## Adding a Dataset
- **Name:** WebSRC
- **Description:** WebSRC is a novel Web-based Structural Reading Comprehension dataset. It consists of 0.44M question-answer pairs, which are collected from 6.5K web pages with corresponding HTML source code, screenshots and metadata.
- **Paper:** https://arxiv.org/abs/2101.09465
- **Data:** https://x-lance.github.io/WebSRC/dashboard.html#
- **Motivation:** Currently adding MarkupLM to HuggingFace Transformers, which achieves SOTA on this dataset.
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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] | closed | false | null | [] | null | 28 | 2021-11-22 12:27:54+00:00 | 2023-02-08 10:31:05+00:00 | 2021-11-29 22:22:37+00:00 | NONE | null | null | null | null | ## Describe the bug
Fatal error when using the library
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('wikiann', 'en')
```
## Expected results
No fatal errors
## Actual results
```
Fatal error condition occurred in D:\bld\aws-c-io_1633633258269\work\source\event_loop.c:74: aws_thread_launch(&cleanup_thread, s_event_loop_destroy_async_thread_fn, el_group, &thread_options) == AWS_OP_SUCCESS
Exiting Application
```
## Environment info
- `datasets` version: 1.15.2.dev0
- Platform: Windows-10-10.0.22504-SP0
- Python version: 3.8.12
- PyArrow version: 6.0.0
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} | Files were counted twice in a structure like:
```
my_dataset_local_path/
├── README.md
└── data/
├── train/
│ ├── shard_0.csv
│ ├── shard_1.csv
│ ├── shard_2.csv
│ └── shard_3.csv
└── valid/
├── shard_0.csv
└── shard_1.csv
```
The reason is that they were matching both `*train*/*` and `*train*/**/*`.
This PR fixes it. @lhoestq | {
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"descrip... | open | false | null | [] | null | 3 | 2021-11-21 00:07:22+00:00 | 2022-01-19 13:55:32+00:00 | NaT | NONE | null | null | null | null | ## Describe the bug
In the repository, every dataset has its metadata in a file called`dataset_infos.json`. But, this file is missing for two datasets: `chr_en` and `mc4`.
## Steps to reproduce the bug
Check [chr_en](https://github.com/huggingface/datasets/tree/master/datasets/chr_en) and [mc4](https://github.com/huggingface/datasets/tree/master/datasets/mc4) | null | {
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... | null | 3 | 2021-11-20 16:57:54+00:00 | 2021-12-08 13:02:15+00:00 | 2021-12-08 13:02:15+00:00 | NONE | null | null | null | null | ## Describe the bug
As the title, nested sequence feature won't encode example if the first item of the outside sequence is an empty list.
## Steps to reproduce the bug
```python
from datasets import Features, Sequence, ClassLabel
features = Features({
'x': Sequence(Sequence(ClassLabel(names=['a', 'b']))),
})
print(features.encode_batch({
'x': [
[['a'], ['b']],
[[], ['b']],
]
}))
```
## Expected results
print `{'x': [[[0], [1]], [[], ['1']]]}`
## Actual results
print `{'x': [[[0], [1]], [[], ['b']]]}`
## Environment info
- `datasets` version: 1.15.1
- Platform: Linux-5.13.0-21-generic-x86_64-with-glibc2.34
- Python version: 3.9.7
- PyArrow version: 6.0.0
## Additional information
I think the issue stems from [here](https://github.com/huggingface/datasets/blob/8555197a3fe826e98bd0206c2d031c4488c53c5c/src/datasets/features/features.py#L847-L848).
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https://api.github.com/repos/huggingface/datasets/issues/3305 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3305/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3305/comments | https://api.github.com/repos/huggingface/datasets/issues/3305/events | https://github.com/huggingface/datasets/pull/3305 | 1,059,161,000 | PR_kwDODunzps4uzZWv | 3,305 | asserts replaced with exception for ``fingerprint.py``, ``search.py``, ``arrow_writer.py`` and ``metric.py`` | {
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} | Addresses #3171
Fixes exception for ``fingerprint.py``, ``search.py``, ``arrow_writer.py`` and ``metric.py`` and modified tests | {
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https://api.github.com/repos/huggingface/datasets/issues/3304 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3304/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3304/comments | https://api.github.com/repos/huggingface/datasets/issues/3304/events | https://github.com/huggingface/datasets/issues/3304 | 1,059,130,494 | I_kwDODunzps4_IQx- | 3,304 | Dataset object has no attribute `to_tf_dataset` | {
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] | closed | false | null | [] | null | 1 | 2021-11-20 12:03:59+00:00 | 2021-11-21 07:07:25+00:00 | 2021-11-21 07:07:25+00:00 | NONE | null | null | null | null | I am following HuggingFace Course. I am at Fine-tuning a model.
Link: https://huggingface.co/course/chapter3/2?fw=tf
I use tokenize_function and `map` as mentioned in the course to process data.
`# define a tokenize function`
`def Tokenize_function(example):`
` return tokenizer(example['sentence'], truncation=True)`
`# tokenize entire data`
`tokenized_data = raw_data.map(Tokenize_function, batched=True)`
I get Dataset object at this point. When I try converting this to a TF dataset object as mentioned in the course, it throws the following error.
`# convert to TF dataset`
`train_data = tokenized_data["train"].to_tf_dataset( `
` columns = ['attention_mask', 'input_ids', 'token_type_ids'], `
` label_cols = ['label'], `
` shuffle = True, `
` collate_fn = data_collator, `
` batch_size = 8 `
`)`
Output:
`---------------------------------------------------------------------------`
`AttributeError Traceback (most recent call last)`
`/tmp/ipykernel_42/103099799.py in <module>`
` 1 # convert to TF dataset`
`----> 2 train_data = tokenized_data["train"].to_tf_dataset( \`
` 3 columns = ['attention_mask', 'input_ids', 'token_type_ids'], \`
` 4 label_cols = ['label'], \`
` 5 shuffle = True, \`
`AttributeError: 'Dataset' object has no attribute 'to_tf_dataset'`
When I look for `dir(tokenized_data["train"])`, there is no method or attribute in the name of `to_tf_dataset`.
Why do I get this error? And how to clear this?
Please help me. | {
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https://api.github.com/repos/huggingface/datasets/issues/3303 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3303/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3303/comments | https://api.github.com/repos/huggingface/datasets/issues/3303/events | https://github.com/huggingface/datasets/issues/3303 | 1,059,129,732 | I_kwDODunzps4_IQmE | 3,303 | DataCollatorWithPadding: TypeError | {
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I am following the HuggingFace course. I am now at Fine-tuning [https://huggingface.co/course/chapter3/3?fw=tf](https://huggingface.co/course/chapter3/3?fw=tf). When I set up `DataCollatorWithPadding` as following I got an error while trying to reproduce the course code in Kaggle. This error occurs with either a CPU-only-device or a GPU-device.
Input:
```checkpoint = 'bert-base-uncased'
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
data_collator = DataCollatorWithPadding(tokenizer=tokenizer, return_tensors="tf")
```
Output:
```---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/tmp/ipykernel_42/1563280798.py in <module>
1 checkpoint = 'bert-base-uncased'
2 tokenizer = AutoTokenizer.from_pretrained(checkpoint)
----> 3 data_collator = DataCollatorWithPadding(tokenizer=tokenizer, return_tensors="pt")
TypeError: __init__() got an unexpected keyword argument 'return_tensors'
```
When I call `help` method, it too confirms that there is no argument `return_tensors`.
Input:
```
help(DataCollatorWithPadding.__init__)
```
Output:
```
Help on function __init__ in module transformers.data.data_collator:
__init__(self, tokenizer: transformers.tokenization_utils_base.PreTrainedTokenizerBase, padding: Union[bool, str, transformers.file_utils.PaddingStrategy] = True, max_length: Union[int, NoneType] = None, pad_to_multiple_of: Union[int, NoneType] = None) -> None
```
But, the source file *[Data Collator - docs](https://huggingface.co/transformers/main_classes/data_collator.html#datacollatorwithpadding)* says that there is such an argument. By default, it returns Pytorch tensors while I need TF tensors.
Where do I miss?
Please help me. | {
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https://api.github.com/repos/huggingface/datasets/issues/3302 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3302/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3302/comments | https://api.github.com/repos/huggingface/datasets/issues/3302/events | https://github.com/huggingface/datasets/pull/3302 | 1,058,907,168 | PR_kwDODunzps4uynjc | 3,302 | fix old_val typo in f-string | {
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This PR is to correct a typo in #3277 that @Carlosbogo revieled in a comment.
Related closed issue : #3257
Sorry about that 😅. | {
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https://api.github.com/repos/huggingface/datasets/issues/3301 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3301/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3301/comments | https://api.github.com/repos/huggingface/datasets/issues/3301/events | https://github.com/huggingface/datasets/pull/3301 | 1,058,718,957 | PR_kwDODunzps4uyA9o | 3,301 | Add wikipedia tags | {
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} | Add the missing tags to the wikipedia dataset card.
I also added the missing languages code in our language codes list.
This should also fix the code snippet that is presented on the Hub to load the dataset: fix https://github.com/huggingface/datasets/issues/3292 | {
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