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https://api.github.com/repos/huggingface/datasets/issues/3361 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3361/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3361/comments | https://api.github.com/repos/huggingface/datasets/issues/3361/events | https://github.com/huggingface/datasets/issues/3361 | 1,068,736,268 | I_kwDODunzps4_s58M | 3,361 | Jeopardy _URL access denied | [
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] | closed | false | null | 1 | 2021-12-01T18:21:33Z | 2021-12-11T12:50:23Z | 2021-12-06T11:16:31Z | null | ## Describe the bug
http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz returns Access Denied now.
However, https://drive.google.com/file/d/0BwT5wj_P7BKXb2hfM3d2RHU1ckE/view?usp=sharing from the original Reddit post https://www.reddit.com/r/datasets/comments/1uyd0t/200000_jeopardy_questions_in_a_json_file/ may work.
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
```
```python
>>> from datasets import load_dataset
>>> load_dataset("jeopardy")
```
## Expected results
The download completes.
## Actual results
```shell
Downloading: 4.18kB [00:00, 1.60MB/s]
Downloading: 2.03kB [00:00, 1.04MB/s]
Using custom data configuration default
Downloading and preparing dataset jeopardy/default (download: 12.13 MiB, generated: 34.46 MiB, post-processed: Unknown size, total: 46.59 MiB) to /Users/mike/.cache/huggingface/datasets/jeopardy/default/0.1.0/25ee3e4a73755e637b8810f6493fd36e4523dea3ca8a540529d0a6e24c7f9810...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/load.py", line 1632, in load_dataset
use_auth_token=use_auth_token,
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/builder.py", line 608, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/Users/mike/.cache/huggingface/modules/datasets_modules/datasets/jeopardy/25ee3e4a73755e637b8810f6493fd36e4523dea3ca8a540529d0a6e24c7f9810/jeopardy.py", line 72, in _split_generators
filepath = dl_manager.download_and_extract(_DATA_URL)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 197, in download
download_func, url_or_urls, map_tuple=True, num_proc=download_config.num_proc, disable_tqdm=False
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 197, in map_nested
return function(data_struct)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 305, in cached_path
use_auth_token=download_config.use_auth_token,
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 594, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz
```
---
```shell
> curl http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz
```
```xml
<?xml version="1.0" encoding="UTF-8"?>
<Error><Code>AccessDenied</Code><Message>Access Denied</Message><RequestId>70Y9R36XNPEQXMGV</RequestId><HostId>G6F5AK4qo7JdaEdKGMtS0P6gdLPeFOdEfSEfvTOZEfk9km0/jAfp08QLfKSTFFj1oWIKoAoBehM=</HostId></Error>
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.14.0
- Platform: macOS Catalina 10.15.7
- Python version: 3.7.12
- PyArrow version: 6.0.1
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"Just a side note: duplicate #3264"
] |
https://api.github.com/repos/huggingface/datasets/issues/4701 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4701/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4701/comments | https://api.github.com/repos/huggingface/datasets/issues/4701/events | https://github.com/huggingface/datasets/pull/4701 | 1,307,689,625 | PR_kwDODunzps47jeE9 | 4,701 | Added more information in the README about contributors of the Arabic Speech Corpus | [] | closed | false | null | 0 | 2022-07-18T09:48:03Z | 2022-07-28T10:33:05Z | 2022-07-28T10:33:05Z | null | Added more information in the README about contributors and encouraged reading the thesis for more infos | {
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https://api.github.com/repos/huggingface/datasets/issues/634 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/634/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/634/comments | https://api.github.com/repos/huggingface/datasets/issues/634/events | https://github.com/huggingface/datasets/pull/634 | 702,676,041 | MDExOlB1bGxSZXF1ZXN0NDg3OTEzOTk4 | 634 | Add ConLL-2000 dataset | [] | closed | false | null | 0 | 2020-09-16T11:14:11Z | 2020-09-17T10:38:10Z | 2020-09-17T10:38:10Z | null | Adds ConLL-2000 dataset used for text chunking. See https://www.clips.uantwerpen.be/conll2000/chunking/ for details and [motivation](https://github.com/huggingface/transformers/pull/7041#issuecomment-692710948) behind this PR | {
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https://api.github.com/repos/huggingface/datasets/issues/82 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/82/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/82/comments | https://api.github.com/repos/huggingface/datasets/issues/82/events | https://github.com/huggingface/datasets/pull/82 | 616,805,194 | MDExOlB1bGxSZXF1ZXN0NDE2ODQ1Njc5 | 82 | [Datasets] add ted_hrlr | [] | closed | false | null | 0 | 2020-05-12T16:46:50Z | 2020-05-13T07:52:54Z | 2020-05-13T07:52:53Z | null | @thomwolf - After looking at `xnli` I think it's better to leave the translation features and add a `translation` key to make them work in our framework.
The result looks like this:
you can see that each split has a `translation` key which value is the nlp.features.Translation object.
That's a simple change. If it's ok for you, I will add dummy data for the other configs and treat the other translation scripts in the same way. | {
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https://api.github.com/repos/huggingface/datasets/issues/2983 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2983/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2983/comments | https://api.github.com/repos/huggingface/datasets/issues/2983/events | https://github.com/huggingface/datasets/pull/2983 | 1,010,263,058 | PR_kwDODunzps4saw_v | 2,983 | added SwissJudgmentPrediction dataset | [] | closed | false | null | 0 | 2021-09-28T22:17:56Z | 2021-10-01T16:03:05Z | 2021-10-01T16:03:05Z | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2241 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2241/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2241/comments | https://api.github.com/repos/huggingface/datasets/issues/2241/events | https://github.com/huggingface/datasets/pull/2241 | 862,696,460 | MDExOlB1bGxSZXF1ZXN0NjE5MjI0MzIw | 2,241 | Add SLR32 to OpenSLR | [] | closed | false | null | 1 | 2021-04-20T11:02:45Z | 2021-04-23T16:21:24Z | 2021-04-23T15:36:15Z | null | I would like to add SLR32 to OpenSLR. It contains four South African languages: Afrikaans, Sesotho, Setswana and isiXhosa | {
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"> And yet another one ! Thanks a lot :)\r\n\r\nI just hope you don’t get fed up with openslr PR 😊 there are still few other datasets created by google in openslr that is not in hf dataset yet\r\n"
] |
https://api.github.com/repos/huggingface/datasets/issues/878 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/878/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/878/comments | https://api.github.com/repos/huggingface/datasets/issues/878/events | https://github.com/huggingface/datasets/issues/878 | 748,621,981 | MDU6SXNzdWU3NDg2MjE5ODE= | 878 | Loading Data From S3 Path in Sagemaker | [
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"description": "New feature or request",
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"name": "enhancement",
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"default": true... | open | false | null | 16 | 2020-11-23T09:17:22Z | 2020-12-23T09:53:08Z | null | null | In Sagemaker Im tring to load the data set from S3 path as follows
`train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv'
valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv'
test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv'
data_files = {}
data_files["train"] = train_path
data_files["validation"] = valid_path
data_files["test"] = test_path
extension = train_path.split(".")[-1]
datasets = load_dataset(extension, data_files=data_files, s3_enabled=True)
print(datasets)`
I getting an error of
`algo-1-7plil_1 | File "main.py", line 21, in <module>
algo-1-7plil_1 | datasets = load_dataset(extension, data_files=data_files)
algo-1-7plil_1 | File "/opt/conda/lib/python3.6/site-packages/datasets/load.py", line 603, in load_dataset
algo-1-7plil_1 | **config_kwargs,
algo-1-7plil_1 | File "/opt/conda/lib/python3.6/site-packages/datasets/builder.py", line 155, in __init__
algo-1-7plil_1 | **config_kwargs,
algo-1-7plil_1 | File "/opt/conda/lib/python3.6/site-packages/datasets/builder.py", line 305, in _create_builder_config
algo-1-7plil_1 | m.update(str(os.path.getmtime(data_file)))
algo-1-7plil_1 | File "/opt/conda/lib/python3.6/genericpath.py", line 55, in getmtime
algo-1-7plil_1 | return os.stat(filename).st_mtime
algo-1-7plil_1 | FileNotFoundError: [Errno 2] No such file or directory: 's3://lsmv-sagemaker/pubmedbert/test.csv`
But when im trying with pandas , it is able to load from S3
Does the datasets library support S3 path to load | {
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"This would be a neat feature",
"> neat feature\r\n\r\nI dint get these clearly, can you please elaborate like how to work on these ",
"It could maybe work almost out of the box just by using `cached_path` in the text/csv/json scripts, no?",
"Thanks thomwolf and julien-c\r\n\r\nI'm still confusion on what you... |
https://api.github.com/repos/huggingface/datasets/issues/3046 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3046/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3046/comments | https://api.github.com/repos/huggingface/datasets/issues/3046/events | https://github.com/huggingface/datasets/pull/3046 | 1,021,021,368 | PR_kwDODunzps4s8MjS | 3,046 | Fix MedDialog metadata JSON | [] | closed | false | null | 0 | 2021-10-08T12:04:40Z | 2021-10-11T07:46:43Z | 2021-10-11T07:46:42Z | null | Fix #2969. | {
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https://api.github.com/repos/huggingface/datasets/issues/1222 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1222/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1222/comments | https://api.github.com/repos/huggingface/datasets/issues/1222/events | https://github.com/huggingface/datasets/pull/1222 | 758,018,953 | MDExOlB1bGxSZXF1ZXN0NTMzMjYzODIx | 1,222 | Add numeric fused head dataset | [] | closed | false | null | 2 | 2020-12-06T20:46:53Z | 2020-12-08T11:17:56Z | 2020-12-08T11:17:55Z | null | Adding the [NFH: Numeric Fused Head](https://nlp.biu.ac.il/~lazary/fh/) dataset.
Everything looks sensible and I've included both the identification and resolution tasks. I haven't personally used this dataset in my research so am unable to specify what the default configuration / supervised keys should be.
I've filled out the basic info on the model card to the best of my knowledge but it's a little tricky to understand exactly what the fields represent.
Dataset author: @yanaiela | {
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"> Thanks for adding this @ghomasHudson!\r\n> I added some comments for some of the fields.\r\n> \r\n> Also, I'm not sure about this since I haven't used the library yet, but maybe it's worth adding the identification and resolution as two separate datasets?\r\n\r\nThanks for replying @yanaiela - I hope this will m... |
https://api.github.com/repos/huggingface/datasets/issues/1606 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1606/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1606/comments | https://api.github.com/repos/huggingface/datasets/issues/1606/events | https://github.com/huggingface/datasets/pull/1606 | 771,116,455 | MDExOlB1bGxSZXF1ZXN0NTQyNzMwNTEw | 1,606 | added Semantic Scholar Open Research Corpus | [] | closed | false | null | 1 | 2020-12-18T19:21:24Z | 2021-02-03T09:30:59Z | 2021-02-03T09:30:59Z | null | I picked up this dataset [Semantic Scholar Open Research Corpus](https://allenai.org/data/s2orc) but it contains 6000 files to be downloaded. I tried the current code with 100 files and it worked fine (took ~15GB space). For 6000 files it would occupy ~900GB space which I don’t have. Can someone from the HF team with that much of disk space help me with generate dataset_infos and dummy_data? | {
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"I think we’ll need complete dataset_infos.json to create YAML tags. I ran the script again with 100 files after going through your comments and it was occupying ~16 GB space. So in total it should take ~960GB and I don’t have this much memory available with me. Also, I'll have to download the whole dataset for gen... |
https://api.github.com/repos/huggingface/datasets/issues/2507 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2507/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2507/comments | https://api.github.com/repos/huggingface/datasets/issues/2507/events | https://github.com/huggingface/datasets/pull/2507 | 921,441,962 | MDExOlB1bGxSZXF1ZXN0NjcwNDQ0MDgz | 2,507 | Rearrange JSON field names to match passed features schema field names | [] | closed | false | {
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} | 0 | 2021-06-15T14:10:02Z | 2021-06-16T10:47:49Z | 2021-06-16T10:47:49Z | null | This PR depends on PR #2453 (which must be merged first).
Close #2366. | {
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https://api.github.com/repos/huggingface/datasets/issues/956 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/956/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/956/comments | https://api.github.com/repos/huggingface/datasets/issues/956/events | https://github.com/huggingface/datasets/pull/956 | 754,368,378 | MDExOlB1bGxSZXF1ZXN0NTMwMjgwMzU1 | 956 | Add Norwegian NER | [] | closed | false | null | 1 | 2020-12-01T12:51:02Z | 2020-12-02T08:53:11Z | 2020-12-01T18:09:21Z | null | This PR adds the [Norwegian NER](https://github.com/ljos/navnkjenner) dataset.
I have added the `conllu` package as a test dependency. This is required to properly parse the `.conllu` files. | {
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"Merging this one, good job and thank you @jplu :) "
] |
https://api.github.com/repos/huggingface/datasets/issues/807 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/807/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/807/comments | https://api.github.com/repos/huggingface/datasets/issues/807/events | https://github.com/huggingface/datasets/issues/807 | 737,509,954 | MDU6SXNzdWU3Mzc1MDk5NTQ= | 807 | load_dataset for LOCAL CSV files report CONNECTION ERROR | [] | closed | false | null | 11 | 2020-11-06T06:33:04Z | 2021-01-11T01:30:27Z | 2020-11-14T05:30:34Z | null | ## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/807/timeline | null | completed | null | null | false | [
"Hi !\r\nThe url works on my side.\r\n\r\nIs the url working in your navigator ?\r\nAre you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?",
"> Hi !\r\n> The url works on my side.\r\n> \r\n> Is the url working in your navigator ?\r\n> Are you connected to internet ? Does y... |
https://api.github.com/repos/huggingface/datasets/issues/2728 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2728/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2728/comments | https://api.github.com/repos/huggingface/datasets/issues/2728/events | https://github.com/huggingface/datasets/issues/2728 | 955,892,970 | MDU6SXNzdWU5NTU4OTI5NzA= | 2,728 | Concurrent use of same dataset (already downloaded) | [
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"name": "bug",
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] | open | false | null | 4 | 2021-07-29T14:18:38Z | 2021-08-02T07:25:57Z | null | null | ## Describe the bug
When launching several jobs at the same time loading the same dataset trigger some errors see (last comments).
## Steps to reproduce the bug
export HF_DATASETS_CACHE=/gpfswork/rech/toto/datasets
for MODEL in "bert-base-uncased" "roberta-base" "distilbert-base-cased"; do # "bert-base-uncased" "bert-large-cased" "roberta-large" "albert-base-v1" "albert-large-v1"; do
for TASK_NAME in "mrpc" "rte" 'imdb' "paws" "mnli"; do
export OUTPUT_DIR=${MODEL}_${TASK_NAME}
sbatch --job-name=${OUTPUT_DIR} \
--gres=gpu:1 \
--no-requeue \
--cpus-per-task=10 \
--hint=nomultithread \
--time=1:00:00 \
--output=jobinfo/${OUTPUT_DIR}_%j.out \
--error=jobinfo/${OUTPUT_DIR}_%j.err \
--qos=qos_gpu-t4 \
--wrap="module purge; module load pytorch-gpu/py3/1.7.0 ; export HF_DATASETS_OFFLINE=1; export HF_DATASETS_CACHE=/gpfswork/rech/toto/datasets; python compute_measures.py --seed=$SEED --saving_path=results --batch_size=$BATCH_SIZE --task_name=$TASK_NAME --model_name=/gpfswork/rech/toto/transformers_models/$MODEL"
done
done
```python
# Sample code to reproduce the bug
dataset_train = load_dataset('imdb', split='train', download_mode="reuse_cache_if_exists")
dataset_train = dataset_train.map(lambda e: tokenizer(e['text'], truncation=True, padding='max_length'),
batched=True).select(list(range(args.filter)))
dataset_val = load_dataset('imdb', split='train', download_mode="reuse_cache_if_exists")
dataset_val = dataset_val.map(lambda e: tokenizer(e['text'], truncation=True, padding='max_length'),
batched=True).select(list(range(args.filter, args.filter + 5000)))
dataset_test = load_dataset('imdb', split='test', download_mode="reuse_cache_if_exists")
dataset_test = dataset_test.map(lambda e: tokenizer(e['text'], truncation=True, padding='max_length'),
batched=True)
```
## Expected results
I believe I am doing something wrong with the objects.
## Actual results
Traceback (most recent call last):
File "/gpfslocalsup/pub/anaconda-py3/2020.02/envs/pytorch-gpu-1.7.0/lib/python3.7/site-packages/datasets/builder.py", line 652, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/gpfslocalsup/pub/anaconda-py3/2020.02/envs/pytorch-gpu-1.7.0/lib/python3.7/site-packages/datasets/builder.py", line 983, in _prepare_split
check_duplicates=True,
File "/gpfslocalsup/pub/anaconda-py3/2020.02/envs/pytorch-gpu-1.7.0/lib/python3.7/site-packages/datasets/arrow_writer.py", line 192, in __init__
self.stream = pa.OSFile(self._path, "wb")
File "pyarrow/io.pxi", line 829, in pyarrow.lib.OSFile.__cinit__
File "pyarrow/io.pxi", line 844, in pyarrow.lib.OSFile._open_writable
File "pyarrow/error.pxi", line 122, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 97, in pyarrow.lib.check_status
FileNotFoundError: [Errno 2] Failed to open local file '/gpfswork/rech/tts/unm25jp/datasets/paws/labeled_final/1.1.0/09d8fae989bb569009a8f5b879ccf2924d3e5cd55bfe2e89e6dab1c0b50ecd34.incomplete/paws-test.arrow'. Detail: [errno 2] No such file or directory
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "compute_measures.py", line 181, in <module>
train_loader, val_loader, test_loader = get_dataloader(args)
File "/gpfsdswork/projects/rech/toto/intRAOcular/dataset_utils.py", line 69, in get_dataloader
dataset_train = load_dataset('paws', "labeled_final", split='train', download_mode="reuse_cache_if_exists")
File "/gpfslocalsup/pub/anaconda-py3/2020.02/envs/pytorch-gpu-1.7.0/lib/python3.7/site-packages/datasets/load.py", line 748, in load_dataset
use_auth_token=use_auth_token,
File "/gpfslocalsup/pub/anaconda-py3/2020.02/envs/pytorch-gpu-1.7.0/lib/python3.7/site-packages/datasets/builder.py", line 575, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/gpfslocalsup/pub/anaconda-py3/2020.02/envs/pytorch-gpu-1.7.0/lib/python3.7/site-packages/datasets/builder.py", line 658, in _download_and_prepare
+ str(e)
OSError: Cannot find data file.
Original error:
[Errno 2] Failed to open local file '/gpfswork/rech/toto/datasets/paws/labeled_final/1.1.0/09d8fae989bb569009a8f5b879ccf2924d3e5cd55bfe2e89e6dab1c0b50ecd34.incomplete/paws-test.arrow'. Detail: [errno 2] No such file or directory
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: datasets==1.8.0
- Platform: linux (jeanzay)
- Python version: pyarrow==2.0.0
- PyArrow version: 3.7.8
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"Launching simultaneous job relying on the same datasets try some writing issue. I guess it is unexpected since I only need to load some already downloaded file.",
"If i have two jobs that use the same dataset. I got :\r\n\r\n\r\n File \"compute_measures.py\", line 181, in <module>\r\n train_loader, val_loade... |
https://api.github.com/repos/huggingface/datasets/issues/5535 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5535/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5535/comments | https://api.github.com/repos/huggingface/datasets/issues/5535/events | https://github.com/huggingface/datasets/pull/5535 | 1,586,520,369 | PR_kwDODunzps5KEb5L | 5,535 | Add JAX-formatting documentation | [] | closed | false | null | 9 | 2023-02-15T20:35:11Z | 2023-02-20T10:39:42Z | 2023-02-20T10:32:39Z | null | ## What's in this PR?
As a follow-up of #5522, I've created this entry in the documentation to explain how to use `.with_format("jax")` and why is it useful.
@lhoestq Feel free to drop any feedback and/or suggestion, as probably more useful features can be included there! | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> Awesome thank you !\r\n> \r\n> Could you also explain how to use certain types like ClassLabel, Image or Audio with jax ? You can get a lot of inspiration from the \"Other feature types\" section in the [PyTorch page](https://huggi... |
https://api.github.com/repos/huggingface/datasets/issues/1390 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1390/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1390/comments | https://api.github.com/repos/huggingface/datasets/issues/1390/events | https://github.com/huggingface/datasets/pull/1390 | 760,431,051 | MDExOlB1bGxSZXF1ZXN0NTM1MjYzNzk1 | 1,390 | Add SPC Dataset | [] | closed | false | null | 0 | 2020-12-09T15:31:51Z | 2020-12-14T11:13:53Z | 2020-12-14T11:13:52Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/607 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/607/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/607/comments | https://api.github.com/repos/huggingface/datasets/issues/607/events | https://github.com/huggingface/datasets/pull/607 | 698,094,442 | MDExOlB1bGxSZXF1ZXN0NDgzOTcyMDg4 | 607 | Add transmit_format wrapper and tests | [] | closed | false | null | 0 | 2020-09-10T15:03:50Z | 2020-09-10T15:21:48Z | 2020-09-10T15:21:47Z | null | Same as #605 but using a decorator on-top of dataset transforms that are not in place | {
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https://api.github.com/repos/huggingface/datasets/issues/4152 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4152/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4152/comments | https://api.github.com/repos/huggingface/datasets/issues/4152/events | https://github.com/huggingface/datasets/issues/4152 | 1,202,034,115 | I_kwDODunzps5HpZXD | 4,152 | ArrayND error in pyarrow 5 | [] | closed | false | null | 2 | 2022-04-12T15:41:40Z | 2022-05-04T09:29:46Z | 2022-05-04T09:29:46Z | null | As found in https://github.com/huggingface/datasets/pull/3903, The ArrayND features fail on pyarrow 5:
```python
import pyarrow as pa
from datasets import Array2D
from datasets.table import cast_array_to_feature
arr = pa.array([[[0]]])
feature_type = Array2D(shape=(1, 1), dtype="int64")
cast_array_to_feature(arr, feature_type)
```
raises
```python
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-8-04610f9fa78c> in <module>
----> 1 cast_array_to_feature(pa.array([[[0]]]), Array2D(shape=(1, 1), dtype="int32"))
~/Desktop/hf/datasets/src/datasets/table.py in wrapper(array, *args, **kwargs)
1672 return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
1673 else:
-> 1674 return func(array, *args, **kwargs)
1675
1676 return wrapper
~/Desktop/hf/datasets/src/datasets/table.py in cast_array_to_feature(array, feature, allow_number_to_str)
1806 return array_cast(array, get_nested_type(feature), allow_number_to_str=allow_number_to_str)
1807 elif not isinstance(feature, (Sequence, dict, list, tuple)):
-> 1808 return array_cast(array, feature(), allow_number_to_str=allow_number_to_str)
1809 raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}")
1810
~/Desktop/hf/datasets/src/datasets/table.py in wrapper(array, *args, **kwargs)
1672 return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
1673 else:
-> 1674 return func(array, *args, **kwargs)
1675
1676 return wrapper
~/Desktop/hf/datasets/src/datasets/table.py in array_cast(array, pa_type, allow_number_to_str)
1705 array = array.storage
1706 if isinstance(pa_type, pa.ExtensionType):
-> 1707 return pa_type.wrap_array(array)
1708 elif pa.types.is_struct(array.type):
1709 if pa.types.is_struct(pa_type) and (
AttributeError: 'Array2DExtensionType' object has no attribute 'wrap_array'
```
The thing is that `cast_array_to_feature` is called when writing an Arrow file, so creating an Arrow dataset using any ArrayND type currently fails.
`wrap_array` has been added in pyarrow 6, so we can either bump the required pyarrow version or fix this for pyarrow 5 | {
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"Where do we bump the required pyarrow version? Any inputs on how I fix this issue? ",
"We need to bump it in `setup.py` as well as update some CI job to use pyarrow 6 instead of 5 in `.circleci/config.yaml` and `.github/workflows/benchmarks.yaml`"
] |
https://api.github.com/repos/huggingface/datasets/issues/6076 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6076/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6076/comments | https://api.github.com/repos/huggingface/datasets/issues/6076/events | https://github.com/huggingface/datasets/pull/6076 | 1,822,345,597 | PR_kwDODunzps5WcGVR | 6,076 | No gzip encoding from github | [] | closed | false | null | 3 | 2023-07-26T12:46:07Z | 2023-07-27T16:15:11Z | 2023-07-27T16:14:40Z | null | Don't accept gzip encoding from github, otherwise some files are not streamable + seekable.
fix https://huggingface.co/datasets/code_x_glue_cc_code_to_code_trans/discussions/2#64c0e0c1a04a514ba6303e84
and making sure https://github.com/huggingface/datasets/issues/2918 works as well | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/2752 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2752/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2752/comments | https://api.github.com/repos/huggingface/datasets/issues/2752/events | https://github.com/huggingface/datasets/pull/2752 | 959,023,608 | MDExOlB1bGxSZXF1ZXN0NzAyMjAxMjAy | 2,752 | Generate metadata JSON for lm1b dataset | [] | closed | false | null | 0 | 2021-08-03T11:34:56Z | 2021-08-04T06:40:40Z | 2021-08-04T06:40:39Z | null | Related to #2743. | {
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https://api.github.com/repos/huggingface/datasets/issues/2989 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2989/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2989/comments | https://api.github.com/repos/huggingface/datasets/issues/2989/events | https://github.com/huggingface/datasets/pull/2989 | 1,011,220,375 | PR_kwDODunzps4sdlt1 | 2,989 | Add CommonLanguage | [] | closed | false | null | 0 | 2021-09-29T17:21:30Z | 2021-10-01T17:36:39Z | 2021-10-01T17:00:03Z | null | This PR adds the Common Language dataset (https://zenodo.org/record/5036977)
The dataset is intended for language-identification speech classifiers and is already used by models on the Hub:
* https://huggingface.co/speechbrain/lang-id-commonlanguage_ecapa
* https://huggingface.co/anton-l/wav2vec2-base-langid
cc @patrickvonplaten | {
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https://api.github.com/repos/huggingface/datasets/issues/3897 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3897/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3897/comments | https://api.github.com/repos/huggingface/datasets/issues/3897/events | https://github.com/huggingface/datasets/pull/3897 | 1,166,715,104 | PR_kwDODunzps40UJH4 | 3,897 | Align tqdm control/cache control with Transformers | [] | closed | false | null | 1 | 2022-03-11T18:12:22Z | 2022-03-14T15:01:10Z | 2022-03-14T15:01:08Z | null | This PR:
* aligns the `tqdm` logic with Transformers (follows https://github.com/huggingface/transformers/pull/15167) by moving the code to `utils/logging.py`, adding `enable_progres_bar`/`disable_progres_bar` and removing `set_progress_bar_enabled` (a note for @lhoestq: I'm not adding `logging.tqdm` to the public namespace in this PR to avoid the situation where `from datasets import *; tqdm` would overshadow the standard `tqdm`
* aligns the cache control with the new `tqdm` logic by adding `enable_caching`/`disable_caching` to the public namespace and deprecating `set_caching_enabled` (not fully removing it because it's used more often than `set_progress_bar_enabled` and has a dedicated example in the old docs)
Fix #3586 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3897). All of your documentation changes will be reflected on that endpoint."
] |
https://api.github.com/repos/huggingface/datasets/issues/5376 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5376/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5376/comments | https://api.github.com/repos/huggingface/datasets/issues/5376/events | https://github.com/huggingface/datasets/pull/5376 | 1,502,730,559 | PR_kwDODunzps5FxWkM | 5,376 | set dev version | [] | closed | false | null | 1 | 2022-12-19T10:56:56Z | 2022-12-19T11:01:55Z | 2022-12-19T10:57:16Z | null | null | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5376). All of your documentation changes will be reflected on that endpoint."
] |
https://api.github.com/repos/huggingface/datasets/issues/293 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/293/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/293/comments | https://api.github.com/repos/huggingface/datasets/issues/293/events | https://github.com/huggingface/datasets/pull/293 | 642,942,182 | MDExOlB1bGxSZXF1ZXN0NDM3ODM1ODI4 | 293 | Don't test community datasets | [] | closed | false | null | 0 | 2020-06-22T10:15:33Z | 2020-06-22T11:07:00Z | 2020-06-22T11:06:59Z | null | This PR disables testing for community datasets on aws.
It should fix the CI that is currently failing. | {
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https://api.github.com/repos/huggingface/datasets/issues/238 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/238/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/238/comments | https://api.github.com/repos/huggingface/datasets/issues/238/events | https://github.com/huggingface/datasets/issues/238 | 631,260,143 | MDU6SXNzdWU2MzEyNjAxNDM= | 238 | [Metric] Bertscore : Warning : Empty candidate sentence; Setting recall to be 0. | [
{
"color": "25b21e",
"default": false,
"description": "A bug in a metric script",
"id": 2067393914,
"name": "metric bug",
"node_id": "MDU6TGFiZWwyMDY3MzkzOTE0",
"url": "https://api.github.com/repos/huggingface/datasets/labels/metric%20bug"
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] | closed | false | null | 1 | 2020-06-05T02:14:47Z | 2020-06-29T17:10:19Z | 2020-06-29T17:10:19Z | null | When running BERT-Score, I'm meeting this warning :
> Warning: Empty candidate sentence; Setting recall to be 0.
Code :
```
import nlp
metric = nlp.load_metric("bertscore")
scores = metric.compute(["swag", "swags"], ["swags", "totally something different"], lang="en", device=0)
```
---
**What am I doing wrong / How can I hide this warning ?** | {
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"This print statement comes from the official implementation of bert_score (see [here](https://github.com/Tiiiger/bert_score/blob/master/bert_score/utils.py#L343)). The warning shows up only if the attention mask outputs no candidate.\r\nRight now we want to only use official code for metrics to have fair evaluatio... |
https://api.github.com/repos/huggingface/datasets/issues/2448 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2448/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2448/comments | https://api.github.com/repos/huggingface/datasets/issues/2448/events | https://github.com/huggingface/datasets/pull/2448 | 912,360,109 | MDExOlB1bGxSZXF1ZXN0NjYyNTI2NjA3 | 2,448 | Fix flores download link | [] | closed | false | null | 0 | 2021-06-05T17:30:24Z | 2021-06-08T20:02:58Z | 2021-06-07T08:18:25Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2177 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2177/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2177/comments | https://api.github.com/repos/huggingface/datasets/issues/2177/events | https://github.com/huggingface/datasets/pull/2177 | 852,065,307 | MDExOlB1bGxSZXF1ZXN0NjEwMzc5MDYx | 2,177 | add social thumbnial | [] | closed | false | null | 0 | 2021-04-07T06:40:06Z | 2021-04-07T08:16:01Z | 2021-04-07T08:16:01Z | null | # What does this PR do?
I added OpenGraph/ Twitter Card support to the docs to create nice social thumbnails.
To be able to add these I needed to install `sphinxext-opengraph`. I came across this [issue](https://github.com/readthedocs/readthedocs.org/issues/1758) on the readthedocs repo saying that since someone has built this plugin they are not integrating and providing documentation to it. That's why I added it for creating the documentation. The repository can be found [here](https://github.com/wpilibsuite/sphinxext-opengraph/tree/main).
P.S. It seemed that `make style` never ran for `docs/` i hope the changes are okay otherwise I'll revert it. | {
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https://api.github.com/repos/huggingface/datasets/issues/4609 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4609/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4609/comments | https://api.github.com/repos/huggingface/datasets/issues/4609/events | https://github.com/huggingface/datasets/issues/4609 | 1,290,392,083 | I_kwDODunzps5M6dIT | 4,609 | librispeech dataset has to download whole subset when specifing the split to use | [
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] | closed | false | null | 2 | 2022-06-30T16:38:24Z | 2022-07-12T21:44:32Z | 2022-07-12T21:44:32Z | null | ## Describe the bug
librispeech dataset has to download whole subset when specifing the split to use
## Steps to reproduce the bug
see below
# Sample code to reproduce the bug
```
!pip install datasets
from datasets import load_dataset
raw_dataset = load_dataset("librispeech_asr", "clean", split="train.100")
```
## Expected results
The split "train.clean.100" is downloaded.
## Actual results
All four splits in "clean" subset is downloaded.
## Environment info
- `datasets` version: 2.3.2
- Platform: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 6.0.1
- Pandas version: 1.3.5
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} | https://api.github.com/repos/huggingface/datasets/issues/4609/timeline | null | completed | null | null | false | [
"Hi! You can use streaming to fetch only a subset of the data:\r\n```python\r\nraw_dataset = load_dataset(\"librispeech_asr\", \"clean\", split=\"train.100\", streaming=True)\r\n```\r\nAlso, we plan to make it possible to download a particular split in the non-streaming mode, but this task is not easy due to how ou... |
https://api.github.com/repos/huggingface/datasets/issues/5607 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5607/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5607/comments | https://api.github.com/repos/huggingface/datasets/issues/5607/events | https://github.com/huggingface/datasets/pull/5607 | 1,609,166,035 | PR_kwDODunzps5LQPbG | 5,607 | Fix outdated `verification_mode` values | [] | closed | false | null | 2 | 2023-03-03T19:50:29Z | 2023-03-09T17:34:13Z | 2023-03-09T17:27:07Z | null | ~I think it makes sense not to save `dataset_info.json` file to a dataset cache directory when loading dataset with `verification_mode="no_checks"` because otherwise when next time the dataset is loaded **without** `verification_mode="no_checks"`, it will be loaded successfully, despite some values in info might not correspond to the ones in the repo which was the reason for using `verification_mode="no_checks"` first.~
Updated values of `verification_mode` to the current ones in some places ("none" -> "no_checks", "all" -> "all_checks") | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/3451 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3451/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3451/comments | https://api.github.com/repos/huggingface/datasets/issues/3451/events | https://github.com/huggingface/datasets/pull/3451 | 1,083,459,137 | PR_kwDODunzps4wA5LP | 3,451 | [Staging] Update dataset repos automatically on the Hub | [] | closed | false | null | 2 | 2021-12-17T17:12:11Z | 2021-12-21T10:25:46Z | 2021-12-20T14:09:51Z | null | Let's have a script that updates the dataset repositories on staging for now. This way we can make sure it works fine before going in prod.
Related to https://github.com/huggingface/datasets/issues/3341
The script runs on each commit on `master`. It checks the datasets that were changed, and it pushes the changes to the corresponding repositories on the Hub.
If there's a new dataset, then a new repository is created.
If the commit is a new release of `datasets`, it also pushes the tag to all the repositories. | {
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"do keep us updated on how it's going in staging! cc @SBrandeis ",
"Sure ! For now it works smoothly. We'll also do a new release today.\r\n\r\nI can send you some repos to explore on staging, in case you want to see how they look like after being updated.\r\nFor example [swahili_news](https://moon-staging.huggin... |
https://api.github.com/repos/huggingface/datasets/issues/2835 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2835/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2835/comments | https://api.github.com/repos/huggingface/datasets/issues/2835/events | https://github.com/huggingface/datasets/pull/2835 | 979,209,394 | MDExOlB1bGxSZXF1ZXN0NzE5NjUxOTE4 | 2,835 | Update: timit_asr - make the dataset streamable | [] | closed | false | null | 0 | 2021-08-25T14:22:49Z | 2021-09-07T13:15:47Z | 2021-09-07T13:15:46Z | null | The TIMIT ASR dataset had two issues that was preventing it from being streamable:
1. it was missing a call to `open` before `pd.read_csv`
2. it was using `os.path.dirname` which is not supported for streaming
I made the dataset streamable by using `open` to load the CSV, and by adding the support for `os.path.dirname` in dataset scripts to stream data
You can now do
```python
from datasets import load_dataset
timit_asr = load_dataset("timit_asr", streaming=True)
print(next(iter(timit_asr["train"])))
```
prints:
```json
{"file": "zip://data/TRAIN/DR4/MMDM0/SI681.WAV::https://data.deepai.org/timit.zip",
"phonetic_detail": {"start": [0, 1960, 2466, 3480, 4000, 5960, 7480, 7880, 9400, 9960, 10680, 13480, 15680, 15880, 16920, 18297, 18882, 19480, 21723, 22516, 24040, 25190, 27080, 28160, 28560, 30120, 31832, 33240, 34640, 35968, 37720],
"utterance": ["h#", "w", "ix", "dcl", "s", "ah", "tcl", "ch", "ix", "n", "ae", "kcl", "t", "ix", "v", "r", "ix", "f", "y", "ux", "zh", "el", "bcl", "b", "iy", "y", "ux", "s", "f", "el", "h#"],
"stop": [1960, 2466, 3480, 4000, 5960, 7480, 7880, 9400, 9960, 10680, 13480, 15680, 15880, 16920, 18297, 18882, 19480, 21723, 22516, 24040, 25190, 27080, 28160, 28560, 30120, 31832, 33240, 34640, 35968, 37720, 39920]},
"sentence_type": "SI", "id": "SI681",
"speaker_id": "MMDM0",
"dialect_region": "DR4",
"text": "Would such an act of refusal be useful?",
"word_detail": {
"start": [1960, 4000, 9400, 10680, 15880, 18297, 27080, 30120],
"utterance": ["would", "such", "an", "act", "of", "refusal", "be", "useful"],
"stop": [4000, 9400, 10680, 15880, 18297, 27080, 30120, 37720]
}}
```
cc @patrickvonplaten @vrindaprabhu | {
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https://api.github.com/repos/huggingface/datasets/issues/85 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/85/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/85/comments | https://api.github.com/repos/huggingface/datasets/issues/85/events | https://github.com/huggingface/datasets/pull/85 | 617,253,428 | MDExOlB1bGxSZXF1ZXN0NDE3MjA0ODA4 | 85 | Add boolq | [] | closed | false | null | 1 | 2020-05-13T08:32:27Z | 2020-05-13T09:09:39Z | 2020-05-13T09:09:38Z | null | I just added the dummy data for this dataset.
This one was uses `tf.io.gfile.copy` to download the data but I added the support for custom download in the mock_download_manager. I also had to add a `tensorflow` dependency for tests. | {
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"Awesome :-) Thanks for adding the function to the Mock DL Manager"
] |
https://api.github.com/repos/huggingface/datasets/issues/4962 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4962/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4962/comments | https://api.github.com/repos/huggingface/datasets/issues/4962/events | https://github.com/huggingface/datasets/pull/4962 | 1,368,155,365 | PR_kwDODunzps4-sh-o | 4,962 | Update setup.py | [] | closed | false | null | 2 | 2022-09-09T17:57:56Z | 2022-09-12T14:33:04Z | 2022-09-12T14:33:04Z | null | exclude broken version of fsspec. See the [related issue](https://github.com/huggingface/datasets/issues/4961) | {
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"Before addressing this PR, we should be sure about the issue. See my comment in:\r\n- https://github.com/huggingface/datasets/issues/4961#issuecomment-1243376247",
"Once we know 2022.8.2 works, I'm closing this PR, as the corresponding issue."
] |
https://api.github.com/repos/huggingface/datasets/issues/2780 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2780/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2780/comments | https://api.github.com/repos/huggingface/datasets/issues/2780/events | https://github.com/huggingface/datasets/pull/2780 | 964,794,764 | MDExOlB1bGxSZXF1ZXN0NzA3MTk2NjA3 | 2,780 | VIVOS dataset for Vietnamese ASR | [] | closed | false | null | 0 | 2021-08-10T09:47:36Z | 2021-08-12T11:09:30Z | 2021-08-12T11:09:30Z | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/3008 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3008/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3008/comments | https://api.github.com/repos/huggingface/datasets/issues/3008/events | https://github.com/huggingface/datasets/pull/3008 | 1,014,849,163 | PR_kwDODunzps4sn7iU | 3,008 | Fix precision/recall metrics with None average | [] | closed | false | null | 0 | 2021-10-04T07:54:15Z | 2021-10-04T09:29:37Z | 2021-10-04T09:29:36Z | null | Related to issue #2979 and PR #2992. | {
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https://api.github.com/repos/huggingface/datasets/issues/1820 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1820/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1820/comments | https://api.github.com/repos/huggingface/datasets/issues/1820/events | https://github.com/huggingface/datasets/pull/1820 | 801,529,936 | MDExOlB1bGxSZXF1ZXN0NTY3ODI4OTg1 | 1,820 | Add metrics usage examples and tests | [] | closed | false | null | 0 | 2021-02-04T18:23:50Z | 2021-02-05T14:00:01Z | 2021-02-05T14:00:00Z | null | All metrics finally have usage examples and proper fast + slow tests :)
I added examples of usage for every metric, and I use doctest to make sure they all work as expected.
For "slow" metrics such as bert_score or bleurt which require to download + run a transformer model, the download + forward pass are only done in the slow test.
In the fast test on the other hand, the download + forward pass are monkey patched.
Metrics that need to be installed from github are not added to setup.py because it prevents uploading the `datasets` package to pypi.
An additional-test-requirements.txt file is used instead. This file also include `comet` in order to not have to resolve its *impossible* dependencies.
Also `comet` is not tested on windows because one of its dependencies (fairseq) can't be installed in the CI for some reason. | {
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https://api.github.com/repos/huggingface/datasets/issues/4536 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4536/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4536/comments | https://api.github.com/repos/huggingface/datasets/issues/4536/events | https://github.com/huggingface/datasets/pull/4536 | 1,278,734,727 | PR_kwDODunzps46C2z6 | 4,536 | Properly raise FileNotFound even if the dataset is private | [] | closed | false | null | 1 | 2022-06-21T17:05:50Z | 2022-06-28T10:46:51Z | 2022-06-28T10:36:10Z | null | `tests/test_load.py::test_load_streaming_private_dataset` was failing because the hub now returns 401 when getting the HfApi.dataset_info of a dataset without authentication. `load_dataset` was raising ConnectionError, while it should be FileNoteFoundError since it first checks for local files before checking the Hub.
Moreover when use_auth_token is not set (default is False), we should not pass `token=None` to HfApi.dataset_info, or it will use the local token by default - instead it should use no token. It's currently not possible to ask for no token to be used, so as a workaround I simply set token="no-token" | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/5496 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5496/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5496/comments | https://api.github.com/repos/huggingface/datasets/issues/5496/events | https://github.com/huggingface/datasets/issues/5496 | 1,567,301,765 | I_kwDODunzps5dayCF | 5,496 | Add a `reduce` method | [
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] | closed | false | null | 3 | 2023-02-02T04:30:22Z | 2023-07-21T14:24:32Z | 2023-07-21T14:24:32Z | null | ### Feature request
Right now the `Dataset` class implements `map()` and `filter()`, but leaves out the third functional idiom popular among Python users: `reduce`.
### Motivation
A `reduce` method is often useful when calculating dataset statistics, for example, the occurrence of a particular n-gram or the average line length of a code dataset.
### Your contribution
I haven't contributed to `datasets` before, but I don't expect this will be too difficult, since the implementation will closely follow that of `map` and `filter`. I could have a crack over the weekend. | {
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"Hi! Sure, feel free to open a PR, so we can see the API you have in mind.",
"I would like to give it a go! #self-assign",
"Closing as `Dataset.map` can be used instead (see https://github.com/huggingface/datasets/pull/5533#issuecomment-1440571658 and https://github.com/huggingface/datasets/pull/5533#issuecomme... |
https://api.github.com/repos/huggingface/datasets/issues/5796 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5796/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5796/comments | https://api.github.com/repos/huggingface/datasets/issues/5796/events | https://github.com/huggingface/datasets/pull/5796 | 1,685,451,919 | PR_kwDODunzps5PORm- | 5,796 | Spark docs | [] | closed | false | null | 4 | 2023-04-26T17:39:43Z | 2023-04-27T16:41:50Z | 2023-04-27T16:34:45Z | null | Added a "Use with Spark" doc page to document `Dataset.from_spark` following https://github.com/huggingface/datasets/pull/5701
cc @maddiedawson | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/1173 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1173/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1173/comments | https://api.github.com/repos/huggingface/datasets/issues/1173/events | https://github.com/huggingface/datasets/pull/1173 | 757,761,967 | MDExOlB1bGxSZXF1ZXN0NTMzMDc5MTk0 | 1,173 | add wikipedia biography dataset | [] | closed | false | null | 7 | 2020-12-05T19:14:50Z | 2020-12-07T11:13:14Z | 2020-12-07T11:13:14Z | null | My first PR containing the Wikipedia biographies dataset. I have followed all the steps in the [guide](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). It passes all the tests. | {
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"Does anyone know why am I getting this \"Some checks were not successful\" message? For the _code_quality_ one, I have successfully run the flake8 command.",
"Ok, I need to update the README.md, but don't know if that will fix the errors",
"Hi @ACR0S , thanks for adding the dataset!\r\n\r\nIt looks like `black... |
https://api.github.com/repos/huggingface/datasets/issues/3977 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3977/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3977/comments | https://api.github.com/repos/huggingface/datasets/issues/3977/events | https://github.com/huggingface/datasets/issues/3977 | 1,175,049,927 | I_kwDODunzps5GCdbH | 3,977 | Adapt `docs/README.md` for datasets | [
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] | closed | false | null | 1 | 2022-03-21T08:26:49Z | 2023-02-27T10:32:37Z | 2023-02-27T10:32:37Z | null | ## Describe the bug
Currently `docs/README.md` is a direct copy from `transformers`, we should probably adapt this file for `datasets`. | {
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"Thanks for reporting @qqaatw.\r\n\r\nYes, we should definitely adapt that file for `datasets`. "
] |
https://api.github.com/repos/huggingface/datasets/issues/3870 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3870/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3870/comments | https://api.github.com/repos/huggingface/datasets/issues/3870/events | https://github.com/huggingface/datasets/pull/3870 | 1,163,633,239 | PR_kwDODunzps40KAYy | 3,870 | Add wikitablequestions dataset | [] | closed | false | null | 4 | 2022-03-09T08:27:43Z | 2022-03-14T11:19:24Z | 2022-03-14T11:16:19Z | null | null | {
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"@lhoestq Would you mind reviewing it when you're available? Thanks!\r\n",
"> Awesome thanks for adding this dataset ! :) The dataset script and dataset cards look pretty good\r\n> \r\n> It looks like your `dummy_data.zip` files are quite big though (>1MB each), do you think we can reduce their sizes ? This way t... |
https://api.github.com/repos/huggingface/datasets/issues/5667 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5667/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5667/comments | https://api.github.com/repos/huggingface/datasets/issues/5667/events | https://github.com/huggingface/datasets/pull/5667 | 1,637,789,361 | PR_kwDODunzps5Mv8Im | 5,667 | Jax requires jaxlib | [] | closed | false | null | 6 | 2023-03-23T15:41:09Z | 2023-03-23T16:23:11Z | 2023-03-23T16:14:52Z | null | close https://github.com/huggingface/datasets/issues/5666 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/2445 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2445/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2445/comments | https://api.github.com/repos/huggingface/datasets/issues/2445/events | https://github.com/huggingface/datasets/pull/2445 | 911,577,578 | MDExOlB1bGxSZXF1ZXN0NjYxODMzMTky | 2,445 | Fix broken URLs for bn_hate_speech and covid_tweets_japanese | [] | closed | false | null | 2 | 2021-06-04T14:53:35Z | 2021-06-04T17:39:46Z | 2021-06-04T17:39:45Z | null | Closes #2388 | {
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"Thanks ! To fix the CI you just have to rename the dummy data file in the dummy_data.zip files",
"thanks for the tip with the dummy data - all fixed now!"
] |
https://api.github.com/repos/huggingface/datasets/issues/3809 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3809/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3809/comments | https://api.github.com/repos/huggingface/datasets/issues/3809/events | https://github.com/huggingface/datasets/issues/3809 | 1,158,143,480 | I_kwDODunzps5FB934 | 3,809 | Checksums didn't match for datasets on Google Drive | [
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"descript... | closed | false | null | 1 | 2022-03-03T09:01:10Z | 2022-03-03T09:24:58Z | 2022-03-03T09:24:05Z | null | ## Describe the bug
Datasets hosted on Google Drive do not seem to work right now.
Loading them fails with a checksum error.
## Steps to reproduce the bug
```python
from datasets import load_dataset
for dataset in ["head_qa", "yelp_review_full"]:
try:
load_dataset(dataset)
except Exception as exception:
print("Error", dataset, exception)
```
Here is a [colab](https://colab.research.google.com/drive/1wOtHBmL8I65NmUYakzPV5zhVCtHhi7uQ#scrollTo=cDzdCLlk-Bo4).
## Expected results
The datasets should be loaded.
## Actual results
```
Downloading and preparing dataset head_qa/es (download: 75.69 MiB, generated: 2.86 MiB, post-processed: Unknown size, total: 78.55 MiB) to /root/.cache/huggingface/datasets/head_qa/es/1.1.0/583ab408e8baf54aab378c93715fadc4d8aa51b393e27c3484a877e2ac0278e9...
Error head_qa Checksums didn't match for dataset source files:
['https://drive.google.com/u/0/uc?export=download&id=1a_95N5zQQoUCq8IBNVZgziHbeM-QxG2t']
Downloading and preparing dataset yelp_review_full/yelp_review_full (download: 187.06 MiB, generated: 496.94 MiB, post-processed: Unknown size, total: 684.00 MiB) to /root/.cache/huggingface/datasets/yelp_review_full/yelp_review_full/1.0.0/13c31a618ba62568ec8572a222a283dfc29a6517776a3ac5945fb508877dde43...
Error yelp_review_full Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbZlU4dXhHTFhZQU0']
```
## Environment info
- `datasets` version: 1.18.3
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyArrow version: 6.0.1
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} | https://api.github.com/repos/huggingface/datasets/issues/3809/timeline | null | completed | null | null | false | [
"Hi @muelletm, thanks for reporting.\r\n\r\nThis issue was already reported and its root cause is a change in the Google Drive service. See:\r\n- #3786 \r\n\r\nWe have already fixed it. See:\r\n- #3787 \r\n\r\nUntil our next `datasets` library release, you can get this fix by installing our library from the GitHub ... |
https://api.github.com/repos/huggingface/datasets/issues/5037 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5037/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5037/comments | https://api.github.com/repos/huggingface/datasets/issues/5037/events | https://github.com/huggingface/datasets/pull/5037 | 1,389,244,722 | PR_kwDODunzps4_xcp0 | 5,037 | Improve CI performance speed of PackagedDatasetTest | [] | closed | false | null | 2 | 2022-09-28T12:08:16Z | 2022-09-30T16:05:42Z | 2022-09-30T16:03:24Z | null | This PR improves PackagedDatasetTest CI performance speed. For Ubuntu (latest):
- Duration (without parallelism) before: 334.78s (5.58m)
- Duration (without parallelism) afterwards: 0.48s
The approach is passing a dummy `data_files` argument to load the builder, so that it avoids the slow inferring of it over the entire root directory of the repo.
## Total duration of PackagedDatasetTest
| | Before | Afterwards | Improvement
|---|---:|---:|---:|
| Linux | 334.78s | 0.48s | x700
| Windows | 513.02s | 1.09s | x500
## Durations by each individual sub-test
More accurate durations, running them on GitHub, for Linux (latest).
Before this PR, the total test time (without parallelism) for `tests/test_dataset_common.py::PackagedDatasetTest` is 334.78s (5.58m)
```
39.07s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_imagefolder
38.94s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_audiofolder
34.18s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_parquet
34.12s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_csv
34.00s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_pandas
34.00s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_text
33.86s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_json
10.39s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_class_audiofolder
6.50s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_configs_audiofolder
6.46s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_configs_imagefolder
6.40s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_class_imagefolder
5.77s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_class_csv
5.77s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_class_text
5.74s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_configs_parquet
5.69s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_class_json
5.68s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_configs_pandas
5.67s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_class_parquet
5.67s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_class_pandas
5.66s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_configs_json
5.66s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_configs_csv
5.55s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_configs_text
(42 durations < 0.005s hidden.)
```
With this PR: 0.48s
```
0.09s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_audiofolder
0.08s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_csv
0.08s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_imagefolder
0.06s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_json
0.05s call tests/test_dataset_common.py::PackagedDatasetTest::test_builder_class_audiofolder
0.05s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_parquet
0.04s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_pandas
0.03s call tests/test_dataset_common.py::PackagedDatasetTest::test_load_dataset_offline_text
(55 durations < 0.005s hidden.)
```
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"_The documentation is not available anymore as the PR was closed or merged._",
"There was a CI error which seemed unrelated: https://github.com/huggingface/datasets/actions/runs/3143581330/jobs/5111807056\r\n```\r\nFAILED tests/test_load.py::test_load_dataset_private_zipped_images[True] - FileNotFoundError: http... |
https://api.github.com/repos/huggingface/datasets/issues/1171 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1171/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1171/comments | https://api.github.com/repos/huggingface/datasets/issues/1171/events | https://github.com/huggingface/datasets/pull/1171 | 757,757,000 | MDExOlB1bGxSZXF1ZXN0NTMzMDc1NzE3 | 1,171 | Add imdb Urdu Reviews dataset. | [] | closed | false | null | 1 | 2020-12-05T18:46:05Z | 2020-12-07T11:11:17Z | 2020-12-07T11:11:17Z | null | Added the imdb Urdu reviews dataset. More info about the dataset over <a href="https://github.com/mirfan899/Urdu">here</a>. | {
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"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/975 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/975/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/975/comments | https://api.github.com/repos/huggingface/datasets/issues/975/events | https://github.com/huggingface/datasets/pull/975 | 754,823,701 | MDExOlB1bGxSZXF1ZXN0NTMwNjUzNjg4 | 975 | add MeTooMA dataset | [] | closed | false | null | 0 | 2020-12-02T00:15:55Z | 2020-12-02T10:58:56Z | 2020-12-02T10:58:55Z | null | This PR adds the #MeToo MA dataset. It presents multi-label data points for tweets mined in the backdrop of the #MeToo movement. The dataset includes data points in the form of Tweet ids and appropriate labels. Please refer to the accompanying paper for detailed information regarding annotation, collection, and guidelines.
Paper: https://ojs.aaai.org/index.php/ICWSM/article/view/7292
Dataset Link: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/JN4EYU
---
annotations_creators:
- expert-generated
language_creators:
- found
languages:
- en
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
- text-retrieval
task_ids:
- multi-class-classification
- multi-label-classification
---
# Dataset Card for #MeTooMA dataset
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Homepage:** https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/JN4EYU
- **Paper:** https://ojs.aaai.org//index.php/ICWSM/article/view/7292
- **Point of Contact:** https://github.com/midas-research/MeTooMA
### Dataset Summary
- The dataset consists of tweets belonging to #MeToo movement on Twitter, labeled into different categories.
- This dataset includes more data points and has more labels than any of the previous datasets that contain social media
posts about sexual abuse disclosures. Please refer to the Related Datasets of the publication for detailed information about this.
- Due to Twitter's development policies, the authors provide only the tweet IDs and corresponding labels,
other data can be fetched via Twitter API.
- The data has been labeled by experts, with the majority taken into the account for deciding the final label.
- The authors provide these labels for each of the tweets.
- Relevance
- Directed Hate
- Generalized Hate
- Sarcasm
- Allegation
- Justification
- Refutation
- Support
- Oppose
- The definitions for each task/label are in the main publication.
- Please refer to the accompanying paper https://aaai.org/ojs/index.php/ICWSM/article/view/7292 for statistical analysis on the textual data
extracted from this dataset.
- The language of all the tweets in this dataset is English
- Time period: October 2018 - December 2018
- Suggested Use Cases of this dataset:
- Evaluating usage of linguistic acts such as hate-speech and sarcasm in the context of public sexual abuse disclosures.
- Extracting actionable insights and virtual dynamics of gender roles in sexual abuse revelations.
- Identifying how influential people were portrayed on the public platform in the
events of mass social movements.
- Polarization analysis based on graph simulations of social nodes of users involved
in the #MeToo movement.
### Supported Tasks and Leaderboards
Multi-Label and Multi-Class Classification
### Languages
English
## Dataset Structure
- The dataset is structured into CSV format with TweetID and accompanying labels.
- Train and Test sets are split into respective files.
### Data Instances
Tweet ID and the appropriate labels
### Data Fields
Tweet ID and appropriate labels (binary label applicable for a data point) and multiple labels for each Tweet ID
### Data Splits
- Train: 7979
- Test: 1996
## Dataset Creation
### Curation Rationale
- Twitter was the major source of all the public disclosures of sexual abuse incidents during the #MeToo movement.
- People expressed their opinions over issues that were previously missing from the social media space.
- This provides an option to study the linguistic behaviors of social media users in an informal setting,
therefore the authors decide to curate this annotated dataset.
- The authors expect this dataset would be of great interest and use to both computational and socio-linguists.
- For computational linguists, it provides an opportunity to model three new complex dialogue acts (allegation, refutation, and justification) and also to study how these acts interact with some of the other linguistic components like stance, hate, and sarcasm. For socio-linguists, it provides an opportunity to explore how a movement manifests in social media.
### Source Data
- Source of all the data points in this dataset is a Twitter social media platform.
#### Initial Data Collection and Normalization
- All the tweets are mined from Twitter with initial search parameters identified using keywords from the #MeToo movement.
- Redundant keywords were removed based on manual inspection.
- Public streaming APIs of Twitter was used for querying with the selected keywords.
- Based on text de-duplication and cosine similarity score, the set of tweets were pruned.
- Non-English tweets were removed.
- The final set was labeled by experts with the majority label taken into the account for deciding the final label.
- Please refer to this paper for detailed information: https://ojs.aaai.org//index.php/ICWSM/article/view/7292
#### Who are the source language producers?
Please refer to this paper for detailed information: https://ojs.aaai.org//index.php/ICWSM/article/view/7292
### Annotations
#### Annotation process
- The authors chose against crowdsourcing for labeling this dataset due to its highly sensitive nature.
- The annotators are domain experts having degrees in advanced clinical psychology and gender studies.
- They were provided a guidelines document with instructions about each task and its definitions, labels, and examples.
- They studied the document, worked on a few examples to get used to this annotation task.
- They also provided feedback for improving the class definitions.
- The annotation process is not mutually exclusive, implying that the presence of one label does not mean the
absence of the other one.
#### Who are the annotators?
- The annotators are domain experts having a degree in clinical psychology and gender studies.
- Please refer to the accompanying paper for a detailed annotation process.
### Personal and Sensitive Information
- Considering Twitter's policy for distribution of data, only Tweet ID and applicable labels are shared for public use.
- It is highly encouraged to use this dataset for scientific purposes only.
- This dataset collection completely follows the Twitter mandated guidelines for distribution and usage.
## Considerations for Using the Data
### Social Impact of Dataset
- The authors of this dataset do not intend to conduct a population-centric analysis of the #MeToo movement on Twitter.
- The authors acknowledge that findings from this dataset cannot be used as-is for any direct social intervention, these
should be used to assist already existing human intervention tools and therapies.
- Enough care has been taken to ensure that this work comes off as trying to target a specific person for their
the personal stance of issues pertaining to the #MeToo movement.
- The authors of this work do not aim to vilify anyone accused in the #MeToo movement in any manner.
- Please refer to the ethics and discussion section of the mentioned publication for appropriate sharing of this dataset
and the social impact of this work.
### Discussion of Biases
- The #MeToo movement acted as a catalyst for implementing social policy changes to benefit the members of
the community affected by sexual abuse.
- Any work undertaken on this dataset should aim to minimize the bias against minority groups which
might amplify in cases of a sudden outburst of public reactions over sensitive social media discussions.
### Other Known Limitations
- Considering privacy concerns, social media practitioners should be aware of making automated interventions
to aid the victims of sexual abuse as some people might not prefer to disclose their notions.
- Concerned social media users might also repeal their social information if they found out that their
information is being used for computational purposes, hence it is important to seek subtle individual consent
before trying to profile authors involved in online discussions to uphold personal privacy.
## Additional Information
Please refer to this link: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/JN4EYU
### Dataset Curators
- If you use the corpus in a product or application, then please credit the authors
and [Multimodal Digital Media Analysis Lab - Indraprastha Institute of Information Technology, New Delhi]
(http://midas.iiitd.edu.in) appropriately.
Also, if you send us an email, we will be thrilled to know about how you have used the corpus.
- If interested in the commercial use of the corpus, send an email to midas@iiitd.ac.in.
- Multimodal Digital Media Analysis Lab - Indraprastha Institute of Information Technology, New Delhi, India
disclaims any responsibility for the use of the corpus and does not provide technical support.
However, the contact listed above will be happy to respond to queries and clarifications
- Please feel free to send us an email:
- with feedback regarding the corpus.
- with information on how you have used the corpus.
- if interested in having us analyze your social media data.
- if interested in a collaborative research project.
### Licensing Information
[More Information Needed]
### Citation Information
Please cite the following publication if you make use of the dataset: https://ojs.aaai.org/index.php/ICWSM/article/view/7292
```
@article{Gautam_Mathur_Gosangi_Mahata_Sawhney_Shah_2020, title={#MeTooMA: Multi-Aspect Annotations of Tweets Related to the MeToo Movement}, volume={14}, url={https://aaai.org/ojs/index.php/ICWSM/article/view/7292}, abstractNote={<p>In this paper, we present a dataset containing 9,973 tweets related to the MeToo movement that were manually annotated for five different linguistic aspects: relevance, stance, hate speech, sarcasm, and dialogue acts. We present a detailed account of the data collection and annotation processes. The annotations have a very high inter-annotator agreement (0.79 to 0.93 k-alpha) due to the domain expertise of the annotators and clear annotation instructions. We analyze the data in terms of geographical distribution, label correlations, and keywords. Lastly, we present some potential use cases of this dataset. We expect this dataset would be of great interest to psycholinguists, socio-linguists, and computational linguists to study the discursive space of digitally mobilized social movements on sensitive issues like sexual harassment.</p&gt;}, number={1}, journal={Proceedings of the International AAAI Conference on Web and Social Media}, author={Gautam, Akash and Mathur, Puneet and Gosangi, Rakesh and Mahata, Debanjan and Sawhney, Ramit and Shah, Rajiv Ratn}, year={2020}, month={May}, pages={209-216} }
```
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https://api.github.com/repos/huggingface/datasets/issues/490 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/490/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/490/comments | https://api.github.com/repos/huggingface/datasets/issues/490/events | https://github.com/huggingface/datasets/issues/490 | 676,482,242 | MDU6SXNzdWU2NzY0ODIyNDI= | 490 | Loading preprocessed Wikipedia dataset requires apache_beam | [] | closed | false | null | 0 | 2020-08-10T23:46:50Z | 2020-08-14T13:17:20Z | 2020-08-14T13:17:20Z | null | Running
`nlp.load_dataset("wikipedia", "20200501.en", split="train", dir="/tmp/wikipedia")`
gives an error if apache_beam is not installed, stemming from
https://github.com/huggingface/nlp/blob/38eb2413de54ee804b0be81781bd65ac4a748ced/src/nlp/builder.py#L981-L988
This succeeded without the dependency in version 0.3.0. This seems like an unnecessary dependency to process some dataset info if you're using the already-preprocessed version. Could it be removed? | {
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https://api.github.com/repos/huggingface/datasets/issues/1878 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1878/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1878/comments | https://api.github.com/repos/huggingface/datasets/issues/1878/events | https://github.com/huggingface/datasets/pull/1878 | 808,526,883 | MDExOlB1bGxSZXF1ZXN0NTczNTUyODk3 | 1,878 | Add LJ Speech dataset | [] | closed | false | null | 3 | 2021-02-15T13:10:42Z | 2021-02-15T19:39:41Z | 2021-02-15T14:18:09Z | null | This PR adds the LJ Speech dataset (https://keithito.com/LJ-Speech-Dataset/)
As requested by #1841
The ASR format is based on #1767
There are a couple of quirks that should be addressed:
- I tagged this dataset as `other-other-automatic-speech-recognition` and `other-other-text-to-speech` (as classified by paperswithcode). Since the number of speech datasets is about to grow, maybe these categories should be added to the main list?
- Similarly to #1767 this dataset uses only a single dummy sample to reduce the zip size (`wav`s are quite heavy). Is there a plan to allow LFS or S3 usage for dummy data in the repo?
- The dataset is distributed under the Public Domain license, which is not used anywhere else in the repo, AFAIK. Do you think Public Domain is worth adding to the tagger app as well?
Pinging @patrickvonplaten to review | {
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"Hey @anton-l,\r\n\r\nThanks a lot for the very clean integration!\r\n\r\n1) I think we should now start having \"automatic-speech-recognition\" as a label in the dataset tagger (@yjernite is it easy to add?). But we can surely add this dataset with the tag you've added and then later change the label to `asr` \r\n... |
https://api.github.com/repos/huggingface/datasets/issues/2691 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2691/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2691/comments | https://api.github.com/repos/huggingface/datasets/issues/2691/events | https://github.com/huggingface/datasets/issues/2691 | 949,758,379 | MDU6SXNzdWU5NDk3NTgzNzk= | 2,691 | xtreme / pan-x cannot be downloaded | [
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] | closed | false | null | 5 | 2021-07-21T14:18:05Z | 2021-07-26T09:34:22Z | 2021-07-26T09:34:22Z | null | ## Describe the bug
Dataset xtreme / pan-x cannot be loaded
Seems related to https://github.com/huggingface/datasets/pull/2326
## Steps to reproduce the bug
```python
dataset = load_dataset("xtreme", "PAN-X.fr")
```
## Expected results
Load the dataset
## Actual results
```
FileNotFoundError: Couldn't find file at https://www.dropbox.com/s/12h3qqog6q4bjve/panx_dataset.tar?dl=1
```
## Environment info
- `datasets` version: 1.9.0
- Platform: macOS-11.4-x86_64-i386-64bit
- Python version: 3.8.11
- PyArrow version: 4.0.1
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"Hi @severo, thanks for reporting.\r\n\r\nHowever I have not been able to reproduce this issue. Could you please confirm if the problem persists for you?\r\n\r\nMaybe Dropbox (where the data source is hosted) was temporarily unavailable when you tried.",
"Hmmm, the file (https://www.dropbox.com/s/dl/12h3qqog6q4bj... |
https://api.github.com/repos/huggingface/datasets/issues/4832 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4832/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4832/comments | https://api.github.com/repos/huggingface/datasets/issues/4832/events | https://github.com/huggingface/datasets/pull/4832 | 1,336,727,389 | PR_kwDODunzps49EQav | 4,832 | Fix tags in dataset cards | [] | closed | false | null | 2 | 2022-08-12T04:11:23Z | 2022-08-12T04:41:55Z | 2022-08-12T04:27:24Z | null | Fix wrong tags in dataset cards. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The non-passing tests are caused by other missing information in the dataset cards."
] |
https://api.github.com/repos/huggingface/datasets/issues/2173 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2173/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2173/comments | https://api.github.com/repos/huggingface/datasets/issues/2173/events | https://github.com/huggingface/datasets/pull/2173 | 851,359,284 | MDExOlB1bGxSZXF1ZXN0NjA5Nzk2NzI2 | 2,173 | Add OpenSLR dataset | [] | closed | false | null | 0 | 2021-04-06T12:08:34Z | 2021-04-12T16:54:46Z | 2021-04-12T16:54:46Z | null | OpenSLR (https://openslr.org/) is a site devoted to hosting speech and language resources, such as training corpora for speech recognition, and software related to speech recognition. There are around 80 speech datasets listed in OpenSLR, currently this PR includes only 9 speech datasets SLR41, SLR42, SLR43, SLR44, SLR63, SLR64, SLR65, SLR66 and SLR69 (Javanese, Khmer, Nepali and Sundanese, Malayalam, Marathi, Tamil, Telugu and Catalan). I can add other speech datasets gradually next time. | {
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https://api.github.com/repos/huggingface/datasets/issues/6031 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6031/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6031/comments | https://api.github.com/repos/huggingface/datasets/issues/6031/events | https://github.com/huggingface/datasets/issues/6031 | 1,804,183,858 | I_kwDODunzps5riaky | 6,031 | Argument type for map function changes when using `input_columns` for `IterableDataset` | [] | closed | false | null | 1 | 2023-07-14T05:11:14Z | 2023-07-14T14:44:15Z | 2023-07-14T14:44:15Z | null | ### Describe the bug
I wrote `tokenize(examples)` function as an argument for `map` function for `IterableDataset`.
It process dictionary type `examples` as a parameter.
It is used in `train_dataset = train_dataset.map(tokenize, batched=True)`
No error is raised.
And then, I found some unnecessary keys and values in `examples` so I added `input_columns` argument to `map` function to select keys and values.
It gives me an error saying
```
TypeError: tokenize() takes 1 positional argument but 3 were given.
```
The code below matters.
https://github.com/huggingface/datasets/blob/406b2212263c0d33f267e35b917f410ff6b3bc00/src/datasets/iterable_dataset.py#L687
For example, `inputs = {"a":1, "b":2, "c":3}`.
If `self.input_coluns` is `None`,
`inputs` is a dictionary type variable and `function_args` becomes a `list` of a single `dict` variable.
`function_args` becomes `[{"a":1, "b":2, "c":3}]`
Otherwise, lets say `self.input_columns = ["a", "c"]`
`[inputs[col] for col in self.input_columns]` results in `[1, 3]`.
I think it should be `[{"a":1, "c":3}]`.
I want to ask if the resulting format is intended.
Maybe I can modify `tokenize()` to have 2 parameters in this case instead of having 1 dictionary.
But this is confusing to me.
Or it should be fixed as `[{col:inputs[col] for col in self.input_columns}]`
### Steps to reproduce the bug
Run `map` function of `IterableDataset` with `input_columns` argument.
### Expected behavior
`function_args` looks better to have same format.
I think it should be `[{"a":1, "c":3}]`.
### Environment info
dataset version: 2.12
python: 3.8 | {
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"Yes, this is intended."
] |
https://api.github.com/repos/huggingface/datasets/issues/5789 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5789/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5789/comments | https://api.github.com/repos/huggingface/datasets/issues/5789/events | https://github.com/huggingface/datasets/issues/5789 | 1,682,611,179 | I_kwDODunzps5kSpvr | 5,789 | Support streaming datasets that use jsonlines | [
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] | open | false | null | 0 | 2023-04-25T07:40:02Z | 2023-04-25T07:40:03Z | null | null | Extend support for streaming datasets that use `jsonlines.open`.
Currently, if `jsonlines` is installed, `datasets` raises a `FileNotFoundError`:
```
FileNotFoundError: [Errno 2] No such file or directory: 'https://...'
```
See:
- https://huggingface.co/datasets/masakhane/afriqa/discussions/1 | {
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https://api.github.com/repos/huggingface/datasets/issues/5700 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5700/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5700/comments | https://api.github.com/repos/huggingface/datasets/issues/5700/events | https://github.com/huggingface/datasets/pull/5700 | 1,652,527,530 | PR_kwDODunzps5Ng6g_ | 5,700 | fix: fix wrong modification of the 'cache_file_name' -related paramet… | [] | open | false | null | 7 | 2023-04-03T18:05:26Z | 2023-04-06T17:17:27Z | null | null | …ers values in 'train_test_split' + fix bad interaction between 'keep_in_memory' and 'cache_file_name' -related parameters (#5699) | {
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"Have you tried to set the cache file names if `keep_in_memory`is True ?\r\n\r\n```diff\r\n- if self.cache_files:\r\n+ if self.cache_files and not keep_in_memory:\r\n```\r\n\r\nThis way it doesn't change the indice cache arguments and leave them as `None`",
"@lhoestq \r\nRegarding what you suggest:\r\nThe thing i... |
https://api.github.com/repos/huggingface/datasets/issues/3733 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3733/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3733/comments | https://api.github.com/repos/huggingface/datasets/issues/3733/events | https://github.com/huggingface/datasets/issues/3733 | 1,140,011,378 | I_kwDODunzps5D8zFy | 3,733 | Bugs in NewsQA dataset | [
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] | closed | false | null | 0 | 2022-02-16T13:17:37Z | 2022-02-17T07:54:25Z | 2022-02-17T07:54:25Z | null | ## Describe the bug
NewsQA dataset has the following bugs:
- the field `validated_answers` is an exact copy of the field `answers` but with the addition of `'count': [0]` to each dict
- the field `badQuestion` does not appear in `answers` nor `validated_answers`
## Steps to reproduce the bug
By inspecting the dataset script we can see that:
- the parsing of `validated_answers` is a copy-paste of the one for `answers`
- the `badQuestion` field is ignored in the parsing of both `answers` and `validated_answers`
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https://api.github.com/repos/huggingface/datasets/issues/6065 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6065/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6065/comments | https://api.github.com/repos/huggingface/datasets/issues/6065/events | https://github.com/huggingface/datasets/pull/6065 | 1,819,334,932 | PR_kwDODunzps5WR8jI | 6,065 | Add column type guessing from map return function | [] | closed | false | null | 5 | 2023-07-25T00:34:17Z | 2023-07-26T15:13:45Z | 2023-07-26T15:13:44Z | null | As discussed [here](https://github.com/huggingface/datasets/issues/5965), there are some cases where datasets is unable to automatically promote columns during mapping. The fix is to explicitly provide a `features` definition so pyarrow can configure itself with the right column types from the outset.
This PR provides an alternative approach, which is functionally equivalent to specifying features but a bit cleaner within a larger mapping pipeline. It allows clients to typehint the return variable coming from the mapper function - if we find one of these type annotations specified, and no explicit features have been passed in, we'll try to convert it into a Features map. If the map function runs and casting is unable to succeed, it will raise a DatasetTransformationNotAllowedError that indicates the typehint may be to blame. It works for batched and non-batched mapping functions.
Currently supported column types:
- builtins primitives: string, int, float, bool
- dictionaries, lists (nested and one-deep)
- Optional types and None-Unions (synonymous with optional types)
It's used like:
```python
class DatasetTyped(TypedDict):
texts: list[str]
def dataset_typed_map(batch) -> DatasetTyped:
return {"texts": [text.split() for text in batch["raw_text"]]}
dataset = {"raw_text": ["", "This is a test", "This is another test"]}
with Dataset.from_dict(dataset) as dset:
new_dataset = dset.map(
dataset_typed_map,
batched=True,
batch_size=1,
num_proc=1,
)
```
Open questions:
- Should logging indicate we have automatically guessed these types? Or proceed quietly until we hit an error (as is the current implementation). | {
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"Thanks for working on this. However, having thought about this issue a bit more, supporting this doesn't seem like a good idea - it's better to be explicit than implicit, according to the Zen of Python 🙂. Also, I don't think many users would use this, so this raises the question of whether this is something we wa... |
https://api.github.com/repos/huggingface/datasets/issues/794 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/794/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/794/comments | https://api.github.com/repos/huggingface/datasets/issues/794/events | https://github.com/huggingface/datasets/issues/794 | 735,158,725 | MDU6SXNzdWU3MzUxNTg3MjU= | 794 | self.options cannot be converted to a Python object for pickling | [
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] | closed | false | null | 1 | 2020-11-03T09:27:34Z | 2020-11-19T17:35:38Z | 2020-11-19T17:35:38Z | null | Hi,
Currently I am trying to load csv file with customized read_options. And the latest master seems broken if we pass the ReadOptions object.
Here is a code snippet
```python
from datasets import load_dataset
from pyarrow.csv import ReadOptions
load_dataset("csv", data_files=["out.csv"], read_options=ReadOptions(block_size=16*1024*1024))
```
error is `self.options cannot be converted to a Python object for pickling`
Would you mind to take a look? Thanks!
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-28-ab83fec2ded4> in <module>
----> 1 load_dataset("csv", data_files=["out.csv"], read_options=ReadOptions(block_size=16*1024*1024))
/tmp/datasets/src/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
602 hash=hash,
603 features=features,
--> 604 **config_kwargs,
605 )
606
/tmp/datasets/src/datasets/builder.py in __init__(self, cache_dir, name, hash, features, **config_kwargs)
162 name,
163 custom_features=features,
--> 164 **config_kwargs,
165 )
166
/tmp/datasets/src/datasets/builder.py in _create_builder_config(self, name, custom_features, **config_kwargs)
281 )
282 else:
--> 283 suffix = Hasher.hash(config_kwargs_to_add_to_suffix)
284
285 if builder_config.data_files is not None:
/tmp/datasets/src/datasets/fingerprint.py in hash(cls, value)
51 return cls.dispatch[type(value)](cls, value)
52 else:
---> 53 return cls.hash_default(value)
54
55 def update(self, value):
/tmp/datasets/src/datasets/fingerprint.py in hash_default(cls, value)
44 @classmethod
45 def hash_default(cls, value):
---> 46 return cls.hash_bytes(dumps(value))
47
48 @classmethod
/tmp/datasets/src/datasets/utils/py_utils.py in dumps(obj)
365 file = StringIO()
366 with _no_cache_fields(obj):
--> 367 dump(obj, file)
368 return file.getvalue()
369
/tmp/datasets/src/datasets/utils/py_utils.py in dump(obj, file)
337 def dump(obj, file):
338 """pickle an object to a file"""
--> 339 Pickler(file, recurse=True).dump(obj)
340 return
341
~/.local/lib/python3.6/site-packages/dill/_dill.py in dump(self, obj)
444 raise PicklingError(msg)
445 else:
--> 446 StockPickler.dump(self, obj)
447 stack.clear() # clear record of 'recursion-sensitive' pickled objects
448 return
/usr/lib/python3.6/pickle.py in dump(self, obj)
407 if self.proto >= 4:
408 self.framer.start_framing()
--> 409 self.save(obj)
410 self.write(STOP)
411 self.framer.end_framing()
/usr/lib/python3.6/pickle.py in save(self, obj, save_persistent_id)
474 f = self.dispatch.get(t)
475 if f is not None:
--> 476 f(self, obj) # Call unbound method with explicit self
477 return
478
~/.local/lib/python3.6/site-packages/dill/_dill.py in save_module_dict(pickler, obj)
931 # we only care about session the first pass thru
932 pickler._session = False
--> 933 StockPickler.save_dict(pickler, obj)
934 log.info("# D2")
935 return
/usr/lib/python3.6/pickle.py in save_dict(self, obj)
819
820 self.memoize(obj)
--> 821 self._batch_setitems(obj.items())
822
823 dispatch[dict] = save_dict
/usr/lib/python3.6/pickle.py in _batch_setitems(self, items)
850 k, v = tmp[0]
851 save(k)
--> 852 save(v)
853 write(SETITEM)
854 # else tmp is empty, and we're done
/usr/lib/python3.6/pickle.py in save(self, obj, save_persistent_id)
494 reduce = getattr(obj, "__reduce_ex__", None)
495 if reduce is not None:
--> 496 rv = reduce(self.proto)
497 else:
498 reduce = getattr(obj, "__reduce__", None)
~/.local/lib/python3.6/site-packages/pyarrow/_csv.cpython-36m-x86_64-linux-gnu.so in pyarrow._csv.ReadOptions.__reduce_cython__()
TypeError: self.options cannot be converted to a Python object for pickling
``` | {
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"Hi ! Thanks for reporting that's a bug on master indeed.\r\nWe'll fix that soon"
] |
https://api.github.com/repos/huggingface/datasets/issues/4030 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4030/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4030/comments | https://api.github.com/repos/huggingface/datasets/issues/4030/events | https://github.com/huggingface/datasets/pull/4030 | 1,182,157,056 | PR_kwDODunzps41FxjE | 4,030 | Use a constant for the articles regex in SQuAD v2 | [] | closed | false | null | 1 | 2022-03-26T23:06:30Z | 2022-04-12T16:30:45Z | 2022-04-12T11:00:24Z | null | The main reason for doing this is to be able to change the articles list if using another language, for example. It's not the most elegant solution but at least it makes the metric more extensible with no drawbacks.
BTW, what could be the best way to make this more generic (i.e., SQuAD in other languages)? Maybe receive a regex as an optional param, with the current value as the default? Similarly for SQuAD v1 (can't they re-use code?). | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/4101 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4101/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4101/comments | https://api.github.com/repos/huggingface/datasets/issues/4101/events | https://github.com/huggingface/datasets/issues/4101 | 1,193,399,204 | I_kwDODunzps5HIdOk | 4,101 | How can I download only the train and test split for full numbers using load_dataset()? | [
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] | open | false | null | 1 | 2022-04-05T16:00:15Z | 2022-04-06T13:09:01Z | null | null | How can I download only the train and test split for full numbers using load_dataset()?
I do not need the extra split and it will take 40 mins just to download in Colab. I have very short time in hand. Please help. | {
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"Hi! Can you please specify the full name of the dataset? IIRC `full_numbers` is one of the configs of the `svhn` dataset, and its generation is slow due to data being stored in binary Matlab files. Even if you specify a specific split, `datasets` downloads all of them, but we plan to fix that soon and only downloa... |
https://api.github.com/repos/huggingface/datasets/issues/2346 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2346/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2346/comments | https://api.github.com/repos/huggingface/datasets/issues/2346/events | https://github.com/huggingface/datasets/pull/2346 | 886,632,114 | MDExOlB1bGxSZXF1ZXN0NjM5OTAzMjk3 | 2,346 | Add Qasper Dataset | [] | closed | false | null | 1 | 2021-05-11T09:25:44Z | 2021-05-18T12:28:28Z | 2021-05-18T12:28:28Z | null | [Question Answering on Scientific Research Papers](https://allenai.org/project/qasper/home)
Doing NLP on NLP papers to do NLP ♻️ I had to add it~
- [x] Add README (just gotta fill out some more )
- [x] Dataloader code
- [x] Make dummy dataset
- [x] generate dataset infos
- [x] Tests
| {
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"I saw that the README [template](https://github.com/huggingface/datasets/blob/master/templates/README.md) changed while I was working on this 😅 Some TOC titles may be different but I filled it to the best of my knowledge & readme quality check passes now.\r\nready for review @lhoestq "
] |
https://api.github.com/repos/huggingface/datasets/issues/4064 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4064/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4064/comments | https://api.github.com/repos/huggingface/datasets/issues/4064/events | https://github.com/huggingface/datasets/pull/4064 | 1,186,650,321 | PR_kwDODunzps41UqXS | 4,064 | Contributing MedMCQA dataset | [] | closed | false | null | 15 | 2022-03-30T15:42:47Z | 2022-05-06T09:40:40Z | 2022-05-06T08:42:56Z | null | Adding MedMCQA dataset ( https://paperswithcode.com/dataset/medmcqa )
**Name**: MedMCQA
**Description**: MedMCQA is a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions.
MedMCQA has more than 194k high-quality AIIMS & NEET PG entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average token length of 12.77 and high topical diversity.
The dataset contains questions about the following topics: Anesthesia, Anatomy, Biochemistry, Dental, ENT, Forensic Medicine (FM), Obstetrics and Gynecology (O&G), Medicine, Microbiology, Ophthalmology, Orthopedics Pathology, Pediatrics, Pharmacology, Physiology,
Psychiatry, Radiology Skin, Preventive & Social Medicine (PSM), and Surgery
**Code**: https://github.com/medmcqa/medmcqa
All files are at place :
**a dataset script** : medmcqa.py
**a dataset card with tags and information** : README.md.
**a metadata file** : dataset_infos.json
**a dummy-data file** : Please help to generate this file, I was facing
` raise JSONDecodeError("Extra data", s, end)` error | {
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"@lhoestq Could you please take a look?\r\nThank you!!",
"Hi, thank you for the modifications and suggestions. Please check the changes.",
"Can you run `make style` to fix the code formatting please ?\r\n\r\nOh and was wrong with the dummy_data.zip file, it must actually be placed at `datasets/medmcqa/dummy/1.1... |
https://api.github.com/repos/huggingface/datasets/issues/5643 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5643/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5643/comments | https://api.github.com/repos/huggingface/datasets/issues/5643/events | https://github.com/huggingface/datasets/pull/5643 | 1,626,160,220 | PR_kwDODunzps5MI9zO | 5,643 | Support PyArrow arrays as column values in `from_dict` | [] | closed | false | null | 3 | 2023-03-15T19:32:40Z | 2023-03-16T17:23:06Z | 2023-03-16T17:15:40Z | null | For consistency with `pa.Table.from_pydict`, which supports both Python lists and PyArrow arrays as column values.
"Fixes" https://discuss.huggingface.co/t/pyarrow-lib-floatarray-did-not-recognize-python-value-type-when-inferring-an-arrow-data-type/33417 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/5637 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5637/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5637/comments | https://api.github.com/repos/huggingface/datasets/issues/5637/events | https://github.com/huggingface/datasets/issues/5637 | 1,625,295,691 | I_kwDODunzps5g4AtL | 5,637 | IterableDataset with_format does not support 'device' keyword for jax | [] | open | false | null | 2 | 2023-03-15T11:04:12Z | 2023-03-16T18:30:59Z | null | null | ### Describe the bug
As seen here: https://huggingface.co/docs/datasets/use_with_jax dataset.with_format() supports the keyword 'device', to put data on a specific device when loaded as jax. However, when called on an IterableDataset, I got the error `TypeError: with_format() got an unexpected keyword argument 'device'`
Looking over the code, it seems IterableDataset support only pytorch and no support for jax device keyword?
https://github.com/huggingface/datasets/blob/fc5c84f36684343bff3e424cb0fd1ac5ecdd66da/src/datasets/iterable_dataset.py#L1029
### Steps to reproduce the bug
1. Load an IterableDataset (tested in streaming mode)
2. Call with_format('jax',device=device)
### Expected behavior
I expect to call `with_format('jax', device=device)` as per [documentation](https://huggingface.co/docs/datasets/use_with_jax) without error
### Environment info
Tested with installing newest (dev) and also pip release (2.10.1).
- `datasets` version: 2.10.2.dev0
- Platform: Linux-5.15.89+-x86_64-with-debian-bullseye-sid
- Python version: 3.7.12
- Huggingface_hub version: 0.12.1
- PyArrow version: 11.0.0
- Pandas version: 1.3.5
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"Hi! Yes, only `torch` is currently supported. Unlike `Dataset`, `IterableDataset` is not PyArrow-backed, so we cannot simply call `to_numpy` on the underlying subtables to format them numerically. Instead, we must manually convert examples to (numeric) arrays while preserving consistency with `Dataset`, which is n... |
https://api.github.com/repos/huggingface/datasets/issues/1885 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1885/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1885/comments | https://api.github.com/repos/huggingface/datasets/issues/1885/events | https://github.com/huggingface/datasets/pull/1885 | 808,881,501 | MDExOlB1bGxSZXF1ZXN0NTczODQyNzcz | 1,885 | add missing info on how to add large files | [] | closed | false | null | 0 | 2021-02-15T23:46:39Z | 2021-02-16T16:22:19Z | 2021-02-16T11:44:12Z | null | Thanks to @lhoestq's instructions I was able to add data files to a custom dataset repo. This PR is attempting to tell others how to do the same if they need to.
@lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/3415 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3415/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3415/comments | https://api.github.com/repos/huggingface/datasets/issues/3415/events | https://github.com/huggingface/datasets/issues/3415 | 1,076,472,534 | I_kwDODunzps5AKarW | 3,415 | Non-deterministic tests: CI tests randomly fail | [
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}
] | closed | false | null | 2 | 2021-12-10T06:08:59Z | 2022-03-31T16:38:51Z | 2022-03-31T16:38:51Z | null | ## Describe the bug
Some CI tests fail randomly.
1. In https://github.com/huggingface/datasets/pull/3375/commits/c10275fe36085601cb7bdb9daee9a8f1fc734f48, there were 3 failing tests, only on Linux:
```
=========================== short test summary info ============================
FAILED tests/test_streaming_download_manager.py::test_streaming_dl_manager_get_extraction_protocol[https://drive.google.com/uc?export=download&id=1k92sUfpHxKq8PXWRr7Y5aNHXwOCNUmqh-zip]
FAILED tests/test_streaming_download_manager.py::test_streaming_gg_drive - Fi...
FAILED tests/test_streaming_download_manager.py::test_streaming_gg_drive_zipped
= 3 failed, 3553 passed, 2950 skipped, 2 xfailed, 1 xpassed, 125 warnings in 192.79s (0:03:12) =
```
2. After re-running the CI (without any change in the code) in https://github.com/huggingface/datasets/pull/3375/commits/57bfe1f342cd3c59d2510b992d5f06a0761eb147, there was only 1 failing test (one on Linux and a different one on Windows):
- On Linux:
```
=========================== short test summary info ============================
FAILED tests/test_streaming_download_manager.py::test_streaming_gg_drive_zipped
= 1 failed, 3555 passed, 2950 skipped, 2 xfailed, 1 xpassed, 125 warnings in 199.76s (0:03:19) =
```
- On Windows:
```
=========================== short test summary info ===========================
FAILED tests/test_load.py::test_load_dataset_builder_for_community_dataset_without_script
= 1 failed, 3551 passed, 2954 skipped, 2 xfailed, 1 xpassed, 121 warnings in 478.58s (0:07:58) =
```
The test `tests/test_streaming_download_manager.py::test_streaming_gg_drive_zipped` passes locally.
3. After re-running again the CI (without any change in the code) in https://github.com/huggingface/datasets/pull/3375/commits/39f32f2119cf91b86867216bb5c356c586503c6a, ALL the tests passed.
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"I think it might come from two different issues:\r\n1. Google Drive is an unreliable host, mainly because of quota limitations\r\n2. the staging environment can sometimes raise some errors\r\n\r\nFor Google Drive tests we could set up some retries with backup URLs if necessary I guess.\r\nFor staging on the other ... |
https://api.github.com/repos/huggingface/datasets/issues/4490 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4490/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4490/comments | https://api.github.com/repos/huggingface/datasets/issues/4490/events | https://github.com/huggingface/datasets/issues/4490 | 1,270,719,074 | I_kwDODunzps5LvaJi | 4,490 | Use `torch.nested_tensor` for arrays of varying length in torch formatter | [
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] | open | false | null | 2 | 2022-06-14T12:19:40Z | 2023-07-07T13:02:58Z | null | null | Use `torch.nested_tensor` for arrays of varying length in `TorchFormatter`.
The PyTorch API of nested tensors is in the prototype stage, so wait for it to become more mature. | {
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"What's the current behavior?",
"Currently, we return a list of Torch tensors if their shapes don't match. If they do, we consolidate them into a single Torch tensor."
] |
https://api.github.com/repos/huggingface/datasets/issues/3984 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3984/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3984/comments | https://api.github.com/repos/huggingface/datasets/issues/3984/events | https://github.com/huggingface/datasets/issues/3984 | 1,175,822,117 | I_kwDODunzps5GFZ8l | 3,984 | Local and automatic tests fail | [
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] | closed | false | null | 1 | 2022-03-21T19:07:37Z | 2023-07-25T15:18:40Z | 2023-07-25T15:18:40Z | null | ## Describe the bug
Running the tests from CircleCI on a PR or locally fails, even with no changes. Tests seem to fail on `test_metric_common.py`
## Steps to reproduce the bug
```shell
git clone https://huggingface/datasets.git
cd datasets
```
```python
python -m pip install -e .
pytest
```
## Expected results
All tests passing
## Actual results
```
tests/test_metric_common.py:91:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../.pyenv/versions/3.8.5/lib/python3.8/doctest.py:1336: in __run
exec(compile(example.source, filename, "single",
<doctest datasets_modules.metrics.ter.c0cfb5adedac7eb15ffa47bba6a70fabd80f3eb906ee508abf5e1906285d1155.ter.Ter[3]>:1: in <module>
???
../datasets/src/datasets/metric.py:430: in compute
output = self._compute(**inputs, **compute_kwargs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = Metric(name: "ter", features: {'predictions': Value(dtype='string', id='sequence'), 'references': Sequence(feature=Val...ences=references)
>>> print(results)
{'score': 0.0, 'num_edits': 0, 'ref_length': 6.5}
""", stored examples: 0)
predictions = ['hello there general kenobi', 'foo bar foobar']
references = [['hello there general kenobi', 'hello there !'], ['foo bar foobar', 'foo bar foobar']]
normalized = False, no_punct = False, asian_support = False, case_sensitive = False
def _compute(
self,
predictions,
references,
normalized: bool = False,
no_punct: bool = False,
asian_support: bool = False,
case_sensitive: bool = False,
):
references_per_prediction = len(references[0])
if any(len(refs) != references_per_prediction for refs in references):
raise ValueError("Sacrebleu requires the same number of references for each prediction")
transformed_references = [[refs[i] for refs in references] for i in range(references_per_prediction)]
> sb_ter = TER(normalized, no_punct, asian_support, case_sensitive)
E TypeError: __init__() takes 2 positional arguments but 5 were given
/tmp/pytest-of-markussagen/pytest-1/cache/modules/datasets_modules/metrics/ter/c0cfb5adedac7eb15ffa47bba6a70fabd80f3eb906ee508abf5e1906285d1155/ter.py:130: TypeError
------------------------------ Captured stdout call -------------------------------
Trying:
predictions = ["hello there general kenobi", "foo bar foobar"]
Expecting nothing
ok
Trying:
references = [["hello there general kenobi", "hello there !"], ["foo bar foobar", "foo bar foobar"]]
Expecting nothing
ok
Trying:
ter = datasets.load_metric("ter")
Expecting nothing
ok
Trying:
results = ter.compute(predictions=predictions, references=references)
Expecting nothing
================================ warnings summary =================================
../.pyenv/versions/3.8.5/envs/huggingface/lib/python3.8/site-packages/hdfs/config.py:15
/home/markussagen/.pyenv/versions/3.8.5/envs/huggingface/lib/python3.8/site-packages/hdfs/config.py:15: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
from imp import load_source
../datasets/src/datasets/commands/test.py:35
/home/markussagen/datasets/src/datasets/commands/test.py:35: PytestCollectionWarning: cannot collect test class 'TestCommand' because it has a __init__ constructor (from: tests/commands/test_test.py)
class TestCommand(BaseDatasetsCLICommand):
tests/commands/test_test.py:33
/home/markussagen/mydataset/tests/commands/test_test.py:33: PytestCollectionWarning: cannot collect test class 'TestCommandArgs' because it has a __new__ constructor (from: tests/commands/test_test.py)
class TestCommandArgs:
tests/test_arrow_dataset.py: 760 warnings
tests/test_formatting.py: 60 warnings
tests/test_search.py: 31 warnings
tests/features/test_array_xd.py: 117 warnings
/home/markussagen/datasets/src/datasets/formatting/formatting.py:197: DeprecationWarning: `np.object` is a deprecated alias for the builtin `object`. To silence this warning, use `object` by itself. Doing this will not modify any behavior and is safe.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
(isinstance(x, np.ndarray) and (x.dtype == np.object or x.shape != array[0].shape))
tests/test_arrow_dataset.py: 154 warnings
tests/features/test_array_xd.py: 1 warning
/home/markussagen/datasets/src/datasets/formatting/formatting.py:201: DeprecationWarning: `np.object` is a deprecated alias for the builtin `object`. To silence this warning, use `object` by itself. Doing this will not modify any behavior and is safe.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
return np.array(array, copy=False, **{**self.np_array_kwargs, "dtype": np.object})
tests/test_arrow_dataset.py: 60 warnings
/home/markussagen/datasets/src/datasets/arrow_dataset.py:3105: DeprecationWarning: `np.str` is a deprecated alias for the builtin `str`. To silence this warning, use `str` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.str_` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
elif np.issubdtype(values.dtype, np.str):
tests/test_arrow_dataset.py: 138 warnings
tests/test_formatting.py: 21 warnings
/home/markussagen/datasets/src/datasets/formatting/tf_formatter.py:69: DeprecationWarning: `np.object` is a deprecated alias for the builtin `object`. To silence this warning, use `object` by itself. Doing this will not modify any behavior and is safe.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
data_struct.dtype == np.object
tests/test_arrow_dataset.py: 240 warnings
tests/test_formatting.py: 20 warnings
/home/markussagen/datasets/src/datasets/formatting/torch_formatter.py:49: DeprecationWarning: `np.object` is a deprecated alias for the builtin `object`. To silence this warning, use `object` by itself. Doing this will not modify any behavior and is safe.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
if data_struct.dtype == np.object: # pytorch tensors cannot be instantied from an array of objects
tests/test_arrow_dataset.py: 12 warnings
tests/test_search.py: 2 warnings
tests/features/test_array_xd.py: 6 warnings
tests/features/test_image.py: 4 warnings
/home/markussagen/datasets/src/datasets/features/features.py:1129: DeprecationWarning: `np.object` is a deprecated alias for the builtin `object`. To silence this warning, use `object` by itself. Doing this will not modify any behavior and is safe.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
[0] + [len(arr) for arr in l_arr], dtype=np.object
tests/test_dataset_common.py::LocalDatasetTest::test_builder_class_banking77
/tmp/pytest-of-markussagen/pytest-1/cache/modules/datasets_modules/datasets/banking77/aec0289529599d4572d76ab00c8944cb84f88410ad0c9e7da26189d31f62a55b/banking77.py:24: DeprecationWarning: invalid escape sequence \~
_CITATION = """\
tests/test_dataset_common.py::LocalDatasetTest::test_builder_class_universal_dependencies
/tmp/pytest-of-markussagen/pytest-1/cache/modules/datasets_modules/datasets/universal_dependencies/065e728dfe9a8371434a6e87132c2386a6eacab1a076d3a12aa417b994e6ef7d/universal_dependencies.py:6: DeprecationWarning: invalid escape sequence \=
_CITATION = """\
tests/test_filesystem.py: 105 warnings
/home/markussagen/.pyenv/versions/3.8.5/envs/huggingface/lib/python3.8/site-packages/responses/__init__.py:398: DeprecationWarning: stream argument is deprecated. Use stream parameter in request directly
warn(
tests/test_formatting.py::FormatterTest::test_jax_formatter
tests/test_formatting.py::FormatterTest::test_jax_formatter
tests/test_formatting.py::FormatterTest::test_jax_formatter
tests/test_formatting.py::FormatterTest::test_jax_formatter
tests/test_formatting.py::FormatterTest::test_jax_formatter_np_array_kwargs
tests/test_formatting.py::FormatterTest::test_jax_formatter_np_array_kwargs
tests/test_formatting.py::FormatterTest::test_jax_formatter_np_array_kwargs
tests/test_formatting.py::FormatterTest::test_jax_formatter_np_array_kwargs
/home/markussagen/datasets/src/datasets/formatting/jax_formatter.py:57: DeprecationWarning: `np.object` is a deprecated alias for the builtin `object`. To silence this warning, use `object` by itself. Doing this will not modify any behavior and is safe.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
if data_struct.dtype == np.object: # jax arrays cannot be instantied from an array of objects
tests/test_formatting.py::FormatterTest::test_jax_formatter
tests/test_formatting.py::FormatterTest::test_jax_formatter
tests/test_formatting.py::FormatterTest::test_jax_formatter
/home/markussagen/.pyenv/versions/3.8.5/envs/huggingface/lib/python3.8/site-packages/jax/_src/numpy/lax_numpy.py:3567: UserWarning: Explicitly requested dtype <class 'jax._src.numpy.lax_numpy.int64'> requested in array is not available, and will be truncated to dtype int32. To enable more dtypes, set the jax_enable_x64 configuration option or the JAX_ENABLE_X64 shell environment variable. See https://github.com/google/jax#current-gotchas for more.
lax._check_user_dtype_supported(dtype, "array")
tests/test_metric_common.py::LocalMetricTest::test_load_metric_frugalscore
/home/markussagen/.pyenv/versions/3.8.5/envs/huggingface/lib/python3.8/site-packages/apscheduler/util.py:95: PytzUsageWarning: The zone attribute is specific to pytz's interface; please migrate to a new time zone provider. For more details on how to do so, see https://pytz-deprecation-shim.readthedocs.io/en/latest/migration.html
if obj.zone == 'local':
tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_to_hub_custom_features
_audio
/home/markussagen/.pyenv/versions/3.8.5/envs/huggingface/lib/python3.8/site-packages/librosa/core/constantq.py:1059: DeprecationWarning: `np.complex` is a deprecated alias for the builtin `complex`. To silence this warning, use `complex` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.complex128` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
dtype=np.complex,
tests/features/test_array_xd.py::test_array_xd_with_none
/home/markussagen/mydataset/tests/features/test_array_xd.py:338: DeprecationWarning: `np.object` is a deprecated alias for the builtin `object`. To silence this warning, use `object` by itself. Doing this will not modify any behavior and is safe.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
assert isinstance(arr, np.ndarray) and arr.dtype == np.object and arr.shape == (3,)
-- Docs: https://docs.pytest.org/en/stable/warnings.html
============================= short test summary info =============================
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_bleurt - I...
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_chrf - Att...
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_code_eval
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_comet - Im...
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_competition_math
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_coval - Im...
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_frugalscore
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_perplexity
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_ter - Type...
```
## Environment info
- `datasets` version: 2.0.1.dev0
- Platform: Linux-5.16.11-76051611-generic-x86_64-with-glibc2.33
- Python version: 3.8.5
- PyArrow version: 5.0.0
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"Hi ! To be able to run the tests, you need to install all the test dependencies and additional ones with\r\n```\r\npip install -e .[tests]\r\npip install -r additional-tests-requirements.txt --no-deps\r\n```\r\n\r\nIn particular, you probably need to `sacrebleu`. It looks like it wasn't able to instantiate `sacreb... |
https://api.github.com/repos/huggingface/datasets/issues/2525 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2525/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2525/comments | https://api.github.com/repos/huggingface/datasets/issues/2525/events | https://github.com/huggingface/datasets/pull/2525 | 925,896,358 | MDExOlB1bGxSZXF1ZXN0Njc0Mjc5MTgy | 2,525 | Use scikit-learn package rather than sklearn in setup.py | [] | closed | false | null | 0 | 2021-06-21T07:04:25Z | 2021-06-21T10:01:13Z | 2021-06-21T08:57:33Z | null | The sklearn package is an historical thing and should probably not be used by anyone, see https://github.com/scikit-learn/scikit-learn/issues/8215#issuecomment-344679114 for some caveats.
Note: this affects only TESTS_REQUIRE so I guess only developers not end users. | {
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https://api.github.com/repos/huggingface/datasets/issues/4467 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4467/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4467/comments | https://api.github.com/repos/huggingface/datasets/issues/4467/events | https://github.com/huggingface/datasets/issues/4467 | 1,266,218,358 | I_kwDODunzps5LePV2 | 4,467 | Transcript string 'null' converted to [None] by load_dataset() | [
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] | closed | false | null | 3 | 2022-06-09T14:26:00Z | 2023-07-04T02:18:39Z | 2022-06-09T16:29:02Z | null | ## Issue
I am training a luxembourgish speech-recognition model in Colab with a custom dataset, including a dictionary of luxembourgish words, for example the speaken numbers 0 to 9. When preparing the dataset with the script
`ds_train1 = mydataset.map(prepare_dataset)`
the following error was issued:
```
ValueError Traceback (most recent call last)
<ipython-input-69-1e8f2b37f5bc> in <module>()
----> 1 ds_train = mydataset_train.map(prepare_dataset)
11 frames
/usr/local/lib/python3.7/dist-packages/transformers/tokenization_utils_base.py in __call__(self, text, text_pair, add_special_tokens, padding, truncation, max_length, stride, is_split_into_words, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)
2450 if not _is_valid_text_input(text):
2451 raise ValueError(
-> 2452 "text input must of type str (single example), List[str] (batch or single pretokenized example) "
2453 "or List[List[str]] (batch of pretokenized examples)."
2454 )
ValueError: text input must of type str (single example), List[str] (batch or single pretokenized example) or List[List[str]] (batch of pretokenized examples).
```
Debugging this problem was not easy, all transcriptions in the dataset are correct strings. Finally I discovered that the transcription string 'null' is interpreted as [None] by the `load_dataset()` script. By deleting this row in the dataset the training worked fine.
## Expected result:
transcription 'null' interpreted as 'str' instead of 'None'.
## Reproduction
Here is the code to reproduce the error with a one-row-dataset.
```
with open("null-test.csv") as f:
reader = csv.reader(f)
for row in reader:
print(row)
```
['wav_filename', 'wav_filesize', 'transcript']
['wavs/female/NULL1.wav', '17530', 'null']
```
dataset = load_dataset('csv', data_files={'train': 'null-test.csv'})
```
Using custom data configuration default-81ac0c0e27af3514
Downloading and preparing dataset csv/default to /root/.cache/huggingface/datasets/csv/default-81ac0c0e27af3514/0.0.0/433e0ccc46f9880962cc2b12065189766fbb2bee57a221866138fb9203c83519...
Downloading data files: 100%
1/1 [00:00<00:00, 29.55it/s]
Extracting data files: 100%
1/1 [00:00<00:00, 23.66it/s]
Dataset csv downloaded and prepared to /root/.cache/huggingface/datasets/csv/default-81ac0c0e27af3514/0.0.0/433e0ccc46f9880962cc2b12065189766fbb2bee57a221866138fb9203c83519. Subsequent calls will reuse this data.
100%
1/1 [00:00<00:00, 25.84it/s]
```
print(dataset['train']['transcript'])
```
[None]
## Environment info
```
!pip install datasets==2.2.2
!pip install transformers==4.19.2
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/4467/timeline | null | completed | null | null | false | [
"Hi @mbarnig, thanks for reporting.\r\n\r\nPlease note that is an expected behavior by `pandas` (we use the `pandas` library to parse CSV files): https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html\r\n```\r\nBy default the following values are interpreted as NaN: \r\n‘’, ‘#N/A’, ‘#N/A N/A’, ‘#NA’, ‘-1... |
https://api.github.com/repos/huggingface/datasets/issues/4745 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4745/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4745/comments | https://api.github.com/repos/huggingface/datasets/issues/4745/events | https://github.com/huggingface/datasets/issues/4745 | 1,318,016,655 | I_kwDODunzps5Oj1aP | 4,745 | Allow `list_datasets` to include private datasets | [
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] | closed | false | null | 4 | 2022-07-26T10:16:08Z | 2023-07-25T15:01:49Z | 2023-07-25T15:01:49Z | null | I am working with a large collection of private datasets, it would be convenient for me to be able to list them.
I would envision extending the convention of using `use_auth_token` keyword argument to `list_datasets` function, then calling:
```
list_datasets(use_auth_token="my_token")
```
would return the list of all datasets I have permissions to view, including private ones. The only current alternative I see is to use the hub website to manually obtain the list of dataset names - this is in the context of BigScience where respective private spaces contain hundreds of datasets, so not very convenient to list manually. | {
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} | https://api.github.com/repos/huggingface/datasets/issues/4745/timeline | null | completed | null | null | false | [
"Thanks for opening this issue :)\r\n\r\nIf it can help, I think you can already use `huggingface_hub` to achieve this:\r\n```python\r\n>>> from huggingface_hub import HfApi\r\n>>> [ds_info.id for ds_info in HfApi().list_datasets(use_auth_token=token) if ds_info.private]\r\n['bigscience/xxxx', 'bigscience-catalogue... |
https://api.github.com/repos/huggingface/datasets/issues/5008 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5008/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5008/comments | https://api.github.com/repos/huggingface/datasets/issues/5008/events | https://github.com/huggingface/datasets/pull/5008 | 1,381,090,903 | PR_kwDODunzps4_XAc5 | 5,008 | Re-apply input columns change | [] | closed | false | null | 1 | 2022-09-21T15:09:01Z | 2022-09-22T13:57:36Z | 2022-09-22T13:55:23Z | null | Fixes the `filter` + `input_columns` combination, which is used in the `transformers` examples for instance.
Revert #5006 (which in turn reverts #4971)
Fix https://github.com/huggingface/datasets/issues/4858 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/199 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/199/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/199/comments | https://api.github.com/repos/huggingface/datasets/issues/199/events | https://github.com/huggingface/datasets/pull/199 | 625,217,440 | MDExOlB1bGxSZXF1ZXN0NDIzNDc4ODIx | 199 | Fix GermEval 2014 dataset infos | [] | closed | false | null | 2 | 2020-05-26T21:41:44Z | 2020-05-26T21:50:24Z | 2020-05-26T21:50:24Z | null | Hi,
this PR just removes the `dataset_info.json` file and adds a newly generated `dataset_infos.json` file. | {
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"Hopefully. this also fixes the dataset view on https://huggingface.co/nlp/viewer/ :)",
"Oh good catch ! This should fix it indeed"
] |
https://api.github.com/repos/huggingface/datasets/issues/2103 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2103/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2103/comments | https://api.github.com/repos/huggingface/datasets/issues/2103/events | https://github.com/huggingface/datasets/issues/2103 | 838,946,916 | MDU6SXNzdWU4Mzg5NDY5MTY= | 2,103 | citation, homepage, and license fields of `dataset_info.json` are duplicated many times | [
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"default": true... | closed | false | null | 1 | 2021-03-23T17:18:09Z | 2021-04-06T14:39:59Z | 2021-04-06T14:39:59Z | null | This happens after a `map` operation when `num_proc` is set to `>1`. I tested this by cleaning up the json before running the `map` op on the dataset so it's unlikely it's coming from an earlier concatenation.
Example result:
```
"citation": "@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n url = {https://dumps.wikimedia.org}\n}\n\n@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {Wikimedia Downloads},\n
```
@lhoestq and I believe this is happening due to the fields being concatenated `num_proc` times. | {
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"Thanks for reporting :)\r\nMaybe we can concatenate fields only if they are different.\r\n\r\nCurrently this is done here:\r\n\r\nhttps://github.com/huggingface/nlp/blob/349ac4398a3bcae6356f14c5754483383a60e8a4/src/datasets/info.py#L180-L196\r\n\r\nThis can be a good first contribution to the library.\r\nPlease co... |
https://api.github.com/repos/huggingface/datasets/issues/4463 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4463/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4463/comments | https://api.github.com/repos/huggingface/datasets/issues/4463/events | https://github.com/huggingface/datasets/pull/4463 | 1,265,093,211 | PR_kwDODunzps45Vnzu | 4,463 | Use config_id to check split sizes instead of config name | [] | closed | false | null | 2 | 2022-06-08T17:45:24Z | 2022-06-09T08:15:43Z | 2022-06-09T08:06:37Z | null | Fix https://github.com/huggingface/datasets/issues/4462 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"closing in favor of https://github.com/huggingface/datasets/pull/4465"
] |
https://api.github.com/repos/huggingface/datasets/issues/190 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/190/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/190/comments | https://api.github.com/repos/huggingface/datasets/issues/190/events | https://github.com/huggingface/datasets/pull/190 | 624,124,600 | MDExOlB1bGxSZXF1ZXN0NDIyNjA4NzAw | 190 | add squad Spanish v1 and v2 | [] | closed | false | null | 5 | 2020-05-25T08:08:40Z | 2020-05-25T16:28:46Z | 2020-05-25T16:28:45Z | null | This PR add the Spanish Squad versions 1 and 2 datasets.
Fixes #164 | {
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"Nice ! :) \r\nCan we group them into one dataset with two versions, instead of having two datasets ?",
"Yes sure, I can use the version as config name",
"@lhoestq can you check? I grouped them",
"Awesome :) feel free to merge after fixing the test in the CI",
"@mariamabarham - feel free to merge when you'r... |
https://api.github.com/repos/huggingface/datasets/issues/2226 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2226/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2226/comments | https://api.github.com/repos/huggingface/datasets/issues/2226/events | https://github.com/huggingface/datasets/issues/2226 | 859,720,302 | MDU6SXNzdWU4NTk3MjAzMDI= | 2,226 | Batched map fails when removing all columns | [
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] | closed | false | null | 3 | 2021-04-16T11:17:01Z | 2022-10-05T17:32:15Z | 2022-10-05T17:32:15Z | null | Hi @lhoestq ,
I'm hijacking this issue, because I'm currently trying to do the approach you recommend:
> Currently the optimal setup for single-column computations is probably to do something like
>
> ```python
> result = dataset.map(f, input_columns="my_col", remove_columns=dataset.column_names)
> ```
Here is my code: (see edit, in which I added a simplified version
```
This is the error:
```bash
pyarrow.lib.ArrowInvalid: Column 1 named tokens expected length 8964 but got length 1000
```
I wonder why this error occurs, when I delete every column? Can you give me a hint?
### Edit:
I preprocessed my dataset before (using map with the features argument) and saved it to disk. May this be part of the error? I can iterate over the
complete dataset and print every sample before calling map. There seems to be no other problem with the dataset.
I tried to simplify the code that crashes:
```python
# works
log.debug(dataset.column_names)
log.debug(dataset)
for i, sample in enumerate(dataset):
log.debug(i, sample)
# crashes
counted_dataset = dataset.map(
lambda x: {"a": list(range(20))},
input_columns=column,
remove_columns=dataset.column_names,
load_from_cache_file=False,
num_proc=num_workers,
batched=True,
)
```
```
pyarrow.lib.ArrowInvalid: Column 1 named tokens expected length 20 but got length 1000
```
Edit2:
May this be a problem with a schema I set when preprocessing the dataset before? I tried to add the `features` argument to the function and then I get a new error:
```python
# crashes
counted_dataset = dataset.map(
lambda x: {"a": list(range(20))},
input_columns=column,
remove_columns=dataset.column_names,
load_from_cache_file=False,
num_proc=num_workers,
batched=True,
features=datasets.Features(
{
"a": datasets.Sequence(datasets.Value("int32"))
}
)
)
```
```
File "env/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1704, in _map_single
writer.write_batch(batch)
File "env/lib/python3.8/site-packages/datasets/arrow_writer.py", line 312, in write_batch
col_type = schema.field(col).type if schema is not None else None
File "pyarrow/types.pxi", line 1341, in pyarrow.lib.Schema.field
KeyError: 'Column tokens does not exist in schema'
```
_Originally posted by @villmow in https://github.com/huggingface/datasets/issues/2193#issuecomment-820230874_ | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2226/timeline | null | completed | null | null | false | [
"I found the problem. I called `set_format` on some columns before. This makes it crash. Here is a complete example to reproduce:\r\n\r\n```python\r\nfrom datasets import load_dataset\r\nsst = load_dataset(\"sst\")\r\nsst.set_format(\"torch\", columns=[\"label\"], output_all_columns=True)\r\nds = sst[\"train\"]\r\n... |
https://api.github.com/repos/huggingface/datasets/issues/965 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/965/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/965/comments | https://api.github.com/repos/huggingface/datasets/issues/965/events | https://github.com/huggingface/datasets/pull/965 | 754,553,169 | MDExOlB1bGxSZXF1ZXN0NTMwNDMzODQ2 | 965 | Add CLINC150 Dataset | [] | closed | false | null | 0 | 2020-12-01T16:43:00Z | 2020-12-01T16:51:16Z | 2020-12-01T16:49:15Z | null | Added CLINC150 Dataset. The link to the dataset can be found [here](https://github.com/clinc/oos-eval) and the paper can be found [here](https://www.aclweb.org/anthology/D19-1131.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | {
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https://api.github.com/repos/huggingface/datasets/issues/3926 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3926/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3926/comments | https://api.github.com/repos/huggingface/datasets/issues/3926/events | https://github.com/huggingface/datasets/pull/3926 | 1,169,945,052 | PR_kwDODunzps40ehVP | 3,926 | Doc maintenance | [
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] | closed | false | null | 1 | 2022-03-15T17:00:46Z | 2022-03-15T19:27:15Z | 2022-03-15T19:27:12Z | null | This PR adds some minor maintenance to the docs. The main fix is properly linking to pages in the callouts because some of the links would just redirect to a non-existent section on the same page. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3926). All of your documentation changes will be reflected on that endpoint."
] |
https://api.github.com/repos/huggingface/datasets/issues/5871 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5871/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5871/comments | https://api.github.com/repos/huggingface/datasets/issues/5871/events | https://github.com/huggingface/datasets/issues/5871 | 1,712,573,073 | I_kwDODunzps5mE8qR | 5,871 | data configuration hash suffix depends on uncanonicalized data_dir | [
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] | closed | false | null | 3 | 2023-05-16T18:56:04Z | 2023-06-02T15:52:05Z | 2023-06-02T15:52:05Z | null | ### Describe the bug
I am working with the `recipe_nlg` dataset, which requires manual download. Once it's downloaded, I've noticed that the hash in the custom data configuration is different if I add a trailing `/` to my `data_dir`. It took me a while to notice that the hashes were different, and to understand that that was the cause of my dataset being processed anew instead of the cached version being used.
### Steps to reproduce the bug
1. Follow the steps to manually download the `recipe_nlg` dataset to `/data/recipenlg`.
2. Load it using `load_dataset`, once without a trailing slash and once with one:
```python
>>> ds = load_dataset("recipe_nlg", data_dir="/data/recipenlg")
Using custom data configuration default-082278caeea85765
Downloading and preparing dataset recipe_nlg/default to /home/kyle/.cache/huggingface/datasets/recipe_nlg/default-082278caeea85765/1.0.0/aa4f120223637bedf7360cecb70a9bd108acfd64e38207ca90c9f385d21e5e74...
Dataset recipe_nlg downloaded and prepared to /home/kyle/.cache/huggingface/datasets/recipe_nlg/default-082278caeea85765/1.0.0/aa4f120223637bedf7360cecb70a9bd108acfd64e38207ca90c9f385d21e5e74. Subsequent calls will reuse this data.
100%|███████████████████████████████████████████████████████████████████| 1/1 [00:01<00:00, 1.10s/it]
DatasetDict({
train: Dataset({
features: ['id', 'title', 'ingredients', 'directions', 'link', 'source', 'ner'],
num_rows: 2231142
})
})
>>> ds = load_dataset("recipe_nlg", data_dir="/data/recipenlg/")
Using custom data configuration default-83e87680785d0493
Downloading and preparing dataset recipe_nlg/default to /home/user/.cache/huggingface/datasets/recipe_nlg/default-83e87680785d0493/1.0.0/aa4f120223637bedf7360cecb70a9bd108acfd64e38207ca90c9f385d21e5e74...
Generating train split: 1%| | 12701/2231142 [00:04<13:15, 2790.25 examples/s
^C
```
3. Observe that the hash suffix in the custom data configuration changes due to the altered string.
### Expected behavior
I think I would expect the hash to remain constant if it actually points to the same location on disk. I would expect the use of `os.path.normpath` to canonicalize the paths.
### Environment info
- `datasets` version: 2.8.0
- Platform: Linux-5.4.0-147-generic-x86_64-with-glibc2.31
- Python version: 3.10.8
- PyArrow version: 10.0.1
- Pandas version: 1.5.2 | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5871/timeline | null | completed | null | null | false | [
"It could even use `os.path.realpath` to resolve symlinks.",
"Indeed, it makes sense to normalize `data_dir`. Feel free to submit a PR (this can be \"fixed\" [here](https://github.com/huggingface/datasets/blob/89f775226321ba94e5bf4670a323c0fb44f5f65c/src/datasets/builder.py#L173))",
"#self-assign"
] |
https://api.github.com/repos/huggingface/datasets/issues/1842 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1842/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1842/comments | https://api.github.com/repos/huggingface/datasets/issues/1842/events | https://github.com/huggingface/datasets/issues/1842 | 803,563,149 | MDU6SXNzdWU4MDM1NjMxNDk= | 1,842 | Add AMI Corpus | [
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"color": "d93f0b",... | closed | false | null | 3 | 2021-02-08T13:25:00Z | 2023-02-28T16:29:22Z | 2023-02-28T16:29:22Z | null | ## Adding a Dataset
- **Name:** *AMI*
- **Description:** *The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. For a gentle introduction to the corpus, see the corpus overview. To access the data, follow the directions given there. Around two-thirds of the data has been elicited using a scenario in which the participants play different roles in a design team, taking a design project from kick-off to completion over the course of a day. The rest consists of naturally occurring meetings in a range of domains. Detailed information can be found in the documentation section.*
- **Paper:** *Homepage*: http://groups.inf.ed.ac.uk/ami/corpus/
- **Data:** *http://groups.inf.ed.ac.uk/ami/download/* - Select all cases in 1) and select "Individual Headsets" & "Microphone array" for 2)
- **Motivation:** Important speech dataset
If interested in tackling this issue, feel free to tag @patrickvonplaten
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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"Available here: ~https://huggingface.co/datasets/ami~ https://huggingface.co/datasets/edinburghcstr/ami",
"@mariosasko actually the \"official\" AMI dataset can be found here: https://huggingface.co/datasets/edinburghcstr/ami -> the old one under `datasets/ami` doesn't work and should be deleted. \r\n\r\nThe new... |
https://api.github.com/repos/huggingface/datasets/issues/2807 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2807/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2807/comments | https://api.github.com/repos/huggingface/datasets/issues/2807/events | https://github.com/huggingface/datasets/pull/2807 | 971,849,863 | MDExOlB1bGxSZXF1ZXN0NzEzNTMxNjIw | 2,807 | Add cats_vs_dogs dataset | [] | closed | false | null | 0 | 2021-08-16T15:21:11Z | 2021-08-30T16:35:25Z | 2021-08-30T16:35:24Z | null | Adds Microsoft's [Cats vs. Dogs](https://www.microsoft.com/en-us/download/details.aspx?id=54765) dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/1823 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1823/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1823/comments | https://api.github.com/repos/huggingface/datasets/issues/1823/events | https://github.com/huggingface/datasets/pull/1823 | 802,042,181 | MDExOlB1bGxSZXF1ZXN0NTY4MjUyMjIx | 1,823 | Add FewRel Dataset | [] | closed | false | null | 11 | 2021-02-05T10:22:03Z | 2021-03-01T11:56:20Z | 2021-03-01T10:21:39Z | null | Hi,
This PR closes this [Card](https://github.com/huggingface/datasets/projects/1#card-53285184) and Issue #1757.
I wasn't sure how to add `pid2name` along with the dataset so I added it as a separate configuration. For each (head, tail, tokens) triplet, I have created one example. I have added the dictionary key as `"relation"` in the dataset. Additionally, for `pubmed_unsupervised`, I kept `"relation":""` in the dictionary.
Please recommend better alternatives, if any.
Thanks,
Gunjan | {
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"Hi @lhoestq,\r\n\r\nSorry for the late response. What do you mean when you say \"adding names to default config\"? Should I handle \"pid2name\" in the same config as \"default\"?",
"Yes I was thinking of having the pid2name field available in the default configuration (and therefore only have one config). What d... |
https://api.github.com/repos/huggingface/datasets/issues/6075 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6075/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6075/comments | https://api.github.com/repos/huggingface/datasets/issues/6075/events | https://github.com/huggingface/datasets/issues/6075 | 1,822,341,398 | I_kwDODunzps5snrkW | 6,075 | Error loading music files using `load_dataset` | [] | closed | false | null | 2 | 2023-07-26T12:44:05Z | 2023-07-26T13:08:08Z | 2023-07-26T13:08:08Z | null | ### Describe the bug
I tried to load a music file using `datasets.load_dataset()` from the repository - https://huggingface.co/datasets/susnato/pop2piano_real_music_test
I got the following error -
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 2803, in __getitem__
return self._getitem(key)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 2788, in _getitem
formatted_output = format_table(
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 629, in format_table
return formatter(pa_table, query_type=query_type)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 398, in __call__
return self.format_column(pa_table)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 442, in format_column
column = self.python_features_decoder.decode_column(column, pa_table.column_names[0])
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 218, in decode_column
return self.features.decode_column(column, column_name) if self.features else column
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/features.py", line 1924, in decode_column
[decode_nested_example(self[column_name], value) if value is not None else None for value in column]
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/features.py", line 1924, in <listcomp>
[decode_nested_example(self[column_name], value) if value is not None else None for value in column]
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/features.py", line 1325, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/audio.py", line 184, in decode_example
array, sampling_rate = sf.read(f)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 372, in read
with SoundFile(file, 'r', samplerate, channels,
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 740, in __init__
self._file = self._open(file, mode_int, closefd)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 1264, in _open
_error_check(_snd.sf_error(file_ptr),
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 1455, in _error_check
raise RuntimeError(prefix + _ffi.string(err_str).decode('utf-8', 'replace'))
RuntimeError: Error opening <_io.BufferedReader name='/home/susnato/.cache/huggingface/datasets/downloads/d2b09cb974b967b13f91553297c40c0f02f3c0d4c8356350743598ff48d6f29e'>: Format not recognised.
```
### Steps to reproduce the bug
Code to reproduce the error -
```python
from datasets import load_dataset
ds = load_dataset("susnato/pop2piano_real_music_test", split="test")
print(ds[0])
```
### Expected behavior
I should be able to read the music file without any error.
### Environment info
- `datasets` version: 2.14.0
- Platform: Linux-5.19.0-50-generic-x86_64-with-glibc2.35
- Python version: 3.9.16
- Huggingface_hub version: 0.15.1
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
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} | https://api.github.com/repos/huggingface/datasets/issues/6075/timeline | null | completed | null | null | false | [
"This code behaves as expected on my local machine or in Colab. Which version of `soundfile` do you have installed? MP3 requires `soundfile>=0.12.1`.",
"I upgraded the `soundfile` and it's working now! \r\nThanks @mariosasko for the help!"
] |
https://api.github.com/repos/huggingface/datasets/issues/1691 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1691/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1691/comments | https://api.github.com/repos/huggingface/datasets/issues/1691/events | https://github.com/huggingface/datasets/pull/1691 | 779,882,271 | MDExOlB1bGxSZXF1ZXN0NTQ5ODE3NTM0 | 1,691 | Updated HuggingFace Datasets README (fix typos) | [] | closed | false | null | 0 | 2021-01-06T02:14:38Z | 2021-01-16T23:30:47Z | 2021-01-07T10:06:32Z | null | Awesome work on 🤗 Datasets. I found a couple of small typos in the README. Hope this helps.
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https://api.github.com/repos/huggingface/datasets/issues/5783 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5783/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5783/comments | https://api.github.com/repos/huggingface/datasets/issues/5783/events | https://github.com/huggingface/datasets/issues/5783 | 1,679,664,393 | I_kwDODunzps5kHaUJ | 5,783 | Offset overflow while doing regex on a text column | [] | open | false | null | 1 | 2023-04-22T19:12:03Z | 2023-05-05T15:57:41Z | null | null | ### Describe the bug
`ArrowInvalid: offset overflow while concatenating arrays`
Same error as [here](https://github.com/huggingface/datasets/issues/615)
### Steps to reproduce the bug
Steps to reproduce: (dataset is a few GB big so try in colab maybe)
```
import datasets
import re
ds = datasets.load_dataset('nishanthc/dnd_map_dataset_v0.1', split = 'train')
def get_text_caption(example):
regex_pattern = r'\s\d+x\d+|,\sLQ|,\sgrid|\.\w+$'
example['text_caption'] = re.sub(regex_pattern, '', example['picture_text'])
return example
ds = ds.map(get_text_caption)
```
I am trying to apply a regex to remove certain patterns from a text column. Not sure why this error is showing up.
### Expected behavior
Dataset should have a new column with processed text
### Environment info
Datasets version - 2.11.0 | {
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"Hi! This looks like an Arrow bug, but it can be avoided by reducing the `writer_batch_size`.\r\n\r\n(`ds = ds.map(get_text_caption, writer_batch_size=100)` in Colab runs without issues)\r\n"
] |
https://api.github.com/repos/huggingface/datasets/issues/3164 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3164/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3164/comments | https://api.github.com/repos/huggingface/datasets/issues/3164/events | https://github.com/huggingface/datasets/issues/3164 | 1,035,662,830 | I_kwDODunzps49uvXu | 3,164 | Add raw data files to the Hub with GitHub LFS for canonical dataset | [] | closed | false | null | 3 | 2021-10-25T23:28:21Z | 2021-10-30T19:54:51Z | 2021-10-30T19:54:51Z | null | I'm interested in sharing the CaseHOLD dataset (https://arxiv.org/abs/2104.08671) as a canonical dataset on the HuggingFace Hub and would like to add the raw data files to the Hub with GitHub LFS, since it seems like a more sustainable long term storage solution, compared to other storage solutions available to my team. From what I can tell, this option is not immediately supported if one follows the sharing steps detailed here: [https://huggingface.co/docs/datasets/share_dataset.html#sharing-a-canonical-dataset](https://huggingface.co/docs/datasets/share_dataset.html#sharing-a-canonical-dataset), since GitHub LFS is not supported for public forks. Is there a way to request this? Thanks! | {
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} | https://api.github.com/repos/huggingface/datasets/issues/3164/timeline | null | completed | null | null | false | [
"Hi @zlucia, I would actually suggest hosting the dataset as a huggingface.co-hosted dataset.\r\n\r\nThe only difference with a \"canonical\"/legacy dataset is that it's nested under an organization (here `stanford` or `stanfordnlp` for instance – completely up to you) but then you can upload your data using git-lf... |
https://api.github.com/repos/huggingface/datasets/issues/3269 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3269/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3269/comments | https://api.github.com/repos/huggingface/datasets/issues/3269/events | https://github.com/huggingface/datasets/issues/3269 | 1,053,218,769 | I_kwDODunzps4-xtfR | 3,269 | coqa NonMatchingChecksumError | [
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] | closed | false | null | 18 | 2021-11-15T05:04:07Z | 2022-01-19T13:58:19Z | 2022-01-19T13:58:19Z | null | ```
>>> from datasets import load_dataset
>>> dataset = load_dataset("coqa")
Downloading: 3.82kB [00:00, 1.26MB/s]
Downloading: 1.79kB [00:00, 733kB/s]
Using custom data configuration default
Downloading and preparing dataset coqa/default (download: 55.40 MiB, generated: 18.35 MiB, post-processed: Unknown size, total: 73.75 MiB) to /Users/zhaofengw/.cache/huggingface/datasets/coqa/default/1.0.0/553ce70bfdcd15ff4b5f4abc4fc2f37137139cde1f58f4f60384a53a327716f0...
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 222/222 [00:00<00:00, 1.38MB/s]
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 222/222 [00:00<00:00, 1.32MB/s]
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:01<00:00, 1.91it/s]
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1117.44it/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/builder.py", line 679, in _download_and_prepare
verify_checksums(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://nlp.stanford.edu/data/coqa/coqa-train-v1.0.json', 'https://nlp.stanford.edu/data/coqa/coqa-dev-v1.0.json']
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/3269/timeline | null | completed | null | null | false | [
"Hi @ZhaofengWu, thanks for reporting.\r\n\r\nUnfortunately, I'm not able to reproduce your bug:\r\n```python\r\nIn [1]: from datasets import load_dataset\r\n\r\nIn [2]: ds = load_dataset(\"coqa\")\r\nDownloading: 3.82kB [00:00, 1.91MB/s]\r\nDownloading: 1.79kB [00:00, 1.79MB/s]\r\nUsing custom data configuration d... |
https://api.github.com/repos/huggingface/datasets/issues/4671 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4671/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4671/comments | https://api.github.com/repos/huggingface/datasets/issues/4671/events | https://github.com/huggingface/datasets/issues/4671 | 1,300,385,909 | I_kwDODunzps5NglB1 | 4,671 | Dataset Viewer issue for wmt16 | [
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"color": "E5583E",
"default": false,
"description": "Related to the dataset viewer on huggingface.co",
"id": 3470211881,
"name": "dataset-viewer",
"node_id": "LA_kwDODunzps7O1zsp",
"url": "https://api.github.com/repos/huggingface/datasets/labels/dataset-viewer"
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] | closed | false | null | 6 | 2022-07-11T08:34:11Z | 2022-09-13T13:27:02Z | 2022-09-08T08:16:06Z | null | ### Link
https://huggingface.co/datasets/wmt16
### Description
[Reported](https://huggingface.co/spaces/autoevaluate/model-evaluator/discussions/12#62cb83f14c7f35284e796f9c) by a user of AutoTrain Evaluate. AFAIK this dataset was working 1-2 weeks ago, and I'm not sure how to interpret this error.
```
Status code: 400
Exception: NotImplementedError
Message: This is a abstract method
```
Thanks!
### Owner
No | {
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} | https://api.github.com/repos/huggingface/datasets/issues/4671/timeline | null | completed | null | null | false | [
"Thanks for reporting, @lewtun.\r\n\r\n~We can't load the dataset locally, so I think this is an issue with the loading script (not the viewer).~\r\n\r\n We are investigating...",
"Recently, there was a merged PR related to this dataset:\r\n- #4554\r\n\r\nWe are looking at this...",
"Indeed, the above mentioned... |
https://api.github.com/repos/huggingface/datasets/issues/1117 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1117/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1117/comments | https://api.github.com/repos/huggingface/datasets/issues/1117/events | https://github.com/huggingface/datasets/pull/1117 | 757,133,789 | MDExOlB1bGxSZXF1ZXN0NTMyNTYwNzM4 | 1,117 | Fix incorrect MRQA train+SQuAD URL | [] | closed | false | null | 3 | 2020-12-04T14:14:26Z | 2020-12-06T17:14:11Z | 2020-12-06T17:14:10Z | null | Fix issue #1115
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"Thanks ! could you regenerate the dataset_infos.json file ?\r\n\r\n```\r\ndatasets-cli test ./datasets/mrqa --save_infos --all_configs --ignore_verifications\r\n```\r\n\r\nalso cc @VictorSanh ",
"Oooops, good catch @jimmycode ",
"> Thanks ! could you regenerate the dataset_infos.json file ?\r\n> \r\n> ```\r\n>... |
https://api.github.com/repos/huggingface/datasets/issues/200 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/200/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/200/comments | https://api.github.com/repos/huggingface/datasets/issues/200/events | https://github.com/huggingface/datasets/pull/200 | 625,226,638 | MDExOlB1bGxSZXF1ZXN0NDIzNDg2NTM0 | 200 | [ArrowWriter] Set schema at first write example | [] | closed | false | null | 1 | 2020-05-26T21:59:48Z | 2020-05-27T09:07:54Z | 2020-05-27T09:07:53Z | null | Right now if the schema was not specified when instantiating `ArrowWriter`, then it could be set with the first `write_table` for example (it calls `self._build_writer()` to do so).
I noticed that it was not done if the first example is added via `.write`, so I added it for coherence. | {
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"Good point!\r\n\r\nI guess we could add this to `write_batch` as well (before using `self._schema` in the first line of this method)?"
] |
https://api.github.com/repos/huggingface/datasets/issues/3147 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3147/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3147/comments | https://api.github.com/repos/huggingface/datasets/issues/3147/events | https://github.com/huggingface/datasets/pull/3147 | 1,033,607,659 | PR_kwDODunzps4tjRHG | 3,147 | Fix CLI test to ignore verfications when saving infos | [] | closed | false | null | 0 | 2021-10-22T13:52:46Z | 2021-10-27T08:01:50Z | 2021-10-27T08:01:49Z | null | Fix #3146. | {
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https://api.github.com/repos/huggingface/datasets/issues/5250 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5250/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5250/comments | https://api.github.com/repos/huggingface/datasets/issues/5250/events | https://github.com/huggingface/datasets/pull/5250 | 1,451,720,030 | PR_kwDODunzps5DB-1y | 5,250 | Change release procedure to use only pull requests | [] | closed | false | null | 7 | 2022-11-16T14:35:32Z | 2022-11-22T16:30:58Z | 2022-11-22T16:27:48Z | null | This PR changes the release procedure so that:
- it only make changes to main branch via pull requests
- it is no longer necessary to directly commit/push to main branch
Close #5251.
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"_The documentation is not available anymore as the PR was closed or merged._",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5250). All of your documentation changes will be reflected on that endpoint.",
"The docs for this PR live [here](https://moon-ci-docs.huggingface... |
https://api.github.com/repos/huggingface/datasets/issues/1502 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1502/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1502/comments | https://api.github.com/repos/huggingface/datasets/issues/1502/events | https://github.com/huggingface/datasets/pull/1502 | 763,658,208 | MDExOlB1bGxSZXF1ZXN0NTM4MDQ1OTY5 | 1,502 | Add Senti_Lex Dataset | [] | closed | false | null | 5 | 2020-12-12T11:55:29Z | 2020-12-28T14:01:12Z | 2020-12-28T14:01:12Z | null | TODO:
Fix feature format issue
Create dataset_info.json file
Run pytests
Make Style | {
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"Better will be if you close this PR and make a fresh PR",
"Feel free to ping me if you also have questions about the dummy data",
"also it looks like this PR includes changes about dummy_data.zip files in the ./datasets//un_pc folder. Can you remove them ?",
"Thanks for all the advice @lhoestq. I've implemen... |
https://api.github.com/repos/huggingface/datasets/issues/1603 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1603/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1603/comments | https://api.github.com/repos/huggingface/datasets/issues/1603/events | https://github.com/huggingface/datasets/pull/1603 | 770,857,221 | MDExOlB1bGxSZXF1ZXN0NTQyNTIwNDkx | 1,603 | Add retries to HTTP requests | [
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"color": "a2eeef",
"default": true,
"description": "New feature or request",
"id": 1935892871,
"name": "enhancement",
"node_id": "MDU6TGFiZWwxOTM1ODkyODcx",
"url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement"
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] | closed | false | null | 1 | 2020-12-18T12:41:31Z | 2020-12-22T15:34:07Z | 2020-12-22T15:34:07Z | null | ## What does this PR do ?
Adding retries to HTTP GET & HEAD requests, when they fail with a `ConnectTimeout` exception.
The "canonical" way to do this is to use [urllib's Retry class](https://urllib3.readthedocs.io/en/latest/reference/urllib3.util.html#urllib3.util.Retry) and wrap it in a [HttpAdapter](https://requests.readthedocs.io/en/master/api/#requests.adapters.HTTPAdapter). Seems a bit overkill to me, plus it forces us to use the `requests.Session` object. I prefer this simpler implementation. I'm open to remarks and suggestions @lhoestq @yjernite
Fixes #1102 | {
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"merging this one then :) "
] |
https://api.github.com/repos/huggingface/datasets/issues/4449 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4449/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4449/comments | https://api.github.com/repos/huggingface/datasets/issues/4449/events | https://github.com/huggingface/datasets/issues/4449 | 1,261,262,326 | I_kwDODunzps5LLVX2 | 4,449 | Rj | [] | closed | false | null | 0 | 2022-06-06T02:24:32Z | 2022-06-06T15:44:50Z | 2022-06-06T15:44:50Z | null | import android.content.DialogInterface;
import android.database.Cursor;
import android.os.Bundle;
import android.view.View;
import android.widget.ArrayAdapter;
import android.widget.Button;
import android.widget.EditText;
import android.widget.Toast;
import androidx.appcompat.app.AlertDialog;
import androidx.appcompat.app.AppCompatActivity;
public class MainActivity extends AppCompatActivity {
private EditText editTextID;
private EditText editTextName;
private EditText editTextNum;
private String name;
private int number;
private String ID;
private dbHelper db;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
db = new dbHelper(this);
editTextID = findViewById(R.id.editText1);
editTextName = findViewById(R.id.editText2);
editTextNum = findViewById(R.id.editText3);
Button buttonSave = findViewById(R.id.button);
Button buttonRead = findViewById(R.id.button2);
Button buttonUpdate = findViewById(R.id.button3);
Button buttonDelete = findViewById(R.id.button4);
Button buttonSearch = findViewById(R.id.button5);
Button buttonDeleteAll = findViewById(R.id.button6);
buttonSave.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View v) {
name = editTextName.getText().toString();
String num = editTextNum.getText().toString();
if (name.isEmpty() || num.isEmpty()) {
Toast.makeText(MainActivity.this, "Cannot Submit Empty Fields", Toast.LENGTH_SHORT).show();
} else {
number = Integer.parseInt(num);
try {
// Insert Data
db.insertData(name, number);
// Clear the fields
editTextID.getText().clear();
editTextName.getText().clear();
editTextNum.getText().clear();
} catch (Exception e) {
e.printStackTrace();
}
}
}
});
buttonRead.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View v) {
final ArrayAdapter<String> adapter = new ArrayAdapter<>(MainActivity.this, android.R.layout.simple_list_item_1);
String name;
String num;
String id;
try {
Cursor cursor = db.readData();
if (cursor != null && cursor.getCount() > 0) {
while (cursor.moveToNext()) {
id = cursor.getString(0); // get data in column index 0
name = cursor.getString(1); // get data in column index 1
num = cursor.getString(2); // get data in column index 2
// Add SQLite data to listView
adapter.add("ID :- " + id + "\n" +
"Name :- " + name + "\n" +
"Number :- " + num + "\n\n");
}
} else {
adapter.add("No Data");
}
cursor.close();
} catch (Exception e) {
e.printStackTrace();
}
// show the saved data in alertDialog
AlertDialog.Builder builder = new AlertDialog.Builder(MainActivity.this);
builder.setTitle("SQLite saved data");
builder.setIcon(R.mipmap.app_icon_foreground);
builder.setAdapter(adapter, new DialogInterface.OnClickListener() {
@Override
public void onClick(DialogInterface dialog, int which) {
}
});
builder.setPositiveButton("OK", new DialogInterface.OnClickListener() {
@Override
public void onClick(DialogInterface dialog, int which) {
dialog.cancel();
}
});
AlertDialog dialog = builder.create();
dialog.show();
}
});
buttonUpdate.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View v) {
name = editTextName.getText().toString();
String num = editTextNum.getText().toString();
ID = editTextID.getText().toString();
if (name.isEmpty() || num.isEmpty() || ID.isEmpty()) {
Toast.makeText(MainActivity.this, "Cannot Submit Empty Fields", Toast.LENGTH_SHORT).show();
} else {
number = Integer.parseInt(num);
try {
// Update Data
db.updateData(ID, name, number);
// Clear the fields
editTextID.getText().clear();
editTextName.getText().clear();
editTextNum.getText().clear();
} catch (Exception e) {
e.printStackTrace();
}
}
}
});
buttonDelete.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View v) {
ID = editTextID.getText().toString();
if (ID.isEmpty()) {
Toast.makeText(MainActivity.this, "Please enter the ID", Toast.LENGTH_SHORT).show();
} else {
try {
// Delete Data
db.deleteData(ID);
// Clear the fields
editTextID.getText().clear();
editTextName.getText().clear();
editTextNum.getText().clear();
} catch (Exception e) {
e.printStackTrace();
}
}
}
});
buttonDeleteAll.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View v) {
// Delete all data
// You can simply delete all the data by calling this method --> db.deleteAllData();
// You can try this also
AlertDialog.Builder builder = new AlertDialog.Builder(MainActivity.this);
builder.setIcon(R.mipmap.app_icon_foreground);
builder.setTitle("Delete All Data");
builder.setCancelable(false);
builder.setMessage("Do you really need to delete your all data ?");
builder.setPositiveButton("Yes", new DialogInterface.OnClickListener() {
@Override
public void onClick(DialogInterface dialog, int which) {
// User confirmed , now you can delete the data
db.deleteAllData();
// Clear the fields
editTextID.getText().clear();
editTextName.getText().clear();
editTextNum.getText().clear();
}
});
builder.setNegativeButton("No", new DialogInterface.OnClickListener() {
@Override
public void onClick(DialogInterface dialog, int which) {
// user not confirmed
dialog.cancel();
}
});
AlertDialog dialog = builder.create();
dialog.show();
}
});
buttonSearch.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View v) {
ID = editTextID.getText().toString();
if (ID.isEmpty()) {
Toast.makeText(MainActivity.this, "Please enter the ID", Toast.LENGTH_SHORT).show();
} else {
try {
// Search data
Cursor cursor = db.searchData(ID);
if (cursor.moveToFirst()) {
editTextName.setText(cursor.getString(1));
editTextNum.setText(cursor.getString(2));
Toast.makeText(MainActivity.this, "Data successfully searched", Toast.LENGTH_SHORT).show();
} else {
Toast.makeText(MainActivity.this, "ID not found", Toast.LENGTH_SHORT).show();
editTextNum.setText("ID Not found");
editTextName.setText("ID not found");
}
cursor.close();
} catch (Exception e) {
e.printStackTrace();
}
}
}
});
}
} | {
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https://api.github.com/repos/huggingface/datasets/issues/2661 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2661/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2661/comments | https://api.github.com/repos/huggingface/datasets/issues/2661/events | https://github.com/huggingface/datasets/pull/2661 | 946,446,967 | MDExOlB1bGxSZXF1ZXN0NjkxNjE5MzAz | 2,661 | Add SD task for SUPERB | [] | closed | false | null | 11 | 2021-07-16T16:43:21Z | 2021-08-04T17:03:53Z | 2021-08-04T17:03:53Z | null | Include the SD (Speaker Diarization) task as described in the [SUPERB paper](https://arxiv.org/abs/2105.01051) and `s3prl` [instructions](https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#sd-speaker-diarization).
TODO:
- [x] Generate the LibriMix corpus
- [x] Prepare the corpus for diarization
- [x] Upload these files to the superb-data repo
- [x] Transcribe the corresponding s3prl processing of these files into our superb loading script
- [x] README: tags + description sections
- ~~Add DER metric~~ (we leave the DER metric for a follow-up PR)
Related to #2619.
Close #2653.
cc: @lewtun | {
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"I make a summary about our discussion with @lewtun and @Narsil on the agreed schema for this dataset and the additional steps required to generate the 2D array labels:\r\n- The labels for this dataset are a 2D array:\r\n Given an example:\r\n ```python\r\n {\"record_id\": record_id, \"file\": file, \"start\": s... |
https://api.github.com/repos/huggingface/datasets/issues/5904 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5904/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5904/comments | https://api.github.com/repos/huggingface/datasets/issues/5904/events | https://github.com/huggingface/datasets/pull/5904 | 1,727,415,626 | PR_kwDODunzps5Rbfks | 5,904 | Validate name parameter in make_file_instructions | [] | closed | false | null | 2 | 2023-05-26T11:12:46Z | 2023-05-31T07:43:32Z | 2023-05-31T07:34:57Z | null | Validate `name` parameter in `make_file_instructions`.
This way users get more informative error messages, instead of:
```stacktrace
.../huggingface/datasets/src/datasets/arrow_reader.py in make_file_instructions(name, split_infos, instruction, filetype_suffix, prefix_path)
110 name2len = {info.name: info.num_examples for info in split_infos}
111 name2shard_lengths = {info.name: info.shard_lengths for info in split_infos}
--> 112 name2filenames = {
113 info.name: filenames_for_dataset_split(
114 path=prefix_path,
.../huggingface/datasets/src/datasets/arrow_reader.py in <dictcomp>(.0)
111 name2shard_lengths = {info.name: info.shard_lengths for info in split_infos}
112 name2filenames = {
--> 113 info.name: filenames_for_dataset_split(
114 path=prefix_path,
115 dataset_name=name,
.../huggingface/datasets/src/datasets/naming.py in filenames_for_dataset_split(path, dataset_name, split, filetype_suffix, shard_lengths)
68
69 def filenames_for_dataset_split(path, dataset_name, split, filetype_suffix=None, shard_lengths=None):
---> 70 prefix = filename_prefix_for_split(dataset_name, split)
71 prefix = os.path.join(path, prefix)
72
.../huggingface/datasets/src/datasets/naming.py in filename_prefix_for_split(name, split)
52
53 def filename_prefix_for_split(name, split):
---> 54 if os.path.basename(name) != name:
55 raise ValueError(f"Should be a dataset name, not a path: {name}")
56 if not re.match(_split_re, split):
.../lib/python3.9/posixpath.py in basename(p)
140 def basename(p):
141 """Returns the final component of a pathname"""
--> 142 p = os.fspath(p)
143 sep = _get_sep(p)
144 i = p.rfind(sep) + 1
TypeError: expected str, bytes or os.PathLike object, not NoneType
```
Related to #5895. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/2546 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2546/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2546/comments | https://api.github.com/repos/huggingface/datasets/issues/2546/events | https://github.com/huggingface/datasets/pull/2546 | 929,091,689 | MDExOlB1bGxSZXF1ZXN0Njc2OTk2MjQ0 | 2,546 | Add license to the Cambridge English Write & Improve + LOCNESS dataset card | [] | closed | false | null | 0 | 2021-06-24T10:39:29Z | 2021-06-24T10:52:01Z | 2021-06-24T10:52:01Z | null | As noticed in https://github.com/huggingface/datasets/pull/2539, the licensing information was missing for this dataset.
I added it and I also filled a few other empty sections. | {
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