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https://api.github.com/repos/huggingface/datasets/issues/5737 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5737/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5737/comments | https://api.github.com/repos/huggingface/datasets/issues/5737/events | https://github.com/huggingface/datasets/issues/5737 | 1,662,919,811 | I_kwDODunzps5jHiSD | 5,737 | ClassLabel Error | {
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"Hi, you can use the `cast_column` function to change the feature type from a `Value(int64)` to `ClassLabel`:\r\n\r\n```py\r\ndataset = dataset.cast_column(\"label\", ClassLabel(names=[\"label_1\", \"label_2\", \"label_3\"]))\r\nprint(dataset.features)\r\n{'text': Value(dtype='string', id=None),\r\n 'label': ClassL... | 2023-04-11T17:14:13Z | 2023-04-13T16:49:57Z | 2023-04-13T16:49:57Z | NONE | null | null | {
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} | ### Describe the bug
I still getting the error "call() takes 1 positional argument but 2 were given" even after ensuring that the value being passed to the label object is a single value and that the ClassLabel object has been created with the correct number of label classes
### Steps to reproduce the bug
from datasets import ClassLabel, Dataset
1. Create the ClassLabel object with 3 label values and their corresponding names
label_test = ClassLabel(num_classes=3, names=["label_1", "label_2", "label_3"])
2. Define a dictionary with text and label fields
data = {
'text': ['text_1', 'text_2', 'text_3'],
'label': [1, 2, 3],
}
3. Create a Hugging Face dataset from the dictionary
dataset = Dataset.from_dict(data)
print(dataset.features)
4. Map the label values to their corresponding label names using the label object
dataset = dataset.map(lambda example: {'text': example['text'], 'label': label_test(example['label'])})
5. Print the resulting dataset
print(dataset)
### Expected behavior
I hope my label type is class label instead int.
### Environment info
python 3.9
google colab | {
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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._"
] | 2022-09-15T16:51:03Z | 2022-09-22T12:37:55Z | 2022-09-15T17:12:09Z | MEMBER | null | null | null | Fix missing tags in dataset cards:
- amazon_us_reviews
- art
- discofuse
- indic_glue
- ubuntu_dialogs_corpus
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/7157 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7157/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7157/comments | https://api.github.com/repos/huggingface/datasets/issues/7157/events | https://github.com/huggingface/datasets/pull/7157 | 2,540,354,890 | PR_kwDODunzps58P-1R | 7,157 | Fix zero proba interleave datasets | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7157). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2024-09-21T15:19:14Z | 2024-09-24T14:33:54Z | 2024-09-24T14:33:54Z | MEMBER | null | null | null | fix https://github.com/huggingface/datasets/issues/7147 | {
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} | CLI convert_to_parquet cannot create "script" branch on 3rd party repos.
It can only create it on repos where the user executing the script has write access.
Otherwise, a 403 Forbidden HTTPError is raised:
```
Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_errors.py", line 304, in hf_raise_for_status
response.raise_for_status()
File "/usr/local/lib/python3.10/dist-packages/requests/models.py", line 1021, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 403 Client Error: Forbidden for url: https://huggingface.co/api/datasets/ORG/DATASET/branch/script
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/bin/datasets-cli", line 8, in <module>
sys.exit(main())
File "/usr/local/lib/python3.10/dist-packages/datasets/commands/datasets_cli.py", line 41, in main
service.run()
File "/usr/local/lib/python3.10/dist-packages/datasets/commands/convert_to_parquet.py", line 92, in run
create_branch(dataset_id, branch="script", repo_type="dataset", token=token, exist_ok=True)
File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/hf_api.py", line 5503, in create_branch
hf_raise_for_status(response)
File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_errors.py", line 367, in hf_raise_for_status
raise HfHubHTTPError(message, response=response) from e
huggingface_hub.utils._errors.HfHubHTTPError: (Request ID: Root=1-6645ee0d-4db1ed8a1fbe04956be15897;139a6e23-df7d-4f62-b5ba-adb6d8e6e696)
403 Forbidden: Forbidden: cannot write to script.
Cannot access content at: https://huggingface.co/api/datasets/ORG/DATASET/branch/script.
If you are trying to create or update content,make sure you have a token with the `write` role.
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https://api.github.com/repos/huggingface/datasets/issues/5135 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5135/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5135/comments | https://api.github.com/repos/huggingface/datasets/issues/5135/events | https://github.com/huggingface/datasets/issues/5135 | 1,414,413,519 | I_kwDODunzps5UTjzP | 5,135 | Update docs once dataset scripts transferred to the Hub | {
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"completed": 0,
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} | ## Describe the bug
As discussed in:
- https://github.com/huggingface/hub-docs/pull/423#pullrequestreview-1146083701
we should update our docs once dataset scripts have been transferred to the Hub (and removed from GitHub):
- #4974
Concretely:
- [x] Datasets on GitHub (legacy): https://huggingface.co/docs/datasets/main/en/share#datasets-on-github-legacy
- [x] ADD_NEW_DATASET: https://github.com/huggingface/datasets/blob/main/ADD_NEW_DATASET.md
- ...
This PR complements the work of:
- #5067
This PR is a follow-up of PRs:
- #3777
CC: @julien-c | {
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https://api.github.com/repos/huggingface/datasets/issues/6972 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6972/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6972/comments | https://api.github.com/repos/huggingface/datasets/issues/6972/events | https://github.com/huggingface/datasets/pull/6972 | 2,353,531,912 | PR_kwDODunzps5yfa_e | 6,972 | Fix webdataset pickling | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6972). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-06-14T14:43:02Z | 2024-06-14T15:43:43Z | 2024-06-14T15:37:35Z | MEMBER | null | null | null | ...by making tracked iterables picklable.
This is important to make streaming datasets compatible with multiprocessing e.g. for parallel data loading | {
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https://api.github.com/repos/huggingface/datasets/issues/5656 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5656/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5656/comments | https://api.github.com/repos/huggingface/datasets/issues/5656/events | https://github.com/huggingface/datasets/pull/5656 | 1,634,156,563 | PR_kwDODunzps5Mjxoo | 5,656 | Fix `fsspec.open` when using an HTTP proxy | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-03-21T15:23:29Z | 2023-03-23T14:14:50Z | 2023-03-23T13:15:46Z | CONTRIBUTOR | null | null | null | Most HTTP(S) downloads from this library support proxy automatically by reading the `HTTP_PROXY` environment variable (et al.) because `requests` is widely used. However, in some parts of the code, `fsspec` is used, which in turn uses `aiohttp` for HTTP(S) requests (as opposed to `requests`), which in turn doesn't support reading proxy env variables by default. This PR enables reading them automatically.
Read [aiohttp docs on using proxies](https://docs.aiohttp.org/en/stable/client_advanced.html?highlight=trust_env#proxy-support).
For context, [the Python library requests](https://requests.readthedocs.io/en/latest/user/advanced/?highlight=http_proxy#proxies) and [the official Python library via `urllib.urlopen` support this automatically by default](https://docs.python.org/3/library/urllib.request.html#urllib.request.urlopen). Many (most common ones?) programs also do the same, including cURL, APT, Wget, and many others. | {
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https://api.github.com/repos/huggingface/datasets/issues/6908 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6908/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6908/comments | https://api.github.com/repos/huggingface/datasets/issues/6908/events | https://github.com/huggingface/datasets/issues/6908 | 2,304,958,116 | I_kwDODunzps6JYt6k | 6,908 | Fail to load "stas/c4-en-10k" dataset since 2.16 version | {
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"I am not able to reproduce the error with datasets 2.19.1:\r\n```python\r\nIn [1]: from datasets import load_dataset; ds = load_dataset(\"stas/c4-en-10k\", streaming=True); item = next(iter(ds[\"train\"])); item\r\nOut[1]: {'text': 'Beginners BBQ Class Taking Place in Missoula!\\nDo you want to get better at makin... | 2024-05-20T02:43:59Z | 2024-05-24T10:58:09Z | 2024-05-24T10:58:09Z | NONE | null | null | {
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} | ### Describe the bug
When update datasets library to version 2.16+ ( I test it on 2.16, 2.19.0 and 2.19.1), using the following code to load stas/c4-en-10k dataset
```python
from datasets import load_dataset, Dataset
dataset = load_dataset('stas/c4-en-10k')
```
and then it raise UnicodeDecodeError like
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/*/conda3/envs/watermark/lib/python3.10/site-packages/datasets/load.py", line 2523, in load_dataset
builder_instance = load_dataset_builder(
File "/home/*/conda3/envs/watermark/lib/python3.10/site-packages/datasets/load.py", line 2195, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/home/*/conda3/envs/watermark/lib/python3.10/site-packages/datasets/load.py", line 1846, in dataset_module_factory
raise e1 from None
File "/home/*/conda3/envs/watermark/lib/python3.10/site-packages/datasets/load.py", line 1798, in dataset_module_factory
can_load_config_from_parquet_export = "DEFAULT_CONFIG_NAME" not in f.read()
File "/home/*/conda3/envs/watermark/lib/python3.10/codecs.py", line 322, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x8b in position 1: invalid start byte
```
I found that fs.open loads a gzip file and parses it like plain text using utf-8 encoder.
```python
fs = HfFileSystem('https://huggingface.co')
fs.open("datasets/stas/c4-en-10k/c4-en-10k.py", "rb")
data = fs.read() # data is gzip bytes begin with b'\x1f\x8b\x08\x00\x00\tn\x88\x00...'
data2 = unzip_gzip_bytes(data) # data2 is what we want: '# coding=utf-8\n# Copyright 2020 The HuggingFace Datasets...'
```
### Steps to reproduce the bug
1. Install datasets between version 2.16 and 2.19
2. Use `datasets.load_dataset` method to load `stas/c4-en-10k` dataset.
### Expected behavior
Load dataset normally.
### Environment info
Platform = Linux-5.4.0-159-generic-x86_64-with-glibc2.35
Python = 3.10.14
Datasets = 2.19 | {
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https://api.github.com/repos/huggingface/datasets/issues/5013 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5013/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5013/comments | https://api.github.com/repos/huggingface/datasets/issues/5013/events | https://github.com/huggingface/datasets/issues/5013 | 1,383,415,971 | I_kwDODunzps5SdUCj | 5,013 | would huggingface like publish cpp binding for datasets package ? | {
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"Hi ! Can you share more information about your use case ? How could it help you to have cpp bindings versus using the python libraries ?",
"> Hi ! Can you share more information about your use case ? How could it help you to have cpp bindings versus using the python libraries ?\r\n\r\nfor example ,the huggingfac... | 2022-09-23T07:42:49Z | 2023-02-24T16:20:57Z | 2023-02-24T16:20:57Z | NONE | null | null | {
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I use cpp env libtorch, I like use hugggingface ,but huggingface not cpp binding, would you like publish cpp binding for it.
thanks | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-04-21T15:04:28Z | 2023-04-26T12:20:01Z | 2023-04-26T12:11:15Z | MEMBER | null | null | null | We need to call `fs.makedirs` when saving a dataset using `save_to_disk`, because some fs implementations have actual directories (S3 and others don't)
Close https://github.com/huggingface/datasets/issues/5775 | {
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https://api.github.com/repos/huggingface/datasets/issues/5094 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5094/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5094/comments | https://api.github.com/repos/huggingface/datasets/issues/5094/events | https://github.com/huggingface/datasets/issues/5094 | 1,403,214,950 | I_kwDODunzps5To1xm | 5,094 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock | {
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"Hi ! Could it be an Out of Memory issue that could have killed one of the processes ? can you check your memory ?",
"Hi! I don't think it is a memory issue. I'm monitoring the main and spawn python processes and threads with `htop` and the memory does not peak. Besides, the example I've posted above should not b... | 2022-10-10T13:50:56Z | 2023-07-24T15:29:13Z | 2023-07-24T15:29:13Z | NONE | null | null | {
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} | ## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `datasets.Dataset.map` spawns [a this step](https://github.com/huggingface/datasets/blob/1b935dab9d2f171a8c6294269421fe967eb55e34/src/datasets/arrow_dataset.py#L2663) go into wait mode forever.
## Steps to reproduce the bug
The below code goes into deadlock when `NUMBER_OF_PROCESSES` is greater than one.
```python
NUMBER_OF_PROCESSES = 2
from transformers import AutoTokenizer, AutoModel
from datasets import load_dataset
dataset = load_dataset("glue", "mrpc", split="train")
tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/all-MiniLM-L6-v2")
model = AutoModel.from_pretrained("sentence-transformers/all-MiniLM-L6-v2")
model.to("cpu")
def cls_pooling(model_output):
return model_output.last_hidden_state[:, 0]
def generate_embeddings_batched(examples):
sentences_batch = list(examples['sentence1'])
encoded_input = tokenizer(
sentences_batch, padding=True, truncation=True, return_tensors="pt"
)
encoded_input = {k: v.to("cpu") for k, v in encoded_input.items()}
model_output = model(**encoded_input)
embeddings = cls_pooling(model_output)
examples['embeddings'] = embeddings.detach().cpu().numpy() # 64, 384
return examples
embeddings_dataset = dataset.map(
generate_embeddings_batched,
batched=True,
batch_size=10,
num_proc=NUMBER_OF_PROCESSES
)
```
While debugging it I've seen that it gets "stuck" when calling `torch.nn.Embedding.forward` but some testing shows that the same happens with other functions from `torch.nn`.
## Environment info
- Platform: Linux-5.14.0-1052-oem-x86_64-with-glibc2.31
- Python version: 3.9.14
- PyArrow version: 9.0.0
- Pandas version: 1.5.0
Not sure if this is a HF problem, a PyTorch problem or something I'm doing wrong..
Thanks!
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https://api.github.com/repos/huggingface/datasets/issues/4661 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4661/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4661/comments | https://api.github.com/repos/huggingface/datasets/issues/4661/events | https://github.com/huggingface/datasets/issues/4661 | 1,298,374,944 | I_kwDODunzps5NY6Eg | 4,661 | Concurrency bug when using same cache among several jobs | {
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"I can confirm that if I run one job first that processes the dataset, then I can run any jobs in parallel with no problem (no write-concurrency anymore...). ",
"Hi! That's weird. It seems like the error points to the `mkstemp` function, but the official docs state the following:\r\n```\r\nThere are no race condi... | 2022-07-08T01:58:11Z | 2025-04-10T13:21:23Z | null | NONE | null | null | {
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} | ## Describe the bug
I used to see this bug with an older version of the datasets. It seems to persist.
This is my concrete scenario: I launch several evaluation jobs on a cluster in which I share the file system and I share the cache directory used by huggingface libraries. The evaluation jobs read the same *.csv files. If my jobs get all scheduled pretty much at the same time, there are all kinds of weird concurrency errors. Sometime it crashes silently. This time I got lucky that it crashed with a stack trace that I can share and maybe you get to the bottom of this. If you don't have a similar setup available, it may be hard to reproduce as you really need two jobs accessing the same file at the same time to see this type of bug.
## Steps to reproduce the bug
I'm running a modified version of `run_glue.py` script adapted to my use case. I've seen the same problem when running some glue datasets as well (so it's not specific to loading the datasets from csv files).
## Expected results
No crash, concurrent access to the (intermediate) files just fine.
## Actual results
Crashes due to races/concurrency bugs.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.2
- Platform: Linux-4.18.0-348.23.1.el8_5.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyArrow version: 8.0.0
- Pandas version: 1.1.0
Stack trace that I just got with the crash (I've obfuscated some names, it should still be quite informative):
```
Running tokenizer on dataset: 0%| | 0/3 [00:00<?, ?ba/s]
Traceback (most recent call last):
File "../../src/models//run_*******.py", line 600, in <module>
main()
File "../../src/models//run_*******.py", line 444, in main
raw_datasets = raw_datasets.map(
File "/*******//envs/tr-crt/lib/python3.8/site-packages/datasets/dataset_dict.py", line 770, in map
{
File "/*******//envs/tr-crt/lib/python3.8/site-packages/datasets/dataset_dict.py", line 771, in <dictcomp>
k: dataset.map(
File "/*******//envs/tr-crt/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2376, in map
return self._map_single(
File "/*******/envs/tr-crt/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 551, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/*******//envs/tr-crt/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 518, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/*******/envs/tr-crt/lib/python3.8/site-packages/datasets/fingerprint.py", line 458, in wrapper
out = func(self, *args, **kwargs)
File "/*******//envs/tr-crt/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2776, in _map_single
buf_writer, writer, tmp_file = init_buffer_and_writer()
File "/*******//envs/tr-crt/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2696, in init_buffer_and_writer
tmp_file = tempfile.NamedTemporaryFile("wb", dir=os.path.dirname(cache_file_name), delete=False)
File "/*******//envs/tr-crt/lib/python3.8/tempfile.py", line 541, in NamedTemporaryFile
(fd, name) = _mkstemp_inner(dir, prefix, suffix, flags, output_type)
File "/*******//envs/tr-crt/lib/python3.8/tempfile.py", line 250, in _mkstemp_inner
fd = _os.open(file, flags, 0o600)
FileNotFoundError: [Errno 2] No such file or directory: '/*******/cache-transformers//transformers/csv/default-ef9cd184210742a7/0.0.0/51cce309a08df9c4d82ffd9363bbe090bf173197fc01a71b034e8594995a1a58/tmps8l6j5yc'
```
As I ran 100s of experiments last year for an empirical paper, I ran into this type of bugs several times. I found several bandaid/work-arounds, e.g., run one job first that caches the dataset => eliminate concurrency; OR use unique caches => eliminate concurrency (but increase storage space), etc. and it all works fine.
I'd like to help you fixing this bug as it's really annoying to always apply the work arounds. Let me know what other info from my side could help you figure out the issue.
Thanks for your help!
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4778). All of your documentation changes will be reflected on that endpoint.",
"I would rather have a section in the docs that explains how to modify the script of an existing dataset (`inspect_dataset` + modification + `load_d... | 2022-08-01T20:21:07Z | 2022-08-23T16:32:26Z | 2022-08-23T16:32:22Z | MEMBER | null | null | null | This PR clarifies the local loading script section to include how to load a dataset after you've modified the local loading script (closes #4732). | {
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https://api.github.com/repos/huggingface/datasets/issues/4620 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4620/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4620/comments | https://api.github.com/repos/huggingface/datasets/issues/4620/events | https://github.com/huggingface/datasets/issues/4620 | 1,292,797,878 | I_kwDODunzps5NDoe2 | 4,620 | Data type is not recognized when using datetime.time | {
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"cc @mariosasko ",
"Hi, thanks for reporting! I'm investigating the issue."
] | 2022-07-04T08:13:38Z | 2022-07-07T13:57:11Z | 2022-07-07T13:57:11Z | COLLABORATOR | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ## Describe the bug
Creating a dataset from a pandas dataframe with `datetime.time` format generates an error.
## Steps to reproduce the bug
```python
import pandas as pd
from datetime import time
from datasets import Dataset
df = pd.DataFrame({"feature_name": [time(1, 1, 1)]})
dataset = Dataset.from_pandas(df)
```
## Expected results
The dataset should be created.
## Actual results
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 823, in from_pandas
return cls(table, info=info, split=split)
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 679, in __init__
inferred_features = Features.from_arrow_schema(arrow_table.schema)
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1551, in from_arrow_schema
obj = {field.name: generate_from_arrow_type(field.type) for field in pa_schema}
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1551, in <dictcomp>
obj = {field.name: generate_from_arrow_type(field.type) for field in pa_schema}
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1315, in generate_from_arrow_type
return Value(dtype=_arrow_to_datasets_dtype(pa_type))
File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 83, in _arrow_to_datasets_dtype
return f"time64[{arrow_type.unit}]"
AttributeError: 'pyarrow.lib.DataType' object has no attribute 'unit'
```
## Environment info
- `datasets` version: 2.3.3.dev0
- Platform: Linux-5.13.0-1031-aws-x86_64-with-glibc2.31
- Python version: 3.9.6
- PyArrow version: 7.0.0
- Pandas version: 1.4.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6270 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6270/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6270/comments | https://api.github.com/repos/huggingface/datasets/issues/6270/events | https://github.com/huggingface/datasets/issues/6270 | 1,920,329,373 | I_kwDODunzps5ydead | 6,270 | Dataset.from_generator raises with sharded gen_args | {
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"`gen_kwargs` should be a `dict`, as stated in the docstring, but you are passing a `list`.\r\n\r\nSo, to fix the error, replace the list of dicts with a dict of lists (and slightly modify the generator function):\r\n```python\r\nfrom pathlib import Path\r\nimport datasets\r\n\r\ndef process_yaml(files):\r\n for... | 2023-09-30T16:50:06Z | 2023-10-11T20:29:12Z | 2023-10-11T20:29:11Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards in `gen_kwargs`.
```
So I'd expect that if gen_kwargs was a list, then my generator would be called once for each element in the list with the dict in the list for that element.
It doesn't work that way though.
### Steps to reproduce the bug
```python
#!/usr/bin/python
from pathlib import Path
import datasets
def process_yaml(file):
yield dict(example=42)
if __name__ == '__main__':
import sys
dir = Path(sys.argv[0]).parent
ds = datasets.Dataset.from_generator(process_yaml, gen_kwargs=[{'file':f} for f in dir.glob('*.yml')],
)
ds.to_json('training.jsonl')
```
```
Generating train split: 0 examples [00:00, ? examples/s]
Traceback (most recent call last):
File "/tmp/dataset_bug.py", line 13, in <module>
ds = datasets.Dataset.from_generator(process_yaml, gen_kwargs=[{'file':f} for f in dir.glob('*.yml')],
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/hartmans/ai/venv/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 1072, in from_generator
).read()
^^^^^^
File "/home/hartmans/ai/venv/lib/python3.11/site-packages/datasets/io/generator.py", line 47, in read
self.builder.download_and_prepare(
File "/home/hartmans/ai/venv/lib/python3.11/site-packages/datasets/builder.py", line 954, in download_and_prepare
self._download_and_prepare(
File "/home/hartmans/ai/venv/lib/python3.11/site-packages/datasets/builder.py", line 1717, in _download_and_prepare
super()._download_and_prepare(
File "/home/hartmans/ai/venv/lib/python3.11/site-packages/datasets/builder.py", line 1049, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/hartmans/ai/venv/lib/python3.11/site-packages/datasets/builder.py", line 1555, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/home/hartmans/ai/venv/lib/python3.11/site-packages/datasets/builder.py", line 1656, in _prepare_split_single
generator = self._generate_examples(**gen_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: datasets.packaged_modules.generator.generator.Generator._generate_examples() argument after ** must be a ```
mapping, not list
### Expected behavior
I would expect that process_yaml would be called once for each yaml file in the directory where the script is run.
I also tried with the list being in gen_kwargs, but in that case process_yaml gets called with a list.
### Environment info
- `datasets` version: 2.14.6.dev0 (git commit 0cc77d7f45c7369; also tested with 2.14.0)
- Platform: Linux-6.1.0-10-amd64-x86_64-with-glibc2.36
- Python version: 3.11.2
- Huggingface_hub version: 0.16.4
- PyArrow version: 12.0.1
- Pandas version: 2.0.3
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https://api.github.com/repos/huggingface/datasets/issues/6152 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6152/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6152/comments | https://api.github.com/repos/huggingface/datasets/issues/6152/events | https://github.com/huggingface/datasets/issues/6152 | 1,852,494,646 | I_kwDODunzps5uatM2 | 6,152 | FolderBase Dataset automatically resolves under current directory when data_dir is not specified | {
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"@lhoestq ",
"Makes sense, I guess this can be fixed in the load_dataset_builder method.\r\nIt concerns every packaged builder I think (see values in `_PACKAGED_DATASETS_MODULES`)",
"I think the behavior is related to these lines, which short circuited the error handling.\r\nhttps://github.com/huggingface/datas... | 2023-08-16T04:38:09Z | 2025-04-08T13:13:03Z | null | CONTRIBUTOR | null | null | {
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} | ### Describe the bug
FolderBase Dataset automatically resolves under current directory when data_dir is not specified.
For example:
```
load_dataset("audiofolder")
```
takes long time to resolve and collect data_files from current directory. But I think it should reach out to this line for error handling https://github.com/huggingface/datasets/blob/cb8c5de5145c7e7eee65391cb7f4d92f0d565d62/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py#L58-L59
### Steps to reproduce the bug
```
load_dataset("audiofolder")
```
### Expected behavior
Error report
### Environment info
- `datasets` version: 2.14.4
- Platform: Linux-5.15.0-78-generic-x86_64-with-glibc2.17
- Python version: 3.8.15
- Huggingface_hub version: 0.16.4
- PyArrow version: 12.0.1
- Pandas version: 1.5.3 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7474 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7474/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7474/comments | https://api.github.com/repos/huggingface/datasets/issues/7474/events | https://github.com/huggingface/datasets/pull/7474 | 2,945,066,258 | PR_kwDODunzps6P91lM | 7,474 | Remove conditions for Python < 3.9 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7474). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"Thanks ! can you run `make style` to fix code formatting ? then we can merge",
"@lhoe... | 2025-03-25T03:08:04Z | 2025-04-16T00:11:06Z | 2025-04-15T16:07:55Z | CONTRIBUTOR | null | null | null | This PR remove conditions for Python < 3.9. | {
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https://api.github.com/repos/huggingface/datasets/issues/6513 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6513/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6513/comments | https://api.github.com/repos/huggingface/datasets/issues/6513/events | https://github.com/huggingface/datasets/issues/6513 | 2,048,869,151 | I_kwDODunzps56H0Mf | 6,513 | Support huggingface-hub 0.20.0 | {
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} | CI to test the support of `huggingface-hub` 0.20.0: https://github.com/huggingface/datasets/compare/main...ci-test-huggingface-hub-v0.20.0.rc1
We need to merge:
- #6510
- #6512
- #6516 | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-10-23T10:44:16Z | 2023-10-23T12:13:20Z | 2023-10-23T12:04:36Z | MEMBER | null | null | null | Pin upper version of `fsspec` to avoid disruptions introduced by breaking changes (and the need of urgent patch releases with hotfixes) on each release on their side. See:
- #6331
- #6210
- #5731
- #5617
- #5447
I propose that we explicitly test, introduce fixes and support each new `fsspec` version release.
CC: @LysandreJik | {
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https://api.github.com/repos/huggingface/datasets/issues/7094 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7094/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7094/comments | https://api.github.com/repos/huggingface/datasets/issues/7094/events | https://github.com/huggingface/datasets/pull/7094 | 2,454,418,130 | PR_kwDODunzps53w2b7 | 7,094 | Add Arabic Docs to Datasets | {
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[Arabic Docs](https://github.com/AhmedAlmaghz/datasets/blob/main/docs/source/ar/index.mdx)
[English Docs](https://github.com/AhmedAlmaghz/datasets/blob/main/docs/source/en/index.mdx)
@stevhliu | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5096 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5096/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5096/comments | https://api.github.com/repos/huggingface/datasets/issues/5096/events | https://github.com/huggingface/datasets/issues/5096 | 1,403,379,816 | I_kwDODunzps5TpeBo | 5,096 | Transfer some canonical datasets under an organization namespace | {
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"The transfer of the dummy dataset to the dummy org works as expected:\r\n```python\r\nIn [1]: from datasets import load_dataset; ds = load_dataset(\"dummy_canonical_dataset\", download_mode=\"force_redownload\"); ds\r\nDownloading builder script: 100%|███████████████████████████████████████████████████████████████... | 2022-10-10T15:44:31Z | 2024-06-24T06:06:28Z | 2024-06-24T06:02:45Z | MEMBER | null | null | {
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} | As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organization namespace, we are deprecating the canonical one (and eventually delete it).
First, we should test it using a dummy dataset/organization.
TODO:
- [x] Test with a dummy dataset
- [x] Create dummy canonical dataset: https://huggingface.co/datasets/dummy_canonical_dataset
- [x] Create dummy organization: https://huggingface.co/dummy-canonical-org
- [x] Transfer dummy canonical dataset to dummy organization
- [ ] Transfer datasets
- [x] babi_qa => facebook
- [x] blbooks => TheBritishLibrary/blbooks
- [x] blbooksgenre => TheBritishLibrary/blbooksgenre
- [x] common_gen => allenai
- [x] commonsense_qa => tau
- [x] competition_math => hendrycks/competition_math
- [x] cord19 => allenai
- [x] emotion => dair-ai
- [ ] gem => GEM
- [x] hellaswag => Rowan
- [x] hendrycks_test => cais/mmlu
- [x] indonlu => indonlp
- [ ] multilingual_librispeech => facebook
- It already exists "facebook/multilingual_librispeech"
- [ ] oscar => oscar-corpus
- [x] peer_read => allenai
- [x] qasper => allenai
- [x] reddit => webis/tldr-17
- [x] russian_super_glue => russiannlp
- [x] rvl_cdip => aharley
- [x] s2orc => allenai
- [x] scicite => allenai
- [x] scifact => allenai
- [x] scitldr => allenai
- [x] swiss_judgment_prediction => rcds
- [x] the_pile => EleutherAI
- [ ] wmt14, wmt15, wmt16, wmt17, wmt18, wmt19,... => wmt
- [ ] Deprecate (and eventually remove) datasets that cannot be transferred because they already exist
- [x] banking77 => PolyAI
- [x] common_voice => mozilla-foundation
- [x] german_legal_entity_recognition => elenanereiss
- ...
EDIT: the list above is continuously being updated | {
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https://api.github.com/repos/huggingface/datasets/issues/7512 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7512/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7512/comments | https://api.github.com/repos/huggingface/datasets/issues/7512/events | https://github.com/huggingface/datasets/issues/7512 | 2,994,043,544 | I_kwDODunzps6ydXqY | 7,512 | .map() fails if function uses pyvista | {
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"I found a similar (?) issue in https://github.com/huggingface/datasets/issues/6435, where someone had issues with forks and CUDA. According to https://huggingface.co/docs/datasets/main/en/process#multiprocessing we should do \n\n```\nfrom multiprocess import set_start_method\nset_start_method(\"spawn\")\n```\n\nto... | 2025-04-14T19:43:02Z | 2025-04-14T20:01:53Z | null | NONE | null | null | {
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} | ### Describe the bug
Using PyVista inside a .map() produces a crash with `objc[78796]: +[NSResponder initialize] may have been in progress in another thread when fork() was called. We cannot safely call it or ignore it in the fork() child process. Crashing instead. Set a breakpoint on objc_initializeAfterForkError to debug.`
### Steps to reproduce the bug
Run
```python
import numpy as np
import pyvista as pv
import datasets
data = [{"coords": np.random.rand(5, 3)} for _ in range(3)]
def render_point(example):
plotter = pv.Plotter(off_screen=True)
cloud = pv.PolyData(example["coords"])
plotter.add_mesh(cloud)
img = plotter.screenshot(return_img=True)
return {"image": img}
# breaks if num_proc>1
ds = datasets.Dataset.from_list(data).map(render_point, num_proc=2)
```
### Expected behavior
It should work. Just like when I use a process pool to make it work.
```python
import numpy as np
import pyvista as pv
import multiprocessing
data = [{"coords": np.random.rand(5, 3)} for _ in range(3)]
def render_point(example):
plotter = pv.Plotter(off_screen=True)
cloud = pv.PolyData(example["coords"])
plotter.add_mesh(cloud)
img = plotter.screenshot(return_img=True)
return {"image": img}
if __name__ == "__main__":
with multiprocessing.Pool(processes=2) as pool:
results = pool.map(render_point, data)
print(results[0]["image"].shape)
```
### Environment info
- `datasets` version: 3.3.2
- Platform: macOS-15.3.2-arm64-arm-64bit
- Python version: 3.11.10
- `huggingface_hub` version: 0.28.1
- PyArrow version: 18.1.0
- Pandas version: 2.2.3
- `fsspec` version: 2024.10.0
And then I suppose pyvista info is good to have.
```python
import pyvista as pv
print(pv.Report())
```
gives
--------------------------------------------------------------------------------
Date: Mon Apr 14 21:42:08 2025 CEST
OS : Darwin (macOS 15.3.2)
CPU(s) : 10
Machine : arm64
Architecture : 64bit
RAM : 32.0 GiB
Environment : IPython
File system : apfs
GPU Vendor : Apple
GPU Renderer : Apple M1 Max
GPU Version : 4.1 Metal - 89.3
MathText Support : True
Python 3.11.10 (main, Oct 7 2024, 23:25:27) [Clang 18.1.8 ]
pyvista : 0.44.2
vtk : 9.4.0
numpy : 2.2.2
matplotlib : 3.10.0
scooby : 0.10.0
pooch : 1.8.2
pillow : 11.1.0
imageio : 2.36.1
PyQt5 : 5.15.11
IPython : 8.30.0
scipy : 1.14.1
tqdm : 4.67.1
jupyterlab : 4.3.5
nest_asyncio : 1.6.0
-------------------------------------------------------------------------------- | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5655 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5655/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5655/comments | https://api.github.com/repos/huggingface/datasets/issues/5655/events | https://github.com/huggingface/datasets/pull/5655 | 1,634,030,017 | PR_kwDODunzps5MjWYy | 5,655 | Improve features decoding in to_iterable_dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-03-21T14:18:09Z | 2023-03-23T13:19:27Z | 2023-03-23T13:12:25Z | MEMBER | null | null | null | Following discussion at https://github.com/huggingface/datasets/pull/5589
Right now `to_iterable_dataset` on images/audio hurts iterable dataset performance a lot (e.g. x4 slower because it encodes+decodes images/audios unnecessarily).
I fixed it by providing a generator that yields undecoded examples | {
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https://api.github.com/repos/huggingface/datasets/issues/5907 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5907/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5907/comments | https://api.github.com/repos/huggingface/datasets/issues/5907/events | https://github.com/huggingface/datasets/pull/5907 | 1,728,648,560 | PR_kwDODunzps5RfqUU | 5,907 | Add `flatten_indices` to `DatasetDict` | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-05-27T10:55:44Z | 2023-06-01T11:46:35Z | 2023-06-01T11:39:36Z | CONTRIBUTOR | null | null | null | Add `flatten_indices` to `DatasetDict` for convinience | {
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https://api.github.com/repos/huggingface/datasets/issues/5639 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5639/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5639/comments | https://api.github.com/repos/huggingface/datasets/issues/5639/events | https://github.com/huggingface/datasets/issues/5639 | 1,625,737,098 | I_kwDODunzps5g5seK | 5,639 | Parquet file wrongly recognized as zip prevents loading a dataset | {
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} | [] | closed | false | null | [] | null | [] | 2023-03-15T15:20:45Z | 2023-03-16T13:40:14Z | 2023-03-16T13:40:14Z | MEMBER | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
When trying to `load_dataset_builder` for `HuggingFaceGECLM/StackExchange_Mar2023`, extraction fails, because parquet file [devops-00000-of-00001-22fe902fd8702892.parquet](https://huggingface.co/datasets/HuggingFaceGECLM/StackExchange_Mar2023/resolve/1f8c9a2ab6f7d0f9ae904b8b922e4384592ae1a5/data/devops-00000-of-00001-22fe902fd8702892.parquet) is wrongly identified by python as being a zip not a parquet.
(Full thread on [Slack](https://huggingface.slack.com/archives/C02V51Q3800/p1678890880803599))
### Steps to reproduce the bug
```python
from datasets import load_dataset_builder
ds = load_dataset_builder("HuggingFaceGECLM/StackExchange_Mar2023")
```
### Expected behavior
Loading the file normally.
### Environment info
- `datasets` version: 2.3.2
- Platform: Linux-5.14.0-1058-oem-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 8.0.0
- Pandas version: 1.4.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/7141 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7141/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7141/comments | https://api.github.com/repos/huggingface/datasets/issues/7141/events | https://github.com/huggingface/datasets/issues/7141 | 2,510,797,653 | I_kwDODunzps6Vp7tV | 7,141 | Older datasets throwing safety errors with 2.21.0 | {
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"I am also getting this error with this dataset: https://huggingface.co/datasets/google/IFEval",
"Me too, didn't have this issue few hours ago.",
"same observation. I even downgraded `datasets==2.20.0` and `huggingface_hub==0.23.5` leading me to believe it's an issue on the server.\r\n\r\nany known workarounds?... | 2024-09-06T16:26:30Z | 2024-09-06T21:14:14Z | 2024-09-06T19:09:29Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
The dataset loading was throwing some safety errors for this popular dataset `wmt14`.
[in]:
```
import datasets
# train_data = datasets.load_dataset("wmt14", "de-en", split="train")
train_data = datasets.load_dataset("wmt14", "de-en", split="train")
val_data = datasets.load_dataset("wmt14", "de-en", split="validation[:10%]")
```
[out]:
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[<ipython-input-9-445f0ecc4817>](https://localhost:8080/#) in <cell line: 4>()
2
3 # train_data = datasets.load_dataset("wmt14", "de-en", split="train")
----> 4 train_data = datasets.load_dataset("wmt14", "de-en", split="train")
5 val_data = datasets.load_dataset("wmt14", "de-en", split="validation[:10%]")
12 frames
[/usr/local/lib/python3.10/dist-packages/huggingface_hub/hf_api.py](https://localhost:8080/#) in __init__(self, **kwargs)
636 if security is not None:
637 security = BlobSecurityInfo(
--> 638 safe=security["safe"], av_scan=security["avScan"], pickle_import_scan=security["pickleImportScan"]
639 )
640 self.security = security
KeyError: 'safe'
```
### Steps to reproduce the bug
See above.
### Expected behavior
Dataset properly loaded.
### Environment info
version: 2.21.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/7418 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7418/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7418/comments | https://api.github.com/repos/huggingface/datasets/issues/7418/events | https://github.com/huggingface/datasets/issues/7418 | 2,868,701,471 | I_kwDODunzps6q_Okf | 7,418 | pyarrow.lib.arrowinvalid: cannot mix list and non-list, non-null values with map function | {
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"@lhoestq ",
"Can you try passing text: None for the image object ? Pyarrow expects all the objects to have the exact same type, in particular the dicttionaries in \"content\" should all have the keys \"type\" and \"text\"",
"The following modification on system prompt works, but it is different from the usual ... | 2025-02-21T10:58:06Z | 2025-02-25T15:26:46Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Encounter pyarrow.lib.arrowinvalid error with map function in some example when loading the dataset
### Steps to reproduce the bug
```
from datasets import load_dataset
from PIL import Image, PngImagePlugin
dataset = load_dataset("leonardPKU/GEOQA_R1V_Train_8K")
system_prompt="You are a helpful AI Assistant"
def make_conversation(example):
prompt = []
prompt.append({"role": "system", "content": system_prompt})
prompt.append(
{
"role": "user",
"content": [
{"type": "image"},
{"type": "text", "text": example["problem"]},
]
}
)
return {"prompt": prompt}
def check_data_types(example):
for key, value in example.items():
if key == 'image':
if not isinstance(value, PngImagePlugin.PngImageFile):
print(value)
if key == "problem" or key == "solution":
if not isinstance(value, str):
print(value)
return example
dataset = dataset.map(check_data_types)
dataset = dataset.map(make_conversation)
```
### Expected behavior
Successfully process the dataset with map
### Environment info
datasets==3.3.1 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6089 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6089/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6089/comments | https://api.github.com/repos/huggingface/datasets/issues/6089/events | https://github.com/huggingface/datasets/issues/6089 | 1,825,761,476 | I_kwDODunzps5s0ujE | 6,089 | AssertionError: daemonic processes are not allowed to have children | {
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"We could add a \"threads\" parallel backend to `datasets.parallel.parallel_backend` to support downloading with threads but note that `download_and_extract` also decompresses archives, and this is a CPU-intensive task, which is not ideal for (Python) threads (good for IO-intensive tasks).",
"> We could add a \"t... | 2023-07-28T06:04:00Z | 2023-07-31T02:34:02Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
When I load_dataset with num_proc > 0 in a deamon process, I got an error:
```python
File "/Users/codingl2k1/Work/datasets/src/datasets/download/download_manager.py", line 564, in download_and_extract
return self.extract(self.download(url_or_urls))
^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/Work/datasets/src/datasets/download/download_manager.py", line 427, in download
downloaded_path_or_paths = map_nested(
^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/Work/datasets/src/datasets/utils/py_utils.py", line 468, in map_nested
mapped = parallel_map(function, iterable, num_proc, types, disable_tqdm, desc, _single_map_nested)
^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/Work/datasets/src/datasets/utils/experimental.py", line 40, in _inner_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/Work/datasets/src/datasets/parallel/parallel.py", line 34, in parallel_map
return _map_with_multiprocessing_pool(
^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/Work/datasets/src/datasets/parallel/parallel.py", line 64, in _map_with_multiprocessing_pool
with Pool(num_proc, initargs=initargs, initializer=initializer) as pool:
^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/multiprocessing/context.py", line 119, in Pool
return Pool(processes, initializer, initargs, maxtasksperchild,
^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/multiprocessing/pool.py", line 215, in __init__
self._repopulate_pool()
^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/multiprocessing/pool.py", line 306, in _repopulate_pool
return self._repopulate_pool_static(self._ctx, self.Process,
^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/multiprocessing/pool.py", line 329, in _repopulate_pool_static
w.start()
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/multiprocessing/process.py", line 118, in start
assert not _current_process._config.get('daemon'), ^^^^^^^^^^^^^^^^^
AssertionError: daemonic processes are not allowed to have children
```
The download is io-intensive computing, may be datasets can replece the multi processing pool by a multi threading pool if in a deamon process.
### Steps to reproduce the bug
1. start a deamon process
2. run load_dataset with num_proc > 0
### Expected behavior
No error.
### Environment info
Python 3.11.4
datasets latest master | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7377 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7377/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7377/comments | https://api.github.com/repos/huggingface/datasets/issues/7377/events | https://github.com/huggingface/datasets/issues/7377 | 2,802,723,285 | I_kwDODunzps6nDinV | 7,377 | Support for sparse arrays with the Arrow Sparse Tensor format? | {
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] | open | false | null | [] | null | [
"Hi ! Unfortunately the Sparse Tensor structure in Arrow is not part of the Arrow format (yes it's confusing...), so it's not possible to use it in `datasets`. It's a separate structure that doesn't correspond to any type or extension type in Arrow.\n\nThe Arrow community recently added an extension type for fixed ... | 2025-01-21T20:14:35Z | 2025-01-30T14:06:45Z | null | NONE | null | null | {
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} | ### Feature request
AI in biology is becoming a big thing. One thing that would be a huge benefit to the field that Huggingface Datasets doesn't currently have is native support for **sparse arrays**.
Arrow has support for sparse tensors.
https://arrow.apache.org/docs/format/Other.html#sparse-tensor
It would be a big deal if Hugging Face Datasets supported sparse tensors as a feature type, natively.
### Motivation
This is important for example in the field of transcriptomics (modeling and understanding gene expression), because a large fraction of the genes are not expressed (zero). More generally, in science, sparse arrays are very common, so adding support for them would be very benefitial, it would make just using Hugging Face Dataset objects a lot more straightforward and clean.
### Your contribution
We can discuss this further once the team comments of what they think about the feature, and if there were previous attempts at making it work, and understanding their evaluation of how hard it would be. My intuition is that it should be fairly straightforward, as the Arrow backend already supports it. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5861 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5861/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5861/comments | https://api.github.com/repos/huggingface/datasets/issues/5861/events | https://github.com/huggingface/datasets/pull/5861 | 1,709,807,340 | PR_kwDODunzps5Qf55q | 5,861 | Better error message when combining dataset dicts instead of datasets | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-05-15T10:36:24Z | 2023-05-23T10:40:13Z | 2023-05-23T10:32:58Z | MEMBER | null | null | null | close https://github.com/huggingface/datasets/issues/5851 | {
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https://api.github.com/repos/huggingface/datasets/issues/7462 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7462/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7462/comments | https://api.github.com/repos/huggingface/datasets/issues/7462/events | https://github.com/huggingface/datasets/pull/7462 | 2,925,612,945 | PR_kwDODunzps6O9EA1 | 7,462 | set dev version | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7462). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-03-17T16:00:53Z | 2025-03-17T16:03:31Z | 2025-03-17T16:01:08Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6326 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6326/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6326/comments | https://api.github.com/repos/huggingface/datasets/issues/6326/events | https://github.com/huggingface/datasets/pull/6326 | 1,955,420,536 | PR_kwDODunzps5dcSRa | 6,326 | Create battery_analysis.py | {
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https://api.github.com/repos/huggingface/datasets/issues/5389 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5389/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5389/comments | https://api.github.com/repos/huggingface/datasets/issues/5389/events | https://github.com/huggingface/datasets/pull/5389 | 1,509,348,626 | PR_kwDODunzps5GHsOo | 5,389 | Fix link in `load_dataset` docstring | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2022-12-23T13:26:31Z | 2023-01-25T19:00:43Z | 2023-01-24T16:33:38Z | COLLABORATOR | null | null | null | Fix https://github.com/huggingface/datasets/issues/5387, fix https://github.com/huggingface/datasets/issues/4566 | {
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https://api.github.com/repos/huggingface/datasets/issues/7009 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7009/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7009/comments | https://api.github.com/repos/huggingface/datasets/issues/7009/events | https://github.com/huggingface/datasets/pull/7009 | 2,379,619,132 | PR_kwDODunzps5z2Xe6 | 7,009 | Support ruff 0.5.0 in CI | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7009). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-06-28T05:37:36Z | 2024-06-28T07:17:26Z | 2024-06-28T07:11:17Z | MEMBER | null | null | null | Support ruff 0.5.0 in CI and revert:
- #7007
Fix #7008. | {
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https://api.github.com/repos/huggingface/datasets/issues/7384 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7384/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7384/comments | https://api.github.com/repos/huggingface/datasets/issues/7384/events | https://github.com/huggingface/datasets/pull/7384 | 2,828,208,828 | PR_kwDODunzps6J4wVi | 7,384 | Support async functions in map() | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7384). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"example of what you can do with it:\r\n\r\n```python\r\nimport aiohttp\r\nfrom huggingf... | 2025-02-03T18:18:40Z | 2025-02-13T14:01:13Z | 2025-02-13T14:00:06Z | MEMBER | null | null | null | e.g. to download images or call an inference API like HF or vLLM
```python
import asyncio
import random
from datasets import Dataset
async def f(x):
await asyncio.sleep(random.random())
ds = Dataset.from_dict({"data": range(100)})
ds.map(f)
# Map: 100%|█████████████████████████████| 100/100 [00:01<00:00, 99.81 examples/s]
```
TODO
- [x] clean code (right now it's a big copy paste)
- [x] batched
- [x] Dataset.map()
- [x] IterableDataset.map()
- [x] Dataset.filter()
- [x] IterableDataset.filter()
- [x] test
- [x] docs | {
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https://api.github.com/repos/huggingface/datasets/issues/6687 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6687/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6687/comments | https://api.github.com/repos/huggingface/datasets/issues/6687/events | https://github.com/huggingface/datasets/pull/6687 | 2,148,554,178 | PR_kwDODunzps5nnqBB | 6,687 | fsspec: support fsspec>=2023.12.0 glob changes | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6687). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"Looking into the CI failure, this PR is incompatible with `huggingface-hub>=0.20.0`. It... | 2024-02-22T08:59:32Z | 2024-03-04T12:59:42Z | 2024-02-29T15:12:17Z | CONTRIBUTOR | null | null | null | - adds support for the `fs.glob` changes introduced in `fsspec==2023.12.0` and unpins the current upper bound
Should close #6644
Should close #6645
The `test_data_files` glob/pattern tests pass for me in:
- `fsspec==2023.10.0` (the pinned max version in datasets `main`)
- `fsspec==2023.12.0` (#6644)
- `fsspec==2024.2.0` (#6645) | {
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https://api.github.com/repos/huggingface/datasets/issues/5602 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5602/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5602/comments | https://api.github.com/repos/huggingface/datasets/issues/5602/events | https://github.com/huggingface/datasets/pull/5602 | 1,607,054,110 | PR_kwDODunzps5LJGfa | 5,602 | Return dict structure if columns are lists - to_tf_dataset | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5602). All of your documentation changes will be reflected on that endpoint.",
"This is a great PR! Thinking about the UX though, maybe we could do it without the extra argument? Before this PR, the logic in `to_tf_dataset` was... | 2023-03-02T15:51:12Z | 2023-04-12T15:54:53Z | null | CONTRIBUTOR | null | null | null | This PR introduces new logic to `to_tf_dataset` affecting the returned data structure, enabling a dictionary structure to be returned, even if only one feature column is selected.
If the passed in `columns` or `label_cols` to `to_tf_dataset` are a list, they are returned as a dictionary, respectively. If they are a string, the tensor is returned.
An outline of the behaviour:
```
dataset,to_tf_dataset(columns=["col_1"], label_cols="col_2")
# ({'col_1': col_1}, col_2}
dataset,to_tf_dataset(columns="col1", label_cols="col_2")
# (col1, col2)
dataset,to_tf_dataset(columns="col1")
# col1
dataset,to_tf_dataset(columns=["col_1"], labels=["col_2"])
# ({'col1': tensor}, {'col2': tensor}}
dataset,to_tf_dataset(columns="col_1", labels=["col_2"])
# (col1, {'col2': tensor}}
```
## Motivation
Currently, when calling `to_tf_dataset`, the returned dataset will always return a tuple structure if a single feature column is used. This can cause issues when calling `model.fit` on models which train without labels e.g. [TFVitMAEForPreTraining](https://github.com/huggingface/transformers/blob/b6f47b539377ac1fd845c7adb4ccaa5eb514e126/src/transformers/models/vit_mae/modeling_vit_mae.py#L849). Specifically, [this line](https://github.com/huggingface/transformers/blob/d9e28d91a8b2d09b51a33155d3a03ad9fcfcbd1f/src/transformers/modeling_tf_utils.py#L1521) where it's assumed the input `x` is a dictionary if there is no label.
## Example
Previous behaviour
```python
In [1]: import tensorflow as tf
...: from datasets import load_dataset
...:
...:
...: def transform(batch):
...: def _transform_img(img):
...: img = img.convert("RGB")
...: img = tf.keras.utils.img_to_array(img)
...: img = tf.image.resize(img, (224, 224))
...: img /= 255.0
...: img = tf.transpose(img, perm=[2, 0, 1])
...: return img
...: batch['pixel_values'] = [_transform_img(pil_img) for pil_img in batch['img']]
...: return batch
...:
...:
...: def collate_fn(examples):
...: pixel_values = tf.stack([example["pixel_values"] for example in examples])
...: return {"pixel_values": pixel_values}
...:
...:
...: dataset = load_dataset('cifar10')['train']
...: dataset = dataset.with_transform(transform)
...: dataset.to_tf_dataset(batch_size=8, columns=['pixel_values'], collate_fn=collate_fn)
Out[1]: <PrefetchDataset element_spec=TensorSpec(shape=(None, 3, 224, 224), dtype=tf.float32, name=None)>
```
New behaviour
```python
In [1]: import tensorflow as tf
...: from datasets import load_dataset
...:
...:
...: def transform(batch):
...: def _transform_img(img):
...: img = img.convert("RGB")
...: img = tf.keras.utils.img_to_array(img)
...: img = tf.image.resize(img, (224, 224))
...: img /= 255.0
...: img = tf.transpose(img, perm=[2, 0, 1])
...: return img
...: batch['pixel_values'] = [_transform_img(pil_img) for pil_img in batch['img']]
...: return batch
...:
...:
...: def collate_fn(examples):
...: pixel_values = tf.stack([example["pixel_values"] for example in examples])
...: return {"pixel_values": pixel_values}
...:
...:
...: dataset = load_dataset('cifar10')['train']
...: dataset = dataset.with_transform(transform)
...: dataset.to_tf_dataset(batch_size=8, columns=['pixel_values'], collate_fn=collate_fn)
Out[1]: <PrefetchDataset element_spec={'pixel_values': TensorSpec(shape=(None, 3, 224, 224), dtype=tf.float32, name=None)}>
``` | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6704 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6704/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6704/comments | https://api.github.com/repos/huggingface/datasets/issues/6704/events | https://github.com/huggingface/datasets/pull/6704 | 2,163,752,391 | PR_kwDODunzps5obZyj | 6,704 | Improve default patterns resolution | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6704). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"Awesome !\r\n\r\nNote that it can still create duplicates if a path matches several dir... | 2024-03-01T16:31:25Z | 2024-04-23T09:43:09Z | 2024-03-15T15:22:03Z | COLLABORATOR | null | null | null | Separate the default patterns that match directories from the ones matching files and ensure directories are checked first (reverts the change from https://github.com/huggingface/datasets/pull/6244, which merged these patterns). Also, ensure that the glob patterns do not overlap to avoid duplicates in the result.
Additionally, replace `get_fs_token_paths` with `url_to_fs` to avoid [unnecessary glob calls](https://github.com/fsspec/filesystem_spec/blob/14dce8ca78f7aa509a20edb263bff83a7760c24d/fsspec/core.py#L655-L656).
fix https://github.com/huggingface/datasets/issues/6259
fix https://github.com/huggingface/datasets/issues/6272 | {
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https://api.github.com/repos/huggingface/datasets/issues/6425 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6425/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6425/comments | https://api.github.com/repos/huggingface/datasets/issues/6425/events | https://github.com/huggingface/datasets/pull/6425 | 1,995,269,382 | PR_kwDODunzps5fi5ye | 6,425 | Fix deprecation warning when building conda package | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-11-15T18:00:11Z | 2023-12-13T14:22:30Z | 2023-12-13T14:16:00Z | MEMBER | null | null | null | When building/releasing conda package, we get this deprecation warning:
```
/usr/share/miniconda/envs/build-datasets/bin/conda-build:11: DeprecationWarning: conda_build.cli.main_build.main is deprecated and will be removed in 4.0.0. Use `conda build` instead.
```
This PR fixes the deprecation warning by using `conda build` instead. | {
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https://api.github.com/repos/huggingface/datasets/issues/5818 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5818/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5818/comments | https://api.github.com/repos/huggingface/datasets/issues/5818/events | https://github.com/huggingface/datasets/issues/5818 | 1,695,052,555 | I_kwDODunzps5lCHML | 5,818 | Ability to update a dataset | {
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"This [reply](https://discuss.huggingface.co/t/how-do-i-add-things-rows-to-an-already-saved-dataset/27423) from @mariosasko on the forums may be useful :)",
"In this case, I think we can avoid the `PermissionError` by unpacking the underlying `ConcatenationTable` and saving only the newly added data blocks (in ne... | 2023-05-04T01:08:13Z | 2023-05-04T20:43:39Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Feature request
The ability to load a dataset, add or change something, and save it back to disk.
Maybe it's possible, but I can't work out how to do it, e.g. this fails:
```py
import datasets
dataset = datasets.load_from_disk("data/test1")
dataset = dataset.add_item({"text": "A new item"})
dataset.save_to_disk("data/test1")
```
With the error:
```
PermissionError: Tried to overwrite /mnt/c/Users/david/py/learning/mini_projects/data_sorting_and_filtering/data/test1 but a dataset can't overwrite itself.
```
### Motivation
My use case is that I want to process a dataset in a particular way but it doesn't fit in memory if I do it in one go. So I want to perform a loop and at each step in the loop, process one shard and append it to an ever-growing dataset. The code in the loop will load a dataset, add some rows, then save it again.
Maybe I'm just thinking about things incorrectly and there's a better approach. FWIW I can't use `dataset.map()` to do the task because that doesn't work with `num_proc` when adding rows, so is confined to a single process which is too slow.
The only other way I can think of is to create a new file each time, but surely that's not how people do this sort of thing.
### Your contribution
na | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5662 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5662/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5662/comments | https://api.github.com/repos/huggingface/datasets/issues/5662/events | https://github.com/huggingface/datasets/pull/5662 | 1,637,140,813 | PR_kwDODunzps5MtvsM | 5,662 | Fix unnecessary dict comprehension | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I am merging because the CI error is unrelated.",
"<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 | re... | 2023-03-23T09:18:58Z | 2023-03-23T09:46:59Z | 2023-03-23T09:37:49Z | MEMBER | null | null | null | After ruff-0.0.258 release, the C416 rule was updated with unnecessary dict comprehensions. See:
- https://github.com/charliermarsh/ruff/releases/tag/v0.0.258
- https://github.com/charliermarsh/ruff/pull/3605
This PR fixes one unnecessary dict comprehension in our code: no need to unpack and re-pack the tuple values.
Fix #5661 | {
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https://api.github.com/repos/huggingface/datasets/issues/7535 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7535/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7535/comments | https://api.github.com/repos/huggingface/datasets/issues/7535/events | https://github.com/huggingface/datasets/pull/7535 | 3,018,289,872 | PR_kwDODunzps6T0lm3 | 7,535 | Change dill version in requirements | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7535). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-04-24T19:44:28Z | 2025-04-25T09:31:44Z | null | NONE | null | null | null | Change dill version to >=0.3.9,<0.4.5 and check for errors | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5636 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5636/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5636/comments | https://api.github.com/repos/huggingface/datasets/issues/5636/events | https://github.com/huggingface/datasets/pull/5636 | 1,623,721,577 | PR_kwDODunzps5MAunR | 5,636 | Fix CI: ignore C901 ("some_func" is to complex) in `ruff` | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-03-14T15:29:11Z | 2023-03-14T16:37:06Z | 2023-03-14T16:29:52Z | CONTRIBUTOR | null | null | null | idk if I should have added this ignore to `ruff` too, but I added :) | {
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https://api.github.com/repos/huggingface/datasets/issues/6135 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6135/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6135/comments | https://api.github.com/repos/huggingface/datasets/issues/6135/events | https://github.com/huggingface/datasets/pull/6135 | 1,844,870,943 | PR_kwDODunzps5Xn2AT | 6,135 | Remove unused allowed_extensions param | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-08-10T10:09:54Z | 2023-08-10T12:08:38Z | 2023-08-10T12:00:02Z | MEMBER | null | null | null | This PR removes unused `allowed_extensions` parameter from `create_builder_configs_from_metadata_configs`. | {
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https://api.github.com/repos/huggingface/datasets/issues/5915 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5915/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5915/comments | https://api.github.com/repos/huggingface/datasets/issues/5915/events | https://github.com/huggingface/datasets/pull/5915 | 1,732,389,984 | PR_kwDODunzps5RsVzj | 5,915 | Raise error in `DatasetBuilder.as_dataset` when `file_format` is not `"arrow"` | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-05-30T14:27:55Z | 2023-05-31T13:31:21Z | 2023-05-31T13:23:54Z | COLLABORATOR | null | null | null | Raise an error in `DatasetBuilder.as_dataset` when `file_format != "arrow"` (and fix the docstring)
Fix #5874 | {
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https://api.github.com/repos/huggingface/datasets/issues/4842 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4842/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4842/comments | https://api.github.com/repos/huggingface/datasets/issues/4842/events | https://github.com/huggingface/datasets/pull/4842 | 1,337,527,764 | PR_kwDODunzps49G8CC | 4,842 | Update stackexchange license | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-12T17:39:06Z | 2022-08-14T10:43:18Z | 2022-08-14T10:28:49Z | CONTRIBUTOR | null | null | null | The correct license of the stackexchange subset of the Pile is `cc-by-sa-4.0`, as can for example be seen here: https://stackoverflow.com/help/licensing | {
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https://api.github.com/repos/huggingface/datasets/issues/5322 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5322/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5322/comments | https://api.github.com/repos/huggingface/datasets/issues/5322/events | https://github.com/huggingface/datasets/pull/5322 | 1,471,502,162 | PR_kwDODunzps5EEeQP | 5,322 | Raise error for `.tar` archives in the same way as for `.tar.gz` and `.tgz` in `_get_extraction_protocol` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-12-01T15:19:28Z | 2022-12-14T16:37:16Z | 2022-12-14T16:33:30Z | CONTRIBUTOR | null | null | null | Currently `download_and_extract` doesn't throw an error when it is used with files with `.tar` extension in streaming mode because `_get_extraction_protocol` doesn't do it (like it does for `tar.gz` and `tgz`). `_get_extraction_protocol` returns formatted url as if we support tar protocol but we don't.
That means that in dataset scripts `.tar` files would be attempted to load and fail during examples generation (after `download_and_extract` execution). So this PR raises error for `tar` files too.
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https://api.github.com/repos/huggingface/datasets/issues/6176 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6176/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6176/comments | https://api.github.com/repos/huggingface/datasets/issues/6176/events | https://github.com/huggingface/datasets/issues/6176 | 1,864,436,408 | I_kwDODunzps5vIQq4 | 6,176 | how to limit the size of memory mapped file? | {
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"Hi! Can you share the error this reproducer throws in your environment? `streaming=True` streams the dataset as it's iterated over without creating a memory-map file.",
"The trace of the error. Streaming works but is slower.\r\n```\r\nRoot Cause (first observed failure):\r\n[0]:\r\n time : 2023-08-24_06:06... | 2023-08-24T05:33:45Z | 2023-10-11T06:00:10Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Huggingface datasets use memory-mapped file to map large datasets in memory for fast access.
However, it seems like huggingface will occupy all the memory for memory-mapped files, which makes a troublesome situation since we cluster will distribute a small portion of memory to me (once it's over the limit, memory cannot be allocated), however, when the dataset checks the total memory, all of the memory will be taken into account which makes huggingface dataset try to allocate more memory than allowed.
So is there a way to explicitly limit the size of memory mapped file?
### Steps to reproduce the bug
python
>>> from datasets import load_dataset
>>> dataset = load_dataset("c4", "en", streaming=True)
### Expected behavior
In a normal environment, this will not have any problem.
However, when the system allocates a portion of the memory to the program and when the dataset checks the total memory, all of the memory will be taken into account which makes huggingface dataset try to allocate more memory than allowed.
### Environment info
linux cluster with SGE（Sun Grid Engine） | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5077 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5077/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5077/comments | https://api.github.com/repos/huggingface/datasets/issues/5077/events | https://github.com/huggingface/datasets/pull/5077 | 1,398,080,859 | PR_kwDODunzps5AOs9L | 5,077 | Fix passed download_config in HubDatasetModuleFactoryWithoutScript | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-10-05T16:42:36Z | 2022-10-06T05:31:22Z | 2022-10-06T05:29:06Z | MEMBER | null | null | null | Fix passed `download_config` in `HubDatasetModuleFactoryWithoutScript`. | {
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https://api.github.com/repos/huggingface/datasets/issues/7261 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7261/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7261/comments | https://api.github.com/repos/huggingface/datasets/issues/7261/events | https://github.com/huggingface/datasets/issues/7261 | 2,620,510,840 | I_kwDODunzps6cMdJ4 | 7,261 | Cannot load the cache when mapping the dataset | {
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"@zhangn77 Hi ，have you solved this problem? I encountered the same issue during training. Could we discuss it?",
"I also encountered the same problem, why is that？"
] | 2024-10-29T08:29:40Z | 2025-03-24T13:27:55Z | null | NONE | null | null | {
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} | ### Describe the bug
I'm training the flux controlnet. The train_dataset.map() takes long time to finish. However, when I killed one training process and want to restart a new training with the same dataset. I can't reuse the mapped result even I defined the cache dir for the dataset.
with accelerator.main_process_first():
from datasets.fingerprint import Hasher
# fingerprint used by the cache for the other processes to load the result
# details: https://github.com/huggingface/diffusers/pull/4038#discussion_r1266078401
new_fingerprint = Hasher.hash(args)
train_dataset = train_dataset.map(
compute_embeddings_fn, batched=True, new_fingerprint=new_fingerprint, batch_size=10,
)
### Steps to reproduce the bug
train flux controlnet and start again
### Expected behavior
will not map again
### Environment info
latest diffusers
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https://api.github.com/repos/huggingface/datasets/issues/7336 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7336/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7336/comments | https://api.github.com/repos/huggingface/datasets/issues/7336/events | https://github.com/huggingface/datasets/issues/7336 | 2,744,746,456 | I_kwDODunzps6jmYHY | 7,336 | Clarify documentation or Create DatasetCard | {
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] | open | false | null | [] | null | [] | 2024-12-17T12:01:00Z | 2024-12-17T12:01:00Z | null | NONE | null | null | {
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} | ### Feature request
I noticed that you can use a Model Card instead of a Dataset Card when pushing a dataset to the Hub, but this isn’t clearly mentioned in [the docs.](https://huggingface.co/docs/datasets/dataset_card)
- Update the docs to clarify that a Model Card can work for datasets too.
- It might be worth creating a dedicated DatasetCard module, similar to the ModelCard module, for consistency and better support.
Not sure if this belongs here or on the [Hub repo](https://github.com/huggingface/huggingface_hub), but thought I’d bring it up!
### Motivation
I just spent an hour like on [this issue](https://github.com/huggingface/trl/pull/2491) trying to create a `DatasetCard` for a script.
### Your contribution
might later | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4536 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4536/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4536/comments | https://api.github.com/repos/huggingface/datasets/issues/4536/events | https://github.com/huggingface/datasets/pull/4536 | 1,278,734,727 | PR_kwDODunzps46C2z6 | 4,536 | Properly raise FileNotFound even if the dataset is private | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-21T17:05:50Z | 2022-06-28T10:46:51Z | 2022-06-28T10:36:10Z | MEMBER | null | null | null | `tests/test_load.py::test_load_streaming_private_dataset` was failing because the hub now returns 401 when getting the HfApi.dataset_info of a dataset without authentication. `load_dataset` was raising ConnectionError, while it should be FileNoteFoundError since it first checks for local files before checking the Hub.
Moreover when use_auth_token is not set (default is False), we should not pass `token=None` to HfApi.dataset_info, or it will use the local token by default - instead it should use no token. It's currently not possible to ask for no token to be used, so as a workaround I simply set token="no-token" | {
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https://api.github.com/repos/huggingface/datasets/issues/6133 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6133/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6133/comments | https://api.github.com/repos/huggingface/datasets/issues/6133/events | https://github.com/huggingface/datasets/issues/6133 | 1,844,511,519 | I_kwDODunzps5t8QMf | 6,133 | Dataset is slower after calling `to_iterable_dataset` | {
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"@lhoestq ",
"It's roughly the same code between the two so we can expected roughly the same speed, could you share a benchmark ?"
] | 2023-08-10T06:36:23Z | 2023-08-16T09:18:54Z | null | CONTRIBUTOR | null | null | {
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} | ### Describe the bug
Can anyone explain why looping over a dataset becomes slower after calling `to_iterable_dataset` to convert to `IterableDataset`
### Steps to reproduce the bug
Any dataset after converting to `IterableDataset`
### Expected behavior
Maybe it should be faster on big dataset? I only test on small dataset
### Environment info
- `datasets` version: 2.14.4
- Platform: Linux-5.15.0-76-generic-x86_64-with-glibc2.17
- Python version: 3.8.15
- Huggingface_hub version: 0.16.4
- PyArrow version: 12.0.1
- Pandas version: 1.5.3 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7201 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7201/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7201/comments | https://api.github.com/repos/huggingface/datasets/issues/7201/events | https://github.com/huggingface/datasets/issues/7201 | 2,569,837,015 | I_kwDODunzps6ZLJnX | 7,201 | `load_dataset()` of images from a single directory where `train.png` image exists | {
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} | ### Describe the bug
Hey!
Firstly, thanks for maintaining such framework!
I had a small issue, where I wanted to load a custom dataset of image+text captioning. I had all of my images in a single directory, and one of the images had the name `train.png`. Then, the loaded dataset had only this image.
I guess it's related to "train" as a split name, but it's definitely an unexpected behavior :)
Unfortunately I don't have time to submit a proper PR. I'm attaching a toy example to reproduce the issue.
Thanks,
Sagi
### Steps to reproduce the bug
All of the steps I'm attaching are in a fresh env :)
```
(base) sagipolaczek@Sagis-MacBook-Pro ~ % conda activate hf_issue_env
(hf_issue_env) sagipolaczek@Sagis-MacBook-Pro ~ % python --version
Python 3.10.15
(hf_issue_env) sagipolaczek@Sagis-MacBook-Pro ~ % pip list | grep datasets
datasets 3.0.1
(hf_issue_env) sagipolaczek@Sagis-MacBook-Pro ~ % ls -la Documents/hf_datasets_issue
total 352
drwxr-xr-x 6 sagipolaczek staff 192 Oct 7 11:59 .
drwx------@ 23 sagipolaczek staff 736 Oct 7 11:46 ..
-rw-r--r--@ 1 sagipolaczek staff 72 Oct 7 11:59 metadata.csv
-rw-r--r--@ 1 sagipolaczek staff 160154 Oct 6 18:00 pika.png
-rw-r--r--@ 1 sagipolaczek staff 5495 Oct 6 12:02 pika_pika.png
-rw-r--r--@ 1 sagipolaczek staff 1753 Oct 6 11:50 train.png
(hf_issue_env) sagipolaczek@Sagis-MacBook-Pro ~ % cat Documents/hf_datasets_issue/metadata.csv
file_name,text
train.png,A train
pika.png,Pika
pika_pika.png,Pika Pika!
(hf_issue_env) sagipolaczek@Sagis-MacBook-Pro ~ % python
Python 3.10.15 (main, Oct 3 2024, 02:33:33) [Clang 14.0.6 ] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from datasets import load_dataset
>>> dataset = load_dataset("imagefolder", data_dir="Documents/hf_datasets_issue/")
>>> dataset
DatasetDict({
train: Dataset({
features: ['image', 'text'],
num_rows: 1
})
})
>>> dataset["train"][0]
{'image': <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=354x84 at 0x10B50FD90>, 'text': 'A train'}
### DELETING `train.png` sample ###
(hf_issue_env) sagipolaczek@Sagis-MacBook-Pro ~ % vim Documents/hf_datasets_issue/metadata.csv
(hf_issue_env) sagipolaczek@Sagis-MacBook-Pro ~ % rm Documents/hf_datasets_issue/train.png
(hf_issue_env) sagipolaczek@Sagis-MacBook-Pro ~ % python
Python 3.10.15 (main, Oct 3 2024, 02:33:33) [Clang 14.0.6 ] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from datasets import load_dataset
>>> dataset = load_dataset("imagefolder", data_dir="Documents/hf_datasets_issue/")
Generating train split: 2 examples [00:00, 65.99 examples/s]
>>> dataset
DatasetDict({
train: Dataset({
features: ['image', 'text'],
num_rows: 2
})
})
>>> dataset["train"]
Dataset({
features: ['image', 'text'],
num_rows: 2
})
>>> dataset["train"][0],dataset["train"][1]
({'image': <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=2356x1054 at 0x10DD11E70>, 'text': 'Pika'}, {'image': <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=343x154 at 0x10E258C70>, 'text': 'Pika Pika!'})
```
### Expected behavior
My expected behavior would be to get a dataset with the sample `train.png` in it (along with the others data points).
### Environment info
I've attached it in the example:
Python 3.10.15
datasets 3.0.1
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https://api.github.com/repos/huggingface/datasets/issues/4743 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4743/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4743/comments | https://api.github.com/repos/huggingface/datasets/issues/4743/events | https://github.com/huggingface/datasets/pull/4743 | 1,317,362,561 | PR_kwDODunzps48EUFs | 4,743 | Update map docs | {
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] | 2022-07-25T20:59:35Z | 2022-07-27T16:22:04Z | 2022-07-27T16:10:04Z | MEMBER | null | null | null | This PR updates the `map` docs for processing text to include `return_tensors="np"` to make it run faster (see #4676). | {
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https://api.github.com/repos/huggingface/datasets/issues/4781 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4781/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4781/comments | https://api.github.com/repos/huggingface/datasets/issues/4781/events | https://github.com/huggingface/datasets/pull/4781 | 1,326,114,161 | PR_kwDODunzps48hOie | 4,781 | Fix label renaming and add a battery of tests | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Why don't we deprecate label renaming already instead ?",
"I think it'll break a lot of workflows if we deprecate it now! There isn't really a non-deprecated workflow yet - once we've added the `auto_rename_labels` option, then we ... | 2022-08-02T16:42:07Z | 2022-09-12T11:27:06Z | 2022-09-12T11:24:45Z | MEMBER | null | null | null | This PR makes some changes to label renaming in `to_tf_dataset()`, both to fix some issues when users input something we weren't expecting, and also to make it easier to deprecate label renaming in future, if/when we want to move this special-casing logic to a function in `transformers`.
The main changes are:
- Label renaming now only happens when the `auto_rename_labels` argument is set. For backward compatibility, this defaults to `True` for now.
- If the user requests "label" but the data collator renames that column to "labels", the label renaming logic will now handle that case correctly.
- Added a battery of tests to make this more reliable in future.
- Adds an optimization to loading in `to_tf_dataset()` for unshuffled datasets (uses slicing instead of a list of indices)
Fixes #4772 | {
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https://api.github.com/repos/huggingface/datasets/issues/5108 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5108/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5108/comments | https://api.github.com/repos/huggingface/datasets/issues/5108/events | https://github.com/huggingface/datasets/pull/5108 | 1,407,044,107 | PR_kwDODunzps5AskeK | 5,108 | Fix a typo in arrow_dataset.py | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6960). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"Yes!",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\... | 2024-06-07T16:18:23Z | 2024-06-08T14:58:27Z | 2024-06-08T14:52:18Z | MEMBER | null | null | null | ### What does this PR do?
Adding a GH action to scan for leaked secrets on each commit.
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https://api.github.com/repos/huggingface/datasets/issues/5237 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5237/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5237/comments | https://api.github.com/repos/huggingface/datasets/issues/5237/events | https://github.com/huggingface/datasets/pull/5237 | 1,448,202,491 | PR_kwDODunzps5C2KGz | 5,237 | Encode path only for old versions of hfh | {
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] | 2022-11-14T14:46:57Z | 2022-11-14T17:38:18Z | 2022-11-14T17:35:59Z | MEMBER | null | null | null | Next version of `huggingface-hub` 0.11 does encode the `path`, and we don't want to encode twice | {
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https://api.github.com/repos/huggingface/datasets/issues/4599 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4599/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4599/comments | https://api.github.com/repos/huggingface/datasets/issues/4599/events | https://github.com/huggingface/datasets/pull/4599 | 1,288,849,933 | PR_kwDODunzps46kvfC | 4,599 | Smooth-BLEU bug fixed | {
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"Thanks @Aktsvigun for your fix.\r\n\r\nHowever, metrics in `datasets` are in deprecation mode:\r\n- #4739\r\n\r\nYou should transfer this PR to the `evaluate` library: https://github.com/huggingface/evaluate\r\n\r\nJust for context, here the link to the PR by @Aktsvigun on tensorflow/nmt:\r\n- https://github.com/t... | 2022-06-29T14:51:42Z | 2022-09-23T07:42:40Z | 2022-09-23T07:42:40Z | NONE | null | null | null | Hi,
the current implementation of smooth-BLEU contains a bug: it smoothes unigrams as well. Consequently, when both the reference and translation consist of totally different tokens, it anyway returns a non-zero value (please see the attached image).
This however contradicts the source paper suggesting the smooth-BLEU _(Chin-Yew Lin, Franz Josef Och. ORANGE: a method for evaluating automatic evaluation metrics for machine translation. COLING 2004.)_ :
> Add one count to the n-gram hit and total ngram count for n > 1. Therefore, for candidate translations with less than n words, they can still get a positive smoothed BLEU score from shorter n-gram matches; however if nothing matches then they will get zero scores.
This pull request aims at fixing this bug.
I made a pull request in the target repository `tensorflow/nmt`, which implements this script, yet the last commit there is dating 19.02.2019 and I doubt whether this will be fixed promptly. Yet, this bug is critical, for instance for summarization datasets with short summaries (e.g. AESLC), since smoothing needs to be applied there. Therefore, the easiest solution that I found is to fork the repo and download this script directly from the forked fixed repo.
Kind,
Akim Tsvigun
<img width="516" alt="Снимок экрана 2022-06-29 в 17 49 27" src="https://user-images.githubusercontent.com/36672861/176466935-ac579e6d-6a93-4111-ab41-9b33056e7d47.png">
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https://api.github.com/repos/huggingface/datasets/issues/5844 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5844/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5844/comments | https://api.github.com/repos/huggingface/datasets/issues/5844/events | https://github.com/huggingface/datasets/issues/5844 | 1,705,907,812 | I_kwDODunzps5lrhZk | 5,844 | TypeError: Couldn't cast array of type struct<answer: struct<unanswerable: bool, answerType: string, free_form_answer: string, evidence: list<item: string>, evidenceAnnotate: list<item: string>, highlighted_evidence: list<item: string>>> to ... | {
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"completed": 0,
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} | ### Describe the bug
TypeError: Couldn't cast array of type struct<answer: struct<unanswerable: bool, answerType: string, free_form_answer: string, evidence: list<item: string>, evidenceAnnotate: list<item: string>, highlighted_evidence: list<item: string>>> to {'answer': {'unanswerable': Value(dtype='bool', id=None), 'answerType': Value(dtype='string', id=None), 'free_form_answer': Value(dtype='string', id=None), 'evidence': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'evidenceAnnotate': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'highlighted_evidence': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)}, 'unanswerable': Value(dtype='bool', id=None), 'answerType': Value(dtype='string', id=None), 'free_form_answer': Value(dtype='string', id=None), 'evidence': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'evidenceAnnotate': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'highlighted_evidence': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)}
When I use _load_dataset()_ I get the error
`from datasets import load_dataset
datafiles = {'train': './data/train.json', 'validation': './data/validation.json', 'test': './data/test.json'}
raw_data = load_dataset("json", data_files=datafiles, cache_dir="./cache")
`
Detailed error information is as follows：
Traceback (most recent call last):
File "C:/Users/CHENJIALEI/Desktop/NLPCC2023/NLPCC23_SciMRC-main/test2.py", line 9, in <module>
raw_data = load_dataset("json", data_files=datafiles, cache_dir="./cache")
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\load.py", line 1747, in load_dataset
builder_instance.download_and_prepare(
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\builder.py", line 814, in download_and_prepare
self._download_and_prepare(
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\builder.py", line 905, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\builder.py", line 1521, in _prepare_split
writer.write_table(table)
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\arrow_writer.py", line 540, in write_table
pa_table = table_cast(pa_table, self._schema)
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 2069, in table_cast
return cast_table_to_schema(table, schema)
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 2031, in cast_table_to_schema
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 2031, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 1740, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 1740, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 1867, in cast_array_to_feature
casted_values = _c(array.values, feature[0])
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 1742, in wrapper
return func(array, *args, **kwargs)
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 1862, in cast_array_to_feature
arrays = [_c(array.field(name), subfeature) for name, subfeature in feature.items()]
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 1862, in <listcomp>
arrays = [_c(array.field(name), subfeature) for name, subfeature in feature.items()]
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 1742, in wrapper
return func(array, *args, **kwargs)
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 1867, in cast_array_to_feature
casted_values = _c(array.values, feature[0])
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 1742, in wrapper
return func(array, *args, **kwargs)
File "D:\Environment\anaconda3\envs\test\lib\site-packages\datasets\table.py", line 1913, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}")
It is successful when I load the data separately
`raw_data = load_dataset("json", data_files="./data/train.json", cache_dir="./cache")`
### Steps to reproduce the bug
1.from datasets import load_dataset
2.datafiles = {'train': './data/train.json', 'validation': './data/validation.json', 'test': './data/test.json'}
3.raw_data = load_dataset("json", data_files=datafiles, cache_dir="./cache")
### Expected behavior
Successfully load dataset
### Environment info
datasets == 2.6.1
pyarrow == 8.0.0
python == 3.8
platform:windows11 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6549 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6549/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6549/comments | https://api.github.com/repos/huggingface/datasets/issues/6549/events | https://github.com/huggingface/datasets/issues/6549 | 2,062,420,259 | I_kwDODunzps567gkj | 6,549 | Loading from hf hub with clearer error message | {
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{
"color": "a2eeef",
"default": true,
"description": "New feature or request",
"id": 1935892871,
"name": "enhancement",
"node_id": "MDU6TGFiZWwxOTM1ODkyODcx",
"url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement"
}
] | open | false | null | [] | null | [
"Maybe we can add a helper message like `Maybe try again using \"hf://path/without/resolve\"` if the path contains `/resolve/` ?\r\n\r\ne.g.\r\n\r\n```\r\nFileNotFoundError: Unable to find 'hf://datasets/HuggingFaceTB/eval_data/resolve/main/eval_data_context_and_answers.json'\r\nIt looks like you used parts of the ... | 2024-01-02T13:26:34Z | 2024-01-02T14:06:49Z | null | MEMBER | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Feature request
Shouldn't this kinda work ?
```
Dataset.from_json("hf://datasets/HuggingFaceTB/eval_data/resolve/main/eval_data_context_and_answers.json")
```
I got an error
```
File ~/miniconda3/envs/datatrove/lib/python3.10/site-packages/datasets/data_files.py:380, in resolve_pattern(pattern, base_path, allowed_extensions, download_config)
378 if allowed_extensions is not None:
379 error_msg += f" with any supported extension {list(allowed_extensions)}"
--> 380 raise FileNotFoundError(error_msg)
381 return out
FileNotFoundError: Unable to find 'hf://datasets/HuggingFaceTB/eval_data/resolve/main/eval_data_context_and_answers.json'
(I'm logged in)
```
Fix: the correct path is
```
hf://datasets/HuggingFaceTB/eval_data/eval_data_context_and_answers.json
```
Proposal: raise a clearer error
### Motivation
Clearer error message
### Your contribution
Can open a PR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5619 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5619/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5619/comments | https://api.github.com/repos/huggingface/datasets/issues/5619/events | https://github.com/huggingface/datasets/pull/5619 | 1,613,439,709 | PR_kwDODunzps5LeaYP | 5,619 | unpin fsspec | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-03-07T13:22:41Z | 2023-03-07T13:47:01Z | 2023-03-07T13:39:02Z | MEMBER | null | null | null | close https://github.com/huggingface/datasets/issues/5618 | {
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https://api.github.com/repos/huggingface/datasets/issues/6028 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6028/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6028/comments | https://api.github.com/repos/huggingface/datasets/issues/6028/events | https://github.com/huggingface/datasets/pull/6028 | 1,803,294,981 | PR_kwDODunzps5Vb3LJ | 6,028 | Use new hffs | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-07-13T15:41:44Z | 2023-07-17T17:09:39Z | 2023-07-17T17:01:00Z | MEMBER | null | null | null | Thanks to @janineguo 's work in https://github.com/huggingface/datasets/pull/5919 which was needed to support HfFileSystem.
Switching to `HfFileSystem` will help implementing optimization in data files resolution
## Implementation details
I replaced all the from_hf_repo and from_local_or_remote in data_files.py to only use a new `from_patterns` which works for any fsspec path, including hf:// paths, https:// URLs and local paths. This simplifies the codebase since there is no logic duplication anymore when it comes to data files resolution.
I added `_prepare_path_and_storage_options` which returns the right storage_options to use given a path and a `DownloadConfig`. This is the only place where the logic depends on the filesystem type that must be used.
I also removed the `get_metadata_data_files_list ` and `get_patterns_and_data_files` functions added recently, since data files resolution is now handled using a common interface.
## New features
hf:// paths are now supported in data_files
## Breaking changes
DataFilesList and DataFilesDict:
- use `str` paths instead of `Union[Path, Url]`
- require posix paths for windows paths
close https://github.com/huggingface/datasets/issues/6017 | {
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https://api.github.com/repos/huggingface/datasets/issues/6793 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6793/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6793/comments | https://api.github.com/repos/huggingface/datasets/issues/6793/events | https://github.com/huggingface/datasets/issues/6793 | 2,231,400,200 | I_kwDODunzps6FAHcI | 6,793 | Loading just one particular split is not possible for imagenet-1k | {
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"+1"
] | 2024-04-08T14:39:14Z | 2024-09-12T16:24:48Z | null | NONE | null | null | {
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} | ### Describe the bug
I'd expect the following code to download just the validation split but instead I get all data on my disk (train, test and validation splits)
`
from datasets import load_dataset
dataset = load_dataset("imagenet-1k", split="validation", trust_remote_code=True)
`
Is it expected to work like that?
### Steps to reproduce the bug
1. Install the required libraries (python, datasets, huggingface_hub)
2. Login using huggingface cli
2. Run the code in the description
### Expected behavior
Just a single (validation) split should be downloaded.
### Environment info
python: 3.12.2
datasets: 2.18.0
huggingface_hub: 0.22.2 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5718 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5718/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5718/comments | https://api.github.com/repos/huggingface/datasets/issues/5718/events | https://github.com/huggingface/datasets/pull/5718 | 1,658,958,406 | PR_kwDODunzps5N2IZC | 5,718 | Reorder default data splits to have validation before test | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"After this CI error: https://github.com/huggingface/datasets/actions/runs/4639528358/jobs/8210492953?pr=5718\r\n```\r\nFAILED tests/test_data_files.py::test_get_data_files_patterns[data_file_per_split4] - AssertionError: assert ['ran... | 2023-04-07T16:01:26Z | 2023-04-27T14:43:13Z | 2023-04-27T14:35:52Z | MEMBER | null | null | null | This PR reorders data splits, so that by default validation appears before test.
The default order becomes: [train, validation, test] instead of [train, test, validation]. | {
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https://api.github.com/repos/huggingface/datasets/issues/6147 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6147/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6147/comments | https://api.github.com/repos/huggingface/datasets/issues/6147/events | https://github.com/huggingface/datasets/issues/6147 | 1,848,914,830 | I_kwDODunzps5uNDOO | 6,147 | ValueError when running BeamBasedBuilder with GCS path in cache_dir | {
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"The cause of the error seems to be that `datasets` adds \"gcs://\" as a schema, while `beam` checks only \"gs://\".\r\n\r\ndatasets: https://github.com/huggingface/datasets/blob/c02a44715c036b5261686669727394b1308a3a4b/src/datasets/builder.py#L822\r\n\r\nbeam: [link](https://github.com/apache/beam/blob/25e1a64641b... | 2023-08-14T03:11:34Z | 2024-03-18T16:59:15Z | 2024-03-18T16:59:14Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
When running the BeamBasedBuilder with a GCS path specified in the cache_dir, the following ValueError occurs:
```
ValueError: Unable to get filesystem from specified path, please use the correct path or ensure the required dependency is installed, e.g., pip install apache-beam[gcp]. Path specified: gcs://my-bucket/huggingface_datasets/my_beam_dataset/default/0.0.0/my_beam_dataset-train [while running 'train/Save to parquet/Write/WriteImpl/InitializeWrite']
```
Same error occurs after running `pip install apache-beam[gcp]` as instructed.
### Steps to reproduce the bug
Put `my_beam_dataset.py`:
```python
import datasets
class MyBeamDataset(datasets.BeamBasedBuilder):
def _info(self):
features = datasets.Features({"value": datasets.Value("int64")})
return datasets.DatasetInfo(features=features)
def _split_generators(self, dl_manager, pipeline):
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={})]
def _build_pcollection(self, pipeline):
import apache_beam as beam
return pipeline | beam.Create([{"value": i} for i in range(10)])
```
Run:
```bash
datasets-cli run_beam my_beam_dataset.py --cache_dir=gs://my-bucket/huggingface_datasets/ --beam_pipeline_options="runner=DirectRunner"
```
### Expected behavior
Running the BeamBasedBuilder with a GCS cache path without any errors.
### Environment info
- `datasets` version: 2.14.4
- Platform: macOS-13.4-arm64-arm-64bit
- Python version: 3.9.17
- Huggingface_hub version: 0.16.4
- PyArrow version: 9.0.0
- Pandas version: 2.0.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/6754 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6754/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6754/comments | https://api.github.com/repos/huggingface/datasets/issues/6754/events | https://github.com/huggingface/datasets/pull/6754 | 2,204,214,595 | PR_kwDODunzps5qk-nr | 6,754 | Fix cache path to snakecase for `CachedDatasetModuleFactory` and `Cache` | {
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"@lhoestq hi 😃, is there something else I need to do to check this change?",
"I added two tests and passed them on my server.\r\n\r\n```\r\npytest tests/packaged_modules/test_cache.py \r\n========================================================================== test session starts ==============================... | 2024-03-24T06:59:15Z | 2024-04-15T15:45:44Z | 2024-04-15T15:38:51Z | CONTRIBUTOR | null | null | null | Fix https://github.com/huggingface/datasets/issues/6750#issuecomment-2016678729
I didn't find a guideline on how to run the tests, so i just run the following steps to make sure that this bug is fixed.
1. `python test.py`,
2. then `HF_DATASETS_OFFLINE=1 python test.py`
The `test.py` is
```
import datasets
datasets.utils.logging.set_verbosity_info()
ds = datasets.load_dataset('izhx/STS17-debug')
print(ds)
ds = datasets.load_dataset('C-MTEB/AFQMC', revision='b44c3b011063adb25877c13823db83bb193913c4')
print(ds)
```
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https://api.github.com/repos/huggingface/datasets/issues/4714 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4714/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4714/comments | https://api.github.com/repos/huggingface/datasets/issues/4714/events | https://github.com/huggingface/datasets/pull/4714 | 1,309,265,682 | PR_kwDODunzps47o0YG | 4,714 | Fix named split sorting and remove unnecessary casting | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"hahaha what a timing, I added my comment right after you merged x)\r\n\r\nyou can ignore my (nit), it's fine",
"Sorry, just too sync... :sweat_smile: "
] | 2022-07-19T09:48:28Z | 2022-07-22T09:39:45Z | 2022-07-22T09:10:57Z | MEMBER | null | null | null | This PR:
- makes `NamedSplit` sortable: so that `sorted()` can be called on them
- removes unnecessary `sorted()` on `dict.keys()`: `dict_keys` view is already like a `set`
- removes unnecessary casting of `NamedSplit` to `str` | {
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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."
] | 2022-09-09T17:57:56Z | 2022-09-12T14:33:04Z | 2022-09-12T14:33:04Z | NONE | null | null | 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/6102 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6102/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6102/comments | https://api.github.com/repos/huggingface/datasets/issues/6102/events | https://github.com/huggingface/datasets/pull/6102 | 1,828,494,896 | PR_kwDODunzps5WwyGy | 6,102 | Release 2.14.2 | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-07-31T06:27:47Z | 2023-07-31T06:48:09Z | 2023-07-31T06:32:58Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4584 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4584/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4584/comments | https://api.github.com/repos/huggingface/datasets/issues/4584/events | https://github.com/huggingface/datasets/pull/4584 | 1,286,911,993 | PR_kwDODunzps46eVF7 | 4,584 | Add binary classification task IDs | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4584). All of your documentation changes will be reflected on that endpoint.",
"> Awesome thanks ! Can you add it to https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts first please ? This is where ... | 2022-06-28T07:30:39Z | 2023-09-24T10:04:04Z | 2023-01-26T09:27:52Z | MEMBER | null | null | null | As a precursor to aligning the task IDs in `datasets` and AutoTrain, we need a way to distinguish binary vs multiclass vs multilabel classification.
This PR adds binary classification to the task IDs to enable this.
Related AutoTrain issue: https://github.com/huggingface/autonlp-backend/issues/597
cc @abhishekkrthakur @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/7478 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7478/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7478/comments | https://api.github.com/repos/huggingface/datasets/issues/7478/events | https://github.com/huggingface/datasets/pull/7478 | 2,948,993,461 | PR_kwDODunzps6QLPe3 | 7,478 | update fsspec 2025.3.0 | {
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"Sorry for tagging you @lhoestq but since you merged the linked PR, I wondered if you might be able to help me get this triaged so it can be reviewed/rejected etc. 🙏🏼 ",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7478). All of your documentation changes will be reflec... | 2025-03-26T09:53:05Z | 2025-03-28T19:15:54Z | 2025-03-28T15:51:55Z | CONTRIBUTOR | null | null | null | It appears there have been two releases of fsspec since this dependency was last updated, it would be great if Datasets could be updated so that it didn't hold back the usage of newer fsspec versions in consuming projects.
PR based on https://github.com/huggingface/datasets/pull/7352 | {
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https://api.github.com/repos/huggingface/datasets/issues/7301 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7301/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7301/comments | https://api.github.com/repos/huggingface/datasets/issues/7301/events | https://github.com/huggingface/datasets/pull/7301 | 2,701,813,922 | PR_kwDODunzps6DdYLZ | 7,301 | update load_dataset doctring | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7301). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2024-11-28T11:19:20Z | 2024-11-29T10:31:43Z | 2024-11-29T10:31:40Z | MEMBER | null | null | null | - remove canonical dataset name
- remove dataset script logic
- add streaming info
- clearer download and prepare steps | {
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https://api.github.com/repos/huggingface/datasets/issues/6347 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6347/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6347/comments | https://api.github.com/repos/huggingface/datasets/issues/6347/events | https://github.com/huggingface/datasets/issues/6347 | 1,959,004,835 | I_kwDODunzps50xAqj | 6,347 | Incorrect example code in 'Create a dataset' docs | {
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"This was fixed in https://github.com/huggingface/datasets/pull/6247. You can find the fix in the `main` version of the docs",
"Ah great, thanks :)"
] | 2023-10-24T11:01:21Z | 2023-10-25T13:05:21Z | 2023-10-25T13:05:21Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
On [this](https://huggingface.co/docs/datasets/create_dataset) page, the example code for loading in images and audio is incorrect.
Currently, examples are:
``` python
from datasets import ImageFolder
dataset = load_dataset("imagefolder", data_dir="/path/to/pokemon")
```
and
``` python
from datasets import AudioFolder
dataset = load_dataset("audiofolder", data_dir="/path/to/folder")
```
I'm pretty sure the imports are wrong and should be:
``` python
from datasets import load_dataset
dataset = load_dataset("audiofolder", data_dir="/path/to/folder")
```
I am happy to update this if this is right but just wanted to check before making any changes.
### Steps to reproduce the bug
Go to https://huggingface.co/docs/datasets/create_dataset
### Expected behavior
N/A
### Environment info
N/A | {
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https://api.github.com/repos/huggingface/datasets/issues/6891 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6891/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6891/comments | https://api.github.com/repos/huggingface/datasets/issues/6891/events | https://github.com/huggingface/datasets/issues/6891 | 2,291,118,869 | I_kwDODunzps6Ij7MV | 6,891 | Unable to load JSON saved using `to_json` | {
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"Hi @DarshanDeshpande,\r\n\r\nPlease note that the default format of the method `Dataset.to_json` is [JSON-Lines](https://jsonlines.org/): it passes `orient=\"records\", lines=True` to `pandas.DataFrame.to_json`. This format is specially useful for large datasets, since unlike regular JSON files, it does not requir... | 2024-05-12T01:02:51Z | 2024-05-16T14:32:55Z | 2024-05-12T07:02:02Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Datasets stored in the JSON format cannot be loaded using `json.load()`
### Steps to reproduce the bug
```
import json
from datasets import load_dataset
dataset = load_dataset("squad")
train_dataset, test_dataset = dataset["train"], dataset["validation"]
test_dataset.to_json("full_dataset.json")
# This works
loaded_test = load_dataset("json", data_files="full_dataset.json")
# This fails
loaded_test = json.load(open("full_dataset.json", "r"))
```
### Expected behavior
The JSON should be correctly formatted when writing so that it can be loaded using `json.load()`.
### Environment info
Colab: https://colab.research.google.com/drive/1st1iStFUVgu9ZPvnzSzL4vDeYWDwYpUm?usp=sharing | {
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https://api.github.com/repos/huggingface/datasets/issues/5868 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5868/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5868/comments | https://api.github.com/repos/huggingface/datasets/issues/5868/events | https://github.com/huggingface/datasets/issues/5868 | 1,711,173,098 | I_kwDODunzps5l_m3q | 5,868 | Is it possible to change a cached file and 're-cache' it instead of re-generating? | {
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"Arrow files/primitives (tables and arrays) are immutable, so re-generating them is the only option, I'm afraid.",
"> \r\n\r\nGot it, thanks for your reply"
] | 2023-05-16T03:45:42Z | 2023-05-17T11:21:36Z | 2023-05-17T11:21:36Z | NONE | null | null | {
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} | ### Feature request
Hi,
I have a huge cached file using `map`(over 500GB), and I want to change an attribution of each element, is there possible to do it using some method instead of re-generating, because `map` takes over 24 hours
### Motivation
For large datasets, I think it is very important because we always face the problem which is changing something in the original cache without re-generating it.
### Your contribution
For now, I can't help, sorry. | {
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https://api.github.com/repos/huggingface/datasets/issues/5466 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5466/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5466/comments | https://api.github.com/repos/huggingface/datasets/issues/5466/events | https://github.com/huggingface/datasets/pull/5466 | 1,557,584,845 | PR_kwDODunzps5Ij-z1 | 5,466 | remove pathlib.Path with URIs | {
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"Thanks !\r\n`os.path.join` will use a backslash `\\` on windows which will also fail. You can use this instead in `load_from_disk`:\r\n```python\r\nfrom .filesystems import is_remote_filesystem\r\n\r\nis_local = not is_remote_filesystem(fs)\r\npath_join = os.path.join if is_local else posixpath.join\r\n```",
"Th... | 2023-01-26T03:25:45Z | 2023-01-26T17:08:57Z | 2023-01-26T16:59:11Z | CONTRIBUTOR | null | null | null | Pathlib will convert "//" to "/" which causes retry errors when downloading from cloud storage | {
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https://api.github.com/repos/huggingface/datasets/issues/4895 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4895/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4895/comments | https://api.github.com/repos/huggingface/datasets/issues/4895/events | https://github.com/huggingface/datasets/issues/4895 | 1,350,798,527 | I_kwDODunzps5Qg4y_ | 4,895 | load_dataset method returns Unknown split "validation" even if this dir exists | {
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"I don't know the main problem but it looks like, it is ignoring the last directory in your case. So, create a directory called 'zzz' in the same folder as train, validation and test. if it doesn't work, create a directory called \"aaa\". It worked for me.\r\n",
"@SamSamhuns could you please try to load it with t... | 2022-08-25T12:11:00Z | 2024-03-26T16:47:48Z | 2022-09-29T08:07:50Z | NONE | null | null | {
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} | ## Describe the bug
The `datasets.load_dataset` returns a `ValueError: Unknown split "validation". Should be one of ['train', 'test'].` when running `load_dataset(local_data_dir_path, split="validation")` even if the `validation` sub-directory exists in the local data path.
The data directories are as follows and attached to this issue:
```
test_data1
|_ train
|_ 1012.png
|_ metadata.jsonl
...
|_ test
...
|_ validation
|_ 234.png
|_ metadata.jsonl
...
test_data2
|_ train
|_ train_1012.png
|_ metadata.jsonl
...
|_ test
...
|_ validation
|_ val_234.png
|_ metadata.jsonl
...
```
They contain the same image files and `metadata.jsonl` but the images in `test_data2` have the split names prepended i.e.
`train_1012.png, val_234.png` and the images in `test_data1` do not have the split names prepended to the image names i.e. `1012.png, 234.png`
I actually saw in another issue `val` was not recognized as a split name but here I would expect the files to take the split from the parent directory name i.e. val should become part of the validation split?
## Steps to reproduce the bug
```python
import datasets
datasets.logging.set_verbosity_error()
from datasets import load_dataset, get_dataset_split_names
# the following only finds train, validation and test splits correctly
path = "./test_data1"
print("######################", get_dataset_split_names(path), "######################")
dataset_list = []
for spt in ["train", "test", "validation"]:
dataset = load_dataset(path, split=spt)
dataset_list.append(dataset)
# the following only finds train and test splits
path = "./test_data2"
print("######################", get_dataset_split_names(path), "######################")
dataset_list = []
for spt in ["train", "test", "validation"]:
dataset = load_dataset(path, split=spt)
dataset_list.append(dataset)
```
## Expected results
```
###################### ['train', 'test', 'validation'] ######################
###################### ['train', 'test', 'validation'] ######################
```
## Actual results
```
Traceback (most recent call last):
File "test_data_loader.py", line 11, in <module>
dataset = load_dataset(path, split=spt)
File "/home/venv/lib/python3.8/site-packages/datasets/load.py", line 1758, in load_dataset
ds = builder_instance.as_dataset(split=split, ignore_verifications=ignore_verifications, in_memory=keep_in_memory)
File "/home/venv/lib/python3.8/site-packages/datasets/builder.py", line 893, in as_dataset
datasets = map_nested(
File "/home/venv/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 385, in map_nested
return function(data_struct)
File "/home/venv/lib/python3.8/site-packages/datasets/builder.py", line 924, in _build_single_dataset
ds = self._as_dataset(
File "/home/venv/lib/python3.8/site-packages/datasets/builder.py", line 993, in _as_dataset
dataset_kwargs = ArrowReader(self._cache_dir, self.info).read(
File "/home/venv/lib/python3.8/site-packages/datasets/arrow_reader.py", line 211, in read
files = self.get_file_instructions(name, instructions, split_infos)
File "/home/venv/lib/python3.8/site-packages/datasets/arrow_reader.py", line 184, in get_file_instructions
file_instructions = make_file_instructions(
File "/home/venv/lib/python3.8/site-packages/datasets/arrow_reader.py", line 107, in make_file_instructions
absolute_instructions = instruction.to_absolute(name2len)
File "/home/venv/lib/python3.8/site-packages/datasets/arrow_reader.py", line 616, in to_absolute
return [_rel_to_abs_instr(rel_instr, name2len) for rel_instr in self._relative_instructions]
File "/home/venv/lib/python3.8/site-packages/datasets/arrow_reader.py", line 616, in <listcomp>
return [_rel_to_abs_instr(rel_instr, name2len) for rel_instr in self._relative_instructions]
File "/home/venv/lib/python3.8/site-packages/datasets/arrow_reader.py", line 433, in _rel_to_abs_instr
raise ValueError(f'Unknown split "{split}". Should be one of {list(name2len)}.')
ValueError: Unknown split "validation". Should be one of ['train', 'test'].
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- Platform: Linux Ubuntu 18.04
- Python version: 3.8.12
- PyArrow version: 9.0.0
Data files
[test_data1.zip](https://github.com/huggingface/datasets/files/9424463/test_data1.zip)
[test_data2.zip](https://github.com/huggingface/datasets/files/9424468/test_data2.zip)
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https://api.github.com/repos/huggingface/datasets/issues/6922 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6922/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6922/comments | https://api.github.com/repos/huggingface/datasets/issues/6922/events | https://github.com/huggingface/datasets/pull/6922 | 2,318,602,059 | PR_kwDODunzps5wolTm | 6,922 | Remove torchaudio remnants from code | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6922). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-05-27T08:45:07Z | 2024-05-27T09:08:19Z | 2024-05-27T08:59:21Z | MEMBER | null | null | null | Remove torchaudio remnants from code.
Follow-up on:
- #5573 | {
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https://api.github.com/repos/huggingface/datasets/issues/5070 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5070/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5070/comments | https://api.github.com/repos/huggingface/datasets/issues/5070/events | https://github.com/huggingface/datasets/issues/5070 | 1,396,765,647 | I_kwDODunzps5TQPPP | 5,070 | Support default config name when no builder configs | {
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"Thank you for creating this feature request, Albert.\r\n\r\nFor context this is the datatest where Albert has been helping me to switch to on-the-fly split config https://huggingface.co/datasets/HuggingFaceM4/cm4-synthetic-testing\r\n\r\nand the attempt to switch on-the-fly splits was here: https://huggingface.co/... | 2022-10-04T19:49:35Z | 2022-10-06T14:40:26Z | 2022-10-06T14:40:26Z | MEMBER | null | null | {
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} | **Is your feature request related to a problem? Please describe.**
As discussed with @stas00, we could support defining a default config name, even if no predefined allowed config names are set. That is, support `DEFAULT_CONFIG_NAME`, even when `BUILDER_CONFIGS` is not defined.
**Additional context**
In order to support creating configs on the fly **by name** (not using kwargs), the list of allowed builder configs `BUILDER_CONFIGS` must not be set.
However, if so, then `DEFAULT_CONFIG_NAME` is not supported.
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https://api.github.com/repos/huggingface/datasets/issues/6363 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6363/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6363/comments | https://api.github.com/repos/huggingface/datasets/issues/6363/events | https://github.com/huggingface/datasets/issues/6363 | 1,968,891,277 | I_kwDODunzps51WuWN | 6,363 | dataset.transform() hangs indefinitely while finetuning the stable diffusion XL | {
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"I think the code hangs on the `accelerator.main_process_first()` context manager exit. To verify this, you can append a print statement to the end of the `accelerator.main_process_first()` block. \r\n\r\n\r\nIf the problem is in `with_transform`, it would help if you could share the error stack trace printed when... | 2023-10-30T17:34:05Z | 2023-11-22T00:29:21Z | 2023-11-22T00:29:21Z | NONE | null | null | {
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} | ### Describe the bug
Multi-GPU fine-tuning the stable diffusion X by following https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/README_sdxl.md hangs indefinitely.
### Steps to reproduce the bug
accelerate launch train_text_to_image_sdxl.py --pretrained_model_name_or_path=$MODEL_NAME --pretrained_vae_model_name_or_path=$VAE_NAME --dataset_name=$DATASET_NAME --enable_xformers_memory_efficient_attention --resolution=512 --center_crop --random_flip --proportion_empty_prompts=0.2 --train_batch_size=1 --gradient_accumulation_steps=4 --gradient_checkpointing --max_train_steps=10000 --use_8bit_adam --learning_rate=1e-06 --lr_scheduler="constant" --lr_warmup_steps=0 --mixed_precision="fp16" --report_to="wandb" --validation_prompt="a cute Sundar Pichai creature" --validation_epochs 5 --checkpointing_steps=5000 --output_dir="sdxl-pokemon-model"
### Expected behavior
It should start the training as it does for the single GPU training. I opened the issue in diffusers **https://github.com/huggingface/diffusers/issues/5534 but it does seem to be an issue with the Pokemon dataset.
I added some debug prints
```
print("==========HERE3=============")
with accelerator.main_process_first():
print(accelerator.is_main_process)
print("===========Here3.1===========")
if args.max_train_samples is not None:
dataset["train"] = dataset["train"].shuffle(seed=args.seed).select(range(args.max_train_samples))
print("===========Here3.2===========")
# Set the training transforms
train_dataset = dataset["train"].with_transform(preprocess_train)
print("==========HERE4=============")
Corresponding Output
Detected kernel version 5.4.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
10/25/2023 21:18:04 - INFO - main - Distributed environment: MULTI_GPU Backend: nccl
Num processes: 3
Process index: 1
Local process index: 1
Device: cuda:1
Mixed precision type: fp16
10/25/2023 21:18:04 - INFO - main - Distributed environment: MULTI_GPU Backend: nccl
Num processes: 3
Process index: 2
Local process index: 2
Device: cuda:2
Mixed precision type: fp16
10/25/2023 21:18:04 - INFO - main - Distributed environment: MULTI_GPU Backend: nccl
Num processes: 3
Process index: 0
Local process index: 0
Device: cuda:0
Mixed precision type: fp16
You are using a model of type clip_text_model to instantiate a model of type . This is not supported for all configurations of models and can yield errors.
You are using a model of type clip_text_model to instantiate a model of type . This is not supported for all configurations of models and can yield errors.
{‘variance_type’, ‘clip_sample_range’, ‘thresholding’, ‘dynamic_thresholding_ratio’} was not found in config. Values will be initialized to default values.
{‘attention_type’, ‘reverse_transformer_layers_per_block’, ‘dropout’} was not found in config. Values will be initialized to default values.
==========HERE1=============
==========HERE1=============
==========HERE1=============
==========HERE2=============
==========HERE2=============
==========HERE2=============
==========HERE3=============
True
===========Here3.1===========
===========Here3.2===========
==========HERE3=============
==========HERE3=========
```
### Environment info
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yarl 1.9.2 pypi_0 pypi
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zlib 1.2.13 h5eee18b_0
zstd 1.5.5 hc292b87_0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5279 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5279/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5279/comments | https://api.github.com/repos/huggingface/datasets/issues/5279/events | https://github.com/huggingface/datasets/pull/5279 | 1,459,635,002 | PR_kwDODunzps5Dcoue | 5,279 | Warn about checksums | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I'm also in favor of disabling this by default - it's kinda impractical",
"Great, thanks for the quick turnaround on this!"
] | 2022-11-22T10:58:48Z | 2022-11-23T11:43:50Z | 2022-11-23T09:47:02Z | MEMBER | null | null | null | It takes a lot of time on big datasets to compute the checksums, we should at least add a warning to notify the user about this step. I also mentioned how to disable it, and added a tqdm bar (delay=5 seconds)
cc @ola13 | {
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https://api.github.com/repos/huggingface/datasets/issues/6039 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6039/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6039/comments | https://api.github.com/repos/huggingface/datasets/issues/6039/events | https://github.com/huggingface/datasets/issues/6039 | 1,806,508,451 | I_kwDODunzps5rrSGj | 6,039 | Loading column subset from parquet file produces error since version 2.13 | {
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"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
`load_dataset` allows loading a subset of columns from a parquet file with the `columns` argument. Since version 2.13, this produces the following error:
```
Traceback (most recent call last):
File "/usr/lib/python3.10/site-packages/datasets/builder.py", line 1879, in _prepare_split_single
for _, table in generator:
File "/usr/lib/python3.10/site-packages/datasets/packaged_modules/parquet/parquet.py", line 68, in _generate_tables
raise ValueError(
ValueError: Tried to load parquet data with columns '['sepal_length']' with mismatching features '{'sepal_length': Value(dtype='float64', id=None), 'sepal_width': Value(dtype='float64', id=None), 'petal_length': Value(dtype='float64', id=None), 'petal_width': Value(dtype='float64', id=None), 'species': Value(dtype='string', id=None)}'
```
This seems to occur because `datasets` is checking whether the columns in the schema exactly match the provided list of columns, instead of whether they are a subset.
### Steps to reproduce the bug
```python
# Prepare some sample data
import pandas as pd
iris = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv')
iris.to_parquet('iris.parquet')
# ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
print(iris.columns)
# Load data with datasets
from datasets import load_dataset
# Load full parquet file
dataset = load_dataset('parquet', data_files='iris.parquet')
# Load column subset; throws error for datasets>=2.13
dataset = load_dataset('parquet', data_files='iris.parquet', columns=['sepal_length'])
```
### Expected behavior
No error should be thrown and the given column subset should be loaded.
### Environment info
- `datasets` version: 2.13.0
- Platform: Linux-5.15.0-76-generic-x86_64-with-glibc2.35
- Python version: 3.10.9
- Huggingface_hub version: 0.16.4
- PyArrow version: 12.0.1
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/6212 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6212/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6212/comments | https://api.github.com/repos/huggingface/datasets/issues/6212/events | https://github.com/huggingface/datasets/issues/6212 | 1,880,399,516 | I_kwDODunzps5wFJ6c | 6,212 | Tilde (~) is not supported for data_files | {
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} | [] | open | false | null | [] | null | [
"Hi @exs-avianello, is it really needed? Note you can alternatively use `pathlib.Path` among others as it follows:\r\n\r\n```python\r\nimport datasets\r\nfrom pathlib import Path\r\n\r\n# save a parquet file at ~/path/to/data.parquet\r\n\r\ndata_files = Path.home() / \"path/to/data.parquet\"\r\ndataset = datasets.l... | 2023-09-04T14:23:49Z | 2023-09-05T08:28:39Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Attempting to `load_dataset` from a path starting with `~` (as a shorthand for the user's home directory) seems not to be fully working - at least as far as the `parquet` dataset builder is concerned.
(the same file can be loaded correctly if providing its absolute path instead)
I think that this is very similar to https://github.com/huggingface/datasets/issues/5757, but for `data_files` rather than `data_dir`
### Steps to reproduce the bug
```python
import datasets
# save a parquet file at ~/path/to/data.parquet
data_files = "~/path/to/data.parquet"
dataset = datasets.load_dataset("parquet", data_files=data_files)
```
```
Downloading data files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 12671.61it/s]
Extracting data files: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 22671.91it/s]
Generating train split: 0 examples [00:00, ? examples/s]
Traceback (most recent call last):
File ".venv/lib/python3.11/site-packages/datasets/builder.py", line 1949, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.11/site-packages/datasets/arrow_writer.py", line 598, in finalize
raise SchemaInferenceError("Please pass `features` or at least one example when writing data")
datasets.arrow_writer.SchemaInferenceError: Please pass `features` or at least one example when writing data
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File ".venv/lib/python3.11/site-packages/datasets/load.py", line 2133, in load_dataset
builder_instance.download_and_prepare(
File ".venv/lib/python3.11/site-packages/datasets/builder.py", line 954, in download_and_prepare
self._download_and_prepare(
File ".venv/lib/python3.11/site-packages/datasets/builder.py", line 1049, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File ".venv/lib/python3.11/site-packages/datasets/builder.py", line 1813, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File ".venv/lib/python3.11/site-packages/datasets/builder.py", line 1958, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.builder.DatasetGenerationError: An error occurred while generating the dataset
```
### Expected behavior
Can use `~` shorthand in paths when loading local (parquet) datasets.
### Environment info
`datasets 2.14.3`
| null | {
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https://api.github.com/repos/huggingface/datasets/issues/7520 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7520/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7520/comments | https://api.github.com/repos/huggingface/datasets/issues/7520/events | https://github.com/huggingface/datasets/issues/7520 | 2,997,422,044 | I_kwDODunzps6yqQfc | 7,520 | Update items in the dataset without `map` | {
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"description": "New feature or request",
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"name": "enhancement",
"node_id": "MDU6TGFiZWwxOTM1ODkyODcx",
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] | open | false | null | [] | null | [
"Hello!\n\nHave you looked at `Dataset.shard`? [Docs](https://huggingface.co/docs/datasets/en/process#shard)\n\nUsing this method you could break your dataset in N shards. Apply `map` on each shard and concatenate them back."
] | 2025-04-15T19:39:01Z | 2025-04-19T18:47:46Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Feature request
I would like to be able to update items in my dataset without affecting all rows. At least if there was a range option, I would be able to process those items, save the dataset, and then continue.
If I am supposed to split the dataset first, that is not clear, since the docs suggest that any of those functions returns a new object, so I don't think I can do that.
### Motivation
I am applying an extremely time-consuming function to each item in my `Dataset`. Unfortunately, datasets only supports updating values via `map`, so if my computer dies in the middle of this long-running process, I lose all progress. This is far from ideal. I would like to use `datasets` throughout this processing, but this limitation is now forcing me to write my own dataset format just to do this intermediary operation.
It would be less intuitive but I suppose I could split and then concatenate the dataset before saving? But this feels very inefficient.
### Your contribution
I can test the feature. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6825 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6825/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6825/comments | https://api.github.com/repos/huggingface/datasets/issues/6825/events | https://github.com/huggingface/datasets/pull/6825 | 2,252,404,599 | PR_kwDODunzps5tJEMw | 6,825 | Release: 2.19.0 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6825). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-04-19T08:29:02Z | 2024-05-04T12:23:26Z | 2024-04-19T08:44:57Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7105 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7105/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7105/comments | https://api.github.com/repos/huggingface/datasets/issues/7105/events | https://github.com/huggingface/datasets/pull/7105 | 2,468,207,039 | PR_kwDODunzps54eZ0D | 7,105 | Use `huggingface_hub` cache | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7105). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"Nice\r\n\r\n<img width=\"141\" alt=\"Capture d’écran 2024-08-19 à 15 25 00\" src=\"ht... | 2024-08-15T14:45:22Z | 2024-09-12T04:36:08Z | 2024-08-21T15:47:16Z | MEMBER | null | null | null | - use `hf_hub_download()` from `huggingface_hub` for HF files
- `datasets` cache_dir is still used for:
- caching datasets as Arrow files (that back `Dataset` objects)
- extracted archives, uncompressed files
- files downloaded via http (datasets with scripts)
- I removed code that were made for http files (and also the dummy_data / mock_download_manager stuff that happened to rely on them and have been legacy for a while now) | {
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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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} | See: https://github.com/huggingface/datasets/actions/runs/11106149906/job/30853879890
```
=========================== 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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https://api.github.com/repos/huggingface/datasets/issues/6652 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6652/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6652/comments | https://api.github.com/repos/huggingface/datasets/issues/6652/events | https://github.com/huggingface/datasets/pull/6652 | 2,126,760,798 | PR_kwDODunzps5mdgcv | 6,652 | Release: 2.17.0 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6652). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-02-09T09:25:01Z | 2024-02-09T10:11:48Z | 2024-02-09T10:05:35Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7380 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7380/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7380/comments | https://api.github.com/repos/huggingface/datasets/issues/7380/events | https://github.com/huggingface/datasets/pull/7380 | 2,811,566,116 | PR_kwDODunzps6JAkj5 | 7,380 | fix: dill default for version bigger 0.3.8 | {
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"`datasets` doesn't support `dill` 0.3.9 yet afaik since `dill` made some changes related to the determinism of dumps\r\n\r\nIt would be cool to investigate (maybe run the `datasets` test) with recent `dill` to see excactly what breaks and if we can make `dill` 0.3.9 work with `datasets`"
] | 2025-01-26T13:37:16Z | 2025-03-13T20:40:19Z | 2025-03-13T20:40:19Z | NONE | null | null | null | Fixes def log for dill version >= 0.3.9
https://pypi.org/project/dill/
This project uses dill with the release of version 0.3.9 the datasets lib. | {
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https://api.github.com/repos/huggingface/datasets/issues/6151 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6151/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6151/comments | https://api.github.com/repos/huggingface/datasets/issues/6151/events | https://github.com/huggingface/datasets/issues/6151 | 1,851,497,818 | I_kwDODunzps5uW51a | 6,151 | Faster sorting for single key items | {
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"`Dataset.sort` essentially does the same thing except it uses `pyarrow.compute.sort_indices` which doesn't involve copying the data into python objects (saving memory)\r\n\r\n```python\r\nsort_keys = [(col, \"ascending\") for col in column_names]\r\nindices = pc.sort_indices(self.data, sort_keys=sort_keys)\r\nretu... | 2023-08-15T14:02:31Z | 2023-08-21T14:38:26Z | 2023-08-21T14:38:25Z | NONE | null | null | {
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} | ### Feature request
A faster way to sort a dataset which contains a large number of rows.
### Motivation
The current sorting implementations took significantly longer than expected when I was running on a dataset trying to sort by timestamps.
**Code snippet:**
```python
ds = datasets.load_dataset( "json", **{"data_files": {"train": "path-to-jsonlines"}, "split": "train"}, num_proc=os.cpu_count(), keep_in_memory=True)
sorted_ds = ds.sort("pubDate", keep_in_memory=True)
```
However, once I switched to a different method which
1. unpacked to a list of tuples
2. sorted tuples by key
3. run `.select` with the sorted list of indices
It was significantly faster (orders of magnitude, especially with M's of rows)
### Your contribution
I'd be happy to implement a crude single key sorting algorithm so that other users can benefit from this trick. Broadly, this would take a `Dataset` and perform;
```python
# ds is a Dataset object
# key_name is the sorting key
class Dataset:
...
def _sort(key_name: str) -> Dataset:
index_keys = [(i,x) for i,x in enumerate(self[key_name])]
sorted_rows = sorted(row_pubdate, key=lambda x: x[1])
sorted_indicies = [x[0] for x in sorted_rows]
return self.select(sorted_indicies)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4561 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4561/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4561/comments | https://api.github.com/repos/huggingface/datasets/issues/4561/events | https://github.com/huggingface/datasets/pull/4561 | 1,283,624,242 | PR_kwDODunzps46TnVe | 4,561 | Add evaluation data to acronym_identification | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-24T11:17:33Z | 2022-06-27T09:37:55Z | 2022-06-27T08:49:22Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5355 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5355/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5355/comments | https://api.github.com/repos/huggingface/datasets/issues/5355/events | https://github.com/huggingface/datasets/pull/5355 | 1,493,076,860 | PR_kwDODunzps5FQcYG | 5,355 | Clean up Table class docstrings | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-12-13T00:29:47Z | 2022-12-13T18:17:56Z | 2022-12-13T18:14:42Z | MEMBER | null | null | null | This PR cleans up the `Table` class docstrings :) | {
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https://api.github.com/repos/huggingface/datasets/issues/7468 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7468/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7468/comments | https://api.github.com/repos/huggingface/datasets/issues/7468/events | https://github.com/huggingface/datasets/issues/7468 | 2,934,094,103 | I_kwDODunzps6u4rkX | 7,468 | function `load_dataset` can't solve folder path with regex characters like "[]" | {
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"Hi ! Have you tried escaping the glob special characters `[` and `]` ?\n\nbtw note that`AbstractFileSystem.glob` doesn't support regex, instead it supports glob patterns as in the python library [glob](https://docs.python.org/3/library/glob.html)\n"
] | 2025-03-20T05:21:59Z | 2025-03-25T10:18:12Z | null | NONE | null | null | {
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} | ### Describe the bug
When using the `load_dataset` function with a folder path containing regex special characters (such as "[]"), the issue occurs due to how the path is handled in the `resolve_pattern` function. This function passes the unprocessed path directly to `AbstractFileSystem.glob`, which supports regular expressions. As a result, the globbing mechanism interprets these characters as regex patterns, leading to a traversal of the entire disk partition instead of confining the search to the intended directory.
### Steps to reproduce the bug
just create a folder like `E:\[D_DATA]\koch_test`, then `load_dataset("parquet", data_dir="E:\[D_DATA]\\test", split="train")`
it will keep searching the whole disk.
I add two `print` in `glob` and `resolve_pattern` to see the path
### Expected behavior
it should load the dataset as in normal folders
### Environment info
- `datasets` version: 3.3.2
- Platform: Windows-10-10.0.22631-SP0
- Python version: 3.10.16
- `huggingface_hub` version: 0.29.1
- PyArrow version: 19.0.1
- Pandas version: 2.2.3
- `fsspec` version: 2024.12.0 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4799 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4799/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4799/comments | https://api.github.com/repos/huggingface/datasets/issues/4799/events | https://github.com/huggingface/datasets/issues/4799 | 1,330,889,854 | I_kwDODunzps5PU8R- | 4,799 | video dataset loader/parser | {
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"Hi! We've just started discussing the video support in `datasets` (decoding backends, video feature type, etc.), so I believe we should have something tangible by the end of this year.\r\n\r\nAlso, if you have additional video features in mind that you would like to see, feel free to let us know",
"Coool thanks ... | 2022-08-07T01:54:12Z | 2023-10-01T00:08:31Z | 2022-08-09T16:42:51Z | CONTRIBUTOR | null | null | {
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} | you know how you can [use `load_dataset` with any arbitrary csv file](https://huggingface.co/docs/datasets/loading#csv)? and you can also [use it to load a local image dataset](https://huggingface.co/docs/datasets/image_load#local-files)?
could you please add functionality to load a video dataset? it would be really cool if i could point it to a bunch of video files and use pytorch to start looping through batches of videos. like if my batch size is 16, each sample in the batch is a frame from a video. i'm competing in the [minerl challenge](https://www.aicrowd.com/challenges/neurips-2022-minerl-basalt-competition), and it would be awesome to use the HF ecosystem. | {
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https://api.github.com/repos/huggingface/datasets/issues/7082 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7082/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7082/comments | https://api.github.com/repos/huggingface/datasets/issues/7082/events | https://github.com/huggingface/datasets/pull/7082 | 2,437,354,975 | PR_kwDODunzps522dTJ | 7,082 | Support HTTP authentication in non-streaming mode | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7082). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-07-30T09:25:49Z | 2024-08-08T08:29:55Z | 2024-08-08T08:24:06Z | MEMBER | null | null | null | Support HTTP authentication in non-streaming mode, by support passing HTTP storage_options in non-streaming mode.
- Note that currently, HTTP authentication is supported only in streaming mode.
For example, this is necessary if a remote HTTP host requires authentication to download the data. | {
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https://api.github.com/repos/huggingface/datasets/issues/6329 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6329/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6329/comments | https://api.github.com/repos/huggingface/datasets/issues/6329/events | https://github.com/huggingface/datasets/issues/6329 | 1,955,858,020 | I_kwDODunzps50lAZk | 6,329 | شبکه های متن به گفتار ابتدا متن داده شده را به بازنمایی میانی | {
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https://api.github.com/repos/huggingface/datasets/issues/5402 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5402/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5402/comments | https://api.github.com/repos/huggingface/datasets/issues/5402/events | https://github.com/huggingface/datasets/issues/5402 | 1,517,409,429 | I_kwDODunzps5acdSV | 5,402 | Missing state.json when creating a cloud dataset using a dataset_builder | {
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"`load_from_disk` must be used on datasets saved using `save_to_disk`: they correspond to fully serialized datasets including their state.\r\n\r\nOn the other hand, `download_and_prepare` just downloads the raw data and convert them to arrow (or parquet if you want). We are working on allowing you to reload a datas... | 2023-01-03T13:39:59Z | 2023-01-04T17:23:57Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Using `load_dataset_builder` to create a builder, run `download_and_prepare` do upload it to S3. However when trying to load it, there are missing `state.json` files. Complete example:
```python
from aiobotocore.session import AioSession as Session
from datasets import load_from_disk, load_datase, load_dataset_builder
import s3fs
storage_options = {"session": Session()}
fs = s3fs.S3FileSystem(**storage_options)
output_dir = "s3://bucket/imdb"
builder = load_dataset_builder("imdb")
builder.download_and_prepare(output_dir, storage_options=storage_options)
load_from_disk(output_dir, fs=fs) # ERROR
# [Errno 2] No such file or directory: '/tmp/tmpy22yys8o/bucket/imdb/state.json'
```
As a comparison, if you use the non lazy `load_dataset`, it works and the S3 folder has different structure + state.json files. Example:
```python
from aiobotocore.session import AioSession as Session
from datasets import load_from_disk, load_dataset, load_dataset_builder
import s3fs
storage_options = {"session": Session()}
fs = s3fs.S3FileSystem(**storage_options)
output_dir = "s3://bucket/imdb"
dataset = load_dataset("imdb",)
dataset.save_to_disk(output_dir, fs=fs)
load_from_disk(output_dir, fs=fs) # WORKS
```
You still want the 1st option for the laziness and the parquet conversion. Thanks!
### Steps to reproduce the bug
```python
from aiobotocore.session import AioSession as Session
from datasets import load_from_disk, load_datase, load_dataset_builder
import s3fs
storage_options = {"session": Session()}
fs = s3fs.S3FileSystem(**storage_options)
output_dir = "s3://bucket/imdb"
builder = load_dataset_builder("imdb")
builder.download_and_prepare(output_dir, storage_options=storage_options)
load_from_disk(output_dir, fs=fs) # ERROR
# [Errno 2] No such file or directory: '/tmp/tmpy22yys8o/bucket/imdb/state.json'
```
BTW, you need the AioSession as s3fs is now based on aiobotocore, see https://github.com/fsspec/s3fs/issues/385.
### Expected behavior
Expected to be able to load the dataset from S3.
### Environment info
```
s3fs 2022.11.0
s3transfer 0.6.0
datasets 2.8.0
aiobotocore 2.4.2
boto3 1.24.59
botocore 1.27.59
```
python 3.7.15. | null | {
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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._",
"Thank you for adding this fix! \r\n\r\nWould it be possible to get `fn_kwargs` added to `IterableDatasetDict.map` as well? It looks like a very similar problem, and hopefully shouldn't be a huge change. \r\n",
"Hi @brianhill11! htt... | 2022-09-13T16:19:05Z | 2023-05-05T16:53:43Z | 2022-09-13T16:45:34Z | COLLABORATOR | null | null | 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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