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https://api.github.com/repos/huggingface/datasets/issues/5624 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5624/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5624/comments | https://api.github.com/repos/huggingface/datasets/issues/5624/events | https://github.com/huggingface/datasets/issues/5624 | 1,617,400,192 | I_kwDODunzps5gZ5GA | 5,624 | glue datasets returning -1 for test split | {
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"Hi @lithafnium, thanks for reporting.\r\n\r\nPlease note that you can use the \"Community\" tab in the corresponding dataset page to start any discussion: https://huggingface.co/datasets/glue/discussions\r\n\r\nIndeed this issue was already raised there (https://huggingface.co/datasets/glue/discussions/5) and answered: https://huggingface.co/datasets/glue/discussions/5#63907885937867f0cb3cde31\r\n> The test labels are not public.\r\n>\r\n> Note this dataset belongs to a benchmark: people send their predictions for the test split to GLUE (https://gluebenchmark.com/) and then they get a score in their leaderboard...\r\n"
] | "2023-03-09T14:47:18" | "2023-03-09T16:49:29" | "2023-03-09T16:49:29" | NONE | null | ### Describe the bug
Downloading any dataset from GLUE has -1 as class labels for test split. Train and validation have regular 0/1 class labels. This is also present in the dataset card online.
### Steps to reproduce the bug
```
dataset = load_dataset("glue", "sst2")
for d in dataset:
# prints out -1
print(d["label"]
```
### Expected behavior
Expected behavior should be 0/1 instead of -1.
### Environment info
- `datasets` version: 2.4.0
- Platform: Linux-5.15.0-46-generic-x86_64-with-glibc2.17
- Python version: 3.8.16
- PyArrow version: 8.0.0
- Pandas version: 1.5.3
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https://api.github.com/repos/huggingface/datasets/issues/5623 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5623/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5623/comments | https://api.github.com/repos/huggingface/datasets/issues/5623/events | https://github.com/huggingface/datasets/pull/5623 | 1,616,712,665 | PR_kwDODunzps5Lpb4q | 5,623 | Remove set_access_token usage + fail tests if FutureWarning | {
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} | [] | closed | false | null | [] | null | [] | "2023-03-09T08:46:01" | "2023-03-09T15:39:00" | "2023-03-09T15:31:59" | CONTRIBUTOR | null | `set_access_token` is deprecated and will be removed in `huggingface_hub>=0.14`.
This PR removes it from the tests (it was not used in `datasets` source code itself). FYI, it was not needed since `set_access_token` was just setting git credentials and `datasets` doesn't seem to use git anywhere.
In the future, use `set_git_credential` if needed. It is a git-credential-agnostic helper, i.e. you can store your git token in `git-credential-cache`, `git-credential-store`, `osxkeychain`, etc. The legacy `set_access_token` could only set in `git-credential-store` no matter the user preference.
(for context, I found out about this while working on https://github.com/huggingface/huggingface_hub/pull/1381)
---
In addition to this, I have added
```
filterwarnings =
error::FutureWarning:huggingface_hub*
```
to the `setup.cfg` config file to fail on future warnings from `huggingface_hub`. In `hfh`'s CI we trigger on FutureWarning from any package but it's less robust (any package update leads can lead to a failure). No obligation to keep it like that (I can remove it if you prefer) but I think it's a good idea in order to track future FutureWarnings.
FYI, in `huggingface_hub` tests we use `-Werror::FutureWarning --log-cli-level=INFO -sv --durations=0`
- FutureWarning are processed as error
- verbose mode / INFO logs (and above) are captured for easier debugging in github report
- track each test duration, just to see where we can improve. We have a quite long CI (~10min) so it helped improve that. | {
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https://api.github.com/repos/huggingface/datasets/issues/5622 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5622/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5622/comments | https://api.github.com/repos/huggingface/datasets/issues/5622/events | https://github.com/huggingface/datasets/pull/5622 | 1,615,190,942 | PR_kwDODunzps5LkSj8 | 5,622 | Update README template to better template | {
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https://api.github.com/repos/huggingface/datasets/issues/5621 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5621/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5621/comments | https://api.github.com/repos/huggingface/datasets/issues/5621/events | https://github.com/huggingface/datasets/pull/5621 | 1,615,029,615 | PR_kwDODunzps5LjwD8 | 5,621 | Adding Oracle Cloud to docs | {
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} | [] | closed | false | null | [] | null | [] | "2023-03-08T10:22:50" | "2023-03-11T00:57:18" | "2023-03-11T00:49:56" | CONTRIBUTOR | null | Adding Oracle Cloud's fsspec implementation to the list of supported cloud storage providers. | {
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https://api.github.com/repos/huggingface/datasets/issues/5620 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5620/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5620/comments | https://api.github.com/repos/huggingface/datasets/issues/5620/events | https://github.com/huggingface/datasets/pull/5620 | 1,613,460,520 | PR_kwDODunzps5LefAf | 5,620 | Bump pyarrow to 8.0.0 | {
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} | [] | closed | false | null | [] | null | [] | "2023-03-07T13:31:53" | "2023-03-08T14:01:27" | "2023-03-08T13:54:22" | MEMBER | null | Fix those for Pandas 2.0 (tested [here](https://github.com/huggingface/datasets/actions/runs/4346221280/jobs/7592010397) with pandas==2.0.0.rc0):
```python
=========================== short test summary info ============================
FAILED tests/test_arrow_dataset.py::BaseDatasetTest::test_to_parquet_in_memory - ImportError: Unable to find a usable engine; tried using: 'pyarrow', 'fastparquet'.
A suitable version of pyarrow or fastparquet is required for parquet support.
Trying to import the above resulted in these errors:
- Pandas requires version '7.0.0' or newer of 'pyarrow' (version '6.0.1' currently installed).
- Missing optional dependency 'fastparquet'. fastparquet is required for parquet support. Use pip or conda to install fastparquet.
FAILED tests/test_arrow_dataset.py::BaseDatasetTest::test_to_parquet_on_disk - ImportError: Unable to find a usable engine; tried using: 'pyarrow', 'fastparquet'.
A suitable version of pyarrow or fastparquet is required for parquet support.
Trying to import the above resulted in these errors:
- Pandas requires version '7.0.0' or newer of 'pyarrow' (version '6.0.1' currently installed).
- Missing optional dependency 'fastparquet'. fastparquet is required for parquet support. Use pip or conda to install fastparquet.
===== 2 failed, 2137 passed, 18 skipped, 32 warnings in 212.76s (0:03:32) ======
```
EDIT: also for performance - with 8.0 we can use `.to_reader()` | {
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https://api.github.com/repos/huggingface/datasets/issues/5619 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5619/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5619/comments | https://api.github.com/repos/huggingface/datasets/issues/5619/events | https://github.com/huggingface/datasets/pull/5619 | 1,613,439,709 | PR_kwDODunzps5LeaYP | 5,619 | unpin fsspec | {
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} | [] | closed | false | null | [] | null | [] | "2023-03-07T13:22:41" | "2023-03-07T13:47:01" | "2023-03-07T13:39:02" | MEMBER | null | close https://github.com/huggingface/datasets/issues/5618 | {
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https://api.github.com/repos/huggingface/datasets/issues/5618 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5618/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5618/comments | https://api.github.com/repos/huggingface/datasets/issues/5618/events | https://github.com/huggingface/datasets/issues/5618 | 1,612,977,934 | I_kwDODunzps5gJBcO | 5,618 | Unpin fsspec < 2023.3.0 once issue fixed | {
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} | [] | closed | false | null | [] | null | [] | "2023-03-07T08:41:51" | "2023-03-07T13:39:03" | "2023-03-07T13:39:03" | MEMBER | null | Unpin `fsspec` upper version once root cause of our CI break is fixed.
See:
- #5614 | {
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https://api.github.com/repos/huggingface/datasets/issues/5617 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5617/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5617/comments | https://api.github.com/repos/huggingface/datasets/issues/5617/events | https://github.com/huggingface/datasets/pull/5617 | 1,612,947,422 | PR_kwDODunzps5LcvI- | 5,617 | Fix CI by temporarily pinning fsspec < 2023.3.0 | {
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Fix #5616.
Until root cause is fixed, see:
- #5614 | {
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https://api.github.com/repos/huggingface/datasets/issues/5616 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5616/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5616/comments | https://api.github.com/repos/huggingface/datasets/issues/5616/events | https://github.com/huggingface/datasets/issues/5616 | 1,612,932,508 | I_kwDODunzps5gI2Wc | 5,616 | CI is broken after fsspec-2023.3.0 release | {
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] | closed | false | null | [] | null | [] | "2023-03-07T08:06:39" | "2023-03-07T08:37:29" | "2023-03-07T08:37:29" | MEMBER | null | As reported by @lhoestq, our CI is broken after `fsspec` 2023.3.0 release:
```
FAILED tests/test_filesystem.py::test_compression_filesystems[Bz2FileSystem] - AssertionError: assert [{'created': ...: False, ...}] == ['file.txt']
At index 0 diff: {'name': 'file.txt', 'size': 70, 'type': 'file', 'created': 1678175677.1887748, 'islink': False, 'mode': 33188, 'uid': 1001, 'gid': 123, 'mtime': 1678175677.1887748, 'ino': 286957, 'nlink': 1} != 'file.txt'
Full diff:
[
- 'file.txt',
+ {'created': 1678175677.1887748,
+ 'gid': 123,
+ 'ino': 286957,
+ 'islink': False,
+ 'mode': 33188,
+ 'mtime': 1678175677.1887748,
+ 'name': 'file.txt',
+ 'nlink': 1,
+ 'size': 70,
+ 'type': 'file',
+ 'uid': 1001},
]
```
Also:
```
FAILED tests/test_filesystem.py::test_compression_filesystems[GzipFileSystem] - AssertionError: assert [{'created': ...: False, ...}] == ['file.txt']
FAILED tests/test_filesystem.py::test_compression_filesystems[Lz4FileSystem] - AssertionError: assert [{'created': ...: False, ...}] == ['file.txt']
FAILED tests/test_filesystem.py::test_compression_filesystems[XzFileSystem] - AssertionError: assert [{'created': ...: False, ...}] == ['file.txt']
FAILED tests/test_filesystem.py::test_compression_filesystems[ZstdFileSystem] - AssertionError: assert [{'created': ...: False, ...}] == ['file.txt']
===== 5 failed, 2134 passed, 18 skipped, 38 warnings in 157.21s (0:02:37) ======
```
See:
- fsspec/filesystem_spec#1205 | {
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https://api.github.com/repos/huggingface/datasets/issues/5615 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5615/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5615/comments | https://api.github.com/repos/huggingface/datasets/issues/5615/events | https://github.com/huggingface/datasets/issues/5615 | 1,612,552,653 | I_kwDODunzps5gHZnN | 5,615 | IterableDataset.add_column is unable to accept another IterableDataset as a parameter. | {
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] | closed | false | null | [] | null | [
"Hi! You can use `concatenate_datasets([ids1, ids2], axis=1)` to do this."
] | "2023-03-07T01:52:00" | "2023-03-09T15:24:05" | "2023-03-09T15:23:54" | NONE | null | ### Describe the bug
`IterableDataset.add_column` occurs an exception when passing another `IterableDataset` as a parameter.
The method seems to accept only eager evaluated values.
https://github.com/huggingface/datasets/blob/35b789e8f6826b6b5a6b48fcc2416c890a1f326a/src/datasets/iterable_dataset.py#L1388-L1391
I wrote codes below to make it.
```py
def add_column(dataset: IterableDataset, name: str, add_dataset: IterableDataset, key: str) -> IterableDataset:
iter_add_dataset = iter(add_dataset)
def add_column_fn(example):
if name in example:
raise ValueError(f"Error when adding {name}: column {name} is already in the dataset.")
return {name: next(iter_add_dataset)[key]}
return dataset.map(add_column_fn)
```
Is there other way to do it? Or is it intended?
### Steps to reproduce the bug
Thie codes below occurs `NotImplementedError`
```py
from datasets import IterableDataset
def gen(num):
yield {f"col{num}": 1}
yield {f"col{num}": 2}
yield {f"col{num}": 3}
ids1 = IterableDataset.from_generator(gen, gen_kwargs={"num": 1})
ids2 = IterableDataset.from_generator(gen, gen_kwargs={"num": 2})
new_ids = ids1.add_column("new_col", ids1)
for row in new_ids:
print(row)
```
### Expected behavior
`IterableDataset.add_column` is able to task `IterableDataset` and lazy evaluated values as a parameter since IterableDataset is lazy evalued.
### Environment info
- `datasets` version: 2.8.0
- Platform: Linux-3.10.0-1160.36.2.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.9.7
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
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https://api.github.com/repos/huggingface/datasets/issues/5614 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5614/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5614/comments | https://api.github.com/repos/huggingface/datasets/issues/5614/events | https://github.com/huggingface/datasets/pull/5614 | 1,611,896,357 | PR_kwDODunzps5LZOTd | 5,614 | Fix archive fs test | {
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} | [] | closed | false | null | [] | null | [] | "2023-03-06T17:28:09" | "2023-03-07T13:27:50" | "2023-03-07T13:20:57" | MEMBER | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5608 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5608/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5608/comments | https://api.github.com/repos/huggingface/datasets/issues/5608/events | https://github.com/huggingface/datasets/issues/5608 | 1,609,996,563 | I_kwDODunzps5f9pkT | 5,608 | audiofolder only creates dataset of 13 rows (files) when the data folder it's reading from has 20,000 mp3 files. | {
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"Hi!\r\n\r\n> naming convention of mp3 files\r\n\r\nYes, this could be the problem. MP3 files should end with `.mp3`/`.MP3` to be recognized as audio files.\r\n\r\nIf the file names are not the culprit, can you paste the audio folder's directory structure to help us reproduce the error (e.g., by running the `tree \"x\"` command)?",
"Hi! I'm sorry, I don't want to reveal my entire dataset, but here's a snippet (all of the mp3 files below are some of the ones not being recognized by audiofolder. Also, for another dataset, audiofolder loaded zero mp3 files because \"train\" was in the name of one of the mp3 files. \r\nmy_dataset\r\n├── data\r\n│ ├── VHA_Innovation_Stories_-_Day_2-123.mp3\r\n│ ├── VHA_Innovation_Stories_-_Day_2-124.mp3\r\n│ ├── ASSOCIATION_OF_GENERAL_PRACTITIONERS_OF_JAMAICA_NEPHROLOGY_CONFERENCE_-_JULY_3,_2022-93.mp3\r\n│ ├── ASSOCIATION_OF_GENERAL_PRACTITIONERS_OF_JAMAICA_NEPHROLOGY_CONFERENCE_-_JULY_3,_2022-94.mp3\r\n│ ├── ASSOCIATION_OF_GENERAL_PRACTITIONERS_OF_JAMAICA_NEPHROLOGY_CONFERENCE_-_JULY_3,_2022-95.mp3\r\n│ ├── Your_Impact\\357\\274\\232_Neurosurgery_equipment-5.mp3\r\n│ └── Your_Impact\\357\\274\\232_Neurosurgery_equipment-6.mp3\r\n└── metadata.csv\r\n\r\nHere's a few of the 13 files recognized by the dataset:\r\nBritish_Heart_Foundation_-_Your_guide_to_a_Coronary_Angiogram,_a_test_for_heart_disease-1.mp3\r\nBritish_Heart_Foundation_-_Your_guide_to_a_Coronary_Angiogram,_a_test_for_heart_disease-2.mp3\r\nBritish_Heart_Foundation_-_Your_guide_to_a_Coronary_Angiogram,_a_test_for_heart_disease-3.mp3\r\nIVP_⧸_IVU_test_Procedure_for_Kidneys_intravenous_pyelogram_-_medical_radiology_X-ray_ivp-1.mp3\r\nIVP_⧸_IVU_test_Procedure_for_Kidneys_intravenous_pyelogram_-_medical_radiology_X-ray_ivp-2.mp3"
] | "2023-03-05T00:14:45" | "2023-03-12T00:02:57" | "2023-03-12T00:02:57" | NONE | null | ### Describe the bug
x = load_dataset("audiofolder", data_dir="x")
When running this, x is a dataset of 13 rows (files) when it should be 20,000 rows (files) as the data_dir "x" has 20,000 mp3 files. Does anyone know what could possibly cause this (naming convention of mp3 files, etc.)
### Steps to reproduce the bug
x = load_dataset("audiofolder", data_dir="x")
### Expected behavior
x = load_dataset("audiofolder", data_dir="x") should create a dataset of 20,000 rows (files).
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-3.10.0-1160.80.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.9.16
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/5607 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5607/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5607/comments | https://api.github.com/repos/huggingface/datasets/issues/5607/events | https://github.com/huggingface/datasets/pull/5607 | 1,609,166,035 | PR_kwDODunzps5LQPbG | 5,607 | Fix outdated `verification_mode` values | {
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} | [] | closed | false | null | [] | null | [] | "2023-03-03T19:50:29" | "2023-03-09T17:34:13" | "2023-03-09T17:27:07" | CONTRIBUTOR | null | ~I think it makes sense not to save `dataset_info.json` file to a dataset cache directory when loading dataset with `verification_mode="no_checks"` because otherwise when next time the dataset is loaded **without** `verification_mode="no_checks"`, it will be loaded successfully, despite some values in info might not correspond to the ones in the repo which was the reason for using `verification_mode="no_checks"` first.~
Updated values of `verification_mode` to the current ones in some places ("none" -> "no_checks", "all" -> "all_checks") | {
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https://api.github.com/repos/huggingface/datasets/issues/5605 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5605/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5605/comments | https://api.github.com/repos/huggingface/datasets/issues/5605/events | https://github.com/huggingface/datasets/pull/5605 | 1,608,865,460 | PR_kwDODunzps5LPPf5 | 5,605 | Update README logo | {
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https://api.github.com/repos/huggingface/datasets/issues/5603 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5603/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5603/comments | https://api.github.com/repos/huggingface/datasets/issues/5603/events | https://github.com/huggingface/datasets/pull/5603 | 1,607,143,509 | PR_kwDODunzps5LJZzG | 5,603 | Don't compute checksums if not necessary in `datasets-cli test` | {
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https://api.github.com/repos/huggingface/datasets/issues/5598 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5598/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5598/comments | https://api.github.com/repos/huggingface/datasets/issues/5598/events | https://github.com/huggingface/datasets/pull/5598 | 1,605,018,478 | PR_kwDODunzps5LCMiX | 5,598 | Fix push_to_hub with no dataset_infos | {
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cc @clefourrier | {
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https://api.github.com/repos/huggingface/datasets/issues/5597 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5597/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5597/comments | https://api.github.com/repos/huggingface/datasets/issues/5597/events | https://github.com/huggingface/datasets/issues/5597 | 1,604,928,721 | I_kwDODunzps5fqUTR | 5,597 | in-place dataset update | {
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"We won't support in-place modifications since `datasets` is based on the Apache Arrow format which doesn't support in-place modifications.\r\n\r\nIn your case the old dataset is garbage collected pretty quickly so you won't have memory issues.\r\n\r\nNote that datasets loaded from disk (memory mapped) are not loaded in memory, and therefore the new dataset actually use the same buffers as the old one.",
"Thank you for your detailed reply.\r\n\r\n> In your case the old dataset is garbage collected pretty quickly so you won't have memory issues.\r\n\r\nI understand this, but it still copies the old dataset to create the new one, is this correct? So maybe it is not memory-consuming, but time-consuming?",
"Indeed, and because of that it is more efficient to add multiple rows at once instead of one by one, using `concatenate_datasets` for example."
] | "2023-03-01T12:58:18" | "2023-03-02T13:30:41" | "2023-03-02T03:47:00" | NONE | null | ### Motivation
For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this.
```python
from datasets import Dataset
ds = Dataset.from_list([])
ds.add_item({'a': [1, 2, 3], 'b': 4})
print(ds)
>>> Dataset({
>>> features: [],
>>> num_rows: 0
>>> })
ds = ds.add_item({'a': [1, 2, 3], 'b': 4})
print(ds)
>>> Dataset({
>>> features: ['a', 'b'],
>>> num_rows: 1
>>> })
```
### Feature request
Call for in-place dataset update functions, that update the existing `Dataset` in place without creating a new copy. The interface is supposed to keep the same style as PyTorch, such as the in-place version of a `function` is named `function_`. For example, the in-pace version of `add_item`, i.e., `add_item_`, immediately updates the `Dataset`.
```python
from datasets import Dataset
ds = Dataset.from_list([])
ds.add_item({'a': [1, 2, 3], 'b': 4})
print(ds)
>>> Dataset({
>>> features: [],
>>> num_rows: 0
>>> })
ds.add_item_({'a': [1, 2, 3], 'b': 4})
print(ds)
>>> Dataset({
>>> features: ['a', 'b'],
>>> num_rows: 1
>>> })
```
### Related Functions
* `.map`
* `.filter`
* `.add_item` | {
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https://api.github.com/repos/huggingface/datasets/issues/5596 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5596/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5596/comments | https://api.github.com/repos/huggingface/datasets/issues/5596/events | https://github.com/huggingface/datasets/issues/5596 | 1,604,919,993 | I_kwDODunzps5fqSK5 | 5,596 | [TypeError: Couldn't cast array of type] Can only load a subset of the dataset | {
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"Apparently some JSON objects have a `\"labels\"` field. Since this field is not present in every object, you must specify all the fields types in the README.md\r\n\r\nEDIT: actually specifying the feature types doesn’t solve the issue, it raises an error because “labels” is missing in the data",
"We've updated the dataset to remove the extra `labels` field from some files, closing this issue. Thanks!"
] | "2023-03-01T12:53:08" | "2023-03-02T11:12:11" | "2023-03-02T11:12:11" | NONE | null | ### Describe the bug
I'm trying to load this [dataset](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues) which consists of jsonl files and I get the following error:
```
casted_values = _c(array.values, feature[0])
File "/opt/conda/lib/python3.7/site-packages/datasets/table.py", line 1839, in wrapper
return func(array, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/table.py", line 2132, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}")
TypeError: Couldn't cast array of type
struct<type: string, action: string, datetime: timestamp[s], author: string, title: string, description: string, comment_id: int64, comment: string, labels: list<item: string>>
to
{'type': Value(dtype='string', id=None), 'action': Value(dtype='string', id=None), 'datetime': Value(dtype='timestamp[s]', id=None), 'author': Value(dtype='string', id=None), 'title': Value(dtype='string', id=None), 'description': Value(dtype='string', id=None), 'comment_id': Value(dtype='int64', id=None), 'comment': Value(dtype='string', id=None)}
```
But I can succesfully load a subset of the dataset, for example this works:
```python
ds = load_dataset('bigcode-data/the-stack-gh-issues', split="train", data_files=[f"data/data-{x}.jsonl" for x in range(10)])
```
and `ds.features` returns:
```
{'repo': Value(dtype='string', id=None),
'org': Value(dtype='string', id=None),
'issue_id': Value(dtype='int64', id=None),
'issue_number': Value(dtype='int64', id=None),
'pull_request': {'user_login': Value(dtype='string', id=None),
'repo': Value(dtype='string', id=None),
'number': Value(dtype='int64', id=None)},
'events': [{'type': Value(dtype='string', id=None),
'action': Value(dtype='string', id=None),
'datetime': Value(dtype='timestamp[s]', id=None),
'author': Value(dtype='string', id=None),
'title': Value(dtype='string', id=None),
'description': Value(dtype='string', id=None),
'comment_id': Value(dtype='int64', id=None),
'comment': Value(dtype='string', id=None)}]}
```
So I'm not sure if there's an issue with just some of the files. Grateful if you have any suggestions to fix the issue.
Side note:
I saw this related [issue](https://github.com/huggingface/datasets/issues/3637) and tried to write a loading script to have `events` as a `Sequence` and not `list` [here](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues/blob/main/loading.py) (the script was renamed). It worked with a subset locally but doesn't for the remote dataset it can't find https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues/resolve/main/data.
### Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset('bigcode-data/the-stack-gh-issues', split="train")
```
### Expected behavior
Load the entire dataset succesfully.
### Environment info
- `datasets` version: 2.10.1
- Platform: Linux-4.19.0-23-cloud-amd64-x86_64-with-debian-10.13
- Python version: 3.7.12
- PyArrow version: 9.0.0
- Pandas version: 1.3.4 | {
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https://api.github.com/repos/huggingface/datasets/issues/5592 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5592/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5592/comments | https://api.github.com/repos/huggingface/datasets/issues/5592/events | https://github.com/huggingface/datasets/pull/5592 | 1,603,619,124 | PR_kwDODunzps5K9dWr | 5,592 | Fix docstring example | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-28T18:42:37" | "2023-02-28T19:26:33" | "2023-02-28T19:19:15" | MEMBER | null | Fixes #5581 to use the correct output for the `set_format` method. | {
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https://api.github.com/repos/huggingface/datasets/issues/5588 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5588/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5588/comments | https://api.github.com/repos/huggingface/datasets/issues/5588/events | https://github.com/huggingface/datasets/pull/5588 | 1,603,304,766 | PR_kwDODunzps5K8YYz | 5,588 | Flatten dataset on the fly in `save_to_disk` | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-28T15:37:46" | "2023-02-28T17:28:35" | "2023-02-28T17:21:17" | CONTRIBUTOR | null | Flatten a dataset on the fly in `save_to_disk` instead of doing it with `flatten_indices` to avoid creating an additional cache file.
(this is one of the sub-tasks in https://github.com/huggingface/datasets/issues/5507) | {
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https://api.github.com/repos/huggingface/datasets/issues/5587 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5587/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5587/comments | https://api.github.com/repos/huggingface/datasets/issues/5587/events | https://github.com/huggingface/datasets/pull/5587 | 1,603,139,420 | PR_kwDODunzps5K70pp | 5,587 | Fix `sort` with indices mapping | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-28T14:05:08" | "2023-02-28T17:28:57" | "2023-02-28T17:21:58" | CONTRIBUTOR | null | Fixes the `key` range in the `query_table` call in `sort` to account for an indices mapping
Fix #5586 | {
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https://api.github.com/repos/huggingface/datasets/issues/5586 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5586/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5586/comments | https://api.github.com/repos/huggingface/datasets/issues/5586/events | https://github.com/huggingface/datasets/issues/5586 | 1,602,961,544 | I_kwDODunzps5fi0CI | 5,586 | .sort() is broken when used after .filter(), only in 2.10.0 | {
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"Thanks for reporting and thanks @mariosasko for fixing ! We just did a patch release `2.10.1` with the fix"
] | "2023-02-28T12:18:09" | "2023-02-28T18:17:26" | "2023-02-28T17:21:59" | NONE | null | ### Describe the bug
Hi, thank you for your support!
It seems like the addition of multiple key sort (#5502) in 2.10.0 broke the `.sort()` method.
After filtering a dataset with `.filter()`, the `.sort()` seems to refer to the query_table index of the previous unfiltered dataset, resulting in an IndexError.
This only happens with the 2.10.0 release.
### Steps to reproduce the bug
```Python
from datasets import load_dataset
# dataset with length of 1104
ds = load_dataset('glue', 'ax')['test']
ds = ds.filter(lambda x: x['idx'] > 1100)
ds.sort('premise')
print('Done')
```
File "/home/dongkeun/datasets_test/test.py", line 5, in <module>
ds.sort('premise')
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 528, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/fingerprint.py", line 511, in wrapper
out = func(dataset, *args, **kwargs)
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3959, in sort
sort_table = query_table(
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 588, in query_table
_check_valid_index_key(key, size)
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 537, in _check_valid_index_key
_check_valid_index_key(max(key), size=size)
File "/home/dongkeun/miniconda3/envs/datasets_test/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 531, in _check_valid_index_key
raise IndexError(f"Invalid key: {key} is out of bounds for size {size}")
IndexError: Invalid key: 1103 is out of bounds for size 3
### Expected behavior
It should sort the dataset and print "Done". Which it does on 2.9.0.
### Environment info
- `datasets` version: 2.10.0
- Platform: Linux-5.15.0-41-generic-x86_64-with-glibc2.31
- Python version: 3.9.16
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/5585 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5585/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5585/comments | https://api.github.com/repos/huggingface/datasets/issues/5585/events | https://github.com/huggingface/datasets/issues/5585 | 1,602,190,030 | I_kwDODunzps5ff3rO | 5,585 | Cache is not transportable | {
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"Hi ! No the cache is not transportable in general. It will work on a shared filesystem if you use the same python environment, but not across machines/os/environments.\r\n\r\nIn particular, reloading cached datasets does work, but reloading cached processed datasets (e.g. from `map`) may not work. This is because some hashes used by caching are based on pickle dumps of the function you pass to `map`.\r\n\r\nFinally you may copy the cache to another machine, but all the `cached-*.arrow` files are unlikely to be reloaded.",
"OK good to know. Thanks @lhoestq !"
] | "2023-02-28T00:53:06" | "2023-02-28T21:26:52" | "2023-02-28T21:26:52" | NONE | null | ### Describe the bug
I would like to share cache between two machines (a Windows host machine and a WSL instance).
I run most my code in WSL. I have just run out of space in the virtual drive. Rather than expand the drive size, I plan to move to cache to the host Windows machine, thereby sharing the downloads.
I'm hoping that I can just copy/paste the cache files, but I notice that a lot of the file names start with the path name, e.g. `_home_davidg_.cache_huggingface_datasets_conll2003_default-451...98.lock` where `home/davidg` is where the cache is in WSL.
This seems to suggest that the cache is not portable/cannot be centralised or shared. Is this the case, or are the files that start with path names not integral to the caching mechanism? Because copying the cache files _seems_ to work, but I'm not filled with confidence that something isn't going to break.
A related issue, when trying to load a dataset that should come from cache (running in WSL, pointing to cache on the Windows host) it seemed to work fine, but it still uses a WSL directory for `.cache\huggingface\modules\datasets_modules`. I see nothing in the docs about this, or how to point it to a different place.
I have asked a related question on the forum: https://discuss.huggingface.co/t/is-datasets-cache-operating-system-agnostic/32656
### Steps to reproduce the bug
View the cache directory in WSL/Windows.
### Expected behavior
Cache can be shared between (virtual) machines and be transportable.
It would be nice to have a simple way to say "Dear Hugging Face packages, please put ALL your cache in `blah/de/blah`" and have all the Hugging Face packages respect that single location.
### 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: 11.0.0
- Pandas version: 1.5.3
- ``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5584 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5584/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5584/comments | https://api.github.com/repos/huggingface/datasets/issues/5584/events | https://github.com/huggingface/datasets/issues/5584 | 1,601,821,808 | I_kwDODunzps5fedxw | 5,584 | Unable to load coyo700M dataset | {
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"Hi @manuaero \r\n\r\nThank you for your interest in the COYO dataset.\r\n\r\nOur dataset provides the img-url and alt-text in the form of a parquet, so to utilize the coyo dataset you will need to download it directly.\r\n\r\nWe provide a [guide](https://github.com/kakaobrain/coyo-dataset/blob/main/download/README.md) to download, so check it out.\r\n\r\nThank you."
] | "2023-02-27T19:35:03" | "2023-02-28T07:27:59" | "2023-02-28T07:27:58" | NONE | null | ### Describe the bug
Seeing this error when downloading https://huggingface.co/datasets/kakaobrain/coyo-700m:
```ArrowInvalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.```
Full stack trace
```Downloading and preparing dataset parquet/kakaobrain--coyo-700m to /root/.cache/huggingface/datasets/kakaobrain___parquet/kakaobrain--coyo-700m-ae729692ae3e0073/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec...
Downloading data files: 100%
1/1 [00:00<00:00, 63.35it/s]
Extracting data files: 100%
1/1 [00:00<00:00, 5.00it/s]
---------------------------------------------------------------------------
ArrowInvalid Traceback (most recent call last)
[/usr/local/lib/python3.8/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, job_id)
1859 _time = time.time()
-> 1860 for _, table in generator:
1861 if max_shard_size is not None and writer._num_bytes > max_shard_size:
9 frames
ArrowInvalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.
The above exception was the direct cause of the following exception:
DatasetGenerationError Traceback (most recent call last)
[/usr/local/lib/python3.8/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, job_id)
1890 if isinstance(e, SchemaInferenceError) and e.__context__ is not None:
1891 e = e.__context__
-> 1892 raise DatasetGenerationError("An error occurred while generating the dataset") from e
1893
1894 yield job_id, True, (total_num_examples, total_num_bytes, writer._features, num_shards, shard_lengths)
DatasetGenerationError: An error occurred while generating the dataset```
### Steps to reproduce the bug
```
from datasets import load_dataset
hf_dataset = load_dataset("kakaobrain/coyo-700m")
```
### Expected behavior
The above commands load the dataset successfully. Or handles exception and continue loading the remainder.
### Environment info
colab. any | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-27T17:04:46" | "2023-02-28T13:52:15" | "2023-02-28T13:44:04" | CONTRIBUTOR | null | Ensures all the writers that use Pandas for conversion (JSON, CSV, SQL) do not export `index` by default (https://github.com/huggingface/datasets/pull/5490 only did this for CSV) | {
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https://api.github.com/repos/huggingface/datasets/issues/5581 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5581/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5581/comments | https://api.github.com/repos/huggingface/datasets/issues/5581/events | https://github.com/huggingface/datasets/issues/5581 | 1,600,675,489 | I_kwDODunzps5faF6h | 5,581 | [DOC] Mistaken docs on set_format | {
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"Thanks for reporting!"
] | "2023-02-27T08:03:09" | "2023-02-28T19:19:17" | "2023-02-28T19:19:17" | CONTRIBUTOR | null | ### Describe the bug
https://huggingface.co/docs/datasets/v2.10.0/en/package_reference/main_classes#datasets.Dataset.set_format
<img width="700" alt="image" src="https://user-images.githubusercontent.com/36224762/221506973-ae2e3991-60a7-4d4e-99f8-965c6eb61e59.png">
While actually running it will result in:
<img width="1094" alt="image" src="https://user-images.githubusercontent.com/36224762/221507032-007dab82-8781-4319-b21a-e6e4d40d97b3.png">
### Steps to reproduce the bug
_
### Expected behavior
_
### Environment info
- `datasets` version: 2.10.0
- Platform: Linux-5.10.147+-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 9.0.0
- Pandas version: 1.3.5 | {
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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 | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-27T04:06:05" | "2023-03-11T01:02:49" | "2023-03-11T00:55:40" | CONTRIBUTOR | 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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https://api.github.com/repos/huggingface/datasets/issues/5578 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5578/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5578/comments | https://api.github.com/repos/huggingface/datasets/issues/5578/events | https://github.com/huggingface/datasets/pull/5578 | 1,598,863,119 | PR_kwDODunzps5Kto96 | 5,578 | Add `huggingface_hub` version to env cli command | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-24T15:37:43" | "2023-02-27T17:28:25" | "2023-02-27T17:21:09" | CONTRIBUTOR | null | Add the `huggingface_hub` version to the `env` command's output. | {
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https://api.github.com/repos/huggingface/datasets/issues/5577 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5577/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5577/comments | https://api.github.com/repos/huggingface/datasets/issues/5577/events | https://github.com/huggingface/datasets/issues/5577 | 1,598,587,665 | I_kwDODunzps5fSIMR | 5,577 | Cannot load `the_pile_openwebtext2` | {
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"Hi! I've merged a PR to use `int32` instead of `int8` for `reddit_scores`, so it should work now.\r\n\r\n"
] | "2023-02-24T13:01:48" | "2023-02-24T14:01:09" | "2023-02-24T14:01:09" | NONE | null | ### Describe the bug
I met the same bug mentioned in #3053 which is never fixed. Because several `reddit_scores` are larger than `int8` even `int16`. https://huggingface.co/datasets/the_pile_openwebtext2/blob/main/the_pile_openwebtext2.py#L62
### Steps to reproduce the bug
```python3
from datasets import load_dataset
dataset = load_dataset("the_pile_openwebtext2")
```
### Expected behavior
load as normal.
### Environment info
- `datasets` version: 2.10.0
- Platform: Linux-5.4.143.bsk.7-amd64-x86_64-with-glibc2.31
- Python version: 3.9.2
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/5576 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5576/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5576/comments | https://api.github.com/repos/huggingface/datasets/issues/5576/events | https://github.com/huggingface/datasets/issues/5576 | 1,598,582,744 | I_kwDODunzps5fSG_Y | 5,576 | I was getting a similar error `pyarrow.lib.ArrowInvalid: Integer value 528 not in range: -128 to 127` - AFAICT, this is because the type specified for `reddit_scores` is `datasets.Sequence(datasets.Value("int8"))`, but the actual values can be well outside the max range for 8-bit integers. | {
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"Duplicated issue."
] | "2023-02-24T12:57:49" | "2023-02-24T12:58:31" | "2023-02-24T12:58:18" | NONE | null | I was getting a similar error `pyarrow.lib.ArrowInvalid: Integer value 528 not in range: -128 to 127` - AFAICT, this is because the type specified for `reddit_scores` is `datasets.Sequence(datasets.Value("int8"))`, but the actual values can be well outside the max range for 8-bit integers.
I worked around this by downloading the `the_pile_openwebtext2.py` and editing it to use local files and drop reddit scores as a column (not needed for my purposes).
_Originally posted by @tc-wolf in https://github.com/huggingface/datasets/issues/3053#issuecomment-1281392422_
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https://api.github.com/repos/huggingface/datasets/issues/5574 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5574/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5574/comments | https://api.github.com/repos/huggingface/datasets/issues/5574/events | https://github.com/huggingface/datasets/issues/5574 | 1,598,104,691 | I_kwDODunzps5fQSRz | 5,574 | c4 dataset streaming fails with `FileNotFoundError` | {
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"Also encountering this issue for every dataset I try to stream! Installed datasets from main:\r\n```\r\n- `datasets` version: 2.10.1.dev0\r\n- Platform: macOS-13.1-arm64-arm-64bit\r\n- Python version: 3.9.13\r\n- PyArrow version: 10.0.1\r\n- Pandas version: 1.5.2\r\n```\r\n\r\nRepro:\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nspigi = load_dataset(\"kensho/spgispeech\", \"dev\", split=\"validation\", streaming=True, use_auth_token=True)\r\nsample = next(iter(spigi))\r\n```\r\n\r\n<details>\r\n<summary> Traceback </summary>\r\n\r\n```python\r\n---------------------------------------------------------------------------\r\nClientResponseError Traceback (most recent call last)\r\nFile ~/venv/lib/python3.9/site-packages/fsspec/implementations/http.py:407, in HTTPFileSystem._info(self, url, **kwargs)\r\n 405 try:\r\n 406 info.update(\r\n--> 407 await _file_info(\r\n 408 self.encode_url(url),\r\n 409 size_policy=policy,\r\n 410 session=session,\r\n 411 **self.kwargs,\r\n 412 **kwargs,\r\n 413 )\r\n 414 )\r\n 415 if info.get(\"size\") is not None:\r\n\r\nFile ~/venv/lib/python3.9/site-packages/fsspec/implementations/http.py:792, in _file_info(url, session, size_policy, **kwargs)\r\n 791 async with r:\r\n--> 792 r.raise_for_status()\r\n 794 # TODO:\r\n 795 # recognise lack of 'Accept-Ranges',\r\n 796 # or 'Accept-Ranges': 'none' (not 'bytes')\r\n 797 # to mean streaming only, no random access => return None\r\n\r\nFile ~/venv/lib/python3.9/site-packages/aiohttp/client_reqrep.py:1005, in ClientResponse.raise_for_status(self)\r\n 1004 self.release()\r\n-> 1005 raise ClientResponseError(\r\n 1006 self.request_info,\r\n 1007 self.history,\r\n 1008 status=self.status,\r\n 1009 message=self.reason,\r\n 1010 headers=self.headers,\r\n 1011 )\r\n\r\nClientResponseError: 403, message='Forbidden', url=URL('[https://cdn-lfs.huggingface.co/repos/e2/89/e28905247d6f48bb4edad5baf9b1bb4158e897a13fdf18bf3b8ee89ff8387ab8/46eca7431a7b6bad344bf451800e5b10cea1dd168f26d1027a6d9eb374b7fac3?response-content-disposition=attachment%3B+filename*%3DUTF-8''dev.csv%3B+filename%3D%22dev.csv%22%3B&response-content-type=text/csv&Expires=1677494732&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL3JlcG9zL2UyLzg5L2UyODkwNTI0N2Q2ZjQ4YmI0ZWRhZDViYWY5YjFiYjQxNThlODk3YTEzZmRmMThiZjNiOGVlODlmZjgzODdhYjgvNDZlY2E3NDMxYTdiNmJhZDM0NGJmNDUxODAwZTViMTBjZWExZGQxNjhmMjZkMTAyN2E2ZDllYjM3NGI3ZmFjMz9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSomcmVzcG9uc2UtY29udGVudC10eXBlPXRleHQlMkZjc3YiLCJDb25kaXRpb24iOnsiRGF0ZUxlc3NUaGFuIjp7IkFXUzpFcG9jaFRpbWUiOjE2Nzc0OTQ3MzJ9fX1dfQ__&Signature=EzQB9f7xPckvqfFB6LzcyR-wzTnQCqtPDdWtQUzZ3QJ-gY-IHG5mxQITJgMr1nVTbJZrPmGAaDngMcPFUfSQa8RmCqYH~dZl-UGE8CO4neKNUT1DvA2WEvLDS4WaAJ3SN-9rX0uFb03~c1QS78cIgIRboYvf6ugKiJz86Bd7Vs~tcp201JFR0A6jIMseqApOnkb9d8dHMP3Ny~F6gO3Qf2QpEWM-QsDIyw2Kz2QV55nq8TsDpRYZCZo50~WwD~73Hej0PoDhEA1K37d19pa0CQhkaN-gjCrbT9xLabbvhJWa~ZkWcMdD0teCgjYqv1wKyvFXDAxukxLGEc7OBXVbYw__&Key-Pair-Id=KVTP0A1DKRTAX](https://cdn-lfs.huggingface.co/repos/e2/89/e28905247d6f48bb4edad5baf9b1bb4158e897a13fdf18bf3b8ee89ff8387ab8/46eca7431a7b6bad344bf451800e5b10cea1dd168f26d1027a6d9eb374b7fac3?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27dev.csv%3B+filename%3D%22dev.csv%22%3B&response-content-type=text/csv&Expires=1677494732&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL3JlcG9zL2UyLzg5L2UyODkwNTI0N2Q2ZjQ4YmI0ZWRhZDViYWY5YjFiYjQxNThlODk3YTEzZmRmMThiZjNiOGVlODlmZjgzODdhYjgvNDZlY2E3NDMxYTdiNmJhZDM0NGJmNDUxODAwZTViMTBjZWExZGQxNjhmMjZkMTAyN2E2ZDllYjM3NGI3ZmFjMz9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSomcmVzcG9uc2UtY29udGVudC10eXBlPXRleHQlMkZjc3YiLCJDb25kaXRpb24iOnsiRGF0ZUxlc3NUaGFuIjp7IkFXUzpFcG9jaFRpbWUiOjE2Nzc0OTQ3MzJ9fX1dfQ__&Signature=EzQB9f7xPckvqfFB6LzcyR-wzTnQCqtPDdWtQUzZ3QJ-gY-IHG5mxQITJgMr1nVTbJZrPmGAaDngMcPFUfSQa8RmCqYH~dZl-UGE8CO4neKNUT1DvA2WEvLDS4WaAJ3SN-9rX0uFb03~c1QS78cIgIRboYvf6ugKiJz86Bd7Vs~tcp201JFR0A6jIMseqApOnkb9d8dHMP3Ny~F6gO3Qf2QpEWM-QsDIyw2Kz2QV55nq8TsDpRYZCZo50~WwD~73Hej0PoDhEA1K37d19pa0CQhkaN-gjCrbT9xLabbvhJWa~ZkWcMdD0teCgjYqv1wKyvFXDAxukxLGEc7OBXVbYw__&Key-Pair-Id=KVTP0A1DKRTAX)')\r\n\r\nThe above exception was the direct cause of the following exception:\r\n\r\nFileNotFoundError Traceback (most recent call last)\r\nCell In[5], line 4\r\n 1 from datasets import load_dataset\r\n 3 spigi = load_dataset(\"kensho/spgispeech\", \"dev\", split=\"validation\", streaming=True)\r\n----> 4 sample = next(iter(spigi))\r\n\r\nFile ~/datasets/src/datasets/iterable_dataset.py:937, in IterableDataset.__iter__(self)\r\n 934 yield from self._iter_pytorch(ex_iterable)\r\n 935 return\r\n--> 937 for key, example in ex_iterable:\r\n 938 if self.features:\r\n 939 # `IterableDataset` automatically fills missing columns with None.\r\n 940 # This is done with `_apply_feature_types_on_example`.\r\n 941 yield _apply_feature_types_on_example(\r\n 942 example, self.features, token_per_repo_id=self._token_per_repo_id\r\n 943 )\r\n\r\nFile ~/datasets/src/datasets/iterable_dataset.py:113, in ExamplesIterable.__iter__(self)\r\n 112 def __iter__(self):\r\n--> 113 yield from self.generate_examples_fn(**self.kwargs)\r\n\r\nFile ~/.cache/huggingface/modules/datasets_modules/datasets/kensho--spgispeech/5fbf75dd9ef795a9b5a673457d2cbaf0b8fa0de8fb62acbd1da338d83a41e2f0/spgispeech.py:186, in Spgispeech._generate_examples(self, local_extracted_archive_paths, archives, meta_path)\r\n 183 dict_keys = [\"wav_filename\", \"wav_filesize\", \"transcript\"]\r\n 185 logging.info(\"Reading metadata...\")\r\n--> 186 with open(meta_path, encoding=\"utf-8\") as f:\r\n 187 csvreader = csv.DictReader(f, delimiter=\"|\")\r\n 188 metadata = {x[\"wav_filename\"]: dict((k, x[k]) for k in dict_keys) for x in csvreader}\r\n\r\nFile ~/datasets/src/datasets/streaming.py:70, in extend_module_for_streaming.<locals>.wrap_auth.<locals>.wrapper(*args, **kwargs)\r\n 68 @wraps(function)\r\n 69 def wrapper(*args, **kwargs):\r\n---> 70 return function(*args, use_auth_token=use_auth_token, **kwargs)\r\n\r\nFile ~/datasets/src/datasets/download/streaming_download_manager.py:495, in xopen(file, mode, use_auth_token, *args, **kwargs)\r\n 493 kwargs = {**kwargs, **new_kwargs}\r\n 494 try:\r\n--> 495 file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()\r\n 496 except ValueError as e:\r\n 497 if str(e) == \"Cannot seek streaming HTTP file\":\r\n\r\nFile ~/venv/lib/python3.9/site-packages/fsspec/core.py:135, in OpenFile.open(self)\r\n 128 def open(self):\r\n 129 \"\"\"Materialise this as a real open file without context\r\n 130 \r\n 131 The OpenFile object should be explicitly closed to avoid enclosed file\r\n 132 instances persisting. You must, therefore, keep a reference to the OpenFile\r\n 133 during the life of the file-like it generates.\r\n 134 \"\"\"\r\n--> 135 return self.__enter__()\r\n\r\nFile ~/venv/lib/python3.9/site-packages/fsspec/core.py:103, in OpenFile.__enter__(self)\r\n 100 def __enter__(self):\r\n 101 mode = self.mode.replace(\"t\", \"\").replace(\"b\", \"\") + \"b\"\r\n--> 103 f = self.fs.open(self.path, mode=mode)\r\n 105 self.fobjects = [f]\r\n 107 if self.compression is not None:\r\n\r\nFile ~/venv/lib/python3.9/site-packages/fsspec/spec.py:1106, in AbstractFileSystem.open(self, path, mode, block_size, cache_options, compression, **kwargs)\r\n 1104 else:\r\n 1105 ac = kwargs.pop(\"autocommit\", not self._intrans)\r\n-> 1106 f = self._open(\r\n 1107 path,\r\n 1108 mode=mode,\r\n 1109 block_size=block_size,\r\n 1110 autocommit=ac,\r\n 1111 cache_options=cache_options,\r\n 1112 **kwargs,\r\n 1113 )\r\n 1114 if compression is not None:\r\n 1115 from fsspec.compression import compr\r\n\r\nFile ~/venv/lib/python3.9/site-packages/fsspec/implementations/http.py:346, in HTTPFileSystem._open(self, path, mode, block_size, autocommit, cache_type, cache_options, size, **kwargs)\r\n 344 kw[\"asynchronous\"] = self.asynchronous\r\n 345 kw.update(kwargs)\r\n--> 346 size = size or self.info(path, **kwargs)[\"size\"]\r\n 347 session = sync(self.loop, self.set_session)\r\n 348 if block_size and size:\r\n\r\nFile ~/venv/lib/python3.9/site-packages/fsspec/asyn.py:113, in sync_wrapper.<locals>.wrapper(*args, **kwargs)\r\n 110 @functools.wraps(func)\r\n 111 def wrapper(*args, **kwargs):\r\n 112 self = obj or args[0]\r\n--> 113 return sync(self.loop, func, *args, **kwargs)\r\n\r\nFile ~/venv/lib/python3.9/site-packages/fsspec/asyn.py:98, in sync(loop, func, timeout, *args, **kwargs)\r\n 96 raise FSTimeoutError from return_result\r\n 97 elif isinstance(return_result, BaseException):\r\n---> 98 raise return_result\r\n 99 else:\r\n 100 return return_result\r\n\r\nFile ~/venv/lib/python3.9/site-packages/fsspec/asyn.py:53, in _runner(event, coro, result, timeout)\r\n 51 coro = asyncio.wait_for(coro, timeout=timeout)\r\n 52 try:\r\n---> 53 result[0] = await coro\r\n 54 except Exception as ex:\r\n 55 result[0] = ex\r\n\r\nFile ~/venv/lib/python3.9/site-packages/fsspec/implementations/http.py:420, in HTTPFileSystem._info(self, url, **kwargs)\r\n 417 except Exception as exc:\r\n 418 if policy == \"get\":\r\n 419 # If get failed, then raise a FileNotFoundError\r\n--> 420 raise FileNotFoundError(url) from exc\r\n 421 logger.debug(str(exc))\r\n 423 return {\"name\": url, \"size\": None, **info, \"type\": \"file\"}\r\n\r\nFileNotFoundError: https://huggingface.co/datasets/kensho/spgispeech/resolve/main/data/meta/dev.csv\r\n```\r\n</details>",
"Hi ! We're investigating this issue, sorry for the inconvenience",
"This has been resolved ! Thanks for reporting",
"Wow, thanks for the very quick fix!",
"This problem now appears again, this time with an underlying HTTP 502 status code:\r\n\r\n```\r\naiohttp.client_exceptions.ClientResponseError: 502, message='Bad Gateway', url=URL('https://huggingface.co/datasets/allenai/c4/resolve/1ddc917116b730e1859edef32896ec5c16be51d0/en/c4-validation.00002-of-00008.json.gz')\r\n```",
"Re-executing a minute later, the underlying cause is an HTTP 403 status code, as reported yesterday:\r\n\r\n```\r\naiohttp.client_exceptions.ClientResponseError: 403, message='Forbidden', url=URL('https://cdn-lfs.huggingface.co/datasets/allenai/c4/4bf6b248b0f910dcde2cdf2118d6369d8208c8f9515ec29ab73e531f380b18e2?response-content-disposition=attachment%3B+filename*%3DUTF-8''c4-validation.00002-of-00008.json.gz%3B+filename%3D%22c4-validation.00002-of-00008.json.gz%22%3B&response-content-type=application/gzip&Expires=1677571273&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL2RhdGFzZXRzL2FsbGVuYWkvYzQvNGJmNmIyNDhiMGY5MTBkY2RlMmNkZjIxMThkNjM2OWQ4MjA4YzhmOTUxNWVjMjlhYjczZTUzMWYzODBiMThlMj9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSomcmVzcG9uc2UtY29udGVudC10eXBlPWFwcGxpY2F0aW9uJTJGZ3ppcCIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY3NzU3MTI3M319fV19&Signature=WW42NOKkLuX~xVB1QfbkqzdvGo2AOXpgbF3PjTXy6iKd~ffilr1N9ScPXfvTXqy5yvdhJg1G0xJy1zYtUjGAL8GEx3Av-0vIhpWMGYTM8XKEU5gYA9qt30oVtNph6TkTYSABrsYTaj-hzQL9WCgyapmjvG69ETMh4wj44r2rcbk4T3j0l6l4u76Gh~lyRSll3aK4qycdUwcyL7FECDu~0W1mJIJwKkCrWHhSpHJSshb-0ElwG71pq4eyQ5g2uxHdK6JbRF7loxUpRQQJ1vlk0EHXdw0wTMaQ9tqHy6xcrQd8Ep0Yvx3tUD8MR0vWOcbQKnL6LwPQByc8tkChlpjnig__&Key-Pair-Id=KVTP0A1DKRTAX')\r\n```",
"I'm facing the same problem. Interestingly using `wget` I can download the file. ",
"It's been resolved again ;)",
"> It's been resolved again ;)\r\n\r\nI'm experiencing the same issue when trying to load this dataset, `FileNotFoundError: https://huggingface.co/datasets/allenai/c4/resolve/1ddc917116b730e1859edef32896ec5c16be51d0/realnewslike/c4-train.00000-of-00512.json.gz`"
] | "2023-02-24T07:57:32" | "2023-03-06T13:14:11" | "2023-02-27T04:03:38" | NONE | null | ### Describe the bug
Loading the `c4` dataset in streaming mode with `load_dataset("c4", "en", split="validation", streaming=True)` and then using it fails with a `FileNotFoundException`.
### Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("c4", "en", split="train", streaming=True)
next(iter(dataset))
```
causes a
```
FileNotFoundError: https://huggingface.co/datasets/allenai/c4/resolve/1ddc917116b730e1859edef32896ec5c16be51d0/en/c4-train.00000-of-01024.json.gz
```
I can download this file manually though e.g. by entering this URL in a browser.
There is an underlying HTTP 403 status code:
```
aiohttp.client_exceptions.ClientResponseError: 403, message='Forbidden', url=URL('https://cdn-lfs.huggingface.co/datasets/allenai/c4/8ef8d75b0e045dec4aa5123a671b4564466b0707086a7ed1ba8721626dfffbc9?response-content-disposition=attachment%3B+filename*%3DUTF-8''c4-train.00000-of-01024.json.gz%3B+filename%3D%22c4-train.00000-of-01024.json.gz%22%3B&response-content-type=application/gzip&Expires=1677483770&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL2RhdGFzZXRzL2FsbGVuYWkvYzQvOGVmOGQ3NWIwZTA0NWRlYzRhYTUxMjNhNjcxYjQ1NjQ0NjZiMDcwNzA4NmE3ZWQxYmE4NzIxNjI2ZGZmZmJjOT9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSomcmVzcG9uc2UtY29udGVudC10eXBlPWFwcGxpY2F0aW9uJTJGZ3ppcCIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY3NzQ4Mzc3MH19fV19&Signature=yjL3UeY72cf2xpnvPvD68eAYOEe2qtaUJV55sB-jnPskBJEMwpMJcBZvg2~GqXZdM3O-GWV-Z3CI~d4u5VCb4YZ-HlmOjr3VBYkvox2EKiXnBIhjMecf2UVUPtxhTa9kBVlWjqu4qKzB9gKXZF2Cwpp5ctLzapEaT2nnqF84RAL-rsqMA3I~M8vWWfivQsbBK63hMfgZqqKMgdWM0iKMaItveDl0ufQ29azMFmsR7qd8V7sU2Z-F1fAeohS8HpN9OOnClW34yi~YJ2AbgZJJBXA~qsylfVA0Qp7Q~yX~q4P8JF1vmJ2BjkiSbGrj3bAXOGugpOVU5msI52DT88yMdA__&Key-Pair-Id=KVTP0A1DKRTAX')
```
### Expected behavior
This should retrieve the first example from the C4 validation set. This worked a few days ago but stopped working now.
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-5.15.0-60-generic-x86_64-with-glibc2.31
- Python version: 3.9.16
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
| {
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https://api.github.com/repos/huggingface/datasets/issues/5573 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5573/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5573/comments | https://api.github.com/repos/huggingface/datasets/issues/5573/events | https://github.com/huggingface/datasets/pull/5573 | 1,597,400,836 | PR_kwDODunzps5Kop7n | 5,573 | Use soundfile for mp3 decoding instead of torchaudio | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-23T19:19:44" | "2023-02-28T20:25:14" | "2023-02-28T20:16:02" | CONTRIBUTOR | null | I've removed `torchaudio` completely and switched to use `soundfile` for everything. With the new version of `soundfile` package this should work smoothly because the `libsndfile` C library is bundled, in Linux wheels too.
Let me know if you think it's too harsh and we should continue to support `torchaudio` decoding.
I decided that we can drop it completely because:
1. it's always something wrong with `torchaudio` (for example recently https://github.com/huggingface/datasets/issues/5488 )
2. the results of mp3 decoding are different depending on `torchaudio` version
3. `soundfile` is slightly faster then the latest `torchaudio`
4. anyway users can pass any custom decoding function with any library they want if needed (worth putting a snippet in the docs).
cc @sanchit-gandhi @vaibhavad | {
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https://api.github.com/repos/huggingface/datasets/issues/5572 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5572/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5572/comments | https://api.github.com/repos/huggingface/datasets/issues/5572/events | https://github.com/huggingface/datasets/issues/5572 | 1,597,257,624 | I_kwDODunzps5fNDeY | 5,572 | Datasets 2.10.0 does not reuse the dataset cache | {
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download_mode="reuse_dataset_if_exists" will always consider that a dataset doesn't exist.
Specifically, upon losing an internet connection trying to load a dataset for a second time in ten seconds, a connection error results, showing a breakpoint of:
```
File ~/jupyterlab/.direnv/python-3.9.6/lib/python3.9/site-packages/datasets/load.py:1174, in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)
1165 except Exception as e: # noqa: catch any exception of hf_hub and consider that the dataset doesn't exist
1166 if isinstance(
1167 e,
1168 (
(...)
1172 ),
1173 ):
-> 1174 raise ConnectionError(f"Couldn't reach '{path}' on the Hub ({type(e).__name__})")
1175 elif "404" in str(e):
1176 msg = f"Dataset '{path}' doesn't exist on the Hub"
ConnectionError: Couldn't reach 'lsb/tenk' on the Hub (ConnectionError)
```
This has been around since at least v2.0.
### Steps to reproduce the bug
```
from datasets import load_dataset
import numpy as np
tenk = load_dataset("lsb/tenk") # ten thousand integers
print(np.average(tenk['train']['a'])) # prints 4999.5
### now disconnect your internet
tenk_too = load_dataset("lsb/tenk", download_mode="reuse_dataset_if_exists")
# Raises ConnectionError: Couldn't reach 'lsb/tenk' on the Hub (ConnectionError)
```
### Expected behavior
I expected that I would be able to reuse the dataset I just downloaded.
### Environment info
- `datasets` version: 2.10.0
- Platform: macOS-13.1-arm64-arm-64bit
- Python version: 3.9.6
- PyArrow version: 7.0.0
- Pandas version: 1.5.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/5571 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5571/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5571/comments | https://api.github.com/repos/huggingface/datasets/issues/5571/events | https://github.com/huggingface/datasets/issues/5571 | 1,597,198,953 | I_kwDODunzps5fM1Jp | 5,571 | load_dataset fails for JSON in windows | {
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"Hi! \r\n\r\nYou need to pass an input json file explicitly as `data_files` to `load_dataset` to avoid this error:\r\n```python\r\n ds = load_dataset(\"json\", data_files=args.input_json)\r\n```\r\n\r\n",
"Thanks it worked!"
] | "2023-02-23T16:50:11" | "2023-02-24T13:21:47" | "2023-02-24T13:21:47" | NONE | null | ### Describe the bug
Steps:
1. Created a dataset in a Linux VM and created a small sample using dataset.to_json() method.
2. Downloaded the JSON file to my local Windows machine for working and saved in say - r"C:\Users\name\file.json"
3. I am reading the file in my local PyCharm - the location of python file is different than the location of the JSON.
4. When I read using load_dataset("json",args.input_json), it throws and error from builder.py.
raise InvalidConfigName(
f"Bad characters from black list '{invalid_windows_characters}' found in '{self.name}'. "
f"They could create issues when creating a directory for this config on Windows filesystem."
6. When I bring the data to the current directory, it works fine.
### Steps to reproduce the bug
Steps:
1. Created a dataset in a Linux VM and created a small sample using dataset.to_json() method.
2. Downloaded the JSON file to my local Windows machine for working and saved in say - r"C:\Users\name\file.json"
3. I am reading the file in my local PyCharm - the location of python file is different than the location of the JSON.
4. When I read using load_dataset("json",args.input_json), it throws and error from builder.py.
raise InvalidConfigName(
f"Bad characters from black list '{invalid_windows_characters}' found in '{self.name}'. "
f"They could create issues when creating a directory for this config on Windows filesystem."
6. When I bring the data to the current directory, it works fine.
### Expected behavior
Should be able to read from a path different than current directory in Windows machine.
### Environment info
datasets version: 2.3.1
python version: 3.8
Windows OS | {
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"Hi ! Oh good catch. I think the features should be passed to `IterableDataset.from_generator()` in `to_iterable_dataset()` indeed.\r\n\r\nSetting this as a good first issue if someone would like to contribute, otherwise we can take care of it :)",
"#self-assign",
"seems like the feature parameter is missing from `return IterableDataset.from_generator(Dataset._iter_shards, gen_kwargs={\"shards\": shards})` hence it defaults to None."
] | "2023-02-23T13:45:33" | "2023-02-24T13:22:36" | "2023-02-24T13:22:36" | CONTRIBUTOR | null | ### Describe the bug
Hello,
I like the new `to_iterable_dataset` feature but I noticed something that seems to be missing.
When using `to_iterable_dataset` to transform your map style dataset into iterable dataset, you lose valuable metadata like the features.
These metadata are useful if you want to interleave iterable datasets, cast columns etc.
### Steps to reproduce the bug
```python
dataset = load_dataset("lhoestq/demo1")["train"]
print(dataset.features)
# {'id': Value(dtype='string', id=None), 'package_name': Value(dtype='string', id=None), 'review': Value(dtype='string', id=None), 'date': Value(dtype='string', id=None), 'star': Value(dtype='int64', id=None), 'version_id': Value(dtype='int64', id=None)}
dataset = dataset.to_iterable_dataset()
print(dataset.features)
# None
```
### Expected behavior
Keep the relevant information
### Environment info
datasets==2.10.0 | {
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This can be useful for `datasets-server` to keep control of the row groups size which can affect random access performance for audio/image/video datasets
Right now having 1,000 examples per row group cause some image datasets to be pretty slow for random access (e.g. 4seconds for `beans` to get 20 rows) | {
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https://api.github.com/repos/huggingface/datasets/issues/5562 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5562/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5562/comments | https://api.github.com/repos/huggingface/datasets/issues/5562/events | https://github.com/huggingface/datasets/pull/5562 | 1,594,625,539 | PR_kwDODunzps5KfTUT | 5,562 | Update csv.py | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-22T07:56:10" | "2023-02-23T11:07:49" | "2023-02-23T11:00:58" | CONTRIBUTOR | null | Removed mangle_dup_cols=True from BuilderConfig.
It triggered following deprecation warning:
/usr/local/lib/python3.8/dist-packages/datasets/download/streaming_download_manager.py:776: FutureWarning: the 'mangle_dupe_cols' keyword is deprecated and will be removed in a future version. Please take steps to stop the use of 'mangle_dupe_cols'
return pd.read_csv(xopen(filepath_or_buffer, "rb", use_auth_token=use_auth_token), **kwargs)
Further documentation of pandas: https://pandas.pydata.org/docs/whatsnew/v1.4.0.html#mangle-dupe-cols-in-read-csv-no-longer-renames-unique-columns-conflicting-with-target-names
At first sight it seems like this flag is resolved internally, it might need some more research. | {
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https://api.github.com/repos/huggingface/datasets/issues/5561 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5561/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5561/comments | https://api.github.com/repos/huggingface/datasets/issues/5561/events | https://github.com/huggingface/datasets/pull/5561 | 1,593,862,388 | PR_kwDODunzps5Kcxw_ | 5,561 | Add pre-commit config yaml file to enable automatic code formatting | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-21T17:35:07" | "2023-02-28T15:37:22" | "2023-02-23T18:23:29" | CONTRIBUTOR | null | @huggingface/datasets do you think it would be useful? Motivation - sometimes PRs are like 30% "fix: style" commits :)
If so - I need to double check the config but for me locally it works as expected. | {
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https://api.github.com/repos/huggingface/datasets/issues/5560 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5560/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5560/comments | https://api.github.com/repos/huggingface/datasets/issues/5560/events | https://github.com/huggingface/datasets/pull/5560 | 1,593,809,978 | PR_kwDODunzps5Kcml6 | 5,560 | Ensure last tqdm update in `map` | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-21T16:56:17" | "2023-02-21T18:26:23" | "2023-02-21T18:19:09" | CONTRIBUTOR | null | This PR modifies `map` to:
* ensure the TQDM bar gets the last progress update
* when a map function fails, avoid throwing a chained exception in the single-proc mode | {
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https://api.github.com/repos/huggingface/datasets/issues/5559 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5559/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5559/comments | https://api.github.com/repos/huggingface/datasets/issues/5559/events | https://github.com/huggingface/datasets/pull/5559 | 1,593,676,489 | PR_kwDODunzps5KcKSb | 5,559 | Fix map suffix_template | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-21T15:26:26" | "2023-02-21T17:21:37" | "2023-02-21T17:14:29" | MEMBER | null | #5455 introduced a small bug that lead `map` to ignore the `suffix_template` argument and not put suffixes to cached files in multiprocessing.
I fixed this and also improved a few things:
- regarding logging: "Loading cached processed dataset" is now logged only once even in multiprocessing (it used to be logged `num_proc` times)
- regarding new_fingerprint: I made sure that the returned dataset satisfies `ds._fingerprint==new_fingerprint` if `new_fingerprint` is passed to `map` | {
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https://api.github.com/repos/huggingface/datasets/issues/5558 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5558/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5558/comments | https://api.github.com/repos/huggingface/datasets/issues/5558/events | https://github.com/huggingface/datasets/pull/5558 | 1,593,655,815 | PR_kwDODunzps5KcF5E | 5,558 | Remove instructions for `ffmpeg` system package installation on Colab | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-21T15:13:36" | "2023-03-01T13:46:04" | "2023-02-23T13:50:27" | CONTRIBUTOR | null | Colab now has Ubuntu 20.04 which already has `ffmpeg` of required (>4) version. | {
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https://api.github.com/repos/huggingface/datasets/issues/5557 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5557/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5557/comments | https://api.github.com/repos/huggingface/datasets/issues/5557/events | https://github.com/huggingface/datasets/pull/5557 | 1,593,545,324 | PR_kwDODunzps5Kbube | 5,557 | Add filter desc | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-21T14:04:42" | "2023-02-21T14:19:54" | "2023-02-21T14:12:39" | MEMBER | null | Otherwise it would show a `Map` progress bar, since it uses `map` under the hood | {
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https://api.github.com/repos/huggingface/datasets/issues/5556 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5556/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5556/comments | https://api.github.com/repos/huggingface/datasets/issues/5556/events | https://github.com/huggingface/datasets/pull/5556 | 1,593,246,936 | PR_kwDODunzps5KauVL | 5,556 | Use default audio resampling type | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-21T10:45:50" | "2023-02-21T12:49:50" | "2023-02-21T12:42:52" | MEMBER | null | ...instead of relying on the optional librosa dependency `resampy`.
It was only used for `_decode_non_mp3_file_like` anyway and not for the other ones - removing it fixes consistency between decoding methods (except torchaudio decoding)
Therefore I think it is a better solution than adding `resampy` as a dependency in https://github.com/huggingface/datasets/pull/5554
cc @polinaeterna | {
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https://api.github.com/repos/huggingface/datasets/issues/5554 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5554/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5554/comments | https://api.github.com/repos/huggingface/datasets/issues/5554/events | https://github.com/huggingface/datasets/pull/5554 | 1,592,285,062 | PR_kwDODunzps5KXhZh | 5,554 | Add resampy dep | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-20T18:15:43" | "2023-02-21T12:46:10" | "2023-02-21T12:43:38" | MEMBER | null | In librosa 0.10 they removed the `resmpy` dependency and set it to optional.
However it is necessary for resampling. I added it to the "audio" extra dependencies. | {
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https://api.github.com/repos/huggingface/datasets/issues/5552 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5552/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5552/comments | https://api.github.com/repos/huggingface/datasets/issues/5552/events | https://github.com/huggingface/datasets/pull/5552 | 1,592,186,703 | PR_kwDODunzps5KXMjA | 5,552 | Make tiktoken tokenizers hashable | {
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https://api.github.com/repos/huggingface/datasets/issues/5551 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5551/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5551/comments | https://api.github.com/repos/huggingface/datasets/issues/5551/events | https://github.com/huggingface/datasets/pull/5551 | 1,592,140,836 | PR_kwDODunzps5KXCof | 5,551 | Suggest scikit-learn instead of sklearn | {
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The current error message if sklearn is not installed:
```
ImportError: To be able to use [dataset name], you need to install the following dependency: sklearn.
Please install it using 'pip install sklearn' for instance.
```
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https://api.github.com/repos/huggingface/datasets/issues/5550 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5550/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5550/comments | https://api.github.com/repos/huggingface/datasets/issues/5550/events | https://github.com/huggingface/datasets/pull/5550 | 1,591,409,475 | PR_kwDODunzps5KUl5i | 5,550 | Resolve four broken refs in the docs | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-20T08:52:11" | "2023-02-20T15:16:13" | "2023-02-20T15:09:13" | CONTRIBUTOR | null | Hello!
## Pull Request overview
* Resolve 4 broken references in the docs
## The problems
Two broken references [here](https://huggingface.co/docs/datasets/package_reference/main_classes#datasets.Dataset.class_encode_column):
---
One broken reference [here](https://huggingface.co/docs/datasets/package_reference/main_classes#datasets.Dataset.unique):
---
One missing reference [here](https://huggingface.co/docs/datasets/v2.9.0/en/package_reference/main_classes#datasets.DatasetDict.class_encode_column):
- Tom Aarsen | {
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} | [] | closed | false | null | [] | null | [] | "2023-02-19T20:09:28" | "2023-02-23T14:06:39" | "2023-02-23T13:59:39" | CONTRIBUTOR | null | Fix #5548
Apply ruff's flake8-comprehension checks for better performance, and more readable code. | {
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] | closed | false | null | [] | null | [] | "2023-02-19T20:05:38" | "2023-02-23T13:59:41" | "2023-02-23T13:59:41" | CONTRIBUTOR | null | ### Feature request
Apply ruff flake8 comprehension checks to codebase.
### Motivation
This should strictly improve the performance / readability of the codebase by removing unnecessary iteration, function calls, etc. This should generate better Python bytecode which should strictly improve performance.
I already applied this fixes to PyTorch and Sympy with little issue and have opened PRs to diffusers and transformers todo this as well.
### Your contribution
Making a PR. | {
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