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https://api.github.com/repos/huggingface/datasets/issues/5505 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5505/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5505/comments | https://api.github.com/repos/huggingface/datasets/issues/5505/events | https://github.com/huggingface/datasets/issues/5505 | 1,571,720,814 | I_kwDODunzps5dro5u | 5,505 | PyTorch BatchSampler still loads from Dataset one-by-one | [] | closed | false | null | 2 | 2023-02-06T01:14:55Z | 2023-02-19T18:27:30Z | 2023-02-19T18:27:30Z | null | ### Describe the bug
In [the docs here](https://huggingface.co/docs/datasets/use_with_pytorch#use-a-batchsampler), it mentions the issue of the Dataset being read one-by-one, then states that using a BatchSampler resolves the issue.
I'm not sure if this is a mistake in the docs or the code, but it seems that the only way for a Dataset to be passed a list of indexes by PyTorch (instead of one index at a time) is to define a `__getitems__` method (note the plural) on the Dataset object, and since the HF Dataset doesn't have this, PyTorch executes [this line of code](https://github.com/pytorch/pytorch/blob/master/torch/utils/data/_utils/fetch.py#L58), reverting to fetching one-by-one.
### Steps to reproduce the bug
You can put a breakpoint in `Dataset.__getitem__()` or just print the args from there and see that it's called multiple times for a single `next(iter(dataloader))`, even when using the code from the docs:
```py
from torch.utils.data.sampler import BatchSampler, RandomSampler
batch_sampler = BatchSampler(RandomSampler(ds), batch_size=32, drop_last=False)
dataloader = DataLoader(ds, batch_sampler=batch_sampler)
```
### Expected behavior
The expected behaviour would be for it to fetch batches from the dataset, rather than one-by-one.
To demonstrate that there is room for improvement: once I have a HF dataset `ds`, if I just add this line:
```py
ds.__getitems__ = ds.__getitem__
```
...then the time taken to loop over the dataset improves considerably (for wikitext-103, from one minute to 13 seconds with batch size 32). Probably not a big deal in the grand scheme of things, but seems like an easy win.
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
- Python version: 3.10.8
- PyArrow version: 10.0.1
- Pandas version: 1.5.3 | {
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"This change seems to come from a few months ago in the PyTorch side. That's good news and it means we may not need to pass a batch_sampler as soon as we add `Dataset.__getitems__` to get the optimal speed :)\r\n\r\nThanks for reporting ! Would you like to open a PR to add `__getitems__` and remove this outdated do... |
https://api.github.com/repos/huggingface/datasets/issues/5774 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5774/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5774/comments | https://api.github.com/repos/huggingface/datasets/issues/5774/events | https://github.com/huggingface/datasets/pull/5774 | 1,676,716,662 | PR_kwDODunzps5OxIMe | 5,774 | Fix style | [] | closed | false | null | 2 | 2023-04-20T13:21:32Z | 2023-04-20T13:34:26Z | 2023-04-20T13:24:28Z | null | Fix C419 issues | {
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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/2097 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2097/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2097/comments | https://api.github.com/repos/huggingface/datasets/issues/2097/events | https://github.com/huggingface/datasets/pull/2097 | 838,105,289 | MDExOlB1bGxSZXF1ZXN0NTk4MzM4MTA3 | 2,097 | fixes issue #1110 by descending further if `obj["_type"]` is a dict | [] | closed | false | null | 0 | 2021-03-22T21:00:55Z | 2021-03-22T21:01:11Z | 2021-03-22T21:01:11Z | null | Check metrics | {
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https://api.github.com/repos/huggingface/datasets/issues/2127 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2127/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2127/comments | https://api.github.com/repos/huggingface/datasets/issues/2127/events | https://github.com/huggingface/datasets/pull/2127 | 843,017,199 | MDExOlB1bGxSZXF1ZXN0NjAyNDYxMzc3 | 2,127 | make documentation more clear to use different cloud storage | [] | closed | false | null | 0 | 2021-03-29T06:24:06Z | 2021-03-29T12:16:24Z | 2021-03-29T12:16:24Z | null | This PR extends the cloud storage documentation. To show you can use a different `fsspec` implementation. | {
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https://api.github.com/repos/huggingface/datasets/issues/1213 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1213/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1213/comments | https://api.github.com/repos/huggingface/datasets/issues/1213/events | https://github.com/huggingface/datasets/pull/1213 | 757,983,884 | MDExOlB1bGxSZXF1ZXN0NTMzMjM4NzEz | 1,213 | add taskmaster3 | [] | closed | false | null | 2 | 2020-12-06T17:56:03Z | 2020-12-09T11:05:10Z | 2020-12-09T11:00:29Z | null | Adding Taskmaster-3 dataset
https://github.com/google-research-datasets/Taskmaster/tree/master/TM-3-2020.
The dataset structure almost same as original dataset with these two changes
1. In original dataset, each `apis` has a `args` filed which is a `dict` with variable keys, which represent the name and value of the args. Here converted that to a `list` of `dict` with keys `arg_name` and `arg_value`. For ex.
```python
args = {"name.movie": "Mulan", "name.theater": ": "Mountain AMC 16"}
```
becomes
```python
[
{
"arg_name": "name.movie",
"arg_value": "Mulan"
},
{
"arg_name": "name.theater",
"arg_value": "Mountain AMC 16"
}
]
```
2. Each `apis` has a `response` which is also a `dict` with variable keys representing response name/type and it's value. As above converted it to `list` of `dict` with keys `response_name` and `response_value`.
| {
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"(you were unlucky, my rule of thumb for reducing the dummy data is to check whether they're above 50KB and you're at 52KB ^^')",
"> (you were unlucky, my rule of thumb for reducing the dummy data is to check whether they're above 50KB and you're at 52KB ^^')\r\n\r\nOops :(\r\n\r\nThanks for the suggestion, will ... |
https://api.github.com/repos/huggingface/datasets/issues/4168 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4168/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4168/comments | https://api.github.com/repos/huggingface/datasets/issues/4168/events | https://github.com/huggingface/datasets/pull/4168 | 1,203,867,540 | PR_kwDODunzps42NL6F | 4,168 | Add code examples to API docs | [
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] | closed | false | null | 4 | 2022-04-13T23:03:38Z | 2022-04-27T18:53:37Z | 2022-04-27T18:48:34Z | null | This PR adds code examples for functions related to the base Datasets class to highlight usage. Most of the examples use the `rotten_tomatoes` dataset since it is nice and small. Several things I would appreciate feedback on:
- Do you think it is clearer to make every code example fully reproducible so when users copy the code they can actually run it and get an output? This seems quite repetitive - maybe even unnecessary - but it is definitely clearer. Personally, I think we might be able to get away with not including this since users probably want to try the function on their own dataset. For example:
```py
>>> from datasets import load_dataset
>>> ds = load_dataset("rotten_tomatoes", split="validation")
>>> code example goes here
```
- Should we showcase a function with more than one parameter to highlight different use-cases (it's pretty basic right now, but I'd be happy to add more)?
- For the `class_encode_column` function, let me know if there is a simpler dataset with fewer columns (currently using `winograd_wsc`) so it is easier for users to see what changed.
- Where possible, I try to show the input before and the output after using a function like `flatten` for example. Do you think this is too much and just showing the usage (ie, `>>> ds.flatten()`) will be sufficient?
Thanks :) | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> Do you think it is clearer to make every code example fully reproducible so when users copy the code they can actually run it and get an output? This seems quite repetitive - maybe even unnecessary - but it is definitely clearer.\r... |
https://api.github.com/repos/huggingface/datasets/issues/5411 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5411/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5411/comments | https://api.github.com/repos/huggingface/datasets/issues/5411/events | https://github.com/huggingface/datasets/pull/5411 | 1,523,297,786 | PR_kwDODunzps5G23-T | 5,411 | Update docs of S3 filesystem with async aiobotocore | [] | closed | false | null | 2 | 2023-01-06T23:19:17Z | 2023-01-18T11:18:59Z | 2023-01-18T11:12:04Z | null | [s3fs has migrated to all async calls](https://github.com/fsspec/s3fs/commit/0de2c6fb3d87c08ea694de96dca0d0834034f8bf).
Updating documentation to use `AioSession` while using s3fs for download manager as well as working with datasets | {
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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==6.0.0\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/776 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/776/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/776/comments | https://api.github.com/repos/huggingface/datasets/issues/776/events | https://github.com/huggingface/datasets/pull/776 | 732,343,550 | MDExOlB1bGxSZXF1ZXN0NTEyMjk5NzQx | 776 | Allow custom split names in text dataset | [] | closed | false | null | 1 | 2020-10-29T14:04:06Z | 2020-10-30T13:46:45Z | 2020-10-30T13:23:52Z | null | The `text` dataset used to return only splits like train, test and validation. Other splits were ignored.
Now any split name is allowed.
I did the same for `json`, `pandas` and `csv`
Fix #735 | {
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"Awesome! This will make the behaviour much more intuitive for some non-standard code.\r\n\r\nThanks!"
] |
https://api.github.com/repos/huggingface/datasets/issues/5242 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5242/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5242/comments | https://api.github.com/repos/huggingface/datasets/issues/5242/events | https://github.com/huggingface/datasets/issues/5242 | 1,449,069,382 | I_kwDODunzps5WXwtG | 5,242 | Failed Data Processing upon upload with zip file full of images | [] | open | false | null | 1 | 2022-11-15T02:47:52Z | 2022-11-15T17:59:23Z | null | null | I went to autotrain and under image classification arrived where it was time to prepare my dataset. Screenshot below
I chose the method 2 option. I have a csv file with two columns. ~23,000 files.
I uploaded this and chose the image_relpath, and target columns.
The image uploader said that I could only upload 10,000 singular images at a time so the 2nd option was to zip the images up and upload a zip archive which I did.
That all uploaded.
Now I have the message below. It appears the zip archive does just uncompress on the Hugging Face end?
What am I missing here?
| {
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"cc @abhishekkrthakur @SBrandeis "
] |
https://api.github.com/repos/huggingface/datasets/issues/5100 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5100/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5100/comments | https://api.github.com/repos/huggingface/datasets/issues/5100/events | https://github.com/huggingface/datasets/issues/5100 | 1,404,458,586 | I_kwDODunzps5TtlZa | 5,100 | datasets[s3] sagemaker can't run a model - datasets issue with Value and ClassLabel and cast() method | [] | closed | false | null | 0 | 2022-10-11T11:16:31Z | 2022-10-11T13:48:26Z | 2022-10-11T13:48:26Z | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/599 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/599/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/599/comments | https://api.github.com/repos/huggingface/datasets/issues/599/events | https://github.com/huggingface/datasets/pull/599 | 697,377,786 | MDExOlB1bGxSZXF1ZXN0NDgzMzI3ODQ5 | 599 | Add MATINF dataset | [] | closed | false | null | 2 | 2020-09-10T03:31:09Z | 2020-09-17T12:17:25Z | 2020-09-17T12:17:25Z | null | @lhoestq The command to create metadata failed. I guess it's because the zip is not downloaded from a remote address? How to solve that? Also the CI fails and I don't know how to fix that :( | {
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"Hi ! sorry for the late response\r\n\r\nCould you try to rebase from master ? We changed the named of the library last week so you have to include this change in your code.\r\n\r\nCan you give me more details about the error you get when running the cli command ?\r\n\r\nNote that in case of a manual download you h... |
https://api.github.com/repos/huggingface/datasets/issues/4563 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4563/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4563/comments | https://api.github.com/repos/huggingface/datasets/issues/4563/events | https://github.com/huggingface/datasets/pull/4563 | 1,283,914,383 | PR_kwDODunzps46UmZQ | 4,563 | Support streaming allocine dataset | [] | closed | false | null | 1 | 2022-06-24T15:55:03Z | 2022-06-24T16:54:57Z | 2022-06-24T16:44:41Z | null | Support streaming allocine dataset.
Fix #4562. | {
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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/5821 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5821/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5821/comments | https://api.github.com/repos/huggingface/datasets/issues/5821/events | https://github.com/huggingface/datasets/pull/5821 | 1,696,400,343 | PR_kwDODunzps5PzHLU | 5,821 | IterableDataset Arrow formatting | [] | closed | false | null | 13 | 2023-05-04T17:23:43Z | 2023-05-31T09:43:26Z | 2023-05-31T09:36:18Z | null | Adding an optional `.iter_arrow` to examples iterable. This allows to use Arrow formatting in map/filter.
This will also be useful for torch formatting, since we can reuse the TorchFormatter that converts Arrow data to torch tensors
Related to https://github.com/huggingface/datasets/issues/5793 and https://github.com/huggingface/datasets/issues/3444
Required for https://github.com/huggingface/datasets/pull/5852
### Example:
Speed x10 in map
```python
from datasets import Dataset
import pyarrow.compute as pc
import time
ds = Dataset.from_dict({"a": range(100_000)})
ids = ds.to_iterable_dataset()
ids = ids.map(lambda x: {"a": [a + 10 for a in x["a"]]}, batched=True)
_start = time.time()
print(f"Python ({sum(1 for _ in ids)} items):\t{(time.time() - _start) * 1000:.1f}ms")
# Python (100000 items): 695.7ms
ids = ds.to_iterable_dataset().with_format("arrow")
ids = ids.map(lambda t: t.set_column(0, "a", pc.add(t[0], 10)), batched=True)
ids = ids.with_format(None)
_start = time.time()
print(f"Arrow ({sum(1 for _ in ids)} items):\t{(time.time() - _start) * 1000:.1f}ms)")
# Arrow (100000 items): 81.0ms)
```
### Implementation details
I added an optional `iter_arrow` method to examples iterable. If an example iterable has this method, then it can be used to iterate on the examples by batch of arrow tables. | {
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"<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 | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... |
https://api.github.com/repos/huggingface/datasets/issues/3292 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3292/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3292/comments | https://api.github.com/repos/huggingface/datasets/issues/3292/events | https://github.com/huggingface/datasets/issues/3292 | 1,056,962,554 | I_kwDODunzps4-__f6 | 3,292 | Not able to load 'wikipedia' dataset | [
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] | closed | false | null | 1 | 2021-11-18T05:41:18Z | 2021-11-19T16:49:29Z | 2021-11-19T16:49:29Z | null | ## Describe the bug
I am following the instruction for loading the wikipedia dataset using datasets. However getting the below error.
## Steps to reproduce the bug
from datasets import load_dataset
dataset = load_dataset("wikipedia")
```
## Expected results
A clear and concise description of the expected results.
## Actual results
~/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/datasets/builder.py in _create_builder_config(self, name, custom_features, **config_kwargs)
339 "Config name is missing."
340 "\nPlease pick one among the available configs: %s" % list(self.builder_configs.keys())
--> 341 + "\nExample of usage:\n\t`{}`".format(example_of_usage)
342 )
343 builder_config = self.BUILDER_CONFIGS[0]
ValueError: Config name is missing.
Please pick one among the available configs: ['20200501.aa', '20200501.ab', '20200501.ace', '20200501.ady', '20200501.af', '20200501.ak', '20200501.als', '20200501.am', '20200501.an', '20200501.ang', '20200501.ar', '20200501.arc', '20200501.arz', '20200501.as', '20200501.ast', '20200501.atj', '20200501.av', '20200501.ay', '20200501.az', '20200501.azb', '20200501.ba', '20200501.bar', '20200501.bat-smg', '20200501.bcl', '20200501.be', '20200501.be-x-old', '20200501.bg', '20200501.bh', '20200501.bi', '20200501.bjn', '20200501.bm', '20200501.bn', '20200501.bo', '20200501.bpy', '20200501.br', '20200501.bs', '20200501.bug', '20200501.bxr', '20200501.ca', '20200501.cbk-zam', '20200501.cdo', '20200501.ce', '20200501.ceb', '20200501.ch', '20200501.cho', '20200501.chr', '20200501.chy', '20200501.ckb', '20200501.co', '20200501.cr', '20200501.crh', '20200501.cs', '20200501.csb', '20200501.cu', '20200501.cv', '20200501.cy', '20200501.da', '20200501.de', '20200501.din', '20200501.diq', '20200501.dsb', '20200501.dty', '20200501.dv', '20200501.dz', '20200501.ee', '20200501.el', '20200501.eml', '20200501.en', '20200501.eo', '20200501.es', '20200501.et', '20200501.eu', '20200501.ext', '20200501.fa', '20200501.ff', '20200501.fi', '20200501.fiu-vro', '20200501.fj', '20200501.fo', '20200501.fr', '20200501.frp', '20200501.frr', '20200501.fur', '20200501.fy', '20200501.ga', '20200501.gag', '20200501.gan', '20200501.gd', '20200501.gl', '20200501.glk', '20200501.gn', '20200501.gom', '20200501.gor', '20200501.got', '20200501.gu', '20200501.gv', '20200501.ha', '20200501.hak', '20200501.haw', '20200501.he', '20200501.hi', '20200501.hif', '20200501.ho', '20200501.hr', '20200501.hsb', '20200501.ht', '20200501.hu', '20200501.hy', '20200501.ia', '20200501.id', '20200501.ie', '20200501.ig', '20200501.ii', '20200501.ik', '20200501.ilo', '20200501.inh', '20200501.io', '20200501.is', '20200501.it', '20200501.iu', '20200501.ja', '20200501.jam', '20200501.jbo', '20200501.jv', '20200501.ka', '20200501.kaa', '20200501.kab', '20200501.kbd', '20200501.kbp', '20200501.kg', '20200501.ki', '20200501.kj', '20200501.kk', '20200501.kl', '20200501.km', '20200501.kn', '20200501.ko', '20200501.koi', '20200501.krc', '20200501.ks', '20200501.ksh', '20200501.ku', '20200501.kv', '20200501.kw', '20200501.ky', '20200501.la', '20200501.lad', '20200501.lb', '20200501.lbe', '20200501.lez', '20200501.lfn', '20200501.lg', '20200501.li', '20200501.lij', '20200501.lmo', '20200501.ln', '20200501.lo', '20200501.lrc', '20200501.lt', '20200501.ltg', '20200501.lv', '20200501.mai', '20200501.map-bms', '20200501.mdf', '20200501.mg', '20200501.mh', '20200501.mhr', '20200501.mi', '20200501.min', '20200501.mk', '20200501.ml', '20200501.mn', '20200501.mr', '20200501.mrj', '20200501.ms', '20200501.mt', '20200501.mus', '20200501.mwl', '20200501.my', '20200501.myv', '20200501.mzn', '20200501.na', '20200501.nah', '20200501.nap', '20200501.nds', '20200501.nds-nl', '20200501.ne', '20200501.new', '20200501.ng', '20200501.nl', '20200501.nn', '20200501.no', '20200501.nov', '20200501.nrm', '20200501.nso', '20200501.nv', '20200501.ny', '20200501.oc', '20200501.olo', '20200501.om', '20200501.or', '20200501.os', '20200501.pa', '20200501.pag', '20200501.pam', '20200501.pap', '20200501.pcd', '20200501.pdc', '20200501.pfl', '20200501.pi', '20200501.pih', '20200501.pl', '20200501.pms', '20200501.pnb', '20200501.pnt', '20200501.ps', '20200501.pt', '20200501.qu', '20200501.rm', '20200501.rmy', '20200501.rn', '20200501.ro', '20200501.roa-rup', '20200501.roa-tara', '20200501.ru', '20200501.rue', '20200501.rw', '20200501.sa', '20200501.sah', '20200501.sat', '20200501.sc', '20200501.scn', '20200501.sco', '20200501.sd', '20200501.se', '20200501.sg', '20200501.sh', '20200501.si', '20200501.simple', '20200501.sk', '20200501.sl', '20200501.sm', '20200501.sn', '20200501.so', '20200501.sq', '20200501.sr', '20200501.srn', '20200501.ss', '20200501.st', '20200501.stq', '20200501.su', '20200501.sv', '20200501.sw', '20200501.szl', '20200501.ta', '20200501.tcy', '20200501.te', '20200501.tet', '20200501.tg', '20200501.th', '20200501.ti', '20200501.tk', '20200501.tl', '20200501.tn', '20200501.to', '20200501.tpi', '20200501.tr', '20200501.ts', '20200501.tt', '20200501.tum', '20200501.tw', '20200501.ty', '20200501.tyv', '20200501.udm', '20200501.ug', '20200501.uk', '20200501.ur', '20200501.uz', '20200501.ve', '20200501.vec', '20200501.vep', '20200501.vi', '20200501.vls', '20200501.vo', '20200501.wa', '20200501.war', '20200501.wo', '20200501.wuu', '20200501.xal', '20200501.xh', '20200501.xmf', '20200501.yi', '20200501.yo', '20200501.za', '20200501.zea', '20200501.zh', '20200501.zh-classical', '20200501.zh-min-nan', '20200501.zh-yue', '20200501.zu']
Example of usage:
`load_dataset('wikipedia', '20200501.aa')`
I think the other parameter is missing in the load_dataset function that is not shown in the instruction. | {
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} | https://api.github.com/repos/huggingface/datasets/issues/3292/timeline | null | completed | null | null | false | [
"Hi ! Indeed it looks like the code snippet on the Hugging face Hub doesn't show the second parameter\r\n\r\n\r\n\r\nThanks for reporting, I'm taking a look\r\n"
] |
https://api.github.com/repos/huggingface/datasets/issues/5248 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5248/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5248/comments | https://api.github.com/repos/huggingface/datasets/issues/5248/events | https://github.com/huggingface/datasets/pull/5248 | 1,451,338,676 | PR_kwDODunzps5DAqwt | 5,248 | Complete doc migration | [] | closed | false | null | 2 | 2022-11-16T10:41:04Z | 2022-11-16T15:06:50Z | 2022-11-16T10:41:10Z | null | Reverts huggingface/datasets#5214
Everything is handled on the doc-builder side now 😊 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5248). All of your documentation changes will be reflected on that endpoint.",
"Thanks for the fix @mishig25.\r\n\r\nI guess this is the reason why the docs are not generated for the latest release version 2.7.0? https://huggin... |
https://api.github.com/repos/huggingface/datasets/issues/1972 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1972/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1972/comments | https://api.github.com/repos/huggingface/datasets/issues/1972/events | https://github.com/huggingface/datasets/issues/1972 | 819,752,761 | MDU6SXNzdWU4MTk3NTI3NjE= | 1,972 | 'Dataset' object has no attribute 'rename_column' | [] | closed | false | null | 1 | 2021-03-02T08:01:49Z | 2022-06-01T16:08:47Z | 2022-06-01T16:08:47Z | null | 'Dataset' object has no attribute 'rename_column' | {
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"Hi ! `rename_column` has been added recently and will be available in the next release"
] |
https://api.github.com/repos/huggingface/datasets/issues/249 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/249/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/249/comments | https://api.github.com/repos/huggingface/datasets/issues/249/events | https://github.com/huggingface/datasets/issues/249 | 633,393,443 | MDU6SXNzdWU2MzMzOTM0NDM= | 249 | [Dataset created] some critical small issues when I was creating a dataset | [] | closed | false | null | 2 | 2020-06-07T12:58:54Z | 2020-06-12T08:28:51Z | 2020-06-12T08:28:51Z | null | Hi, I successfully created a dataset and has made a pr #248.
But I have encountered several problems when I was creating it, and those should be easy to fix.
1. Not found dataset_info.json
should be fixed by #241 , eager to wait it be merged.
2. Forced to install `apach_beam`
If we should install it, then it might be better to include it in the pakcage dependency or specified in `CONTRIBUTING.md`
```
Traceback (most recent call last):
File "nlp-cli", line 10, in <module>
from nlp.commands.run_beam import RunBeamCommand
File "/home/yisiang/nlp/src/nlp/commands/run_beam.py", line 6, in <module>
import apache_beam as beam
ModuleNotFoundError: No module named 'apache_beam'
```
3. `cached_dir` is `None`
```
File "/home/yisiang/nlp/src/nlp/datasets/bookscorpus/aea0bd5142d26df645a8fce23d6110bb95ecb81772bb2a1f29012e329191962c/bookscorpus.py", line 88, in _split_generators
downloaded_path_or_paths = dl_manager.download_custom(_GDRIVE_FILE_ID, download_file_from_google_drive)
File "/home/yisiang/nlp/src/nlp/utils/download_manager.py", line 128, in download_custom
downloaded_path_or_paths = map_nested(url_to_downloaded_path, url_or_urls)
File "/home/yisiang/nlp/src/nlp/utils/py_utils.py", line 172, in map_nested
return function(data_struct)
File "/home/yisiang/nlp/src/nlp/utils/download_manager.py", line 126, in url_to_downloaded_path
return os.path.join(self._download_config.cache_dir, hash_url_to_filename(url))
File "/home/yisiang/miniconda3/envs/nlppr/lib/python3.7/posixpath.py", line 80, in join
a = os.fspath(a)
```
This is because this line
https://github.com/huggingface/nlp/blob/2e0a8639a79b1abc848cff5c669094d40bba0f63/src/nlp/commands/test.py#L30-L32
And I add `--cache_dir="...."` to `python nlp-cli test datasets/<your-dataset-folder> --save_infos --all_configs` in the doc, finally I could pass this error.
But it seems to ignore my arg and use `/home/yisiang/.cache/huggingface/datasets/bookscorpus/plain_text/1.0.0` as cahe_dir
4. There is no `pytest`
So maybe in the doc we should specify a step to install pytest
5. Not enough capacity in my `/tmp`
When run test for dummy data, I don't know why it ask me for 5.6g to download something,
```
def download_and_prepare
...
if not utils.has_sufficient_disk_space(self.info.size_in_bytes or 0, directory=self._cache_dir_root):
raise IOError(
"Not enough disk space. Needed: {} (download: {}, generated: {})".format(
utils.size_str(self.info.size_in_bytes or 0),
utils.size_str(self.info.download_size or 0),
> utils.size_str(self.info.dataset_size or 0),
)
)
E OSError: Not enough disk space. Needed: 5.62 GiB (download: 1.10 GiB, generated: 4.52 GiB)
```
I add a `processed_temp_dir="some/dir"; raw_temp_dir="another/dir"` to 71, and the test passed
https://github.com/huggingface/nlp/blob/a67a6c422dece904b65d18af65f0e024e839dbe8/tests/test_dataset_common.py#L70-L72
I suggest we can create tmp dir under the `/home/user/tmp` but not `/tmp`, because take our lab server for example, everyone use `/tmp` thus it has not much capacity. Or at least we can improve error message, so the user know is what directory has no space and how many has it lefted. Or we could do both.
6. name of datasets
I was surprised by the dataset name `books_corpus`, and didn't know it is from `class BooksCorpus(nlp.GeneratorBasedBuilder)` . I change it to `Bookscorpus` afterwards. I think this point shold be also on the doc.
7. More thorough doc to how to create `dataset.py`
I believe there will be.
**Feel free to close this issue** if you think these are solved. | {
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"Thanks for noticing all these :) They should be easy to fix indeed",
"Alright I think I fixed all the problems you mentioned. Thanks again, that will be useful for many people.\r\nThere is still more work needed for point 7. but we plan to have some nice docs soon."
] |
https://api.github.com/repos/huggingface/datasets/issues/4084 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4084/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4084/comments | https://api.github.com/repos/huggingface/datasets/issues/4084/events | https://github.com/huggingface/datasets/issues/4084 | 1,190,060,415 | I_kwDODunzps5G7uF_ | 4,084 | Errors in `Train with Datasets` Tensorflow code section on Huggingface.co | [
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] | closed | false | null | 1 | 2022-04-01T17:02:47Z | 2022-04-04T07:24:37Z | 2022-04-04T07:21:31Z | null | ## Describe the bug
Hi
### Error 1
Running the Tensforlow code on [Huggingface](https://huggingface.co/docs/datasets/use_dataset) gives a TypeError: __init__() got an unexpected keyword argument 'return_tensors'
### Error 2
`DataCollatorWithPadding` isn't imported
## Steps to reproduce the bug
```python
import tensorflow as tf
from datasets import load_dataset
from transformers import AutoTokenizer
dataset = load_dataset('glue', 'mrpc', split='train')
tokenizer = AutoTokenizer.from_pretrained('bert-base-cased')
dataset = dataset.map(lambda e: tokenizer(e['sentence1'], truncation=True, padding='max_length'), batched=True)
data_collator = DataCollatorWithPadding(tokenizer=tokenizer, return_tensors="tf")
train_dataset = dataset["train"].to_tf_dataset(
columns=['input_ids', 'token_type_ids', 'attention_mask', 'label'],
shuffle=True,
batch_size=16,
collate_fn=data_collator,
)
```
This is the same code on Huggingface.co
## Actual results
TypeError: __init__() got an unexpected keyword argument 'return_tensors'
## Environment info
- `datasets` version: 2.0.0
- Platform: Windows-10-10.0.19044-SP0
- Python version: 3.9.7
- PyArrow version: 6.0.0
- Pandas version: 1.4.1
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} | https://api.github.com/repos/huggingface/datasets/issues/4084/timeline | null | completed | null | null | false | [
"Hi @blackhat-coder, thanks for reporting.\r\n\r\nPlease note that the `transformers` library updated their data collators API last year (version 4.10.0):\r\n- huggingface/transformers#13105\r\n\r\nnow requiring to pass `return_tensors` argument at Data Collator instantiation.\r\n\r\nAnd therefore, we also updated ... |
https://api.github.com/repos/huggingface/datasets/issues/15 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/15/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/15/comments | https://api.github.com/repos/huggingface/datasets/issues/15/events | https://github.com/huggingface/datasets/pull/15 | 604,906,708 | MDExOlB1bGxSZXF1ZXN0NDA3NDEwOTk3 | 15 | [Tests] General Test Design for all dataset scripts | [] | closed | false | null | 10 | 2020-04-22T16:46:01Z | 2022-10-04T09:31:54Z | 2020-04-27T14:48:02Z | null | The general idea is similar to how testing is done in `transformers`. There is one general `test_dataset_common.py` file which has a `DatasetTesterMixin` class. This class implements all of the logic that can be used in a generic way for all dataset classes. The idea is to keep each individual dataset test file as minimal as possible.
In order to test whether the specific data set class can download the data and generate the examples **without** downloading the actual data all the time, a MockDataLoaderManager class is used which receives a `mock_folder_structure_fn` function from each individual dataset test file that create "fake" data and which returns the same folder structure that would have been created when using the real data downloader. | {
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"> I think I'm fine with this.\r\n> \r\n> The alternative would be to host a small subset of the dataset on the S3 together with the testing script. But I think having all (test file creation + actual tests) in one file is actually quite convenient.\r\n> \r\n> Good for me!\r\n> \r\n> One question though, will we ha... |
https://api.github.com/repos/huggingface/datasets/issues/84 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/84/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/84/comments | https://api.github.com/repos/huggingface/datasets/issues/84/events | https://github.com/huggingface/datasets/pull/84 | 617,249,815 | MDExOlB1bGxSZXF1ZXN0NDE3MjAxODcz | 84 | [TedHrLr] add left dummy data | [] | closed | false | null | 0 | 2020-05-13T08:27:20Z | 2020-05-13T08:29:22Z | 2020-05-13T08:29:21Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5721 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5721/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5721/comments | https://api.github.com/repos/huggingface/datasets/issues/5721/events | https://github.com/huggingface/datasets/issues/5721 | 1,659,680,682 | I_kwDODunzps5i7Leq | 5,721 | Calling datasets.load_dataset("text" ...) results in a wrong split. | [] | open | false | null | 0 | 2023-04-08T23:55:12Z | 2023-04-08T23:55:12Z | null | null | ### Describe the bug
When creating a text dataset, the training split should have the bulk of the examples by default. Currently, testing does.
### Steps to reproduce the bug
I have a folder with 18K text files in it. Each text file essentially consists in a document or article scraped from online. Calling the following codeL
```
folder_path = "/home/cyril/Downloads/llama_dataset"
data = datasets.load_dataset("text", data_dir=folder_path)
data.save_to_disk("/home/cyril/Downloads/data.hf")
data = datasets.load_from_disk("/home/cyril/Downloads/data.hf")
print(data)
```
Results in the following split:
```
DatasetDict({
train: Dataset({
features: ['text'],
num_rows: 2114
})
test: Dataset({
features: ['text'],
num_rows: 200882
})
validation: Dataset({
features: ['text'],
num_rows: 152
})
})
```
It seems to me like the train/test/validation splits are in the wrong order since test split >>>> train_split
### Expected behavior
Train split should have the bulk of the training examples.
### Environment info
datasets 2.11.0, python 3.10.6 | {
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https://api.github.com/repos/huggingface/datasets/issues/5281 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5281/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5281/comments | https://api.github.com/repos/huggingface/datasets/issues/5281/events | https://github.com/huggingface/datasets/issues/5281 | 1,459,930,271 | I_kwDODunzps5XBMSf | 5,281 | Support cloud storage in load_dataset | [
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"default": fals... | open | false | null | 13 | 2022-11-22T14:00:10Z | 2023-05-10T12:20:44Z | null | null | Would be nice to be able to do
```python
load_dataset("s3://...")
```
or even
```python
data_files=["gs://..."]
storage_options = {...}
load_dataset(..., data_files=data_files, storage_options=storage_options)
```
The idea would be to use `fsspec` as in `download_and_prepare` and `save_to_disk`.
This has been requested several times already. Some users want to use their data from private cloud storage to train models
related:
https://github.com/huggingface/datasets/issues/3490
https://github.com/huggingface/datasets/issues/5244
[forum](https://discuss.huggingface.co/t/how-to-use-s3-path-with-load-dataset-with-streaming-true/25739/2) | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5281/timeline | null | reopened | null | null | false | [
"Or for example an archive on GitHub releases! Before I added support for JXL (locally only, PR still pending) I was considering hosting my files on GitHub instead...",
"+1 to this. I would like to use 'audiofolder' with a data_dir that's on S3, for example. I don't want to upload my dataset to the Hub, but I wo... |
https://api.github.com/repos/huggingface/datasets/issues/1074 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1074/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1074/comments | https://api.github.com/repos/huggingface/datasets/issues/1074/events | https://github.com/huggingface/datasets/pull/1074 | 756,483,172 | MDExOlB1bGxSZXF1ZXN0NTMyMDIyNTIy | 1,074 | Swedish MT STS-B | [] | closed | false | null | 0 | 2020-12-03T19:06:25Z | 2020-12-04T20:22:27Z | 2020-12-03T20:44:28Z | null | Added a Swedish machine translated version of the well known STS-B Corpus | {
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https://api.github.com/repos/huggingface/datasets/issues/4053 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4053/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4053/comments | https://api.github.com/repos/huggingface/datasets/issues/4053/events | https://github.com/huggingface/datasets/issues/4053 | 1,184,500,378 | I_kwDODunzps5Gmgqa | 4,053 | Modify datatype from `int32` to `float` for pearsonr, spearmanr. | [
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] | closed | false | null | 1 | 2022-03-29T08:27:41Z | 2022-03-29T14:02:20Z | 2022-03-29T14:02:20Z | null | **Is your feature request related to a problem? Please describe.**
- Now [Pearsonr](https://github.com/huggingface/datasets/blob/master/metrics/pearsonr/pearsonr.py) and [Spearmanr](https://github.com/huggingface/datasets/blob/master/metrics/spearmanr/spearmanr.py) both get input data as 'int32'.
**Describe the solution you'd like**
- Considering that those metrics are widely used for the STS task(labels are in 'float' data type),
it would be better to modify datatype from 'int32' to 'float' for getting exact values of similarity. | {
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"@Woodywarhol9 good catch, thanks for reporting.\r\n\r\nWe are fixing this."
] |
https://api.github.com/repos/huggingface/datasets/issues/3377 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3377/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3377/comments | https://api.github.com/repos/huggingface/datasets/issues/3377/events | https://github.com/huggingface/datasets/pull/3377 | 1,070,562,907 | PR_kwDODunzps4vXCHn | 3,377 | COCO 🥥 on the 🤗 Hub? | [] | closed | false | null | 4 | 2021-12-03T12:55:27Z | 2021-12-20T14:14:01Z | 2021-12-20T14:14:00Z | null | This is a draft PR since I ran into few small problems.
I referred to this TFDS code: https://github.com/tensorflow/datasets/blob/2538a08c184d53b37bfcf52cc21dd382572a88f4/tensorflow_datasets/object_detection/coco.py
cc: @mariosasko | {
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"@mariosasko I fixed couple of bugs",
"TO-DO: \r\n- [x] Add unlabeled 2017 splits, train and validation splits of 2015\r\n- [x] Add Class Labels as list instead",
"@mariosasko added fine & coarse grained labels, will fix the bugs (currently getting set up with VM, my internet is too slow to run the tests and do... |
https://api.github.com/repos/huggingface/datasets/issues/2277 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2277/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2277/comments | https://api.github.com/repos/huggingface/datasets/issues/2277/events | https://github.com/huggingface/datasets/pull/2277 | 870,071,994 | MDExOlB1bGxSZXF1ZXN0NjI1MzI5NjIz | 2,277 | Create CacheManager | [
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} | 0 | 2021-04-28T15:23:42Z | 2022-07-06T15:19:48Z | null | null | Perform refactoring to decouple cache functionality (method `as_dataset`). | {
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https://api.github.com/repos/huggingface/datasets/issues/5204 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5204/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5204/comments | https://api.github.com/repos/huggingface/datasets/issues/5204/events | https://github.com/huggingface/datasets/issues/5204 | 1,437,221,259 | I_kwDODunzps5VqkGL | 5,204 | `push_to_hub` not propagating `token` through `DownloadConfig` | [] | closed | false | null | 3 | 2022-11-05T23:32:20Z | 2022-11-08T10:12:09Z | 2022-11-08T10:12:08Z | null | ### Describe the bug
When trying to upload a new 🤗 Dataset to the Hub via Python, and providing the `token` as a parameter to the `Dataset.push_to_hub` function, it just works for the first time, assuming that the dataset didn't exist before.
But when trying to run `Dataset.push_to_hub` again over the same dataset, instead of updating it, it throws a `ConnectionError` when trying to retrieve the `README.md` that may contain some metadata about the dataset, so as to also update it, but since the `token` is not propagated, the `DownloadConfig` provided to the `datasets.utils.file_utils.get_from_cache` function doesn't contain the `use_auth_token` value set to `token`, it's just using the default one which is None/False.
So on, when uploading a dataset via Python with `push_to_hub` with the `token` as a parameter with the HuggingFace API Token as value, it can just be uploaded when the dataset is new, otherwise it fails with to `ConnectionError` due to the `token` not being propagated as `use_auth_token`.
### Steps to reproduce the bug
Let's create a new dataset in our HF account via Python as:
```python
from datasets import Dataset
data = {"a": [1, 2, 3], "b": [4, 5, 6]}
ds = Dataset.from_dict(data)
ds.push_to_hub(repo_id=<HF_USERNAME>/<HF_DATASET>, private=private, token=<HF_TOKEN_HERE>)
```
When we create the `Dataset` for the first time it works and there are no issues, but when trying to actually upload a new version of the same dataset (same name under the same username), we encounter the following issue:
```python
from datasets import Dataset
data = {"a": [1, 2, 3], "b": [4, 5, 6]}
ds = Dataset.from_dict(data)
ds.push_to_hub(repo_id=<HF_USERNAME>/<HF_DATASET>, private=private, token=<HF_TOKEN_HERE>)
>>> ConnectionError: Couldn't reach https://huggingface.co/datasets/alvarobartt/demo/resolve/main/README.md (ConnectionError('Unauthorized for URL https://huggingface.co/datasets/<HF_USERNAME>/<HF_DATASET>/resolve/main/README.md. Please use the parameter `use_auth_token=True` after logging in with `huggingface-cli login`'))
```
### Expected behavior
Ideally, the `token` parameter provided to `push_to_hub` should be propagated and used to download the `README.md` when trying to update a `Dataset`, instead of throwing that exception, so that the authentication can be done directly through code without running `huggingface-cli login`as mentioned at https://huggingface.co/docs/datasets/upload_dataset#upload-with-python.
### Environment info
- `datasets` version: 2.6.1
- Platform: macOS-13.0-arm64-arm-64bit
- Python version: 3.10.8
- PyArrow version: 10.0.0
- Pandas version: 1.5.1 | {
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"#self-assign",
"@lhoestq can you close this issue as part of the recent #5205 merge? Thanks 🤗 ",
"Thank you :)"
] |
https://api.github.com/repos/huggingface/datasets/issues/534 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/534/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/534/comments | https://api.github.com/repos/huggingface/datasets/issues/534/events | https://github.com/huggingface/datasets/issues/534 | 686,115,912 | MDU6SXNzdWU2ODYxMTU5MTI= | 534 | `list_datasets()` is broken. | [] | closed | false | null | 3 | 2020-08-26T08:19:01Z | 2020-08-27T06:31:11Z | 2020-08-27T06:31:11Z | null | version = '0.4.0'
`list_datasets()` is broken. It results in the following error :
```
In [3]: nlp.list_datasets()
Out[3]: ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
~/.virtualenvs/san-lgUCsFg_/lib/python3.8/site-packages/IPython/core/formatters.py in __call__(self, obj)
700 type_pprinters=self.type_printers,
701 deferred_pprinters=self.deferred_printers)
--> 702 printer.pretty(obj)
703 printer.flush()
704 return stream.getvalue()
~/.virtualenvs/san-lgUCsFg_/lib/python3.8/site-packages/IPython/lib/pretty.py in pretty(self, obj)
375 if cls in self.type_pprinters:
376 # printer registered in self.type_pprinters
--> 377 return self.type_pprinters[cls](obj, self, cycle)
378 else:
379 # deferred printer
~/.virtualenvs/san-lgUCsFg_/lib/python3.8/site-packages/IPython/lib/pretty.py in inner(obj, p, cycle)
553 p.text(',')
554 p.breakable()
--> 555 p.pretty(x)
556 if len(obj) == 1 and type(obj) is tuple:
557 # Special case for 1-item tuples.
~/.virtualenvs/san-lgUCsFg_/lib/python3.8/site-packages/IPython/lib/pretty.py in pretty(self, obj)
392 if cls is not object \
393 and callable(cls.__dict__.get('__repr__')):
--> 394 return _repr_pprint(obj, self, cycle)
395
396 return _default_pprint(obj, self, cycle)
~/.virtualenvs/san-lgUCsFg_/lib/python3.8/site-packages/IPython/lib/pretty.py in _repr_pprint(obj, p, cycle)
698 """A pprint that just redirects to the normal repr function."""
699 # Find newlines and replace them with p.break_()
--> 700 output = repr(obj)
701 lines = output.splitlines()
702 with p.group():
~/.virtualenvs/san-lgUCsFg_/lib/python3.8/site-packages/nlp/hf_api.py in __repr__(self)
110
111 def __repr__(self):
--> 112 single_line_description = self.description.replace("\n", "")
113 return f"nlp.ObjectInfo(id='{self.id}', description='{single_line_description}', files={self.siblings})"
114
AttributeError: 'NoneType' object has no attribute 'replace'
``` | {
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"Thanks for reporting !\r\nThis has been fixed in #475 and the fix will be available in the next release",
"What you can do instead to get the list of the datasets is call\r\n\r\n```python\r\nprint([dataset.id for dataset in nlp.list_datasets()])\r\n```",
"Thanks @lhoestq . "
] |
https://api.github.com/repos/huggingface/datasets/issues/2803 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2803/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2803/comments | https://api.github.com/repos/huggingface/datasets/issues/2803/events | https://github.com/huggingface/datasets/pull/2803 | 970,858,928 | MDExOlB1bGxSZXF1ZXN0NzEyNzQxODMz | 2,803 | add stack exchange | [] | closed | false | null | 2 | 2021-08-14T08:11:02Z | 2021-08-19T10:07:33Z | 2021-08-19T08:07:38Z | null | stack exchange is part of EleutherAI/The Pile, but AFAIK, The Pile dataset blend all sub datasets together thus we are not able to use just one of its sub dataset from The Pile data. So I create an independent dataset using The Pile preliminary components.
I also change default `timeout` to 100 seconds instead of 10 seconds, otherwise I keep getting read time out when downloading source data of stack exchange and cc100 dataset.
When I was creating dataset card. I found there is room for creating / editing dataset card. I've made it an issue. #2797
Also I am wondering whether the import of The Pile dataset is actively undertaken (because I may need it recently)? #1675 | {
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"Hi ! Merging this one since it's all good :)\r\n\r\nHowever I think it would also be better to actually rename it `the_pile_stack_exchange` to make things clearer and to avoid name collisions in the future. I would like to do the same for `books3` as well.\r\n\r\nIf you don't mind I'll open a PR to do the renaming... |
https://api.github.com/repos/huggingface/datasets/issues/5456 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5456/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5456/comments | https://api.github.com/repos/huggingface/datasets/issues/5456/events | https://github.com/huggingface/datasets/pull/5456 | 1,553,905,148 | PR_kwDODunzps5IXq92 | 5,456 | feat: tqdm for `to_parquet` | [] | closed | false | null | 2 | 2023-01-23T22:05:38Z | 2023-01-24T11:26:47Z | 2023-01-24T11:17:12Z | null | As described in #5418
I noticed also that the `to_json` function supports multi-workers whereas `to_parquet`, is that not possible/not needed with Parquet or something that hasn't been implemented yet? | {
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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==6.0.0\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/1901 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1901/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1901/comments | https://api.github.com/repos/huggingface/datasets/issues/1901/events | https://github.com/huggingface/datasets/pull/1901 | 810,845,605 | MDExOlB1bGxSZXF1ZXN0NTc1NDY5MDUy | 1,901 | Fix OPUS dataset download errors | [] | closed | false | null | 0 | 2021-02-18T07:39:41Z | 2021-02-18T15:07:20Z | 2021-02-18T09:39:21Z | null | Replace http to https.
https://github.com/huggingface/datasets/issues/854
https://discuss.huggingface.co/t/cannot-download-wmt16/2081
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https://api.github.com/repos/huggingface/datasets/issues/1986 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1986/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1986/comments | https://api.github.com/repos/huggingface/datasets/issues/1986/events | https://github.com/huggingface/datasets/issues/1986 | 822,176,290 | MDU6SXNzdWU4MjIxNzYyOTA= | 1,986 | wmt datasets fail to load | [] | closed | false | null | 1 | 2021-03-04T14:18:55Z | 2021-03-04T14:31:07Z | 2021-03-04T14:31:07Z | null | ~\.cache\huggingface\modules\datasets_modules\datasets\wmt14\43e717d978d2261502b0194999583acb874ba73b0f4aed0ada2889d1bb00f36e\wmt_utils.py in _split_generators(self, dl_manager)
758 # Extract manually downloaded files.
759 manual_files = dl_manager.extract(manual_paths_dict)
--> 760 extraction_map = dict(downloaded_files, **manual_files)
761
762 for language in self.config.language_pair:
TypeError: type object argument after ** must be a mapping, not list | {
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} | https://api.github.com/repos/huggingface/datasets/issues/1986/timeline | null | completed | null | null | false | [
"caching issue, seems to work again.."
] |
https://api.github.com/repos/huggingface/datasets/issues/5325 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5325/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5325/comments | https://api.github.com/repos/huggingface/datasets/issues/5325/events | https://github.com/huggingface/datasets/issues/5325 | 1,471,536,822 | I_kwDODunzps5Xtd62 | 5,325 | map(...batch_size=None) for IterableDataset | [
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"default": true... | closed | false | null | 5 | 2022-12-01T15:43:42Z | 2022-12-07T15:54:43Z | 2022-12-07T15:54:42Z | null | ### Feature request
Dataset.map(...) allows batch_size to be None. It would be nice if IterableDataset did too.
### Motivation
Although it may seem a bit of a spurious request given that `IterableDataset` is meant for larger than memory datasets, but there are a couple of reasons why this might be nice.
One is that load_dataset(...) can return either IterableDataset or Dataset. mypy will then complain if batch_size=None even if we know it is Dataset. Of course we can do:
assert isinstance(d, datasets.DatasetDict)
But it is a mild inconvenience. What's more annoying is that whenever we use something like e.g. `combine_datasets(...)`, we end up with the union again, and so have to do the assert again.
Another is that we could actually end up with an IterableDataset small enough for memory in normal/correct usage, e.g. by filtering a massive IterableDataset.
For practical usages, an alternative to this would be to convert from an iterable dataset to a map-style dataset, but it is not obvious how to do this.
### Your contribution
Not this time. | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5325/timeline | null | completed | null | null | false | [
"Hi! I agree it makes sense for `IterableDataset.map` to support the `batch_size=None` case. This should be super easy to fix.",
"@mariosasko as this is something simple maybe I can include it as part of https://github.com/huggingface/datasets/pull/5311? Let me know :+1:",
"#self-assign",
"Feel free to close ... |
https://api.github.com/repos/huggingface/datasets/issues/3480 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3480/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3480/comments | https://api.github.com/repos/huggingface/datasets/issues/3480/events | https://github.com/huggingface/datasets/issues/3480 | 1,088,267,110 | I_kwDODunzps5A3aNm | 3,480 | the compression format requested when saving a dataset in json format is not respected | [
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] | closed | false | null | 3 | 2021-12-24T09:23:51Z | 2022-01-05T13:03:35Z | 2022-01-05T13:03:35Z | null | ## Describe the bug
In the documentation of the `to_json` method, it is stated in the parameters that
> **to_json_kwargs – Parameters to pass to pandas’s pandas.DataFrame.to_json.
however when we pass for example `compression="gzip"`, the saved file is not compressed.
Would you also have expected compression to be applied? :relaxed:
## Steps to reproduce the bug
```python
my_dict = {"a": [1, 2, 3], "b": [1, 2, 3]}
```
### Result with datasets
```python
from datasets import Dataset
dataset = Dataset.from_dict(my_dict)
dataset.to_json("dic_with_datasets.jsonl.gz", compression="gzip")
!cat dic_with_datasets.jsonl.gz
```
output
```
{"a":1,"b":1}
{"a":2,"b":2}
{"a":3,"b":3}
```
Note: I would expected to see binary data here
### Result with pandas
```python
import pandas as pd
df = pd.DataFrame(my_dict)
df.to_json("dic_with_pandas.jsonl.gz", lines=True, orient="records", compression="gzip")
!cat dic_with_pandas.jsonl.gz
```
output
```
4��a�dic_with_pandas.jsonl��VJT�2�QJ��\� ��g��yƵ���������)���
```
Note: It looks like binary data
## Expected results
I would have expected that the saved result with datasets would also be a binary file
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.1
- Platform: Linux-4.18.0-193.70.1.el8_2.x86_64-x86_64-with-glibc2.17
- Python version: 3.8.11
- PyArrow version: 5.0.0
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} | https://api.github.com/repos/huggingface/datasets/issues/3480/timeline | null | completed | null | null | false | [
"Thanks for reporting @SaulLu.\r\n\r\nAt first sight I think the problem is caused because `pandas` only takes into account the `compression` parameter if called with a non-null file path or buffer. And in our implementation, we call pandas `to_json` with `None` `path_or_buf`.\r\n\r\nWe should fix this:\r\n- either... |
https://api.github.com/repos/huggingface/datasets/issues/5782 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5782/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5782/comments | https://api.github.com/repos/huggingface/datasets/issues/5782/events | https://github.com/huggingface/datasets/issues/5782 | 1,679,622,367 | I_kwDODunzps5kHQDf | 5,782 | Support for various audio-loading backends instead of always relying on SoundFile | [
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] | closed | false | null | 3 | 2023-04-22T17:09:25Z | 2023-05-10T20:23:04Z | 2023-05-10T20:23:04Z | null | ### Feature request
Introduce an option to select from a variety of audio-loading backends rather than solely relying on the SoundFile library. For instance, if the ffmpeg library is installed, it can serve as a fallback loading option.
### Motivation
- The SoundFile library, used in [features/audio.py](https://github.com/huggingface/datasets/blob/649d5a3315f9e7666713b6affe318ee00c7163a0/src/datasets/features/audio.py#L185), supports only a [limited number of audio formats](https://pysoundfile.readthedocs.io/en/latest/index.html?highlight=supported#soundfile.available_formats).
- However, current methods for creating audio datasets permit the inclusion of audio files in formats not supported by SoundFile.
- As a result, developers may potentially create a dataset they cannot read back.
In my most recent project, I dealt with phone call recordings in `.amr` or `.gsm` formats and was genuinely surprised when I couldn't read the dataset I had just packaged a minute prior. Nonetheless, I can still accurately read these files using the librosa library, which employs the audioread library that internally leverages ffmpeg to read such files.
Example:
```python
audio_dataset_amr = Dataset.from_dict({"audio": ["audio_samples/audio.amr"]}).cast_column("audio", Audio())
audio_dataset_amr.save_to_disk("audio_dataset_amr")
audio_dataset_amr = Dataset.load_from_disk("audio_dataset_amr")
print(audio_dataset_amr[0])
```
Results in:
```
Traceback (most recent call last):
...
raise LibsndfileError(err, prefix="Error opening {0!r}: ".format(self.name))
soundfile.LibsndfileError: Error opening <_io.BytesIO object at 0x7f316323e4d0>: Format not recognised.
```
While I acknowledge that support for these rare file types may not be a priority, I believe it's quite unfortunate that it's possible to create an unreadable dataset in this manner.
### Your contribution
I've created a [simple demo repository](https://github.com/BoringDonut/hf-datasets-ffmpeg-audio) that highlights the mentioned issue. It demonstrates how to create an .amr dataset that results in an error when attempting to read it just a few lines later.
Additionally, I've made a [fork with a rudimentary solution](https://github.com/BoringDonut/datasets/blob/fea73a8fbbc8876467c7e6422c9360546c6372d8/src/datasets/features/audio.py#L189) that utilizes ffmpeg to load files not supported by SoundFile.
Here you may see github actions fails to read `.amr` dataset using the version of the current dataset, but will work with the patched version:
- https://github.com/BoringDonut/hf-datasets-ffmpeg-audio/actions/runs/4773780420/jobs/8487063785
- https://github.com/BoringDonut/hf-datasets-ffmpeg-audio/actions/runs/4773780420/jobs/8487063829
As evident from the GitHub action above, this solution resolves the previously mentioned problem.
I'd be happy to create a proper pull request, provide runtime benchmarks and tests if you could offer some guidance on the following:
- Where should I incorporate the ffmpeg (or other backends) code? For example, should I create a new file or simply add a function within the Audio class?
- Is it feasible to pass the audio-loading function as an argument within the current architecture? This would be useful if I know in advance that I'll be reading files not supported by SoundFile.
A few more notes:
- In theory, it's possible to load audio using librosa/audioread since librosa is already expected to be installed. However, librosa [will soon discontinue audioread support](https://github.com/librosa/librosa/blob/aacb4c134002903ae56bbd4b4a330519a5abacc0/librosa/core/audio.py#L227). Moreover, using audioread on its own seems inconvenient because it requires a file [path as input](https://github.com/beetbox/audioread/blob/ff9535df934c48038af7be9617fdebb12078cc07/audioread/__init__.py#L108) and cannot work with bytes already loaded into memory or an open file descriptor (as mentioned in [librosa docs](https://librosa.org/doc/main/generated/librosa.load.html#librosa.load), only SoundFile backend supports an open file descriptor as an input). | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5782/timeline | null | completed | null | null | false | [
"Hi! \r\n\r\nYou can use `set_transform`/`with_transform` to define a custom decoding for audio formats not supported by `soundfile`:\r\n```python\r\naudio_dataset_amr = Dataset.from_dict({\"audio\": [\"audio_samples/audio.amr\"]})\r\n\r\ndef decode_audio(batch):\r\n batch[\"audio\"] = [read_ffmpeg(audio_path) f... |
https://api.github.com/repos/huggingface/datasets/issues/2500 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2500/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2500/comments | https://api.github.com/repos/huggingface/datasets/issues/2500/events | https://github.com/huggingface/datasets/pull/2500 | 920,471,411 | MDExOlB1bGxSZXF1ZXN0NjY5NjE2MjQ1 | 2,500 | Add load_dataset_builder | [] | closed | false | null | 6 | 2021-06-14T14:27:45Z | 2021-07-09T00:08:16Z | 2021-07-05T10:45:58Z | null | Adds the `load_dataset_builder` function. The good thing is that we can reuse this function to load the dataset info without downloading the dataset itself.
TODOs:
- [x] Add docstring and entry in the docs
- [x] Add tests
Closes #2484
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"Hi @mariosasko, thanks for taking on this issue.\r\n\r\nJust a few logistic suggestions, as you are one of our most active contributors ❤️ :\r\n- When you start working on an issue, you can self-assign it to you by commenting on the issue page with the keyword: `#self-assign`; we have implemented a GitHub Action t... |
https://api.github.com/repos/huggingface/datasets/issues/83 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/83/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/83/comments | https://api.github.com/repos/huggingface/datasets/issues/83/events | https://github.com/huggingface/datasets/pull/83 | 616,863,601 | MDExOlB1bGxSZXF1ZXN0NDE2ODkyOTUz | 83 | New datasets | [] | closed | false | null | 0 | 2020-05-12T18:22:27Z | 2020-05-12T18:22:47Z | 2020-05-12T18:22:45Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/81 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/81/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/81/comments | https://api.github.com/repos/huggingface/datasets/issues/81/events | https://github.com/huggingface/datasets/pull/81 | 616,793,010 | MDExOlB1bGxSZXF1ZXN0NDE2ODM1NzE1 | 81 | add tests | [] | closed | false | null | 0 | 2020-05-12T16:28:19Z | 2020-05-13T07:43:57Z | 2020-05-13T07:43:56Z | null | Tests for py_utils functions and for the BaseReader used to read from arrow and parquet.
I also removed unused utils functions. | {
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https://api.github.com/repos/huggingface/datasets/issues/2372 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2372/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2372/comments | https://api.github.com/repos/huggingface/datasets/issues/2372/events | https://github.com/huggingface/datasets/pull/2372 | 894,496,064 | MDExOlB1bGxSZXF1ZXN0NjQ2ODUxODc2 | 2,372 | ConvQuestions benchmark added | [] | closed | false | null | 3 | 2021-05-18T15:16:50Z | 2021-05-26T10:31:45Z | 2021-05-26T10:31:45Z | null | Hello,
I would like to integrate our dataset on conversational QA. The answers are grounded in the KG.
The work was published in CIKM 2019 (https://dl.acm.org/doi/10.1145/3357384.3358016).
We hope for further research on how to deal with the challenges of factoid conversational QA.
Thanks! :) | {
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"Thanks for your helpful comments and suggestions! :)\r\nI integrated the additional fields, and extended some of the README/dataset card.\r\nAnd I actually realized that we had the cc-by-4.0 for the dataset, so this was also changed.",
"I added the answers to the test set actually :)",
"Oh great ! Let me rever... |
https://api.github.com/repos/huggingface/datasets/issues/424 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/424/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/424/comments | https://api.github.com/repos/huggingface/datasets/issues/424/events | https://github.com/huggingface/datasets/pull/424 | 663,858,552 | MDExOlB1bGxSZXF1ZXN0NDU1MTk4MTY0 | 424 | Web of science | [] | closed | false | null | 0 | 2020-07-22T15:38:31Z | 2020-07-23T14:27:58Z | 2020-07-23T14:27:56Z | null | this PR adds the WebofScience dataset
#353 | {
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https://api.github.com/repos/huggingface/datasets/issues/5580 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5580/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5580/comments | https://api.github.com/repos/huggingface/datasets/issues/5580/events | https://github.com/huggingface/datasets/pull/5580 | 1,600,431,792 | PR_kwDODunzps5Kys1c | 5,580 | Support cloud storage in load_dataset via fsspec | [] | closed | false | null | 6 | 2023-02-27T04:06:05Z | 2023-03-11T01:02:49Z | 2023-03-11T00:55:40Z | null | Closes https://github.com/huggingface/datasets/issues/5281
This PR uses fsspec to support datasets on cloud storage (tested manually with GCS). ETags are currently unsupported for cloud storage. In general, a much larger refactor could be done to just use fsspec for all schemes (ftp, http/s, s3, gcs) to unify the interfaces here, but I ultimately opted to leave that out of this PR
I didn't create a GCS filesystem class in `datasets.filesystems` since the S3 one appears to be a wrapper around `s3fs.S3FileSystem` and mainly used to generate docs. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> Regarding the tests I think it should be possible to use the mockfs fixture, it allows to play with a dummy fsspec FileSystem with the \"mock://\" protocol.\r\n\r\n> However it requires some storage_options to be passed. Maybe it c... |
https://api.github.com/repos/huggingface/datasets/issues/1387 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1387/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1387/comments | https://api.github.com/repos/huggingface/datasets/issues/1387/events | https://github.com/huggingface/datasets/pull/1387 | 760,368,355 | MDExOlB1bGxSZXF1ZXN0NTM1MjExODQ1 | 1,387 | Add LIAR dataset | [] | closed | false | null | 2 | 2020-12-09T14:16:55Z | 2020-12-14T18:06:43Z | 2020-12-14T16:23:59Z | null | Add LIAR dataset from [“Liar, Liar Pants on Fire”: A New Benchmark Dataset for Fake News Detection](https://www.aclweb.org/anthology/P17-2067/). | {
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"@lhoestq done! The failing testes don't seem to be related, it seems to be a connection issue, if I understand it correctly.",
"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/1092 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1092/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1092/comments | https://api.github.com/repos/huggingface/datasets/issues/1092/events | https://github.com/huggingface/datasets/pull/1092 | 756,913,134 | MDExOlB1bGxSZXF1ZXN0NTMyMzc5MDY0 | 1,092 | Add Coached Conversation Preference Dataset | [] | closed | false | null | 0 | 2020-12-04T08:36:49Z | 2020-12-20T13:34:00Z | 2020-12-04T13:49:50Z | null | Adding [Coached Conversation Preference Dataset](https://research.google/tools/datasets/coached-conversational-preference-elicitation/)
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https://api.github.com/repos/huggingface/datasets/issues/2865 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2865/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2865/comments | https://api.github.com/repos/huggingface/datasets/issues/2865/events | https://github.com/huggingface/datasets/pull/2865 | 986,460,698 | MDExOlB1bGxSZXF1ZXN0NzI1NjY1ODgx | 2,865 | Add MultiEURLEX dataset | [] | closed | false | null | 6 | 2021-09-02T09:42:24Z | 2021-09-10T11:50:06Z | 2021-09-10T11:50:06Z | null | **Add new MultiEURLEX Dataset**
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource). Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU. As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels); this is multi-label classification task (given the text, predict multiple labels). | {
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"Hi @lhoestq, we have this new cool multilingual dataset coming at EMNLP 2021. It would be really nice if we could have it in Hugging Face asap. Thanks! ",
"Hi @lhoestq, I adopted most of your suggestions:\r\n\r\n- Dummy data files reduced, including the 2 smallest documents per subset JSONL.\r\n- README was upda... |
https://api.github.com/repos/huggingface/datasets/issues/4841 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4841/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4841/comments | https://api.github.com/repos/huggingface/datasets/issues/4841/events | https://github.com/huggingface/datasets/pull/4841 | 1,337,401,243 | PR_kwDODunzps49Gf0I | 4,841 | Update ted_talks_iwslt license to include ND | [] | closed | false | null | 1 | 2022-08-12T16:14:52Z | 2022-08-14T11:15:22Z | 2022-08-14T11:00:22Z | null | Excerpt from the paper's abstract: "Aside from its cultural and social relevance, this content, which is published under the Creative Commons BY-NC-ND license, also represents a precious language resource for the machine translation research community" | {
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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/615 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/615/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/615/comments | https://api.github.com/repos/huggingface/datasets/issues/615/events | https://github.com/huggingface/datasets/issues/615 | 699,410,773 | MDU6SXNzdWU2OTk0MTA3NzM= | 615 | Offset overflow when slicing a big dataset with an array of indices in Pyarrow >= 1.0.0 | [] | closed | false | null | 8 | 2020-09-11T14:50:38Z | 2023-07-03T15:19:33Z | 2020-09-19T16:46:31Z | null | How to reproduce:
```python
from datasets import load_dataset
wiki = load_dataset("wikipedia", "20200501.en", split="train")
wiki[[0]]
---------------------------------------------------------------------------
ArrowInvalid Traceback (most recent call last)
<ipython-input-13-381aedc9811b> in <module>
----> 1 wikipedia[[0]]
~/Desktop/hf/nlp/src/datasets/arrow_dataset.py in __getitem__(self, key)
1069 format_columns=self._format_columns,
1070 output_all_columns=self._output_all_columns,
-> 1071 format_kwargs=self._format_kwargs,
1072 )
1073
~/Desktop/hf/nlp/src/datasets/arrow_dataset.py in _getitem(self, key, format_type, format_columns, output_all_columns, format_kwargs)
1037 )
1038 else:
-> 1039 data_subset = self._data.take(indices_array)
1040
1041 if format_type is not None:
~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/pyarrow/table.pxi in pyarrow.lib.Table.take()
~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/pyarrow/compute.py in take(data, indices, boundscheck)
266 """
267 options = TakeOptions(boundscheck)
--> 268 return call_function('take', [data, indices], options)
269
270
~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/pyarrow/_compute.pyx in pyarrow._compute.call_function()
~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/pyarrow/_compute.pyx in pyarrow._compute.Function.call()
~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
ArrowInvalid: offset overflow while concatenating arrays
```
It seems to work fine with small datasets or with pyarrow 0.17.1 | {
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"Related: https://issues.apache.org/jira/browse/ARROW-9773\r\n\r\nIt's definitely a size thing. I took a smaller dataset with 87000 rows and did:\r\n```\r\nfor i in range(10,1000,20):\r\n table = pa.concat_tables([dset._data]*i)\r\n table.take([0])\r\n```\r\nand it broke at around i=300.\r\n\r\nAlso when `_in... |
https://api.github.com/repos/huggingface/datasets/issues/1835 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1835/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1835/comments | https://api.github.com/repos/huggingface/datasets/issues/1835/events | https://github.com/huggingface/datasets/issues/1835 | 803,524,790 | MDU6SXNzdWU4MDM1MjQ3OTA= | 1,835 | Add CHiME4 dataset | [
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"color": "d93f0b",... | open | false | null | 0 | 2021-02-08T12:36:38Z | 2021-02-08T13:13:31Z | null | null | ## Adding a Dataset
- **Name:** Chime4
- **Description:** Chime4 is a dataset for automatic speech recognition. It is especially useful for evaluating models in a noisy environment and for multi-channel ASR
- **Paper:** Dataset comes from a channel: http://spandh.dcs.shef.ac.uk/chime_challenge/CHiME4/ . Results paper:
- **Data:** http://spandh.dcs.shef.ac.uk/chime_challenge/CHiME4/download.html
- **Motivation:** So far there are very little datasets for speech in `datasets`. Only `lbirispeech_asr` so far.
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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https://api.github.com/repos/huggingface/datasets/issues/2797 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2797/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2797/comments | https://api.github.com/repos/huggingface/datasets/issues/2797/events | https://github.com/huggingface/datasets/issues/2797 | 970,331,634 | MDU6SXNzdWU5NzAzMzE2MzQ= | 2,797 | Make creating/editing dataset cards easier, by editing on site and dumping info from test command. | [
{
"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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] | open | false | null | 0 | 2021-08-13T11:54:49Z | 2021-08-14T08:42:09Z | null | null | **Is your feature request related to a problem? Please describe.**
Creating and editing dataset cards should be but not that easy
- If other else know Some information I don't know (bias of dataset, dataset curation, supported dataset, ...), he/she should know the description on hf.co comes from README.md under github huggingface/datasets/datasets/the dataset, and willing to make a pr to add or fix information.
- Many information is also saved in `dataset_info.json` (citaion, description), but still need to write it down to README.md again.
- Contributor need to pip install and start a local server just for tagging the dataset's size. And contributor may be creating the dataset on lab's server, which can't open a browser.
- if any one proposes a new tag, it doesn't show in the list that another creator see. (a stackoverflow way may be ideal)
- dataset card generator web app doesn't generate the necessary subsecion `Contributions` for us.
**Describe the solution you'd like**
- Everyone (or at least the author/contributor) can edit the description, information, tags of the dataset, on hf.co website. Just like wikipedia+stackoverflow
- We can infer the actual data size, citation, data instance, ... from `dataset_info.json` and `dataset.arrow` via `dataset-cli test`
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https://api.github.com/repos/huggingface/datasets/issues/553 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/553/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/553/comments | https://api.github.com/repos/huggingface/datasets/issues/553/events | https://github.com/huggingface/datasets/pull/553 | 690,143,182 | MDExOlB1bGxSZXF1ZXN0NDc3MDgxNTg2 | 553 | [Fix GitHub Actions] test adding tmate | [] | closed | false | null | 0 | 2020-09-01T13:28:03Z | 2021-05-05T18:24:38Z | 2020-09-03T09:01:13Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5897 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5897/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5897/comments | https://api.github.com/repos/huggingface/datasets/issues/5897/events | https://github.com/huggingface/datasets/pull/5897 | 1,726,135,494 | PR_kwDODunzps5RXJaY | 5,897 | Fix `FixedSizeListArray` casting | [] | closed | false | null | 4 | 2023-05-25T16:26:33Z | 2023-05-26T12:22:04Z | 2023-05-26T11:57:16Z | null | Fix cast on sliced `FixedSizeListArray`s.
Fix #5866 | {
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"<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 | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... |
https://api.github.com/repos/huggingface/datasets/issues/4809 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4809/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4809/comments | https://api.github.com/repos/huggingface/datasets/issues/4809/events | https://github.com/huggingface/datasets/pull/4809 | 1,332,842,747 | PR_kwDODunzps483Y4h | 4,809 | Complete the mlqa dataset card | [] | closed | false | null | 4 | 2022-08-09T07:38:06Z | 2022-08-09T16:26:21Z | 2022-08-09T13:26:43Z | null | I fixed the issue #4808
Details of PR:
- Added languages included in the dataset.
- Added task id and task category.
- Updated the citation information.
Fix #4808. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> Thanks for your contribution, @eldhoittangeorge.\r\n> \r\n> The CI error message: https://github.com/huggingface/datasets/runs/7743526624?check_suite_focus=true\r\n> \r\n> ```\r\n> E ValueError: The following issues have ... |
https://api.github.com/repos/huggingface/datasets/issues/4345 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4345/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4345/comments | https://api.github.com/repos/huggingface/datasets/issues/4345/events | https://github.com/huggingface/datasets/pull/4345 | 1,235,062,787 | PR_kwDODunzps43xrky | 4,345 | Fix never ending GH Action to build documentation | [] | closed | false | null | 1 | 2022-05-13T10:40:10Z | 2022-05-13T11:29:43Z | 2022-05-13T11:22:00Z | null | There was an unclosed code block introduced by:
- #4313
https://github.com/huggingface/datasets/pull/4313/files#diff-f933ce41f71c6c0d1ce658e27de62cbe0b45d777e9e68056dd012ac3eb9324f7R538
This causes the "Make documentation" step in the "Build documentation" workflow to never finish.
- I think this issue should also be addressed in the `doc-builder` lib.
Fix #4346. | {
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] |
https://api.github.com/repos/huggingface/datasets/issues/307 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/307/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/307/comments | https://api.github.com/repos/huggingface/datasets/issues/307/events | https://github.com/huggingface/datasets/issues/307 | 644,187,262 | MDU6SXNzdWU2NDQxODcyNjI= | 307 | Specify encoding for MRPC | [] | closed | false | null | 0 | 2020-06-23T22:24:49Z | 2020-06-25T12:16:09Z | 2020-06-25T12:16:09Z | null | Same as #242, but with MRPC: on Windows, I get a `UnicodeDecodeError` when I try to download the dataset:
```python
dataset = nlp.load_dataset('glue', 'mrpc')
```
```python
Downloading and preparing dataset glue/mrpc (download: Unknown size, generated: Unknown size, total: Unknown size) to C:\Users\Python\.cache\huggingface\datasets\glue\mrpc\1.0.0...
---------------------------------------------------------------------------
UnicodeDecodeError Traceback (most recent call last)
~\Miniconda3\envs\nlp\lib\site-packages\nlp\builder.py in incomplete_dir(dirname)
369 try:
--> 370 yield tmp_dir
371 if os.path.isdir(dirname):
~\Miniconda3\envs\nlp\lib\site-packages\nlp\builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, try_from_hf_gcs, dl_manager, **download_and_prepare_kwargs)
430 verify_infos = not save_infos and not ignore_verifications
--> 431 self._download_and_prepare(
432 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
~\Miniconda3\envs\nlp\lib\site-packages\nlp\builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
482 # Prepare split will record examples associated to the split
--> 483 self._prepare_split(split_generator, **prepare_split_kwargs)
484 except OSError:
~\Miniconda3\envs\nlp\lib\site-packages\nlp\builder.py in _prepare_split(self, split_generator)
663 generator = self._generate_examples(**split_generator.gen_kwargs)
--> 664 for key, record in utils.tqdm(generator, unit=" examples", total=split_info.num_examples, leave=False):
665 example = self.info.features.encode_example(record)
~\Miniconda3\envs\nlp\lib\site-packages\tqdm\notebook.py in __iter__(self, *args, **kwargs)
217 try:
--> 218 for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
219 # return super(tqdm...) will not catch exception
~\Miniconda3\envs\nlp\lib\site-packages\tqdm\std.py in __iter__(self)
1128 try:
-> 1129 for obj in iterable:
1130 yield obj
~\Miniconda3\envs\nlp\lib\site-packages\nlp\datasets\glue\7fc58099eb3983a04c8dac8500b70d27e6eceae63ffb40d7900c977897bb58c6\glue.py in _generate_examples(self, data_file, split, mrpc_files)
514 examples = self._generate_example_mrpc_files(mrpc_files=mrpc_files, split=split)
--> 515 for example in examples:
516 yield example["idx"], example
~\Miniconda3\envs\nlp\lib\site-packages\nlp\datasets\glue\7fc58099eb3983a04c8dac8500b70d27e6eceae63ffb40d7900c977897bb58c6\glue.py in _generate_example_mrpc_files(self, mrpc_files, split)
576 reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
--> 577 for n, row in enumerate(reader):
578 is_row_in_dev = [row["#1 ID"], row["#2 ID"]] in dev_ids
~\Miniconda3\envs\nlp\lib\csv.py in __next__(self)
110 self.fieldnames
--> 111 row = next(self.reader)
112 self.line_num = self.reader.line_num
~\Miniconda3\envs\nlp\lib\encodings\cp1252.py in decode(self, input, final)
22 def decode(self, input, final=False):
---> 23 return codecs.charmap_decode(input,self.errors,decoding_table)[0]
24
UnicodeDecodeError: 'charmap' codec can't decode byte 0x9d in position 1180: character maps to <undefined>
```
The fix is the same: specify `utf-8` encoding when opening the file. The previous fix didn't work as MRPC's download process is different from the others in GLUE.
I am going to propose a new PR :) | {
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https://api.github.com/repos/huggingface/datasets/issues/4554 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4554/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4554/comments | https://api.github.com/repos/huggingface/datasets/issues/4554/events | https://github.com/huggingface/datasets/pull/4554 | 1,283,369,453 | PR_kwDODunzps46Sv_f | 4,554 | Fix WMT dataset loading issue and docs update (Re-opened) | [] | closed | false | null | 1 | 2022-06-24T07:26:16Z | 2022-07-08T15:39:20Z | 2022-07-08T15:27:44Z | null | This PR is a fix for #4354
Changes are made for `wmt14`, `wmt15`, `wmt16`, `wmt17`, `wmt18`, `wmt19` and `wmt_t2t`. And READMEs are updated for the corresponding datasets.
Let me know, if any additional changes are required.
Thanks | {
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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/3379 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3379/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3379/comments | https://api.github.com/repos/huggingface/datasets/issues/3379/events | https://github.com/huggingface/datasets/pull/3379 | 1,071,079,146 | PR_kwDODunzps4vYr7K | 3,379 | iter_archive on zipfiles with better compression type check | [] | closed | false | null | 10 | 2021-12-04T01:04:48Z | 2023-01-24T13:00:19Z | 2023-01-24T12:53:08Z | null | Hello @lhoestq , thank you for your detailed answer on previous PR !
I made this new PR because I misused git on the previous one #3347.
Related issue #3272.
# Comments :
* For extension check I used the `_get_extraction_protocol` function in **download_manager.py** with a slight change and called it `_get_extraction_protocol_local`:
**I removed this part :**
```python
elif path.endswith(".tar.gz") or path.endswith(".tgz"):
raise NotImplementedError(
f"Extraction protocol for TAR archives like '{urlpath}' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead."
)
```
**And also changed :**
```diff
- extension = path.split(".")[-1]
+ extension = "tar" if path.endswith(".tar.gz") else path.split(".")[-1]
```
The reason for this is a compression like **.tar.gz** will be considered a **.gz** which is handled with **zipfile**, though **tar.gz** can only be opened using **tarfile**.
Please tell me if there's anything to change.
# Tasks :
- [x] download_manager.py
- [x] streaming_download_manager.py | {
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"Hello @lhoestq, thank you for your answer.\r\n\r\nI don't use pytest a lot so I think I might need some help on it :) but I tried some tests for `streaming_download_manager.py` only. I don't know how to test `download_manager.py` since we need to use local files.\r\n\r\n# Comments : \r\n* In **download_manager.py*... |
https://api.github.com/repos/huggingface/datasets/issues/2684 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2684/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2684/comments | https://api.github.com/repos/huggingface/datasets/issues/2684/events | https://github.com/huggingface/datasets/pull/2684 | 948,771,753 | MDExOlB1bGxSZXF1ZXN0NjkzNTY0MDY4 | 2,684 | Print absolute local paths in load_dataset error messages | [] | closed | false | null | 0 | 2021-07-20T15:28:28Z | 2021-07-22T20:48:19Z | 2021-07-22T14:01:10Z | null | Use absolute local paths in the error messages of `load_dataset` as per @stas00's suggestion in https://github.com/huggingface/datasets/pull/2500#issuecomment-874891223 | {
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https://api.github.com/repos/huggingface/datasets/issues/928 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/928/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/928/comments | https://api.github.com/repos/huggingface/datasets/issues/928/events | https://github.com/huggingface/datasets/pull/928 | 753,722,324 | MDExOlB1bGxSZXF1ZXN0NTI5NzQ1OTIx | 928 | Add the Multilingual Amazon Reviews Corpus | [] | closed | false | null | 0 | 2020-11-30T18:58:06Z | 2020-12-01T16:04:30Z | 2020-12-01T16:04:27Z | null | - **Name:** Multilingual Amazon Reviews Corpus* (`amazon_reviews_multi`)
- **Description:** A collection of Amazon reviews in English, Japanese, German, French, Spanish and Chinese.
- **Paper:** https://arxiv.org/abs/2010.02573
### Checkbox
- [x] Create the dataset script `/datasets/my_dataset/my_dataset.py` using the template
- [x] Fill the `_DESCRIPTION` and `_CITATION` variables
- [x] Implement `_infos()`, `_split_generators()` and `_generate_examples()`
- [x] Make sure that the `BUILDER_CONFIGS` class attribute is filled with the different configurations of the dataset and that the `BUILDER_CONFIG_CLASS` is specified if there is a custom config class.
- [x] Generate the metadata file `dataset_infos.json` for all configurations
- [x] Generate the dummy data `dummy_data.zip` files to have the dataset script tested and that they don't weigh too much (<50KB)
- [x] Add the dataset card `README.md` using the template : fill the tags and the various paragraphs
- [x] Both tests for the real data and the dummy data pass. | {
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https://api.github.com/repos/huggingface/datasets/issues/4658 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4658/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4658/comments | https://api.github.com/repos/huggingface/datasets/issues/4658/events | https://github.com/huggingface/datasets/issues/4658 | 1,297,001,390 | I_kwDODunzps5NTquu | 4,658 | Transfer CI tests to GitHub Actions | [] | closed | false | null | 0 | 2022-07-07T08:10:50Z | 2022-07-12T11:18:25Z | 2022-07-12T11:18:25Z | null | Let's try CI tests using GitHub Actions to see if they are more stable than on CircleCI. | {
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https://api.github.com/repos/huggingface/datasets/issues/5060 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5060/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5060/comments | https://api.github.com/repos/huggingface/datasets/issues/5060/events | https://github.com/huggingface/datasets/issues/5060 | 1,395,382,940 | I_kwDODunzps5TK9qc | 5,060 | Unable to Use Custom Dataset Locally | [
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"color": "d73a4a",
"default": true,
"description": "Something isn't working",
"id": 1935892857,
"name": "bug",
"node_id": "MDU6TGFiZWwxOTM1ODkyODU3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
}
] | closed | false | null | 4 | 2022-10-03T21:55:16Z | 2022-10-06T14:29:18Z | 2022-10-06T14:29:17Z | null | ## Describe the bug
I have uploaded a [dataset](https://huggingface.co/datasets/zpn/pubchem_selfies) and followed the instructions from the [dataset_loader](https://huggingface.co/docs/datasets/dataset_script#download-data-files-and-organize-splits) tutorial. In that tutorial, it says
```
If the data files live in the same folder or repository of the dataset script,
you can just pass the relative paths to the files instead of URLs.
```
Accordingly, I put the [relative path](https://huggingface.co/datasets/zpn/pubchem_selfies/blob/main/pubchem_selfies.py#L76) to the data to be used. I was able to test the dataset and generate the metadata locally with `datasets-cli test path/to/<your-dataset-loading-script> --save_infos --all_configs`
However, if I try to load the data using `load_dataset`, I get the following error
```
with gzip.open(filepath, mode="rt") as f:
File "/usr/local/Cellar/python@3.9/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/gzip.py", line 58, in open
binary_file = GzipFile(filename, gz_mode, compresslevel)
File "/usr/local/Cellar/python@3.9/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/gzip.py", line 173, in __init__
fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: 'https://huggingface.co/datasets/zpn/pubchem_selfies/resolve/main/data/Compound_021000001_021500000/Compound_021000001_021500000_SELFIES.jsonl.gz'
```
## Steps to reproduce the bug
```python
>>> from datasets import load_dataset
>>> dataset = load_dataset("zpn/pubchem_selfies", streaming=True)
>>> t = dataset["train"]
>>> for item in t:
...... print(item)
...... break
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/zachnussbaum/env/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 723, in __iter__
for key, example in self._iter():
File "/Users/zachnussbaum/env/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 713, in _iter
yield from ex_iterable
File "/Users/zachnussbaum/env/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 113, in __iter__
yield from self.generate_examples_fn(**self.kwargs)
File "/Users/zachnussbaum/.cache/huggingface/modules/datasets_modules/datasets/zpn--pubchem_selfies/d2571f35996765aea70fd3f3f8e3882d59c401fb738615c79282e2eb1d9f7a25/pubchem_selfies.py", line 475, in _generate_examples
with gzip.open(filepath, mode="rt") as f:
File "/usr/local/Cellar/python@3.9/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/gzip.py", line 58, in open
binary_file = GzipFile(filename, gz_mode, compresslevel)
File "/usr/local/Cellar/python@3.9/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/gzip.py", line 173, in __init__
fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: 'https://huggingface.co/datasets/zpn/pubchem_selfies/resolve/main/data/Compound_021000001_021500000/Compound_021000001_021500000_SELFIES.jsonl.gz'
````
```
## Expected results
A clear and concise description of the expected results.
## Actual results
Specify the actual results or traceback.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.5.1
- Platform: macOS-12.5.1-x86_64-i386-64bit
- Python version: 3.9.7
- PyArrow version: 9.0.0
- Pandas version: 1.5.0
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} | https://api.github.com/repos/huggingface/datasets/issues/5060/timeline | null | completed | null | null | false | [
"Hi ! I opened a PR in your repo to fix this :)\r\nhttps://huggingface.co/datasets/zpn/pubchem_selfies/discussions/7\r\n\r\nbasically you need to use `open` for streaming to work properly",
"Thank you so much for this! Naive question, is this a feature of `open` or have you all overloaded it to be able to read fr... |
https://api.github.com/repos/huggingface/datasets/issues/1766 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1766/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1766/comments | https://api.github.com/repos/huggingface/datasets/issues/1766/events | https://github.com/huggingface/datasets/issues/1766 | 792,044,105 | MDU6SXNzdWU3OTIwNDQxMDU= | 1,766 | Issues when run two programs compute the same metrics | [] | closed | false | null | 2 | 2021-01-22T14:22:55Z | 2021-02-02T10:38:06Z | 2021-02-02T10:38:06Z | null | I got the following error when running two different programs that both compute sacreblue metrics. It seems that both read/and/write to the same location (.cache/huggingface/metrics/sacrebleu/default/default_experiment-1-0.arrow) where it caches the batches:
```
File "train_matching_min.py", line 160, in <module>ch_9_label
avg_loss = valid(epoch, args.batch, args.validation, args.with_label)
File "train_matching_min.py", line 93, in valid
bleu += eval.compute()
File "/u/tlhoang/projects/seal/match/models/eval.py", line 23, in compute
return self.metric.compute()['score']
File "/dccstor/know/anaconda3/lib/python3.7/site-packages/datasets/metric.py", line 387, in compute
self._finalize()
File "/dccstor/know/anaconda3/lib/python3.7/site-packages/datasets/metric.py", line 355, in _finalize
self.data = Dataset(**reader.read_files([{"filename": f} for f in file_paths]))
File "/dccstor/know/anaconda3/lib/python3.7/site-packages/datasets/arrow_reader.py", line 231, in read_files
pa_table = self._read_files(files)
File "/dccstor/know/anaconda3/lib/python3.7/site-packages/datasets/arrow_reader.py", line 170, in _read_files
pa_table: pa.Table = self._get_dataset_from_filename(f_dict)
File "/dccstor/know/anaconda3/lib/python3.7/site-packages/datasets/arrow_reader.py", line 299, in _get_dataset_from_filename
pa_table = f.read_all()
File "pyarrow/ipc.pxi", line 481, in pyarrow.lib.RecordBatchReader.read_all
File "pyarrow/error.pxi", line 84, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Expected to read 1819307375 metadata bytes, but only read 454396
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/1766/timeline | null | completed | null | null | false | [
"Hi ! To avoid collisions you can specify a `experiment_id` when instantiating your metric using `load_metric`. It will replace \"default_experiment\" with the experiment id that you provide in the arrow filename. \r\n\r\nAlso when two `experiment_id` collide we're supposed to detect it using our locking mechanism.... |
https://api.github.com/repos/huggingface/datasets/issues/390 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/390/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/390/comments | https://api.github.com/repos/huggingface/datasets/issues/390/events | https://github.com/huggingface/datasets/pull/390 | 656,956,384 | MDExOlB1bGxSZXF1ZXN0NDQ5MTYxMzY3 | 390 | Concatenate datasets | [] | closed | false | null | 6 | 2020-07-14T23:24:37Z | 2020-07-22T09:49:58Z | 2020-07-22T09:49:58Z | null | I'm constructing the "WikiBooks" dataset, which is a concatenation of Wikipedia & BookCorpus. So I implemented the `Dataset.from_concat()` method, which concatenates two datasets with the same schema.
This would also be useful if someone wants to pretrain on a large generic dataset + their own custom dataset. Not in love with the method name, so would love to hear suggestions.
Usage:
```python
from nlp import Dataset, load_dataset
data1, data2 = {"id": [0, 1, 2]}, {"id": [3, 4, 5]}
dset1, dset2 = Dataset.from_dict(data1), Dataset.from_dict(data2)
dset_concat = Dataset.from_concat([dset1, dset2])
print(dset_concat)
# Dataset(schema: {'id': 'int64'}, num_rows: 6)
``` | {
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"Looks cool :)\r\n\r\nI feel like \r\n```python\r\nconcatenated_dataset = dataset1.concatenate(dataset2)\r\n```\r\ncould be more natural. What do you think ?\r\n\r\nAlso could you also concatenate the `nlp.Dataset._data_files` ?\r\n```python\r\nreturn cls(table, info=info, split=split, data_files=self._data_files +... |
https://api.github.com/repos/huggingface/datasets/issues/3456 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3456/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3456/comments | https://api.github.com/repos/huggingface/datasets/issues/3456/events | https://github.com/huggingface/datasets/pull/3456 | 1,084,687,973 | PR_kwDODunzps4wEwXz | 3,456 | [WER] Better error message for wer | [] | closed | false | null | 4 | 2021-12-20T11:38:40Z | 2021-12-20T16:53:37Z | 2021-12-20T16:53:36Z | null | Currently we have the following problem when using the WER. When the input format to the WER metric is wrong, instead of throwing an error message a word-error-rate is computed which is incorrect. E.g. when doing the following:
```python
from datasets import load_metric
wer = load_metric("wer")
target_str = ["hello this is nice", "hello the weather is bloomy"]
pred_str = [["hello it's nice"], ["hello it's the weather"]]
print("Wrong:", wer.compute(predictions=pred_str, references=target_str))
print("Correct", wer.compute(predictions=[x[0] for x in pred_str], references=target_str))
```
We get:
```
Wrong: 1.0
Correct 0.5555555555555556
```
meaning that we get a word-error rate for incorrectly passed input formats. We should raise an error here instead so that people don't spent hours fixing a model while it's their incorrect evaluation metric is the problem for a low WER. | {
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"Hi ! I don't think this would solve this issue.\r\nCurrently it looks like there's a bug that converts the list `[\"hello it's nice\"]` to a string `'[\"hello it's nice\"]'` since this is what the metric expects as input. The conversion is done before the data are passed to `_compute()`.\r\n\r\nThis is `Value(\"st... |
https://api.github.com/repos/huggingface/datasets/issues/3497 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3497/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3497/comments | https://api.github.com/repos/huggingface/datasets/issues/3497/events | https://github.com/huggingface/datasets/issues/3497 | 1,090,050,148 | I_kwDODunzps5A-Nhk | 3,497 | Changing sampling rate in audio dataset and subsequently mapping with `num_proc > 1` leads to weird bug | [
{
"color": "d73a4a",
"default": true,
"description": "Something isn't working",
"id": 1935892857,
"name": "bug",
"node_id": "MDU6TGFiZWwxOTM1ODkyODU3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
}
] | closed | false | null | 2 | 2021-12-28T18:03:49Z | 2022-01-21T13:22:27Z | 2022-01-21T13:22:27Z | null | Running:
```python
from datasets import load_dataset, DatasetDict
import datasets
from transformers import AutoFeatureExtractor
raw_datasets = DatasetDict()
raw_datasets["train"] = load_dataset("common_voice", "ab", split="train")
feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/wav2vec2-base")
raw_datasets = raw_datasets.cast_column(
"audio", datasets.features.Audio(sampling_rate=feature_extractor.sampling_rate)
)
num_workers = 16
def prepare_dataset(batch):
sample = batch["audio"]
inputs = feature_extractor(sample["array"], sampling_rate=sample["sampling_rate"])
batch["input_values"] = inputs.input_values[0]
batch["input_length"] = len(batch["input_values"])
return batch
raw_datasets.map(
prepare_dataset,
remove_columns=next(iter(raw_datasets.values())).column_names,
num_proc=16,
desc="preprocess datasets",
)
```
gives
```bash
File "/home/patrick/experiments/run_bug.py", line 25, in <module>
raw_datasets.map(
File "/home/patrick/python_bin/datasets/dataset_dict.py", line 492, in map
{
File "/home/patrick/python_bin/datasets/dataset_dict.py", line 493, in <dictcomp>
k: dataset.map(
File "/home/patrick/python_bin/datasets/arrow_dataset.py", line 2139, in map
shards = [
File "/home/patrick/python_bin/datasets/arrow_dataset.py", line 2140, in <listcomp>
self.shard(num_shards=num_proc, index=rank, contiguous=True, keep_in_memory=keep_in_memory)
File "/home/patrick/python_bin/datasets/arrow_dataset.py", line 3164, in shard
return self.select(
File "/home/patrick/python_bin/datasets/arrow_dataset.py", line 485, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/patrick/python_bin/datasets/fingerprint.py", line 411, in wrapper
out = func(self, *args, **kwargs)
File "/home/patrick/python_bin/datasets/arrow_dataset.py", line 2756, in select
return self._new_dataset_with_indices(indices_buffer=buf_writer.getvalue(), fingerprint=new_fingerprint)
File "/home/patrick/python_bin/datasets/arrow_dataset.py", line 2667, in _new_dataset_with_indices
return Dataset(
File "/home/patrick/python_bin/datasets/arrow_dataset.py", line 659, in __init__
raise ValueError(
ValueError: External features info don't match the dataset:
Got
{'client_id': Value(dtype='string', id=None), 'path': Value(dtype='string', id=None), 'audio': Audio(sampling_rate=16000, mono=True, _storage_dtype='string', id=None), 'sentence': Value(dtype='string', id=None), 'up_votes': Value(dtype='int64', id=None), 'down_votes': Value(dtype='int64', id=None), 'age': Value(dtype='string', id=None), 'gender': Value(dtype='string', id=None), 'accent': Value(dtype='string', id=None), 'locale': Value(dtype='string', id=None), 'segment': Value(dtype='string', id=None)}
with type
struct<client_id: string, path: string, audio: string, sentence: string, up_votes: int64, down_votes: int64, age: string, gender: string, accent: string, locale: string, segment: string>
but expected something like
{'client_id': Value(dtype='string', id=None), 'path': Value(dtype='string', id=None), 'audio': {'path': Value(dtype='string', id=None), 'bytes': Value(dtype='binary', id=None)}, 'sentence': Value(dtype='string', id=None), 'up_votes': Value(dtype='int64', id=None), 'down_votes': Value(dtype='int64', id=None), 'age': Value(dtype='string', id=None), 'gender': Value(dtype='string', id=None), 'accent': Value(dtype='string', id=None), 'locale': Value(dtype='string', id=None), 'segment': Value(dtype='string', id=None)}
with type
struct<client_id: string, path: string, audio: struct<path: string, bytes: binary>, sentence: string, up_votes: int64, down_votes: int64, age: string, gender: string, accent: string, locale: string, segment: string>
```
Versions:
```python
- `datasets` version: 1.16.2.dev0
- Platform: Linux-5.15.8-76051508-generic-x86_64-with-glibc2.33
- Python version: 3.9.7
- PyArrow version: 6.0.1
```
and `transformers`:
```
- `transformers` version: 4.16.0.dev0
- Platform: Linux-5.15.8-76051508-generic-x86_64-with-glibc2.33
- Python version: 3.9.7
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/3497/timeline | null | completed | null | null | false | [
"Same error occures when using max samples with https://github.com/huggingface/transformers/blob/master/examples/pytorch/speech-recognition/run_speech_recognition_seq2seq.py",
"I'm seeing this too, when using preprocessing_num_workers with \r\nhttps://github.com/huggingface/transformers/blob/master/examples/pytor... |
https://api.github.com/repos/huggingface/datasets/issues/2014 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2014/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2014/comments | https://api.github.com/repos/huggingface/datasets/issues/2014/events | https://github.com/huggingface/datasets/pull/2014 | 825,916,531 | MDExOlB1bGxSZXF1ZXN0NTg3OTY1NDg3 | 2,014 | more explicit method parameters | [] | closed | false | null | 0 | 2021-03-09T13:18:29Z | 2021-03-10T10:08:37Z | 2021-03-10T10:08:36Z | null | re: #2009
not super convinced this is better, and while I usually fight against kwargs here it seems to me that it better conveys the relationship to the `_split_generator` method. | {
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https://api.github.com/repos/huggingface/datasets/issues/972 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/972/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/972/comments | https://api.github.com/repos/huggingface/datasets/issues/972/events | https://github.com/huggingface/datasets/pull/972 | 754,787,314 | MDExOlB1bGxSZXF1ZXN0NTMwNjI0NTI3 | 972 | Add Children's Book Test (CBT) dataset | [] | closed | false | null | 2 | 2020-12-01T22:53:26Z | 2021-03-19T11:30:03Z | 2021-03-19T11:30:03Z | null | Add the Children's Book Test (CBT) from Facebook (Hill et al. 2016).
Sentence completion given a few sentences as context from a children's book. | {
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"Hi @lhoestq,\r\n\r\nI guess this PR can be closed since we merged #2044?\r\n\r\nI have used the same link for the homepage, as it is where the dataset is provided, hope that is okay?",
"Closing in favor of #2044, thanks again :)\r\n\r\n> I have used the same link for the homepage, as it is where the dataset is p... |
https://api.github.com/repos/huggingface/datasets/issues/1335 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1335/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1335/comments | https://api.github.com/repos/huggingface/datasets/issues/1335/events | https://github.com/huggingface/datasets/pull/1335 | 759,705,835 | MDExOlB1bGxSZXF1ZXN0NTM0NjYzNzQ2 | 1,335 | Added Bianet dataset | [] | closed | false | null | 1 | 2020-12-08T19:10:32Z | 2020-12-14T10:00:56Z | 2020-12-14T10:00:56Z | null | Hi :hugs:, This is a PR for [Bianet: A parallel news corpus in Turkish, Kurdish and English; Source](http://opus.nlpl.eu/Bianet.php) dataset | {
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} | true | [
"merging since the Ci is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/4710 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4710/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4710/comments | https://api.github.com/repos/huggingface/datasets/issues/4710/events | https://github.com/huggingface/datasets/pull/4710 | 1,308,958,525 | PR_kwDODunzps47ny0L | 4,710 | Add object detection processing tutorial | [] | closed | false | null | 3 | 2022-07-19T04:23:46Z | 2022-07-21T20:10:35Z | 2022-07-21T19:56:42Z | null | The following adds a quick guide on how to process object detection datasets with `albumentations`. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Great idea! Now that we have more than one task, it makes sense to separate image classification and object detection so it'll be easier for users to follow.",
"@lhoestq do we want to do that in this PR, or should we merge it and l... |
https://api.github.com/repos/huggingface/datasets/issues/235 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/235/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/235/comments | https://api.github.com/repos/huggingface/datasets/issues/235/events | https://github.com/huggingface/datasets/pull/235 | 630,952,297 | MDExOlB1bGxSZXF1ZXN0NDI3OTM1MjQ0 | 235 | Add experimental datasets | [] | closed | false | null | 6 | 2020-06-04T15:54:56Z | 2020-06-12T15:38:55Z | 2020-06-12T15:38:55Z | null | ## Adding an *experimental datasets* folder
After using the 🤗nlp library for some time, I find that while it makes it super easy to create new memory-mapped datasets with lots of cool utilities, a lot of what I want to do doesn't work well with the current `MockDownloader` based testing paradigm, making it hard to share my work with the community.
My suggestion would be to add a **datasets\_experimental** folder so we can start making these new datasets public without having to completely re-think testing for every single one. We would allow contributors to submit dataset PRs in this folder, but require an explanation for why the current testing suite doesn't work for them. We can then aggregate the feedback and periodically see what's missing from the current tests.
I have added a **datasets\_experimental** folder to the repository and S3 bucket with two initial datasets: ELI5 (explainlikeimfive) and a Wikipedia Snippets dataset to support indexing (wiki\_snippets)
### ELI5
#### Dataset description
This allows people to download the [ELI5: Long Form Question Answering](https://arxiv.org/abs/1907.09190) dataset, along with two variants based on the r/askscience and r/AskHistorians. Full Reddit dumps for each month are downloaded from [pushshift](https://files.pushshift.io/reddit/), filtered for submissions and comments from the desired subreddits, then deleted one at a time to save space. The resulting dataset is split into a training, validation, and test dataset for r/explainlikeimfive, r/askscience, and r/AskHistorians respectively, where each item is a question along with all of its high scoring answers.
#### Issues with the current testing
1. the list of files to be downloaded is not pre-defined, but rather determined by parsing an index web page at run time. This is necessary as the name and compression type of the dump files changes from month to month as the pushshift website is maintained. Currently, the dummy folder requires the user to know which files will be downloaded.
2. to save time, the script works on the compressed files using the corresponding python packages rather than first running `download\_and\_extract` then filtering the extracted files.
### Wikipedia Snippets
#### Dataset description
This script creates a *snippets* version of a source Wikipedia dataset: each article is split into passages of fixed length which can then be indexed using ElasticSearch or a dense indexer. The script currently handles all **wikipedia** and **wiki40b** source datasets, and allows the user to choose the passage length and how much overlap they want across passages. In addition to the passage text, each snippet also has the article title, list of titles of sections covered by the text, and information to map the passage back to the initial dataset at the paragraph and character level.
#### Issues with the current testing
1. The DatasetBuilder needs to call `nlp.load_dataset()`. Currently, testing is not recursive (the test doesn't know where to find the dummy data for the source dataset)
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"I think it would be nicer to not create a new folder `datasets_experimental` , but just put your datasets also into the folder `datasets` for the following reasons:\r\n\r\n- From my point of view, the datasets are not very different from the other datasets (assuming that we soon have C4, and the beam datasets) so ... |
https://api.github.com/repos/huggingface/datasets/issues/5725 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5725/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5725/comments | https://api.github.com/repos/huggingface/datasets/issues/5725/events | https://github.com/huggingface/datasets/issues/5725 | 1,660,455,202 | I_kwDODunzps5i-Iki | 5,725 | How to limit the number of examples in dataset, for testing? | [] | closed | false | null | 3 | 2023-04-10T08:41:43Z | 2023-04-21T06:16:24Z | 2023-04-21T06:16:24Z | null | ### Describe the bug
I am using this command:
`data = load_dataset("json", data_files=data_path)`
However, I want to add a parameter, to limit the number of loaded examples to be 10, for development purposes, but can't find this simple parameter.
### Steps to reproduce the bug
In the description.
### Expected behavior
To be able to limit the number of examples
### Environment info
Nothing special | {
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"Hi! You can use the `nrows` parameter for this:\r\n```python\r\ndata = load_dataset(\"json\", data_files=data_path, nrows=10)\r\n```",
"@mariosasko I get:\r\n\r\n`TypeError: __init__() got an unexpected keyword argument 'nrows'`",
"I misread the format in which the dataset is stored - the `nrows` parameter wo... |
https://api.github.com/repos/huggingface/datasets/issues/4531 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4531/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4531/comments | https://api.github.com/repos/huggingface/datasets/issues/4531/events | https://github.com/huggingface/datasets/issues/4531 | 1,277,054,172 | I_kwDODunzps5MHkzc | 4,531 | Dataset Viewer issue for CSV datasets | [
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] | closed | false | null | 2 | 2022-06-20T14:56:24Z | 2022-06-21T08:28:46Z | 2022-06-21T08:28:27Z | null | ### Link
https://huggingface.co/datasets/scikit-learn/breast-cancer-wisconsin
### Description
I'm populating CSV datasets [here](https://huggingface.co/scikit-learn) but the viewer is not enabled and it looks for a dataset loading script, the datasets aren't on queue as well.
You can replicate the problem by simply uploading any CSV dataset.
### Owner
Yes | {
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"this should now be fixed",
"Confirmed, it's fixed now. Thanks for reporting, and thanks @coyotte508 for fixing it\r\n\r\n<img width=\"1123\" alt=\"Capture d’écran 2022-06-21 à 10 28 05\" src=\"https://user-images.githubusercontent.com/1676121/174753833-1b453a5a-6a90-4717-bca1-1b5fc6b75e4a.png\">\r\n"
] |
https://api.github.com/repos/huggingface/datasets/issues/2292 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2292/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2292/comments | https://api.github.com/repos/huggingface/datasets/issues/2292/events | https://github.com/huggingface/datasets/pull/2292 | 871,230,183 | MDExOlB1bGxSZXF1ZXN0NjI2MjgzNTYy | 2,292 | Fixed typo seperate->separate | [] | closed | false | null | 0 | 2021-04-29T16:40:53Z | 2021-04-30T13:29:18Z | 2021-04-30T13:03:12Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/3259 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3259/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3259/comments | https://api.github.com/repos/huggingface/datasets/issues/3259/events | https://github.com/huggingface/datasets/pull/3259 | 1,052,189,775 | PR_kwDODunzps4ud5W3 | 3,259 | Updating details of IRC disentanglement data | [] | closed | false | null | 1 | 2021-11-12T17:16:58Z | 2021-11-18T17:19:33Z | 2021-11-18T17:19:33Z | null | I was pleasantly surprised to find that someone had already added my dataset to the huggingface library, but some details were missing or incorrect. This PR fixes the documentation. | {
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"Thank you for the cleanup!"
] |
https://api.github.com/repos/huggingface/datasets/issues/3067 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3067/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3067/comments | https://api.github.com/repos/huggingface/datasets/issues/3067/events | https://github.com/huggingface/datasets/pull/3067 | 1,024,023,185 | PR_kwDODunzps4tFSCy | 3,067 | add story_cloze | [] | closed | false | null | 4 | 2021-10-12T16:36:53Z | 2021-10-13T13:48:13Z | 2021-10-13T13:48:13Z | null | null | {
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"Thanks for pushing this dataset :)\r\n\r\nAccording to the CI, the file `cloze_test_val__spring2016 - cloze_test_ALL_val.csv` is missing in the dummy data zip file (the zip files seem empty). Feel free to add this file with 4-5 lines and it should be good\r\n\r\nAnd you can fix the YAML tags with\r\n```yaml\r\npre... |
https://api.github.com/repos/huggingface/datasets/issues/3249 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3249/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3249/comments | https://api.github.com/repos/huggingface/datasets/issues/3249/events | https://github.com/huggingface/datasets/pull/3249 | 1,050,193,138 | PR_kwDODunzps4uXeea | 3,249 | Fix streaming for id_newspapers_2018 | [] | closed | false | null | 0 | 2021-11-10T18:55:30Z | 2021-11-12T14:01:32Z | 2021-11-12T14:01:31Z | null | To be compatible with streaming, this dataset must use `dl_manager.iter_archive` since the data are in a .tgz file | {
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https://api.github.com/repos/huggingface/datasets/issues/1545 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1545/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1545/comments | https://api.github.com/repos/huggingface/datasets/issues/1545/events | https://github.com/huggingface/datasets/pull/1545 | 765,550,283 | MDExOlB1bGxSZXF1ZXN0NTM4OTg3OTY0 | 1,545 | add hrwac | [] | closed | false | null | 1 | 2020-12-13T17:31:54Z | 2020-12-18T13:35:17Z | 2020-12-18T13:35:17Z | null | {
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"merging since the CI is fixed on master"
] | |
https://api.github.com/repos/huggingface/datasets/issues/3661 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3661/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3661/comments | https://api.github.com/repos/huggingface/datasets/issues/3661/events | https://github.com/huggingface/datasets/pull/3661 | 1,121,000,251 | PR_kwDODunzps4x61ad | 3,661 | Remove unnecessary 'r' arg in | [] | closed | false | null | 1 | 2022-02-01T17:29:27Z | 2022-02-07T16:57:27Z | 2022-02-07T16:02:42Z | null | Originally from #3489 | {
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"The CI failure is only because of the datasets is missing some sections in their cards - we can ignore that since it's unrelated to this PR"
] |
https://api.github.com/repos/huggingface/datasets/issues/4382 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4382/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4382/comments | https://api.github.com/repos/huggingface/datasets/issues/4382/events | https://github.com/huggingface/datasets/issues/4382 | 1,243,839,783 | I_kwDODunzps5KI30n | 4,382 | First time trying | [
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] | closed | false | null | 0 | 2022-05-21T02:15:18Z | 2022-05-21T19:20:44Z | 2022-05-21T19:20:44Z | null | ## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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https://api.github.com/repos/huggingface/datasets/issues/5498 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5498/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5498/comments | https://api.github.com/repos/huggingface/datasets/issues/5498/events | https://github.com/huggingface/datasets/issues/5498 | 1,568,190,529 | I_kwDODunzps5deLBB | 5,498 | TypeError: 'bool' object is not iterable when filtering a datasets.arrow_dataset.Dataset | [] | closed | false | null | 2 | 2023-02-02T14:46:49Z | 2023-02-04T17:19:37Z | 2023-02-04T17:19:36Z | null | ### Describe the bug
Hi,
Thanks for the amazing work on the library!
**Describe the bug**
I think I might have noticed a small bug in the filter method.
Having loaded a dataset using `load_dataset`, when I try to filter out empty entries with `batched=True`, I get a TypeError.
### Steps to reproduce the bug
```
train_dataset = train_dataset.filter(
function=lambda example: example["image"] is not None,
batched=True,
batch_size=10)
```
Error message:
```
File .../lib/python3.9/site-packages/datasets/fingerprint.py:480, in fingerprint_transform.<locals>._fingerprint.<locals>.wrapper(*args, **kwargs)
476 validate_fingerprint(kwargs[fingerprint_name])
478 # Call actual function
--> 480 out = func(self, *args, **kwargs)
...
-> 5666 indices_array = [i for i, to_keep in zip(indices, mask) if to_keep]
5667 if indices_mapping is not None:
5668 indices_array = pa.array(indices_array, type=pa.uint64())
TypeError: 'bool' object is not iterable
```
**Removing batched=True allows to bypass the issue.**
### Expected behavior
According to the doc, "[batch_size corresponds to the] number of examples per batch provided to function if batched = True", so we shouldn't need to remove the batchd=True arg?
source: https://huggingface.co/docs/datasets/v2.9.0/en/package_reference/main_classes#datasets.Dataset.filter
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-5.4.0-122-generic-x86_64-with-glibc2.31
- Python version: 3.9.10
- PyArrow version: 10.0.1
- Pandas version: 1.5.3 | {
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"Hi! Instead of a single boolean, your filter function should return an iterable (of booleans) in the batched mode like so:\r\n```python\r\ntrain_dataset = train_dataset.filter(\r\n function=lambda batch: [image is not None for image in batch[\"image\"]], \r\n batched=True,\r\n batc... |
https://api.github.com/repos/huggingface/datasets/issues/3273 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3273/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3273/comments | https://api.github.com/repos/huggingface/datasets/issues/3273/events | https://github.com/huggingface/datasets/issues/3273 | 1,053,554,038 | I_kwDODunzps4-y_V2 | 3,273 | Respect row ordering when concatenating datasets along axis=1 | [
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] | closed | false | null | 0 | 2021-11-15T11:27:14Z | 2021-11-17T15:41:11Z | 2021-11-17T15:41:11Z | null | Currently, there is a bug when concatenating datasets along `axis=1` if more than one dataset has the `_indices` attribute defined. In that scenario, all indices mappings except the first one get ignored.
A minimal reproducible example:
```python
>>> from datasets import Dataset, concatenate_datasets
>>> a = Dataset.from_dict({"a": [30, 20, 10]})
>>> b = Dataset.from_dict({"b": [2, 1, 3]})
>>> d = concatenate_datasets([a.sort("a"), b.sort("b")], axis=1)
>>> print(d[:3]) # expected: {'a': [10, 20, 30], 'b': [1, 2, 3]}
{'a': [10, 20, 30], 'b': [3, 1, 2]}
```
I've noticed the bug while working on #3195. | {
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https://api.github.com/repos/huggingface/datasets/issues/710 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/710/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/710/comments | https://api.github.com/repos/huggingface/datasets/issues/710/events | https://github.com/huggingface/datasets/pull/710 | 714,186,999 | MDExOlB1bGxSZXF1ZXN0NDk3MzQ1NjQ0 | 710 | fix README typos/ consistency | [] | closed | false | null | 0 | 2020-10-03T22:20:56Z | 2020-10-17T09:52:45Z | 2020-10-17T09:52:45Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/838 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/838/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/838/comments | https://api.github.com/repos/huggingface/datasets/issues/838/events | https://github.com/huggingface/datasets/pull/838 | 740,328,382 | MDExOlB1bGxSZXF1ZXN0NTE4ODM0NTE5 | 838 | CNN/Dailymail Dataset Card | [] | closed | false | null | 0 | 2020-11-10T23:56:43Z | 2020-11-25T21:09:51Z | 2020-11-25T21:09:50Z | null | Link to the card page: https://github.com/mcmillanmajora/datasets/tree/cnn_dailymail_card/datasets/cnn_dailymail
One of the questions this dataset brings up is how we want to handle versioning of the cards to mirror versions of the dataset. The different versions of this dataset are used for different tasks (which may not be reflected in the versions that we currently have in the repo?), but it's only the structure that's changing rather than the content in this particular case, at least between versions 2.0.0 and 3.0.0. | {
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https://api.github.com/repos/huggingface/datasets/issues/1715 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1715/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1715/comments | https://api.github.com/repos/huggingface/datasets/issues/1715/events | https://github.com/huggingface/datasets/pull/1715 | 782,754,441 | MDExOlB1bGxSZXF1ZXN0NTUyMjM2NDA5 | 1,715 | add Korean intonation-aided intention identification dataset | [] | closed | false | null | 0 | 2021-01-10T06:29:04Z | 2021-09-17T16:54:13Z | 2021-01-12T17:14:33Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4967 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4967/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4967/comments | https://api.github.com/repos/huggingface/datasets/issues/4967/events | https://github.com/huggingface/datasets/pull/4967 | 1,369,092,452 | PR_kwDODunzps4-vbS- | 4,967 | Strip "/" in local dataset path to avoid empty dataset name error | [] | closed | false | null | 2 | 2022-09-11T23:09:16Z | 2022-09-29T10:46:21Z | 2022-09-12T15:30:38Z | null | null | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Cool :-)"
] |
https://api.github.com/repos/huggingface/datasets/issues/5962 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5962/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5962/comments | https://api.github.com/repos/huggingface/datasets/issues/5962/events | https://github.com/huggingface/datasets/issues/5962 | 1,761,589,882 | I_kwDODunzps5o_7p6 | 5,962 | Issue with train_test_split maintaining the same underlying PyArrow Table | [] | open | false | null | 0 | 2023-06-17T02:19:58Z | 2023-06-17T02:19:58Z | null | null | ### Describe the bug
I've been using the train_test_split method in the datasets module to split my HuggingFace Dataset into separate training, validation, and testing subsets. However, I've noticed an issue where the split datasets appear to maintain the same underlying PyArrow Table.
### Steps to reproduce the bug
1. Load any dataset ```dataset = load_dataset("lhoestq/demo1")```
2. Try the next code:
```python
from datasets import Dataset, DatasetDict
train_size = 0.6
split_train = dataset["train"].train_test_split(
train_size=train_size,
)
separate_dataset_dict = DatasetDict({
"train": split_train["train"],
"test": split_train["test"],
})
```
3. The next code ```print(separate_dataset_dict)``` when printing the dataset it gives the indication that they have 3 and 2 rows respectively.
4. But the next code:
```python
print(len(separate_dataset_dict["train"].data['id']))
print(len(separate_dataset_dict["test"].data['id']))
```
Indicates that both tables still have 5 rows.
### Expected behavior
However, I've noticed that train_test_split["train"].data, test_val_split["train"].data, and test_val_split["test"].data are identical, suggesting that they all point to the same underlying PyArrow Table. This means that the split datasets are not independent, as I expected.
I believe this is a bug in the train_test_split implementation, as I would expect this function to return datasets with separate underlying PyArrow Tables. Could you please help me understand if this is expected behavior, or if there's a workaround to create truly independent split datasets?
I would appreciate any assistance with this issue. Thank you.
### Environment info
I tried in Colab:
- `datasets` version: 2.13.0
- Platform: Windows-10-10.0.22621-SP0
- Python version: 3.10.11
- Huggingface_hub version: 0.14.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.1
and my PC:
- `datasets` version: 2.13.0
- Platform: Linux-5.15.107+-x86_64-with-glibc2.31
- Python version: 3.10.12
- Huggingface_hub version: 0.15.1
- PyArrow version: 9.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/5450 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5450/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5450/comments | https://api.github.com/repos/huggingface/datasets/issues/5450/events | https://github.com/huggingface/datasets/issues/5450 | 1,551,109,365 | I_kwDODunzps5cdAz1 | 5,450 | to_tf_dataset with a TF collator causes bizarrely persistent slowdown | [] | closed | false | null | 7 | 2023-01-20T16:08:37Z | 2023-02-13T14:13:34Z | 2023-02-13T14:13:34Z | null | ### Describe the bug
This will make more sense if you take a look at [a Colab notebook that reproduces this issue.](https://colab.research.google.com/drive/1rxyeciQFWJTI0WrZ5aojp4Ls1ut18fNH?usp=sharing)
Briefly, there are several datasets that, when you iterate over them with `to_tf_dataset` **and** a data collator that returns `tf` tensors, become very slow. We haven't been able to figure this one out - it can be intermittent, and we have no idea what could possibly cause it. The weirdest thing is that **the slowdown affects other attempts to access the underlying dataset**. If you try to iterate over the `tf.data.Dataset`, then interrupt execution, and then try to iterate over the original dataset, the original dataset is now also very slow! This is true even if the dataset format is not set to `tf` - the iteration is slow even though it's not calling TF at all!
There is a simple workaround for this - we can simply get our data collators to return `np` tensors. When we do this, the bug is never triggered and everything is fine. In general, `np` is preferred for this kind of preprocessing work anyway, when the preprocessing is not going to be compiled into a pure `tf.data` pipeline! However, the issue is fascinating, and the TF team were wondering if anyone in datasets (cc @lhoestq @mariosasko) might have an idea of what could cause this.
### Steps to reproduce the bug
Run the attached Colab.
### Expected behavior
The slowdown should go away, or at least not persist after we stop iterating over the `tf.data.Dataset`
### Environment info
The issue occurs on multiple versions of Python and TF, both on local machines and on Colab.
All testing was done using the latest versions of `transformers` and `datasets` from `main` | {
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"wtf",
"Couldn't find what's causing this, this will need more investigation",
"A possible hint: The function it seems to be spending a lot of time in (when iterating over the original dataset) is `_get_mp` in the PIL JPEG decoder: \r\n: https://arxiv.org/abs/1906.05394 | {
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"you can rebase from master to fix the CI error :)",
"Awesome !"
] |
https://api.github.com/repos/huggingface/datasets/issues/1721 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1721/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1721/comments | https://api.github.com/repos/huggingface/datasets/issues/1721/events | https://github.com/huggingface/datasets/pull/1721 | 783,828,428 | MDExOlB1bGxSZXF1ZXN0NTUzMTIyODQ5 | 1,721 | [Scientific papers] Mirror datasets zip | [] | closed | false | null | 4 | 2021-01-12T01:15:40Z | 2021-01-12T11:49:15Z | 2021-01-12T11:41:47Z | null | Datasets were uploading to https://s3.amazonaws.com/datasets.huggingface.co/scientific_papers/1.1.1/arxiv-dataset.zip and https://s3.amazonaws.com/datasets.huggingface.co/scientific_papers/1.1.1/pubmed-dataset.zip respectively to escape google drive quota and enable faster download. | {
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"> Nice !\r\n> \r\n> Could you try to reduce the size of the dummy_data.zip files ? they're quite big (300KB)\r\n\r\nYes, I think it might make sense to enhance the tool a tiny bit to prevent this automatically",
"That's the lightest I can make it...it's long-range summarization so a single sample has ~11000 toke... |
https://api.github.com/repos/huggingface/datasets/issues/2738 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2738/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2738/comments | https://api.github.com/repos/huggingface/datasets/issues/2738/events | https://github.com/huggingface/datasets/pull/2738 | 957,517,746 | MDExOlB1bGxSZXF1ZXN0NzAwOTI5NzA4 | 2,738 | Sunbird AI Ugandan low resource language dataset | [
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] | closed | false | null | 4 | 2021-08-01T15:18:00Z | 2022-10-03T09:37:30Z | 2022-10-03T09:37:30Z | null | Multi-way parallel text corpus of 5 key Ugandan languages for the task of machine translation. | {
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"Hi @ak3ra , have you had a chance to take my comments into account ?\r\n\r\nLet me know if you have questions or if I can help :)",
"@lhoestq Working on this, thanks for the detailed review :) ",
"Hi ! Cool thanks :)\r\nFeel free to merge master into your branch to fix the CI issues\r\n\r\nLet me know if you ... |
https://api.github.com/repos/huggingface/datasets/issues/890 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/890/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/890/comments | https://api.github.com/repos/huggingface/datasets/issues/890/events | https://github.com/huggingface/datasets/pull/890 | 751,534,050 | MDExOlB1bGxSZXF1ZXN0NTI4MDI5NjA3 | 890 | Add LER | [] | closed | false | null | 9 | 2020-11-26T11:58:23Z | 2020-12-01T13:33:35Z | 2020-12-01T13:26:16Z | null | {
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"Thanks for the comments. I addressed them and pushed again.\r\nWhen I run \"make quality\" I get the following error but I don't know how to resolve it or what the problem ist respectively:\r\nwould reformat /Users/joelniklaus/NextCloud/PhDJoelNiklaus/Code/datasets/datasets/ler/ler.py\r\nOh no! 💥 💔 💥\r\n1 file ... | |
https://api.github.com/repos/huggingface/datasets/issues/4464 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4464/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4464/comments | https://api.github.com/repos/huggingface/datasets/issues/4464/events | https://github.com/huggingface/datasets/pull/4464 | 1,265,682,931 | PR_kwDODunzps45XlWW | 4,464 | Extend support for streaming datasets that use xml.dom.minidom.parse | [] | closed | false | null | 1 | 2022-06-09T06:58:25Z | 2022-06-09T08:43:24Z | 2022-06-09T08:34:16Z | null | This PR extends the support in streaming mode for datasets that use `xml.dom.minidom.parse`, by patching that function.
This PR adds support for streaming datasets like "Yaxin/SemEval2015".
Fix #4453. | {
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] |
https://api.github.com/repos/huggingface/datasets/issues/5443 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5443/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5443/comments | https://api.github.com/repos/huggingface/datasets/issues/5443/events | https://github.com/huggingface/datasets/pull/5443 | 1,550,178,914 | PR_kwDODunzps5ILbk8 | 5,443 | Update share tutorial | [] | closed | false | null | 2 | 2023-01-20T01:09:14Z | 2023-01-20T15:44:45Z | 2023-01-20T15:37:30Z | null | Based on feedback from discussion #5423, this PR updates the sharing tutorial with a mention of writing your own dataset loading script to support more advanced dataset creation options like multiple configs.
I'll open a separate PR to update the *Create a Dataset card* with the new Hub metadata UI update 😄 | {
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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==6.0.0\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/1561 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1561/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1561/comments | https://api.github.com/repos/huggingface/datasets/issues/1561/events | https://github.com/huggingface/datasets/pull/1561 | 765,831,436 | MDExOlB1bGxSZXF1ZXN0NTM5MTAwNjAy | 1,561 | Lama | [] | closed | false | null | 6 | 2020-12-14T03:27:10Z | 2020-12-28T09:51:47Z | 2020-12-28T09:51:47Z | null | This the LAMA dataset for probing facts and common sense from language models.
See https://github.com/facebookresearch/LAMA for more details. | {
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"Let me know why the pyarrow test is failing. For one of the config \"trex\", I had to load an initial datafile for a dictionary which is used to augment the rest of the datasets. In the dummy data, the dictionary file was truncated so I had to fudge that. I'm not sure if that is the issue.\r\n",
"@ontocord it ju... |
https://api.github.com/repos/huggingface/datasets/issues/7 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7/comments | https://api.github.com/repos/huggingface/datasets/issues/7/events | https://github.com/huggingface/datasets/pull/7 | 601,780,534 | MDExOlB1bGxSZXF1ZXN0NDA0OTgyMzA2 | 7 | Fix issue 5: allow empty datasets | [] | closed | false | null | 0 | 2020-04-17T07:59:56Z | 2020-04-29T09:27:13Z | 2020-04-20T13:23:48Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/3550 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3550/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3550/comments | https://api.github.com/repos/huggingface/datasets/issues/3550/events | https://github.com/huggingface/datasets/issues/3550 | 1,096,522,377 | I_kwDODunzps5BW5qJ | 3,550 | Bug in `openbookqa` dataset | [
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"descrip... | closed | false | null | 1 | 2022-01-07T17:32:57Z | 2022-05-04T06:33:00Z | 2022-05-04T06:32:19Z | null | ## Describe the bug
Dataset entries contains a typo.
## Steps to reproduce the bug
```python
>>> from datasets import load_dataset
>>> obqa = load_dataset('openbookqa', 'main')
>>> obqa['train'][0]
```
## Expected results
```python
{'id': '7-980', 'question_stem': 'The sun is responsible for', 'choices': {'text': ['puppies learning new tricks', 'children growing up and getting old', 'flowers wilting in a vase', 'plants sprouting, blooming and wilting'], 'label': ['A', 'B', 'C', 'D']}, 'answerKey': 'D'}
```
## Actual results
```python
{'id': '7-980', 'question_stem': 'The sun is responsible for', 'choices': {'text': ['puppies learning new tricks', 'children growing up and getting old', 'flowers wilting in a vase', 'plants sprouting, blooming and wilting'], 'label': ['puppies learning new tricks', 'children growing up and getting old', 'flowers wilting in a vase', 'plants sprouting, blooming and wilting']}, 'answerKey': 'D'}
```
The bug is present in all configs and all splits.
## Environment info
- `datasets` version: 1.17.0
- Platform: Linux-5.4.0-1057-aws-x86_64-with-glibc2.27
- Python version: 3.9.7
- PyArrow version: 4.0.1
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"Closed by:\r\n- #4259"
] |
https://api.github.com/repos/huggingface/datasets/issues/4952 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4952/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4952/comments | https://api.github.com/repos/huggingface/datasets/issues/4952/events | https://github.com/huggingface/datasets/pull/4952 | 1,366,354,604 | PR_kwDODunzps4-meM0 | 4,952 | Add test-datasets CI job | [] | closed | false | null | 2 | 2022-09-08T13:38:30Z | 2022-09-16T13:28:02Z | 2022-09-16T13:25:48Z | null | To avoid having too many conflicts in the datasets and metrics dependencies I split the CI into test and test-catalog
test does the test of the core of the `datasets` lib, while test-catalog tests the datasets scripts and metrics scripts
This also makes `pip install -e .[dev]` much smaller for developers
WDYT @albertvillanova ? | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Closing this one since the dataset scripts will be removed in https://github.com/huggingface/datasets/pull/4974"
] |
https://api.github.com/repos/huggingface/datasets/issues/1473 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1473/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1473/comments | https://api.github.com/repos/huggingface/datasets/issues/1473/events | https://github.com/huggingface/datasets/pull/1473 | 762,055,694 | MDExOlB1bGxSZXF1ZXN0NTM2NjQyODI5 | 1,473 | add srwac | [] | closed | false | null | 2 | 2020-12-11T08:20:29Z | 2020-12-17T11:40:59Z | 2020-12-17T11:40:59Z | null | {
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"Connection error failed. Need rerun",
"merging since the CI is fixed on master"
] | |
https://api.github.com/repos/huggingface/datasets/issues/3339 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3339/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3339/comments | https://api.github.com/repos/huggingface/datasets/issues/3339/events | https://github.com/huggingface/datasets/issues/3339 | 1,066,662,477 | I_kwDODunzps4_k_pN | 3,339 | to_tf_dataset fails on TPU | [
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] | open | false | null | 5 | 2021-11-30T00:50:52Z | 2021-12-02T14:21:27Z | null | null | Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGouFxqD4OuWfnycW_1TaT276z?usp=sharing
## Expected results
dataset from `to_tf_dataset` works in `model.fit`
Right below the first error in the colab I use `tf.data.Dataset.from_tensor_slices` and `model.fit` works just fine. This is the desired outcome.
## Actual results
```
InternalError: 5 root error(s) found.
(0) INTERNAL: {{function_node __inference_train_function_30558}} failed to connect to all addresses
Additional GRPC error information from remote target /job:localhost/replica:0/task:0/device:CPU:0:
:{"created":"@1638231897.932218653","description":"Failed to pick subchannel","file":"third_party/grpc/src/core/ext/filters/client_channel/client_channel.cc","file_line":3151,"referenced_errors":[{"created":"@1638231897.932216754","description":"failed to connect to all addresses","file":"third_party/grpc/src/core/lib/transport/error_utils.cc","file_line":161,"grpc_status":14}]}
[[{{node StatefulPartitionedCall}}]]
[[MultiDeviceIteratorGetNextFromShard]]
Executing non-communication op <MultiDeviceIteratorGetNextFromShard> originally returned UnavailableError, and was replaced by InternalError to avoid invoking TF network error handling logic.
[[RemoteCall]]
[[IteratorGetNextAsOptional]]
[[tpu_compile_succeeded_assert/_14023832043698465348/_7/_439]]
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyArrow version: 3.0.0
- Tensorflow 2.7.0
- `transformers` 4.12.5
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"This might be related to https://github.com/tensorflow/tensorflow/issues/38762 , what do you think @Rocketknight1 ?\r\n> Dataset.from_generator is expected to not work with TPUs as it uses py_function underneath which is incompatible with Cloud TPU 2VM setup. If you would like to read from large datasets, maybe tr... |
https://api.github.com/repos/huggingface/datasets/issues/1345 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1345/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1345/comments | https://api.github.com/repos/huggingface/datasets/issues/1345/events | https://github.com/huggingface/datasets/pull/1345 | 759,835,486 | MDExOlB1bGxSZXF1ZXN0NTM0NzY5NzMw | 1,345 | First commit of NarrativeQA Dataset | [] | closed | false | null | 0 | 2020-12-08T22:31:59Z | 2021-01-25T15:31:52Z | 2020-12-09T09:29:52Z | null | Added NarrativeQA dataset and included a manual downloading option to download scripts from the original scripts provided by the authors. | {
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https://api.github.com/repos/huggingface/datasets/issues/3159 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3159/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3159/comments | https://api.github.com/repos/huggingface/datasets/issues/3159/events | https://github.com/huggingface/datasets/pull/3159 | 1,035,174,560 | PR_kwDODunzps4toKD5 | 3,159 | Make inspect.get_dataset_config_names always return a non-empty list | [] | closed | false | null | 4 | 2021-10-25T13:59:43Z | 2021-10-29T13:14:37Z | 2021-10-28T05:44:49Z | null | Make all named configs cases, so that no special unnamed config case needs to be handled differently.
Fix #3135. | {
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"This PR is already working (although not very beautiful; see below): the idea was to have the `DatasetModule.builder_kwargs` accessible from the `builder_cls`, so that this can generate the default builder config (at the class level, without requiring the builder to be instantiated).\r\n\r\nI have a plan for a fol... |
https://api.github.com/repos/huggingface/datasets/issues/2197 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2197/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2197/comments | https://api.github.com/repos/huggingface/datasets/issues/2197/events | https://github.com/huggingface/datasets/pull/2197 | 854,356,559 | MDExOlB1bGxSZXF1ZXN0NjEyMzEzMzQw | 2,197 | fix missing indices_files in load_form_disk | [] | closed | false | null | 0 | 2021-04-09T09:37:57Z | 2021-04-09T09:54:40Z | 2021-04-09T09:54:39Z | null | This should fix #2195
`load_from_disk` was failing if there was no "_indices_files" field in state.json. This can happen if the dataset has no indices mapping | {
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