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https://github.com/huggingface/datasets/issues/5990 | Apparently this happened because of bad modifications in the README.md split metadata.
I fixed them in this PR: https://huggingface.co/datasets/Antreas/TALI-base/discussions/1 | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 19 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
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0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | @lhoestq It's a bit odd that when uploading a dataset, one set at a time "train", "val", "test", the push_to_hub function overwrites the readme and removes differently named sets from previous commits. i.e., you push "val", all is well. Then you push "test", and the "val" entry disappears from the readme, while the dat... | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 56 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
-0.42933112382888794,
-0.06096188724040985,
0.08869528025388718,
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-0.06696006655693054,
0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | Also, just found another related issue. One of the many that make things hang or fail when pushing to hub.
In the following code:
```python
train_generator = lambda: data_generator("train", percentage=1.0)
val_generator = lambda: data_generator("val")
test_generator = lambda: data_generator("test")
... | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 738 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
-0.42933112382888794,
-0.06096188724040985,
0.08869528025388718,
0.21317243576049805,
-0.06696006655693054,
0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | > @lhoestq It's a bit odd that when uploading a dataset, one set at a time "train", "val", "test", the push_to_hub function overwrites the readme and removes differently named sets from previous commits. i.e., you push "val", all is well. Then you push "test", and the "val" entry disappears from the readme, while the d... | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 74 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
-0.42933112382888794,
-0.06096188724040985,
0.08869528025388718,
0.21317243576049805,
-0.06696006655693054,
0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | > I have a while loop that forces retries, but it seems that the progress itself is randomly getting lost as well. Any ideas on how to improve this? It has been blocking me for way too long.
Could you also print the cause of the error (`e.__cause__`) ? Or show the full stack trace when the error happens ?
This woul... | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 73 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
-0.42933112382888794,
-0.06096188724040985,
0.08869528025388718,
0.21317243576049805,
-0.06696006655693054,
0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | > Should I build the parquet manually and then push manually as well? If I do things manually, how can I ensure my dataset works properly with "stream=True"?
Parquet is supported out of the box ^^
If you want to make sure it works as expected you can try locally first:
```python
ds = load_dataset("path/to/local... | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 57 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
-0.42933112382888794,
-0.06096188724040985,
0.08869528025388718,
0.21317243576049805,
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0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | @lhoestq @AntreasAntoniou I transferred this issue to the `datasets` repository as the questions and answers are more related to this repo. Hope it can help other users find the bug and fixes more easily (like updating [tqdm](https://github.com/huggingface/datasets/issues/5990#issuecomment-1607120204) and [pyarrow](htt... | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 99 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
-0.42933112382888794,
-0.06096188724040985,
0.08869528025388718,
0.21317243576049805,
-0.06696006655693054,
0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | > @lhoestq @AntreasAntoniou I transferred this issue to the datasets repository as the questions and answers are more related to this repo. Hope it can help other users find the bug and fixes more easily (like updating https://github.com/huggingface/datasets/issues/5990#issuecomment-1607120204 and https://github.com/hu... | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 133 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
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0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | > As I've already said in other discussions, I would not recommend pushing files saved with save_to_disk to the Hub but save to parquet shards and upload them instead. The Hub does not support datasets saved with save_to_disk, which is meant for disk only.
Well noted, thanks. That part was not clear to me :) | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 55 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
-0.42933112382888794,
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-0.06696006655693054,
0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | Sorry for not replying in a few days, I was on leave. :)
So, here are more information as to the error that causes some of the delay
```bash
Pushing Antreas/TALI-tiny to hub
Attempting to push to hub
Pushing split train to the Hub.
Creating parquet from Arrow format: 100%|████████████████████████████████████... | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 228 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
-0.42933112382888794,
-0.06096188724040985,
0.08869528025388718,
0.21317243576049805,
-0.06696006655693054,
0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | So, other than the random connection drops here and there, any idea why the progress does not continue where it left off?
```bash
Pushing split train to the Hub.
Creating parquet from Arrow format: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████... | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 352 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
-0.42933112382888794,
-0.06096188724040985,
0.08869528025388718,
0.21317243576049805,
-0.06696006655693054,
0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5990 | If the any shard is missing on the Hub, it will re-upload it. It looks like the 30th shard was missing on the Hub in your case.
It also means that the other files up to the 77th that were successfully uploaded won't be uploaded again.
cc @mariosasko who might know better | Pushing a large dataset on the hub consistently hangs | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 52 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-0.3251087963581085,
-0.42933112382888794,
-0.06096188724040985,
0.08869528025388718,
0.21317243576049805,
-0.06696006655693054,
0.1970674693584442,
0.5384528636932373,
0.05225852131843567,
0.3061686158180237,
0.08448541909456253,
0.10903309285640717,
0.03724048659205437,
0.220244064927101... |
https://github.com/huggingface/datasets/issues/5936 | Related, `float16` is the only dtype not supported by `Array2D` (probably by every `ArrayND`):
```python
from datasets import Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
"int8", # ok
"int16", # ok
"int32", # ok
"int64", # ok
"uint8", # ok
... | 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
"int8", # failed
"int16", # failed
... | 91 | 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
... | [
0.04710427671670914,
-0.41798651218414307,
-0.2184605449438095,
0.2592160701751709,
0.27266204357147217,
0.06292104721069336,
0.35634270310401917,
0.26765280961990356,
0.2174539715051651,
0.05035853013396263,
0.19395580887794495,
0.30664554238319397,
-0.23231127858161926,
0.203426793217659... |
https://github.com/huggingface/datasets/issues/5936 | 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/... | 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
"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
... | [
0.04710427671670914,
-0.41798651218414307,
-0.2184605449438095,
0.2592160701751709,
0.27266204357147217,
0.06292104721069336,
0.35634270310401917,
0.26765280961990356,
0.2174539715051651,
0.05035853013396263,
0.19395580887794495,
0.30664554238319397,
-0.23231127858161926,
0.203426793217659... |
https://github.com/huggingface/datasets/issues/5936 | 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. | 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
"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
... | [
0.04710427671670914,
-0.41798651218414307,
-0.2184605449438095,
0.2592160701751709,
0.27266204357147217,
0.06292104721069336,
0.35634270310401917,
0.26765280961990356,
0.2174539715051651,
0.05035853013396263,
0.19395580887794495,
0.30664554238319397,
-0.23231127858161926,
0.203426793217659... |
https://github.com/huggingface/datasets/issues/5936 | Ok the conversion to list shouldn't be there indeed ! Could you open a PR to remove it ? | 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
"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
... | [
0.04710427671670914,
-0.41798651218414307,
-0.2184605449438095,
0.2592160701751709,
0.27266204357147217,
0.06292104721069336,
0.35634270310401917,
0.26765280961990356,
0.2174539715051651,
0.05035853013396263,
0.19395580887794495,
0.30664554238319397,
-0.23231127858161926,
0.203426793217659... |
https://github.com/huggingface/datasets/issues/5931 | 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 ... | `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 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... | [
-0.3097192645072937,
-0.046798959374427795,
0.03724795579910278,
0.1807716339826584,
0.309833824634552,
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0.21164464950561523,
0.05735986307263374,
0.06278633326292038,
0.18938514590263367,
0.05401896685361862,
0.464792937040329,
0.017879262566566467,
-0.199603617191314... |
https://github.com/huggingface/datasets/issues/5929 | 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. | 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 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... | [
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0.27668696641921997,
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0.3374318778514862,
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0.022196978330612183,
0.7091225385665894,
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-0.2934114... |
https://github.com/huggingface/datasets/issues/5929 | 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... | 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 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... | [
-0.3842312693595886,
-0.4190558195114136,
-0.06506878137588501,
0.25460851192474365,
0.016989463940262794,
-0.07231605798006058,
0.3079421818256378,
0.10683570802211761,
0.26538482308387756,
-0.005690142512321472,
0.0011331140995025635,
0.7020175457000732,
-0.11789332330226898,
-0.23182722... |
https://github.com/huggingface/datasets/issues/5927 | 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. | `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,
]
]
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,
... | [
0.07399076223373413,
-0.09210389852523804,
-0.20227259397506714,
0.2803235650062561,
0.09471626579761505,
0.08701851218938828,
0.4704388678073883,
0.2795632481575012,
0.11865653097629547,
0.1826413869857788,
-0.0019682087004184723,
0.1382116973400116,
-0.3078857362270355,
-0.01453299447894... |
https://github.com/huggingface/datasets/issues/5923 | 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... | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | > 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... | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | 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 | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | 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? | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | 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 | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | 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... | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | 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... | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | 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
``` | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | > 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. | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | > 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 | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | > 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 ... | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | 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.
| 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | I got different. Solved with
pip install pyarrow==12.0.1
pip install cchardet
env:
Python 3.9.16
transformers 4.32.1 | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | > 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 | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | > 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! | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5923 | 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 | 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
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
... | [
-0.5389391183853149,
0.41014090180397034,
-0.09792473912239075,
0.2319422960281372,
0.14288535714149475,
-0.13102033734321594,
0.21223437786102295,
0.2684710919857025,
-0.408712774515152,
0.09050598740577698,
-0.20407867431640625,
0.27507221698760986,
-0.12025684118270874,
0.14097011089324... |
https://github.com/huggingface/datasets/issues/5922 | 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. | 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
### 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. | ### 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... | [
-0.3578908443450928,
0.19285902380943298,
-0.1386357843875885,
0.29010456800460815,
0.2431730031967163,
0.024912923574447632,
0.3775229752063751,
0.46858498454093933,
-0.17913463711738586,
0.09429796785116196,
-0.07349081337451935,
0.28123247623443604,
-0.12814085185527802,
-0.016829665750... |
https://github.com/huggingface/datasets/issues/5913 | > 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! | 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 _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... | [
-0.3578908443450928,
0.19285902380943298,
-0.1386357843875885,
0.29010456800460815,
0.2431730031967163,
0.024912923574447632,
0.3775229752063751,
0.46858498454093933,
-0.17913463711738586,
0.09429796785116196,
-0.07349081337451935,
0.28123247623443604,
-0.12814085185527802,
-0.016829665750... |
https://github.com/huggingface/datasets/issues/5912 | 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):
...
``` | 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 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... | [
0.06454868614673615,
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0.3354438245296478,
0.02739712968468666,
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0.6815289258956909,
0.3147595524787903,
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0.27320611476898193,
0.12604013085365295,
0.12251227349042892,
0.14440776407718658,
-0.01866451650857... |
https://github.com/huggingface/datasets/issues/5910 | 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... | 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.
### 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.... | [
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0.2621923089027405,
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0.19510203599... |
https://github.com/huggingface/datasets/issues/5910 | 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... | 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.
### 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.... | [
-0.173383891582489,
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0.08512470871210098,
0.3002565801143646,
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0.4715593159198761,
0.41056767106056213,
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0.2118729054927826,
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0.152435958385... |
https://github.com/huggingface/datasets/issues/5910 | > 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... | 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.
### 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.... | [
-0.18959437310695648,
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0.06828268617391586,
0.24726474285125732,
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0.5087500810623169,
0.3649783134460449,
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0.19695761799812317,
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0.1315827369... |
https://github.com/huggingface/datasets/issues/5908 | 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 ... | 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 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... | [
-0.21201182901859283,
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0.17018406093120575,
0.12224605679512024,
0.0028864890336990356,
0.2648853659629822,
0.2745974659919739,
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0.1251973956823349,
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0.2705242931842804,
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-0.04856801... |
https://github.com/huggingface/datasets/issues/5908 | @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... | 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 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... | [
-0.2189244031906128,
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0.17111873626708984,
0.07388722896575928,
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0.0844036340713501,
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0.2340613603591919,
0.018153764307498932,
-0.2102927565574... |
https://github.com/huggingface/datasets/issues/5908 | 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 | 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 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... | [
-0.13646171987056732,
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0.1945437639951706,
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https://github.com/huggingface/datasets/issues/5908 | > 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? | 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 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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0.014982257038354874,
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https://github.com/huggingface/datasets/issues/5908 | 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... | 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 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... | [
-0.10508766770362854,
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0.31414133310317993,
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https://github.com/huggingface/datasets/issues/5905 | 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... | 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 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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0.018579598516225815,
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0.42274853587150574,
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0.29184761643409... |
https://github.com/huggingface/datasets/issues/5895 | 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... | 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 "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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0.31327390670776367,
0.03887961432337761,
0.01273556798696... |
https://github.com/huggingface/datasets/issues/5892 | I think this has been addressed.
Please open a new issue if you are still not getting notified. | 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 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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0.2397032529115677,
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0.00... |
https://github.com/huggingface/datasets/issues/5887 | 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... | HuggingsFace dataset example give error | ### 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... | [
-0.30471837520599365,
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0.2454974353313446,
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0.2697404623031616,
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0.147871732711792,
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0.0014945566654205... |
https://github.com/huggingface/datasets/issues/5887 | 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). | HuggingsFace dataset example give error | ### 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... | [
-0.30471837520599365,
-0.32953858375549316,
-0.009535536170005798,
0.2454974353313446,
0.3616688549518585,
0.02109256386756897,
0.3034208416938782,
0.3132304549217224,
0.1804969310760498,
0.2697404623031616,
-0.23079945147037506,
0.147871732711792,
-0.008146129548549652,
0.0014945566654205... |
https://github.com/huggingface/datasets/issues/5886 | 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. | 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 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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https://github.com/huggingface/datasets/issues/5888 | 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 ... | 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 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... | [
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https://github.com/huggingface/datasets/issues/5888 | 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... | 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 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... | [
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https://github.com/huggingface/datasets/issues/5888 | > 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... | 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 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... | [
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https://github.com/huggingface/datasets/issues/5888 | @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? | 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 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... | [
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0.6612888... |
https://github.com/huggingface/datasets/issues/5888 | The streaming would work, but the video paths would require using `fsspec.open` to get the content. | 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 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... | [
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https://github.com/huggingface/datasets/issues/5888 | 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) | 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 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... | [
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0.685682058334... |
https://github.com/huggingface/datasets/issues/5888 | 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 | 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 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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0.7047359943389... |
https://github.com/huggingface/datasets/issues/5881 | 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) | 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, 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 | I am also facing the same problem. Could you let me know if you found a solution for this? | 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, 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, ... | [
-0.3438449800014496,
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0.276222825050354,
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-0.00888334959745... |
https://github.com/huggingface/datasets/issues/5881 | I couldn't reproduce with the latest version of `datasets` 2.16.1, can you update `datasets` and try again ? | 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, 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, ... | [
-0.3438449800014496,
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0.10152041167020798,
0.276222825050354,
-0.19482579827308655,
-0.00888334959745... |
https://github.com/huggingface/datasets/issues/5880 | This sounds related to #5281.
Can you try passing `storage_options=s3_client.storage_options` instead passing it to `use_auth_token=` ? | 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/cc0778d3-36f3-45b5-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-... | [
-0.02854137122631073,
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0.5485132336616516,
0.4296378791332245,
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0.3991794288158417,
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0.05558111146092415,
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0.3006925582885742,
0.08064774423837662,
0.393470764160... |
https://github.com/huggingface/datasets/issues/5880 | 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... | 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/cc0778d3-36f3-45b5-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-... | [
-0.028941556811332703,
-0.3251906633377075,
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0.5395929217338562,
0.4121260344982147,
0.09475596994161606,
0.3216099739074707,
-0.0892593115568161,
0.08491154760122299,
0.16818025708198547,
-0.043760765343904495,
0.30375683307647705,
0.07043804228305817,
0.2703854143619... |
https://github.com/huggingface/datasets/issues/5880 | 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 ! | 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/cc0778d3-36f3-45b5-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-... | [
-0.02695624530315399,
-0.29852840304374695,
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0.49376577138900757,
0.41069313883781433,
0.04066244512796402,
0.35842058062553406,
-0.07718323916196823,
0.0702420100569725,
0.11812220513820648,
0.01759123057126999,
0.2411087453365326,
0.08481022715568542,
0.3905630111694... |
https://github.com/huggingface/datasets/issues/5880 | 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. | 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/cc0778d3-36f3-45b5-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-... | [
-0.0944085493683815,
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0.34636640548706055,
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0.10418137907981873,
-0.02822217345237732,
0.2770599126815796,
0.01125609502196312,
0.3468599617481231... |
https://github.com/huggingface/datasets/issues/5878 | 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 | 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 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... | [
-0.46986472606658936,
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0.011188313364982605,
0.2757582366466522,
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0.07481328397989273,
0.06472859531641006,
0.059693120419979095,
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0.4955103397... |
https://github.com/huggingface/datasets/issues/5878 | 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). | 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 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... | [
-0.3687434196472168,
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0.035193853080272675,
0.11722812056541443,
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0.49919074773... |
https://github.com/huggingface/datasets/issues/5878 | Ultimately settled on using webdataset to circumvent huggingface datasets entirely. Would definitely switch back if: https://github.com/huggingface/datasets/issues/5337 was resolved. | 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 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... | [
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0.0228714719414711,
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0.01316484808921814,
-0.008307550102472305,
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0.546294987... |
https://github.com/huggingface/datasets/issues/5878 | 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... | 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 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... | [
-0.4951932728290558,
-0.21732252836227417,
-0.09793658554553986,
-0.33331742882728577,
0.04191122204065323,
0.0207659974694252,
0.3390699326992035,
0.24473732709884644,
0.23043428361415863,
0.05596419423818588,
-0.021707583218812943,
0.1356603503227234,
-0.3293340504169464,
0.3118507564067... |
https://github.com/huggingface/datasets/issues/5878 | 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... | 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 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... | [
-0.5272353887557983,
-0.14079159498214722,
-0.12215772271156311,
-0.365050733089447,
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0.3421747088432312,
0.260110467672348,
0.19832269847393036,
0.027485936880111694,
0.011267807334661484,
0.0798882395029068,
-0.3678653836250305,
0.3089249432... |
https://github.com/huggingface/datasets/issues/5877 | 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... | 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.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... | [
-0.19005602598190308,
-0.09308367222547531,
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0.12080073356628418,
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0.04617947340011597,
0.04579456150531769,
0.1417374312877655,
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0.5272765159606934,
0.1366443932056427,
0.0757007151... |
https://github.com/huggingface/datasets/issues/5877 | 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... | 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.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... | [
-0.018998324871063232,
-0.04216289520263672,
-0.05457958206534386,
0.07354654371738434,
-0.01498129591345787,
0.04807283729314804,
0.24181589484214783,
0.1446562111377716,
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0.04932622238993645,
-0.22304725646972656,
0.6511831879615784,
0.16353574395179749,
0.0256322622... |
https://github.com/huggingface/datasets/issues/5877 | 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 | 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.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... | [
0.017037756741046906,
-0.034986838698387146,
-0.19809168577194214,
0.0182168111205101,
-0.09988635778427124,
-0.04359694570302963,
0.08050928264856339,
0.1296909600496292,
-0.1064215674996376,
-0.016252078115940094,
-0.06651753187179565,
0.40503963828086853,
0.023526210337877274,
0.2481715... |
https://github.com/huggingface/datasets/issues/5876 | 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? | 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 `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... | [
-0.32871371507644653,
0.2323617786169052,
-0.10847318172454834,
0.27989068627357483,
0.27650871872901917,
0.12257921695709229,
0.1858045905828476,
0.03771381080150604,
0.12055659294128418,
0.1787029206752777,
-0.2229849100112915,
0.1549004316329956,
0.057372260838747025,
0.0828115716576576... |
https://github.com/huggingface/datasets/issues/5876 | 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 | 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 `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... | [
-0.32871371507644653,
0.2323617786169052,
-0.10847318172454834,
0.27989068627357483,
0.27650871872901917,
0.12257921695709229,
0.1858045905828476,
0.03771381080150604,
0.12055659294128418,
0.1787029206752777,
-0.2229849100112915,
0.1549004316329956,
0.057372260838747025,
0.0828115716576576... |
https://github.com/huggingface/datasets/issues/5874 | 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 ... | 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/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... | [
-0.43764203786849976,
0.06156957149505615,
0.04537085443735123,
0.6551530361175537,
0.18418003618717194,
-0.07021303474903107,
0.09196878969669342,
0.1106797456741333,
0.07750609517097473,
-0.10491342842578888,
0.11259061843156815,
0.5481758117675781,
-0.39214813709259033,
0.03461502492427... |
https://github.com/huggingface/datasets/issues/5871 | 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)) | 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 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... | [
-0.10499189049005508,
-0.11921073496341705,
-0.05035083740949631,
0.3601611852645874,
0.21914991736412048,
0.17273661494255066,
0.13491305708885193,
0.18599238991737366,
-0.2106330692768097,
-0.0157313272356987,
-0.13083800673484802,
-0.027857616543769836,
-0.2343911975622177,
-0.305201351... |
https://github.com/huggingface/datasets/issues/5870 | 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. | 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 >=2.9.0 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.... | [
-0.08458377420902252,
-0.31345874071121216,
0.024995312094688416,
0.20392443239688873,
0.1627897322177887,
-0.16763734817504883,
0.36135008931159973,
0.03422381728887558,
-0.12551893293857574,
0.039429426193237305,
-0.20617347955703735,
0.4666687846183777,
-0.27213236689567566,
-0.04151483... |
https://github.com/huggingface/datasets/issues/5869 | 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 🙏) | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | 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 ... | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | 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_... | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | 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 ;) | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | 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(... | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | 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 ? | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | > 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... | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | I see ! I think it's a bug on our side - it should work without the metadata - let me investigate | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | Alright, it's fixed: https://huggingface.co/datasets/philippemo/dummy_dataset_without_schema
It shows the image correctly now - even without the extra metadata :) | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | Thanks @lhoestq!
I tested pushing a dataset again without the metadata and it works perfectly!
I appreciate the help | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | 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... | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | 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 | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | 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? | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5869 | 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 :) | 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 (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 (... | [
-0.07916499674320221,
-0.19343626499176025,
0.05645659565925598,
0.4631294906139374,
0.24050284922122955,
-0.03627727925777435,
-0.07235730439424515,
0.15203076601028442,
-0.020293869078159332,
0.08434884250164032,
0.2394731044769287,
0.25118616223335266,
-0.05058019608259201,
0.1921534389... |
https://github.com/huggingface/datasets/issues/5868 | Arrow files/primitives (tables and arrays) are immutable, so re-generating them is the only option, I'm afraid. | 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
### 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
... | [
-0.09704175591468811,
-0.11337361484766006,
-0.12200784683227539,
0.3231933116912842,
-0.00935971736907959,
-0.008812941610813141,
-0.03176719322800636,
0.19218578934669495,
0.27105098962783813,
0.01684783771634102,
-0.1376347541809082,
0.3374762535095215,
0.12592363357543945,
-0.324794411... |
https://github.com/huggingface/datasets/issues/5864 | 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... | 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 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... | [
-0.2172592431306839,
-0.6703982353210449,
-0.03890440985560417,
0.3632587790489197,
0.2197183072566986,
-0.024108730256557465,
0.47505125403404236,
0.32326722145080566,
-0.01830008625984192,
0.4166612923145294,
-0.08816803991794586,
0.4426257610321045,
-0.222381591796875,
-0.47148168087005... |
https://github.com/huggingface/datasets/issues/5862 | 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... | 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://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... | [
-0.15684950351715088,
0.01811794936656952,
-0.13773664832115173,
0.5326906442642212,
0.08840986341238022,
0.08455762267112732,
0.32124248147010803,
0.3956218361854553,
0.16981171071529388,
0.20749667286872864,
-0.5241460204124451,
-0.32136598229408264,
0.16142502427101135,
-0.0424503609538... |
https://github.com/huggingface/datasets/issues/5858 | 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... | 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 = 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 = ... | [
-0.1127646341919899,
-0.029433786869049072,
-0.032245755195617676,
0.3046644330024719,
-0.01760469563305378,
0.198896586894989,
0.3279401659965515,
0.36500996351242065,
0.04006601870059967,
0.15649382770061493,
-0.02362341806292534,
0.3770912289619446,
0.0017942748963832855,
-0.18223139643... |
https://github.com/huggingface/datasets/issues/5857 | 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.
| 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 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... | [
-0.11878088116645813,
-0.4045315980911255,
-0.13821867108345032,
0.1770075112581253,
-0.09072478115558624,
-0.04768268018960953,
-0.11828918755054474,
0.09518729150295258,
0.2977321147918701,
0.07220054417848587,
-0.21887800097465515,
0.06159263104200363,
-0.46998897194862366,
0.6341657638... |
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