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[] | null | 10 | 2024-06-19T13:22:28 | 2024-08-20T08:23:57 | 2024-06-25T05:40:51 |
NONE
| null | null | null |
### Describe the bug
I have been struggling with this for two days, any help would be appreciated. Python 3.10
```
from setfit import SetFitModel
from huggingface_hub import login
access_token_read = "cccxxxccc"
# Authenticate with the Hugging Face Hub
login(token=access_token_read)
# Load the models from the Hugging Face Hub
trainer_relv = SetFitModel.from_pretrained("snowdere/trainer_relevance")
trainer_trust = SetFitModel.from_pretrained("snowdere/trainer_trust")
trainer_sent = SetFitModel.from_pretrained("snowdere/trainer_sent")
trainer_topic = SetFitModel.from_pretrained("snowdere/trainer_topic")
```
```
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[6], line 1
----> 1 from setfit import SetFitModel
2 from huggingface_hub import login
4 access_token_read = "ccsddsds"
File /opt/conda/lib/python3.10/site-packages/setfit/__init__.py:7
4 import os
5 import warnings
----> 7 from .data import get_templated_dataset, sample_dataset
8 from .model_card import SetFitModelCardData
9 from .modeling import SetFitHead, SetFitModel
File /opt/conda/lib/python3.10/site-packages/setfit/data.py:5
3 import pandas as pd
4 import torch
----> 5 from datasets import Dataset, DatasetDict, load_dataset
6 from torch.utils.data import Dataset as TorchDataset
8 from . import logging
File /opt/conda/lib/python3.10/site-packages/datasets/__init__.py:18
1 # ruff: noqa
2 # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
3 #
(...)
13 # See the License for the specific language governing permissions and
14 # limitations under the License.
16 __version__ = "2.19.0"
---> 18 from .arrow_dataset import Dataset
19 from .arrow_reader import ReadInstruction
20 from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:76
73 from tqdm.contrib.concurrent import thread_map
75 from . import config
---> 76 from .arrow_reader import ArrowReader
77 from .arrow_writer import ArrowWriter, OptimizedTypedSequence
78 from .data_files import sanitize_patterns
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_reader.py:29
26 from typing import TYPE_CHECKING, List, Optional, Union
28 import pyarrow as pa
---> 29 import pyarrow.parquet as pq
30 from tqdm.contrib.concurrent import thread_map
32 from .download.download_config import DownloadConfig
File /opt/conda/lib/python3.10/site-packages/pyarrow/parquet/__init__.py:20
1 # Licensed to the Apache Software Foundation (ASF) under one
2 # or more contributor license agreements. See the NOTICE file
3 # distributed with this work for additional information
(...)
17
18 # flake8: noqa
---> 20 from .core import *
File /opt/conda/lib/python3.10/site-packages/pyarrow/parquet/core.py:33
30 import pyarrow as pa
32 try:
---> 33 import pyarrow._parquet as _parquet
34 except ImportError as exc:
35 raise ImportError(
36 "The pyarrow installation is not built with support "
37 f"for the Parquet file format ({str(exc)})"
38 ) from None
File /opt/conda/lib/python3.10/site-packages/pyarrow/_parquet.pyx:1, in init pyarrow._parquet()
AttributeError: module 'pyarrow.lib' has no attribute 'ListViewType'
```
setfit: 1.0.3
transformers: 4.41.2
lingua-language-detector: 2.0.2
polars: 0.20.31
lightning: None
google-cloud-bigquery: 3.24.0
shapely: 2.0.4
pyarrow: 16.0.0
### Steps to reproduce the bug
I have tried all version combinations for Dataset and Pyarrow, the all have the same error since a few days ago. This is accross multiple scripts I have.
### Expected behavior
Just ron normally.
### Environment info
3.10
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I_kwDODunzps6My3NC
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Convert polars DataFrame back to datasets
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NONE
| null | null | null |
### Feature request
This returns error.
```python
from datasets import Dataset
dsdf = Dataset.from_dict({"x": [[1, 2], [3, 4, 5]], "y": ["a", "b"]})
Dataset.from_polars(dsdf.to_polars())
```
ValueError: Arrow type large_list<item: int64> does not have a datasets dtype equivalent.
### Motivation
When datasets contain Sequence data type, it will be converted to Arrow type large_list. However, the reverse (from large_list to Sequence) does not work.
### Your contribution
No
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Remove metrics
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Remove all metrics, as part of the 3.0 release.
Note they are deprecated since 2.5.0 version.
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I_kwDODunzps6MxBgd
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cannot split dataset when using load_dataset
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NONE
| null | null | null |
### 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
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Update docs on trust_remote_code defaults to False
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Update docs on trust_remote_code defaults to False.
The docs needed to be updated due to this PR:
- #6954
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Support NumPy 2.0
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[] | null | 0 | 2024-06-18T23:30:22 | 2024-07-12T12:04:54 | 2024-07-12T12:04:53 |
CONTRIBUTOR
| null | null | null |
### 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
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How can I load partial parquet files only?
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[] | null | 12 | 2024-06-18T15:44:16 | 2024-06-21T17:09:32 | 2024-06-21T13:32:50 |
NONE
| null | null | null |
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**
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Fix regression for pandas < 2.0.0 in JSON loader
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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
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I_kwDODunzps6Mn_xF
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load json file error with v2.20.0
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NONE
| null | null | null |
### 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
```
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| 2,357,107,203 |
PR_kwDODunzps5yrmNP
| 6,976 |
Ensure compatibility with numpy 2.0.0
|
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CONTRIBUTOR
| null | false |
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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)
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PR_kwDODunzps5yrPct
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Set temporary numpy upper version < 2.0.0 to fix CI
|
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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.
```
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I_kwDODunzps6MZley
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IndexError during training with Squad dataset and T5-small model
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NONE
| null | null | null |
### 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
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PR_kwDODunzps5yfa_e
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Fix webdataset pickling
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...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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PR_kwDODunzps5yZoc3
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packaging: Remove useless dependencies
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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`.
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Set dev version
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PR_kwDODunzps5yX_nC
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Release: 2.20.0
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Use `HF_HUB_OFFLINE` instead of `HF_DATASETS_OFFLINE`
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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.
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Remove underlines between badges
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[] | null | 1 | 2024-06-12T14:32:11 | 2024-06-19T14:16:21 | 2024-06-19T14:10:11 |
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## 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">
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https://api.github.com/repos/huggingface/datasets/issues/6965
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PR_kwDODunzps5yOyNG
| 6,965 |
Improve skip take shuffling and distributed
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[] | null | 2 | 2024-06-12T12:30:27 | 2024-06-24T15:22:21 | 2024-06-24T15:16:16 |
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set the right behavior of skip/take depending on whether it's called after or before shuffle/split_by_node
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PR_kwDODunzps5yCNGa
| 6,964 |
Fix resuming arrow format
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following https://github.com/huggingface/datasets/pull/6658
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| null | null | true | 3 days, 16:18:04 |
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| 2,344,269,477 |
PR_kwDODunzps5x_yu-
| 6,963 |
[Streaming] retry on requests errors
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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.
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PR_kwDODunzps5x8yHt
| 6,962 |
fix(ci): remove unnecessary permissions
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### What does this PR do?
Remove unnecessary permissions granted to the actions workflow.
Sorry for the mishap.
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feat(ci): add trufflehog secrets detection
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### What does this PR do?
Adding a GH action to scan for leaked secrets on each commit.
|
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PR_kwDODunzps5xyVt6
| 6,959 |
Better error handling in `dataset_module_factory`
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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
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I_kwDODunzps6LUw8f
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My Private Dataset doesn't exist on the Hub or cannot be accessed
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[] | null | 8 | 2024-06-06T06:52:19 | 2024-07-01T11:27:46 | 2024-07-01T11:27:46 |
NONE
| null | null | null |
### 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
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PR_kwDODunzps5xiTwJ
| 6,957 |
Fix typos in docs
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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
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PR_kwDODunzps5xcwXz
| 6,956 |
update docs on N-dim arrays
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Fix small typo
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| 2,333,530,558 |
PR_kwDODunzps5xbWtU
| 6,954 |
Remove default `trust_remote_code=True`
|
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[] | null | 6 | 2024-06-04T13:22:56 | 2024-06-17T16:32:24 | 2024-06-07T12:20:29 |
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TODO:
- [x] fix tests
|
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| 2,333,366,120 |
I_kwDODunzps6LFFdo
| 6,953 |
Remove canonical datasets from docs
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[] | null | 1 | 2024-06-04T12:09:03 | 2024-07-01T11:31:25 | 2024-07-01T11:31:25 |
MEMBER
| null | null | null |
Remove canonical datasets from docs, now that we no longer have canonical datasets.
|
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PR_kwDODunzps5xaosH
| 6,952 |
Move info_utils errors to exceptions module
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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).
|
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| 2,333,231,042 |
I_kwDODunzps6LEkfC
| 6,951 |
load_dataset() should load all subsets, if no specific subset is specified
|
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[] | null | 4 | 2024-06-04T11:02:33 | 2024-07-01T11:33:10 | 2024-07-01T11:33:10 |
NONE
| null | null | null |
### 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.
|
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| 2,333,005,974 |
I_kwDODunzps6LDtiW
| 6,950 |
`Dataset.with_format` behaves inconsistently with documentation
|
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[] | null | 2 | 2024-06-04T09:18:32 | 2024-06-25T08:05:49 | 2024-06-25T08:05:49 |
NONE
| null | null | null |
### 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
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I_kwDODunzps6LBKG9
| 6,949 |
load_dataset error
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[] | null | 2 | 2024-06-04T01:24:45 | 2024-07-01T11:33:46 | 2024-07-01T11:33:46 |
NONE
| null | null | null |
### 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
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I_kwDODunzps6K8fpH
| 6,947 |
FileNotFoundError：error when loading C4 dataset
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[] | null | 15 | 2024-06-03T13:06:33 | 2024-06-25T06:21:28 | 2024-06-25T06:21:28 |
NONE
| null | null | null |
### 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
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| 2,330,276,848 |
PR_kwDODunzps5xQNao
| 6,946 |
Re-enable import sorting disabled by flake8:noqa directive when using ruff linter
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MEMBER
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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.
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Update yanked version of minimum requests requirement
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Update yanked version of minimum requests requirement.
Version 2.32.1 was yanked: https://pypi.org/project/requests/2.32.1/
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PR_kwDODunzps5xP-KD
| 6,944 |
Set dev version
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PR_kwDODunzps5xP3jp
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Release 2.19.2
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Import sorting is disabled by flake8 noqa directive after switching to ruff linter
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MEMBER
| null | null | null |
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.
|
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I_kwDODunzps6Kw136
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ExpectedMoreSplits error when using data_dir
|
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MEMBER
| null | null | null |
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'}
```
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| 2,327,568,281 |
PR_kwDODunzps5xHNKm
| 6,938 |
Fix expected splits when passing data_files or dir
|
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[] | null | 2 | 2024-05-31T11:04:22 | 2024-05-31T15:28:03 | 2024-05-31T15:28:02 |
MEMBER
| null | false |
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|
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'}
```
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| 2,325,341,717 |
PR_kwDODunzps5w_laB
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Revert ci user
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https://api.github.com/repos/huggingface/datasets/issues/6933
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PR_kwDODunzps5w_cW4
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token is ok to be public since it's only for the hub-ci
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PR_kwDODunzps5w9d7w
| 6,932 |
Update dataset_dict.py
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CONTRIBUTOR
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shape returns (number of rows, number of columns)
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PR_kwDODunzps5w5I-Y
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[WebDataset] Support compressed files
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PR_kwDODunzps5w1ECb
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Update process.mdx: Code Listings Fixes
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Update process.mdx: Minor Code Listings Updates and Fixes
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PR_kwDODunzps5w0uII
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Update process.mdx: Fix code listing in Shard section
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PR_kwDODunzps5wxDRE
| 6,925 |
Fix NonMatchingSplitsSizesError/ExpectedMoreSplits when passing data_dir/data_files in no-code Hub datasets
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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.
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PR_kwDODunzps5wolTm
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Remove torchaudio remnants from code
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Remove torchaudio remnants from code.
Follow-up on:
- #5573
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PR_kwDODunzps5wn4Dz
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Support fsspec 2024.5.0
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Support fsspec 2024.5.0.
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PR_kwDODunzps5wlchX
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[WebDataset] Add `.pth` support for torch tensors
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In this PR I add support for `.pth` but with `weights_only=True` to disallow the use of pickle
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NONE
| null | null | null |
### 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
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I_kwDODunzps6JyV6s
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```push_to_hub()``` - Prevent Automatic Generation of Splits
|
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[] | null | 0 | 2024-05-22T23:52:15 | 2024-05-23T00:07:53 | 2024-05-23T00:07:53 |
NONE
| null | null | null |
### Describe the bug
I currently have a dataset which has not been splited. When pushing the dataset to my hugging face dataset repository, it is split into a testing and training set. How can I prevent the split from happening?
### Steps to reproduce the bug
1. Have a unsplit dataset
```python
Dataset({ features: ['input', 'output', 'Attack', '__index_level_0__'], num_rows: 944685 })
```
2. Push it to huggingface
```python
dataset.push_to_hub(dataset_name)
```
3. On the hugging face dataset repo, the dataset then appears to be splited:
4. Indeed, when loading the dataset from this repo, the dataset is split in two testing and training set.
```python
from datasets import load_dataset, Dataset
dataset = load_dataset("Jetlime/NF-CSE-CIC-IDS2018-v2", streaming=True)
dataset
```
output:
```
IterableDatasetDict({
train: IterableDataset({
features: ['input', 'output', 'Attack', '__index_level_0__'],
n_shards: 2
})
test: IterableDataset({
features: ['input', 'output', 'Attack', '__index_level_0__'],
n_shards: 1
})
```
### Expected behavior
The dataset shall not be splited, as not requested.
### Environment info
- `datasets` version: 2.19.1
- Platform: Linux-6.2.0-35-generic-x86_64-with-glibc2.35
- Python version: 3.10.12
- `huggingface_hub` version: 0.23.0
- PyArrow version: 15.0.2
- Pandas version: 2.2.2
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Validate config name and data_files in packaged modules
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MEMBER
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Validate the config attributes `name` and `data_files` in packaged modules by making the derived classes call their parent `__post_init__` method.
Note that their parent `BuilderConfig` validates its attributes `name` and `data_files` in its `__post_init__` method: https://github.com/huggingface/datasets/blob/60d21efbc01e15d0b596ac1072750cbecd91548a/src/datasets/builder.py#L128-L137
This PR makes the derived config classes call their parent `__post_init__` method to validate their `name` and `data_files` attributes.
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Preserve JSON column order and support list of strings field
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Preserve column order when loading from a JSON file with a list of dict (or with a field containing a list of dicts).
Additionally, support JSON file with a list of strings field.
Fix #6913.
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As reported by @meg-huggingface, the order of the JSON object keys is not preserved while loading a dataset from a JSON file with a list of objects.
For example, when loading a JSON files with a list of objects, each with the following ordered keys:
- [ID, Language, Topic],
the resulting dataset may have columns:
- [ID, Topic, Language], or
- [Topic, Language, ID], or
- [Topic, ID, Language],...
This issue is caused by the use of a Python set (which does not preserve the order):
https://github.com/huggingface/datasets/blob/60d21efbc01e15d0b596ac1072750cbecd91548a/src/datasets/packaged_modules/json/json.py#L168
introduced in
- #5772
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Remove dead code for non-dict data_files from packaged modules
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Remove dead code for non-dict data_files from packaged modules.
Since the merge of this PR:
- #2986
the builders' variable self.config.data_files is always a dict, which makes the condition on (str, list, tuple) dead code.
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Fix wrong type hints in data_files
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Fix wrong type hints in data_files introduced in:
- #6493
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Update requests >=2.32.1 to fix vulnerability
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Update requests >=2.32.1 to fix vulnerability.
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I_kwDODunzps6JYt6k
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Fail to load "stas/c4-en-10k" dataset since 2.16 version
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NONE
| null | null | null |
### 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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| 2,303,679,119 |
I_kwDODunzps6JT1qP
| 6,906 |
irc_disentangle - Issue with splitting data
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NONE
| null | null | null |
### Describe the bug
I am trying to access your database through python using "datasets.load_dataset("irc_disentangle")" and I am getting this error message:
ValueError: Instruction "train" corresponds to no data!
### Steps to reproduce the bug
import datasets
ds = datasets.load_dataset('irc_disentangle')
ds
### Expected behavior
The data is supposed to load into ds and be accessable as such:
ds['train'][1050], ds['train'][1055]
### Environment info
I tired Python 3.12 and 3.10
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| 6,904 |
Fix decoding multi part extension
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e.g. a field named `url.txt` should be a treated as text
I also included a small fix to support .npz correctly
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PR_kwDODunzps5vqLIv
| 6,902 |
Make CLI convert_to_parquet not raise error if no rights to create script branch
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Make CLI convert_to_parquet not raise error if no rights to create "script" branch.
Not that before this PR, the error was not critical because it was raised at the end of the script, once all the rest of the steps were already performed.
Fix #6901.
Bug introduced in datasets-2.19.0 by:
- #6809
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HTTPError 403 raised by CLI convert_to_parquet when creating script branch on 3rd party repos
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MEMBER
| null | null | null |
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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I_kwDODunzps6JACuF
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[WebDataset] KeyError with user-defined `Features` when a field is missing in an example
|
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[] | null | 5 | 2024-05-15T17:48:34 | 2024-06-28T09:30:13 | 2024-06-28T09:30:13 |
MEMBER
| null | null | null |
reported at https://huggingface.co/datasets/ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions/discussions/1
```
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 109, in _generate_examples
example[field_name] = {"path": example["__key__"] + "." + field_name, "bytes": example[field_name]}
```
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PR_kwDODunzps5vWJ9v
| 6,898 |
Fix YAML error in README files appearing on GitHub
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[] | null | 3 | 2024-05-14T05:21:57 | 2024-05-16T14:36:57 | 2024-05-16T14:28:16 |
MEMBER
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|
Fix YAML error in README files appearing on GitHub.
See error message:
Fix #6897.
|
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I_kwDODunzps6IsvAT
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datasets template guide :: issue in documentation YAML
|
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] | null | 2 | 2024-05-13T17:33:59 | 2024-05-16T14:28:17 | 2024-05-16T14:28:17 |
NONE
| null | null | null |
### Describe the bug
There is a YAML error at the top of the page, and I don't think it's supposed to be there
### Steps to reproduce the bug
1. Browse to [this tutorial document](https://github.com/huggingface/datasets/blob/main/templates/README_guide.md)
2. Observe a big red error at the top
3. The rest of the document remains functional
### Expected behavior
I think the YAML block should be displayed or ignored.
### Environment info
N/A
|
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Document that to_json defaults to JSON Lines
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Document that `Dataset.to_json` defaults to JSON Lines, by adding explanation in the corresponding docstring.
Fix #6894.
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Better document defaults of to_json
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Better document defaults of `to_json`: the default format is [JSON-Lines](https://jsonlines.org/).
Related to:
- #6891
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Close gzipped files properly
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close https://github.com/huggingface/datasets/issues/6877
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Add support for categorical/dictionary types
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Arrow has a very useful dictionary/categorical type (https://arrow.apache.org/docs/python/generated/pyarrow.dictionary.html). This data type has significant speed, memory and disk benefits over pa.string() when there are only a few unique text strings in a column.
Unfortunately, huggingface datasets currently does not support this type. So huggingface datasets cannot natively read many parquet files that use this datatype .This PR adds support for Huggingface Datasets to read categorical/dictionary data.
Note: This PR functions by simply converting those dictionary/categorical types to strings. This means that huggingface datasets cannot take advantage of the compute benefits of categoricals, but it significantly simplifies logic. At this time, I do not think it makes sense to optimize categorical support within huggingface datasets and that we should only try to optimize later, if necessary.
Closes #5706
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Unable to load JSON saved using `to_json`
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NONE
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### 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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PR_kwDODunzps5u_hW-
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fix bug #6877
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fix bug #6877 due to maybe f becomes invaild after yield process
the results are below:
Resolving data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 828/828 [00:01<00:00, 420.41it/s]
Resolving data files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 26148.48it/s]
Resolving data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 409731.44it/s]
Resolving data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 289720.84it/s]
Resolving data files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 26663.42it/s]
Resolving data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 434056.21it/s]
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 13222.33files/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 828/828 [00:04<00:00, 180.67files/s]
Downloading data: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 828/828 [01:35<00:00, 8.70files/s]
Generating train split: 1571592 examples [00:08, 176736.09 examples/s]
Generating test split: 85533 examples [00:01, 48224.56 examples/s]
Generating validation split: 86246 examples [00:01, 50164.16 examples/s]
Fix https://github.com/huggingface/datasets/issues/6877.
CC: @natolambert
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Support WebDataset containing file basenames with dots
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Support WebDataset containing file basenames with dots.
Fix #6880.
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Support jax 0.4.27 in CI tests
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Support jax 0.4.27 in CI tests by using jax Array `devices` method instead of `device` (which no longer exists).
Fix #6884.
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CI is broken after jax-0.4.27 release: AttributeError: 'jaxlib.xla_extension.DeviceList' object has no attribute 'device'
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After jax-0.4.27 release (https://github.com/google/jax/releases/tag/jax-v0.4.27), our CI is broken with the error:
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AttributeError: 'jaxlib.xla_extension.DeviceList' object has no attribute 'device'. Did you mean: 'devices'?
```
See: https://github.com/huggingface/datasets/actions/runs/8997488610/job/24715736153
```Python traceback
___________________ FormatterTest.test_jax_formatter_device ____________________
[gw1] linux -- Python 3.10.14 /opt/hostedtoolcache/Python/3.10.14/x64/bin/python
self = <tests.test_formatting.FormatterTest testMethod=test_jax_formatter_device>
@require_jax
def test_jax_formatter_device(self):
import jax
from datasets.formatting import JaxFormatter
pa_table = self._create_dummy_table()
device = jax.devices()[0]
formatter = JaxFormatter(device=str(device))
row = formatter.format_row(pa_table)
> assert row["a"].device() == device
E AttributeError: 'jaxlib.xla_extension.DeviceList' object has no attribute 'device'. Did you mean: 'devices'?
tests/test_formatting.py:630: AttributeError
```
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Require Pillow >= 9.4.0 to avoid AttributeError when loading image dataset
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Require Pillow >= 9.4.0 to avoid AttributeError when loading image dataset.
The `PIL.Image.ExifTags` that we use in our code was implemented in Pillow-9.4.0: https://github.com/python-pillow/Pillow/commit/24a5405a9f7ea22f28f9c98b3e407292ea5ee1d3
The bug #6881 was introduced in datasets-2.19.0 by this PR:
- #6739
Fix #6881.
|
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I_kwDODunzps6ILzCZ
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AttributeError: module 'PIL.Image' has no attribute 'ExifTags'
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MEMBER
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When trying to load an image dataset in an old Python environment (with Pillow-8.4.0), an error is raised:
```Python traceback
AttributeError: module 'PIL.Image' has no attribute 'ExifTags'
```
The error traceback:
```Python traceback
~/huggingface/datasets/src/datasets/iterable_dataset.py in __iter__(self)
1391 # `IterableDataset` automatically fills missing columns with None.
1392 # This is done with `_apply_feature_types_on_example`.
-> 1393 example = _apply_feature_types_on_example(
1394 example, self.features, token_per_repo_id=self._token_per_repo_id
1395 )
~/huggingface/datasets/src/datasets/iterable_dataset.py in _apply_feature_types_on_example(example, features, token_per_repo_id)
1080 encoded_example = features.encode_example(example)
1081 # Decode example for Audio feature, e.g.
-> 1082 decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
1083 return decoded_example
1084
~/huggingface/datasets/src/datasets/features/features.py in decode_example(self, example, token_per_repo_id)
1974
-> 1975 return {
1976 column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
1977 if self._column_requires_decoding[column_name]
~/huggingface/datasets/src/datasets/features/features.py in <dictcomp>(.0)
1974
1975 return {
-> 1976 column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
1977 if self._column_requires_decoding[column_name]
1978 else value
~/huggingface/datasets/src/datasets/features/features.py in decode_nested_example(schema, obj, token_per_repo_id)
1339 # we pass the token to read and decode files from private repositories in streaming mode
1340 if obj is not None and schema.decode:
-> 1341 return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
1342 return obj
1343
~/huggingface/datasets/src/datasets/features/image.py in decode_example(self, value, token_per_repo_id)
187 image = PIL.Image.open(BytesIO(bytes_))
188 image.load() # to avoid "Too many open files" errors
--> 189 if image.getexif().get(PIL.Image.ExifTags.Base.Orientation) is not None:
190 image = PIL.ImageOps.exif_transpose(image)
191 if self.mode and self.mode != image.mode:
~/huggingface/datasets/venv/lib/python3.9/site-packages/PIL/Image.py in __getattr__(name)
75 )
76 return categories[name]
---> 77 raise AttributeError(f"module '{__name__}' has no attribute '{name}'")
78
79
AttributeError: module 'PIL.Image' has no attribute 'ExifTags'
```
### Environment info
Since datasets 2.19.0
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Create function to convert to parquet
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Analogously with `delete_from_hub`, this PR:
- creates the Python function `convert_to_parquet`
- makes the corresponding CLI command use that function.
This way, the functionality can be used both from a terminal and from a Python console.
This PR also implements a test for convert_to_parquet function.
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OSError: [Errno 24] Too many open files
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NONE
| null | null | null |
### Describe the bug
I am trying to load the 'default' subset of the following dataset which contains lots of files (828 per split): [https://huggingface.co/datasets/mteb/biblenlp-corpus-mmteb](https://huggingface.co/datasets/mteb/biblenlp-corpus-mmteb)
When trying to load it using the `load_dataset` function I get the following error
```python
>>> from datasets import load_dataset
>>> d = load_dataset('mteb/biblenlp-corpus-mmteb')
Downloading readme: 100%|████████████████████████████████████████████████████████████████████████| 201k/201k [00:00<00:00, 1.07MB/s]
Resolving data files: 100%|█████████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 1069.15it/s]
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Generating train split: 1571592 examples [00:03, 461438.97 examples/s]
Generating test split: 11163 examples [00:00, 118190.72 examples/s]
Traceback (most recent call last):
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1995, in _prepare_split_single
for _, table in generator:
File ".env/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 99, in _generate_tables
with open(file, "rb") as f:
^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/datasets/streaming.py", line 75, in wrapper
return function(*args, download_config=download_config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 1224, in xopen
file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/core.py", line 135, in open
return self.__enter__()
^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/core.py", line 103, in __enter__
f = self.fs.open(self.path, mode=mode)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/spec.py", line 1293, in open
f = self._open(
^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/datasets/filesystems/compression.py", line 81, in _open
return self.file.open()
^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/core.py", line 135, in open
return self.__enter__()
^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/core.py", line 103, in __enter__
f = self.fs.open(self.path, mode=mode)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/spec.py", line 1293, in open
f = self._open(
^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/implementations/local.py", line 197, in _open
return LocalFileOpener(path, mode, fs=self, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/implementations/local.py", line 322, in __init__
self._open()
File ".env/lib/python3.12/site-packages/fsspec/implementations/local.py", line 327, in _open
self.f = open(self.path, mode=self.mode)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
OSError: [Errno 24] Too many open files: '.cache/huggingface/datasets/downloads/3a347186abfc0f9c924dde0221d246db758c7232c0101523f04a87c17d696618'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 981, in incomplete_dir
yield tmp_dir
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 2038, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File ".env/lib/python3.12/site-packages/datasets/load.py", line 2609, in load_dataset
builder_instance.download_and_prepare(
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1007, in download_and_prepare
with incomplete_dir(self._output_dir) as tmp_output_dir:
File "/usr/lib/python3.12/contextlib.py", line 158, in __exit__
self.gen.throw(value)
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 988, in incomplete_dir
shutil.rmtree(tmp_dir)
File "/usr/lib/python3.12/shutil.py", line 785, in rmtree
_rmtree_safe_fd(fd, path, onexc)
File "/usr/lib/python3.12/shutil.py", line 661, in _rmtree_safe_fd
onexc(os.scandir, path, err)
File "/usr/lib/python3.12/shutil.py", line 657, in _rmtree_safe_fd
with os.scandir(topfd) as scandir_it:
^^^^^^^^^^^^^^^^^
OSError: [Errno 24] Too many open files: '.cache/huggingface/datasets/mteb___biblenlp-corpus-mmteb/default/0.0.0/3912ed967b0834547f35b2da9470c4976b357c9a.incomplete'
```
I looked for the maximum number of open files on my machine (Ubuntu 24.04) and it seems to be 1024, but even when I try to load a single split (`load_dataset('mteb/biblenlp-corpus-mmteb', split='train')`) I get the same error
### Steps to reproduce the bug
```python
from datasets import load_dataset
d = load_dataset('mteb/biblenlp-corpus-mmteb')
```
### Expected behavior
Load the dataset without error
### Environment info
- `datasets` version: 2.19.0
- Platform: Linux-6.8.0-31-generic-x86_64-with-glibc2.39
- Python version: 3.12.3
- `huggingface_hub` version: 0.23.0
- PyArrow version: 16.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.3.1
|
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completed
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| 2,281,450,743 |
PR_kwDODunzps5uqs46
| 6,876 |
Unpin hfh
|
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Needed to use those in dataset-viewer:
- dev version of hfh https://github.com/huggingface/dataset-viewer/pull/2781: don't span the hub with /paths-info requests
- dev version of datasets at https://github.com/huggingface/datasets/pull/6875: don't write too big logs in the viewer
close https://github.com/huggingface/datasets/issues/6863
|
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| 2,281,428,826 |
PR_kwDODunzps5uqoJ_
| 6,875 |
Shorten long logs
|
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MEMBER
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Some datasets may have unexpectedly long features/types (e.g. if the files are not formatted correctly).
In that case we should still be able to log something readable
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| 2,280,717,233 |
PR_kwDODunzps5uoOk-
| 6,874 |
Use pandas ujson in JSON loader to improve performance
|
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|
Use pandas ujson in JSON loader to improve performance.
Note that `datasets` has `pandas` as required dependency. And `pandas` includes `ujson` in `pd.io.json.ujson_loads`.
Fix #6867.
CC: @natolambert
|
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| 2,280,463,182 |
PR_kwDODunzps5unXnq
| 6,873 |
Set dev version
|
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PR_kwDODunzps5unSPA
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Release 2.19.1
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PR_kwDODunzps5umJS6
| 6,871 |
Fix download for dict of dicts of URLs
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Fix download for a dict of dicts of URLs when batched (default), introduced by:
- #6794
This PR also implements regression tests.
Fix #6869, fix #6850.
|
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PR_kwDODunzps5umFOL
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Update tqdm >= 4.66.3 to fix vulnerability
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Update tqdm >= 4.66.3 to fix vulnerability,
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I_kwDODunzps6H5sap
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Download is broken for dict of dicts: FileNotFoundError
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It seems there is a bug when downloading a dict of dicts of URLs introduced by:
- #6794
## Steps to reproduce the bug:
```python
from datasets import DownloadManager
dl_manager = DownloadManager()
paths = dl_manager.download({"train": {"frr": "hf://datasets/wikimedia/wikipedia/20231101.frr/train-00000-of-00001.parquet"}})
```
Stack trace:
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
<ipython-input-7-0e0d76d25b09> in <module>
----> 1 paths = dl_manager.download({"train": {"frr": "hf://datasets/wikimedia/wikipedia/20231101.frr/train-00000-of-00001.parquet"}})
.../huggingface/datasets/src/datasets/download/download_manager.py in download(self, url_or_urls)
255 start_time = datetime.now()
256 with stack_multiprocessing_download_progress_bars():
--> 257 downloaded_path_or_paths = map_nested(
258 download_func,
259 url_or_urls,
.../huggingface/datasets/src/datasets/utils/py_utils.py 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)
506 batch_size = max(len(iterable) // num_proc + int(len(iterable) % num_proc > 0), 1)
507 iterable = list(iter_batched(iterable, batch_size))
--> 508 mapped = [
509 _single_map_nested((function, obj, batched, batch_size, types, None, True, None))
510 for obj in hf_tqdm(iterable, disable=disable_tqdm, desc=desc)
.../huggingface/datasets/src/datasets/utils/py_utils.py in <listcomp>(.0)
507 iterable = list(iter_batched(iterable, batch_size))
508 mapped = [
--> 509 _single_map_nested((function, obj, batched, batch_size, types, None, True, None))
510 for obj in hf_tqdm(iterable, disable=disable_tqdm, desc=desc)
511 ]
.../huggingface/datasets/src/datasets/utils/py_utils.py in _single_map_nested(args)
375 and all(not isinstance(v, types) for v in data_struct)
376 ):
--> 377 return [mapped_item for batch in iter_batched(data_struct, batch_size) for mapped_item in function(batch)]
378
379 # Reduce logging to keep things readable in multiprocessing with tqdm
.../huggingface/datasets/src/datasets/utils/py_utils.py in <listcomp>(.0)
375 and all(not isinstance(v, types) for v in data_struct)
376 ):
--> 377 return [mapped_item for batch in iter_batched(data_struct, batch_size) for mapped_item in function(batch)]
378
379 # Reduce logging to keep things readable in multiprocessing with tqdm
.../huggingface/datasets/src/datasets/download/download_manager.py in _download_batched(self, url_or_filenames, download_config)
311 )
312 else:
--> 313 return [
314 self._download_single(url_or_filename, download_config=download_config)
315 for url_or_filename in url_or_filenames
.../huggingface/datasets/src/datasets/download/download_manager.py in <listcomp>(.0)
312 else:
313 return [
--> 314 self._download_single(url_or_filename, download_config=download_config)
315 for url_or_filename in url_or_filenames
316 ]
.../huggingface/datasets/src/datasets/download/download_manager.py in _download_single(self, url_or_filename, download_config)
321 # append the relative path to the base_path
322 url_or_filename = url_or_path_join(self._base_path, url_or_filename)
--> 323 out = cached_path(url_or_filename, download_config=download_config)
324 out = tracked_str(out)
325 out.set_origin(url_or_filename)
.../huggingface/datasets/src/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
220 elif is_local_path(url_or_filename):
221 # File, but it doesn't exist.
--> 222 raise FileNotFoundError(f"Local file {url_or_filename} doesn't exist")
223 else:
224 # Something unknown
FileNotFoundError: Local file .../huggingface/datasets/{'frr': 'hf:/datasets/wikimedia/wikipedia/20231101.frr/train-00000-of-00001.parquet'} doesn't exist
```
Related to:
- #6850
|
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I_kwDODunzps6H3KhH
| 6,868 |
datasets.BuilderConfig does not work.
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[] | null | 1 | 2024-05-05T08:08:55 | 2024-05-05T12:15:02 | 2024-05-05T12:15:01 |
NONE
| null | null | null |
### Describe the bug
I custom a BuilderConfig and GeneratorBasedBuilder.
Here is the code for BuilderConfig
```
class UIEConfig(datasets.BuilderConfig):
def __init__(
self,
*args,
data_dir=None,
instruction_file=None,
instruction_strategy=None,
task_config_dir=None,
num_examples=None,
max_num_instances_per_task=None,
max_num_instances_per_eval_task=None,
over_sampling=None,
**kwargs
):
super().__init__(*args, **kwargs)
self.data_dir = data_dir
self.num_examples = num_examples
self.over_sampling = over_sampling
self.instructions = self._parse_instruction(instruction_file)
self.task_configs = self._parse_task_config(task_config_dir)
self.instruction_strategy = instruction_strategy
self.max_num_instances_per_task = max_num_instances_per_task
self.max_num_instances_per_eval_task = max_num_instances_per_eval_task
```
Besides, here is the code for GeneratorBasedBuilder.
```
class UIEInstructions(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("2.0.0")
BUILDER_CONFIG_CLASS = UIEConfig
BUILDER_CONFIGS = [
UIEConfig(name="default", description="Default config for NaturalInstructions")
]
DEFAULT_CONFIG_NAME = "default"
```
Here is the load_dataset
```
raw_datasets = load_dataset(
os.path.join(CURRENT_DIR, "uie_dataset.py"),
data_dir=data_args.data_dir,
task_config_dir=data_args.task_config_dir,
instruction_file=data_args.instruction_file,
instruction_strategy=data_args.instruction_strategy,
cache_dir=data_cache_dir, # for debug, change dataset size, otherwise open it
max_num_instances_per_task=data_args.max_num_instances_per_task,
max_num_instances_per_eval_task=data_args.max_num_instances_per_eval_task,
num_examples=data_args.num_examples,
over_sampling=data_args.over_sampling
)
```
Finally, I met the error.
```
BuilderConfig UIEConfig(name='default', version=0.0.0, data_dir=None, data_files=None, description='Default config for NaturalInstructions') doesn't have a 'task_config_dir' key.
```
I debugged the code, but I find the parameters added by me may not work.
### Steps to reproduce the bug
https://github.com/BeyonderXX/InstructUIE/blob/master/src/uie_dataset.py
### Expected behavior
```
BuilderConfig UIEConfig(name='default', version=0.0.0, data_dir=None, data_files=None, description='Default config for NaturalInstructions') doesn't have a 'task_config_dir' key.
```
### Environment info
torch 2.3.0+cu118
transformers 4.40.1
python 3.8
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| 2,279,059,787 |
I_kwDODunzps6H17FL
| 6,867 |
Improve performance of JSON loader
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MEMBER
| null | null | null |
As reported by @natolambert, loading regular JSON files with `datasets` shows poor performance.
The cause is that we use the `json` Python standard library instead of other faster libraries. See my old comment: https://github.com/huggingface/datasets/pull/2638#pullrequestreview-706983714
> There are benchmarks that compare different JSON packages, with the Standard Library one among the worst performant:
> - https://github.com/ultrajson/ultrajson#benchmarks
> - https://github.com/ijl/orjson#performance
I remember having a discussion about this and it was decided that it was better not to include an additional dependency on a 3rd-party library.
However:
- We already depend on `pandas` and `pandas` depends on `ujson`: so we have an indirect dependency on `ujson`
- Even if the above were not the case, we always could include `ujson` as an optional extra dependency, and check at runtime if it is installed to decide which library to use, either json or ujson
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DataFilesNotFoundError for datasets in the open-llm-leaderboard
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NONE
| null | null | null |
### Describe the bug
When trying to get config names or load any dataset within the open-llm-leaderboard ecosystem (`open-llm-leaderboard/details_`) I receive the DataFilesNotFoundError. For the last month or so I've been loading datasets from the leaderboard almost everyday; yesterday was the first time I started seeing this.
### Steps to reproduce the bug
This snippet has three cells:
1. Loads the modules
2. Tries to get config names
3. Tries to load the dataset
I've chosen "davidkim205"'s Rhea-72b-v0.5 model because it is one of the best performers on the leaderboard should likely have no dataset issues:
```python
In [1]: from datasets import load_dataset, get_dataset_config_names
In [2]: get_dataset_config_names("open-llm-leaderboard/details_davidkim205__Rhea
...: -72b-v0.5")
---------------------------------------------------------------------------
DataFilesNotFoundError Traceback (most recent call last)
Cell In[2], line 1
----> 1 get_dataset_config_names("open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5")
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/inspect.py:347, in get_dataset_config_names(path, revision, download_config, download_mode, dynamic_modules_path, data_files, **download_kwargs)
291 def get_dataset_config_names(
292 path: str,
293 revision: Optional[Union[str, Version]] = None,
(...)
298 **download_kwargs,
299 ):
300 """Get the list of available config names for a particular dataset.
301
302 Args:
(...)
345 ```
346 """
--> 347 dataset_module = dataset_module_factory(
348 path,
349 revision=revision,
350 download_config=download_config,
351 download_mode=download_mode,
352 dynamic_modules_path=dynamic_modules_path,
353 data_files=data_files,
354 **download_kwargs,
355 )
356 builder_cls = get_dataset_builder_class(dataset_module, dataset_name=os.path.basename(path))
357 return list(builder_cls.builder_configs.keys()) or [
358 dataset_module.builder_kwargs.get("config_name", builder_cls.DEFAULT_CONFIG_NAME or "default")
359 ]
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1821, in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, cache_dir, trust_remote_code, _require_default_config_name, _require_custom_configs, **download_kwargs)
1812 return LocalDatasetModuleFactoryWithScript(
1813 combined_path,
1814 download_mode=download_mode,
1815 dynamic_modules_path=dynamic_modules_path,
1816 trust_remote_code=trust_remote_code,
1817 ).get_module()
1818 elif os.path.isdir(path):
1819 return LocalDatasetModuleFactoryWithoutScript(
1820 path, data_dir=data_dir, data_files=data_files, download_mode=download_mode
-> 1821 ).get_module()
1822 # Try remotely
1823 elif is_relative_path(path) and path.count("/") <= 1:
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1039, in LocalDatasetModuleFactoryWithoutScript.get_module(self)
1033 patterns = get_data_patterns(base_path)
1034 data_files = DataFilesDict.from_patterns(
1035 patterns,
1036 base_path=base_path,
1037 allowed_extensions=ALL_ALLOWED_EXTENSIONS,
1038 )
-> 1039 module_name, default_builder_kwargs = infer_module_for_data_files(
1040 data_files=data_files,
1041 path=self.path,
1042 )
1043 data_files = data_files.filter_extensions(_MODULE_TO_EXTENSIONS[module_name])
1044 # Collect metadata files if the module supports them
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:597, in infer_module_for_data_files(data_files, path, download_config)
595 raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}")
596 if not module_name:
--> 597 raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else ""))
598 return module_name, default_builder_kwargs
DataFilesNotFoundError: No (supported) data files found in open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5
In [3]: data = load_dataset("open-llm-leaderboard/details_davidkim205__Rhea-72b-
...: v0.5", "harness_winogrande_5")
---------------------------------------------------------------------------
DataFilesNotFoundError Traceback (most recent call last)
Cell In[3], line 1
----> 1 data = load_dataset("open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5", "harness_winogrande_5")
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:2587, 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)
2582 verification_mode = VerificationMode(
2583 (verification_mode or VerificationMode.BASIC_CHECKS) if not save_infos else VerificationMode.ALL_CHECKS
2584 )
2586 # Create a dataset builder
-> 2587 builder_instance = load_dataset_builder(
2588 path=path,
2589 name=name,
2590 data_dir=data_dir,
2591 data_files=data_files,
2592 cache_dir=cache_dir,
2593 features=features,
2594 download_config=download_config,
2595 download_mode=download_mode,
2596 revision=revision,
2597 token=token,
2598 storage_options=storage_options,
2599 trust_remote_code=trust_remote_code,
2600 _require_default_config_name=name is None,
2601 **config_kwargs,
2602 )
2604 # Return iterable dataset in case of streaming
2605 if streaming:
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:2259, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, token, use_auth_token, storage_options, trust_remote_code, _require_default_config_name, **config_kwargs)
2257 download_config = download_config.copy() if download_config else DownloadConfig()
2258 download_config.storage_options.update(storage_options)
-> 2259 dataset_module = dataset_module_factory(
2260 path,
2261 revision=revision,
2262 download_config=download_config,
2263 download_mode=download_mode,
2264 data_dir=data_dir,
2265 data_files=data_files,
2266 cache_dir=cache_dir,
2267 trust_remote_code=trust_remote_code,
2268 _require_default_config_name=_require_default_config_name,
2269 _require_custom_configs=bool(config_kwargs),
2270 )
2271 # Get dataset builder class from the processing script
2272 builder_kwargs = dataset_module.builder_kwargs
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1821, in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, cache_dir, trust_remote_code, _require_default_config_name, _require_custom_configs, **download_kwargs)
1812 return LocalDatasetModuleFactoryWithScript(
1813 combined_path,
1814 download_mode=download_mode,
1815 dynamic_modules_path=dynamic_modules_path,
1816 trust_remote_code=trust_remote_code,
1817 ).get_module()
1818 elif os.path.isdir(path):
1819 return LocalDatasetModuleFactoryWithoutScript(
1820 path, data_dir=data_dir, data_files=data_files, download_mode=download_mode
-> 1821 ).get_module()
1822 # Try remotely
1823 elif is_relative_path(path) and path.count("/") <= 1:
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1039, in LocalDatasetModuleFactoryWithoutScript.get_module(self)
1033 patterns = get_data_patterns(base_path)
1034 data_files = DataFilesDict.from_patterns(
1035 patterns,
1036 base_path=base_path,
1037 allowed_extensions=ALL_ALLOWED_EXTENSIONS,
1038 )
-> 1039 module_name, default_builder_kwargs = infer_module_for_data_files(
1040 data_files=data_files,
1041 path=self.path,
1042 )
1043 data_files = data_files.filter_extensions(_MODULE_TO_EXTENSIONS[module_name])
1044 # Collect metadata files if the module supports them
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:597, in infer_module_for_data_files(data_files, path, download_config)
595 raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}")
596 if not module_name:
--> 597 raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else ""))
598 return module_name, default_builder_kwargs
DataFilesNotFoundError: No (supported) data files found in open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5
```
### Expected behavior
No exceptions from `get_dataset_config_names` or `load_dataset`
### Environment info
- `datasets` version: 2.19.0
- Platform: Linux-6.5.0-1018-aws-aarch64-with-glibc2.35
- Python version: 3.11.8
- `huggingface_hub` version: 0.23.0
- PyArrow version: 16.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.3.1
|
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| 2,276,986,981 |
I_kwDODunzps6HuBBl
| 6,864 |
Dataset 'rewardsignal/reddit_writing_prompts' doesn't exist on the Hub
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NONE
| null | null | null |
### Describe the bug
The dataset `rewardsignal/reddit_writing_prompts` is missing in Huggingface Hub.
### Steps to reproduce the bug
```
from datasets import load_dataset
prompt_response_dataset = load_dataset("rewardsignal/reddit_writing_prompts", data_files="prompt_responses_full.csv", split='train[:80%]')
```
### Expected behavior
DatasetNotFoundError: Dataset 'rewardsignal/reddit_writing_prompts' doesn't exist on the Hub or cannot be accessed
### Environment info
Nothing to do with versions
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I_kwDODunzps6Ht-t-
| 6,863 |
Revert temporary pin huggingface-hub < 0.23.0
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MEMBER
| null | null | null |
Revert temporary pin huggingface-hub < 0.23.0 introduced by
- #6861
once the following issue is fixed and released:
- huggingface/transformers#30618
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| 2,276,763,745 |
PR_kwDODunzps5ubOoL
| 6,862 |
Fix load_dataset for data_files with protocols other than HF
|
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CONTRIBUTOR
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|
Fixes huggingface/datasets/issues/6598
I've added a new test case and a solution. Before applying the solution the test case was failing with the same error described in the linked issue.
MRE:
```
pip install "datasets[s3]"
python -c "from datasets import load_dataset; load_dataset('csv', data_files={'train': 's3://noaa-gsod-pds/2024/A5125600451.csv'})"
```
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PR_kwDODunzps5uYkMy
| 6,861 |
Fix CI by temporarily pinning huggingface-hub < 0.23.0
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As a hotfix for CI, temporarily pin `huggingface-hub` upper version
Fix #6860.
Revert once root cause is fixed, see:
- https://github.com/huggingface/transformers/issues/30618
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fix conda release worlflow
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Set dev version
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Release: 3.1.0
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