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After waiting for 2 hours, it still presents ``The dataset viewer should be available soon. Please retry later.''
### Steps to reproduce the bug
dataset link: https://huggingface.co/datasets/BryanW/HI_EDIT
### Expected behavior
Present the dataset viewer.
### Environment info
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} | don't include video bytes when running download_and_prepare(format="parquet")
this also affects push_to_hub which will just upload the local paths of the videos though | {
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} | Will be useful to distribute a dataset across workers (other than pytorch) like spark
I also renamed `.n_shards` -> `.num_shards` for consistency and kept the old name for backward compatibility. And a few changes in internal functions for consistency as well (rank, world_size -> num_shards, index)
Breaking change: the new default for `contiguous` in `Dataset.shard()` is `True`, but imo not a big deal since I couldn't find any usage of `contiguous=False` internally (we always do contiguous=True for map-style datasets since its more optimized) or in the wild | {
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} | enable the viewer for datasets like https://huggingface.co/datasets/FrancophonIA/e-calm (there will be more and more apparently)
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follow up to #7234 | {
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] | closed | false | null | [] | null | 9 | 2024-10-20T03:23:26 | 2024-10-24T17:39:08 | 2024-10-24T17:39:08 | NONE | null | null | null | ### Feature request
Add an `overwrite` argument to the `push_to_hub` method.
### Motivation
I want to overwrite a repo without deleting it on Hugging Face. Is this possible? I couldn't find anything in the documentation or tutorials.
### Your contribution
I can create a PR. | {
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csv kwargs docstring link was pointing to pandas json docs. | {
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https://api.github.com/repos/huggingface/datasets/issues/7232 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7232/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7232/comments | https://api.github.com/repos/huggingface/datasets/issues/7232/events | https://github.com/huggingface/datasets/pull/7232 | 2,593,720,548 | PR_kwDODunzps5-62rY | 7,232 | (Super tiny doc update) Mention to_polars | {
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} | Fix typo in image dataset docs.
Typo reported by @datavistics. | {
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https://api.github.com/repos/huggingface/datasets/issues/7230 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7230/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7230/comments | https://api.github.com/repos/huggingface/datasets/issues/7230/events | https://github.com/huggingface/datasets/pull/7230 | 2,589,531,942 | PR_kwDODunzps5-ttUV | 7,230 | Video support | {
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} | (wip and experimental)
adding the `Video` type based on `VideoReader` from `decord`
```python
>>>from datasets import load_dataset
>>> ds = load_dataset("path/to/videos", split="train").with_format("torch")
>>> print(ds[0]["video"])
<decord.video_reader.VideoReader object at 0x337a47910>
>>> print(ds[0]["video"][0])
tensor([[[73, 73, 73],
[73, 73, 73],
[73, 73, 73],
...,
[23, 23, 23],
[23, 23, 23],
[23, 23, 23]]], dtype=torch.uint8)
```
the storage is the same as for audio and images: `{"path": pa.string(), "bytes": pa.binary()}` and I did a small to keep the hf:// URL in the "path" field if possible, this way the viewer can link to fiels on the hub if possible | {
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https://api.github.com/repos/huggingface/datasets/issues/7229 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7229/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7229/comments | https://api.github.com/repos/huggingface/datasets/issues/7229/events | https://github.com/huggingface/datasets/pull/7229 | 2,588,847,398 | PR_kwDODunzps5-rgrx | 7,229 | handle config_name=None in push_to_hub | {
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https://api.github.com/repos/huggingface/datasets/issues/7219 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7219/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7219/comments | https://api.github.com/repos/huggingface/datasets/issues/7219/events | https://github.com/huggingface/datasets/pull/7219 | 2,581,708,084 | PR_kwDODunzps5-XAQF | 7,219 | bump fsspec | {
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https://api.github.com/repos/huggingface/datasets/issues/7209 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7209/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7209/comments | https://api.github.com/repos/huggingface/datasets/issues/7209/events | https://github.com/huggingface/datasets/pull/7209 | 2,575,526,651 | PR_kwDODunzps5-D6_P | 7,209 | Preserve features in iterable dataset.filter | {
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} | Fixes example in #7208 - I'm not sure what other checks I should do? @lhoestq
I also haven't thought hard about the concatenate / interleaving example iterables but think this might work assuming that features are either all identical or None? | {
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https://api.github.com/repos/huggingface/datasets/issues/7208 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7208/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7208/comments | https://api.github.com/repos/huggingface/datasets/issues/7208/events | https://github.com/huggingface/datasets/issues/7208 | 2,575,484,256 | I_kwDODunzps6ZgsVg | 7,208 | Iterable dataset.filter should not override features | {
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} | [] | closed | false | null | [] | null | 1 | 2024-10-09T10:23:45 | 2024-10-09T16:08:46 | 2024-10-09T16:08:45 | CONTRIBUTOR | null | null | null | ### Describe the bug
When calling filter on an iterable dataset, the features get set to None
### Steps to reproduce the bug
import numpy as np
import time
from datasets import Dataset, Features, Array3D
```python
features=Features(**{"array0": Array3D((None, 10, 10), dtype="float32"), "array1": Array3D((None,10,10), dtype="float32")})
dataset = Dataset.from_dict({f"array{i}": [np.zeros((x,10,10), dtype=np.float32) for x in [2000,1000]*25] for i in range(2)}, features=features)
ds = dataset.to_iterable_dataset()
orig_column_names = ds.column_names
ds = ds.filter(lambda x: True)
assert ds.column_names == orig_column_names
```
### Expected behavior
Filter should preserve features information
### Environment info
3.0.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/7205 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7205/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7205/comments | https://api.github.com/repos/huggingface/datasets/issues/7205/events | https://github.com/huggingface/datasets/pull/7205 | 2,573,490,859 | PR_kwDODunzps599w0I | 7,205 | fix ci benchmark | {
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} | we're not using the benchmarks anymore + they were not working anyway due to token permissions
I keep the code in case we ever want to re-run the benchmark manually | {
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https://api.github.com/repos/huggingface/datasets/issues/7204 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7204/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7204/comments | https://api.github.com/repos/huggingface/datasets/issues/7204/events | https://github.com/huggingface/datasets/pull/7204 | 2,573,289,063 | PR_kwDODunzps599Hem | 7,204 | fix unbatched arrow map for iterable datasets | {
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} | Fixes the bug when applying map to an arrow-formatted iterable dataset described here:
https://github.com/huggingface/datasets/issues/6833#issuecomment-2399903885
```python
from datasets import load_dataset
ds = load_dataset("rotten_tomatoes", split="train", streaming=True)
ds = ds.with_format("arrow").map(lambda x: x)
for ex in ds:
pass
```
@lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/7203 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7203/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7203/comments | https://api.github.com/repos/huggingface/datasets/issues/7203/events | https://github.com/huggingface/datasets/pull/7203 | 2,573,154,222 | PR_kwDODunzps598skr | 7,203 | with_format docstring | {
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} | reported at https://github.com/huggingface/datasets/issues/3444 | {
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https://api.github.com/repos/huggingface/datasets/issues/7200 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7200/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7200/comments | https://api.github.com/repos/huggingface/datasets/issues/7200/events | https://github.com/huggingface/datasets/pull/7200 | 2,567,921,694 | PR_kwDODunzps59sgRd | 7,200 | Fix the environment variable for huggingface cache | {
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} | Resolve #6256. As far as I tested, `HF_DATASETS_CACHE` was ignored and I could not specify the cache directory at all except for the default one by this environment variable. `HF_HOME` has worked. Perhaps the recent change on file downloading by `huggingface_hub` could affect this bug.
In my testing, I could not specify the cache directory even by `load_dataset("dataset_name" cache_dir="...")`. It might be another issue. I also welcome any advice to solve this issue. | {
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https://api.github.com/repos/huggingface/datasets/issues/7194 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7194/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7194/comments | https://api.github.com/repos/huggingface/datasets/issues/7194/events | https://github.com/huggingface/datasets/issues/7194 | 2,563,364,199 | I_kwDODunzps6YydVn | 7,194 | datasets.exceptions.DatasetNotFoundError for private dataset | {
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} | [] | closed | false | null | [] | null | 2 | 2024-10-03T07:49:36 | 2024-10-03T10:09:28 | 2024-10-03T10:09:28 | NONE | null | null | null | ### Describe the bug
The following Python code tries to download a private dataset and fails with the error `datasets.exceptions.DatasetNotFoundError: Dataset 'ClimatePolicyRadar/all-document-text-data-weekly' doesn't exist on the Hub or cannot be accessed.`. Downloading a public dataset doesn't work.
``` py
from datasets import load_dataset
_ = load_dataset("ClimatePolicyRadar/all-document-text-data-weekly")
```
This seems to be just an issue with my machine config as the code above works with a colleague's machine. So far I have tried:
- logging back out and in from the Huggingface CLI using `huggingface-cli logout`
- manually removing the token cache at `/Users/kalyan/.cache/huggingface/token` (found using `huggingface-cli env`)
- manually passing a token in `load_dataset`
My output of `huggingface-cli whoami`:
```
kdutia
orgs: ClimatePolicyRadar
```
### Steps to reproduce the bug
```
python
Python 3.12.2 (main, Feb 6 2024, 20:19:44) [Clang 15.0.0 (clang-1500.1.0.2.5)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from datasets import load_dataset
>>> _ = load_dataset("ClimatePolicyRadar/all-document-text-data-weekly")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/kalyan/Library/Caches/pypoetry/virtualenvs/open-data-cnKQNmjn-py3.12/lib/python3.12/site-packages/datasets/load.py", line 2074, in load_dataset
builder_instance = load_dataset_builder(
^^^^^^^^^^^^^^^^^^^^^
File "/Users/kalyan/Library/Caches/pypoetry/virtualenvs/open-data-cnKQNmjn-py3.12/lib/python3.12/site-packages/datasets/load.py", line 1795, in load_dataset_builder
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kalyan/Library/Caches/pypoetry/virtualenvs/open-data-cnKQNmjn-py3.12/lib/python3.12/site-packages/datasets/load.py", line 1659, in dataset_module_factory
raise e1 from None
File "/Users/kalyan/Library/Caches/pypoetry/virtualenvs/open-data-cnKQNmjn-py3.12/lib/python3.12/site-packages/datasets/load.py", line 1597, in dataset_module_factory
raise DatasetNotFoundError(f"Dataset '{path}' doesn't exist on the Hub or cannot be accessed.") from e
datasets.exceptions.DatasetNotFoundError: Dataset 'ClimatePolicyRadar/all-document-text-data-weekly' doesn't exist on the Hub or cannot be accessed.
>>>
```
### Expected behavior
The dataset downloads successfully.
### Environment info
From `huggingface-cli env`:
```
- huggingface_hub version: 0.25.1
- Platform: macOS-14.2.1-arm64-arm-64bit
- Python version: 3.12.2
- Running in iPython ?: No
- Running in notebook ?: No
- Running in Google Colab ?: No
- Running in Google Colab Enterprise ?: No
- Token path ?: /Users/kalyan/.cache/huggingface/token
- Has saved token ?: True
- Who am I ?: kdutia
- Configured git credential helpers: osxkeychain
- FastAI: N/A
- Tensorflow: N/A
- Torch: N/A
- Jinja2: 3.1.4
- Graphviz: N/A
- keras: N/A
- Pydot: N/A
- Pillow: N/A
- hf_transfer: N/A
- gradio: N/A
- tensorboard: N/A
- numpy: 2.1.1
- pydantic: N/A
- aiohttp: 3.10.8
- ENDPOINT: https://huggingface.co
- HF_HUB_CACHE: /Users/kalyan/.cache/huggingface/hub
- HF_ASSETS_CACHE: /Users/kalyan/.cache/huggingface/assets
- HF_TOKEN_PATH: /Users/kalyan/.cache/huggingface/token
- HF_HUB_OFFLINE: False
- HF_HUB_DISABLE_TELEMETRY: False
- HF_HUB_DISABLE_PROGRESS_BARS: None
- HF_HUB_DISABLE_SYMLINKS_WARNING: False
- HF_HUB_DISABLE_EXPERIMENTAL_WARNING: False
- HF_HUB_DISABLE_IMPLICIT_TOKEN: False
- HF_HUB_ENABLE_HF_TRANSFER: False
- HF_HUB_ETAG_TIMEOUT: 10
- HF_HUB_DOWNLOAD_TIMEOUT: 10
```
from `datasets-cli env`:
```
- `datasets` version: 3.0.1
- Platform: macOS-14.2.1-arm64-arm-64bit
- Python version: 3.12.2
- `huggingface_hub` version: 0.25.1
- PyArrow version: 17.0.0
- Pandas version: 2.2.3
- `fsspec` version: 2024.6.1
``` | {
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} | Pin multiprocess<0.70.1 to align with dill<0.3.9.
Note that multiprocess-0.70.1 requires dill-0.3.9: https://github.com/uqfoundation/multiprocess/releases/tag/0.70.17
Fix #7186. | {
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https://api.github.com/repos/huggingface/datasets/issues/7186 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7186/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7186/comments | https://api.github.com/repos/huggingface/datasets/issues/7186/events | https://github.com/huggingface/datasets/issues/7186 | 2,560,323,917 | I_kwDODunzps6Ym3FN | 7,186 | pinning `dill<0.3.9` without pinning `multiprocess` | {
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] | null | 0 | 2024-10-01T22:29:32 | 2024-10-02T06:08:24 | 2024-10-02T06:08:24 | NONE | null | null | null | ### Describe the bug
The [latest `multiprocess` release](https://github.com/uqfoundation/multiprocess/releases/tag/0.70.17) requires `dill>=0.3.9` which causes issues when installing `datasets` without backtracking during package version resolution. Is it possible to add a pin for multiprocess so something like `multiprocess<=0.70.16` so that the `dill` version is compatible?
### Steps to reproduce the bug
NA
### Expected behavior
NA
### Environment info
NA | {
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https://api.github.com/repos/huggingface/datasets/issues/7185 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7185/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7185/comments | https://api.github.com/repos/huggingface/datasets/issues/7185/events | https://github.com/huggingface/datasets/issues/7185 | 2,558,508,748 | I_kwDODunzps6Yf77M | 7,185 | CI benchmarks are broken | {
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] | closed | false | null | [] | null | 1 | 2024-10-01T08:16:08 | 2024-10-09T16:07:48 | 2024-10-09T16:07:48 | MEMBER | null | null | null | Since Aug 30, 2024, CI benchmarks are broken: https://github.com/huggingface/datasets/actions/runs/11108421214/job/30861323975
```
{"level":"error","message":"Resource not accessible by integration","name":"HttpError","request":{"body":"{\"body\":\"<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 |
...
"headers":{"accept":"application/vnd.github.v3+json","authorization":"token [REDACTED]","content-type":"application/json; charset=utf-8","user-agent":"octokit-rest.js/18.0.0 octokit-core.js/3.6.0 Node.js/16.20.2 (linux; x64)"},"method":"POST","request":{"agent":{"_events":{},"_eventsCount":2,"cache":
...
"response":{"data":{"documentation_url":"https://docs.github.com/rest/issues/comments#create-an-issue-comment","message":"Resource not accessible by integration","status":"403"},
...
"stack":"HttpError: Resource not accessible by integration\n at /usr/lib/node_modules/@dvcorg/cml/node_modules/@octokit/request/dist-node/index.js:86:21\n at processTicksAndRejections (node:internal/process/task_queues:96:5)\n at async Job.doExecute (/usr/lib/node_modules/@dvcorg/cml/node_modules/bottleneck/light.js:405:18)","status":403}
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/7184 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7184/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7184/comments | https://api.github.com/repos/huggingface/datasets/issues/7184/events | https://github.com/huggingface/datasets/pull/7184 | 2,556,855,150 | PR_kwDODunzps59IPEf | 7,184 | Pin dill<0.3.9 to fix CI | {
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} | Pin dill<0.3.9 to fix CI for deps-latest.
Note that dill-0.3.9 was released yesterday Sep 29, 2024:
- https://pypi.org/project/dill/0.3.9/
- https://github.com/uqfoundation/dill/releases/tag/0.3.9
Fix #7183. | {
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https://api.github.com/repos/huggingface/datasets/issues/7183 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7183/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7183/comments | https://api.github.com/repos/huggingface/datasets/issues/7183/events | https://github.com/huggingface/datasets/issues/7183 | 2,556,789,055 | I_kwDODunzps6YZYE_ | 7,183 | CI is broken for deps-latest | {
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```
=========================== short test summary info ============================
FAILED tests/test_arrow_dataset.py::BaseDatasetTest::test_filter_caching_on_disk - AssertionError: Lists differ: [{'fi[44 chars] {'filename': '/tmp/tmp6xcyyjs4/cache-9533fe2601cd3e48.arrow'}] != [{'fi[44 chars] {'filename': '/tmp/tmp6xcyyjs4/cache-e6e0a8b830976289.arrow'}]
First differing element 1:
{'filename': '/tmp/tmp6xcyyjs4/cache-9533fe2601cd3e48.arrow'}
{'filename': '/tmp/tmp6xcyyjs4/cache-e6e0a8b830976289.arrow'}
[{'filename': '/tmp/tmp6xcyyjs4/dataset0.arrow'},
- {'filename': '/tmp/tmp6xcyyjs4/cache-9533fe2601cd3e48.arrow'}]
? ^^^^^ --------
+ {'filename': '/tmp/tmp6xcyyjs4/cache-e6e0a8b830976289.arrow'}]
? ++++++++++ ^^ +
FAILED tests/test_arrow_dataset.py::BaseDatasetTest::test_map_caching_on_disk - AssertionError: Lists differ: [{'filename': '/tmp/tmp5gxrti_n/cache-e58d327daec8626f.arrow'}] != [{'filename': '/tmp/tmp5gxrti_n/cache-d87234c5763e54a3.arrow'}]
First differing element 0:
{'filename': '/tmp/tmp5gxrti_n/cache-e58d327daec8626f.arrow'}
{'filename': '/tmp/tmp5gxrti_n/cache-d87234c5763e54a3.arrow'}
- [{'filename': '/tmp/tmp5gxrti_n/cache-e58d327daec8626f.arrow'}]
? ^^ -----------
+ [{'filename': '/tmp/tmp5gxrti_n/cache-d87234c5763e54a3.arrow'}]
? +++++++++++ ^^
FAILED tests/test_fingerprint.py::TokenizersHashTest::test_hash_regex - NameError: name 'log' is not defined
FAILED tests/test_fingerprint.py::RecurseHashTest::test_hash_ignores_line_definition_of_function - AssertionError: '52e56ee04ad92499' != '0a4f75cec280f634'
- 52e56ee04ad92499
+ 0a4f75cec280f634
FAILED tests/test_fingerprint.py::RecurseHashTest::test_hash_ipython_function - AssertionError: 'a6bd2041ca63d6c0' != '517bf36b7eecdef5'
- a6bd2041ca63d6c0
+ 517bf36b7eecdef5
FAILED tests/test_fingerprint.py::HashingTest::test_hash_tiktoken_encoding - NameError: name 'log' is not defined
FAILED tests/test_fingerprint.py::HashingTest::test_hash_torch_compiled_module - NameError: name 'log' is not defined
FAILED tests/test_fingerprint.py::HashingTest::test_hash_torch_generator - NameError: name 'log' is not defined
FAILED tests/test_fingerprint.py::HashingTest::test_hash_torch_tensor - NameError: name 'log' is not defined
FAILED tests/test_fingerprint.py::HashingTest::test_set_doesnt_depend_on_order - NameError: name 'log' is not defined
FAILED tests/test_fingerprint.py::HashingTest::test_set_stable - NameError: name 'log' is not defined
ERROR tests/test_iterable_dataset.py::test_iterable_dataset_from_file - NameError: name 'log' is not defined
= 11 failed, 2850 passed, 3 skipped, 23 warnings, 1 error in 191.06s (0:03:11) =
``` | {
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} | Support features in metadata configs, like:
```
configs:
- config_name: default
features:
- name: id
dtype: int64
- name: name
dtype: string
- name: score
dtype: float64
```
This will allow to avoid inference of data types.
Currently, we allow passing this information in the `dataset_info` (instead of `configs`) field, but this is not intuitive and it is not properly documented.
TODO:
- [ ] Document usage | {
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https://api.github.com/repos/huggingface/datasets/issues/7181 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7181/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7181/comments | https://api.github.com/repos/huggingface/datasets/issues/7181/events | https://github.com/huggingface/datasets/pull/7181 | 2,554,917,019 | PR_kwDODunzps59Br4E | 7,181 | Fix datasets export to JSON | {
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https://api.github.com/repos/huggingface/datasets/issues/7180 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7180/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7180/comments | https://api.github.com/repos/huggingface/datasets/issues/7180/events | https://github.com/huggingface/datasets/issues/7180 | 2,554,244,750 | I_kwDODunzps6YPq6O | 7,180 | Memory leak when wrapping datasets into PyTorch Dataset without explicit deletion | {
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} | [] | closed | false | null | [] | null | 1 | 2024-09-28T14:00:47 | 2024-09-30T12:07:56 | 2024-09-30T12:07:56 | NONE | null | null | null | ### Describe the bug
I've encountered a memory leak when wrapping the HuggingFace dataset into a PyTorch Dataset. The RAM usage constantly increases during iteration if items are not explicitly deleted after use.
### Steps to reproduce the bug
Steps to reproduce:
Create a PyTorch Dataset wrapper for 'nebula/cc12m':
````
from torch.utils.data import Dataset
from tqdm import tqdm
from datasets import load_dataset
from torchvision import transforms
Image.MAX_IMAGE_PIXELS = None
class CC12M(Dataset):
def __init__(self, path_or_name='nebula/cc12m', split='train', transform=None, single_caption=True):
self.raw_dataset = load_dataset(path_or_name)[split]
if transform is None:
self.transform = transforms.Compose([
transforms.Resize((224, 224)),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize(
mean=[0.48145466, 0.4578275, 0.40821073],
std=[0.26862954, 0.26130258, 0.27577711]
)
])
else:
self.transform = transforms.Compose(transform)
self.single_caption = single_caption
self.length = len(self.raw_dataset)
def __len__(self):
return self.length
def __getitem__(self, index):
item = self.raw_dataset[index]
caption = item['txt']
with io.BytesIO(item['webp']) as buffer:
image = Image.open(buffer).convert('RGB')
if self.transform:
image = self.transform(image)
# del item # Uncomment this line to prevent the memory leak
return image, caption
````
Iterate through the dataset without the del item line in __getitem__.
Observe RAM usage increasing constantly.
Add del item at the end of __getitem__:
```
def __getitem__(self, index):
item = self.raw_dataset[index]
caption = item['txt']
with io.BytesIO(item['webp']) as buffer:
image = Image.open(buffer).convert('RGB')
if self.transform:
image = self.transform(image)
del item # This line prevents the memory leak
return image, caption
```
Iterate through the dataset again and observe that RAM usage remains stable.
### Expected behavior
Expected behavior:
RAM usage should remain stable during iteration without needing to explicitly delete items.
Actual behavior:
RAM usage constantly increases unless items are explicitly deleted after use
### Environment info
- `datasets` version: 2.21.0
- Platform: Linux-4.18.0-513.5.1.el8_9.x86_64-x86_64-with-glibc2.28
- Python version: 3.12.4
- `huggingface_hub` version: 0.24.6
- PyArrow version: 17.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.6.1
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Fix #7178. | {
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During last release, I had to make this additional update. | {
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} | [] | closed | false | null | [] | null | 6 | 2024-09-26T15:42:29 | 2024-10-26T16:12:57 | 2024-09-30T17:28:35 | NONE | null | null | null | ### Describe the bug
When using `load_dataset`to load [HuggingFaceM4/VQAv2](https://huggingface.co/datasets/HuggingFaceM4/VQAv2), I am getting `FSTimeoutError`.
### Error
```
TimeoutError:
The above exception was the direct cause of the following exception:
FSTimeoutError Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/fsspec/asyn.py](https://klh9mr78js-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20240924-060116_RC00_678132060#) in sync(loop, func, timeout, *args, **kwargs)
99 if isinstance(return_result, asyncio.TimeoutError):
100 # suppress asyncio.TimeoutError, raise FSTimeoutError
--> 101 raise FSTimeoutError from return_result
102 elif isinstance(return_result, BaseException):
103 raise return_result
FSTimeoutError:
```
It usually fails around 5-6 GB.
<img width="847" alt="Screenshot 2024-09-26 at 9 10 19 PM" src="https://github.com/user-attachments/assets/ff91995a-fb55-4de6-8214-94025d6c8470">
### Steps to reproduce the bug
To reproduce it, run this in colab notebook:
```
!pip install -q -U datasets
from datasets import load_dataset
ds = load_dataset('HuggingFaceM4/VQAv2', split="train[:10%]")
```
### Expected behavior
It should download properly.
### Environment info
Using Colab Notebook. | {
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