html_url stringlengths 48 51 | title stringlengths 5 280 | comments stringlengths 63 51.8k | body stringlengths 0 36.2k ⌀ | comment_length int64 16 1.52k | text stringlengths 159 54.1k | embeddings listlengths 768 768 |
|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/5936 | Sequence of array not supported for most dtype | Here's something I can't explain:
When an array is encoded in the `from_dict` method, the numpy array is converted to a list (thus losing the original dtype, which is transfromed to the nearest builtin Python type)
https://github.com/huggingface/datasets/blob/6ee61e6e695b1df9f232d47faf3a5e2b30b33737/src/datasets/... | ### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
"int8", # failed
"int16", # failed
... | 132 | Sequence of array not supported for most dtype
### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
... | [
0.04710442200303078,
-0.41798636317253113,
-0.21846047043800354,
0.25921615958213806,
0.27266204357147217,
0.06292108446359634,
0.3563428819179535,
0.2676527798175812,
0.21745391190052032,
0.05035842955112457,
0.19395604729652405,
0.30664584040641785,
-0.2323111742734909,
0.203426659107208... |
https://github.com/huggingface/datasets/issues/5936 | Sequence of array not supported for most dtype | Arrow only support 1d numpy arrays, so we convert multidim arrays to lists of 1s arrays (and keep the dtype).
Though you noticed that it's concerting to lists and lose the dtype. If it's the case then it's a bug. | ### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
"int8", # failed
"int16", # failed
... | 40 | Sequence of array not supported for most dtype
### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
... | [
0.04710442200303078,
-0.41798636317253113,
-0.21846047043800354,
0.25921615958213806,
0.27266204357147217,
0.06292108446359634,
0.3563428819179535,
0.2676527798175812,
0.21745391190052032,
0.05035842955112457,
0.19395604729652405,
0.30664584040641785,
-0.2323111742734909,
0.203426659107208... |
https://github.com/huggingface/datasets/issues/5936 | Sequence of array not supported for most dtype | Ok the conversion to list shouldn't be there indeed ! Could you open a PR to remove it ? | ### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
"int8", # failed
"int16", # failed
... | 19 | Sequence of array not supported for most dtype
### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
... | [
0.04710442200303078,
-0.41798636317253113,
-0.21846047043800354,
0.25921615958213806,
0.27266204357147217,
0.06292108446359634,
0.3563428819179535,
0.2676527798175812,
0.21745391190052032,
0.05035842955112457,
0.19395604729652405,
0.30664584040641785,
-0.2323111742734909,
0.203426659107208... |
https://github.com/huggingface/datasets/issues/5931 | `datasets.map` not reusing cached copy by default | This can happen when a map transform cannot be hashed deterministically (e.g., an object referenced by the transform changes its state after the first call - an issue with fast tokenizers). The solution is to provide `cache_file_name` in the `map` call to check this file for the cached result instead of relying on the ... | ### Describe the bug
When I load the dataset from local directory, it's cached copy is picked up after first time. However, for `map` operation, the operation is applied again and cached copy is not picked up. Is there any way to pick cached copy instead of processing it again? The only solution I could think of was... | 57 | `datasets.map` not reusing cached copy by default
### Describe the bug
When I load the dataset from local directory, it's cached copy is picked up after first time. However, for `map` operation, the operation is applied again and cached copy is not picked up. Is there any way to pick cached copy instead of process... | [
-0.30971917510032654,
-0.046799302101135254,
0.03724800422787666,
0.18077155947685242,
0.30983370542526245,
-0.07924351841211319,
0.21164479851722717,
0.057359784841537476,
0.06278608739376068,
0.18938463926315308,
0.05401935428380966,
0.46479329466819763,
0.01787940412759781,
-0.199603408... |
https://github.com/huggingface/datasets/issues/5929 | Importing PyTorch reduces multiprocessing performance for map | Hi! The times match when I run this code locally or on Colab.
Also, we use `multiprocess`, not `multiprocessing`, for parallelization, and torch's `__init__.py` (executed on `import torch` ) slightly modifies the latter. | ### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import datasets
datasets.disable_caching()
from datasets import Da... | 33 | Importing PyTorch reduces multiprocessing performance for map
### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import... | [
-0.3891278803348541,
-0.4363752007484436,
-0.05353570729494095,
0.2766872048377991,
-0.03466286510229111,
-0.057556185871362686,
0.33743205666542053,
0.0532284714281559,
0.2430381178855896,
-0.000996313989162445,
0.02219698205590248,
0.7091219425201416,
-0.10803565382957458,
-0.29341152310... |
https://github.com/huggingface/datasets/issues/5929 | Importing PyTorch reduces multiprocessing performance for map | Hey Mariosasko,
Thanks for looking into it. We further did some investigations after your comment and figured out it's only affecting some hardware/software configurations with the `pytorch` installation of `conda-forge`. Based on this we found the following issue in PyTorch: https://github.com/pytorch/pytorch/issue... | ### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import datasets
datasets.disable_caching()
from datasets import Da... | 77 | Importing PyTorch reduces multiprocessing performance for map
### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import... | [
-0.38423117995262146,
-0.4190559983253479,
-0.06506846845149994,
0.25460824370384216,
0.016990136355161667,
-0.0723160058259964,
0.3079419732093811,
0.10683608055114746,
0.2653847634792328,
-0.0056900084018707275,
0.0011331884888932109,
0.7020178437232971,
-0.11789294332265854,
-0.23182700... |
https://github.com/huggingface/datasets/issues/5927 | `IndexError` when indexing `Sequence` of `Array2D` with `None` values | Easy fix would be to add:
```python
null_indices -= np.arange(len(null_indices))
```
before L279, but I'm not sure it's the most intuitive way to fix it. | ### Describe the bug
Having `None` values in a `Sequence` of `ArrayND` fails.
### Steps to reproduce the bug
```python
from datasets import Array2D, Dataset, Features, Sequence
data = [
[
[[0]],
None,
None,
]
]
feature = Sequence(Array2D((1, 1), dtype="int64"))
dataset =... | 25 | `IndexError` when indexing `Sequence` of `Array2D` with `None` values
### Describe the bug
Having `None` values in a `Sequence` of `ArrayND` fails.
### Steps to reproduce the bug
```python
from datasets import Array2D, Dataset, Features, Sequence
data = [
[
[[0]],
None,
None,
... | [
0.07399110496044159,
-0.0921040028333664,
-0.20227287709712982,
0.2803232669830322,
0.09471603482961655,
0.08701881021261215,
0.47043877840042114,
0.2795630693435669,
0.11865626275539398,
0.18264147639274597,
-0.001967829652130604,
0.13821138441562653,
-0.3078858256340027,
-0.0145329367369... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Based on https://github.com/rapidsai/cudf/issues/10187, this probably means your `pyarrow` installation is not compatible with `datasets`.
Can you please execute the following commands in the terminal and paste the output here?
```
conda list | grep arrow
```
```
python -c "import pyarrow; print(pyarrow.__file... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 43 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > Based on [rapidsai/cudf#10187](https://github.com/rapidsai/cudf/issues/10187), this probably means your `pyarrow` installation is not compatible with `datasets`.
>
> Can you please execute the following commands in the terminal and paste the output here?
>
> ```
> conda list | grep arrow
> ```
>
> ```
> p... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 78 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | RuntimeError: Failed to import transformers.trainer because of the following error (look up to see its traceback):
pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility. Expected 88 from C header, got 72 from PyObject | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 32 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | I got the same error, pyarrow 12.0.0 released May/2023 (https://pypi.org/project/pyarrow/) is not compatible, running `pip install pyarrow==11.0.0` to force install the previous version solved the problem.
Do we need to update dependencies? | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 32 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Please note that our CI properly passes all tests with `pyarrow-12.0.0`, for Python 3.7 and Python 3.10, for Ubuntu and Windows: see for example https://github.com/huggingface/datasets/actions/runs/5157324334/jobs/9289582291 | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 25 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | For conda with python3.8.16 this solved my problem! thanks!
> I got the same error, pyarrow 12.0.0 released May/2023 (https://pypi.org/project/pyarrow/) is not compatible, running `pip install pyarrow==11.0.0` to force install the previous version solved the problem.
>
> Do we need to update dependencies? I can w... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 57 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Thanks for replying. I am not sure about those environments but it seems like pyarrow-12.0.0 does not work for conda with python 3.8.16.
> Please note that our CI properly passes all tests with `pyarrow-12.0.0`, for Python 3.7 and Python 3.10, for Ubuntu and Windows: see for example https://github.com/huggingface/d... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 49 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Got the same error with:
```
arrow-cpp 11.0.0 py310h7516544_0
pyarrow 12.0.0 pypi_0 pypi
python 3.10.11 h7a1cb2a_2
datasets 2.13.0 pyhd8ed1ab_0 conda-forge
``` | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 21 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > I got the same error, pyarrow 12.0.0 released May/2023 (https://pypi.org/project/pyarrow/) is not compatible, running `pip install pyarrow==11.0.0` to force install the previous version solved the problem.
>
> Do we need to update dependencies?
This solved the issue for me as well. | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 43 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > I got the same error, pyarrow 12.0.0 released May/2023 (https://pypi.org/project/pyarrow/) is not compatible, running `pip install pyarrow==11.0.0` to force install the previous version solved the problem.
>
> Do we need to update dependencies?
Solved it for me also | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 40 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > 基于 [rapidsai/cudf#10187](https://github.com/rapidsai/cudf/issues/10187)，这可能意味着您的安装与 不兼容。`pyarrow``datasets`
>
> 您能否在终端中执行以下命令并将输出粘贴到此处？
>
> ```
> conda list | grep arrow
> ```
>
> ```
> python -c "import pyarrow; print(pyarrow.__file__)"
> ```
arrow-cpp 11.0.0 py310h7516544_0 ... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 37 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Got the same problem with
arrow-cpp 11.0.0 py310h1fc3239_0
pyarrow 12.0.1 pypi_0 pypi
miniforge3/envs/mlp/lib/python3.10/site-packages/pyarrow/__init__.py
Reverting back to pyarrow 11 solved the problem.
| ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 21 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | I got different. Solved with
pip install pyarrow==12.0.1
pip install cchardet
env:
Python 3.9.16
transformers 4.32.1 | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 16 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > I got the same error, pyarrow 12.0.0 released May/2023 (https://pypi.org/project/pyarrow/) is not compatible, running `pip install pyarrow==11.0.0` to force install the previous version solved the problem.
>
> Do we need to update dependencies?
This works for me as well | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 41 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > I got different. Solved with pip install pyarrow==12.0.1 pip install cchardet
>
> env: Python 3.9.16 transformers 4.32.1
I guess it also depends on the Python version. I got Python 3.11.5 and pyarrow==12.0.0.
It works! | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 36 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Hi, if this helps anyone, pip install pyarrow==11.0.0 did not work for me (I'm using Colab) but this worked:
!pip install --extra-index-url=https://pypi.nvidia.com cudf-cu11 | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 23 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > Hi, if this helps anyone, pip install pyarrow==11.0.0 did not work for me (I'm using Colab) but this worked: !pip install --extra-index-url=https://pypi.nvidia.com cudf-cu11
thanks! I met the same problem and your suggestion solved it. | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 35 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | (I was doing quiet install so I didn't notice it initially)
I've been loading the same dataset for months on Colab, just now I got this error as well. I think Colab has changed their image recently (I had some errors regarding CUDA previously as well). beware of this and restart runtime if you're doing quite pip insta... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 137 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | The above methods didn't help me. So I installed an older version: `!pip install datasets==2.16.1`
and `import datasets` worked!! | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 19 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | @rasith1998 @PennlaineChu You can avoid this issue by restarting the session after the `datasets` installation (see https://github.com/huggingface/datasets/issues/6661 for more info)
Also, we've contacted Google Colab folks to update the default PyArrow installation, so the issue should soon be "officially" resolved... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 43 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > Also, we've contacted Google Colab folks to update the default PyArrow installation, so the issue should soon be "officially" resolved on their side.
This has been done! Google Colab now pre-installs PyArrow 14.0.2, which makes this issue unlikely to happen, so I'm closing it. | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 45 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | I am facing this issue outside of Colab, in a normal Python (3.10.14) environment:
```
pyarrow==11.0.0
datasets=2.20.0
transformers==4.41.2
```
What can I do to solve it?
I am somewhat bound to `pyarrow==11.0.0`. Is there a version of `datasets` that supports this? | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 41 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-0.5389385223388672,
0.41014111042022705,
-0.09792448580265045,
0.23194201290607452,
0.1428852081298828,
-0.1310204267501831,
0.21223457157611847,
0.2684714198112488,
-0.40871259570121765,
0.09050580859184265,
-0.2040785551071167,
0.2750715911388397,
-0.12025702744722366,
0.140969902276992... |
https://github.com/huggingface/datasets/issues/5922 | Length of table does not accurately reflect the split | As already replied by @lhoestq (private channel):
> `.train_test_split` (as well as `.shard`, `.select`) doesn't create a new arrow table to save time and disk space. Instead, it uses an indices mapping on top of the table that locate which examples are part of train or test. | ### Describe the bug
I load a Huggingface Dataset and do `train_test_split`. I'm expecting the underlying table for the dataset to also be split, but it's not.
### Steps to reproduce the bug
### Expected behavior... | 47 | Length of table does not accurately reflect the split
### Describe the bug
I load a Huggingface Dataset and do `train_test_split`. I'm expecting the underlying table for the dataset to also be split, but it's not.
### Steps to reproduce the bug
. The dataset contains 50 million text-image pairs, but an error occurred. | Thanks for reporting, @cjt222.
What is the structure of your JSON files. Please note that it is normally simpler if the data file format is JSON-Lines instead. | ### Describe the bug
File "/home/kas/.conda/envs/diffusers/lib/python3.7/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
Downloading and preparing dataset json/default to /home/kas/diffusers/examples/dreambooth/cache_data/datasets/json/default-acf423d8c6ef99d0/0.0.0/e347ab1c932092252e717ff3f94... | 27 | I tried to load a custom dataset using the following statement: dataset = load_dataset('json', data_files=data_files). The dataset contains 50 million text-image pairs, but an error occurred.
### Describe the bug
File "/home/kas/.conda/envs/diffusers/lib/python3.7/site-packages/datasets/builder.py", line 1858, in _p... | [
-0.3578912913799286,
0.19285914301872253,
-0.13863550126552582,
0.2901041507720947,
0.2431727945804596,
0.02491293102502823,
0.3775225579738617,
0.46858522295951843,
-0.17913462221622467,
0.09429802000522614,
-0.07349076122045517,
0.28123223781585693,
-0.12814100086688995,
-0.0168298184871... |
https://github.com/huggingface/datasets/issues/5913 | I tried to load a custom dataset using the following statement: dataset = load_dataset('json', data_files=data_files). The dataset contains 50 million text-image pairs, but an error occurred. | > Thanks for reporting, @cjt222.
>
> What is the structure of your JSON files. Please note that it is normally simpler if the data file format is JSON-Lines instead.
Thanks! I have encountered similar problems. I modify the json format from list to line and works! | ### Describe the bug
File "/home/kas/.conda/envs/diffusers/lib/python3.7/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
Downloading and preparing dataset json/default to /home/kas/diffusers/examples/dreambooth/cache_data/datasets/json/default-acf423d8c6ef99d0/0.0.0/e347ab1c932092252e717ff3f94... | 47 | I tried to load a custom dataset using the following statement: dataset = load_dataset('json', data_files=data_files). The dataset contains 50 million text-image pairs, but an error occurred.
### Describe the bug
File "/home/kas/.conda/envs/diffusers/lib/python3.7/site-packages/datasets/builder.py", line 1858, in _p... | [
-0.3578912913799286,
0.19285914301872253,
-0.13863550126552582,
0.2901041507720947,
0.2431727945804596,
0.02491293102502823,
0.3775225579738617,
0.46858522295951843,
-0.17913462221622467,
0.09429802000522614,
-0.07349076122045517,
0.28123223781585693,
-0.12814100086688995,
-0.0168298184871... |
https://github.com/huggingface/datasets/issues/5912 | Missing elements in `map` a batched dataset | Hi ! in your code batching is **only used within** `map`, to process examples in batch. The dataset itself however is not batched and returns elements one by one.
To iterate on batches, you can do
```python
for batch in dataset.iter(batch_size=8):
...
``` | ### Describe the bug
As outlined [here](https://discuss.huggingface.co/t/length-error-using-map-with-datasets/40969/3?u=sachin), the following collate function drops 5 out of possible 6 elements in the batch (it is 6 because out of the eight, two are bad links in laion). A reproducible [kaggle kernel ](https://www.kag... | 43 | Missing elements in `map` a batched dataset
### Describe the bug
As outlined [here](https://discuss.huggingface.co/t/length-error-using-map-with-datasets/40969/3?u=sachin), the following collate function drops 5 out of possible 6 elements in the batch (it is 6 because out of the eight, two are bad links in laion). A... | [
0.06454850733280182,
-0.23429939150810242,
-0.04375574365258217,
0.3354431986808777,
0.02739741839468479,
0.10073413699865341,
0.6815289855003357,
0.31476011872291565,
-0.14844724535942078,
0.27320611476898193,
0.12604010105133057,
0.12251199036836624,
0.14440780878067017,
-0.0186645202338... |
https://github.com/huggingface/datasets/issues/5910 | Cannot use both set_format and set_transform | Currently, it's not possible to chain `set_format`/`set_transform` calls (plus, this is a breaking change if we decide to implement it), so I see two possible solutions:
* using `set_format`/`set_transform` for the 1st transform and then passing the transformed example/batch to the 2nd transform
* implementing and re... | ### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.
### Steps to reproduce the bug
```
from... | 69 | Cannot use both set_format and set_transform
### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.... | [
-0.2939646244049072,
-0.36669766902923584,
0.011063102632761002,
0.01251910999417305,
0.26930612325668335,
-0.056196391582489014,
0.5307267308235168,
0.34042996168136597,
-0.37947943806648254,
-0.04991009831428528,
-0.07404308766126633,
0.2621925175189972,
-0.19932176172733307,
0.195102006... |
https://github.com/huggingface/datasets/issues/5910 | Cannot use both set_format and set_transform | Hey Mario,
Thanks, for getting back to me. the toDouble was just an example my real life case requires many more transforms.
What do you mean by:
> using set_format/set_transform for the 1st transform and then passing the transformed example/batch to the 2nd transform
How would that go, I thought you can't chai... | ### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.
### Steps to reproduce the bug
```
from... | 86 | Cannot use both set_format and set_transform
### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.... | [
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0.15243540704... |
https://github.com/huggingface/datasets/issues/5910 | Cannot use both set_format and set_transform | > How would that go, I thought you can't chain them?
Yes, they cannot be chained. This is what I meant:
```python
ds.set_transform(first_transform)
# calling the 2nd transform on each accessed batch
second_transform(ds[2:3])
```
> As for the custom formatter, is it possible to reference an existing formatter... | ### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.
### Steps to reproduce the bug
```
from... | 74 | Cannot use both set_format and set_transform
### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.... | [
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https://github.com/huggingface/datasets/issues/5908 | Unbearably slow sorting on big mapped datasets | Hi ! `shard` currently returns a slow dataset by default, with examples evenly distributed in the dataset.
You can get a fast dataset using `contiguous=True` (which should be the default imo):
```python
dataset = dataset.shard(10, 0, contiguous=True)
```
This way you don't need to flatten_indices() and sort ... | ### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially with bigger datasets (wasn't able to sort 700k lin... | 52 | Unbearably slow sorting on big mapped datasets
### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially w... | [
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https://github.com/huggingface/datasets/issues/5908 | Unbearably slow sorting on big mapped datasets | @lhoestq
> contiguous=True (which should be the default imo)
For `IterableDataset`, it's not possible to implement contiguous sharding without knowing the number of examples in advance, so setting the default value to `contiguous=True` would result in an inconsistency between `Dataset` and `IterableDataset` (whe... | ### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially with bigger datasets (wasn't able to sort 700k lin... | 46 | Unbearably slow sorting on big mapped datasets
### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially w... | [
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https://github.com/huggingface/datasets/issues/5908 | Unbearably slow sorting on big mapped datasets | Actually sharded iterable datasets are made of sub iterables that generally yield contiguous data no ? So in a way it's possible to shard an iterable dataset contiguously.
If the dataset is made of one shard it's indeed not possible to shard it contiguously though | ### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially with bigger datasets (wasn't able to sort 700k lin... | 45 | Unbearably slow sorting on big mapped datasets
### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially w... | [
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https://github.com/huggingface/datasets/issues/5908 | Unbearably slow sorting on big mapped datasets | > Actually sharded iterable datasets are made of sub iterables that generally yield contiguous data no ? So in a way it's possible to shard an iterable dataset contiguously.
But sharding an iterable dataset by sharding its `gen_kwargs` would still yield approximate shards(not equal to `Dataset.shard`), no? | ### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially with bigger datasets (wasn't able to sort 700k lin... | 47 | Unbearably slow sorting on big mapped datasets
### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially w... | [
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https://github.com/huggingface/datasets/issues/5908 | Unbearably slow sorting on big mapped datasets | I understand the issue doesn't exist with non-mapped datasets, but if flattening is so much more efficient than sorting the indices, that's an issue in itself.
There are plenty of issues people posted for which the root cause turns out to be the same. It seems like mapped datasets are terribly inefficient. I think I s... | ### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially with bigger datasets (wasn't able to sort 700k lin... | 82 | Unbearably slow sorting on big mapped datasets
### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially w... | [
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https://github.com/huggingface/datasets/issues/5905 | Offer an alternative to Iterable Dataset that allows lazy loading and processing while skipping batches efficiently | We plan to improve this eventually (see https://github.com/huggingface/datasets/issues/5454 and https://github.com/huggingface/datasets/issues/5380).
> Is it possible to lazily load samples of a mapped dataset ? I'm used to [dataset scripts](https://huggingface.co/docs/datasets/dataset_script), maybe something can b... | ### Feature request
I would like a way to resume training from a checkpoint without waiting for a very long time when using an iterable dataset.
### Motivation
I am training models on the speech-recognition task. I have very large datasets that I can't comfortably store on a disk and also quite computationally... | 151 | Offer an alternative to Iterable Dataset that allows lazy loading and processing while skipping batches efficiently
### Feature request
I would like a way to resume training from a checkpoint without waiting for a very long time when using an iterable dataset.
### Motivation
I am training models on the speec... | [
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https://github.com/huggingface/datasets/issues/5895 | The dir name and split strings are confused when loading ArmelR/stack-exchange-instruction dataset | Thanks for reporting, @DongHande.
I think the issue is caused by the metadata in the dataset card: in the header of the `README.md`, they state that the dataset has 4 splits ("finetune", "reward", "rl", "evaluation").
```yaml
splits:
- name: finetune
num_bytes: 6674567576
num_examples: 300000... | ### Describe the bug
When I load the ArmelR/stack-exchange-instruction dataset, I encounter a bug that may be raised by confusing the dir name string and the split string about the dataset.
When I use the script "datasets.load_dataset('ArmelR/stack-exchange-instruction', data_dir="data/finetune", split="train", ... | 122 | The dir name and split strings are confused when loading ArmelR/stack-exchange-instruction dataset
### Describe the bug
When I load the ArmelR/stack-exchange-instruction dataset, I encounter a bug that may be raised by confusing the dir name string and the split string about the dataset.
When I use the script ... | [
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0.01273576356470... |
https://github.com/huggingface/datasets/issues/5892 | User access requests with manual review do not notify the dataset owner | I think this has been addressed.
Please open a new issue if you are still not getting notified. | ### Describe the bug
When a user access requests are enabled, and new requests are set to Manual Review, the dataset owner should be notified of the pending requests. However, instead, currently nothing happens, and so the dataset request can go unanswered for quite some time until the owner happens to check that part... | 18 | User access requests with manual review do not notify the dataset owner
### Describe the bug
When a user access requests are enabled, and new requests are set to Manual Review, the dataset owner should be notified of the pending requests. However, instead, currently nothing happens, and so the dataset request can go... | [
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https://github.com/huggingface/datasets/issues/5887 | HuggingsFace dataset example give error | Nice catch @donhuvy, that's because some models don't need the `token_type_ids`, as in this case, as the example is using `distilbert-base-cased`, and according to the DistilBert documentation at https://huggingface.co/transformers/v3.0.2/model_doc/distilbert.html, `DistilBert doesn’t have token_type_ids, you don’t nee... | ### Describe the bug
### Steps to reproduce the bug
Use link as reference document written https://c... | 107 | HuggingsFace dataset example give error
### Describe the bug
### Steps to reproduce the bug
Use li... | [
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0.00149478... |
https://github.com/huggingface/datasets/issues/5887 | HuggingsFace dataset example give error | This has been addressed in #5902.
The Quicktour notebook is deprecated now - please use the notebook version of the [Quickstart doc page](https://huggingface.co/docs/datasets/main/en/quickstart) instead ("Open in Colab" button). | ### Describe the bug
### Steps to reproduce the bug
Use link as reference document written https://c... | 28 | HuggingsFace dataset example give error
### Describe the bug
### Steps to reproduce the bug
Use li... | [
-0.30471816658973694,
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0.24549731612205505,
0.36166858673095703,
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0.1478714495897293,
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0.00149478... |
https://github.com/huggingface/datasets/issues/5886 | Use work-stealing algorithm when parallel computing | Alternatively we could set the number of shards to be a factor than the number of processes (current they're equal) - this way it will be less likely to end up with a shard that is significantly slower than all the other ones. | ### Feature request
when i used Dataset.map api to process data concurrently, i found that
it gets slower and slower as it gets closer to completion. Then i read the source code of arrow_dataset.py and found that it shard the dataset and use multiprocessing pool to execute each shard.It may cause the slowest task ... | 43 | Use work-stealing algorithm when parallel computing
### Feature request
when i used Dataset.map api to process data concurrently, i found that
it gets slower and slower as it gets closer to completion. Then i read the source code of arrow_dataset.py and found that it shard the dataset and use multiprocessing poo... | [
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0.08089751... |
https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | Hi!
You want to use `push_to_hub` (creates Parquet files) instead of `save_to_disk` (creates Arrow files) when creating a Hub dataset. Parquet is designed for long-term storage and takes less space than the Arrow format, and, most importantly, `load_dataset` can parse it, which should fix the viewer.
Regarding ... | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 142 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
-0.5871185660362244,
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https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | One issue here is that Dataset.from_generator can work well for the non 'infinite sampling' version of the dataset. The training set for example is often sampled dynamically given the video files that I have uploaded. I worry that storing the video data as binary means that I'll end up duplicating a lot of the data. Fu... | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 73 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
-0.5850048065185547,
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0.6762351989... |
https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | > storing video data as anything but .mp4
What I mean by storing as `datasets.Value("binary")` is embedding raw MP4 bytes in the Arrow table, but, indeed, this would waste a lot of space if there are duplicates.
So I see two options:
* if one video is not mapped to too many samples, you can embed the video bytes... | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 159 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
-0.4535919725894928,
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0.04561568796634674,
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0.15140022337436676,
-0.4043417274951935,
0.6011259555... |
https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | @mariosasko Right. If I want my dataset to be streamable, what are the necessary requirements to achieve that within the context of .mp4 binaries like we have here? I guess your second point here would not support that right? | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 39 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
-0.5347315073013306,
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0.6612893939... |
https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | The streaming would work, but the video paths would require using `fsspec.open` to get the content. | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 16 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
-0.5551954507827759,
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0.13698364794254303,
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0.7099343538... |
https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | Not yet. The (open source) tooling for video is not great in terms of ease of use/performance, so we are discussing internally the best way to support it (one option is creating a new library for video IO, but this will require a lot of work) | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 46 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
-0.5383276343345642,
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0.026201993227005005,
-0.033127978444099426,
0.14679758250713348,
-0.3247303068637848,
0.68568176... |
https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | True. I spend a good 4 months just mixing and matching existing solutions so I could get performance that would not IO bound my model training.
This is what I ended up with, in case it's useful
https://github.com/AntreasAntoniou/TALI/blob/045cf9e5aa75b1bf2c6d5351fb910fa10e3ff32c/tali/data/data_plus.py#L85 | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 38 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
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https://github.com/huggingface/datasets/issues/5881 | Split dataset by node: index error when sharding iterable dataset | cc @lhoestq in case you have any ideas here! Might need a multi-host set-up to debug (can give you access to a JAX one if you need) | ### Describe the bug
Context: we're splitting an iterable dataset by node and then passing it to a torch data loader with multiple workers
When we iterate over it for 5 steps, we don't get an error
When we instead iterate over it for 8 steps, we get an `IndexError` when fetching the data if we have too many wo... | 27 | Split dataset by node: index error when sharding iterable dataset
### Describe the bug
Context: we're splitting an iterable dataset by node and then passing it to a torch data loader with multiple workers
When we iterate over it for 5 steps, we don't get an error
When we instead iterate over it for 8 steps, ... | [
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https://github.com/huggingface/datasets/issues/5881 | Split dataset by node: index error when sharding iterable dataset | I am also facing the same problem. Could you let me know if you found a solution for this? | ### Describe the bug
Context: we're splitting an iterable dataset by node and then passing it to a torch data loader with multiple workers
When we iterate over it for 5 steps, we don't get an error
When we instead iterate over it for 8 steps, we get an `IndexError` when fetching the data if we have too many wo... | 19 | Split dataset by node: index error when sharding iterable dataset
### Describe the bug
Context: we're splitting an iterable dataset by node and then passing it to a torch data loader with multiple workers
When we iterate over it for 5 steps, we don't get an error
When we instead iterate over it for 8 steps, ... | [
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0.27622249722480774,
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https://github.com/huggingface/datasets/issues/5881 | Split dataset by node: index error when sharding iterable dataset | I couldn't reproduce with the latest version of `datasets` 2.16.1, can you update `datasets` and try again ? | ### Describe the bug
Context: we're splitting an iterable dataset by node and then passing it to a torch data loader with multiple workers
When we iterate over it for 5 steps, we don't get an error
When we instead iterate over it for 8 steps, we get an `IndexError` when fetching the data if we have too many wo... | 18 | Split dataset by node: index error when sharding iterable dataset
### Describe the bug
Context: we're splitting an iterable dataset by node and then passing it to a torch data loader with multiple workers
When we iterate over it for 5 steps, we don't get an error
When we instead iterate over it for 8 steps, ... | [
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https://github.com/huggingface/datasets/issues/5880 | load_dataset from s3 file system through streaming can't not iterate data | This sounds related to #5281.
Can you try passing `storage_options=s3_client.storage_options` instead passing it to `use_auth_token=` ? | ### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-45b5-ac68-4e7c664c2ed0">
<img width="1144" alt="image" src="https://github.c... | 16 | load_dataset from s3 file system through streaming can't not iterate data
### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-... | [
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0.393470108509... |
https://github.com/huggingface/datasets/issues/5880 | load_dataset from s3 file system through streaming can't not iterate data | I tried `storage_options` before, but it doesn't work, I checked our source code and I found that we even didn't pass this parameter to the following process. if I use `storage_options` instead of `use_auth_token`, then I also need to change another place of the code. the last line of `streaming_download_manager.py`. o... | ### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-45b5-ac68-4e7c664c2ed0">
<img width="1144" alt="image" src="https://github.c... | 70 | load_dataset from s3 file system through streaming can't not iterate data
### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-... | [
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0.1681804060935974,
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0.30375680327415466,
0.07043839991092682,
0.2703858315944... |
https://github.com/huggingface/datasets/issues/5880 | load_dataset from s3 file system through streaming can't not iterate data | Cloud storage support is still experimental indeed and you can expect some bugs.
I think we need to pass the storage options anywhere use_auth_token is passed in indeed. Let me know if you'd be interested in contributing a fix ! | ### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-45b5-ac68-4e7c664c2ed0">
<img width="1144" alt="image" src="https://github.c... | 40 | load_dataset from s3 file system through streaming can't not iterate data
### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-... | [
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0.08481057733297348,
0.3905624449... |
https://github.com/huggingface/datasets/issues/5880 | load_dataset from s3 file system through streaming can't not iterate data | Oh, that's great, I really like to fix it. because datasets is really useful and most of our projects need to use it, but we can store our data on the internet due to security reasons. fix it not only make our own work more efficient but also can benefit others who use it. | ### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-45b5-ac68-4e7c664c2ed0">
<img width="1144" alt="image" src="https://github.c... | 54 | load_dataset from s3 file system through streaming can't not iterate data
### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-... | [
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0.01125592365860939,
0.346860021352767... |
https://github.com/huggingface/datasets/issues/5878 | Prefetching for IterableDataset | Very cool! Do you have a link to the code that you're using to eagerly fetch the data? Would also be interested in hacking around something here for pre-fetching iterable datasets | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk... | 31 | Prefetching for IterableDataset
### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required whe... | [
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https://github.com/huggingface/datasets/issues/5878 | Prefetching for IterableDataset | I ended up just switching back to the pytorch dataloader and using it's multiprocessing functionality to handle this :(. I'm just not that familiar with python multiprocessing to get something to work in jupyter (kept having weird behaviors happening with zombies living after the cell finished). | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk... | 46 | Prefetching for IterableDataset
### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required whe... | [
-0.36874353885650635,
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https://github.com/huggingface/datasets/issues/5878 | Prefetching for IterableDataset | Ultimately settled on using webdataset to circumvent huggingface datasets entirely. Would definitely switch back if: https://github.com/huggingface/datasets/issues/5337 was resolved. | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk... | 18 | Prefetching for IterableDataset
### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required whe... | [
-0.45579200983047485,
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0.5462949872... |
https://github.com/huggingface/datasets/issues/5878 | Prefetching for IterableDataset | Hi! You can combine `datasets` with `torchdata` to prefetch `IterableDataset`'s samples:
```python
from datasets import load_dataset
from torchdata.datapipes.iter import IterableWrapper, HuggingFaceHubReader
from torch.utils.data import DataLoader
ds = load_dataset("sst", split="train", streaming=True)
# proces... | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk... | 47 | Prefetching for IterableDataset
### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required whe... | [
-0.4951934516429901,
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0.311850905418396... |
https://github.com/huggingface/datasets/issues/5878 | Prefetching for IterableDataset | Hey @mariosasko! Thanks for the tip here - introducing prefetch with `torchdata` didn't really give me any performance difference vs not prefetching, but the concept is definitely one that could be really beneficial. Are there any benchmarks that show the speed-up you can get with `torchdata`'s prefetch just for compar... | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk... | 50 | Prefetching for IterableDataset
### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required whe... | [
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0.07988815009593964,
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0.3089246... |
https://github.com/huggingface/datasets/issues/5877 | Request for text deduplication feature | The "exact match" deduplication will be possible when we resolve https://github.com/huggingface/datasets/issues/2514 (first, https://github.com/apache/arrow/issues/30950 needs to be addressed on the Arrow side). In the meantime, you can use Polars or DuckDB (e.g., via [datasets-sql](https://github.com/mariosasko/datase... | ### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.com/google-research/deduplicate-text-datase... | 47 | Request for text deduplication feature
### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.co... | [
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0.5272760987281799,
0.13664475083351135,
0.0757004... |
https://github.com/huggingface/datasets/issues/5877 | Request for text deduplication feature | I have been using polars to remove duplicates but it would be nice to do it directly in pyarrow.
For example,
1. Read dataset with pyarrow
2. Use scan_pyarrow_dataset() with Polars to create a LazyFrame
3. Use sort and unique to remove duplicates based on a subset of columns
4. Convert to table and save data w... | ### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.com/google-research/deduplicate-text-datase... | 104 | Request for text deduplication feature
### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.co... | [
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0.0256318... |
https://github.com/huggingface/datasets/issues/5877 | Request for text deduplication feature | Hi
see this new release from hf [datatrove](https://github.com/huggingface/datatrove)
DataTrove is a library to process, filter and deduplicate text data at a very large scale. It provides a set of prebuilt commonly used processing blocks with a framework to easily add custom functionality | ### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.com/google-research/deduplicate-text-datase... | 42 | Request for text deduplication feature
### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.co... | [
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0.40503939986228943,
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0.248172000... |
https://github.com/huggingface/datasets/issues/5876 | Incompatibility with DataLab | Indeed, `clobber=True` (with a warning if the existing protocol will be overwritten) should fix the issue, but maybe a better solution is to register our compression filesystem before the script is executed and unregister them afterward. WDYT @lhoestq @albertvillanova? | ### Describe the bug
Hello,
I am currently working on a project where both [DataLab](https://github.com/ExpressAI/DataLab) and [datasets](https://github.com/huggingface/datasets) are subdependencies.
I noticed that I cannot import both libraries, as they both register FileSystems in `fsspec`, expecting the FileSyste... | 39 | Incompatibility with DataLab
### Describe the bug
Hello,
I am currently working on a project where both [DataLab](https://github.com/ExpressAI/DataLab) and [datasets](https://github.com/huggingface/datasets) are subdependencies.
I noticed that I cannot import both libraries, as they both register FileSystems in `f... | [
-0.3287138342857361,
0.2323613464832306,
-0.10847358405590057,
0.2798904478549957,
0.2765091359615326,
0.1225794181227684,
0.1858048290014267,
0.03771395981311798,
0.12055669724941254,
0.1787026822566986,
-0.22298473119735718,
0.15490035712718964,
0.057372428476810455,
0.08281169831752777,... |
https://github.com/huggingface/datasets/issues/5876 | Incompatibility with DataLab | I think we should use clobber and show a warning if it overwrote a registered filesystem indeed ! This way the user can re-register the filesystems if needed. Though they should probably be compatible (and maybe do the exact same thing) so I wouldn't de-register the `datasets` filesystems | ### Describe the bug
Hello,
I am currently working on a project where both [DataLab](https://github.com/ExpressAI/DataLab) and [datasets](https://github.com/huggingface/datasets) are subdependencies.
I noticed that I cannot import both libraries, as they both register FileSystems in `fsspec`, expecting the FileSyste... | 48 | Incompatibility with DataLab
### Describe the bug
Hello,
I am currently working on a project where both [DataLab](https://github.com/ExpressAI/DataLab) and [datasets](https://github.com/huggingface/datasets) are subdependencies.
I noticed that I cannot import both libraries, as they both register FileSystems in `f... | [
-0.3287138342857361,
0.2323613464832306,
-0.10847358405590057,
0.2798904478549957,
0.2765091359615326,
0.1225794181227684,
0.1858048290014267,
0.03771395981311798,
0.12055669724941254,
0.1787026822566986,
-0.22298473119735718,
0.15490035712718964,
0.057372428476810455,
0.08281169831752777,... |
https://github.com/huggingface/datasets/issues/5874 | Using as_dataset on a "parquet" builder | Hi! You can refer to [this doc](https://huggingface.co/docs/datasets/filesystems#load-and-save-your-datasets-using-your-cloud-storage-filesystem) to see the intended usage (basically, it skips the Arrow -> Parquet conversion step in `ds = load_dataset(...); ds.to_parquet("path/to/parquet")`) and allows writing Parquet ... | ### Describe the bug
I used a custom builder to ``download_and_prepare`` a dataset. The first (very minor) issue is that the doc seems to suggest ``download_and_prepare`` will return the dataset, while it does not ([builder.py](https://github.com/huggingface/datasets/blob/main/src/datasets/builder.py#L718-L738)).
```... | 104 | Using as_dataset on a "parquet" builder
### Describe the bug
I used a custom builder to ``download_and_prepare`` a dataset. The first (very minor) issue is that the doc seems to suggest ``download_and_prepare`` will return the dataset, while it does not ([builder.py](https://github.com/huggingface/datasets/blob/ma... | [
-0.43764254450798035,
0.061569541692733765,
0.04537069424986839,
0.6551527976989746,
0.1841801255941391,
-0.07021324336528778,
0.09196804463863373,
0.11068017780780792,
0.0775061547756195,
-0.10491333901882172,
0.11259064078330994,
0.5481752753257751,
-0.39214804768562317,
0.03461495041847... |
https://github.com/huggingface/datasets/issues/5871 | data configuration hash suffix depends on uncanonicalized data_dir | Indeed, it makes sense to normalize `data_dir`. Feel free to submit a PR (this can be "fixed" [here](https://github.com/huggingface/datasets/blob/89f775226321ba94e5bf4670a323c0fb44f5f65c/src/datasets/builder.py#L173)) | ### Describe the bug
I am working with the `recipe_nlg` dataset, which requires manual download. Once it's downloaded, I've noticed that the hash in the custom data configuration is different if I add a trailing `/` to my `data_dir`. It took me a while to notice that the hashes were different, and to understand that... | 18 | data configuration hash suffix depends on uncanonicalized data_dir
### Describe the bug
I am working with the `recipe_nlg` dataset, which requires manual download. Once it's downloaded, I've noticed that the hash in the custom data configuration is different if I add a trailing `/` to my `data_dir`. It took me a w... | [
-0.10499203205108643,
-0.11921080946922302,
-0.05035074055194855,
0.3601606488227844,
0.21915030479431152,
0.17273637652397156,
0.13491295278072357,
0.18599224090576172,
-0.21063293516635895,
-0.01573166251182556,
-0.1308375746011734,
-0.027857769280672073,
-0.23439191281795502,
-0.3052013... |
https://github.com/huggingface/datasets/issues/5870 | Behaviour difference between datasets.map and IterableDatasets.map | PS - some work is definitely needed for 'special cases' docs, not explanations, just usages of 'functions' under mixture of special cases, like a combination of custom databuilder + iterable dataset for large size + dynamic .map() application. | ### Describe the bug
All the examples in all the docs mentioned throughout huggingface datasets correspond to datasets object, and not IterableDatasets object. At one point of time, they might have been in sync, but the code for datasets version >=2.9.0 is very different as compared to the docs.
I basically need to ... | 38 | Behaviour difference between datasets.map and IterableDatasets.map
### Describe the bug
All the examples in all the docs mentioned throughout huggingface datasets correspond to datasets object, and not IterableDatasets object. At one point of time, they might have been in sync, but the code for datasets version >=2.... | [
-0.0845835953950882,
-0.3134583830833435,
0.024995308369398117,
0.20392468571662903,
0.16278983652591705,
-0.16763775050640106,
0.36135002970695496,
0.034223806113004684,
-0.1255190670490265,
0.039429180324077606,
-0.2061735987663269,
0.4666685461997986,
-0.27213218808174133,
-0.0415148586... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | Hi @PhilippeMoussalli thanks for opening a detailed issue. It seems the issue is more related to the `datasets` library so I'll ping @lhoestq @mariosasko on this one :)
(edit: also can one of you move the issue to the datasets repo? Thanks in advance 🙏) | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 45 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | Hi ! The `Image()` info is stored in the **schema metadata**. More precisely there should be a "huggingface" field in the schema metadata that contains the `datasets` feature type of each column.
To fix your issue, you can use the same schema as the original Parquet files to write the new ones. You can also get the ... | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 95 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | It appears that the parquet files at `hf://datasets/lambdalabs/pokemon-blip-captions` don't have this metadata, and it is defined in the dataset_infos.json instead (legacy).
You can get the right schema with the HF metadata this way:
```python
from datasets import load_dataset_builder
features = load_dataset_... | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 45 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | Btw in the future we might add support for an dedicated Image extension type in Arrow so that you won't need to add the schema metadata anymore ;) | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 28 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | Thanks @Wauplin @lhoestq for the quick reply :)!
I tried your approach by passing the huggingface schema to the dask writer
```
from datasets import Features, Image, Value
df = dd.read_parquet(f"hf://datasets/lambdalabs/pokemon-blip-captions",index=False)
features = Features({"image": Image(), "text": Value(... | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 152 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | You don't need the dataset_infos.json file as long as you have the schema with HF metadata ;)
I could also check that it works fine myself on the git revision without the dataset_infos.json file.
What made you think it didn't work ? | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 42 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | > You don't need the dataset_infos.json file as long as you have the schema with HF metadata ;) I could also check that it works fine myself on the git revision without the dataset_infos.json file.
>
> What made you think it didn't work ?
Those are two identical dataset repos where both were pushed with dask with... | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 116 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | I see ! I think it's a bug on our side - it should work without the metadata - let me investigate | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 22 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | Alright, it's fixed: https://huggingface.co/datasets/philippemo/dummy_dataset_without_schema
It shows the image correctly now - even without the extra metadata :) | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 17 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | Thanks @lhoestq!
I tested pushing a dataset again without the metadata and it works perfectly!
I appreciate the help | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 19 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | Hi @lhoestq,
I'v tried pushing another dataset again and I think the issue reappeared again:
```
df = dd.read_parquet(f"hf://datasets/lambdalabs/pokemon-blip-captions")
features = datasets.Features({"image": datasets.Image(), "text": datasets.Value("string")})
schema = features.arrow_schema
dd.to_parquet(df... | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 102 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | We're doing some changes in the way we're handling image parquet datasets right now. We'll include the fix from https://github.com/huggingface/datasets/pull/5921 in the new datasets-server version in the coming days | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 29 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | alright thanks for the update :), would that be part of the new release of datasets or is it something separate? if so, where can I track it? | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 28 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | Once the new version of `datasets` is released (tomorrow probably) we'll open an issue on https://github.com/huggingface/datasets-server to update to this version :) | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 22 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-0.07916479557752609,
-0.1934366375207901,
0.05645662173628807,
0.463128924369812,
0.240503191947937,
-0.03627728670835495,
-0.07235728204250336,
0.15203067660331726,
-0.02029368095099926,
0.08434876799583435,
0.23947331309318542,
0.25118619203567505,
-0.0505802184343338,
0.192153424024581... |
https://github.com/huggingface/datasets/issues/5868 | Is it possible to change a cached file and 're-cache' it instead of re-generating? | Arrow files/primitives (tables and arrays) are immutable, so re-generating them is the only option, I'm afraid. | ### Feature request
Hi,
I have a huge cached file using `map`(over 500GB), and I want to change an attribution of each element, is there possible to do it using some method instead of re-generating, because `map` takes over 24 hours
### Motivation
For large datasets, I think it is very important because we always f... | 16 | Is it possible to change a cached file and 're-cache' it instead of re-generating?
### Feature request
Hi,
I have a huge cached file using `map`(over 500GB), and I want to change an attribution of each element, is there possible to do it using some method instead of re-generating, because `map` takes over 24 hours
... | [
-0.09704209864139557,
-0.11337395757436752,
-0.12200796604156494,
0.32319360971450806,
-0.009359266608953476,
-0.008812226355075836,
-0.03176717087626457,
0.19218608736991882,
0.27105122804641724,
0.016848042607307434,
-0.13763441145420074,
0.3374762535095215,
0.1259240359067917,
-0.324794... |
https://github.com/huggingface/datasets/issues/5864 | Slow iteration over Torch tensors | I am highly interested performance of dataset so I ran your example as a curious user.
```python
train_dataset.cast_column("x", Array3D(shape=img_shape, dtype="float32"))
```
have return values and "x" is a new column, it shoulde be
```python
ds=train_dataset.cast_column("img", Array3D(shape=(3,32,32), dtype="flo... | ### Describe the bug
I have a problem related to this [issue](https://github.com/huggingface/datasets/issues/5841): I get a way slower iteration when using a Torch dataloader if I use vanilla Numpy tensors or if I first apply a ToTensor transform to the input. In particular, it takes 5 seconds to iterate over the vani... | 112 | Slow iteration over Torch tensors
### Describe the bug
I have a problem related to this [issue](https://github.com/huggingface/datasets/issues/5841): I get a way slower iteration when using a Torch dataloader if I use vanilla Numpy tensors or if I first apply a ToTensor transform to the input. In particular, it take... | [
-0.217259481549263,
-0.6703980565071106,
-0.03890470415353775,
0.36325907707214355,
0.21971826255321503,
-0.02410857379436493,
0.4750514030456543,
0.32326728105545044,
-0.018299734219908714,
0.41666173934936523,
-0.08816783130168915,
0.44262611865997314,
-0.2223813682794571,
-0.47148159146... |
https://github.com/huggingface/datasets/issues/5862 | IndexError: list index out of range with data hosted on Zenodo | This error is also raised when data is hosted on Google Drive:
- https://huggingface.co/datasets/docred/discussions/5
- https://huggingface.co/datasets/linnaeus/discussions/3
- https://huggingface.co/datasets/poleval2019_mt/discussions/3
- https://huggingface.co/datasets/reddit_tifu/discussions/2
- https://hugging... | The dataset viewer sometimes raises an `IndexError`:
```
IndexError: list index out of range
```
See:
- huggingface/datasets-server#1151
- https://huggingface.co/datasets/reddit/discussions/5
- huggingface/datasets-server#1118
- https://huggingface.co/datasets/krr-oxford/OntoLAMA/discussions/1
- https://hu... | 26 | IndexError: list index out of range with data hosted on Zenodo
The dataset viewer sometimes raises an `IndexError`:
```
IndexError: list index out of range
```
See:
- huggingface/datasets-server#1151
- https://huggingface.co/datasets/reddit/discussions/5
- huggingface/datasets-server#1118
- https://huggin... | [
-0.15684956312179565,
0.018117398023605347,
-0.13773657381534576,
0.5326906442642212,
0.08840961009263992,
0.08455763012170792,
0.3212423324584961,
0.3956218659877777,
0.1698119044303894,
0.20749682188034058,
-0.5241463780403137,
-0.32136568427085876,
0.16142472624778748,
-0.04245059937238... |
https://github.com/huggingface/datasets/issues/5858 | Throw an error when dataset improperly indexed | Thanks for reporting, @sarahwie.
Please note that in `datasets` we do not have vectorized operation like `pandas`. Therefore, your equality comparisons above are `False`:
- For example: `squad['question']` returns a `list`, and this list is not equal to `"Who was the Norse leader?"`
The `False` value is equivale... | ### Describe the bug
Pandas-style subset indexing on dataset does not throw an error, when maybe it should. Instead returns the first instance of the dataset regardless of index condition.
### Steps to reproduce the bug
Steps to reproduce the behavior:
1. `squad = datasets.load_dataset("squad_v2", split="validati... | 99 | Throw an error when dataset improperly indexed
### Describe the bug
Pandas-style subset indexing on dataset does not throw an error, when maybe it should. Instead returns the first instance of the dataset regardless of index condition.
### Steps to reproduce the bug
Steps to reproduce the behavior:
1. `squad = ... | [
-0.11276465654373169,
-0.029434815049171448,
-0.0322456881403923,
0.3046641945838928,
-0.017604663968086243,
0.19889631867408752,
0.3279404044151306,
0.36500948667526245,
0.0400659404695034,
0.15649385750293732,
-0.02362341433763504,
0.3770911395549774,
0.0017946204170584679,
-0.1822313964... |
https://github.com/huggingface/datasets/issues/5857 | Adding chemistry dataset/models in huggingface | Hi!
This would be a nice addition to the Hub! You can find the existing chemistry datasets/models on the Hub (using the `chemistry` tag) [here](https://huggingface.co/search/full-text?q=chemistry&type=model&type=dataset).
Feel free to ping us here on the Hub if you need help adding the datasets.
| ### Feature request
Huggingface is really amazing platform for open science.
In addition to computer vision, video and NLP, would it be of interest to add chemistry/materials science dataset/models in Huggingface? Or, if its already done, can you provide some pointers.
We have been working on a comprehensive ben... | 41 | Adding chemistry dataset/models in huggingface
### Feature request
Huggingface is really amazing platform for open science.
In addition to computer vision, video and NLP, would it be of interest to add chemistry/materials science dataset/models in Huggingface? Or, if its already done, can you provide some pointer... | [
-0.11878079175949097,
-0.40453219413757324,
-0.13821865618228912,
0.1770077496767044,
-0.09072436392307281,
-0.04768332839012146,
-0.11828894913196564,
0.09518717229366302,
0.2977323830127716,
0.07220053672790527,
-0.21887801587581635,
0.06159249693155289,
-0.4699893891811371,
0.6341659426... |
https://github.com/huggingface/datasets/issues/5856 | Error loading natural_questions | Hi! You can avoid this error by using the preprocessed version:
```python
import datasets
ds = datasets.load_dataset('natural_questions')
```
PS: Once we finish https://github.com/huggingface/datasets/pull/5364, this error will no longer be a problem. | ### Describe the bug
When try to load natural_questions through datasets == 2.12.0 with python == 3.8.9:
```python
import datasets
datasets.load_dataset('natural_questions',beam_runner='DirectRunner')
```
It failed with following info:
`pyarrow.lib.ArrowNotImplementedError: Nested data conversions not impl... | 31 | Error loading natural_questions
### Describe the bug
When try to load natural_questions through datasets == 2.12.0 with python == 3.8.9:
```python
import datasets
datasets.load_dataset('natural_questions',beam_runner='DirectRunner')
```
It failed with following info:
`pyarrow.lib.ArrowNotImplementedError... | [
-0.3733486831188202,
0.09020364284515381,
-0.024216599762439728,
0.4655783176422119,
0.3577083945274353,
-0.21396228671073914,
0.15965025126934052,
0.5116322636604309,
0.044096145778894424,
0.017487965524196625,
-0.09487835317850113,
0.6436848640441895,
-0.23180025815963745,
-0.04579793661... |
https://github.com/huggingface/datasets/issues/5856 | Error loading natural_questions | > Hi! You can avoid this error by using the preprocessed version:
>
> ```python
> import datasets
> ds = datasets.load_dataset('natural_questions')
> ```
>
> PS: Once we finish #5364, this error will no longer be a problem.
Thanks, wish #5364 finish early | ### Describe the bug
When try to load natural_questions through datasets == 2.12.0 with python == 3.8.9:
```python
import datasets
datasets.load_dataset('natural_questions',beam_runner='DirectRunner')
```
It failed with following info:
`pyarrow.lib.ArrowNotImplementedError: Nested data conversions not impl... | 44 | Error loading natural_questions
### Describe the bug
When try to load natural_questions through datasets == 2.12.0 with python == 3.8.9:
```python
import datasets
datasets.load_dataset('natural_questions',beam_runner='DirectRunner')
```
It failed with following info:
`pyarrow.lib.ArrowNotImplementedError... | [
-0.3733486831188202,
0.09020364284515381,
-0.024216599762439728,
0.4655783176422119,
0.3577083945274353,
-0.21396228671073914,
0.15965025126934052,
0.5116322636604309,
0.044096145778894424,
0.017487965524196625,
-0.09487835317850113,
0.6436848640441895,
-0.23180025815963745,
-0.04579793661... |
https://github.com/huggingface/datasets/issues/5855 | `to_tf_dataset` consumes too much memory | Cc @amyeroberts @Rocketknight1
Indded I think it's because it does something like this under the hood when there's no multiprocessing:
```python
tf_dataset = tf_dataset.shuffle(len(dataset))
```
PS: with multiprocessing it appears to be different:
```python
indices = np.arange(len(dataset))
if shuffle:... | ### Describe the bug
Hi, I'm using `to_tf_dataset` to convert a _large_ dataset to `tf.data.Dataset`. I observed that the data loading *before* training took a lot of time and memory, even with `batch_size=1`.
After some digging, i believe the reason lies in the shuffle behavior. The [source code](https://github.... | 41 | `to_tf_dataset` consumes too much memory
### Describe the bug
Hi, I'm using `to_tf_dataset` to convert a _large_ dataset to `tf.data.Dataset`. I observed that the data loading *before* training took a lot of time and memory, even with `batch_size=1`.
After some digging, i believe the reason lies in the shuffle ... | [
-0.1582278162240982,
-0.23407310247421265,
0.09227369725704193,
0.377081036567688,
0.5104161500930786,
0.2072504162788391,
-0.03446187451481819,
0.2762851417064667,
-0.256050705909729,
0.33825480937957764,
-0.024285832419991493,
0.16308920085430145,
-0.44833511114120483,
-0.052460305392742... |
https://github.com/huggingface/datasets/issues/5855 | `to_tf_dataset` consumes too much memory | Hi @massquantity, the dataset being shuffled there is not the full dataset. If you look at [the line above](https://github.com/huggingface/datasets/blob/main/src/datasets/utils/tf_utils.py#L182), the dataset is actually just a single indices array at that point, and that array is the only thing that gets fully loaded i... | ### Describe the bug
Hi, I'm using `to_tf_dataset` to convert a _large_ dataset to `tf.data.Dataset`. I observed that the data loading *before* training took a lot of time and memory, even with `batch_size=1`.
After some digging, i believe the reason lies in the shuffle behavior. The [source code](https://github.... | 134 | `to_tf_dataset` consumes too much memory
### Describe the bug
Hi, I'm using `to_tf_dataset` to convert a _large_ dataset to `tf.data.Dataset`. I observed that the data loading *before* training took a lot of time and memory, even with `batch_size=1`.
After some digging, i believe the reason lies in the shuffle ... | [
-0.1582278162240982,
-0.23407310247421265,
0.09227369725704193,
0.377081036567688,
0.5104161500930786,
0.2072504162788391,
-0.03446187451481819,
0.2762851417064667,
-0.256050705909729,
0.33825480937957764,
-0.024285832419991493,
0.16308920085430145,
-0.44833511114120483,
-0.052460305392742... |
https://github.com/huggingface/datasets/issues/5855 | `to_tf_dataset` consumes too much memory | Hi @Rocketknight1, you're right and I also noticed that only indices are used in shuffling. My data has shape (50000000, 10), but really the problem doesn't relate to a specific dataset. Simply running the following code costs me 10GB of memory.
```python
from datasets import Dataset
def gen():
for i in ran... | ### Describe the bug
Hi, I'm using `to_tf_dataset` to convert a _large_ dataset to `tf.data.Dataset`. I observed that the data loading *before* training took a lot of time and memory, even with `batch_size=1`.
After some digging, i believe the reason lies in the shuffle behavior. The [source code](https://github.... | 160 | `to_tf_dataset` consumes too much memory
### Describe the bug
Hi, I'm using `to_tf_dataset` to convert a _large_ dataset to `tf.data.Dataset`. I observed that the data loading *before* training took a lot of time and memory, even with `batch_size=1`.
After some digging, i believe the reason lies in the shuffle ... | [
-0.1582278162240982,
-0.23407310247421265,
0.09227369725704193,
0.377081036567688,
0.5104161500930786,
0.2072504162788391,
-0.03446187451481819,
0.2762851417064667,
-0.256050705909729,
0.33825480937957764,
-0.024285832419991493,
0.16308920085430145,
-0.44833511114120483,
-0.052460305392742... |
https://github.com/huggingface/datasets/issues/5855 | `to_tf_dataset` consumes too much memory | Thanks for that reproduction script - I've confirmed the same issue is occurring for me. Investigating it now! | ### Describe the bug
Hi, I'm using `to_tf_dataset` to convert a _large_ dataset to `tf.data.Dataset`. I observed that the data loading *before* training took a lot of time and memory, even with `batch_size=1`.
After some digging, i believe the reason lies in the shuffle behavior. The [source code](https://github.... | 18 | `to_tf_dataset` consumes too much memory
### Describe the bug
Hi, I'm using `to_tf_dataset` to convert a _large_ dataset to `tf.data.Dataset`. I observed that the data loading *before* training took a lot of time and memory, even with `batch_size=1`.
After some digging, i believe the reason lies in the shuffle ... | [
-0.1582278162240982,
-0.23407310247421265,
0.09227369725704193,
0.377081036567688,
0.5104161500930786,
0.2072504162788391,
-0.03446187451481819,
0.2762851417064667,
-0.256050705909729,
0.33825480937957764,
-0.024285832419991493,
0.16308920085430145,
-0.44833511114120483,
-0.052460305392742... |
https://github.com/huggingface/datasets/issues/5855 | `to_tf_dataset` consumes too much memory | Update: The memory usage is occurring in creation of the index and shuffle buffer. You can reproduce it very simply with:
```python
import tensorflow as tf
indices = tf.range(50_000_000, dtype=tf.int64)
dataset = tf.data.Dataset.from_tensor_slices(indices)
dataset = dataset.shuffle(len(dataset))
print(next(iter... | ### Describe the bug
Hi, I'm using `to_tf_dataset` to convert a _large_ dataset to `tf.data.Dataset`. I observed that the data loading *before* training took a lot of time and memory, even with `batch_size=1`.
After some digging, i believe the reason lies in the shuffle behavior. The [source code](https://github.... | 99 | `to_tf_dataset` consumes too much memory
### Describe the bug
Hi, I'm using `to_tf_dataset` to convert a _large_ dataset to `tf.data.Dataset`. I observed that the data loading *before* training took a lot of time and memory, even with `batch_size=1`.
After some digging, i believe the reason lies in the shuffle ... | [
-0.1582278162240982,
-0.23407310247421265,
0.09227369725704193,
0.377081036567688,
0.5104161500930786,
0.2072504162788391,
-0.03446187451481819,
0.2762851417064667,
-0.256050705909729,
0.33825480937957764,
-0.024285832419991493,
0.16308920085430145,
-0.44833511114120483,
-0.052460305392742... |
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