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Add OpenAI's HumanEval dataset
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"I just fixed the class name, and added `[More Information Needed]` in empty sections in case people want to complete the dataset card :)"
] | 2021-09-11T09:37:47
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This PR adds OpenAI's [HumanEval](https://github.com/openai/human-eval) dataset. The dataset consists of 164 handcrafted programming problems with solutions and unittests to verify solution. This dataset is useful to evaluate code generation models.
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add multi-proc in `to_csv`
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[
"I think you can just add a test `test_dataset_to_csv_multiproc` in `tests/io/test_csv.py` and we'll be good",
"Hi @lhoestq, \r\nI've added `test_dataset_to_csv` apart from `test_dataset_to_csv_multiproc` as no test was there to check generated CSV file when `num_proc=1`. Please let me know if anything is also required! "
] | 2021-09-10T21:35:09
| 2021-10-28T05:47:33
| 2021-10-26T16:00:42
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CONTRIBUTOR
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This PR extends the multi-proc method used in #2747 for`to_json` to `to_csv` as well.
Results on my machine post benchmarking on `ascent_kb` dataset (giving ~45% improvement when compared to num_proc = 1):
```
Time taken on 1 num_proc, 10000 batch_size 674.2055702209473
Time taken on 4 num_proc, 10000 batch_size 425.6553490161896
Time taken on 1 num_proc, 50000 batch_size 623.5897650718689
Time taken on 4 num_proc, 50000 batch_size 380.0402421951294
Time taken on 4 num_proc, 100000 batch_size 361.7168130874634
```
This is a WIP as writing tests is pending for this PR.
I'm also exploring [this](https://arrow.apache.org/docs/python/csv.html#incremental-writing) approach for which I'm using `pyarrow-5.0.0`.
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Use pyarrow.Table.replace_schema_metadata instead of pyarrow.Table.cast
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| 2021-09-21T22:50:01
| 2021-09-21T08:18:35
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CONTRIBUTOR
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This PR partially addresses #2252.
``update_metadata_with_features`` uses ``Table.cast`` which slows down ``load_from_disk`` (and possibly other methods that use it) for very large datasets. Since ``update_metadata_with_features`` is only updating the schema metadata, it makes more sense to use ``pyarrow.Table.replace_schema_metadata`` which is much faster. This PR adds a ``replace_schema_metadata`` method to all table classes, and modifies ``update_metadata_with_features`` to use it instead of ``cast``.
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Fix COUNTER dataset
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| 2021-09-10T16:27:45
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MEMBER
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Fix filename generating `FileNotFoundError`.
Related to #2866.
CC: @severo.
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add mbpp dataset
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"I think it's fine to have the original schema"
] | 2021-09-10T15:27:30
| 2021-09-16T09:35:42
| 2021-09-16T09:35:42
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This PR adds the mbpp dataset introduced by Google [here](https://github.com/google-research/google-research/tree/master/mbpp) as mentioned in #2816.
The dataset contain two versions: a full and a sanitized one. They have a slightly different schema and it is current state the loading preserves the original schema. An open question is whether to harmonize the two schemas when loading the dataset or to preserve the original one. Since not all fields are overlapping the schema will not be exactly the same.
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| 2,892
|
Error when encoding a dataset with None objects with a Sequence feature
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"This has been fixed by https://github.com/huggingface/datasets/pull/2900\r\nWe're doing a new release 1.12 today to make the fix available :)"
] | 2021-09-10T14:11:43
| 2021-09-13T14:18:13
| 2021-09-13T14:17:42
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There is an error when encoding a dataset with None objects with a Sequence feature
To reproduce:
```python
from datasets import Dataset, Features, Value, Sequence
data = {"a": [[0], None]}
features = Features({"a": Sequence(Value("int32"))})
dataset = Dataset.from_dict(data, features=features)
```
raises
```python
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-24-40add67f8751> in <module>
2 data = {"a": [[0], None]}
3 features = Features({"a": Sequence(Value("int32"))})
----> 4 dataset = Dataset.from_dict(data, features=features)
[...]
~/datasets/features.py in encode_nested_example(schema, obj)
888 if isinstance(obj, str): # don't interpret a string as a list
889 raise ValueError("Got a string but expected a list instead: '{}'".format(obj))
--> 890 return [encode_nested_example(schema.feature, o) for o in obj]
891 # Object with special encoding:
892 # ClassLabel will convert from string to int, TranslationVariableLanguages does some checks
TypeError: 'NoneType' object is not iterable
```
Instead, if should run without error, as if the `features` were not passed
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Allow dynamic first dimension for ArrayXD
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[
"@lhoestq, thanks for your review.\r\n\r\nI added test for `to_pylist`, I didn't do that for `to_numpy` because this method shouldn't be called for dynamic dimension ArrayXD - this method will try to make a single numpy array for the whole column which cannot be done for dynamic arrays.\r\n\r\nI dig into `to_pandas()` functionality and I found it quite difficult to implement. `PandasArrayExtensionArray` takes single np.array as an argument. It might be a bit of changes to make it work with the list of arrays. Do you mind if we exclude this work from this PR. I added an error message for the case if somebody tries to use dynamic arrays with `to_pandas`",
"@lhoestq, I just fixed all the tests. Let me know if there is anything else to add.",
"@lhoestq, any chance you had some time to check out this PR?\r\n",
"Hi ! Sorry for the delay\r\n\r\nIt looks good to me ! I think the only thing missing is the support for passing a list of numpy arrays to `map` when the first dimension is dynamic.\r\n\r\nCurrently it raises an error:\r\n```python\r\nfrom datasets import *\r\nimport numpy as np\r\n\r\nfeatures= Features({\"a\": Array3D(shape=(None, 5, 2), dtype=\"int32\")})\r\nd = Dataset.from_dict({\"a\": [np.zeros((5,5,2)), np.zeros((2,5,2))]}, features=features)\r\nd = d.map(lambda a: {\"a\": np.concatenate([a]*2)}, input_columns=\"a\")\r\nprint(d[0])\r\n```\r\nraises\r\n```python\r\nTraceback (most recent call last):\r\n File \"playground/ttest.py\", line 6, in <module>\r\n d = d.map(lambda x: {\"a\": np.concatenate([x]*2)}, input_columns=\"a\")\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_dataset.py\", line 1932, in map\r\n return self._map_single(\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_dataset.py\", line 426, in wrapper\r\n out: Union[\"Dataset\", \"DatasetDict\"] = func(self, *args, **kwargs)\r\n File \"/home/truent/hf/datasets/src/datasets/fingerprint.py\", line 406, in wrapper\r\n out = func(self, *args, **kwargs)\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_dataset.py\", line 2317, in _map_single\r\n writer.finalize()\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_writer.py\", line 443, in finalize\r\n self.write_examples_on_file()\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_writer.py\", line 312, in write_examples_on_file\r\n pa_array = pa.array(typed_sequence)\r\n File \"pyarrow/array.pxi\", line 222, in pyarrow.lib.array\r\n File \"pyarrow/array.pxi\", line 110, in pyarrow.lib._handle_arrow_array_protocol\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_writer.py\", line 108, in __arrow_array__\r\n storage = pa.array(self.data, type.storage_dtype)\r\n File \"pyarrow/array.pxi\", line 305, 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 122, in pyarrow.lib.pyarrow_internal_check_status\r\n File \"pyarrow/error.pxi\", line 84, in pyarrow.lib.check_status\r\npyarrow.lib.ArrowInvalid: Can only convert 1-dimensional array values\r\n```\r\n\r\nI think the issue is that here we don't cover the case where self.data is a list of numpy arrays:\r\n\r\nhttps://github.com/huggingface/datasets/blob/55fd140a63b8f03a0e72985647e498f1fc799d3f/src/datasets/arrow_writer.py#L104-L109\r\n\r\nWe should remove the `isinstance(self.data[0], np.ndarray)` part and add these lines to cover this case:\r\n\r\nhttps://github.com/huggingface/datasets/blob/55fd140a63b8f03a0e72985647e498f1fc799d3f/src/datasets/arrow_writer.py#L112-L113",
"@lhoestq, thanks, good catch!\r\nAre you able to run this check with fixed dimension ArrayXD?\r\nfor below example\r\n```\r\nimport numpy as np\r\nfrom datasets import *\r\n\r\nfeatures = Features({\"a\": Array3D(shape=(2, 5, 2), dtype=\"int32\")})\r\nd = Dataset.from_dict({\"a\": [np.zeros((2, 5, 2)), np.zeros((2, 5, 2))]}, features=features)\r\nd = d.map(lambda a: {\"a\": np.array(a) + 1}, input_columns=\"a\")\r\nprint(d[0])\r\n```\r\n\r\nI am getting:\r\n```\r\n File \"/home/ib/datasets/src/datasets/arrow_writer.py\", line 116, in __arrow_array__\r\n if trying_type and out[0].as_py() != self.data[0]:\r\nValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()\r\n```",
"Nevertheless, I tried to fix that. Let me know if that works.",
"@lhoestq, just resolved the conflicts. Let me know if there is anything left to do with this PR",
"Hi, thanks a lot for your comments.\r\nAgree, happy to contribute to this topic in future PRs",
"Hi @rpowalski, thanks for adding this feature! \r\n\r\nI wanted to check if you are still interested in documenting this, otherwise I'd be happy to help with it :)"
] | 2021-09-10T11:52:52
| 2021-11-23T15:33:13
| 2021-10-29T09:37:17
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Add support for dynamic first dimension for ArrayXD features. See issue [#887](https://github.com/huggingface/datasets/issues/887).
Following changes allow for `to_pylist` method of `ArrayExtensionArray` to return a list of numpy arrays where fist dimension can vary.
@lhoestq Could you suggest how you want to extend test suit. For now I added only very limited testing.
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## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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NONE
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## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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| 2,888
|
v1.11.1 release date
|
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"Hi ! Probably 1.12 on monday :)\r\n",
"@albertvillanova i think this issue is still valid and should not be closed till `>1.11.0` is published :)"
] | 2021-09-09T21:53:15
| 2021-09-12T20:18:35
| 2021-09-12T16:15:39
|
NONE
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Hello, i need to use latest features in one of my packages but there have been no new datasets release since 2 months ago.
When do you plan to publush v1.11.1 release?
|
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#2837 Use cache folder for lockfile
|
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"The CI fail about the meteor metric is unrelated to this PR "
] | 2021-09-09T19:55:56
| 2021-10-05T17:58:22
| 2021-10-05T17:58:22
|
CONTRIBUTOR
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Fixes #2837
Use a cache folder directory to store the FileLock.
The issue was that the lock file was in a readonly folder.
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Hj
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Adding an Elastic Search index to a Dataset
|
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"Hi, is this bug deterministic in your poetry env ? I mean, does it always stop at 90% or is it random ?\r\n\r\nAlso, can you try using another version of Elasticsearch ? Maybe there's an issue with the one of you poetry env",
"I face similar issue with oscar dataset on remote ealsticsearch instance. It was mainly due to timeout of batch indexing requests and I solve these by adding large request_timeout param in `search.py`\r\n\r\n```\r\n for ok, action in es.helpers.streaming_bulk(\r\n client=self.es_client,\r\n index=index_name,\r\n actions=passage_generator(),\r\n request_timeout=3600,\r\n )\r\n ```",
"Hi @MotzWanted - are there any errors in the Elasticsearch cluster logs? Since it works in your local environment and the cluster versions are different between your poetry env and your local env, it is possible that it is some difference in the cluster - either settings or the cluster being under a different load etc that has this effect, so it would be useful to see if any errors are thrown in the cluster's logs when you try to ingest. \r\nWhich elasticsearch client method is the function `add_elasticsearch_index` from your code using under the hood? Is it `helpers.bulk` or is the indexing performed using something else? You can try adding a timeout to the indexing method to see if this helps. Also, you mention that it stops at around 90% - do you know if the timeout/hanging happens always when a particular document is being indexed or does it happen randomly at around 90% completeness but on different documents?"
] | 2021-09-09T12:21:39
| 2021-10-20T18:57:11
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## Describe the bug
When trying to index documents from the squad dataset, the connection to ElasticSearch seems to break:
Reusing dataset squad (/Users/andreasmotz/.cache/huggingface/datasets/squad/plain_text/1.0.0/d6ec3ceb99ca480ce37cdd35555d6cb2511d223b9150cce08a837ef62ffea453)
90%|████████████████████████████████████████████▉ | 9501/10570 [00:01<00:00, 6335.61docs/s]
No error is thrown, but the indexing breaks ~90%.
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
from datasets import load_dataset
from elasticsearch import Elasticsearch
es = Elasticsearch()
squad = load_dataset('squad', split='validation')
index_name = "corpus"
es_config = {
"settings": {
"number_of_shards": 1,
"analysis": {"analyzer": {"stop_standard": {"type": "standard", " stopwords": "_english_"}}},
},
"mappings": {
"properties": {
"idx" : {"type" : "keyword"},
"title" : {"type" : "keyword"},
"text": {
"type": "text",
"analyzer": "standard",
"similarity": "BM25"
},
}
},
}
class IndexBuilder:
"""
Elastic search indexing of a corpus
"""
def __init__(
self,
*args,
#corpus : None,
dataset : squad,
index_name = str,
query = str,
config = dict,
**kwargs,
):
#instantiate HuggingFace dataset
self.dataset = dataset
#instantiate ElasticSearch config
self.config = config
self.es = Elasticsearch()
self.index_name = index_name
self.query = query
def elastic_index(self):
print(self.es.info)
self.es.indices.delete(index=self.index_name, ignore=[400, 404])
search_index = self.dataset.add_elasticsearch_index(column='context', host='localhost', port='9200', es_index_name=self.index_name, es_index_config=self.config)
return search_index
def exact_match_method(self, index):
scores, retrieved_examples = index.get_nearest_examples('context', query=self.query, k=1)
return scores, retrieved_examples
if __name__ == "__main__":
print(type(squad))
Index = IndexBuilder(dataset=squad, index_name='corpus_index', query='Where was Chopin born?', config=es_config)
search_index = Index.elastic_index()
scores, examples = Index.exact_match_method(search_index)
print(scores, examples)
for name in squad.column_names:
print(type(squad[name]))
```
## Environment info
We run the code in Poetry. This might be the issue, since the script runs successfully in our local environment.
Poetry:
- Python version: 3.8
- PyArrow: 4.0.1
- Elasticsearch: 7.13.4
- datasets: 1.10.2
Local:
- Python version: 3.8
- PyArrow: 3.0.0
- Elasticsearch: 7.7.1
- datasets: 1.7.0
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|
Add IC, SI, ER tasks to SUPERB
|
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[
"Sorry for the late PR, uploading 10+GB files to the hub through a VPN was an adventure :sweat_smile: ",
"Thank you so much for adding these subsets @anton-l! \r\n\r\n> These datasets either require manual downloads or have broken/unstable links. You can get all necessary archives in this repo: https://huggingface.co/datasets/anton-l/superb_source_data_dumps/tree/main\r\nAre we allowed to make these datasets public or would that violate the terms of their use?",
"@lewtun These ones all have non-permissive licences, so the mirrored data I linked is open only to the HF org for now. But we could try contacting the authors to ask if they'd like to host these with us. \nFor example VoxCeleb1 now has direct links (the ones in the script) that don't require form submission and passwords, but they ban IPs after each download for some reason :(",
"> @lewtun These ones all have non-permissive licences, so the mirrored data I linked is open only to the HF org for now. But we could try contacting the authors to ask if they'd like to host these with us.\r\n> For example VoxCeleb1 now has direct links (the ones in the script) that don't require form submission and passwords, but they ban IPs after each download for some reason :(\r\n\r\nI think there would be a lot of value added if the authors would be willing to host their data on the HF Hub! As an end-user of `datasets`, I've found I'm more likely to explore a dataset if I'm able to quickly pull the subsets without needing a manual download. Perhaps we can tell them that the Hub offers several advantages like versioning and interactive exploration (with `datasets-viewer`)?"
] | 2021-09-09T11:56:03
| 2021-09-20T09:17:58
| 2021-09-20T09:00:49
|
MEMBER
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This PR adds 3 additional classification tasks to SUPERB
#### Intent Classification
Dataset URL seems to be down at the moment :( See the note below.
S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/fluent_commands/dataset.py
Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#ic-intent-classification---fluent-speech-commands
#### Speaker Identification
Manual download script:
```
mkdir VoxCeleb1
cd VoxCeleb1
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partaa
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partab
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partac
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partad
cat vox1_dev* > vox1_dev_wav.zip
unzip vox1_dev_wav.zip
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_test_wav.zip
unzip vox1_test_wav.zip
# download the official SUPERB train-dev-test split
wget https://raw.githubusercontent.com/s3prl/s3prl/master/s3prl/downstream/voxceleb1/veri_test_class.txt
```
S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/voxceleb1/dataset.py
Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#sid-speaker-identification
#### Intent Classification
Manual download requires going through a slow application process, see the note below.
S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/emotion/IEMOCAP_preprocess.py
Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#er-emotion-recognition
#### :warning: Note
These datasets either require manual downloads or have broken/unstable links. You can get all necessary archives in this repo: https://huggingface.co/datasets/anton-l/superb_source_data_dumps/tree/main
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MDExOlB1bGxSZXF1ZXN0NzMwMzYzNTQz
| 2,883
|
Fix data URLs and metadata in DocRED dataset
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[] | 2021-09-09T08:55:34
| 2021-09-13T11:24:31
| 2021-09-13T11:24:31
|
MEMBER
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The host of `docred` dataset has updated the `dev` data file. This PR:
- Updates the dev URL
- Updates dataset metadata
This PR also fixes the URL of the `train_distant` split, which was wrong.
Fix #2882.
|
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MDU6SXNzdWU5OTE4MDAxNDE=
| 2,882
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`load_dataset('docred')` results in a `NonMatchingChecksumError`
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[
"Hi @tmpr, thanks for reporting.\r\n\r\nTwo weeks ago (23th Aug), the host of the source `docred` dataset updated one of the files (`dev.json`): you can see it [here](https://drive.google.com/drive/folders/1c5-0YwnoJx8NS6CV2f-NoTHR__BdkNqw).\r\n\r\nTherefore, the checksum needs to be updated.\r\n\r\nNormally, in the meantime, you could avoid the error by passing `ignore_verifications=True` to `load_dataset`. However, as the old link points to a non-existing file, the link must be updated too.\r\n\r\nI'm fixing all this.\r\n\r\n"
] | 2021-09-09T05:55:02
| 2021-09-13T11:24:30
| 2021-09-13T11:24:30
|
NONE
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## Describe the bug
I get consistent `NonMatchingChecksumError: Checksums didn't match for dataset source files` errors when trying to execute `datasets.load_dataset('docred')`.
## Steps to reproduce the bug
It is quasi only this code:
```python
import datasets
data = datasets.load_dataset('docred')
```
## Expected results
The DocRED dataset should be loaded without any problems.
## Actual results
```
NonMatchingChecksumError Traceback (most recent call last)
<ipython-input-4-b1b83f25a16c> in <module>
----> 1 d = datasets.load_dataset('docred')
~/anaconda3/lib/python3.8/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, script_version, use_auth_token, task, streaming, **config_kwargs)
845
846 # Download and prepare data
--> 847 builder_instance.download_and_prepare(
848 download_config=download_config,
849 download_mode=download_mode,
~/anaconda3/lib/python3.8/site-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
613 logger.warning("HF google storage unreachable. Downloading and preparing it from source")
614 if not downloaded_from_gcs:
--> 615 self._download_and_prepare(
616 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
617 )
~/anaconda3/lib/python3.8/site-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
673 # Checksums verification
674 if verify_infos:
--> 675 verify_checksums(
676 self.info.download_checksums, dl_manager.get_recorded_sizes_checksums(), "dataset source files"
677 )
~/anaconda3/lib/python3.8/site-packages/datasets/utils/info_utils.py in verify_checksums(expected_checksums, recorded_checksums, verification_name)
38 if len(bad_urls) > 0:
39 error_msg = "Checksums didn't match" + for_verification_name + ":\n"
---> 40 raise NonMatchingChecksumError(error_msg + str(bad_urls))
41 logger.info("All the checksums matched successfully" + for_verification_name)
42
NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=1fDmfUUo5G7gfaoqWWvK81u08m71TK2g7']
```
## Environment info
- `datasets` version: 1.11.0
- Platform: Linux-5.11.0-7633-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyArrow version: 5.0.0
This error also happened on my Windows-partition, after freshly installing python 3.9 and `datasets`.
## Remarks
- I have already called `rm -rf /home/<user>/.cache/huggingface`, i.e., I have tried clearing the cache.
- The problem does not exist for other datasets, i.e., it seems to be DocRED-specific.
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MDExOlB1bGxSZXF1ZXN0NzMwMDc1OTAy
| 2,881
|
Add BIOSSES dataset
|
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[] | 2021-09-09T00:35:36
| 2021-09-13T14:20:40
| 2021-09-13T14:20:40
|
CONTRIBUTOR
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Adding the biomedical semantic sentence similarity dataset, BIOSSES, listed in "Biomedical Datasets - BigScience Workshop 2021"
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| 2,880
|
Extend support for streaming datasets that use pathlib.Path stem/suffix
|
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[] | 2021-09-08T08:42:43
| 2021-09-09T13:13:29
| 2021-09-09T13:13:29
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This PR extends the support in streaming mode for datasets that use `pathlib`, by patching the properties `pathlib.Path.stem` and `pathlib.Path.suffix`.
Related to #2876, #2874, #2866.
CC: @severo
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MDU6SXNzdWU5OTAyNTc0MDQ=
| 2,879
|
In v1.4.1, all TIMIT train transcripts are "Would such an act of refusal be useful?"
|
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[
"Hi @rcgale, thanks for reporting.\r\n\r\nPlease note that this bug was fixed on `datasets` version 1.5.0: https://github.com/huggingface/datasets/commit/a23c73e526e1c30263834164f16f1fdf76722c8c#diff-f12a7a42d4673bb6c2ca5a40c92c29eb4fe3475908c84fd4ce4fad5dc2514878\r\n\r\nIf you update `datasets` version, that should work.\r\n\r\nOn the other hand, would it be possible for @patrickvonplaten to update the [blog post](https://huggingface.co/blog/fine-tune-wav2vec2-english) with the correct version of `datasets`?",
"I just proposed a change in the blog post.\r\n\r\nI had assumed there was a data format change that broke a previous version of the code, since presumably @patrickvonplaten tested the tutorial with the version they explicitly referenced. But that fix you linked suggests a problem in the code, which surprised me.\r\n\r\nI still wonder, though, is there a way for downloads to be invalidated server-side? If the client can announce its version during a download request, perhaps the server could reject known incompatibilities? It would save much valuable time if `datasets` raised an informative error on a known problem (\"Error: the requested data set requires `datasets>=1.5.0`.\"). This kind of API versioning is a prudent move anyhow, as there will surely come a time when you'll need to make a breaking change to data.",
"Also, thank you for a quick and helpful reply!"
] | 2021-09-07T18:53:45
| 2021-09-08T16:55:19
| 2021-09-08T09:12:28
|
NONE
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## Describe the bug
Using version 1.4.1 of `datasets`, TIMIT transcripts are all the same.
## Steps to reproduce the bug
I was following this tutorial
- https://huggingface.co/blog/fine-tune-wav2vec2-english
But here's a distilled repro:
```python
!pip install datasets==1.4.1
from datasets import load_dataset
timit = load_dataset("timit_asr", cache_dir="./temp")
unique_transcripts = set(timit["train"]["text"])
print(unique_transcripts)
assert len(unique_transcripts) > 1
```
## Expected results
Expected the correct TIMIT data. Or an error saying that this version of `datasets` can't produce it.
## Actual results
Every train transcript was "Would such an act of refusal be useful?" Every test transcript was "The bungalow was pleasantly situated near the shore."
## Environment info
- `datasets` version: 1.4.1
- Platform: Darwin-18.7.0-x86_64-i386-64bit
- Python version: 3.7.9
- PyTorch version (GPU?): 1.9.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: tried both
- Using distributed or parallel set-up in script?: no
-
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MDU6SXNzdWU5OTAwOTMzMTY=
| 2,878
|
NotADirectoryError: [WinError 267] During load_from_disk
|
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[] | 2021-09-07T15:15:05
| 2021-09-07T15:15:05
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NONE
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## Describe the bug
Trying to load saved dataset or dataset directory from Amazon S3 on a Windows machine fails.
Performing the same operation succeeds on non-windows environment (AWS Sagemaker).
## Steps to reproduce the bug
```python
# Followed https://huggingface.co/docs/datasets/filesystems.html#loading-a-processed-dataset-from-s3
from datasets import load_from_disk
from datasets.filesystems import S3FileSystem
s3_file = "output of save_to_disk"
s3_filesystem = S3FileSystem()
load_from_disk(s3_file, fs=s3_filesystem)
```
## Expected results
load_from_disk succeeds without error
## Actual results
Seems like it succeeds in pulling the file into a windows temp directory, as it exists in my system, but fails to process it.
```
Exception ignored in: <finalize object at 0x26409231ce0; dead>
Traceback (most recent call last):
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\weakref.py", line 566, in __call__
return info.func(*info.args, **(info.kwargs or {}))
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 817, in _cleanup
cls._rmtree(name)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
[Previous line repeated 2 more times]
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 618, in _rmtree_unsafe
onerror(os.unlink, fullname, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 805, in onerror
cls._rmtree(path)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 599, in _rmtree_unsafe
onerror(os.scandir, path, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 596, in _rmtree_unsafe
with os.scandir(path) as scandir_it:
NotADirectoryError: [WinError 267] The directory name is invalid: 'C:\\Users\\grassycup\\AppData\\Local\\Temp\\tmp45f_qbma\\tests3bucket\\output\\test_output\\train\\dataset.arrow'
Exception ignored in: <finalize object at 0x264091c7880; dead>
Traceback (most recent call last):
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\weakref.py", line 566, in __call__
return info.func(*info.args, **(info.kwargs or {}))
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 817, in _cleanup
cls._rmtree(name)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
[Previous line repeated 2 more times]
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 618, in _rmtree_unsafe
onerror(os.unlink, fullname, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 805, in onerror
cls._rmtree(path)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 599, in _rmtree_unsafe
onerror(os.scandir, path, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 596, in _rmtree_unsafe
with os.scandir(path) as scandir_it:
NotADirectoryError: [WinError 267] The directory name is invalid:
'C:\\Users\\grassycup\\AppData\\Local\\Temp\\tmp45f_qbma\\tests3bucket\\output\\test_output\\train\\dataset.arrow'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Platform: Windows-10-10.0.19042-SP0
- Python version: 3.8.11
- PyArrow version: 3.0.0
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MDU6SXNzdWU5OTAwMjcyNDk=
| 2,877
|
Don't keep the dummy data folder or dataset_infos.json when resolving data files
|
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[
"Hi @lhoestq I am new to huggingface datasets, I would like to work on this issue!\r\n",
"Thanks for the help :) \r\n\r\nAs mentioned in the PR, excluding files named \"dummy_data.zip\" is actually more general than excluding the files inside a \"dummy\" folder. I just did the change in the PR, I think we can merge it now"
] | 2021-09-07T14:09:04
| 2021-09-29T09:05:38
| 2021-09-29T09:05:38
|
MEMBER
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When there's no dataset script, all the data files of a folder or a repository on the Hub are loaded as data files.
There are already a few exceptions:
- files starting with "." are ignored
- the dataset card "README.md" is ignored
- any file named "config.json" is ignored (currently it isn't used anywhere, but it could be used in the future to define splits or configs for example, but not 100% sure)
However any data files in a folder named "dummy" should be ignored as well as they should only be used to test the dataset.
Same for "dataset_infos.json" which should only be used to get the `dataset.info`
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Extend support for streaming datasets that use pathlib.Path.glob
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"I am thinking that ideally we should call `fs.glob()` instead...",
"Thanks, @lhoestq: the idea of adding the mock filesystem is to avoid network calls and reduce testing time ;) \r\n\r\nI have added `rglob` as well and fixed some bugs."
] | 2021-09-07T13:43:45
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| 2021-09-10T09:50:48
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This PR extends the support in streaming mode for datasets that use `pathlib`, by patching the method `pathlib.Path.glob`.
Related to #2874, #2866.
CC: @severo
|
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Add Congolese Swahili speech datasets
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CONTRIBUTOR
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## Adding a Dataset
- **Name:** Congolese Swahili speech corpora
- **Data:** https://gamayun.translatorswb.org/data/
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Also related: https://mobile.twitter.com/OktemAlp/status/1435196393631764482
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Support streaming datasets that use pathlib
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"I've tried https://github.com/huggingface/datasets/issues/2866 again, and I get the same error.\r\n\r\n```python\r\nimport datasets as ds\r\nds.load_dataset('counter', split=\"train\", streaming=False)\r\n```",
"@severo Issue #2866 is not fully fixed yet: multiple patches need to be implemented for `pathlib`, as that dataset uses quite a lot of `pathlib` functions... 😅 ",
"No worry and no stress, I just wanted to check for that case :) I'm very happy that you're working on issues I'm interested in!"
] | 2021-09-07T07:35:49
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| 2021-09-07T11:41:15
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This PR extends the support in streaming mode for datasets that use `pathlib.Path`.
Related to: #2866.
CC: @severo
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adding swedish_medical_ner
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"Hi, what's the current status of this request? It says Changes requested, but I can't see what changes?",
"Hi, it looks like this PR includes changes to other files that `swedish_medical_ner`.\r\n\r\nFeel free to remove these changes, or simply create a new PR that only contains the addition of the dataset"
] | 2021-09-07T04:44:53
| 2021-09-17T20:47:37
| 2021-09-17T20:47:37
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Adding the Swedish Medical NER dataset, listed in "Biomedical Datasets - BigScience Workshop 2021"
Code refactored
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Adding the Swedish Medical NER dataset, listed in "Biomedical Datasets - BigScience Workshop 2021"
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[
"I have changed line 288 to `if int(datasets.config.PYARROW_VERSION.split(\".\")[0]) < 3:` just to get around it.",
"Hi @bwang482,\r\n\r\nI'm sorry but I'm not able to reproduce your bug.\r\n\r\nPlease note that in our current master branch, we made a commit (d03223d4d64b89e76b48b00602aba5aa2f817f1e) that simultaneously modified:\r\n- test_dataset_common.py: https://github.com/huggingface/datasets/commit/d03223d4d64b89e76b48b00602aba5aa2f817f1e#diff-a1bc225bd9a5bade373d1f140e24d09cbbdc97971c2f73bb627daaa803ada002L289 that introduces the usage of `datasets.config.PYARROW_VERSION.major`\r\n- but also changed config.py: https://github.com/huggingface/datasets/commit/d03223d4d64b89e76b48b00602aba5aa2f817f1e#diff-e021fcfc41811fb970fab889b8d245e68382bca8208e63eaafc9a396a336f8f2L40, so that `datasets.config.PYARROW_VERSION.major` exists\r\n",
"Sorted. Thanks!",
"Reopening this. Although the `test_dataset_common.py` script works fine now.\r\n\r\nHas this got something to do with my pull request not passing `ci/circleci: run_dataset_script_tests_pyarrow` tests?\r\n\r\nhttps://github.com/huggingface/datasets/pull/2873",
"Hi @bwang482,\r\n\r\nIf you click on `Details` (on the right of your non passing CI test names: `ci/circleci: run_dataset_script_tests_pyarrow`), you can have more information about the non-passing tests.\r\n\r\nFor example, for [\"ci/circleci: run_dataset_script_tests_pyarrow_1\" details](https://circleci.com/gh/huggingface/datasets/46324?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link), you can see that the only non-passing test has to do with the dataset card (missing information in the `README.md` file): `test_changed_dataset_card`\r\n```\r\n=========================== short test summary info ============================\r\nFAILED tests/test_dataset_cards.py::test_changed_dataset_card[swedish_medical_ner]\r\n= 1 failed, 3214 passed, 2874 skipped, 2 xfailed, 1 xpassed, 15 warnings in 175.59s (0:02:55) =\r\n```\r\n\r\nTherefore, your PR non-passing test has nothing to do with this issue."
] | 2021-09-06T21:06:57
| 2021-09-08T08:51:52
| 2021-09-08T08:51:52
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CONTRIBUTOR
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In the test_dataset_common.py script, line 288-289
```
if datasets.config.PYARROW_VERSION.major < 3:
packaged_datasets = [pd for pd in packaged_datasets if pd["dataset_name"] != "parquet"]
```
which throws the error below. `datasets.config.PYARROW_VERSION` itself return the string '4.0.1'. I have tested this on both datasets.__version_=='1.11.0' and '1.9.0'. I am using Mac OS.
```
import datasets
datasets.config.PYARROW_VERSION.major
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/var/folders/1f/0wqmlgp90qjd5mpj53fnjq440000gn/T/ipykernel_73361/2547517336.py in <module>
1 import datasets
----> 2 datasets.config.PYARROW_VERSION.major
AttributeError: 'str' object has no attribute 'major'
```
## Environment info
- `datasets` version: 1.11.0
- Platform: Darwin-20.6.0-x86_64-i386-64bit
- Python version: 3.7.11
- PyArrow version: 4.0.1
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Changed "bacth_size" to "batch_size" (2x)
Changed "intsructions" to "instructions"
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"Hi, @Chenfei-Kang.\r\n\r\nI'm sorry, but I'm not able to reproduce your bug:\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nds = load_dataset(\"glue\", 'cola')\r\nds\r\n```\r\n```\r\nDatasetDict({\r\n train: Dataset({\r\n features: ['sentence', 'label', 'idx'],\r\n num_rows: 8551\r\n })\r\n validation: Dataset({\r\n features: ['sentence', 'label', 'idx'],\r\n num_rows: 1043\r\n })\r\n test: Dataset({\r\n features: ['sentence', 'label', 'idx'],\r\n num_rows: 1063\r\n })\r\n})\r\n```\r\n\r\nCould you please give more details and environment info (platform, PyArrow version)?",
"> Hi, @Chenfei-Kang.\r\n> \r\n> I'm sorry, but I'm not able to reproduce your bug:\r\n> \r\n> ```python\r\n> from datasets import load_dataset\r\n> \r\n> ds = load_dataset(\"glue\", 'cola')\r\n> ds\r\n> ```\r\n> \r\n> ```\r\n> DatasetDict({\r\n> train: Dataset({\r\n> features: ['sentence', 'label', 'idx'],\r\n> num_rows: 8551\r\n> })\r\n> validation: Dataset({\r\n> features: ['sentence', 'label', 'idx'],\r\n> num_rows: 1043\r\n> })\r\n> test: Dataset({\r\n> features: ['sentence', 'label', 'idx'],\r\n> num_rows: 1063\r\n> })\r\n> })\r\n> ```\r\n> \r\n> Could you please give more details and environment info (platform, PyArrow version)?\r\n\r\nSorry to reply you so late.\r\nplatform: pycharm 2021 + anaconda with python 3.7\r\nPyArrow version: 5.0.0\r\nhuggingface-hub: 0.0.16\r\ndatasets: 1.9.0\r\n",
"- For the platform, we need to know the operating system of your machine. Could you please run the command `datasets-cli env` and copy-and-paste its output below?\r\n- In relation with the error, you just gave us the error type and message (`TypeError: 'NoneType' object is not callable`). Could you please copy-paste the complete stack trace, so that we know exactly which part of the code threw the error?",
"> * For the platform, we need to know the operating system of your machine. Could you please run the command `datasets-cli env` and copy-and-paste its output below?\r\n> * In relation with the error, you just gave us the error type and message (`TypeError: 'NoneType' object is not callable`). Could you please copy-paste the complete stack trace, so that we know exactly which part of the code threw the error?\r\n\r\n1. For the platform, here are the output:\r\n - datasets` version: 1.11.0\r\n - Platform: Windows-10-10.0.19041-SP0\r\n - Python version: 3.7.10\r\n - PyArrow version: 5.0.0\r\n2. For the code and error：\r\n ```python\r\n from datasets import load_dataset, load_metric\r\n dataset = load_dataset(\"glue\", \"cola\")\r\n ```\r\n ```python\r\n Traceback (most recent call last):\r\n ....\r\n ....\r\n File \"my_file.py\", line 2, in <module>\r\n dataset = load_dataset(\"glue\", \"cola\")\r\n File \"My environments\\lib\\site-packages\\datasets\\load.py\", line 830, in load_dataset\r\n **config_kwargs,\r\n File \"My environments\\lib\\site-packages\\datasets\\load.py\", line 710, in load_dataset_builder\r\n **config_kwargs,\r\n TypeError: 'NoneType' object is not callable\r\n ```\r\n Thank you!",
"For that environment, I am sorry but I can't reproduce the bug: I can load the dataset without any problem.",
"One naive question: do you have internet access from the machine where you execute the code?",
"> For that environment, I am sorry but I can't reproduce the bug: I can load the dataset without any problem.\r\n\r\nBut I can download other task dataset such as `dataset = load_dataset('squad')`. I don't know what went wrong. Thank you so much!",
"Hi,friends. I meet the same problem. Do you have a way to fix this? Thanks!\r\n",
"I'm getting the same error. Have you solved the problem? Please tell me how to fix it",
"same error, fix by Downgrade the datasets version to 2.16.0.",
"Similar error when trying to download another dataset with 2.16.0, but 2.10.0 works",
"Same issue in v3.1.0; resolved by downgrading to v2.21.0.",
"same error, using the lower version 2.16.0 works",
"I met the same error, how did you save your problem?",
"> I met the same error, how did you save your problem?\r\n\r\ndown grade datasets version, try 2.16.0 or 2.10.0",
"success solve the problem by downgrade to 2.10.0",
"ERROR: Could not find a version that satisfies the requirement dataset==2.10.0 (from versions: 0.3, 0.3.3, 0.3.5, 0.3.6, 0.3.9, 0.3.10, 0.3.11, 0.3.12, 0.3.13, 0.3.14, 0.3.15, 0.4.0, 0.5.0, 0.5.1, 0.5.2, 0.5.4, 0.5.5, 0.5.6, 0.6.0, 0.6.1, 0.6.2, 0.6.3, 0.6.4, 0.7.0, 0.7.1, 0.8.0, 1.0.0, 1.0.1, 1.0.2, 1.0.3, 1.0.4, 1.0.5, 1.0.6, 1.0.7, 1.0.8, 1.1.0, 1.1.1, 1.1.2, 1.2.0, 1.2.1, 1.2.2, 1.2.3, 1.3.0, 1.3.1, 1.3.2, 1.4.1, 1.4.2, 1.4.3, 1.4.4, 1.4.5, 1.5.0, 1.5.1, 1.5.2, 1.6.0, 1.6.2)\nERROR: No matching distribution found for dataset==2.10.0\n"
] | 2021-09-03T11:27:39
| 2025-02-19T09:57:34
| 2021-09-08T09:24:55
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NONE
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## Describe the bug
TypeError: 'NoneType' object is not callable
## Steps to reproduce the bug
```python
from datasets import load_dataset, load_metric
dataset = datasets.load_dataset("glue", 'cola')
```
## Expected results
A clear and concise description of the expected results.
## Actual results
Specify the actual results or traceback.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Platform:
- Python version: 3.7
- PyArrow version:
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Add Common Objects in 3D (CO3D)
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## Adding a Dataset
- **Name:** *Common Objects in 3D (CO3D)*
- **Description:** *See blog post [here](https://ai.facebook.com/blog/common-objects-in-3d-dataset-for-3d-reconstruction)*
- **Paper:** *[link to paper](https://arxiv.org/abs/2109.00512)*
- **Data:** *[link to data](https://ai.facebook.com/datasets/co3d-downloads/)*
- **Motivation:** *excerpt from above blog post:*
> As the first data set of its kind, CO3D will aptly enable reconstruction of real-life 3D objects. Indeed, CO3D already provides training data to enable our NeRFormer to tackle the new-view synthesis (NVS) task. Here, photorealistic NVS is a major step on the path to fully immersive AR/VR effects, where objects can be virtually transported across different environments, which will allow connecting users by sharing or recollecting their experiences.
>
> Besides practical applications in AR/VR, we hope that the data set will become a standard testbed for the recent proliferation of methods (including NeRFormer, Implicit Differentiable Renderer, NeRF, and others) that reconstruct 3D scenes by means of an implicit shape model.
>
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| null |
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MDExOlB1bGxSZXF1ZXN0NzI2MTE3NzAw
| 2,867
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Add CaSiNo dataset
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[
"Hi @lhoestq \r\n\r\nJust a request to look at the dataset. Please let me know if any changes are necessary before merging it into the repo. Thank you.",
"Hey @lhoestq \r\n\r\nThanks for merging it. One question: I still cannot find the dataset on https://huggingface.co/datasets. Does it take some time or did I miss something?",
"Hi ! It takes a few hours or a day for the list of datasets on the website to be updated ;)"
] | 2021-09-02T17:06:23
| 2021-09-16T15:12:54
| 2021-09-16T09:23:44
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CONTRIBUTOR
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Hi. I request you to add our dataset to the repository.
This data was recently published at NAACL 2021: https://aclanthology.org/2021.naacl-main.254.pdf
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"counter" dataset raises an error in normal mode, but not in streaming mode
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[
"Hi @severo, thanks for reporting.\r\n\r\nJust note that currently not all canonical datasets support streaming mode: this is one case!\r\n\r\nAll datasets that use `pathlib` joins (using `/`) instead of `os.path.join` (as in this dataset) do not support streaming mode yet.",
"OK. Do you think it's possible to detect this, and raise an exception (maybe `NotImplementedError`, or a specific `StreamingError`)?",
"We should definitely support datasets using `pathlib` in streaming mode...\r\n\r\nFor non-supported datasets in streaming mode, we have already a request of raising an error/warning: see #2654.",
"Hi @severo, please note that \"counter\" dataset will be streamable (at least until it arrives at the missing file, error already in normal mode) once these PRs are merged:\r\n- #2874\r\n- #2876\r\n- #2880\r\n\r\nI have tested it. 😉 ",
"Now (on master), we get:\r\n\r\n```\r\nimport datasets as ds\r\nds.load_dataset('counter', split=\"train\", streaming=False)\r\n```\r\n\r\n```\r\nUsing custom data configuration default\r\nDownloading and preparing dataset counter/default (download: 1.29 MiB, generated: 2.48 MiB, post-processed: Unknown size, total: 3.77 MiB) to /home/slesage/.cache/huggingface/datasets/counter/default/1.0.0/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9...\r\nTraceback (most recent call last):\r\n File \"/home/slesage/hf/datasets/src/datasets/builder.py\", line 726, in _download_and_prepare\r\n self._prepare_split(split_generator, **prepare_split_kwargs)\r\n File \"/home/slesage/hf/datasets/src/datasets/builder.py\", line 1124, in _prepare_split\r\n for key, record in utils.tqdm(\r\n File \"/home/slesage/hf/datasets/.venv/lib/python3.8/site-packages/tqdm/std.py\", line 1185, in __iter__\r\n for obj in iterable:\r\n File \"/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/counter/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9/counter.py\", line 161, in _generate_examples\r\n with derived_file.open(encoding=\"utf-8\") as f:\r\n File \"/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py\", line 1222, in open\r\n return io.open(self, mode, buffering, encoding, errors, newline,\r\n File \"/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py\", line 1078, in _opener\r\n return self._accessor.open(self, flags, mode)\r\nFileNotFoundError: [Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml'\r\n\r\nDuring handling of the above exception, another exception occurred:\r\n\r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n File \"/home/slesage/hf/datasets/src/datasets/load.py\", line 1112, in load_dataset\r\n builder_instance.download_and_prepare(\r\n File \"/home/slesage/hf/datasets/src/datasets/builder.py\", line 636, in download_and_prepare\r\n self._download_and_prepare(\r\n File \"/home/slesage/hf/datasets/src/datasets/builder.py\", line 728, in _download_and_prepare\r\n raise OSError(\r\nOSError: Cannot find data file.\r\nOriginal error:\r\n[Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml'\r\n```\r\n\r\nThe error is now the same with or without streaming. I close the issue, thanks @albertvillanova and @lhoestq!\r\n",
"Note that we might want to open an issue to fix the \"counter\" dataset by itself, but I let it up to you.",
"Fixed here: https://github.com/huggingface/datasets/pull/2894. Thanks @albertvillanova ",
"On master, I get:\r\n\r\n```python\r\n>>> import datasets as ds\r\n>>> iterable_dataset = ds.load_dataset('counter', split=\"train\", streaming=True)\r\n>>> rows = list(iterable_dataset.take(100))\r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n File \"/home/slesage/hf/datasets/src/datasets/iterable_dataset.py\", line 341, in __iter__\r\n for key, example in self._iter():\r\n File \"/home/slesage/hf/datasets/src/datasets/iterable_dataset.py\", line 338, in _iter\r\n yield from ex_iterable\r\n File \"/home/slesage/hf/datasets/src/datasets/iterable_dataset.py\", line 273, in __iter__\r\n yield from islice(self.ex_iterable, self.n)\r\n File \"/home/slesage/hf/datasets/src/datasets/iterable_dataset.py\", line 78, in __iter__\r\n for key, example in self.generate_examples_fn(**self.kwargs):\r\n File \"/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/counter/b9e4378dbd3f5ce235d2302e48168c00196e67bbcd13cc7e1f6e69ef82c0cf2a/counter.py\", line 153, in _generate_examples\r\n files = sorted(base_path.glob(r\"[0-9][0-9][0-9][0-9].xml\"))\r\nTypeError: xpathglob() missing 1 required positional argument: 'pattern'\r\n```",
"Associated to the above exception, if I create a test and run it with pytest, I get an awful traceback.\r\n\r\n- create a file `test_counter.py`\r\n\r\n```python\r\nimport pytest\r\nfrom datasets import load_dataset, IterableDataset\r\nfrom typing import Any, cast\r\n\r\n\r\ndef test_counter() -> Any:\r\n iterable_dataset = cast(IterableDataset, load_dataset(\"counter\", split=\"train\", streaming=True))\r\n with pytest.raises(TypeError):\r\n list(iterable_dataset.take(100))\r\n```\r\n\r\n- run the test with pytest\r\n\r\n```bash\r\n$ python -m pytest -x test_counter.py\r\n============================================================================================================================= test session starts ==============================================================================================================================\r\nplatform linux -- Python 3.9.6, pytest-6.2.5, py-1.10.0, pluggy-1.0.0\r\nrootdir: /home/slesage/hf/datasets-preview-backend, configfile: pyproject.toml\r\nplugins: anyio-3.3.2, cov-2.12.1\r\ncollected 1 item\r\n\r\ntests/test_counter.py . [100%]Traceback (most recent call last):\r\n File \"/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/runpy.py\", line 197, in _run_module_as_main\r\n return _run_code(code, main_globals, None,\r\n File \"/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/runpy.py\", line 87, in _run_code\r\n exec(code, run_globals)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pytest/__main__.py\", line 5, in <module>\r\n raise SystemExit(pytest.console_main())\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/config/__init__.py\", line 185, in console_main\r\n code = main()\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/config/__init__.py\", line 162, in main\r\n ret: Union[ExitCode, int] = config.hook.pytest_cmdline_main(\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_hooks.py\", line 265, in __call__\r\n return self._hookexec(self.name, self.get_hookimpls(), kwargs, firstresult)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_manager.py\", line 80, in _hookexec\r\n return self._inner_hookexec(hook_name, methods, kwargs, firstresult)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_callers.py\", line 60, in _multicall\r\n return outcome.get_result()\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_result.py\", line 60, in get_result\r\n raise ex[1].with_traceback(ex[2])\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_callers.py\", line 39, in _multicall\r\n res = hook_impl.function(*args)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/main.py\", line 316, in pytest_cmdline_main\r\n return wrap_session(config, _main)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/main.py\", line 304, in wrap_session\r\n config.hook.pytest_sessionfinish(\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_hooks.py\", line 265, in __call__\r\n return self._hookexec(self.name, self.get_hookimpls(), kwargs, firstresult)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_manager.py\", line 80, in _hookexec\r\n return self._inner_hookexec(hook_name, methods, kwargs, firstresult)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_callers.py\", line 55, in _multicall\r\n gen.send(outcome)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/terminal.py\", line 803, in pytest_sessionfinish\r\n outcome.get_result()\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_result.py\", line 60, in get_result\r\n raise ex[1].with_traceback(ex[2])\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_callers.py\", line 39, in _multicall\r\n res = hook_impl.function(*args)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/cacheprovider.py\", line 428, in pytest_sessionfinish\r\n config.cache.set(\"cache/nodeids\", sorted(self.cached_nodeids))\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/cacheprovider.py\", line 188, in set\r\n f = path.open(\"w\")\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/utils/streaming_download_manager.py\", line 199, in xpathopen\r\n return xopen(_as_posix(path), *args, **kwargs)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/utils/streaming_download_manager.py\", line 117, in _as_posix\r\n path_as_posix = path.as_posix()\r\nAttributeError: 'str' object has no attribute 'as_posix'\r\n```\r\n",
"I opened a PR to fix these issues.\r\nAlso in your test you expect a TypeError but I don't know why. On my side it works fine without raising a TypeError",
"I had the issue (TypeError raised) on my branch, but it's fixed now. Thanks"
] | 2021-09-02T13:10:53
| 2021-10-14T09:24:09
| 2021-10-14T09:24:09
|
COLLABORATOR
|
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## Describe the bug
`counter` dataset raises an error on `load_dataset()`, but simply returns an empty iterator in streaming mode.
## Steps to reproduce the bug
```python
>>> import datasets as ds
>>> a = ds.load_dataset('counter', split="train", streaming=False)
Using custom data configuration default
Downloading and preparing dataset counter/default (download: 1.29 MiB, generated: 2.48 MiB, post-processed: Unknown size, total: 3.77 MiB) to /home/slesage/.cache/huggingface/datasets/counter/default/1.0.0/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9...
Traceback (most recent call last):
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 726, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 1124, in _prepare_split
for key, record in utils.tqdm(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/tqdm/std.py", line 1185, in __iter__
for obj in iterable:
File "/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/counter/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9/counter.py", line 161, in _generate_examples
with derived_file.open(encoding="utf-8") as f:
File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py", line 1222, in open
return io.open(self, mode, buffering, encoding, errors, newline,
File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py", line 1078, in _opener
return self._accessor.open(self, flags, mode)
FileNotFoundError: [Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/load.py", line 1112, in load_dataset
builder_instance.download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 636, in download_and_prepare
self._download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 728, in _download_and_prepare
raise OSError(
OSError: Cannot find data file.
Original error:
[Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml'
```
```python
>>> import datasets as ds
>>> b = ds.load_dataset('counter', split="train", streaming=True)
Using custom data configuration default
>>> list(b)
[]
```
## Expected results
An exception should be raised in streaming mode
## Actual results
No exception is raised in streaming mode: there is no way to tell if something has broken or if the dataset is simply empty.
## Environment info
- `datasets` version: 1.11.1.dev0
- Platform: Linux-5.11.0-1016-aws-x86_64-with-glibc2.29
- Python version: 3.8.11
- PyArrow version: 4.0.1
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| 986,460,698
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MDExOlB1bGxSZXF1ZXN0NzI1NjY1ODgx
| 2,865
|
Add MultiEURLEX dataset
|
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[
"Hi @lhoestq, we have this new cool multilingual dataset coming at EMNLP 2021. It would be really nice if we could have it in Hugging Face asap. Thanks! ",
"Hi @lhoestq, I adopted most of your suggestions:\r\n\r\n- Dummy data files reduced, including the 2 smallest documents per subset JSONL.\r\n- README was updated with the publication URL and instructions on how to download and use label descriptors. Excessive newlines were deleted.\r\n\r\nI would prefer to keep the label list in a pure format (original ids), to enable people to combine those with more information or possibly in the future explore the dataset, find inconsistencies and fix those to release a new version. ",
"Thanks for the changes :)\r\n\r\nRegarding the labels:\r\n\r\nIf you use the ClassLabel feature type, the only change is that it will store the ids as integers instead of (currently) string.\r\nThe advantage is that if people want to know what id corresponds to which label name, they can use `classlabel.int2str`. It is also the format that helps automate model training for classification in `transformers`.\r\n\r\nLet me know if that sounds good to you or if you still want to stick with the labels as they are now.",
"Hey @lhoestq, thanks for providing this information. This sounds great. I updated my code accordingly to use `ClassLabel`. Could you please provide a minimal example of how `classlabel.int2str` works in practice in my case, where labels are a sequence?\r\n\r\n```python\r\nfrom datasets import load_dataset\r\ndataset = load_dataset('multi_eurlex', 'all_languages')\r\n# Read strs from the labels (list of integers) for the 1st sample of the training split\r\n```\r\n\r\nI would like to include this in the README file.\r\n\r\nCould you also provide some info on how I could define the supervized key to automate model training, as you said?\r\n\r\nThanks!",
"Thanks for the update :)\r\n\r\nHere is an example of usage:\r\n```python\r\nfrom datasets import load_dataset\r\ndataset = load_dataset('multi_eurlex', 'all_languages', split='train')\r\nclasslabel = dataset.features[\"labels\"].feature\r\nprint(dataset[0][\"labels\"])\r\n# [1, 20, 7, 3, 0]\r\nprint(classlabel.int2str(dataset[0][\"labels\"]))\r\n# ['100160', '100155', '100158', '100147', '100149']\r\n```\r\n\r\nThe ClassLabel is simply used to define the `id2label` dictionary of classification models, to make the ids match between the model and the dataset. There nothing more to do :p \r\n\r\nI think one last thing to do is just update the `dataset_infos.json` file and we'll be good !",
"Everything is ready! 👍 \r\n"
] | 2021-09-02T09:42:24
| 2021-09-10T11:50:06
| 2021-09-10T11:50:06
|
CONTRIBUTOR
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**Add new MultiEURLEX Dataset**
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource). Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU. As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels); this is multi-label classification task (given the text, predict multiple labels).
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