Datasets:

gusornu

/

isuee_gus

like 0

https://api.github.com/repos/huggingface/datasets/issues/6983

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6983/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6983/comments

https://api.github.com/repos/huggingface/datasets/issues/6983/events

https://github.com/huggingface/datasets/pull/6983

PR_kwDODunzps5y7tK7

Remove metrics

closed

MEMBER

Remove all metrics, as part of the 3.0 release. Note they are deprecated since 2.5.0 version.

https://api.github.com/repos/huggingface/datasets/issues/6983/timeline

https://api.github.com/repos/huggingface/datasets/issues/6982

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6982/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6982/comments

https://api.github.com/repos/huggingface/datasets/issues/6982/events

https://github.com/huggingface/datasets/issues/6982

I_kwDODunzps6MxBgd

cannot split dataset when using load_dataset

closed

NONE

### Describe the bug when I use load_dataset methods to load mozilla-foundation/common_voice_7_0, it can successfully download and extracted the dataset but It cannot generating the arrow document, This bug happened in my server, my laptop, so as #6906 , but it won't happen in the google colab. I work for it for days, even I load the datasets from local path, it can Generating train split and validation split but bug happen again in test split. ### Steps to reproduce the bug from datasets import load_dataset, load_metric, Audio common_voice_train = load_dataset("mozilla-foundation/common_voice_7_0", "ja", split="train", token=selftoken, trust_remote_code=True) ### Expected behavior ``` { "name": "ValueError", "message": "Instruction \"train\" corresponds to no data!", "stack": "--------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[2], line 3 1 from datasets import load_dataset, load_metric, Audio ----> 3 common_voice_train = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"ja\", split=\"train\",token='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')#,trust_remote_code=True)#,streaming=True) 4 common_voice_test = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"ja\", split=\"test\",token='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')#,trust_remote_code=True)#,streaming=True) File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\load.py:2626, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs) 2622 # Build dataset for splits 2623 keep_in_memory = ( 2624 keep_in_memory if keep_in_memory is not None else is_small_dataset(builder_instance.info.dataset_size) 2625 ) -> 2626 ds = builder_instance.as_dataset(split=split, verification_mode=verification_mode, in_memory=keep_in_memory) 2627 # Rename and cast features to match task schema 2628 if task is not None: 2629 # To avoid issuing the same warning twice File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\builder.py:1266, in DatasetBuilder.as_dataset(self, split, run_post_process, verification_mode, ignore_verifications, in_memory) 1263 verification_mode = VerificationMode(verification_mode or VerificationMode.BASIC_CHECKS) 1265 # Create a dataset for each of the given splits -> 1266 datasets = map_nested( 1267 partial( 1268 self._build_single_dataset, 1269 run_post_process=run_post_process, 1270 verification_mode=verification_mode, 1271 in_memory=in_memory, 1272 ), 1273 split, 1274 map_tuple=True, 1275 disable_tqdm=True, 1276 ) 1277 if isinstance(datasets, dict): 1278 datasets = DatasetDict(datasets) File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\utils\\py_utils.py:484, in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, parallel_min_length, batched, batch_size, types, disable_tqdm, desc) 482 if batched: 483 data_struct = [data_struct] --> 484 mapped = function(data_struct) 485 if batched: 486 mapped = mapped[0] File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\builder.py:1296, in DatasetBuilder._build_single_dataset(self, split, run_post_process, verification_mode, in_memory) 1293 split = Split(split) 1295 # Build base dataset -> 1296 ds = self._as_dataset( 1297 split=split, 1298 in_memory=in_memory, 1299 ) 1300 if run_post_process: 1301 for resource_file_name in self._post_processing_resources(split).values(): File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\builder.py:1370, in DatasetBuilder._as_dataset(self, split, in_memory) 1368 if self._check_legacy_cache(): 1369 dataset_name = self.name -> 1370 dataset_kwargs = ArrowReader(cache_dir, self.info).read( 1371 name=dataset_name, 1372 instructions=split, 1373 split_infos=self.info.splits.values(), 1374 in_memory=in_memory, 1375 ) 1376 fingerprint = self._get_dataset_fingerprint(split) 1377 return Dataset(fingerprint=fingerprint, **dataset_kwargs) File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\arrow_reader.py:256, in BaseReader.read(self, name, instructions, split_infos, in_memory) 254 msg = f'Instruction \"{instructions}\" corresponds to no data!' 255 #msg = f'Instruction \"{self._path}\",\"{name}\",\"{instructions}\",\"{split_infos}\" corresponds to no data!' --> 256 raise ValueError(msg) 257 return self.read_files(files=files, original_instructions=instructions, in_memory=in_memory) ValueError: Instruction \"train\" corresponds to no data!" } ``` ### Environment info Environment: python 3.9 windows 11 pro VScode+jupyter

https://api.github.com/repos/huggingface/datasets/issues/6982/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6981

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6981/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6981/comments

https://api.github.com/repos/huggingface/datasets/issues/6981/events

https://github.com/huggingface/datasets/pull/6981

PR_kwDODunzps5y6tnN

Update docs on trust_remote_code defaults to False

closed

MEMBER

Update docs on trust_remote_code defaults to False. The docs needed to be updated due to this PR: - #6954

https://api.github.com/repos/huggingface/datasets/issues/6981/timeline

https://api.github.com/repos/huggingface/datasets/issues/6980

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6980/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6980/comments

https://api.github.com/repos/huggingface/datasets/issues/6980/events

https://github.com/huggingface/datasets/issues/6980

I_kwDODunzps6MuKBq

Support NumPy 2.0

closed

CONTRIBUTOR

### Feature request Support NumPy 2.0. ### Motivation NumPy introduces the Array API, which bridges the gap between machine learning libraries. Many clients of HuggingFace are eager to start using the Array API. Besides that, NumPy 2 provides a cleaner interface than NumPy 1. ### Tasks NumPy 2.0 was released for testing so that libraries could ensure compatibility [since mid-March](https://github.com/numpy/numpy/issues/24300#issuecomment-1986815755). What needs to be done for HuggingFace to support Numpy 2? - [x] Fix use of `array`: https://github.com/huggingface/datasets/pull/6976 - [ ] Remove [NumPy version limit](https://github.com/huggingface/datasets/pull/6975): https://github.com/huggingface/datasets/pull/6991

https://api.github.com/repos/huggingface/datasets/issues/6980/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6979

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6979/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6979/comments

https://api.github.com/repos/huggingface/datasets/issues/6979/events

https://github.com/huggingface/datasets/issues/6979

I_kwDODunzps6MrWsD

How can I load partial parquet files only?

closed

NONE

I have a HUGE dataset about 14TB, I unable to download all parquet all. I just take about 100 from it. dataset = load_dataset("xx/", data_files="data/train-001*-of-00314.parquet") How can I just using 000 - 100 from a 00314 from all partially? I search whole net didn't found a solution, **this is stupid if they didn't support it, and I swear I wont using stupid parquet any more**

https://api.github.com/repos/huggingface/datasets/issues/6979/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6978

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6978/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6978/comments

https://api.github.com/repos/huggingface/datasets/issues/6978/events

https://github.com/huggingface/datasets/pull/6978

PR_kwDODunzps5yz0h6

Fix regression for pandas < 2.0.0 in JSON loader

closed

MEMBER

A regression was introduced for pandas < 2.0.0 in PR: - #6914 As described in pandas docs, the `dtype_backend` parameter was first added in pandas 2.0.0: https://pandas.pydata.org/docs/reference/api/pandas.read_json.html This PR fixes the regression by passing (or not) the `dtype_backend` parameter depending on pandas version. Maybe, in a future 3.0 `datasets` release, we could just require pandas > 2.0. Reported by: - #6977

https://api.github.com/repos/huggingface/datasets/issues/6978/timeline

https://api.github.com/repos/huggingface/datasets/issues/6977

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6977/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6977/comments

https://api.github.com/repos/huggingface/datasets/issues/6977/events

https://github.com/huggingface/datasets/issues/6977

I_kwDODunzps6Mn_xF

load json file error with v2.20.0

closed

NONE

### Describe the bug ``` load_dataset(path="json", data_files="./test.json") ``` ``` Generating train split: 0 examples [00:00, ? examples/s] Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/datasets/packaged_modules/json/json.py", line 132, in _generate_tables pa_table = paj.read_json( File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to array in row 0 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1997, in _prepare_split_single for _, table in generator: File "/usr/local/lib/python3.10/dist-packages/datasets/packaged_modules/json/json.py", line 155, in _generate_tables df = pd.read_json(f, dtype_backend="pyarrow") File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 211, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 331, in wrapper return func(*args, **kwargs) TypeError: read_json() got an unexpected keyword argument 'dtype_backend' The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/app/t1.py", line 11, in <module> load_dataset(path=data_path, data_files="./t2.json") File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2616, in load_dataset builder_instance.download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1029, in download_and_prepare self._download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1124, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1884, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 2040, in _prepare_split_single raise DatasetGenerationError("An error occurred while generating the dataset") from e datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset ``` ``` import pandas as pd with open("./test.json", "r") as f: df = pd.read_json(f, dtype_backend="pyarrow") ``` ``` Traceback (most recent call last): File "/app/t3.py", line 3, in <module> df = pd.read_json(f, dtype_backend="pyarrow") File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 211, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 331, in wrapper return func(*args, **kwargs) TypeError: read_json() got an unexpected keyword argument 'dtype_backend' ``` ### Steps to reproduce the bug . ### Expected behavior . ### Environment info ``` datasets 2.20.0 pandas 1.5.3 ```

https://api.github.com/repos/huggingface/datasets/issues/6977/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6976

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6976/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6976/comments

https://api.github.com/repos/huggingface/datasets/issues/6976/events

https://github.com/huggingface/datasets/pull/6976

PR_kwDODunzps5yrmNP

Ensure compatibility with numpy 2.0.0

closed

CONTRIBUTOR

Following the conversion guide, copy=False is no longer required and will result in an error: https://numpy.org/devdocs/numpy_2_0_migration_guide.html#adapting-to-changes-in-the-copy-keyword. The following fix should resolve the issue. error found during testing on the MTEB repository e.g. [here](https://github.com/embeddings-benchmark/mteb/pull/938)

https://api.github.com/repos/huggingface/datasets/issues/6976/timeline

https://api.github.com/repos/huggingface/datasets/issues/6975

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6975/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6975/comments

https://api.github.com/repos/huggingface/datasets/issues/6975/events

https://github.com/huggingface/datasets/pull/6975

PR_kwDODunzps5yrPct

Set temporary numpy upper version < 2.0.0 to fix CI

closed

MEMBER

Set temporary numpy upper version < 2.0.0 to fix CI. See: https://github.com/huggingface/datasets/actions/runs/9546031216/job/26308072017 ``` A module that was compiled using NumPy 1.x cannot be run in NumPy 2.0.0 as it may crash. To support both 1.x and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuild instead e.g. with 'pybind11>=2.12'. If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules will need time to support NumPy 2. ```

https://api.github.com/repos/huggingface/datasets/issues/6975/timeline

https://api.github.com/repos/huggingface/datasets/issues/6973

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6973/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6973/comments

https://api.github.com/repos/huggingface/datasets/issues/6973/events

https://github.com/huggingface/datasets/issues/6973

I_kwDODunzps6MZley

IndexError during training with Squad dataset and T5-small model

closed

NONE

### Describe the bug I am encountering an IndexError while training a T5-small model on the Squad dataset using the transformers and datasets libraries. The error occurs even with a minimal reproducible example, suggesting a potential bug or incompatibility. ### Steps to reproduce the bug 1.Install the required libraries: !pip install transformers datasets 2.Run the following code: !pip install transformers datasets import torch from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, TrainingArguments, Trainer, DataCollatorWithPadding # Load a small, publicly available dataset from datasets import load_dataset dataset = load_dataset("squad", split="train[:100]") # Use a small subset for testing # Load a pre-trained model and tokenizer model_name = "t5-small" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForSeq2SeqLM.from_pretrained(model_name) # Define a basic data collator data_collator = DataCollatorWithPadding(tokenizer=tokenizer) # Define training arguments training_args = TrainingArguments( output_dir="./results", per_device_train_batch_size=2, num_train_epochs=1, ) # Create a trainer trainer = Trainer( model=model, args=training_args, train_dataset=dataset, data_collator=data_collator, ) # Train the model trainer.train() ### Expected behavior --------------------------------------------------------------------------- IndexError Traceback (most recent call last) [<ipython-input-23-f13a4b23c001>](https://localhost:8080/#) in <cell line: 34>() 32 33 # Train the model ---> 34 trainer.train() 10 frames [/usr/local/lib/python3.10/dist-packages/datasets/formatting/formatting.py](https://localhost:8080/#) in _check_valid_index_key(key, size) 427 if isinstance(key, int): 428 if (key < 0 and key + size < 0) or (key >= size): --> 429 raise IndexError(f"Invalid key: {key} is out of bounds for size {size}") 430 return 431 elif isinstance(key, slice): IndexError: Invalid key: 42 is out of bounds for size 0 ### Environment info transformers version:4.41.2 datasets version:1.18.4 Python version:3.10.12

https://api.github.com/repos/huggingface/datasets/issues/6973/timeline

completed

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

PR_kwDODunzps5yfa_e

Fix webdataset pickling

closed

MEMBER

...by making tracked iterables picklable. This is important to make streaming datasets compatible with multiprocessing e.g. for parallel data loading

https://api.github.com/repos/huggingface/datasets/issues/6972/timeline

https://api.github.com/repos/huggingface/datasets/issues/6971

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6971/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6971/comments

https://api.github.com/repos/huggingface/datasets/issues/6971/events

https://github.com/huggingface/datasets/pull/6971

PR_kwDODunzps5yZoc3

packaging: Remove useless dependencies

closed

CONTRIBUTOR

Revert changes in #6396 and #6404. CVE-2023-47248 has been fixed since PyArrow v14.0.1. Meanwhile Python requirements requires `pyarrow>=15.0.0`.

https://api.github.com/repos/huggingface/datasets/issues/6971/timeline

https://api.github.com/repos/huggingface/datasets/issues/6970

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6970/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6970/comments

https://api.github.com/repos/huggingface/datasets/issues/6970/events

https://github.com/huggingface/datasets/pull/6970

PR_kwDODunzps5yYF37

Set dev version

closed

MEMBER

https://api.github.com/repos/huggingface/datasets/issues/6970/timeline

https://api.github.com/repos/huggingface/datasets/issues/6969

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6969/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6969/comments

https://api.github.com/repos/huggingface/datasets/issues/6969/events

https://github.com/huggingface/datasets/pull/6969

PR_kwDODunzps5yX_nC

Release: 2.20.0

closed

MEMBER

https://api.github.com/repos/huggingface/datasets/issues/6969/timeline

https://api.github.com/repos/huggingface/datasets/issues/6968

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6968/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6968/comments

https://api.github.com/repos/huggingface/datasets/issues/6968/events

https://github.com/huggingface/datasets/pull/6968

PR_kwDODunzps5yX7Qr

Use `HF_HUB_OFFLINE` instead of `HF_DATASETS_OFFLINE`

closed

CONTRIBUTOR

To use `datasets` offline, one can use the `HF_DATASETS_OFFLINE` environment variable. This PR makes `HF_HUB_OFFLINE` the recommended environment variable for offline training. Goal is to be more consistent with the rest of HF ecosystem and have a single config value to set. The changes are backward-compatible meaning that: - `HF_DATASETS_OFFLINE` environment is still taken into account, though not documented - `datasets.config.HF_DATASETS_OFFLINE` still exists, though it is not used anymore (in favor of `datasets.config.HF_HUB_OFFLINE`) **Note:** it might break things in downstream libraries if they were monkeypatching `datasets.config.HF_DATASETS_OFFLINE` in their CI tests (for instance). Not much of a problem IMO.

https://api.github.com/repos/huggingface/datasets/issues/6968/timeline

https://api.github.com/repos/huggingface/datasets/issues/6967

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6967/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6967/comments

https://api.github.com/repos/huggingface/datasets/issues/6967/events

https://github.com/huggingface/datasets/issues/6967

I_kwDODunzps6MBSEe

Method to load Laion400m

open

NONE

### Feature request Large datasets like Laion400m are provided as embeddings. The provided methods in load_dataset are not straightforward for loading embedding files, i.e. img_emb_XX.npy ; XX = 0 to 99 ### Motivation The trial and experimentation is the key pivot of HF. It would be great if HF can load embeddings files s,ealessly. ### Your contribution I cam write the loader with some help.

https://api.github.com/repos/huggingface/datasets/issues/6967/timeline

https://api.github.com/repos/huggingface/datasets/issues/6966

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6966/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6966/comments

https://api.github.com/repos/huggingface/datasets/issues/6966/events

https://github.com/huggingface/datasets/pull/6966

PR_kwDODunzps5yPwL4

Remove underlines between badges

closed

CONTRIBUTOR

## Before: <img width="935" alt="image" src="https://github.com/huggingface/datasets/assets/35881688/93666e72-059b-4180-9e1d-ff176a3d9dac"> ## After: <img width="956" alt="image" src="https://github.com/huggingface/datasets/assets/35881688/75df7c3e-f473-44f0-a872-eeecf6a85fe2">

https://api.github.com/repos/huggingface/datasets/issues/6966/timeline

https://api.github.com/repos/huggingface/datasets/issues/6965

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6965/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6965/comments

https://api.github.com/repos/huggingface/datasets/issues/6965/events

https://github.com/huggingface/datasets/pull/6965

PR_kwDODunzps5yOyNG

Improve skip take shuffling and distributed

closed

MEMBER

set the right behavior of skip/take depending on whether it's called after or before shuffle/split_by_node

https://api.github.com/repos/huggingface/datasets/issues/6965/timeline

https://api.github.com/repos/huggingface/datasets/issues/6964

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6964/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6964/comments

https://api.github.com/repos/huggingface/datasets/issues/6964/events

https://github.com/huggingface/datasets/pull/6964

PR_kwDODunzps5yCNGa

Fix resuming arrow format

closed

MEMBER

following https://github.com/huggingface/datasets/pull/6658

https://api.github.com/repos/huggingface/datasets/issues/6964/timeline

https://api.github.com/repos/huggingface/datasets/issues/6963

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6963/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6963/comments

https://api.github.com/repos/huggingface/datasets/issues/6963/events

https://github.com/huggingface/datasets/pull/6963

PR_kwDODunzps5x_yu-

[Streaming] retry on requests errors

closed

MEMBER

reported in https://discuss.huggingface.co/t/speeding-up-streaming-of-large-datasets-fineweb/90714/6 when training using a streaming a dataloader cc @Wauplin it looks like the retries from `hfh` are not always enough. In this PR I let `datasets` do additional retries (that users can configure in `datasets.config`) since I couldn't find an easy way to increase the max_retries for `hfh` users in general.

https://api.github.com/repos/huggingface/datasets/issues/6963/timeline

https://api.github.com/repos/huggingface/datasets/issues/6962

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6962/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6962/comments

https://api.github.com/repos/huggingface/datasets/issues/6962/events

https://github.com/huggingface/datasets/pull/6962

PR_kwDODunzps5x8yHt

fix(ci): remove unnecessary permissions

closed

MEMBER

### What does this PR do? Remove unnecessary permissions granted to the actions workflow. Sorry for the mishap.

https://api.github.com/repos/huggingface/datasets/issues/6962/timeline

https://api.github.com/repos/huggingface/datasets/issues/6961

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6961/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6961/comments

https://api.github.com/repos/huggingface/datasets/issues/6961/events

https://github.com/huggingface/datasets/issues/6961

I_kwDODunzps6LmG0S

Manual downloads should count as downloads

open

NONE

### Feature request I would like to request that manual downloads of data files from Hugging Face dataset repositories count as downloads of a dataset. According to the documentation for the Hugging Face Hub, that is currently not the case: https://huggingface.co/docs/hub/en/datasets-download-stats ### Motivation This would ensure that downloads are accurately reported to end users. ### Your contribution N/A

https://api.github.com/repos/huggingface/datasets/issues/6961/timeline

https://api.github.com/repos/huggingface/datasets/issues/6960

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6960/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6960/comments

https://api.github.com/repos/huggingface/datasets/issues/6960/events

https://github.com/huggingface/datasets/pull/6960

PR_kwDODunzps5x0R3T

feat(ci): add trufflehog secrets detection

closed

MEMBER

### What does this PR do? Adding a GH action to scan for leaked secrets on each commit.

https://api.github.com/repos/huggingface/datasets/issues/6960/timeline

https://api.github.com/repos/huggingface/datasets/issues/6959

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6959/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6959/comments

https://api.github.com/repos/huggingface/datasets/issues/6959/events

https://github.com/huggingface/datasets/pull/6959

PR_kwDODunzps5xyVt6

Better error handling in `dataset_module_factory`

closed

CONTRIBUTOR

cc @cakiki who reported it on [slack](https://huggingface.slack.com/archives/C039P47V1L5/p1717754405578539) (private link) This PR updates how errors are handled in `dataset_module_factory` when the `dataset_info` cannot be accessed: 1. Use multiple `except ... as e` instead of using `isinstance(e, ...)` 2. Always raise `DatasetNotFoundError` with `from e` so that the initial error is explicitly logged in the stacktrace. 3. Differentiate `RepoNotFoundError` / `GatedRepoError` / `RevisionNotFoundError` cases

https://api.github.com/repos/huggingface/datasets/issues/6959/timeline

https://api.github.com/repos/huggingface/datasets/issues/6958

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6958/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6958/comments

https://api.github.com/repos/huggingface/datasets/issues/6958/events

https://github.com/huggingface/datasets/issues/6958

I_kwDODunzps6LUw8f

My Private Dataset doesn't exist on the Hub or cannot be accessed

closed

NONE

### Describe the bug ``` File "/root/miniconda3/envs/gino_conda/lib/python3.9/site-packages/datasets/load.py", line 1852, in dataset_module_factory raise DatasetNotFoundError(msg + f" at revision '{revision}'" if revision else msg) datasets.exceptions.DatasetNotFoundError: Dataset 'xxx' doesn't exist on the Hub or cannot be accessed >>> dataset = load_dataset("xxxx", token=True) 404 error 404 Client Error. (Request ID: Root=xxxx) Repository Not Found for url: https://huggingface.co/api/datasets/xxx/xxx. Please make sure you specified the correct `repo_id` and `repo_type`. If you are trying to access a private or gated repo, make sure you are authenticated. Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/root/miniconda3/envs/gino_conda/lib/python3.9/site-packages/datasets/load.py", line 2593, in load_dataset builder_instance = load_dataset_builder( File "/root/miniconda3/envs/gino_conda/lib/python3.9/site-packages/datasets/load.py", line 2265, in load_dataset_builder dataset_module = dataset_module_factory( File "/root/miniconda3/envs/gino_conda/lib/python3.9/site-packages/datasets/load.py", line 1910, in dataset_module_factory raise e1 from None File "/root/miniconda3/envs/gino_conda/lib/python3.9/site-packages/datasets/load.py", line 1852, in dataset_module_factory raise DatasetNotFoundError(msg + f" at revision '{revision}'" if revision else msg) datasets.exceptions.DatasetNotFoundError: Dataset 'xxx' doesn't exist on the Hub or cannot be accessed ``` ### Steps to reproduce the bug 123 ### Expected behavior 123 ### Environment info 123

https://api.github.com/repos/huggingface/datasets/issues/6958/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6957

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6957/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6957/comments

https://api.github.com/repos/huggingface/datasets/issues/6957/events

https://github.com/huggingface/datasets/pull/6957

PR_kwDODunzps5xiTwJ

Fix typos in docs

closed

MEMBER

Fix typos in docs introduced by: - #6956 Typos: - `comparisions` => `comparisons` - two consecutive sentences both ending in colon - split one sentence into two Sorry, I did not have time to review that PR. CC: @lhoestq

https://api.github.com/repos/huggingface/datasets/issues/6957/timeline

https://api.github.com/repos/huggingface/datasets/issues/6956

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6956/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6956/comments

https://api.github.com/repos/huggingface/datasets/issues/6956/events

https://github.com/huggingface/datasets/pull/6956

PR_kwDODunzps5xcwXz

update docs on N-dim arrays

closed

MEMBER

https://api.github.com/repos/huggingface/datasets/issues/6956/timeline

https://api.github.com/repos/huggingface/datasets/issues/6955

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6955/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6955/comments

https://api.github.com/repos/huggingface/datasets/issues/6955/events

https://github.com/huggingface/datasets/pull/6955

PR_kwDODunzps5xcSYm

Fix small typo

closed

CONTRIBUTOR

https://api.github.com/repos/huggingface/datasets/issues/6955/timeline

https://api.github.com/repos/huggingface/datasets/issues/6954

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6954/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6954/comments

https://api.github.com/repos/huggingface/datasets/issues/6954/events

https://github.com/huggingface/datasets/pull/6954

PR_kwDODunzps5xbWtU

Remove default `trust_remote_code=True`

closed

MEMBER

TODO: - [x] fix tests

https://api.github.com/repos/huggingface/datasets/issues/6954/timeline

https://api.github.com/repos/huggingface/datasets/issues/6953

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6953/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6953/comments

https://api.github.com/repos/huggingface/datasets/issues/6953/events

https://github.com/huggingface/datasets/issues/6953

I_kwDODunzps6LFFdo

Remove canonical datasets from docs

closed

MEMBER

Remove canonical datasets from docs, now that we no longer have canonical datasets.

https://api.github.com/repos/huggingface/datasets/issues/6953/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6952

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6952/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6952/comments

https://api.github.com/repos/huggingface/datasets/issues/6952/events

https://github.com/huggingface/datasets/pull/6952

PR_kwDODunzps5xaosH

Move info_utils errors to exceptions module

closed

MEMBER

Move `info_utils` errors to `exceptions` module. Additionally rename some of them, deprecate the former ones, and make the deprecation backward compatible (by making the new errors inherit from the former ones).

https://api.github.com/repos/huggingface/datasets/issues/6952/timeline

https://api.github.com/repos/huggingface/datasets/issues/6951

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6951/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6951/comments

https://api.github.com/repos/huggingface/datasets/issues/6951/events

https://github.com/huggingface/datasets/issues/6951

I_kwDODunzps6LEkfC

load_dataset() should load all subsets, if no specific subset is specified

closed

NONE

### Feature request Currently load_dataset() is forcing users to specify a subset. Example `from datasets import load_dataset dataset = load_dataset("m-a-p/COIG-CQIA")` ```--------------------------------------------------------------------------- ValueError Traceback (most recent call last) [<ipython-input-10-c0cb49385da6>](https://localhost:8080/#) in <cell line: 2>() 1 from datasets import load_dataset ----> 2 dataset = load_dataset("m-a-p/COIG-CQIA") 3 frames [/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _create_builder_config(self, config_name, custom_features, **config_kwargs) 582 if not config_kwargs: 583 example_of_usage = f"load_dataset('{self.dataset_name}', '{self.BUILDER_CONFIGS[0].name}')" --> 584 raise ValueError( 585 "Config name is missing." 586 f"\nPlease pick one among the available configs: {list(self.builder_configs.keys())}" ValueError: Config name is missing. Please pick one among the available configs: ['chinese_traditional', 'coig_pc', 'exam', 'finance', 'douban', 'human_value', 'logi_qa', 'ruozhiba', 'segmentfault', 'wiki', 'wikihow', 'xhs', 'zhihu'] Example of usage: `load_dataset('coig-cqia', 'chinese_traditional')` ``` This means a dataset cannot contain all the subsets at the same time. I guess one workaround is to manually specify the subset files like in [here](https://huggingface.co/datasets/m-a-p/COIG-CQIA/discussions/1#658698b44bb41498f75c5622), which is clumsy. ### Motivation Ideally, if not subset is specified, the API should just try to load all subsets. This makes it much easier to handle datasets w/ subsets. ### Your contribution Not sure since I'm not familiar w/ the lib src.

https://api.github.com/repos/huggingface/datasets/issues/6951/timeline

not_planned

https://api.github.com/repos/huggingface/datasets/issues/6950

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6950/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6950/comments

https://api.github.com/repos/huggingface/datasets/issues/6950/events

https://github.com/huggingface/datasets/issues/6950

I_kwDODunzps6LDtiW

`Dataset.with_format` behaves inconsistently with documentation

closed

NONE

### Describe the bug The actual behavior of the interface `Dataset.with_format` is inconsistent with the documentation. https://huggingface.co/docs/datasets/use_with_pytorch#n-dimensional-arrays https://huggingface.co/docs/datasets/v2.19.0/en/use_with_tensorflow#n-dimensional-arrays > If your dataset consists of N-dimensional arrays, you will see that by default they are considered as nested lists. > In particular, a PyTorch formatted dataset outputs nested lists instead of a single tensor. > A TensorFlow formatted dataset outputs a RaggedTensor instead of a single tensor. But I get a single tensor by default, which is inconsistent with the description. Actually the current behavior seems more reasonable to me. Therefore, the document needs to be modified. ### Steps to reproduce the bug ```python >>> from datasets import Dataset >>> data = [[[1, 2],[3, 4]],[[5, 6],[7, 8]]] >>> ds = Dataset.from_dict({"data": data}) >>> ds = ds.with_format("torch") >>> ds[0] {'data': tensor([[1, 2], [3, 4]])} >>> ds = ds.with_format("tf") >>> ds[0] {'data': <tf.Tensor: shape=(2, 2), dtype=int64, numpy= array([[1, 2], [3, 4]])>} ``` ### Expected behavior ```python >>> from datasets import Dataset >>> data = [[[1, 2],[3, 4]],[[5, 6],[7, 8]]] >>> ds = Dataset.from_dict({"data": data}) >>> ds = ds.with_format("torch") >>> ds[0] {'data': [tensor([1, 2]), tensor([3, 4])]} >>> ds = ds.with_format("tf") >>> ds[0] {'data': <tf.RaggedTensor [[1, 2], [3, 4]]>} ``` ### Environment info datasets==2.19.1 torch==2.1.0 tensorflow==2.13.1

https://api.github.com/repos/huggingface/datasets/issues/6950/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6949

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6949/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6949/comments

https://api.github.com/repos/huggingface/datasets/issues/6949/events

https://github.com/huggingface/datasets/issues/6949

I_kwDODunzps6LBKG9

load_dataset error

closed

NONE

### Describe the bug Why does the program get stuck when I use load_dataset method, and it still gets stuck after loading for several hours? In fact, my json file is only 21m, and I can load it in one go using open('', 'r'). ### Steps to reproduce the bug 1. pip install datasets==2.19.2 2. from datasets import Dataset, DatasetDict, NamedSplit, Split, load_dataset 3. data = load_dataset('json', data_files='train.json') ### Expected behavior It is able to load my json correctly ### Environment info datasets==2.19.2

https://api.github.com/repos/huggingface/datasets/issues/6949/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6948

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6948/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6948/comments

https://api.github.com/repos/huggingface/datasets/issues/6948/events

https://github.com/huggingface/datasets/issues/6948

I_kwDODunzps6K-87c

to_tf_dataset: Visible devices cannot be modified after being initialized

open

NONE

### Describe the bug When trying to use to_tf_dataset with a custom data_loader collate_fn when I use parallelism I am met with the following error as many times as number of workers there were in ``num_workers``. File "/opt/miniconda/envs/env/lib/python3.11/site-packages/multiprocess/process.py", line 314, in _bootstrap self.run() File "/opt/miniconda/envs/env/lib/python3.11/site-packages/multiprocess/process.py", line 108, in run self._target(*self._args, **self._kwargs) File "/opt/miniconda/envs/env/lib/python3.11/site-packages/datasets/utils/tf_utils.py", line 438, in worker_loop tf.config.set_visible_devices([], "GPU") # Make sure workers don't try to allocate GPU memory ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/miniconda/envs/env/lib/python3.11/site-packages/tensorflow/python/framework/config.py", line 566, in set_visible_devices context.context().set_visible_devices(devices, device_type) File "/opt/miniconda/envs/env/lib/python3.11/site-packages/tensorflow/python/eager/context.py", line 1737, in set_visible_devices raise RuntimeError( RuntimeError: Visible devices cannot be modified after being initialized ### Steps to reproduce the bug 1. Download a dataset using HuggingFace load_dataset 2. Define a function that transforms the data in some way to be used in the collate_fn argument 3. Provide a ``batch_size`` and ``num_workers`` value in the ``to_tf_dataset`` function 4. Either retrieve directly or use tfds benchmark to test the dataset ``` python from datasets import load_datasets import tensorflow_datasets as tfds from keras_cv.layers import Resizing def data_loader(examples): x = Resizing(examples[0]['image'], 256, 256, crop_to_aspect_ratio=True) return {X[0]: x} ds = load_datasets("logasja/FDF", split="test") ds = ds.to_tf_dataset(collate_fn=data_loader, batch_size=16, num_workers=2) tfds.benchmark(ds) ``` ### Expected behavior Use multiple processes to apply transformations from the collate_fn to the tf dataset on the CPU. ### Environment info - `datasets` version: 2.19.1 - Platform: Linux-6.5.0-1023-oracle-x86_64-with-glibc2.35 - Python version: 3.11.8 - `huggingface_hub` version: 0.22.2 - PyArrow version: 15.0.2 - Pandas version: 2.2.1 - `fsspec` version: 2024.2.0

https://api.github.com/repos/huggingface/datasets/issues/6948/timeline

https://api.github.com/repos/huggingface/datasets/issues/6947

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6947/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6947/comments

https://api.github.com/repos/huggingface/datasets/issues/6947/events

https://github.com/huggingface/datasets/issues/6947

I_kwDODunzps6K8fpH

FileNotFoundError：error when loading C4 dataset

closed

NONE

### Describe the bug can't load c4 datasets When I replace the datasets package to 2.12.2 I get raise datasets.utils.info_utils.ExpectedMoreSplits: {'train'} How can I fix this？ ### Steps to reproduce the bug 1.from datasets import load_dataset 2.dataset = load_dataset('allenai/c4', data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation') 3. raise FileNotFoundError( FileNotFoundError: Couldn't find a dataset script at local_path/c4_val/allenai/c4/c4.py or any data file in the same directory. Couldn't find 'allenai/c4' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/allenai/c4@1588ec454efa1a09f29cd18ddd04fe05fc8653a2/en/c4-validation.00003-of-00008.json.gz' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip'] ### Expected behavior The data was successfully imported ### Environment info python version 3.9 datasets version 2.19.2

https://api.github.com/repos/huggingface/datasets/issues/6947/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6946

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6946/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6946/comments

https://api.github.com/repos/huggingface/datasets/issues/6946/events

https://github.com/huggingface/datasets/pull/6946

PR_kwDODunzps5xQNao

Re-enable import sorting disabled by flake8:noqa directive when using ruff linter

closed

MEMBER

Re-enable import sorting that was wrongly disabled by `flake8: noqa` directive after switching to `ruff` linter in datasets-2.10.0 PR: - #5519 Note that after the linter switch, we wrongly replaced `flake8: noqa` with `ruff: noqa` in datasets-2.17.0 PR: - #6619 That replacement was wrong because we kept the `isort: skip` directives although they were indeed disabled by `flake8: noqa` first and by `ruff: noqa` afterwards. See for example `__init__.py` file after the linter switch: - We kept the `flake8: noqa` directive https://github.com/huggingface/datasets/blob/06ae3f678651bfbb3ca7dd3274ee2f38e0e0237e/src/datasets/__init__.py#L1 - Whereas we also kept the `isort: skip` directives (that were disabled) https://github.com/huggingface/datasets/blob/06ae3f678651bfbb3ca7dd3274ee2f38e0e0237e/src/datasets/__init__.py#L82-L84 Fix #6942.

https://api.github.com/repos/huggingface/datasets/issues/6946/timeline

https://api.github.com/repos/huggingface/datasets/issues/6945

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6945/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6945/comments

https://api.github.com/repos/huggingface/datasets/issues/6945/events

https://github.com/huggingface/datasets/pull/6945

PR_kwDODunzps5xQCCx

Update yanked version of minimum requests requirement

closed

MEMBER

Update yanked version of minimum requests requirement. Version 2.32.1 was yanked: https://pypi.org/project/requests/2.32.1/

https://api.github.com/repos/huggingface/datasets/issues/6945/timeline

https://api.github.com/repos/huggingface/datasets/issues/6944

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6944/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6944/comments

https://api.github.com/repos/huggingface/datasets/issues/6944/events

https://github.com/huggingface/datasets/pull/6944

PR_kwDODunzps5xP-KD

Set dev version

closed

MEMBER

https://api.github.com/repos/huggingface/datasets/issues/6944/timeline

https://api.github.com/repos/huggingface/datasets/issues/6943

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6943/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6943/comments

https://api.github.com/repos/huggingface/datasets/issues/6943/events

https://github.com/huggingface/datasets/pull/6943

PR_kwDODunzps5xP3jp

Release 2.19.2

closed

MEMBER

https://api.github.com/repos/huggingface/datasets/issues/6943/timeline

https://api.github.com/repos/huggingface/datasets/issues/6942

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6942/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6942/comments

https://api.github.com/repos/huggingface/datasets/issues/6942/events

https://github.com/huggingface/datasets/issues/6942

I_kwDODunzps6K2k0O

Import sorting is disabled by flake8 noqa directive after switching to ruff linter

closed

MEMBER

When we switched to `ruff` linter in PR: - #5519 import sorting was disabled in all files containing the `# flake8: noqa` directive - https://github.com/astral-sh/ruff/issues/11679 We should re-enable import sorting on those files.

https://api.github.com/repos/huggingface/datasets/issues/6942/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6941

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6941/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6941/comments

https://api.github.com/repos/huggingface/datasets/issues/6941/events

https://github.com/huggingface/datasets/issues/6941

I_kwDODunzps6K0Kd1

Supporting FFCV: Fast Forward Computer Vision

open

NONE

### Feature request Supporting FFCV, https://github.com/libffcv/ffcv ### Motivation According to the benchmark, FFCV seems to be fastest image loading method. ### Your contribution no

https://api.github.com/repos/huggingface/datasets/issues/6941/timeline

https://api.github.com/repos/huggingface/datasets/issues/6940

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6940/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6940/comments

https://api.github.com/repos/huggingface/datasets/issues/6940/events

https://github.com/huggingface/datasets/issues/6940

I_kwDODunzps6KzDGH

Enable Sharding to Equal Sized Shards

open

NONE

### Feature request Add an option when sharding a dataset to have all shards the same size. Will be good to provide both an option of duplication, and by truncation. ### Motivation Currently the behavior of sharding is "If n % i == l, then the first l shards will have length (n // i) + 1, and the remaining shards will have length (n // i).". However, when using FSDP we want the shards to have the same size. This requires the user to manually handle this situation, but it will be nice if we had an option to shard the dataset into equally sized shards. ### Your contribution For now just a PR. I can also add code that does what is needed, but probably not efficient. Shard to equal size by duplication: ``` remainder = len(dataset) % num_shards num_missing_examples = num_shards - remainder duplicated = dataset.select(list(range(num_missing_examples))) dataset = concatenate_datasets([dataset, duplicated]) shard = dataset.shard(num_shards, shard_idx) ``` Or by truncation: ``` shard = dataset.shard(num_shards, shard_idx) num_examples_per_shard = len(dataset) // num_shards shard = shard.select(list(range(num_examples_per_shard))) ```

https://api.github.com/repos/huggingface/datasets/issues/6940/timeline

https://api.github.com/repos/huggingface/datasets/issues/6939

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6939/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6939/comments

https://api.github.com/repos/huggingface/datasets/issues/6939/events

https://github.com/huggingface/datasets/issues/6939

I_kwDODunzps6Kw136

ExpectedMoreSplits error when using data_dir

closed

MEMBER

As reported by @regisss, an `ExpectedMoreSplits` error is raised when passing `data_dir`: ```python from datasets import load_dataset dataset = load_dataset( "lvwerra/stack-exchange-paired", split="train", cache_dir=None, data_dir="data/rl", ) ``` ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2609, in load_dataset builder_instance.download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1027, in download_and_prepare self._download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1140, in _download_and_prepare verify_splits(self.info.splits, split_dict) File "/usr/local/lib/python3.10/dist-packages/datasets/utils/info_utils.py", line 92, in verify_splits raise ExpectedMoreSplits(str(set(expected_splits) - set(recorded_splits))) datasets.utils.info_utils.ExpectedMoreSplits: {'test'} ```

https://api.github.com/repos/huggingface/datasets/issues/6939/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6938

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6938/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6938/comments

https://api.github.com/repos/huggingface/datasets/issues/6938/events

https://github.com/huggingface/datasets/pull/6938

PR_kwDODunzps5xHNKm

Fix expected splits when passing data_files or dir

closed

MEMBER

reported on slack: The following code snippet gives an error with v2.19 but not with v2.18: from datasets import load_dataset ``` dataset = load_dataset( "lvwerra/stack-exchange-paired", split="train", cache_dir=None, data_dir="data/rl", ) ``` and the error is: ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2609, in load_dataset builder_instance.download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1027, in download_and_prepare self._download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1140, in _download_and_prepare verify_splits(self.info.splits, split_dict) File "/usr/local/lib/python3.10/dist-packages/datasets/utils/info_utils.py", line 92, in verify_splits raise ExpectedMoreSplits(str(set(expected_splits) - set(recorded_splits))) datasets.utils.info_utils.ExpectedMoreSplits: {'test'} ```

https://api.github.com/repos/huggingface/datasets/issues/6938/timeline

https://api.github.com/repos/huggingface/datasets/issues/6937

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6937/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6937/comments

https://api.github.com/repos/huggingface/datasets/issues/6937/events

https://github.com/huggingface/datasets/issues/6937

I_kwDODunzps6KtnJD

JSON loader implicitly coerces floats to integers

open

MEMBER

The JSON loader implicitly coerces floats to integers. The column values `[0.0, 1.0, 2.0]` are coerced to `[0, 1, 2]`. See CI error in dataset-viewer: https://github.com/huggingface/dataset-viewer/actions/runs/9290164936/job/25576926446 ``` =================================== FAILURES =================================== ___________________________ test_statistics_endpoint ___________________________ normal_user_public_json_dataset = 'DVUser/tmp-dataset-17170199043860' def test_statistics_endpoint(normal_user_public_json_dataset: str) -> None: dataset = normal_user_public_json_dataset config, split = get_default_config_split() statistics_response = poll_until_ready_and_assert( relative_url=f"/statistics?dataset={dataset}&config={config}&split={split}", check_x_revision=True, dataset=dataset, ) content = statistics_response.json() assert len(content) == 3 assert sorted(content) == ["num_examples", "partial", "statistics"], statistics_response statistics = content["statistics"] num_examples = content["num_examples"] partial = content["partial"] assert isinstance(statistics, list), statistics assert len(statistics) == 6 assert num_examples == 4 assert partial is False string_label_column = statistics[0] assert "column_name" in string_label_column assert "column_statistics" in string_label_column assert "column_type" in string_label_column assert string_label_column["column_name"] == "col_1" assert string_label_column["column_type"] == "string_label" # 4 unique values -> label assert isinstance(string_label_column["column_statistics"], dict) assert string_label_column["column_statistics"] == { "nan_count": 0, "nan_proportion": 0.0, "no_label_count": 0, "no_label_proportion": 0.0, "n_unique": 4, "frequencies": { "There goes another one.": 1, "Vader turns round and round in circles as his ship spins into space.": 1, "We count thirty Rebel ships, Lord Vader.": 1, "The wingman spots the pirateship coming at him and warns the Dark Lord": 1, }, } int_column = statistics[1] assert "column_name" in int_column assert "column_statistics" in int_column assert "column_type" in int_column assert int_column["column_name"] == "col_2" assert int_column["column_type"] == "int" assert isinstance(int_column["column_statistics"], dict) assert int_column["column_statistics"] == { "histogram": {"bin_edges": [0, 1, 2, 3, 3], "hist": [1, 1, 1, 1]}, "max": 3, "mean": 1.5, "median": 1.5, "min": 0, "nan_count": 0, "nan_proportion": 0.0, "std": 1.29099, } float_column = statistics[2] assert "column_name" in float_column assert "column_statistics" in float_column assert "column_type" in float_column assert float_column["column_name"] == "col_3" > assert float_column["column_type"] == "float" E AssertionError: assert 'int' == 'float' E - float E + int tests/test_14_statistics.py:72: AssertionError =========================== short test summary info ============================ FAILED tests/test_14_statistics.py::test_statistics_endpoint - AssertionError: assert 'int' == 'float' - float + int ``` This bug was introduced after: - #6914 We have reported the issue to pandas: - https://github.com/pandas-dev/pandas/issues/58866

https://api.github.com/repos/huggingface/datasets/issues/6937/timeline

https://api.github.com/repos/huggingface/datasets/issues/6936

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6936/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6936/comments

https://api.github.com/repos/huggingface/datasets/issues/6936/events

https://github.com/huggingface/datasets/issues/6936

I_kwDODunzps6KpcWt

save_to_disk() freezes when saving on s3 bucket with multiprocessing

open

NONE

### Describe the bug I'm trying to save a `Dataset` using the `save_to_disk()` function with: - `num_proc > 1` - `dataset_path` being a s3 bucket path e.g. "s3://{bucket_name}/{dataset_folder}/" The hf progress bar shows up but the saving does not seem to start. When using one processor only (`num_proc=1`), everything works fine. When saving the dataset on local disk (as opposed to s3 bucket) with `num_proc > 1`, everything works fine. Thank you for your help! :) ### Steps to reproduce the bug I tried without any storage options: ``` from datasets import load_dataset sandbox_ds = load_dataset("openai_humaneval") sandbox_ds["test"].save_to_disk( "s3://bucket-name/test_multiprocessing_saving/", num_proc=4, ) ``` and with the specific s3fs storage options: ``` from datasets import load_dataset from s3fs import S3FileSystem def get_s3fs(): return S3FileSystem() sandbox_ds = load_dataset("openai_humaneval") sandbox_ds["test"].save_to_disk( "s3://bucket-name/test_multiprocessing_saving/", num_proc=4, storage_options=get_s3fs().storage_options, # also tried: storage_options=S3FileSystem().storage_options ) ``` I'm guessing I might use `storage_options` parameter wrongly, but I didn't find anything online that made it work. **NB**: Behavior is the same when trying to save the whole `DatasetDict`. ### Expected behavior Progress bar fills in and saving is carried out. ### Environment info `datasets==2.18.0`

https://api.github.com/repos/huggingface/datasets/issues/6936/timeline

https://api.github.com/repos/huggingface/datasets/issues/6935

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6935/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6935/comments

https://api.github.com/repos/huggingface/datasets/issues/6935/events

https://github.com/huggingface/datasets/issues/6935

I_kwDODunzps6KngX2

Support for pathlib.Path in datasets 2.19.0

open

NONE

### Describe the bug After the recent update of `datasets`, Dataset.save_to_disk does not accept a pathlib.Path anymore. It was supported in 2.18.0 and previous versions. Is this intentional? Was it supported before only because of a Python dusk-typing miracle? ### Steps to reproduce the bug ``` from datasets import Dataset import pathlib path = pathlib.Path("./my_out_path") Dataset.from_dict( {"text": ["hello world"], "label": [777], "split": ["train"]} .save_to_disk(path) ``` This results in an error when using datasets 2.19: ``` Traceback (most recent call last): File "<stdin>", line 3, in <module> File "/Users/jb/scratch/venv/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 1515, in save_to_disk fs, _ = url_to_fs(dataset_path, **(storage_options or {})) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/jb/scratch/venv/lib/python3.11/site-packages/fsspec/core.py", line 383, in url_to_fs chain = _un_chain(url, kwargs) ^^^^^^^^^^^^^^^^^^^^^^ File "/Users/jb/scratch/venv/lib/python3.11/site-packages/fsspec/core.py", line 323, in _un_chain if "::" in path ^^^^^^^^^^^^ TypeError: argument of type 'PosixPath' is not iterable ``` Converting to str works, however. ``` Dataset.from_dict( {"text": ["hello world"], "label": [777], "split": ["train"]} ).save_to_disk(str(path)) ``` ### Expected behavior My dataset gets saved to disk without an error. ### Environment info aiohttp==3.9.5 aiosignal==1.3.1 attrs==23.2.0 certifi==2024.2.2 charset-normalizer==3.3.2 datasets==2.19.0 dill==0.3.8 filelock==3.14.0 frozenlist==1.4.1 fsspec==2024.3.1 huggingface-hub==0.23.2 idna==3.7 multidict==6.0.5 multiprocess==0.70.16 numpy==1.26.4 packaging==24.0 pandas==2.2.2 pyarrow==16.1.0 pyarrow-hotfix==0.6 python-dateutil==2.9.0.post0 pytz==2024.1 PyYAML==6.0.1 requests==2.32.3 six==1.16.0 tqdm==4.66.4 typing_extensions==4.12.0 tzdata==2024.1 urllib3==2.2.1 xxhash==3.4.1 yarl==1.9.4

https://api.github.com/repos/huggingface/datasets/issues/6935/timeline

https://api.github.com/repos/huggingface/datasets/issues/6934

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6934/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6934/comments

https://api.github.com/repos/huggingface/datasets/issues/6934/events

https://github.com/huggingface/datasets/pull/6934

PR_kwDODunzps5w_laB

Revert ci user

closed

MEMBER

https://api.github.com/repos/huggingface/datasets/issues/6934/timeline

https://api.github.com/repos/huggingface/datasets/issues/6933

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6933/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6933/comments

https://api.github.com/repos/huggingface/datasets/issues/6933/events

https://github.com/huggingface/datasets/pull/6933

PR_kwDODunzps5w_cW4

update ci user

closed

MEMBER

token is ok to be public since it's only for the hub-ci

https://api.github.com/repos/huggingface/datasets/issues/6933/timeline

https://api.github.com/repos/huggingface/datasets/issues/6932

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6932/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6932/comments

https://api.github.com/repos/huggingface/datasets/issues/6932/events

https://github.com/huggingface/datasets/pull/6932

PR_kwDODunzps5w9d7w

Update dataset_dict.py

closed

CONTRIBUTOR

shape returns (number of rows, number of columns)

https://api.github.com/repos/huggingface/datasets/issues/6932/timeline

https://api.github.com/repos/huggingface/datasets/issues/6931

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6931/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6931/comments

https://api.github.com/repos/huggingface/datasets/issues/6931/events

https://github.com/huggingface/datasets/pull/6931

PR_kwDODunzps5w5I-Y

[WebDataset] Support compressed files

closed

MEMBER

https://api.github.com/repos/huggingface/datasets/issues/6931/timeline

https://api.github.com/repos/huggingface/datasets/issues/6930

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6930/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6930/comments

https://api.github.com/repos/huggingface/datasets/issues/6930/events

https://github.com/huggingface/datasets/issues/6930

I_kwDODunzps6KeZ1C

ValueError: Couldn't infer the same data file format for all splits. Got {'train': ('json', {}), 'validation': (None, {})}

open

NONE

### Describe the bug When I run the code en = load_dataset("allenai/c4", "en", streaming=True), I encounter an error: raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}") ValueError: Couldn't infer the same data file format for all splits. Got {'train': ('json', {}), 'validation': (None, {})}. However, running dataset = load_dataset('allenai/c4', streaming=True, data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation') works fine. What is the issue here? ### Steps to reproduce the bug run code： import os os.environ['HF_ENDPOINT'] = 'https://hf-mirror.com' from datasets import load_dataset en = load_dataset("allenai/c4", "en", streaming=True) ### Expected behavior Successfully loaded the dataset. ### Environment info - `datasets` version: 2.18.0 - Platform: Linux-6.5.0-28-generic-x86_64-with-glibc2.17 - Python version: 3.8.19 - `huggingface_hub` version: 0.22.2 - PyArrow version: 15.0.2 - Pandas version: 2.0.3 - `fsspec` version: 2024.2.0

https://api.github.com/repos/huggingface/datasets/issues/6930/timeline

https://api.github.com/repos/huggingface/datasets/issues/6929

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6929/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6929/comments

https://api.github.com/repos/huggingface/datasets/issues/6929/events

https://github.com/huggingface/datasets/issues/6929

I_kwDODunzps6Kddzt

Avoid downloading the whole dataset when only README.me has been touched on hub.

open

NONE

### Feature request `datasets.load_dataset()` triggers a new download of the **whole dataset** when the README.md file has been touched on huggingface hub, even if data files / parquet files are the exact same. I think the current behaviour of the load_dataset function is triggered whenever a change of the hash of latest commit on huggingface hub, but is there a clever way to only download again the dataset **if and only if** data is modified ? ### Motivation The current behaviour is a waste of network bandwidth / disk space / research time. ### Your contribution I don't have time to submit a PR, but I hope a simple solution will emerge from this issue !

https://api.github.com/repos/huggingface/datasets/issues/6929/timeline

https://api.github.com/repos/huggingface/datasets/issues/6928

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6928/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6928/comments

https://api.github.com/repos/huggingface/datasets/issues/6928/events

https://github.com/huggingface/datasets/pull/6928

PR_kwDODunzps5w1ECb

Update process.mdx: Code Listings Fixes

closed

CONTRIBUTOR

https://api.github.com/repos/huggingface/datasets/issues/6928/timeline

https://api.github.com/repos/huggingface/datasets/issues/6927

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6927/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6927/comments

https://api.github.com/repos/huggingface/datasets/issues/6927/events

https://github.com/huggingface/datasets/pull/6927

PR_kwDODunzps5w1CmF

Update process.mdx: Minor Code Listings Updates and Fixes

closed

CONTRIBUTOR

https://api.github.com/repos/huggingface/datasets/issues/6927/timeline

https://api.github.com/repos/huggingface/datasets/issues/6926

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6926/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6926/comments

https://api.github.com/repos/huggingface/datasets/issues/6926/events

https://github.com/huggingface/datasets/pull/6926

PR_kwDODunzps5w0uII

Update process.mdx: Fix code listing in Shard section

closed

CONTRIBUTOR

https://api.github.com/repos/huggingface/datasets/issues/6926/timeline

https://api.github.com/repos/huggingface/datasets/issues/6925

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6925/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6925/comments

https://api.github.com/repos/huggingface/datasets/issues/6925/events

https://github.com/huggingface/datasets/pull/6925

PR_kwDODunzps5wxDRE

Fix NonMatchingSplitsSizesError/ExpectedMoreSplits when passing data_dir/data_files in no-code Hub datasets

closed

MEMBER

Fix `NonMatchingSplitsSizesError` or `ExpectedMoreSplits` error for no-code Hub datasets if the user passes: - `data_dir` - `data_files` The proposed solution is to avoid using exported dataset info (from Parquet exports) in these cases. Additionally, also if the user passes `revision` other than "main" (so that no network requests are made). This PR fixes a bug introduced by: - #6714 Fix #6918, fix #6939.

https://api.github.com/repos/huggingface/datasets/issues/6925/timeline

https://api.github.com/repos/huggingface/datasets/issues/6924

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6924/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6924/comments

https://api.github.com/repos/huggingface/datasets/issues/6924/events

https://github.com/huggingface/datasets/issues/6924

I_kwDODunzps6KUH5H

Caching map result of DatasetDict.

open

NONE

Hi! I'm currenty using the map function to tokenize a somewhat large dataset, so I need to use the cache to save ~25 mins. Changing num_proc incduces the recomputation of the map, I'm not sure why and if this is excepted behavior? here it says, that cached files are loaded sequentially: https://github.com/huggingface/datasets/blob/bb2664cf540d5ce4b066365e7c8b26e7f1ca4743/src/datasets/arrow_dataset.py#L3005-L3006 it seems like I can pass in a fingerprint, and load it directly: https://github.com/huggingface/datasets/blob/bb2664cf540d5ce4b066365e7c8b26e7f1ca4743/src/datasets/arrow_dataset.py#L3108-L3125 **Environment Setup:** - Python 3.11.9 - datasets 2.19.1 conda-forge - Linux 6.1.83-1.el9.elrepo.x86_64 **MRE** ```python fixed raw_datasets fixed tokenize_function tokenized_datasets = raw_datasets.map( tokenize_function, batched=True, num_proc=9, remove_columns=['text'], load_from_cache_file= True, desc="Running tokenizer on dataset line_by_line", ) tokenized_datasets = raw_datasets.map( tokenize_function, batched=True, num_proc=5, remove_columns=['text'], load_from_cache_file= True, desc="Running tokenizer on dataset line_by_line", ) ```

https://api.github.com/repos/huggingface/datasets/issues/6924/timeline

https://api.github.com/repos/huggingface/datasets/issues/6923

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6923/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6923/comments

https://api.github.com/repos/huggingface/datasets/issues/6923/events

https://github.com/huggingface/datasets/issues/6923

I_kwDODunzps6KPZnI

Export Parquet Tablet Audio-Set is null bytes in Arrow

open

NONE

### Describe the bug Exporting the processed audio inside the table with the dataset.to_parquet function, the object pyarrow {bytes: null, path: "Some/Path"} At the same time, the same dataset uploaded to the hub has bit arrays   ### Steps to reproduce the bug 1.Get dataset from audio and cast it 2.Export and push dataset 3.It’s scary to be indignant at the difference in the uploaded dataset and the fact that it was saved locally ```py from datasets import Dataset, Audio df = Dataset.from_csv("./datasets.csv") df = df.cast_column("audio", Audio(16000)) df.to_parquet("./datasets.parquet") df.push_to_hub(repo_id="************", token="**********************") ``` You can use "try replicate case" for this [replicate_packet.zip](https://github.com/huggingface/datasets/files/15457114/replicate_packet.zip) ### Expected behavior Two parquet tables identical in content. It is obvious? ### Environment info Python 3.11+ (I try did it in 3.12 and got same result )

https://api.github.com/repos/huggingface/datasets/issues/6923/timeline

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

PR_kwDODunzps5wolTm

Remove torchaudio remnants from code

closed

MEMBER

Remove torchaudio remnants from code. Follow-up on: - #5573

https://api.github.com/repos/huggingface/datasets/issues/6922/timeline

https://api.github.com/repos/huggingface/datasets/issues/6921

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6921/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6921/comments

https://api.github.com/repos/huggingface/datasets/issues/6921/events

https://github.com/huggingface/datasets/pull/6921

PR_kwDODunzps5wn4Dz

Support fsspec 2024.5.0

closed

MEMBER

Support fsspec 2024.5.0.

https://api.github.com/repos/huggingface/datasets/issues/6921/timeline

https://api.github.com/repos/huggingface/datasets/issues/6920

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6920/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6920/comments

https://api.github.com/repos/huggingface/datasets/issues/6920/events

https://github.com/huggingface/datasets/pull/6920

PR_kwDODunzps5wlchX

[WebDataset] Add `.pth` support for torch tensors

closed

MEMBER

In this PR I add support for `.pth` but with `weights_only=True` to disallow the use of pickle

https://api.github.com/repos/huggingface/datasets/issues/6920/timeline

https://api.github.com/repos/huggingface/datasets/issues/6919

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6919/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6919/comments

https://api.github.com/repos/huggingface/datasets/issues/6919/events

https://github.com/huggingface/datasets/issues/6919

I_kwDODunzps6KBYqx

Invalid YAML in README.md: unknown tag !<tag:yaml.org,2002:python/tuple>

open

NONE

### Describe the bug I wrote a notebook to load an existing dataset, process it, and upload as a private dataset using `dataset.push_to_hub(...)` at the end. The push to hub is failing with: ``` ValueError: Invalid metadata in README.md. - Invalid YAML in README.md: unknown tag !<tag:yaml.org,2002:python[/tuple](http://192.168.1.128:8888/tuple)> (50:11) 47 | - 4 48 | - 4 49 | - 8 50 | - !!binary | ----------------^ 51 | TwAAAA== 52 | '1': !!python[/object/apply](http://192.168.1.128:8888/object/apply):nump ... ``` My dataset has a `train` and `validation` dataset. These are the features: ``` {'c1': Value(dtype='string', id=None), 'c2': Value(dtype='string', id=None), 'c3': [{'value': Value(dtype='string', id=None), 'start': Value(dtype='int64', id=None), 'end': Value(dtype='int64', id=None), 'label': Value(dtype='string', id=None)}], 'c4': Value(dtype='string', id=None), 'c5': Value(dtype='string', id=None), 'c6': Value(dtype='string', id=None), 'c7': Value(dtype='string', id=None), 'c8': Sequence(feature=Value(dtype='int32', id=None), length=-1, id=None), 'c9': Sequence(feature=Value(dtype='int8', id=None), length=-1, id=None), 'c10': Sequence(feature=Value(dtype='int8', id=None), length=-1, id=None), 'labels': Sequence(feature=ClassLabel(names=['O', 'B-ABC', 'I-ABC', ...], id=None), length=-1, id=None), 'c12': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)} ``` This used to work until I decided to cast the `labels` feature to a `Sequence(ClassLabel(...))` type with: ``` ds['train'] = ds['train'].cast_column("labels", Sequence(ClassLabel(names=list(labels)))) ds['validation'] = ds['validation'].cast_column("labels", Sequence(ClassLabel(names=list(labels)))) ``` ### Steps to reproduce the bug 1. Start with any token classification dataset. 2. Add a `labels` column with data such as `[0,0,0,12,13,13,13,0,0]`. 3. Cast the label column from `Sequence` to `Sequence(ClassLabel))` with: ``` labels = ['O', 'B-TEST', 'I-TEST'] ds = ds.cast_column("labels", Sequence(ClassLabel(names=labels))) ``` 4. Push to hub with `ds.push_to_hub("me/awesome-stuff-dataset")` ### Expected behavior I expected `push_to_hub` to successfully push my dataset to the hub without error. ### Environment info Python 3.11.9 datasets==2.19.1 transformers==4.41.1 PyYAML==6.0.1

https://api.github.com/repos/huggingface/datasets/issues/6919/timeline

https://api.github.com/repos/huggingface/datasets/issues/6918

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6918/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6918/comments

https://api.github.com/repos/huggingface/datasets/issues/6918/events

https://github.com/huggingface/datasets/issues/6918

I_kwDODunzps6KAQVy

NonMatchingSplitsSizesError when using data_dir

closed

NONE

### Describe the bug Loading a dataset from with a data_dir argument generates a NonMatchingSplitsSizesError if there are multiple directories in the dataset. This appears to happen because the expected split is calculated based on the data in all the directories whereas the recorded split is calculated based on the data in the directory specified using the data_dir argument. This is recent behavior. Until the past few weeks loading using the data_dir argument worked without any issue. ### Steps to reproduce the bug Simple test dataset available here: https://huggingface.co/datasets/srehaag/hf-bug-temp The dataset contains two directories "data1" and "data2", each with a file called "train.parquet" with a 2 x 5 table. from datasets import load_dataset dataset = load_dataset("srehaag/hf-bug-temp", data_dir = "data1") Generates: --------------------------------------------------------------------------- NonMatchingSplitsSizesError Traceback (most recent call last) Cell In[3], <a href='vscode-notebook-cell:?execution_count=3&line=2'>line 2</a> <a href='vscode-notebook-cell:?execution_count=3&line=1'>1</a> from datasets import load_dataset ----> <a href='vscode-notebook-cell:?execution_count=3&line=2'>2</a> dataset = load_dataset("srehaag/hf-bug-temp", data_dir = "data1") File ~/.python/current/lib/python3.10/site-packages/datasets/load.py:2609, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs) <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2606'>2606</a> return builder_instance.as_streaming_dataset(split=split) <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2608'>2608</a> # Download and prepare data -> <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2609'>2609</a> builder_instance.download_and_prepare( <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2610'>2610</a> download_config=download_config, <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2611'>2611</a> download_mode=download_mode, <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2612'>2612</a> verification_mode=verification_mode, <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2613'>2613</a> num_proc=num_proc, <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2614'>2614</a> storage_options=storage_options, <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2615'>2615</a> ) <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2617'>2617</a> # Build dataset for splits <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2618'>2618</a> keep_in_memory = ( <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2619'>2619</a> keep_in_memory if keep_in_memory is not None else is_small_dataset(builder_instance.info.dataset_size) <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2620'>2620</a> ) File ~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1027, in DatasetBuilder.download_and_prepare(self, output_dir, download_config, download_mode, verification_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, file_format, max_shard_size, num_proc, storage_options, **download_and_prepare_kwargs) <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1025'>1025</a> if num_proc is not None: <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1026'>1026</a> prepare_split_kwargs["num_proc"] = num_proc -> <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1027'>1027</a> self._download_and_prepare( <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1028'>1028</a> dl_manager=dl_manager, <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1029'>1029</a> verification_mode=verification_mode, <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1030'>1030</a> **prepare_split_kwargs, <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1031'>1031</a> **download_and_prepare_kwargs, <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1032'>1032</a> ) <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1033'>1033</a> # Sync info <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1034'>1034</a> self.info.dataset_size = sum(split.num_bytes for split in self.info.splits.values()) File ~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1140, in DatasetBuilder._download_and_prepare(self, dl_manager, verification_mode, **prepare_split_kwargs) <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1137'>1137</a> dl_manager.manage_extracted_files() <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1139'>1139</a> if verification_mode == VerificationMode.BASIC_CHECKS or verification_mode == VerificationMode.ALL_CHECKS: -> <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1140'>1140</a> verify_splits(self.info.splits, split_dict) <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1142'>1142</a> # Update the info object with the splits. <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1143'>1143</a> self.info.splits = split_dict File ~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:101, in verify_splits(expected_splits, recorded_splits) <a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:95'>95</a> bad_splits = [ <a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:96'>96</a> {"expected": expected_splits[name], "recorded": recorded_splits[name]} <a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:97'>97</a> for name in expected_splits <a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:98'>98</a> if expected_splits[name].num_examples != recorded_splits[name].num_examples <a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:99'>99</a> ] <a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:100'>100</a> if len(bad_splits) > 0: --> <a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:101'>101</a> raise NonMatchingSplitsSizesError(str(bad_splits)) <a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:102'>102</a> logger.info("All the splits matched successfully.") NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=212, num_examples=10, shard_lengths=None, dataset_name=None), 'recorded': SplitInfo(name='train', num_bytes=106, num_examples=5, shard_lengths=None, dataset_name='hf-bug-temp')}] __________ By contrast, this loads the data from both data1/train.parquet and data2/train.parquet without any error message: from datasets import load_dataset dataset = load_dataset("srehaag/hf-bug-temp") ### Expected behavior Should load the 5 x 2 table from data1/train.parquet without error message. ### Environment info Used Codespaces to simplify environment (see details below), but bug is present across various configurations. - `datasets` version: 2.19.1 - Platform: Linux-6.5.0-1021-azure-x86_64-with-glibc2.31 - Python version: 3.10.13 - `huggingface_hub` version: 0.23.1 - PyArrow version: 16.1.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.3.1

https://api.github.com/repos/huggingface/datasets/issues/6918/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/6917

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/6917/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/6917/comments

https://api.github.com/repos/huggingface/datasets/issues/6917/events

https://github.com/huggingface/datasets/issues/6917

I_kwDODunzps6J90UP

WinError 32 The process cannot access the file during load_dataset

open

NONE