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The dataset generation failed
Error code: DatasetGenerationError
Exception: DatasetGenerationError
Message: An error occurred while generating the dataset
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in cast_table_to_schema
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2116, in cast_array_to_feature
return array_cast(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1964, in array_cast
raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
TypeError: Couldn't cast array of type struct<url: string, html_url: string, labels_url: string, id: int64, node_id: string, number: int64, title: string, description: string, creator: struct<login: string, id: int64, node_id: string, avatar_url: string, gravatar_id: string, url: string, html_url: string, followers_url: string, following_url: string, gists_url: string, starred_url: string, subscriptions_url: string, organizations_url: string, repos_url: string, events_url: string, received_events_url: string, type: string, site_admin: bool>, open_issues: int64, closed_issues: int64, state: string, created_at: int64, updated_at: int64, due_on: int64, closed_at: int64> to null
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2038, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Open a discussion for direct support.
url
string | repository_url
string | labels_url
string | comments_url
string | events_url
string | html_url
string | id
int64 | node_id
string | number
int64 | title
string | user
dict | labels
list | state
string | locked
bool | assignee
dict | assignees
list | milestone
null | comments
sequence | created_at
int64 | updated_at
int64 | closed_at
int64 | author_association
string | active_lock_reason
null | body
string | reactions
dict | timeline_url
string | performed_via_github_app
null | state_reason
null | draft
bool | pull_request
dict | is_pull_request
bool |
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https://api.github.com/repos/huggingface/datasets/issues/4989 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4989/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4989/comments | https://api.github.com/repos/huggingface/datasets/issues/4989/events | https://github.com/huggingface/datasets/issues/4989 | 1,376,832,233 | I_kwDODunzps5SEMrp | 4,989 | Running add_column() seems to corrupt existing sequence-type column info | {
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] | open | false | null | [] | null | [] | 1,663,436,525,000 | 1,663,436,525,000 | null | NONE | null | I have a dataset that contains a column ("foo") that is a sequence type of length 4. So when I run .to_pandas() on it, the resulting dataframe correctly contains 4 columns - foo_0, foo_1, foo_2, foo_3. So the 1st row of the dataframe might look like:
ds = load_dataset(...)
df = ds.to_pandas()
df:
foo_0 | foo_1 | foo_2 | foo_3
0.0 | 1.0 | 2.0 | 3.0
If I run .add_column("new_col", data) on the dataset, and then .to_pandas() on the resulting new dataset, the resulting dataframe contains only 2 columns - foo, new_col. The values in column foo are lists of length 4, the 4 elements that should have been split into separate columns. Dataframe 1st row would be:
ds = load_dataset(...)
new_ds = ds.add_column("new_col", data)
df = new_ds.to_pandas()
df:
foo | new_col
[0.0, 1.0, 2.0, 3.0] | new_val
I've explored the 2 datasets in a debugger and haven't noticed any changes to any attributes related to the foo column, but I can't determine why the dataframes are so different. | {
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https://api.github.com/repos/huggingface/datasets/issues/4988 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4988/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4988/comments | https://api.github.com/repos/huggingface/datasets/issues/4988/events | https://github.com/huggingface/datasets/issues/4988 | 1,376,096,584 | I_kwDODunzps5SBZFI | 4,988 | Add `IterableDataset.from_generator` to the API | {
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"#take"
] | 1,663,341,581,000 | 1,663,434,419,000 | null | CONTRIBUTOR | null | We've just added `Dataset.from_generator` to the API. It would also be cool to add `IterableDataset.from_generator` to support creating an iterable dataset from a generator.
cc @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/4987 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4987/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4987/comments | https://api.github.com/repos/huggingface/datasets/issues/4987/events | https://github.com/huggingface/datasets/pull/4987 | 1,376,006,477 | PR_kwDODunzps4_GlIu | 4,987 | Embed image/audio data in dl_and_prepare parquet | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,663,337,367,000 | 1,663,345,487,000 | 1,663,345,355,000 | MEMBER | null | Embed the bytes of the image or audio files in the Parquet files directly, instead of having a "path" that points to a local file.
Indeed Parquet files are often used to share data or to be used by workers that may not have access to the local files. | {
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https://api.github.com/repos/huggingface/datasets/issues/4986 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4986/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4986/comments | https://api.github.com/repos/huggingface/datasets/issues/4986/events | https://github.com/huggingface/datasets/pull/4986 | 1,375,895,035 | PR_kwDODunzps4_GNSd | 4,986 | [doc] Fix broken snippet that had too many quotes | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Spent the day familiarising myself with the huggingface line of products, and happened to run into some small issues here and there. Magically, I've found exactly one small issue in `transformers`, one in `accelerate` and now one in `datasets`, hah!\r\n\r\nAs for this PR, the issue seems solved according to the [new PR documentation](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4986/en/process#map):\r\n\r\n"
] | 1,663,332,067,000 | 1,663,366,341,000 | 1,663,349,534,000 | CONTRIBUTOR | null | Hello!
### Pull request overview
* Fix broken snippet in https://huggingface.co/docs/datasets/main/en/process that has too many quotes
### Details
The snippet in question can be found here: https://huggingface.co/docs/datasets/main/en/process#map
This screenshot shows the issue, there is a quote too many, causing the snippet to be colored incorrectly:
The change speaks for itself.
Thank you for the detailed documentation, by the way.
- Tom Aarsen
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https://api.github.com/repos/huggingface/datasets/issues/4985 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4985/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4985/comments | https://api.github.com/repos/huggingface/datasets/issues/4985/events | https://github.com/huggingface/datasets/pull/4985 | 1,375,807,768 | PR_kwDODunzps4_F6kU | 4,985 | [WIP] Prefer split patterns from directories over split patterns from filenames | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4985). All of your documentation changes will be reflected on that endpoint."
] | 1,663,327,240,000 | 1,663,334,541,000 | null | CONTRIBUTOR | null | related to https://github.com/huggingface/datasets/issues/4895
todo:
- [ ] test | {
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https://api.github.com/repos/huggingface/datasets/issues/4984 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4984/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4984/comments | https://api.github.com/repos/huggingface/datasets/issues/4984/events | https://github.com/huggingface/datasets/pull/4984 | 1,375,690,330 | PR_kwDODunzps4_FhTm | 4,984 | docs: βοΈ add links to the Datasets API | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"OK, thanks @lhoestq. I'll close this PR, and come back to it with @stevhliu once we work on https://github.com/huggingface/datasets-server/issues/568"
] | 1,663,320,852,000 | 1,663,333,814,000 | 1,663,333,653,000 | CONTRIBUTOR | null | I added some links to the Datasets API in the docs. See https://github.com/huggingface/datasets-server/pull/566 for a companion PR in the datasets-server. The idea is to improve the discovery of the API through the docs.
I'm a bit shy about pasting a lot of links to the API in the docs, so it's minimal for now. I'm interested in ideas to integrate the API better in these docs without being too much. cc @lhoestq @julien-c @albertvillanova @stevhliu. | {
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https://api.github.com/repos/huggingface/datasets/issues/4983 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4983/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4983/comments | https://api.github.com/repos/huggingface/datasets/issues/4983/events | https://github.com/huggingface/datasets/issues/4983 | 1,375,667,654 | I_kwDODunzps5R_wXG | 4,983 | How to convert torch.utils.data.Dataset to huggingface dataset? | {
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"Hi! I think you can use the newly-added `from_generator` method for that:\r\n```python\r\nfrom datasets import Dataset\r\n\r\ndef gen():\r\n for idx in len(torch_dataset):\r\n yield torch_dataset[idx] # this has to be a dictionary\r\n ## or if it's an IterableDataset\r\n # for ex in torch_dataset:\r\n # yield ex\r\n\r\ndset = Dataset.from_generator(gen)\r\n```"
] | 1,663,319,710,000 | 1,663,342,106,000 | null | NONE | null | I look through the huggingface dataset docs, and it seems that there is no offical support function to convert `torch.utils.data.Dataset` to huggingface dataset. However, there is a way to convert huggingface dataset to `torch.utils.data.Dataset`, like below:
```python
from datasets import Dataset
data = [[1, 2],[3, 4]]
ds = Dataset.from_dict({"data": data})
ds = ds.with_format("torch")
ds[0]
ds[:2]
```
So is there something I miss, or there IS no function to convert `torch.utils.data.Dataset` to huggingface dataset. If so, is there any way to do this convert?
Thanks. | {
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https://api.github.com/repos/huggingface/datasets/issues/4982 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4982/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4982/comments | https://api.github.com/repos/huggingface/datasets/issues/4982/events | https://github.com/huggingface/datasets/issues/4982 | 1,375,604,693 | I_kwDODunzps5R_g_V | 4,982 | Create dataset_infos.json with VALIDATION and TEST splits | {
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] | open | false | null | [] | null | [] | 1,663,316,479,000 | 1,663,323,163,000 | null | NONE | null | The problem is described in that [issue](https://github.com/huggingface/datasets/issues/4895#issuecomment-1247975569).
> When I try to create data_infos.json using datasets-cli test Peter.py --save_infos --all_configs I get an error:
> ValueError: Unknown split "test". Should be one of ['train'].
>
> The data_infos.json is created perfectly fine when I use only one split - datasets.Split.TRAIN
>
> You can find the code here: https://huggingface.co/datasets/sberbank-ai/Peter/tree/add_splits (add_splits branch)
I tried to clear the cache folder, than I got an another error. I run:
```
rm -r ~/.cache/huggingface
datasets-cli test Peter.py --save_infos --all_configs
```
The error message:
```
Using custom data configuration default
Testing builder 'default' (1/1)
Downloading and preparing dataset peter/default to /Users/kalinin/.cache/huggingface/datasets/peter/default/0.0.0/ef579519e140d6a40df2555996f26165f04c47557d7373709c8d7e7b4fd7465d...
Downloading data files: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 4/4 [00:00<00:00, 5160.63it/s]
Extracting data files: 0%| | 0/4 [00:00<?, ?it/s]Traceback (most recent call last):
File "/usr/local/bin/datasets-cli", line 8, in <module>
sys.exit(main())
File "/usr/local/lib/python3.9/site-packages/datasets/commands/datasets_cli.py", line 39, in main
service.run()
File "/usr/local/lib/python3.9/site-packages/datasets/commands/test.py", line 137, in run
builder.download_and_prepare(
File "/usr/local/lib/python3.9/site-packages/datasets/builder.py", line 704, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.9/site-packages/datasets/builder.py", line 1227, in _download_and_prepare
super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos)
File "/usr/local/lib/python3.9/site-packages/datasets/builder.py", line 771, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/Users/kalinin/.cache/huggingface/modules/datasets_modules/datasets/Peter/ef579519e140d6a40df2555996f26165f04c47557d7373709c8d7e7b4fd7465d/Peter.py", line 23, in _split_generators
data_files = dl_manager.download_and_extract(_URLS)
File "/usr/local/lib/python3.9/site-packages/datasets/download/download_manager.py", line 431, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/usr/local/lib/python3.9/site-packages/datasets/download/download_manager.py", line 403, in extract
extracted_paths = map_nested(
File "/usr/local/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 393, in map_nested
mapped = [
File "/usr/local/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 394, in <listcomp>
_single_map_nested((function, obj, types, None, True, None))
File "/usr/local/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 330, in _single_map_nested
return function(data_struct)
File "/usr/local/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 213, in cached_path
output_path = ExtractManager(cache_dir=download_config.cache_dir).extract(
File "/usr/local/lib/python3.9/site-packages/datasets/utils/extract.py", line 46, in extract
self.extractor.extract(input_path, output_path, extractor_format)
File "/usr/local/lib/python3.9/site-packages/datasets/utils/extract.py", line 263, in extract
with FileLock(lock_path):
File "/usr/local/lib/python3.9/site-packages/datasets/utils/filelock.py", line 399, in __init__
max_filename_length = os.statvfs(os.path.dirname(lock_file)).f_namemax
FileNotFoundError: [Errno 2] No such file or directory: ''
Exception ignored in: <function BaseFileLock.__del__ at 0x11caeec10>
Traceback (most recent call last):
File "/usr/local/lib/python3.9/site-packages/datasets/utils/filelock.py", line 328, in __del__
self.release(force=True)
File "/usr/local/lib/python3.9/site-packages/datasets/utils/filelock.py", line 303, in release
with self._thread_lock:
AttributeError: 'UnixFileLock' object has no attribute '_thread_lock'
Extracting data files: 0%| | 0/4 [00:00<?, ?it/s]
```
Can you help me please?
## Environment info
- `datasets` version: 2.4.0
- Platform: macOS-12.5.1-x86_64-i386-64bit
- Python version: 3.9.5
- PyArrow version: 9.0.0
- Pandas version: 1.2.4
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https://api.github.com/repos/huggingface/datasets/issues/4981 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4981/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4981/comments | https://api.github.com/repos/huggingface/datasets/issues/4981/events | https://github.com/huggingface/datasets/issues/4981 | 1,375,086,773 | I_kwDODunzps5R9ii1 | 4,981 | Can't create a dataset with `float16` features | {
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] | open | false | null | [] | null | [
"Hi @dconathan, thanks for reporting.\r\n\r\nWe rely on Arrow as a backend, and as far as I know currently support for `float16` in Arrow is not fully implemented in Python (C++), hence the `ArrowNotImplementedError` you get.\r\n\r\nSee, e.g.: https://arrow.apache.org/docs/status.html?highlight=float16#data-types",
"Thanks for the linkβ¦. didnβt realize arrow didnβt support it yet. Should it be removed from https://huggingface.co/docs/datasets/v2.4.0/en/package_reference/main_classes#datasets.Value until Arrow supports it?",
"Yes, you are right: maybe we should either remove it from our docs or add a comment explaining the issue.\r\n\r\nThe thing is that in Arrow it is partially supported: you can create `float16` values, but you can't cast them from/to other types. And current implementation of `Value` always tries to perform a cast from `float64` to `float16`."
] | 1,663,275,804,000 | 1,663,322,231,000 | null | NONE | null | ## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried older versions of `pyarrow` as well with the same exact error.
The bug seems to arise from `datasets` casting the values to `double` and then `pyarrow` doesn't know how to convert those back to `float16`... does that sound right? Is there a way to bypass this since it's not necessary in the `numpy` and `torch` cases?
Thanks!
## Steps to reproduce the bug
All of the following raise the following error with the same exact (as far as I can tell) traceback:
```python
ArrowNotImplementedError: Unsupported cast from double to halffloat using function cast_half_float
```
```python
from datasets import Dataset, Features, Value
Dataset.from_dict({"x": [0.0, 1.0, 2.0]}, features=Features(x=Value("float16")))
import numpy as np
Dataset.from_dict({"x": np.arange(3, dtype=np.float16)}, features=Features(x=Value("float16")))
import torch
Dataset.from_dict({"x": torch.arange(3).to(torch.float16)}, features=Features(x=Value("float16")))
```
## Expected results
A dataset with `float16` features is successfully created.
## Actual results
```python
---------------------------------------------------------------------------
ArrowNotImplementedError Traceback (most recent call last)
Cell In [14], line 1
----> 1 Dataset.from_dict({"x": [1.0, 2.0, 3.0]}, features=Features(x=Value("float16")))
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/arrow_dataset.py:870, in Dataset.from_dict(cls, mapping, features, info, split)
865 mapping = features.encode_batch(mapping)
866 mapping = {
867 col: OptimizedTypedSequence(data, type=features[col] if features is not None else None, col=col)
868 for col, data in mapping.items()
869 }
--> 870 pa_table = InMemoryTable.from_pydict(mapping=mapping)
871 if info.features is None:
872 info.features = Features({col: ts.get_inferred_type() for col, ts in mapping.items()})
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:750, in InMemoryTable.from_pydict(cls, *args, **kwargs)
734 @classmethod
735 def from_pydict(cls, *args, **kwargs):
736 """
737 Construct a Table from Arrow arrays or columns
738
(...)
748 :class:`datasets.table.Table`:
749 """
--> 750 return cls(pa.Table.from_pydict(*args, **kwargs))
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/table.pxi:3648, in pyarrow.lib.Table.from_pydict()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/table.pxi:5174, in pyarrow.lib._from_pydict()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:343, in pyarrow.lib.asarray()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:231, in pyarrow.lib.array()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:110, in pyarrow.lib._handle_arrow_array_protocol()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py:197, in TypedSequence.__arrow_array__(self, type)
192 # otherwise we can finally use the user's type
193 elif type is not None:
194 # We use cast_array_to_feature to support casting to custom types like Audio and Image
195 # Also, when trying type "string", we don't want to convert integers or floats to "string".
196 # We only do it if trying_type is False - since this is what the user asks for.
--> 197 out = cast_array_to_feature(out, type, allow_number_to_str=not self.trying_type)
198 return out
199 except (TypeError, pa.lib.ArrowInvalid) as e: # handle type errors and overflows
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1683, in _wrap_for_chunked_arrays.<locals>.wrapper(array, *args, **kwargs)
1681 return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
1682 else:
-> 1683 return func(array, *args, **kwargs)
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1853, in cast_array_to_feature(array, feature, allow_number_to_str)
1851 return array_cast(array, get_nested_type(feature), allow_number_to_str=allow_number_to_str)
1852 elif not isinstance(feature, (Sequence, dict, list, tuple)):
-> 1853 return array_cast(array, feature(), allow_number_to_str=allow_number_to_str)
1854 raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}")
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1683, in _wrap_for_chunked_arrays.<locals>.wrapper(array, *args, **kwargs)
1681 return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
1682 else:
-> 1683 return func(array, *args, **kwargs)
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1762, in array_cast(array, pa_type, allow_number_to_str)
1760 if pa.types.is_null(pa_type) and not pa.types.is_null(array.type):
1761 raise TypeError(f"Couldn't cast array of type {array.type} to {pa_type}")
-> 1762 return array.cast(pa_type)
1763 raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{pa_type}")
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:919, in pyarrow.lib.Array.cast()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/compute.py:389, in cast(arr, target_type, safe, options)
387 else:
388 options = CastOptions.safe(target_type)
--> 389 return call_function("cast", [arr], options)
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/_compute.pyx:560, in pyarrow._compute.call_function()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/_compute.pyx:355, in pyarrow._compute.Function.call()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/error.pxi:144, in pyarrow.lib.pyarrow_internal_check_status()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/error.pxi:121, in pyarrow.lib.check_status()
ArrowNotImplementedError: Unsupported cast from double to halffloat using function cast_half_float
```
## Environment info
- `datasets` version: 2.4.0
- Platform: macOS-12.5.1-arm64-arm-64bit
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.4.4
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https://api.github.com/repos/huggingface/datasets/issues/4980 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4980/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4980/comments | https://api.github.com/repos/huggingface/datasets/issues/4980/events | https://github.com/huggingface/datasets/issues/4980 | 1,374,868,083 | I_kwDODunzps5R8tJz | 4,980 | Make `pyarrow` optional | {
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"The whole datasets library is pretty much a wrapper to pyarrow (just take a look at some of the source for a Dataset) https://github.com/huggingface/datasets/blob/51aef08ad7053c0bfe8f9a961207b26df15850d3/src/datasets/arrow_dataset.py#L639 \r\n\r\nI think removing the pyarrow dependency would involve a complete rewrite / a different library with minimal functionality (datasets-lite ?)",
"Thanks for the proposal, @KOLANICH. And also thanks for your answer, @dconathan.\r\n\r\nIndeed, we are using `pyarrow` as the backend for our datasets, in order to cache them and also allow memory-mapping (using datasets larger than your RAM memory).\r\n\r\nOne way to avoid using `pyarrow` could be loading the datasets in streaming mode, by passing `streaming=True` to `load_dataset`. This way you basically get a generator for the dataset; nothing is downloaded, nor cached. ",
"Thanks for the info. Could `datasets` then be made optional for `transformers` instead? I used `transformers` only to deal with pretrained models to deploy them (convert to ONNX, and then I use TVM), so I don't really need `pyarrow` and `datasets` by now.\r\n"
] | 1,663,263,483,000 | 1,663,349,027,000 | 1,663,349,027,000 | NONE | null | **Is your feature request related to a problem? Please describe.**
Is `pyarrow` really needed for every dataset?
**Describe the solution you'd like**
It is made optional.
**Describe alternatives you've considered**
Likely, no.
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https://api.github.com/repos/huggingface/datasets/issues/4979 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4979/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4979/comments | https://api.github.com/repos/huggingface/datasets/issues/4979/events | https://github.com/huggingface/datasets/pull/4979 | 1,374,820,758 | PR_kwDODunzps4_CouM | 4,979 | Fix missing tags in dataset cards | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,663,260,663,000 | 1,663,262,062,000 | 1,663,261,929,000 | MEMBER | null | Fix missing tags in dataset cards.
This PR partially fixes the missing tags in dataset cards. Subsequent PRs will follow to complete this task.
Related to:
- #4833
- #4891
- #4896
- #4908
- #4921
- #4931 | {
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https://api.github.com/repos/huggingface/datasets/issues/4978 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4978/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4978/comments | https://api.github.com/repos/huggingface/datasets/issues/4978/events | https://github.com/huggingface/datasets/pull/4978 | 1,374,271,504 | PR_kwDODunzps4_Axnh | 4,978 | Update IndicGLUE download links | {
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] | 1,663,236,357,000 | 1,663,279,220,000 | 1,663,279,054,000 | CONTRIBUTOR | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4977 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4977/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4977/comments | https://api.github.com/repos/huggingface/datasets/issues/4977/events | https://github.com/huggingface/datasets/issues/4977 | 1,372,962,157 | I_kwDODunzps5R1b1t | 4,977 | Providing dataset size | {
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"Hi @sashavor, thanks for your suggestion.\r\n\r\nUntil now we have the CLI command \r\n```\r\ndatasets-cli test datasets/<your-dataset-folder> --save_infos --all_configs\r\n```\r\nthat generates the `dataset_infos.json` with the size of the downloaded dataset, among other information.\r\n\r\nWe are currently in the middle of removing those JSON files and putting their information directly in the header of the `README.md` (as YAML tags). Normally, the CLI command should continue working but saving its output to the dataset card instead. See:\r\n- #4926",
"Additionally, the download size can be inferred by doing HEAD requests to the files to be downloaded. And for files hosted on the hub you can even get the file sizes using the Hub API",
"Amazing @albertvillanova ! I think just having that information visible in the dataset info (without having to do any requests/additional coding) would be really useful :hugs: "
] | 1,663,160,967,000 | 1,663,257,838,000 | null | CONTRIBUTOR | null | **Is your feature request related to a problem? Please describe.**
Especially for big datasets like [LAION](https://huggingface.co/datasets/laion/laion2B-en/), it's hard to know exactly the downloaded size (because there are many files and you don't have their exact size when downloaded).
**Describe the solution you'd like**
Auto-populating the downloaded dataset size on the dataset page would be really useful, including that of each split (when there are some).
**Describe alternatives you've considered**
People should be adding this to dataset cards, but I don't think that is systematically the case :slightly_smiling_face:
**Additional context**
Mentioned to @lhoestq
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https://api.github.com/repos/huggingface/datasets/issues/4976 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4976/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4976/comments | https://api.github.com/repos/huggingface/datasets/issues/4976/events | https://github.com/huggingface/datasets/issues/4976 | 1,372,322,382 | I_kwDODunzps5Ry_pO | 4,976 | Hope to adapt Python3.9 as soon as possible | {
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"Hi! `datasets` should work in Python 3.9. What kind of issue have you encountered?",
"There is this related issue already: https://github.com/huggingface/datasets/issues/4113\r\nAnd I guess we need a CI job for 3.9 ^^"
] | 1,663,130,542,000 | 1,663,256,697,000 | null | NONE | null | **Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
**Describe the solution you'd like**
A clear and concise description of what you want to happen.
**Describe alternatives you've considered**
A clear and concise description of any alternative solutions or features you've considered.
**Additional context**
Add any other context about the feature request here.
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https://api.github.com/repos/huggingface/datasets/issues/4975 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4975/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4975/comments | https://api.github.com/repos/huggingface/datasets/issues/4975/events | https://github.com/huggingface/datasets/pull/4975 | 1,371,703,691 | PR_kwDODunzps4-4NXX | 4,975 | Add `fn_kwargs` param to `IterableDataset.map` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,663,085,945,000 | 1,663,087,667,000 | 1,663,087,534,000 | CONTRIBUTOR | null | Add the `fn_kwargs` parameter to `IterableDataset.map`.
("Resolves" https://discuss.huggingface.co/t/how-to-use-large-image-text-datasets-in-hugging-face-hub-without-downloading-for-free/22780/3) | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4974). All of your documentation changes will be reflected on that endpoint."
] | 1,663,084,872,000 | 1,663,333,509,000 | null | MEMBER | null | Now that all the datasets live on the Hub we can remove the /datasets directory that contains all the dataset scripts of this repository
Needs https://github.com/huggingface/datasets/pull/4973 to be merged first
and PR to be enabled on the Hub for non-namespaced datasets | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Duplicate of:\r\n- #4059"
] | 1,663,081,301,000 | 1,663,255,611,000 | 1,663,255,466,000 | MEMBER | null | Currently datasets with no namespace (e.g. squad, glue) are loaded from github.
In this PR I changed this logic to use the Hugging Face Hub instead.
This is the first step in removing all the dataset scripts in this repository
related to discussions in https://github.com/huggingface/datasets/pull/4059 (I should have continued from this PR actually) | {
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https://api.github.com/repos/huggingface/datasets/issues/4972 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4972/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4972/comments | https://api.github.com/repos/huggingface/datasets/issues/4972/events | https://github.com/huggingface/datasets/pull/4972 | 1,371,443,306 | PR_kwDODunzps4-3VVF | 4,972 | Fix map batched with torch output | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4972). All of your documentation changes will be reflected on that endpoint."
] | 1,663,074,994,000 | 1,663,256,568,000 | null | MEMBER | null | Reported in https://discuss.huggingface.co/t/typeerror-when-applying-map-after-set-format-type-torch/23067/2
Currently it fails if one uses batched `map` and the map function returns a torch tensor.
I fixed it for torch, tf, jax and pandas series. | {
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https://api.github.com/repos/huggingface/datasets/issues/4971 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4971/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4971/comments | https://api.github.com/repos/huggingface/datasets/issues/4971/events | https://github.com/huggingface/datasets/pull/4971 | 1,370,319,516 | PR_kwDODunzps4-zk3g | 4,971 | Preserve non-`input_colums` in `Dataset.map` if `input_columns` are specified | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,663,006,104,000 | 1,663,077,068,000 | 1,663,076,925,000 | CONTRIBUTOR | null | Currently, if the `input_columns` list in `Dataset.map` is specified, the columns not in that list are dropped after the `map` transform.
This makes the behavior inconsistent with `IterableDataset.map`.
(It seems this issue was introduced by mistake in https://github.com/huggingface/datasets/pull/2246)
Fix https://github.com/huggingface/datasets/issues/4858 | {
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https://api.github.com/repos/huggingface/datasets/issues/4970 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4970/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4970/comments | https://api.github.com/repos/huggingface/datasets/issues/4970/events | https://github.com/huggingface/datasets/pull/4970 | 1,369,433,074 | PR_kwDODunzps4-wkY2 | 4,970 | Support streaming nli_tr dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,662,968,925,000 | 1,662,972,304,000 | 1,662,972,188,000 | MEMBER | null | Support streaming nli_tr dataset.
This PR removes legacy `codecs.open` and replaces it with `open` that supports passing encoding.
Fix #3186. | {
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https://api.github.com/repos/huggingface/datasets/issues/4969 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4969/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4969/comments | https://api.github.com/repos/huggingface/datasets/issues/4969/events | https://github.com/huggingface/datasets/pull/4969 | 1,369,334,740 | PR_kwDODunzps4-wPOk | 4,969 | Fix data URL and metadata of vivos dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,662,963,154,000 | 1,662,966,975,000 | 1,662,966,859,000 | MEMBER | null | After contacting the authors of the VIVOS dataset to report that their data server is down, we have received a reply from Hieu-Thi Luong that their data is now hosted on Zenodo: https://doi.org/10.5281/zenodo.7068130
This PR updates their data URL and some metadata (homepage, citation and license).
Fix #4936. | {
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https://api.github.com/repos/huggingface/datasets/issues/4968 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4968/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4968/comments | https://api.github.com/repos/huggingface/datasets/issues/4968/events | https://github.com/huggingface/datasets/pull/4968 | 1,369,312,877 | PR_kwDODunzps4-wKkw | 4,968 | Support streaming compguesswhat dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,662,961,344,000 | 1,662,969,606,000 | 1,662,969,486,000 | MEMBER | null | Support streaming `compguesswhat` dataset.
Fix #3191. | {
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https://api.github.com/repos/huggingface/datasets/issues/4967 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4967/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4967/comments | https://api.github.com/repos/huggingface/datasets/issues/4967/events | https://github.com/huggingface/datasets/pull/4967 | 1,369,092,452 | PR_kwDODunzps4-vbS- | 4,967 | Strip "/" in local dataset path to avoid empty dataset name error | {
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https://api.github.com/repos/huggingface/datasets/issues/4965 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4965/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4965/comments | https://api.github.com/repos/huggingface/datasets/issues/4965/events | https://github.com/huggingface/datasets/issues/4965 | 1,368,661,002 | I_kwDODunzps5RlBwK | 4,965 | [Apple M1] MemoryError: Cannot allocate write+execute memory for ffi.callback() | {
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"Hi! This seems like a bug in `soundfile`. Could you please open an issue in their repo? `soundfile` works without any issues on my M1, so I'm not sure we can help.",
"Hi @mariosasko, can you share how you installed `soundfile` on your mac M1?"
] | 1,662,825,349,000 | 1,663,426,281,000 | null | NONE | null | ## Describe the bug
I'm trying to run `cast_column("audio", Audio())` on Apple M1 Pro, but it seems that it doesn't work.
## Steps to reproduce the bug
```python
import datasets
dataset = load_dataset("csv", data_files="./train.csv")["train"]
dataset = dataset.map(lambda x: {"audio": str(DATA_DIR / "audio" / x["audio"])})
dataset = dataset.cast_column("audio", Audio())
dataset[0]
```
## Expected results
```
{'audio': {'bytes': None,
'path': '/root/.cache/huggingface/datasets/downloads/extracted/f14948e0e84be638dd7943ac36518a4cf3324e8b7aa331c5ab11541518e9368c/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav'},
'english_transcription': 'I would like to set up a joint account with my partner',
'intent_class': 11,
'lang_id': 4,
'path': '/root/.cache/huggingface/datasets/downloads/extracted/f14948e0e84be638dd7943ac36518a4cf3324e8b7aa331c5ab11541518e9368c/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav',
'transcription': 'I would like to set up a joint account with my partner'}
```
## Actual results
````---------------------------------------------------------------------------
MemoryError Traceback (most recent call last)
Input In [6], in <cell line: 1>()
----> 1 dataset[0]
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/arrow_dataset.py:2165, in Dataset.__getitem__(self, key)
2163 def __getitem__(self, key): # noqa: F811
2164 """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools)."""
-> 2165 return self._getitem(
2166 key,
2167 )
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/arrow_dataset.py:2150, in Dataset._getitem(self, key, decoded, **kwargs)
2148 formatter = get_formatter(format_type, features=self.features, decoded=decoded, **format_kwargs)
2149 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
-> 2150 formatted_output = format_table(
2151 pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
2152 )
2153 return formatted_output
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:532, in format_table(table, key, formatter, format_columns, output_all_columns)
530 python_formatter = PythonFormatter(features=None)
531 if format_columns is None:
--> 532 return formatter(pa_table, query_type=query_type)
533 elif query_type == "column":
534 if key in format_columns:
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:281, in Formatter.__call__(self, pa_table, query_type)
279 def __call__(self, pa_table: pa.Table, query_type: str) -> Union[RowFormat, ColumnFormat, BatchFormat]:
280 if query_type == "row":
--> 281 return self.format_row(pa_table)
282 elif query_type == "column":
283 return self.format_column(pa_table)
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:312, in PythonFormatter.format_row(self, pa_table)
310 row = self.python_arrow_extractor().extract_row(pa_table)
311 if self.decoded:
--> 312 row = self.python_features_decoder.decode_row(row)
313 return row
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:221, in PythonFeaturesDecoder.decode_row(self, row)
220 def decode_row(self, row: dict) -> dict:
--> 221 return self.features.decode_example(row) if self.features else row
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/features.py:1647, in Features.decode_example(self, example, token_per_repo_id)
1634 def decode_example(self, example: dict, token_per_repo_id: Optional[Dict[str, Union[str, bool, None]]] = None):
1635 """Decode example with custom feature decoding.
1636
1637 Args:
(...)
1644 :obj:`dict[str, Any]`
1645 """
-> 1647 return {
1648 column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
1649 if self._column_requires_decoding[column_name]
1650 else value
1651 for column_name, (feature, value) in zip_dict(
1652 {key: value for key, value in self.items() if key in example}, example
1653 )
1654 }
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/features.py:1648, in <dictcomp>(.0)
1634 def decode_example(self, example: dict, token_per_repo_id: Optional[Dict[str, Union[str, bool, None]]] = None):
1635 """Decode example with custom feature decoding.
1636
1637 Args:
(...)
1644 :obj:`dict[str, Any]`
1645 """
1647 return {
-> 1648 column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
1649 if self._column_requires_decoding[column_name]
1650 else value
1651 for column_name, (feature, value) in zip_dict(
1652 {key: value for key, value in self.items() if key in example}, example
1653 )
1654 }
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/features.py:1260, in decode_nested_example(schema, obj, token_per_repo_id)
1257 # Object with special decoding:
1258 elif isinstance(schema, (Audio, Image)):
1259 # we pass the token to read and decode files from private repositories in streaming mode
-> 1260 return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
1261 return obj
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/audio.py:156, in Audio.decode_example(self, value, token_per_repo_id)
154 array, sampling_rate = self._decode_non_mp3_file_like(file)
155 else:
--> 156 array, sampling_rate = self._decode_non_mp3_path_like(path, token_per_repo_id=token_per_repo_id)
157 return {"path": path, "array": array, "sampling_rate": sampling_rate}
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/audio.py:257, in Audio._decode_non_mp3_path_like(self, path, format, token_per_repo_id)
254 use_auth_token = None
256 with xopen(path, "rb", use_auth_token=use_auth_token) as f:
--> 257 array, sampling_rate = librosa.load(f, sr=self.sampling_rate, mono=self.mono)
258 return array, sampling_rate
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/librosa/util/decorators.py:88, in deprecate_positional_args.<locals>._inner_deprecate_positional_args.<locals>.inner_f(*args, **kwargs)
86 extra_args = len(args) - len(all_args)
87 if extra_args <= 0:
---> 88 return f(*args, **kwargs)
90 # extra_args > 0
91 args_msg = [
92 "{}={}".format(name, arg)
93 for name, arg in zip(kwonly_args[:extra_args], args[-extra_args:])
94 ]
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/librosa/core/audio.py:164, in load(path, sr, mono, offset, duration, dtype, res_type)
161 else:
162 # Otherwise try soundfile first, and then fall back if necessary
163 try:
--> 164 y, sr_native = __soundfile_load(path, offset, duration, dtype)
166 except RuntimeError as exc:
167 # If soundfile failed, try audioread instead
168 if isinstance(path, (str, pathlib.PurePath)):
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/librosa/core/audio.py:195, in __soundfile_load(path, offset, duration, dtype)
192 context = path
193 else:
194 # Otherwise, create the soundfile object
--> 195 context = sf.SoundFile(path)
197 with context as sf_desc:
198 sr_native = sf_desc.samplerate
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/soundfile.py:629, in SoundFile.__init__(self, file, mode, samplerate, channels, subtype, endian, format, closefd)
626 self._mode = mode
627 self._info = _create_info_struct(file, mode, samplerate, channels,
628 format, subtype, endian)
--> 629 self._file = self._open(file, mode_int, closefd)
630 if set(mode).issuperset('r+') and self.seekable():
631 # Move write position to 0 (like in Python file objects)
632 self.seek(0)
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/soundfile.py:1179, in SoundFile._open(self, file, mode_int, closefd)
1177 file_ptr = _snd.sf_open_fd(file, mode_int, self._info, closefd)
1178 elif _has_virtual_io_attrs(file, mode_int):
-> 1179 file_ptr = _snd.sf_open_virtual(self._init_virtual_io(file),
1180 mode_int, self._info, _ffi.NULL)
1181 else:
1182 raise TypeError("Invalid file: {0!r}".format(self.name))
File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/soundfile.py:1197, in SoundFile._init_virtual_io(self, file)
1194 def _init_virtual_io(self, file):
1195 """Initialize callback functions for sf_open_virtual()."""
1196 @_ffi.callback("sf_vio_get_filelen")
-> 1197 def vio_get_filelen(user_data):
1198 curr = file.tell()
1199 file.seek(0, SEEK_END)
MemoryError: Cannot allocate write+execute memory for ffi.callback(). You might be running on a system that prevents this. For more information, see https://cffi.readthedocs.io/en/latest/using.html#callbacks
```
## Environment info
- `datasets` version: 2.4.0
- Platform: macOS-12.5.1-arm64-arm-64bit
- Python version: 3.8.13
- PyArrow version: 9.0.0
- Pandas version: 1.4.4 | {
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https://api.github.com/repos/huggingface/datasets/issues/4964 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4964/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4964/comments | https://api.github.com/repos/huggingface/datasets/issues/4964/events | https://github.com/huggingface/datasets/issues/4964 | 1,368,617,322 | I_kwDODunzps5Rk3Fq | 4,964 | Column of arrays (2D+) are using unreasonably high memory | {
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] | open | false | null | [] | null | [
"note i have tried the same code with `datasets` version 2.4.0, the outcome is the very same as described above."
] | 1,662,815,242,000 | 1,662,815,297,000 | null | NONE | null | ## Describe the bug
When trying to store `Array2D, Array3D, etc` as column values in a dataset, accessing that column (or creating depending on how you create it, see code below) will cause more than 10 fold of memory usage.
## Steps to reproduce the bug
```python
from datasets import Dataset, Features, Array2D, Array3D
import numpy as np
column_name = "a"
array_shape = (64, 64, 3)
data = np.random.random((10000,) + array_shape)
dataset = Dataset.from_dict({column_name: data}, features=Features({column_name: Array3D(shape=array_shape, dtype="float64")}))
```
the code above will use about 10Gb of RAM while constructing the `dataset` object.
The code below will use roughly the same amount of memory (and time) when trying to actually access the data itself of that column.
```python
from datasets import Dataset
import numpy as np
column_name = "a"
array_shape = (64, 64, 3)
data = np.random.random((10000,) + array_shape)
dataset = Dataset.from_dict({column_name: data})
dataset[column_name]
```
## Expected results
Some memory overhead, but not like as it is now and certainly not an overhead of such runtime that is currently happening.
## Actual results
Enormous memory- and runtime overhead.
## Environment info
- `datasets` version: 2.3.2
- Platform: macOS-12.5.1-arm64-arm-64bit
- Python version: 3.8.13
- PyArrow version: 9.0.0
- Pandas version: 1.4.4 | {
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https://api.github.com/repos/huggingface/datasets/issues/4963 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4963/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4963/comments | https://api.github.com/repos/huggingface/datasets/issues/4963/events | https://github.com/huggingface/datasets/issues/4963 | 1,368,201,188 | I_kwDODunzps5RjRfk | 4,963 | Dataset without script does not support regular JSON data file | {
"login": "julien-c",
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"Hi @julien-c,\r\n\r\nOut of the box, we only support JSON lines (NDJSON) data files, but your data file is a regular JSON file. The reason is we use `pyarrow.json.read_json` and this only supports line-delimited JSON. "
] | 1,662,749,133,000 | 1,662,971,727,000 | null | MEMBER | null | ### Link
https://huggingface.co/datasets/julien-c/label-studio-my-dogs
### Description
<img width="1115" alt="image" src="https://user-images.githubusercontent.com/326577/189422048-7e9c390f-bea7-4521-a232-43f049ccbd1f.png">
### Owner
Yes | {
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https://api.github.com/repos/huggingface/datasets/issues/4962 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4962/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4962/comments | https://api.github.com/repos/huggingface/datasets/issues/4962/events | https://github.com/huggingface/datasets/pull/4962 | 1,368,155,365 | PR_kwDODunzps4-sh-o | 4,962 | Update setup.py | {
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"Before addressing this PR, we should be sure about the issue. See my comment in:\r\n- https://github.com/huggingface/datasets/issues/4961#issuecomment-1243376247",
"Once we know 2022.8.2 works, I'm closing this PR, as the corresponding issue."
] | 1,662,746,276,000 | 1,662,993,184,000 | 1,662,993,184,000 | NONE | null | exclude broken version of fsspec. See the [related issue](https://github.com/huggingface/datasets/issues/4961) | {
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https://api.github.com/repos/huggingface/datasets/issues/4961 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4961/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4961/comments | https://api.github.com/repos/huggingface/datasets/issues/4961/events | https://github.com/huggingface/datasets/issues/4961 | 1,368,124,033 | I_kwDODunzps5Ri-qB | 4,961 | fsspec 2022.8.2 breaks xopen in streaming mode | {
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"loading `fsspec==2022.7.1` fixes this issue, setup.py would need to be changed to prevent users from using the latest version of fsspec.",
"Opened [PR](https://github.com/huggingface/datasets/pull/4962) to address this.",
"Hi @DCNemesis, thanks for reporting.\r\n\r\nThat was a temporary issue in `fsspec` releases 2022.8.0 and 2022.8.1. But they fixed it in their patch release 2022.8.2 (and yanked both previous versions). See:\r\n- https://github.com/huggingface/transformers/pull/18846\r\n\r\nAre you sure you have version 2022.8.2 installed?\r\n```shell\r\npip install -U fsspec\r\n```\r\n",
"@albertvillanova I was using a temporary Google Colab instance, but checking it again today it seems it was loading 2022.8.1 rather than 2022.8.2. It's surprising that colab is using the version that was replaced the same day it was released. Testing with 2022.8.2 did work. It appears Colab [will be fixing it](https://github.com/googlecolab/colabtools/issues/3055) on their end too. ",
"Thanks for the additional information.\r\n\r\nOnce we know 2022.8.2 works, I'm closing this issue. Feel free to reopen it if necessary.",
"Colab just upgraded their default `fsspec` version to 2022.8.2:\r\n- https://github.com/googlecolab/colabtools/issues/3055#issuecomment-1244019010"
] | 1,662,744,415,000 | 1,663,004,750,000 | 1,662,993,125,000 | NONE | null | ## Describe the bug
When fsspec 2022.8.2 is installed in your environment, xopen will prematurely close files, making streaming mode inoperable.
## Steps to reproduce the bug
```python
import datasets
data = datasets.load_dataset('MLCommons/ml_spoken_words', 'id_wav', split='train', streaming=True)
```
## Expected results
Dataset should load as iterator.
## Actual results
```
[/usr/local/lib/python3.7/dist-packages/datasets/load.py](https://localhost:8080/#) in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)
1737 # Return iterable dataset in case of streaming
1738 if streaming:
-> 1739 return builder_instance.as_streaming_dataset(split=split)
1740
1741 # Some datasets are already processed on the HF google storage
[/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in as_streaming_dataset(self, split, base_path)
1023 )
1024 self._check_manual_download(dl_manager)
-> 1025 splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}
1026 # By default, return all splits
1027 if split is None:
[~/.cache/huggingface/modules/datasets_modules/datasets/MLCommons--ml_spoken_words/321ea853cf0a05abb7a2d7efea900692a3d8622af65a2f3ce98adb7800a5d57b/ml_spoken_words.py](https://localhost:8080/#) in _split_generators(self, dl_manager)
182 name=datasets.Split.TRAIN,
183 gen_kwargs={
--> 184 "audio_archives": [download_audio(split="train", lang=lang) for lang in self.config.languages],
185 "local_audio_archives_paths": [download_extract_audio(split="train", lang=lang) for lang in
186 self.config.languages] if not dl_manager.is_streaming else None,
[~/.cache/huggingface/modules/datasets_modules/datasets/MLCommons--ml_spoken_words/321ea853cf0a05abb7a2d7efea900692a3d8622af65a2f3ce98adb7800a5d57b/ml_spoken_words.py](https://localhost:8080/#) in <listcomp>(.0)
182 name=datasets.Split.TRAIN,
183 gen_kwargs={
--> 184 "audio_archives": [download_audio(split="train", lang=lang) for lang in self.config.languages],
185 "local_audio_archives_paths": [download_extract_audio(split="train", lang=lang) for lang in
186 self.config.languages] if not dl_manager.is_streaming else None,
[~/.cache/huggingface/modules/datasets_modules/datasets/MLCommons--ml_spoken_words/321ea853cf0a05abb7a2d7efea900692a3d8622af65a2f3ce98adb7800a5d57b/ml_spoken_words.py](https://localhost:8080/#) in _download_audio_archives(dl_manager, lang, format, split)
267 # for streaming case
268 def _download_audio_archives(dl_manager, lang, format, split):
--> 269 archives_paths = _download_audio_archives_paths(dl_manager, lang, format, split)
270 return [dl_manager.iter_archive(archive_path) for archive_path in archives_paths]
[~/.cache/huggingface/modules/datasets_modules/datasets/MLCommons--ml_spoken_words/321ea853cf0a05abb7a2d7efea900692a3d8622af65a2f3ce98adb7800a5d57b/ml_spoken_words.py](https://localhost:8080/#) in _download_audio_archives_paths(dl_manager, lang, format, split)
251 n_files_path = dl_manager.download(n_files_url)
252
--> 253 with open(n_files_path, "r", encoding="utf-8") as file:
254 n_files = int(file.read().strip()) # the file contains a number of archives
255
ValueError: I/O operation on closed file.
```
## Environment info
- `datasets` version: 2.4.0
- Platform: Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 6.0.1
- Pandas version: 1.3.5
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https://api.github.com/repos/huggingface/datasets/issues/4960 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4960/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4960/comments | https://api.github.com/repos/huggingface/datasets/issues/4960/events | https://github.com/huggingface/datasets/issues/4960 | 1,368,035,159 | I_kwDODunzps5Rio9X | 4,960 | BioASQ AttributeError: 'BuilderConfig' object has no attribute 'schema' | {
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"name": "dataset bug",
"color": "2edb81",
"default": false,
"description": "A bug in a dataset script provided in the library"
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] | open | false | null | [] | null | [
"Following worked:\r\n\r\n```\r\ndata_dir = \"/Users/dlituiev/repos/datasets/bioasq/\"\r\nbioasq_task_b = load_dataset(\"aps/bioasq_task_b\", data_dir=data_dir, name=\"bioasq_9b_source\")\r\n```\r\n\r\nWould maintainers be open to one of the following:\r\n- automating this with a latest default config (e.g. `bioasq_9b_source`); how can this be generalized to other datasets?\r\n- providing an actionable error message that lists available `name` values? I only got available `name` values once I've provided something there (`name=\"aps/bioasq_task_b\"`), before it would not even mention that it requires `name` argument",
"Hi ! In general the list of available configurations is prompted. I think this is an issue with this specific dataset.\r\n\r\nFeel free to open a new discussions at https://huggingface.co/datasets/aps/bioasq_task_b/discussions\r\n\r\ncc @apsdehal\r\n\r\nIn particular it sounds like the `BUILDER_CONFIG_CLASS= BigBioConfig ` class attribute is missing and the _info should account for schema being None and raise an error"
] | 1,662,739,603,000 | 1,663,059,063,000 | null | NONE | null | ## Describe the bug
I am trying to load a dataset from drive and running into an error.
## Steps to reproduce the bug
```python
data_dir = "/Users/dlituiev/repos/datasets/bioasq/BioASQ-training9b"
bioasq_task_b = load_dataset("aps/bioasq_task_b", data_dir=data_dir)
```
## Actual results
`AttributeError: 'BuilderConfig' object has no attribute 'schema'`
<details>
```
Using custom data configuration default-a1ca3e05be5abf2f
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Input In [8], in <cell line: 2>()
1 data_dir = "/Users/dlituiev/repos/datasets/bioasq/BioASQ-training9b"
----> 2 bioasq_task_b = load_dataset("aps/bioasq_task_b", data_dir=data_dir)
File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/load.py:1723, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)
1720 ignore_verifications = ignore_verifications or save_infos
1722 # Create a dataset builder
-> 1723 builder_instance = load_dataset_builder(
1724 path=path,
1725 name=name,
1726 data_dir=data_dir,
1727 data_files=data_files,
1728 cache_dir=cache_dir,
1729 features=features,
1730 download_config=download_config,
1731 download_mode=download_mode,
1732 revision=revision,
1733 use_auth_token=use_auth_token,
1734 **config_kwargs,
1735 )
1737 # Return iterable dataset in case of streaming
1738 if streaming:
File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/load.py:1526, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, **config_kwargs)
1523 raise ValueError(error_msg)
1525 # Instantiate the dataset builder
-> 1526 builder_instance: DatasetBuilder = builder_cls(
1527 cache_dir=cache_dir,
1528 config_name=config_name,
1529 data_dir=data_dir,
1530 data_files=data_files,
1531 hash=hash,
1532 features=features,
1533 use_auth_token=use_auth_token,
1534 **builder_kwargs,
1535 **config_kwargs,
1536 )
1538 return builder_instance
File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/builder.py:1154, in GeneratorBasedBuilder.__init__(self, writer_batch_size, *args, **kwargs)
1153 def __init__(self, *args, writer_batch_size=None, **kwargs):
-> 1154 super().__init__(*args, **kwargs)
1155 # Batch size used by the ArrowWriter
1156 # It defines the number of samples that are kept in memory before writing them
1157 # and also the length of the arrow chunks
1158 # None means that the ArrowWriter will use its default value
1159 self._writer_batch_size = writer_batch_size or self.DEFAULT_WRITER_BATCH_SIZE
File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/builder.py:307, in DatasetBuilder.__init__(self, cache_dir, config_name, hash, base_path, info, features, use_auth_token, repo_id, data_files, data_dir, name, **config_kwargs)
305 if info is None:
306 info = self.get_exported_dataset_info()
--> 307 info.update(self._info())
308 info.builder_name = self.name
309 info.config_name = self.config.name
File ~/.cache/huggingface/modules/datasets_modules/datasets/aps--bioasq_task_b/3d54b1213f7e8001eef755af92877f9efa44161ee83c2a70d5d649defa95759e/bioasq_task_b.py:477, in BioasqTaskBDataset._info(self)
474 def _info(self):
475
476 # BioASQ Task B source schema
--> 477 if self.config.schema == "source":
478 features = datasets.Features(
479 {
480 "id": datasets.Value("string"),
(...)
504 }
505 )
506 # simplified schema for QA tasks
AttributeError: 'BuilderConfig' object has no attribute 'schema'
```
</details>
## Environment info
- `datasets` version: 2.4.0
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.10.4
- PyArrow version: 9.0.0
- Pandas version: 1.4.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/4959 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4959/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4959/comments | https://api.github.com/repos/huggingface/datasets/issues/4959/events | https://github.com/huggingface/datasets/pull/4959 | 1,367,924,429 | PR_kwDODunzps4-rx6l | 4,959 | Fix data URLs of compguesswhat dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,662,734,170,000 | 1,662,739,294,000 | 1,662,739,144,000 | MEMBER | null | After we informed the `compguesswhat` dataset authors about an error with their data URLs, they have updated them:
- https://github.com/CompGuessWhat/compguesswhat.github.io/issues/1
This PR updates their data URLs in our loading script.
Related to:
- #3191 | {
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https://api.github.com/repos/huggingface/datasets/issues/4958 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4958/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4958/comments | https://api.github.com/repos/huggingface/datasets/issues/4958/events | https://github.com/huggingface/datasets/issues/4958 | 1,367,695,376 | I_kwDODunzps5RhWAQ | 4,958 | ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/2.4.0/datasets/jsonl/jsonl.py | {
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"I have solved this problem... The extension of the file should be `.json` not `.jsonl`"
] | 1,662,722,995,000 | 1,662,723,524,000 | 1,662,723,524,000 | NONE | null | Hi,
When I use load_dataset from local jsonl files, below error happens, and I type the link into the browser prompting me `404: Not Found`. I download the other `.py` files using the same method and it works. It seems that the server is missing the appropriate file, or it is a problem with the code version.
```
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/2.3.0/datasets/jsonl/jsonl.py (ConnectionError(MaxRetryError("HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/2.3.0/datasets/jsonl/jsonl.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x2b08342004c0>: Failed to establish a new connection: [Errno 101] Network is unreachable'))")))
```
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https://api.github.com/repos/huggingface/datasets/issues/4957 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4957/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4957/comments | https://api.github.com/repos/huggingface/datasets/issues/4957/events | https://github.com/huggingface/datasets/pull/4957 | 1,366,532,849 | PR_kwDODunzps4-nGIk | 4,957 | Add `Dataset.from_generator` | {
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"I restarted the builder PR job just in case",
"_The documentation is not available anymore as the PR was closed or merged._",
"CI is now green. https://github.com/huggingface/doc-builder/pull/296 explains why it failed."
] | 1,662,649,705,000 | 1,663,339,595,000 | 1,663,339,458,000 | CONTRIBUTOR | null | Add `Dataset.from_generator` to the API to allow creating datasets from data larger than RAM. The implementation relies on a packaged module not exposed in `load_dataset` to tie this method with `datasets`' caching mechanism.
Closes https://github.com/huggingface/datasets/issues/4417 | {
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https://api.github.com/repos/huggingface/datasets/issues/4956 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4956/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4956/comments | https://api.github.com/repos/huggingface/datasets/issues/4956/events | https://github.com/huggingface/datasets/pull/4956 | 1,366,475,160 | PR_kwDODunzps4-m5NU | 4,956 | Fix TF tests for 2.10 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,662,647,950,000 | 1,662,650,211,000 | 1,662,650,084,000 | MEMBER | null | Fixes #4953 | {
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https://api.github.com/repos/huggingface/datasets/issues/4955 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4955/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4955/comments | https://api.github.com/repos/huggingface/datasets/issues/4955/events | https://github.com/huggingface/datasets/issues/4955 | 1,366,382,314 | I_kwDODunzps5RcVbq | 4,955 | Raise a more precise error when the URL is unreachable in streaming mode | {
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] | open | false | null | [] | null | [] | 1,662,645,157,000 | 1,662,645,216,000 | null | CONTRIBUTOR | null | See for example:
- https://github.com/huggingface/datasets/issues/3191
- https://github.com/huggingface/datasets/issues/3186
It would help provide clearer information on the Hub and help the dataset maintainer solve the issue by themselves quicker. Currently:
- https://huggingface.co/datasets/compguesswhat
<img width="1029" alt="Capture dβeΜcran 2022-09-08 aΜ 15 51 37" src="https://user-images.githubusercontent.com/1676121/189139946-6deffb91-f21b-4281-8825-a98026c69740.png">
- https://huggingface.co/datasets/nli_tr
<img width="1032" alt="Capture dβeΜcran 2022-09-08 aΜ 15 51 44" src="https://user-images.githubusercontent.com/1676121/189139963-d26490ed-ad23-48ea-9cfc-1ab9c4d08d0c.png">
cc @albertvillanova | {
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https://api.github.com/repos/huggingface/datasets/issues/4954 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4954/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4954/comments | https://api.github.com/repos/huggingface/datasets/issues/4954/events | https://github.com/huggingface/datasets/pull/4954 | 1,366,369,682 | PR_kwDODunzps4-mhl5 | 4,954 | Pin TensorFlow temporarily | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,662,644,775,000 | 1,662,646,353,000 | 1,662,646,203,000 | MEMBER | null | Temporarily fix TensorFlow until a permanent solution is found.
Related to:
- #4953 | {
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] | closed | false | null | [] | null | [] | 1,662,644,369,000 | 1,662,650,085,000 | 1,662,650,085,000 | MEMBER | null | ## Describe the bug
The following CI test fails: https://github.com/huggingface/datasets/runs/8246722693?check_suite_focus=true
```
FAILED tests/test_py_utils.py::TempSeedTest::test_tensorflow - AssertionError:
```
Details:
```
_________________________ TempSeedTest.test_tensorflow _________________________
[gw0] linux -- Python 3.7.13 /opt/hostedtoolcache/Python/3.7.13/x64/bin/python
self = <tests.test_py_utils.TempSeedTest testMethod=test_tensorflow>
@require_tf
def test_tensorflow(self):
import tensorflow as tf
from tensorflow.keras import layers
def gen_random_output():
model = layers.Dense(2)
x = tf.random.uniform((1, 3))
return model(x).numpy()
with temp_seed(42, set_tensorflow=True):
out1 = gen_random_output()
with temp_seed(42, set_tensorflow=True):
out2 = gen_random_output()
out3 = gen_random_output()
> np.testing.assert_equal(out1, out2)
E AssertionError:
E Arrays are not equal
E
E Mismatched elements: 2 / 2 (100%)
E Max absolute difference: 0.84619296
E Max relative difference: 16.083529
E x: array([[-0.793581, 0.333286]], dtype=float32)
E y: array([[0.052612, 0.539708]], dtype=float32)
tests/test_py_utils.py:149: AssertionError
```
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https://api.github.com/repos/huggingface/datasets/issues/4952 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4952/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4952/comments | https://api.github.com/repos/huggingface/datasets/issues/4952/events | https://github.com/huggingface/datasets/pull/4952 | 1,366,354,604 | PR_kwDODunzps4-meM0 | 4,952 | Add test-datasets CI job | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Closing this one since the dataset scripts will be removed in https://github.com/huggingface/datasets/pull/4974"
] | 1,662,644,310,000 | 1,663,334,882,000 | 1,663,334,748,000 | MEMBER | null | To avoid having too many conflicts in the datasets and metrics dependencies I split the CI into test and test-catalog
test does the test of the core of the `datasets` lib, while test-catalog tests the datasets scripts and metrics scripts
This also makes `pip install -e .[dev]` much smaller for developers
WDYT @albertvillanova ? | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,662,631,479,000 | 1,662,648,887,000 | 1,662,648,725,000 | MEMBER | null | This PR adds the license information to `qasc` dataset, once reported via GitHub by Tushar Khot, the dataset is licensed under CC BY 4.0:
- https://github.com/allenai/qasc/issues/5
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https://api.github.com/repos/huggingface/datasets/issues/4950 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4950/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4950/comments | https://api.github.com/repos/huggingface/datasets/issues/4950/events | https://github.com/huggingface/datasets/pull/4950 | 1,365,458,633 | PR_kwDODunzps4-jWZ1 | 4,950 | Update Enwik8 broken link and information | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 1,662,606,900,000 | 1,662,648,810,000 | 1,662,648,660,000 | CONTRIBUTOR | null | The current enwik8 dataset link give a 502 bad gateway error which can be view on https://huggingface.co/datasets/enwik8 (click the dropdown to see the dataset preview, it will show the error). This corrects the links, and json metadata as well as adds a little bit more information about enwik8. | {
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"Closing pull request to following contributing guidelines of making a new branch and will make a new pull request"
] | 1,662,589,034,000 | 1,662,606,844,000 | 1,662,606,844,000 | CONTRIBUTOR | null | The current enwik8 dataset link give a 502 bad gateway error which can be view on https://huggingface.co/datasets/enwik8 (click the dropdown to see the dataset preview, it will show the error). This corrects the links, and json metadata as well as adds a little bit more information about enwik8. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4947). All of your documentation changes will be reflected on that endpoint."
] | 1,662,570,889,000 | 1,662,628,390,000 | 1,662,628,390,000 | MEMBER | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4946 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4946/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4946/comments | https://api.github.com/repos/huggingface/datasets/issues/4946/events | https://github.com/huggingface/datasets/pull/4946 | 1,364,692,069 | PR_kwDODunzps4-g0Hz | 4,946 | Introduce regex check when pushing as well | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Let me take over this PR if you don't mind"
] | 1,662,558,358,000 | 1,663,064,341,000 | 1,663,064,194,000 | MEMBER | null | Closes https://github.com/huggingface/datasets/issues/4945 by adding a regex check when pushing to hub.
Let me know if this is helpful and if it's the fix you would have in mind for the issue and I'm happy to contribute tests. | {
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https://api.github.com/repos/huggingface/datasets/issues/4945 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4945/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4945/comments | https://api.github.com/repos/huggingface/datasets/issues/4945/events | https://github.com/huggingface/datasets/issues/4945 | 1,364,691,096 | I_kwDODunzps5RV4iY | 4,945 | Push to hub can push splits that do not respect the regex | {
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] | closed | false | null | [] | null | [] | 1,662,558,317,000 | 1,663,064,195,000 | 1,663,064,195,000 | MEMBER | null | ## Describe the bug
The `push_to_hub` method can push splits that do not respect the regex check that is used for downloads. Therefore, splits may be pushed but never re-used, which can be painful if the split was done after runtime preprocessing.
## Steps to reproduce the bug
```python
>>> from datasets import Dataset, DatasetDict, load_dataset
>>> d = Dataset.from_dict({'x': [1,2,3], 'y': [1,2,3]})
>>> di = DatasetDict()
>>> di['identifier-with-column'] = d
>>> di.push_to_hub('open-source-metrics/test')
Pushing split identifier-with-column to the Hub.
Pushing dataset shards to the dataset hub: 100%|ββββββββββ| 1/1 [00:04<00:00, 4.40s/it]
```
Loading it afterwards:
```python
>>> load_dataset('open-source-metrics/test')
Downloading: 100%|ββββββββββ| 610/610 [00:00<00:00, 432kB/s]
Using custom data configuration open-source-metrics--test-28b63ec7cde80488
Downloading and preparing dataset None/None (download: 950 bytes, generated: 48 bytes, post-processed: Unknown size, total: 998 bytes) to /home/lysandre/.cache/huggingface/datasets/open-source-metrics___parquet/open-source-metrics--test-28b63ec7cde80488/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec...
Downloading data files: 0%| | 0/1 [00:00<?, ?it/s]
Downloading data: 100%|ββββββββββ| 950/950 [00:00<00:00, 1.01MB/s]
Downloading data files: 100%|ββββββββββ| 1/1 [00:01<00:00, 1.48s/it]
Extracting data files: 100%|ββββββββββ| 1/1 [00:00<00:00, 2291.97it/s]
Traceback (most recent call last):
File "/home/lysandre/.pyenv/versions/3.10.6/lib/python3.10/code.py", line 90, in runcode
exec(code, self.locals)
File "<input>", line 1, in <module>
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/load.py", line 1746, in load_dataset
builder_instance.download_and_prepare(
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/builder.py", line 704, in download_and_prepare
self._download_and_prepare(
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/builder.py", line 771, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/packaged_modules/parquet/parquet.py", line 48, in _split_generators
splits.append(datasets.SplitGenerator(name=split_name, gen_kwargs={"files": files}))
File "<string>", line 5, in __init__
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/splits.py", line 599, in __post_init__
NamedSplit(self.name) # check that it's a valid split name
File "/home/lysandre/Workspaces/python/Metrics/GitHub-Metrics/.env/lib/python3.10/site-packages/datasets/splits.py", line 346, in __init__
raise ValueError(f"Split name should match '{_split_re}' but got '{split_name}'.")
ValueError: Split name should match '^\w+(\.\w+)*$' but got 'identifier-with-column'.
```
## Expected results
I would expect `push_to_hub` to stop me in my tracks if trying to upload a split that will not be working afterwards.
## Actual results
See above
## Environment info
- `datasets` version: 2.4.0
- Platform: Linux-5.15.64-1-lts-x86_64-with-glibc2.36
- Python version: 3.10.6
- PyArrow version: 9.0.0
- Pandas version: 1.4.4
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https://api.github.com/repos/huggingface/datasets/issues/4944 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4944/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4944/comments | https://api.github.com/repos/huggingface/datasets/issues/4944/events | https://github.com/huggingface/datasets/issues/4944 | 1,364,313,569 | I_kwDODunzps5RUcXh | 4,944 | larger dataset, larger GPU memory in the training phase? Is that correct? | {
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"does the trainer save it in GPU? sooo curious... how to fix it",
"It's my bad. didn't limit the input length"
] | 1,662,540,390,000 | 1,662,554,098,000 | 1,662,554,098,000 | NONE | null | from datasets import set_caching_enabled
set_caching_enabled(False)
for ds_name in ["squad","newsqa","nqopen","narrativeqa"]:
train_ds = load_from_disk("../../../dall/downstream/processedproqa/{}-train.hf".format(ds_name))
break
train_ds = concatenate_datasets([train_ds,train_ds,train_ds,train_ds]) #operation 1
trainer = QuestionAnsweringTrainer( #huggingface trainer
model=model,
args=training_args,
train_dataset=train_ds,
eval_dataset= None,
eval_examples=None,
answer_column_name=answer_column,
dataset_name="squad",
tokenizer=tokenizer,
data_collator=data_collator,
compute_metrics=compute_metrics if training_args.predict_with_generate else None,
)
with operation 1, the GPU memory increases from 16G to 23G | {
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https://api.github.com/repos/huggingface/datasets/issues/4943 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4943/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4943/comments | https://api.github.com/repos/huggingface/datasets/issues/4943/events | https://github.com/huggingface/datasets/pull/4943 | 1,363,967,650 | PR_kwDODunzps4-eZd_ | 4,943 | Add splits to MBPP dataset | {
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"```\r\n(env) cwarny@Cedrics-Air datasets % RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_mbpp\r\n================================================================================================ test session starts =================================================================================================\r\nplatform darwin -- Python 3.8.13, pytest-7.1.3, pluggy-1.0.0\r\nrootdir: /Users/cwarny/datasets, configfile: setup.cfg\r\ncollected 1 item \r\n\r\ntests/test_dataset_common.py . [100%]\r\n\r\n================================================================================================= 1 passed in 1.12s ==================================================================================================\r\n(env) cwarny@Cedrics-Air datasets % RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_mbpp \r\n================================================================================================ test session starts =================================================================================================\r\nplatform darwin -- Python 3.8.13, pytest-7.1.3, pluggy-1.0.0\r\nrootdir: /Users/cwarny/datasets, configfile: setup.cfg\r\ncollected 1 item \r\n\r\ntests/test_dataset_common.py . [100%]\r\n\r\n================================================================================================= 1 passed in 0.35s ==================================================================================================\r\n\r\n```",
"_The documentation is not available anymore as the PR was closed or merged._",
"Hi @cwarny ! Thanks for adding the correct splits :)\r\n\r\nYou can fix the CI error by running `make style` - this should reformat the dataset script",
"done"
] | 1,662,513,511,000 | 1,663,072,159,000 | 1,663,072,041,000 | CONTRIBUTOR | null | This PR addresses https://github.com/huggingface/datasets/issues/4795 | {
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"Thanks for reporting, @wmpauli. \r\n\r\nIndeed we recently fixed this issue:\r\n- #4801 \r\n\r\nThe fix will be accessible after our next library release. In the meantime, you can have it by passing `revision=\"main\"` to `load_dataset`."
] | 1,662,502,420,000 | 1,662,635,523,000 | 1,662,635,523,000 | NONE | null | ## Describe the bug
Both coarse and fine labels seem to be out of line.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = "trec"
raw_datasets = load_dataset(dataset)
df = pd.DataFrame(raw_datasets["test"])
df.head()
```
## Expected results
text (string) | coarse_label (class label) | fine_label (class label)
-- | -- | --
How far is it from Denver to Aspen ? | 5 (NUM) | 40 (NUM:dist)
What county is Modesto , California in ? | 4 (LOC) | 32 (LOC:city)
Who was Galileo ? | 3 (HUM) | 31 (HUM:desc)
What is an atom ? | 2 (DESC) | 24 (DESC:def)
When did Hawaii become a state ? | 5 (NUM) | 39 (NUM:date)
## Actual results
index | label-coarse |label-fine | text
-- |-- | -- | --
0 | 4 | 40 | How far is it from Denver to Aspen ?
1 | 5 | 21 | What county is Modesto , California in ?
2 | 3 | 12 | Who was Galileo ?
3 | 0 | 7 | What is an atom ?
4 | 4 | 8 | When did Hawaii become a state ?
## Environment info
- `datasets` version: 2.4.0
- Platform: Linux-5.4.0-1086-azure-x86_64-with-glibc2.27
- Python version: 3.9.13
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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