html_url stringlengths 51 51 | title stringlengths 6 280 | comments stringlengths 67 24.7k | body stringlengths 51 36.2k | __index_level_0__ int64 1 1.17k | comment_length int64 16 1.45k | text stringlengths 190 38.3k | embeddings list |
|---|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | From your feedback, seems to me there are two paths to consider now for supporting spark's `map` function in `map_nested` now:
1. Keep the current `pool.map` implementation, and add an if statement for the spark's `map` code (which is what I did in my current PR) -- the code change is just a few lines in the `map_nest... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 185 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.1312775611877441,
-0.9242454767227173,
-0.714408814907074,
1.547906517982483,
-0.12344713509082794,
-1.2318037748336792,
0.21573010087013245,
-1.112957239151001,
1.7478069067001343,
-0.8699119091033936,
0.3358379304409027,
-1.5951608419418335,
0.11269205808639526,
-0.5536026358604431,
... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Yup correct ! I think it's a nice path because it would be possible for users to define whatever parallel processing backend they want. I think we still need to discuss how that would look like in the `datasets` API : how to specify it has to use the "spark" parallel backend ? And how to specify the spark session param... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 94 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.1700689792633057,
-0.8764587044715881,
-0.8295596241950989,
1.5323126316070557,
-0.14994648098945618,
-1.2969651222229004,
0.13497783243656158,
-1.185383677482605,
1.7357656955718994,
-0.9287930727005005,
0.3179791569709778,
-1.6431914567947388,
0.10531292110681534,
-0.6245393753051758,... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Sure, please let me know if you have more updates regarding the API and implementation from the team.
For parameters we don't need to worry about setting them for Spark, because Spark will figure out the environment / number of worker nodes by itself, so it's preferable to just provide some parameter such as `use_sp... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 61 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.1626156568527222,
-0.9130444526672363,
-0.819238007068634,
1.623268961906433,
-0.14086875319480896,
-1.3001998662948608,
0.17571207880973816,
-1.1379238367080688,
1.7446753978729248,
-0.9287018179893494,
0.3551841974258423,
-1.6384711265563965,
0.11599162966012955,
-0.6144850254058838,
... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Hi! I wanted to check in to see if there is any update from the team.
A potential change of API I can think of is change the argument to `distributed_backend=...`, which accepts `str`, such as `load_dataset(..., distributed_backend="spark")`.
Implementation wise, we can add a class / function to abstract away the... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 66 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.1135056018829346,
-0.8810833096504211,
-0.759917676448822,
1.5548791885375977,
-0.17177189886569977,
-1.3717790842056274,
0.21412622928619385,
-1.1400351524353027,
1.7598307132720947,
-0.9239068627357483,
0.3762843906879425,
-1.5825845003128052,
0.10622622072696686,
-0.6503382921218872,... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | I found this quite interesting: https://github.com/joblib/joblib-spark with this syntax:
```python
with parallel_backend('spark', n_jobs=3):
...
```
cc @lu-wang-dl who might know better | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 21 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.1324222087860107,
-0.8346030712127686,
-0.8242124915122986,
1.6101762056350708,
-0.16984923183918,
-1.3630967140197754,
0.19239874184131622,
-1.0873650312423706,
1.7247227430343628,
-0.8591459393501282,
0.34679192304611206,
-1.6278042793273926,
0.032157622277736664,
-0.6453025341033936,... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Joblib spark is providing Spark backend for joblib. We can implement a general parallel backend like
```
with parallel_backend("<parallel-backedn>", n_jobs=..):
```
It can support multiprocessing , spark, ray, and etc. https://joblib.readthedocs.io/en/latest/parallel.html#joblib.parallel_backend | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 31 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.1696476936340332,
-0.8996327519416809,
-0.8012564182281494,
1.5973737239837646,
-0.20595121383666992,
-1.3456335067749023,
0.199664905667305,
-1.1072782278060913,
1.7262952327728271,
-0.902502179145813,
0.35168763995170593,
-1.6593899726867676,
0.004030873067677021,
-0.6340603828430176,... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Thank you @lhoestq for finding this repo. I validated that it can distribute downloading jobs with Spark to arbitrary cluster worker nodes evenly with `n_jobs=-1`.
For the API, I think it makes sense to define it as
```python
load_dataset(..., parallel_backend=<str>)
```
where `parallel_backend` can be `spark`, ... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 82 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.1136215925216675,
-0.8526799082756042,
-0.7578601241111755,
1.548964500427246,
-0.14344488084316254,
-1.3350157737731934,
0.25061964988708496,
-1.147214651107788,
1.8029663562774658,
-0.8905744552612305,
0.4033561944961548,
-1.6187058687210083,
0.05500779673457146,
-0.6764839291572571,
... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Hello @lhoestq, I wanted to follow up on my previous comment with some prototyping code that demonstrates how `map_nested` would be like if we unify `multiprocessing` and `spark` with `joblib`. The snippet hasn't hashed out the details such as dealing with `tqdm` yet.
In terms of API, the way of using multiprocessin... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 291 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.2034595012664795,
-0.8881780505180359,
-0.6831247806549072,
1.5652879476547241,
-0.16860422492027283,
-1.2131807804107666,
0.20357908308506012,
-1.0910589694976807,
1.6467254161834717,
-0.8577591776847839,
0.3062984049320221,
-1.5372023582458496,
0.061498045921325684,
-0.646149337291717... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Nice ! It should be quite easy to make the change then :)
I think adding spark support can actually be less than 20 lines of code and would roughly require one line of code to change in map_nested:
Maybe we can define a new `datasets.parallel` submodule that has the `parallel_backend()` context manager and a `par... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 108 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.1545783281326294,
-0.859910786151886,
-0.7641624212265015,
1.5488080978393555,
-0.18641091883182526,
-1.3068565130233765,
0.15636751055717468,
-1.1624020338058472,
1.7732734680175781,
-0.9171699285507202,
0.4086684584617615,
-1.600021243095398,
0.07167720794677734,
-0.620754063129425,
... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Although until we've switched to all the steps in `load_dataset` to use `datasets.parallel`, I would require the user to explicitly say which step should use Spark. Maybe something like this, but I'm not sure yet:
```python
from datasets.parallel import parallel_backend
with parallel_backend("spark", steps=["dow... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 106 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.0919241905212402,
-0.8664455413818359,
-0.7287660837173462,
1.494221806526184,
-0.16718550026416779,
-1.2634316682815552,
0.1762145608663559,
-1.2064971923828125,
1.6977709531784058,
-0.8560483455657959,
0.3460804224014282,
-1.6214559078216553,
0.02370581589639187,
-0.5955716371536255,
... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Sounds good! I like the partial rollout idea.
So for example `map_nested` would call `parallel_map` under the hood if `num_proc != 1` or `parallel_backend` is specified right?
I would be happy to start a PR next week to explore this path. | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 41 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.10128915309906,
-0.8351441621780396,
-0.819977343082428,
1.573537826538086,
-0.1171698048710823,
-1.377828598022461,
0.22747087478637695,
-1.1480613946914673,
1.8042625188827515,
-0.9218506813049316,
0.3684820234775543,
-1.6493340730667114,
0.09689544141292572,
-0.6743228435516357,
-0... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Awesome ! I think map_nested can call `parallel_map()` if num_proc > 1, and `parallel_map` can be responsible to use Pool.map by default or joblib. | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 173 | 24 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```pyth... | [
-1.1037724018096924,
-0.8533070087432861,
-0.7624935507774353,
1.5878700017929077,
-0.15887171030044556,
-1.3460118770599365,
0.24077929556369781,
-1.161879062652588,
1.76569664478302,
-0.9278571605682373,
0.3575015068054199,
-1.5890419483184814,
0.0936352014541626,
-0.6315961480140686,
... |
https://github.com/huggingface/datasets/issues/5797 | load_dataset is case sentitive? | Hi @haonan-li , thank you for the report! It seems to be a bug on the [`huggingface_hub`](https://github.com/huggingface/huggingface_hub) site, there is even no such dataset as `mbzuai/bactrian-x` on the Hub. I opened and [issue](https://github.com/huggingface/huggingface_hub/issues/1453) there. | ### Describe the bug
load_dataset() function is case sensitive?
### Steps to reproduce the bug
The following two code, get totally different behavior.
1. load_dataset('mbzuai/bactrian-x','en')
2. load_dataset('MBZUAI/Bactrian-X','en')
### Expected behavior
Compare 1 and 2.
1 will download all 52 subsets, sh... | 174 | 34 | load_dataset is case sentitive?
### Describe the bug
load_dataset() function is case sensitive?
### Steps to reproduce the bug
The following two code, get totally different behavior.
1. load_dataset('mbzuai/bactrian-x','en')
2. load_dataset('MBZUAI/Bactrian-X','en')
### Expected behavior
Compare 1 and 2.
... | [
-1.1215648651123047,
-0.94125896692276,
-0.7942426204681396,
1.5914305448532104,
-0.14628814160823822,
-1.256242036819458,
0.15065868198871613,
-0.9379811882972717,
1.6703059673309326,
-0.7767090201377869,
0.3225754499435425,
-1.7344516515731812,
-0.076690673828125,
-0.6716168522834778,
... |
https://github.com/huggingface/datasets/issues/5797 | load_dataset is case sentitive? | I think `load_dataset("mbzuai/bactrian-x")` shouldn't be loaded at all and raise an error but because of [this fallback](https://github.com/huggingface/datasets/blob/main/src/datasets/load.py#L1194) to packaged loaders when no other options are applicable, it loads the dataset with standard `json` loader instead of the... | ### Describe the bug
load_dataset() function is case sensitive?
### Steps to reproduce the bug
The following two code, get totally different behavior.
1. load_dataset('mbzuai/bactrian-x','en')
2. load_dataset('MBZUAI/Bactrian-X','en')
### Expected behavior
Compare 1 and 2.
1 will download all 52 subsets, sh... | 174 | 40 | load_dataset is case sentitive?
### Describe the bug
load_dataset() function is case sensitive?
### Steps to reproduce the bug
The following two code, get totally different behavior.
1. load_dataset('mbzuai/bactrian-x','en')
2. load_dataset('MBZUAI/Bactrian-X','en')
### Expected behavior
Compare 1 and 2.
... | [
-1.1350953578948975,
-0.8674898147583008,
-0.8282607793807983,
1.5295828580856323,
-0.166192427277565,
-1.207721471786499,
0.15263883769512177,
-1.0018264055252075,
1.701391577720642,
-0.8154732584953308,
0.23492677509784698,
-1.724178671836853,
-0.05635766312479973,
-0.6507952213287354,
... |
https://github.com/huggingface/datasets/issues/5791 | TIFF/TIF support | The issue with multichannel TIFF images has already been reported in Pillow (https://github.com/python-pillow/Pillow/issues/1888). We can't do much about it on our side.
Still, to avoid the error, you can bypass the default Pillow decoding and define a custom one as follows:
```python
import tifffile # pip install... | ### Feature request
I currently have a dataset (with tiff and json files) where I have to do this:
`wget path_to_data/images.zip && unzip images.zip`
`wget path_to_data/annotations.zip && unzip annotations.zip`
Would it make sense a contribution that supports these type of files?
### Motivation
instead o... | 176 | 92 | TIFF/TIF support
### Feature request
I currently have a dataset (with tiff and json files) where I have to do this:
`wget path_to_data/images.zip && unzip images.zip`
`wget path_to_data/annotations.zip && unzip annotations.zip`
Would it make sense a contribution that supports these type of files?
### M... | [
-1.146712064743042,
-0.9168297648429871,
-0.7759732604026794,
1.4893070459365845,
-0.19714568555355072,
-1.2737550735473633,
0.19573849439620972,
-1.0839648246765137,
1.696624994277954,
-0.8172821998596191,
0.44575682282447815,
-1.6353954076766968,
0.13750475645065308,
-0.5648261904716492,... |
https://github.com/huggingface/datasets/issues/5786 | Multiprocessing in a `filter` or `map` function with a Pytorch model | Hi ! PyTorch may hang when calling `load_state_dict()` in a subprocess. To fix that, set the multiprocessing start method to "spawn". Since `datasets` uses `multiprocess`, you should do:
```python
# Required to avoid issues with pytorch (otherwise hangs during load_state_dict in multiprocessing)
import multiproces... | ### Describe the bug
I am trying to use a Pytorch model loaded on CPUs with multiple processes with a `.map` or a `.filter` method.
Usually, when dealing with models that are non-pickable, creating a class such that the `map` function is the method `__call__`, and adding `reduce` helps to solve the problem.
Howe... | 177 | 67 | Multiprocessing in a `filter` or `map` function with a Pytorch model
### Describe the bug
I am trying to use a Pytorch model loaded on CPUs with multiple processes with a `.map` or a `.filter` method.
Usually, when dealing with models that are non-pickable, creating a class such that the `map` function is the met... | [
-1.2766934633255005,
-0.9636735916137695,
-0.6539439558982849,
1.5622365474700928,
-0.15562894940376282,
-1.1848043203353882,
0.27882060408592224,
-1.0496315956115723,
1.6472023725509644,
-0.8125002384185791,
0.3273656964302063,
-1.6085292100906372,
0.09558933973312378,
-0.6590056419372559... |
https://github.com/huggingface/datasets/issues/5786 | Multiprocessing in a `filter` or `map` function with a Pytorch model | @lhoestq Hello, I also encountered this problem but maybe with another reason. Here is my code:
```python
tokenizer = AutoTokenizer.from_pretrained(model_args.model_name_or_path, cache_dir=model_args.cache_dir, model_max_length=training_args.model_max_length)
data = load_dataset("json", data_files=data_args.train_fi... | ### Describe the bug
I am trying to use a Pytorch model loaded on CPUs with multiple processes with a `.map` or a `.filter` method.
Usually, when dealing with models that are non-pickable, creating a class such that the `map` function is the method `__call__`, and adding `reduce` helps to solve the problem.
Howe... | 177 | 64 | Multiprocessing in a `filter` or `map` function with a Pytorch model
### Describe the bug
I am trying to use a Pytorch model loaded on CPUs with multiple processes with a `.map` or a `.filter` method.
Usually, when dealing with models that are non-pickable, creating a class such that the `map` function is the met... | [
-1.2766934633255005,
-0.9636735916137695,
-0.6539439558982849,
1.5622365474700928,
-0.15562894940376282,
-1.1848043203353882,
0.27882060408592224,
-1.0496315956115723,
1.6472023725509644,
-0.8125002384185791,
0.3273656964302063,
-1.6085292100906372,
0.09558933973312378,
-0.6590056419372559... |
https://github.com/huggingface/datasets/issues/5786 | Multiprocessing in a `filter` or `map` function with a Pytorch model | @SkyAndCloud your issue doesn't seem related to the original post - could you open a new issue and provide more details ? (size of the dataset, number of cpus, how much time it took to run, `datasets` version) | ### Describe the bug
I am trying to use a Pytorch model loaded on CPUs with multiple processes with a `.map` or a `.filter` method.
Usually, when dealing with models that are non-pickable, creating a class such that the `map` function is the method `__call__`, and adding `reduce` helps to solve the problem.
Howe... | 177 | 38 | Multiprocessing in a `filter` or `map` function with a Pytorch model
### Describe the bug
I am trying to use a Pytorch model loaded on CPUs with multiple processes with a `.map` or a `.filter` method.
Usually, when dealing with models that are non-pickable, creating a class such that the `map` function is the met... | [
-1.2766934633255005,
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0.09558933973312378,
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https://github.com/huggingface/datasets/issues/5786 | Multiprocessing in a `filter` or `map` function with a Pytorch model | @lhoestq Hi, I just solved this problem. Because the input is extremely long and the tokenizer requests a large amount of memory, which leads to a OOM error and may eventually causes the hang. I didn't filter those too-long sentences because I thought `tokenizer` would stop once the length exceeds the `max_length`. How... | ### Describe the bug
I am trying to use a Pytorch model loaded on CPUs with multiple processes with a `.map` or a `.filter` method.
Usually, when dealing with models that are non-pickable, creating a class such that the `map` function is the method `__call__`, and adding `reduce` helps to solve the problem.
Howe... | 177 | 66 | Multiprocessing in a `filter` or `map` function with a Pytorch model
### Describe the bug
I am trying to use a Pytorch model loaded on CPUs with multiple processes with a `.map` or a `.filter` method.
Usually, when dealing with models that are non-pickable, creating a class such that the `map` function is the met... | [
-1.2766934633255005,
-0.9636735916137695,
-0.6539439558982849,
1.5622365474700928,
-0.15562894940376282,
-1.1848043203353882,
0.27882060408592224,
-1.0496315956115723,
1.6472023725509644,
-0.8125002384185791,
0.3273656964302063,
-1.6085292100906372,
0.09558933973312378,
-0.6590056419372559... |
https://github.com/huggingface/datasets/issues/5783 | Offset overflow while doing regex on a text column | Hi! This looks like an Arrow bug, but it can be avoided by reducing the `writer_batch_size`.
(`ds = ds.map(get_text_caption, writer_batch_size=100)` in Colab runs without issues)
| ### Describe the bug
`ArrowInvalid: offset overflow while concatenating arrays`
Same error as [here](https://github.com/huggingface/datasets/issues/615)
### Steps to reproduce the bug
Steps to reproduce: (dataset is a few GB big so try in colab maybe)
```
import datasets
import re
ds = datasets.lo... | 178 | 25 | Offset overflow while doing regex on a text column
### Describe the bug
`ArrowInvalid: offset overflow while concatenating arrays`
Same error as [here](https://github.com/huggingface/datasets/issues/615)
### Steps to reproduce the bug
Steps to reproduce: (dataset is a few GB big so try in colab maybe)
... | [
-1.2490326166152954,
-1.016045093536377,
-0.7192366719245911,
1.559781789779663,
-0.14998488128185272,
-1.2319121360778809,
0.13393017649650574,
-1.0625097751617432,
1.6829222440719604,
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0.3222373425960541,
-1.6455180644989014,
-0.008762655779719353,
-0.6353757381439209... |
https://github.com/huggingface/datasets/issues/5782 | Support for various audio-loading backends instead of always relying on SoundFile | Hi!
You can use `set_transform`/`with_transform` to define a custom decoding for audio formats not supported by `soundfile`:
```python
audio_dataset_amr = Dataset.from_dict({"audio": ["audio_samples/audio.amr"]})
def decode_audio(batch):
batch["audio"] = [read_ffmpeg(audio_path) for audio_path in batch["a... | ### Feature request
Introduce an option to select from a variety of audio-loading backends rather than solely relying on the SoundFile library. For instance, if the ffmpeg library is installed, it can serve as a fallback loading option.
### Motivation
- The SoundFile library, used in [features/audio.py](https://gith... | 179 | 57 | Support for various audio-loading backends instead of always relying on SoundFile
### Feature request
Introduce an option to select from a variety of audio-loading backends rather than solely relying on the SoundFile library. For instance, if the ffmpeg library is installed, it can serve as a fallback loading option... | [
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0.3129993975162506,
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0.0504981204867363,
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... |
https://github.com/huggingface/datasets/issues/5782 | Support for various audio-loading backends instead of always relying on SoundFile | Considering the number of times a custom decoding transform has been suggested as a solution, an example in the [docs](https://huggingface.co/docs/datasets/process#format-transform) would be nice.
cc @stevhliu | ### Feature request
Introduce an option to select from a variety of audio-loading backends rather than solely relying on the SoundFile library. For instance, if the ffmpeg library is installed, it can serve as a fallback loading option.
### Motivation
- The SoundFile library, used in [features/audio.py](https://gith... | 179 | 25 | Support for various audio-loading backends instead of always relying on SoundFile
### Feature request
Introduce an option to select from a variety of audio-loading backends rather than solely relying on the SoundFile library. For instance, if the ffmpeg library is installed, it can serve as a fallback loading option... | [
-1.2506405115127563,
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1.4030389785766602,
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0.13924826681613922,
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1.6291160583496094,
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0.3129993975162506,
-1.6759306192398071,
0.0504981204867363,
-0.5894086360931396,
... |
https://github.com/huggingface/datasets/issues/5781 | Error using `load_datasets` | It looks like an issue with your installation of scipy, can you try reinstalling it ? | ### Describe the bug
I tried to load a dataset using the `datasets` library in a conda jupyter notebook and got the below error.
```
ImportError: dlopen(/Users/gilbertyoung/miniforge3/envs/review_sense/lib/python3.8/site-packages/scipy/sparse/linalg/_isolve/_iterative.cpython-38-darwin.so, 0x0002): Library not ... | 180 | 16 | Error using `load_datasets`
### Describe the bug
I tried to load a dataset using the `datasets` library in a conda jupyter notebook and got the below error.
```
ImportError: dlopen(/Users/gilbertyoung/miniforge3/envs/review_sense/lib/python3.8/site-packages/scipy/sparse/linalg/_isolve/_iterative.cpython-38-da... | [
-1.1035425662994385,
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1.4833195209503174,
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0.10321732610464096,
-0.8732654452323914,
1.5320765972137451,
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0.27652740478515625,
-1.597454309463501,
-0.2172369658946991,
-0.5587021708488464... |
https://github.com/huggingface/datasets/issues/5778 | Schrödinger's dataset_dict | Hi ! Passing `data_files="path/test.json"` is equivalent to `data_files={"train": ["path/test.json"]}`, that's why you end up with a train split. If you don't pass `data_files=`, then split names are inferred from the data files names | ### Describe the bug
If you use load_dataset('json', data_files="path/test.json"), it will return DatasetDict({train:...}).
And if you use load_dataset("path"), it will return DatasetDict({test:...}).
Why can't the output behavior be unified?
### Steps to reproduce the bug
as description above.
### Expected b... | 181 | 33 | Schrödinger's dataset_dict
### Describe the bug
If you use load_dataset('json', data_files="path/test.json"), it will return DatasetDict({train:...}).
And if you use load_dataset("path"), it will return DatasetDict({test:...}).
Why can't the output behavior be unified?
### Steps to reproduce the bug
as descr... | [
-1.182214617729187,
-1.0347455739974976,
-0.8008841872215271,
1.6343438625335693,
-0.1948118507862091,
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0.12878867983818054,
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1.706277847290039,
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0.266997754573822,
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0.01634538732469082,
-0.6312517523765564,
... |
https://github.com/huggingface/datasets/issues/5777 | datasets.load_dataset("code_search_net", "python") : NotADirectoryError: [Errno 20] Not a directory | Note:
I listed the datasets and grepped around to find what appears to be an alternative source for this:
raw_datasets = load_dataset("espejelomar/code_search_net_python_10000_examples", "python") | ### Describe the bug
While checking out the [tokenizer tutorial](https://huggingface.co/course/chapter6/2?fw=pt), i noticed getting an error while initially downloading the python dataset used in the examples.
The [collab with the error is here](https://colab.research.google.com/github/huggingface/notebooks/blob/ma... | 182 | 23 | datasets.load_dataset("code_search_net", "python") : NotADirectoryError: [Errno 20] Not a directory
### Describe the bug
While checking out the [tokenizer tutorial](https://huggingface.co/course/chapter6/2?fw=pt), i noticed getting an error while initially downloading the python dataset used in the examples.
The ... | [
-1.2191482782363892,
-0.8311535716056824,
-0.7604543566703796,
1.4691193103790283,
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0.09687452018260956,
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1.5775238275527954,
-0.7166644334793091,
0.2938610911369324,
-1.6695624589920044,
-0.05842898041009903,
-0.592119634151458... |
https://github.com/huggingface/datasets/issues/5777 | datasets.load_dataset("code_search_net", "python") : NotADirectoryError: [Errno 20] Not a directory | Thanks for reporting, @jason-brian-anderson.
Yes, this is a known issue: the [CodeSearchNet](https://github.com/github/CodeSearchNet) repo has been archived (Apr 11, 2023) and their source data files are no longer accessible in their S3: e.g. https://s3.amazonaws.com/code-search-net/CodeSearchNet/v2/python.zip gives... | ### Describe the bug
While checking out the [tokenizer tutorial](https://huggingface.co/course/chapter6/2?fw=pt), i noticed getting an error while initially downloading the python dataset used in the examples.
The [collab with the error is here](https://colab.research.google.com/github/huggingface/notebooks/blob/ma... | 182 | 60 | datasets.load_dataset("code_search_net", "python") : NotADirectoryError: [Errno 20] Not a directory
### Describe the bug
While checking out the [tokenizer tutorial](https://huggingface.co/course/chapter6/2?fw=pt), i noticed getting an error while initially downloading the python dataset used in the examples.
The ... | [
-1.2191482782363892,
-0.8311535716056824,
-0.7604543566703796,
1.4691193103790283,
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0.09687452018260956,
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1.5775238275527954,
-0.7166644334793091,
0.2938610911369324,
-1.6695624589920044,
-0.05842898041009903,
-0.592119634151458... |
https://github.com/huggingface/datasets/issues/5777 | datasets.load_dataset("code_search_net", "python") : NotADirectoryError: [Errno 20] Not a directory | This issue is fixed because we are hosting the CodeSearchNet data files in the Hugging Face Hub. See: https://huggingface.co/datasets/code_search_net/discussions/7 | ### Describe the bug
While checking out the [tokenizer tutorial](https://huggingface.co/course/chapter6/2?fw=pt), i noticed getting an error while initially downloading the python dataset used in the examples.
The [collab with the error is here](https://colab.research.google.com/github/huggingface/notebooks/blob/ma... | 182 | 19 | datasets.load_dataset("code_search_net", "python") : NotADirectoryError: [Errno 20] Not a directory
### Describe the bug
While checking out the [tokenizer tutorial](https://huggingface.co/course/chapter6/2?fw=pt), i noticed getting an error while initially downloading the python dataset used in the examples.
The ... | [
-1.2191482782363892,
-0.8311535716056824,
-0.7604543566703796,
1.4691193103790283,
-0.09448185563087463,
-1.2026780843734741,
0.09687452018260956,
-1.0932890176773071,
1.5775238275527954,
-0.7166644334793091,
0.2938610911369324,
-1.6695624589920044,
-0.05842898041009903,
-0.592119634151458... |
https://github.com/huggingface/datasets/issues/5777 | datasets.load_dataset("code_search_net", "python") : NotADirectoryError: [Errno 20] Not a directory | Thanks @hamelsmu for the Zenodo link. I am adding it to the dataset card on the Hugging Face Hub, so that the community knows about this "official" source data. I guess this link is not well known, because some community members already hosted an "unofficial" version of the data on Zenodo as well: https://zenodo.org/re... | ### Describe the bug
While checking out the [tokenizer tutorial](https://huggingface.co/course/chapter6/2?fw=pt), i noticed getting an error while initially downloading the python dataset used in the examples.
The [collab with the error is here](https://colab.research.google.com/github/huggingface/notebooks/blob/ma... | 182 | 54 | datasets.load_dataset("code_search_net", "python") : NotADirectoryError: [Errno 20] Not a directory
### Describe the bug
While checking out the [tokenizer tutorial](https://huggingface.co/course/chapter6/2?fw=pt), i noticed getting an error while initially downloading the python dataset used in the examples.
The ... | [
-1.2191482782363892,
-0.8311535716056824,
-0.7604543566703796,
1.4691193103790283,
-0.09448185563087463,
-1.2026780843734741,
0.09687452018260956,
-1.0932890176773071,
1.5775238275527954,
-0.7166644334793091,
0.2938610911369324,
-1.6695624589920044,
-0.05842898041009903,
-0.592119634151458... |
https://github.com/huggingface/datasets/issues/5773 | train_dataset does not implement __len__ | Thanks for reporting, @v-yunbin.
Could you please give more details, the steps to reproduce the bug, the complete error back trace and the environment information (`datasets-cli env`)? | when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learning rate scheduler.` | 184 | 27 | train_dataset does not implement __len__
when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learni... | [
-1.3317745923995972,
-0.864311695098877,
-0.7249059677124023,
1.3925011157989502,
-0.21591134369373322,
-1.2339130640029907,
0.20677152276039124,
-1.1794809103012085,
1.6692954301834106,
-0.8805052042007446,
0.2583061158657074,
-1.5658608675003052,
0.014881766401231289,
-0.5769771933555603... |
https://github.com/huggingface/datasets/issues/5773 | train_dataset does not implement __len__ | this is a detail error info from transformers：
```
Traceback (most recent call last):
File "finetune.py", line 177, in <module>
whisper_finetune(traindir,devdir,outdir)
File "finetune.py", line 161, in whisper_finetune
trainer = Seq2SeqTrainer(
File "/home/ybZhang/miniconda3/envs/whister/lib/python... | when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learning rate scheduler.` | 184 | 73 | train_dataset does not implement __len__
when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learni... | [
-1.2401282787322998,
-0.8403675556182861,
-0.6372190117835999,
1.5290462970733643,
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0.17171244323253632,
-1.117249608039856,
1.4804695844650269,
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0.33755746483802795,
-1.6157748699188232,
0.045893438160419464,
-0.616722345352172... |
https://github.com/huggingface/datasets/issues/5773 | train_dataset does not implement __len__ | How did you create `train_dataset`? The `datasets` library does not appear in your stack trace.
We need more information in order to reproduce the issue... | when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learning rate scheduler.` | 184 | 25 | train_dataset does not implement __len__
when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learni... | [
-1.300323247909546,
-0.8498461842536926,
-0.7057887315750122,
1.409334659576416,
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0.22090476751327515,
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1.697435975074768,
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0.26459142565727234,
-1.550510287284851,
-0.002974244300276041,
-0.5868687033653259,... |
https://github.com/huggingface/datasets/issues/5773 | train_dataset does not implement __len__ | ```
def asr_dataset(traindir,devdir):
we_voice = IterableDatasetDict()
#we_voice["train"] = load_from_disk(traindir,streaming=True)
#we_voice["test"]= load_from_disk(devdir,streaming=True)
we_voice["train"] = load_dataset("csv",data_files=os.path.join(traindir,"train.csv"),split="train",streaming=T... | when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learning rate scheduler.` | 184 | 29 | train_dataset does not implement __len__
when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learni... | [
-1.2421706914901733,
-0.9405226111412048,
-0.5692014098167419,
1.5513588190078735,
-0.22297008335590363,
-1.0597989559173584,
0.22433164715766907,
-1.0332162380218506,
1.4980961084365845,
-0.8753895163536072,
0.4475371837615967,
-1.5902633666992188,
0.0031615234911441803,
-0.62268716096878... |
https://github.com/huggingface/datasets/issues/5773 | train_dataset does not implement __len__ | As you are using iterable datasets (`streaming=True`), their length is not defined.
You should:
- Either use non-iterable datasets, which have a defined length: use `DatasetDict` and not passing `streaming=True`
- Or pass `args.max_steps` to the `Trainer` | when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learning rate scheduler.` | 184 | 37 | train_dataset does not implement __len__
when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learni... | [
-1.2005255222320557,
-0.9399008750915527,
-0.7182595133781433,
1.5036914348602295,
-0.18478284776210785,
-1.2923835515975952,
0.16731959581375122,
-1.186020016670227,
1.6750397682189941,
-0.8794461488723755,
0.40599796175956726,
-1.627034306526184,
-0.0019488073885440826,
-0.59780639410018... |
https://github.com/huggingface/datasets/issues/5773 | train_dataset does not implement __len__ | @albertvillanova I think @v-yunbin, myself, and others might be slightly confused about max_steps and how it differs from num_train_epochs. | when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learning rate scheduler.` | 184 | 19 | train_dataset does not implement __len__
when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learni... | [
-1.3105714321136475,
-0.943544864654541,
-0.6800290942192078,
1.4268354177474976,
-0.23236320912837982,
-1.1894943714141846,
0.18517981469631195,
-1.0944072008132935,
1.6037583351135254,
-0.8916651010513306,
0.3195977210998535,
-1.510530948638916,
-0.03508378192782402,
-0.6048634648323059,... |
https://github.com/huggingface/datasets/issues/5773 | train_dataset does not implement __len__ | @lkurlandski A **step** is referring to optimizer's update after back propagation, and it's associated with a batch of data. For example, if a dataset contains 64 examples and you have an overall batch size of 4, then an epoch will have 64/4=16 batches. Therefore, in one epoch, you will have 16 optimizer **steps**. | when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learning rate scheduler.` | 184 | 53 | train_dataset does not implement __len__
when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learni... | [
-1.2766127586364746,
-1.0399574041366577,
-0.7259251475334167,
1.4400029182434082,
-0.27168333530426025,
-1.2861191034317017,
0.15733329951763153,
-1.1277066469192505,
1.6771312952041626,
-0.9008724689483643,
0.2899356186389923,
-1.581748366355896,
0.033331915736198425,
-0.6537350416183472... |
https://github.com/huggingface/datasets/issues/5769 | Tiktoken tokenizers are not pickable | Thanks for reporting, @markovalexander.
Unfortunately, I'm not able to reproduce the issue: the `tiktoken` tokenizer can be used within `Dataset.map`, both in my local machine and in a Colab notebook: https://colab.research.google.com/drive/1DhJroZgk0sNFJ2Mrz-jYgrmh9jblXaCG?usp=sharing
Are you sure you are using ... | ### Describe the bug
Since tiktoken tokenizer is not pickable, it is not possible to use it inside `dataset.map()` with multiprocessing enabled. However, you [made](https://github.com/huggingface/datasets/issues/5536) tiktoken's tokenizers pickable in `datasets==2.10.0` for caching. For some reason, this logic does no... | 186 | 40 | Tiktoken tokenizers are not pickable
### Describe the bug
Since tiktoken tokenizer is not pickable, it is not possible to use it inside `dataset.map()` with multiprocessing enabled. However, you [made](https://github.com/huggingface/datasets/issues/5536) tiktoken's tokenizers pickable in `datasets==2.10.0` for cach... | [
-1.1800875663757324,
-0.9220454096794128,
-0.6876906752586365,
1.4953796863555908,
-0.1720784306526184,
-1.163080096244812,
0.14514422416687012,
-1.0526939630508423,
1.6667680740356445,
-0.7231392860412598,
0.2982511520385742,
-1.713374376296997,
0.008714422583580017,
-0.6296529173851013,
... |
https://github.com/huggingface/datasets/issues/5768 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1 | I am not able to reproduce your issue: the dataset loads perfectly on my local machine and on a Colab notebook: https://colab.research.google.com/drive/1Fbdoa1JdNz8DOdX6gmIsOK1nCT8Abj4O?usp=sharing
```python
In [1]: from datasets import load_dataset
In [2]: ds = load_dataset("squad")
Downloading builder script: 1... | ### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properly.
This is not a problem with "squad_v2" dataset for e... | 187 | 134 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1
### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properl... | [
-1.269569754600525,
-0.9472349286079407,
-0.6904863119125366,
1.4093470573425293,
-0.18275101482868195,
-1.1904391050338745,
0.07730994373559952,
-1.1222432851791382,
1.683840036392212,
-0.731477677822113,
0.2488894760608673,
-1.6942880153656006,
0.0029024872928857803,
-0.5075297355651855,... |
https://github.com/huggingface/datasets/issues/5768 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1 | I am at a complete loss for what's happening here. A quick summary, I have 3 machines to try this with:
1) My windows 10 laptop
2) Linux machine1, super computer login node
3) Linux machine2, super computer compute node
Let's define the following as a test script for the machines:
```
import traceback
import... | ### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properly.
This is not a problem with "squad_v2" dataset for e... | 187 | 1,237 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1
### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properl... | [
-1.2798125743865967,
-0.9700546264648438,
-0.6780890822410583,
1.3986114263534546,
-0.1794208586215973,
-1.1662852764129639,
0.08255334943532944,
-1.1187233924865723,
1.736251950263977,
-0.7445816993713379,
0.2425457239151001,
-1.6792999505996704,
-0.001762485597282648,
-0.5085324645042419... |
https://github.com/huggingface/datasets/issues/5768 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1 | I'm back on linux machine 1 (login node) now. After submitting that as a job to machine 2 and it failing with TypeError, linux machine 1 now produces identical traceback to machine 2:
> (arkroyal) [yr3g17@cyan52 squad_qanswering]$ python
> Python 3.10.8 (main, Nov 24 2022, 14:13:03) [GCC 11.2.0] on linux
> Type "h... | ### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properly.
This is not a problem with "squad_v2" dataset for e... | 187 | 156 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1
### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properl... | [
-1.2868084907531738,
-0.962947428226471,
-0.690953254699707,
1.4309908151626587,
-0.1983925849199295,
-1.1768583059310913,
0.08960655331611633,
-1.1221787929534912,
1.7209266424179077,
-0.7430174350738525,
0.25335395336151123,
-1.6798754930496216,
-0.0031185937114059925,
-0.518686652183532... |
https://github.com/huggingface/datasets/issues/5768 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1 | I see this is quite a complex use case...
Let's try multiple things:
- First, update `datasets` and make sure you use the same version in all machines, so that we can easily compare different behaviors.
```
pip install -U datasets
```
- Second, wherever you run the `load_dataset("squad")` command, make su... | ### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properly.
This is not a problem with "squad_v2" dataset for e... | 187 | 244 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1
### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properl... | [
-1.234336018562317,
-0.9501729607582092,
-0.6695875525474548,
1.396459698677063,
-0.17038269340991974,
-1.2012196779251099,
0.11567026376724243,
-1.0877516269683838,
1.7662417888641357,
-0.7621121406555176,
0.2449980229139328,
-1.7011770009994507,
-0.004717961419373751,
-0.5323485136032104... |
https://github.com/huggingface/datasets/issues/5768 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1 | Additionally, we just had an infrastructure issue on the Hugging Face Hub at around 11:30 today. That might have contributed to the connectivity issue... It is fixed now.
https://status.huggingface.co/ | ### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properly.
This is not a problem with "squad_v2" dataset for e... | 187 | 29 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1
### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properl... | [
-1.249747633934021,
-0.9587093591690063,
-0.6873729228973389,
1.4481257200241089,
-0.16937844455242157,
-1.1766108274459839,
0.06997683644294739,
-1.0514603853225708,
1.7328084707260132,
-0.7514103055000305,
0.25581738352775574,
-1.7040141820907593,
-0.0076935249380767345,
-0.4915046095848... |
https://github.com/huggingface/datasets/issues/5768 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1 | Hi again, thanks for your help and insight Albert Villanova.
It's all working now, so thank you for that. For the benefit of anyone else who ends up in this thread, I solved the problem by addressing Albert's advice:
(1) Both Windows and Linux machine 1 (have internet access) and can now access the SQuAD dataset.... | ### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properly.
This is not a problem with "squad_v2" dataset for e... | 187 | 272 | load_dataset("squad") doesn't work in 2.7.1 and 2.10.1
### Describe the bug
There is an issue that seems to be unique to the "squad" dataset, in which it cannot be loaded using standard methods. This issue is most quickly reproduced from the command line, using the HF examples to verify a dataset is loaded properl... | [
-1.2961723804473877,
-0.9696152210235596,
-0.6804463267326355,
1.3996741771697998,
-0.19085818529129028,
-1.1812217235565186,
0.09888231754302979,
-1.1031193733215332,
1.7116256952285767,
-0.766923725605011,
0.21840974688529968,
-1.687854290008545,
0.0072790589183568954,
-0.483093768358230... |
https://github.com/huggingface/datasets/issues/5766 | Support custom feature types | Hi ! Interesting :) What kind of new types would you like to use ?
Note that you can already implement your own decoding by using `set_transform` that can decode data on-the-fly when rows are accessed | ### Feature request
I think it would be nice to allow registering custom feature types with the 🤗 Datasets library. For example, allow to do something along the following lines:
```
from datasets.features import register_feature_type # this would be a new function
@register_feature_type
class CustomFeature... | 189 | 36 | Support custom feature types
### Feature request
I think it would be nice to allow registering custom feature types with the 🤗 Datasets library. For example, allow to do something along the following lines:
```
from datasets.features import register_feature_type # this would be a new function
@register_fe... | [
-1.1635470390319824,
-0.9343589544296265,
-0.8181957602500916,
1.486406922340393,
-0.15031062066555023,
-1.2779946327209473,
0.21437889337539673,
-1.0857570171356201,
1.6582823991775513,
-0.8129419684410095,
0.3232392370700836,
-1.6623361110687256,
0.051158398389816284,
-0.6794191598892212... |
https://github.com/huggingface/datasets/issues/5766 | Support custom feature types | An interesting proposal indeed.
Pandas and Polars have the "extension API", so doing something similar on our side could be useful, too. However, this requires defining a common interface for the existing feature types before discussing the API/workflow for defining/sharing custom feature types, and this could take... | ### Feature request
I think it would be nice to allow registering custom feature types with the 🤗 Datasets library. For example, allow to do something along the following lines:
```
from datasets.features import register_feature_type # this would be a new function
@register_feature_type
class CustomFeature... | 189 | 63 | Support custom feature types
### Feature request
I think it would be nice to allow registering custom feature types with the 🤗 Datasets library. For example, allow to do something along the following lines:
```
from datasets.features import register_feature_type # this would be a new function
@register_fe... | [
-1.165695309638977,
-0.9480094909667969,
-0.8156073093414307,
1.4876782894134521,
-0.14888717234134674,
-1.2785828113555908,
0.21639160811901093,
-1.0897376537322998,
1.6667289733886719,
-0.8262074589729309,
0.3295639157295227,
-1.6618900299072266,
0.037548378109931946,
-0.6801649928092957... |
https://github.com/huggingface/datasets/issues/5766 | Support custom feature types | Thank you for your replies! @lhoestq I have a use case involving whole-slide images in digital pathology. These are very large images (potentially gigapixel scale), so standard image tools are not suitable. Essentially, encoding/decoding can be done from/to [`OpenSlide`](https://openslide.org/api/python/) objects. Thou... | ### Feature request
I think it would be nice to allow registering custom feature types with the 🤗 Datasets library. For example, allow to do something along the following lines:
```
from datasets.features import register_feature_type # this would be a new function
@register_feature_type
class CustomFeature... | 189 | 168 | Support custom feature types
### Feature request
I think it would be nice to allow registering custom feature types with the 🤗 Datasets library. For example, allow to do something along the following lines:
```
from datasets.features import register_feature_type # this would be a new function
@register_fe... | [
-1.1689321994781494,
-0.9416799545288086,
-0.8087755441665649,
1.4847126007080078,
-0.1473194807767868,
-1.2755950689315796,
0.21675023436546326,
-1.0938944816589355,
1.6654192209243774,
-0.8183121085166931,
0.3229815661907196,
-1.6641901731491089,
0.03850048780441284,
-0.6814858317375183,... |
https://github.com/huggingface/datasets/issues/5765 | ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text'] | You need to remove the `text` and `text_en` columns before passing the dataset to the `DataLoader` to avoid this error:
```python
tokenized_datasets = tokenized_datasets.remove_columns(["text", "text_en"])
```
| ### Describe the bug
Following is my code that I am trying to run, but facing an error (have attached the whole error below):
My code:
```
from collections import OrderedDict
import warnings
import flwr as fl
import torch
import numpy as np
import random
from torch.utils.data import DataLoader
from... | 190 | 26 | ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text']
### Describe the bug
Following is my code that I am trying to run, but facing an error (have attached the whole error below):
My code:
```
from collections import OrderedDict
imp... | [
-1.2584954500198364,
-0.941353976726532,
-0.6706098914146423,
1.5620760917663574,
-0.12782131135463715,
-1.0384528636932373,
0.11514334380626678,
-1.174659252166748,
1.5971934795379639,
-0.8362162113189697,
0.2784945070743561,
-1.6470086574554443,
0.01891913264989853,
-0.5115105509757996,
... |
https://github.com/huggingface/datasets/issues/5765 | ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text'] | Thanks @mariosasko. Now I am getting this error:
```
Traceback (most recent call last):
File "client_2.py", line 138, in <module>
main()
File "client_2.py", line 134, in main
fl.client.start_numpy_client(server_address="localhost:8080", client=IMDBClient())
File "/home/saurav/.local/lib/python3.8... | ### Describe the bug
Following is my code that I am trying to run, but facing an error (have attached the whole error below):
My code:
```
from collections import OrderedDict
import warnings
import flwr as fl
import torch
import numpy as np
import random
from torch.utils.data import DataLoader
from... | 190 | 550 | ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text']
### Describe the bug
Following is my code that I am trying to run, but facing an error (have attached the whole error below):
My code:
```
from collections import OrderedDict
imp... | [
-1.2584954500198364,
-0.941353976726532,
-0.6706098914146423,
1.5620760917663574,
-0.12782131135463715,
-1.0384528636932373,
0.11514334380626678,
-1.174659252166748,
1.5971934795379639,
-0.8362162113189697,
0.2784945070743561,
-1.6470086574554443,
0.01891913264989853,
-0.5115105509757996,
... |
https://github.com/huggingface/datasets/issues/5765 | ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text'] | Please also remove/comment these lines:
```python
tokenized_datasets = tokenized_datasets.remove_columns("attention_mask")
tokenized_datasets = tokenized_datasets.remove_columns("input_ids")
tokenized_datasets = tokenized_datasets.remove_columns("label")
``` | ### Describe the bug
Following is my code that I am trying to run, but facing an error (have attached the whole error below):
My code:
```
from collections import OrderedDict
import warnings
import flwr as fl
import torch
import numpy as np
import random
from torch.utils.data import DataLoader
from... | 190 | 16 | ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text']
### Describe the bug
Following is my code that I am trying to run, but facing an error (have attached the whole error below):
My code:
```
from collections import OrderedDict
imp... | [
-1.2584954500198364,
-0.941353976726532,
-0.6706098914146423,
1.5620760917663574,
-0.12782131135463715,
-1.0384528636932373,
0.11514334380626678,
-1.174659252166748,
1.5971934795379639,
-0.8362162113189697,
0.2784945070743561,
-1.6470086574554443,
0.01891913264989853,
-0.5115105509757996,
... |
https://github.com/huggingface/datasets/issues/5765 | ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text'] | Thanks @mariosasko .
Now, I am trying out this [tutorial](https://flower.dev/docs/quickstart-huggingface.html) which basically trains distil-BERT with IMDB dataset (very similar to this [tutorial](https://huggingface.co/docs/transformers/main/tasks/sequence_classification)). But I don't know why my accuracy isn't in... | ### Describe the bug
Following is my code that I am trying to run, but facing an error (have attached the whole error below):
My code:
```
from collections import OrderedDict
import warnings
import flwr as fl
import torch
import numpy as np
import random
from torch.utils.data import DataLoader
from... | 190 | 376 | ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text']
### Describe the bug
Following is my code that I am trying to run, but facing an error (have attached the whole error below):
My code:
```
from collections import OrderedDict
imp... | [
-1.2584954500198364,
-0.941353976726532,
-0.6706098914146423,
1.5620760917663574,
-0.12782131135463715,
-1.0384528636932373,
0.11514334380626678,
-1.174659252166748,
1.5971934795379639,
-0.8362162113189697,
0.2784945070743561,
-1.6470086574554443,
0.01891913264989853,
-0.5115105509757996,
... |
https://github.com/huggingface/datasets/issues/5764 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1 | Thanks for reporting, @sauravtii.
Unfortunately, I'm not able to reproduce the issue:
```python
In [1]: from datasets import load_dataset
In [2]: ds = load_dataset("josianem/imdb")
In [2]: ds
Out[2]:
DatasetDict({
train: Dataset({
features: ['text', 'label'],
num_rows: 25799
})... | ### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset is not getting loaded and gives the error message as the following:
```
Traceback (most rece... | 191 | 72 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1
### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset ... | [
-1.1990083456039429,
-0.8942093253135681,
-0.6647194027900696,
1.4132366180419922,
-0.15078669786453247,
-1.2496379613876343,
0.11945269256830215,
-1.0314009189605713,
1.4859802722930908,
-0.6882316470146179,
0.23124617338180542,
-1.6536903381347656,
-0.1239284798502922,
-0.501595437526702... |
https://github.com/huggingface/datasets/issues/5764 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1 | Thanks @albertvillanova. I am facing another issue now
```
Traceback (most recent call last):
File "sample.py", line 4, in <module>
dataset = load_dataset("josianem/imdb")
File "/home/saurav/.local/lib/python3.8/site-packages/datasets/load.py", line 1112, in load_dataset
builder_instance.download_an... | ### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset is not getting loaded and gives the error message as the following:
```
Traceback (most rece... | 191 | 99 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1
### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset ... | [
-1.1990083456039429,
-0.8942093253135681,
-0.6647194027900696,
1.4132366180419922,
-0.15078669786453247,
-1.2496379613876343,
0.11945269256830215,
-1.0314009189605713,
1.4859802722930908,
-0.6882316470146179,
0.23124617338180542,
-1.6536903381347656,
-0.1239284798502922,
-0.501595437526702... |
https://github.com/huggingface/datasets/issues/5764 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1 | Your connection didn't work and you got an empty dataset (`num_bytes=0, num_examples=0`):
```
datasets.utils.info_utils.NonMatchingSplitsSizesError:
[
{
'expected': SplitInfo(name='train', num_bytes=34501348, num_examples=25799, dataset_name='imdb'),
'recorded': SplitInfo(name='train', num_b... | ### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset is not getting loaded and gives the error message as the following:
```
Traceback (most rece... | 191 | 145 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1
### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset ... | [
-1.1990083456039429,
-0.8942093253135681,
-0.6647194027900696,
1.4132366180419922,
-0.15078669786453247,
-1.2496379613876343,
0.11945269256830215,
-1.0314009189605713,
1.4859802722930908,
-0.6882316470146179,
0.23124617338180542,
-1.6536903381347656,
-0.1239284798502922,
-0.501595437526702... |
https://github.com/huggingface/datasets/issues/5764 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1 | After pasting the link in the browser, it did start the download so it seems that the link is working. But even after including the `download_mode` in my code I am facing the same issue:
Error:
```
Traceback (most recent call last):
File "sample.py", line 4, in <module>
dataset = load_dataset("josianem/imd... | ### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset is not getting loaded and gives the error message as the following:
```
Traceback (most rece... | 191 | 148 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1
### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset ... | [
-1.1990083456039429,
-0.8942093253135681,
-0.6647194027900696,
1.4132366180419922,
-0.15078669786453247,
-1.2496379613876343,
0.11945269256830215,
-1.0314009189605713,
1.4859802722930908,
-0.6882316470146179,
0.23124617338180542,
-1.6536903381347656,
-0.1239284798502922,
-0.501595437526702... |
https://github.com/huggingface/datasets/issues/5764 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1 | I have tried again to reproduce your issue without success: the dataset loads perfectly, both in my local machine and in a Colab notebook.
- See: https://colab.research.google.com/drive/1dky3T0XGFuldggy22NNQQN-UqOFqvnuY?usp=sharing
I think the cause maight be that you are using a very old version of `datasets`. Ple... | ### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset is not getting loaded and gives the error message as the following:
```
Traceback (most rece... | 191 | 56 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1
### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset ... | [
-1.1990083456039429,
-0.8942093253135681,
-0.6647194027900696,
1.4132366180419922,
-0.15078669786453247,
-1.2496379613876343,
0.11945269256830215,
-1.0314009189605713,
1.4859802722930908,
-0.6882316470146179,
0.23124617338180542,
-1.6536903381347656,
-0.1239284798502922,
-0.501595437526702... |
https://github.com/huggingface/datasets/issues/5764 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1 | That worked!! Thanks @albertvillanova : )
```
Downloading builder script: 100%|███████| 4.20k/4.20k [00:00<00:00, 6.69MB/s]
Downloading metadata: 100%|█████████████| 2.60k/2.60k [00:00<00:00, 3.41MB/s]
Downloading readme: 100%|███████████████| 7.52k/7.52k [00:00<00:00, 12.6MB/s]
Downloading and preparing dataset... | ### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset is not getting loaded and gives the error message as the following:
```
Traceback (most rece... | 191 | 86 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1
### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset ... | [
-1.1990083456039429,
-0.8942093253135681,
-0.6647194027900696,
1.4132366180419922,
-0.15078669786453247,
-1.2496379613876343,
0.11945269256830215,
-1.0314009189605713,
1.4859802722930908,
-0.6882316470146179,
0.23124617338180542,
-1.6536903381347656,
-0.1239284798502922,
-0.501595437526702... |
https://github.com/huggingface/datasets/issues/5764 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1 | That is because the cache got the "empty" download file the first time you tried and got the connection error.
Then, once you no longer get the connection error, you need to refresh the cache by passing `download_mode="force_redownload"`. | ### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset is not getting loaded and gives the error message as the following:
```
Traceback (most rece... | 191 | 38 | ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1
### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset ... | [
-1.1990083456039429,
-0.8942093253135681,
-0.6647194027900696,
1.4132366180419922,
-0.15078669786453247,
-1.2496379613876343,
0.11945269256830215,
-1.0314009189605713,
1.4859802722930908,
-0.6882316470146179,
0.23124617338180542,
-1.6536903381347656,
-0.1239284798502922,
-0.501595437526702... |
https://github.com/huggingface/datasets/issues/5762 | Not able to load the pile | Thanks for reporting, @surya-narayanan.
I see you already started a discussion about this on the Community tab of the corresponding dataset: https://huggingface.co/datasets/EleutherAI/the_pile/discussions/10
Let's continue the discussion there! | ### Describe the bug
Got this error when I am trying to load the pile dataset
```
TypeError: Couldn't cast array of type
struct<file: string, id: string>
to
{'id': Value(dtype='string', id=None)}
```
### Steps to reproduce the bug
Please visit the following sample notebook
https://colab.research.goo... | 192 | 27 | Not able to load the pile
### Describe the bug
Got this error when I am trying to load the pile dataset
```
TypeError: Couldn't cast array of type
struct<file: string, id: string>
to
{'id': Value(dtype='string', id=None)}
```
### Steps to reproduce the bug
Please visit the following sample notebook
... | [
-1.1503949165344238,
-0.8827037811279297,
-0.833561897277832,
1.488810658454895,
-0.14794182777404785,
-1.234551191329956,
0.10123256593942642,
-0.9867702722549438,
1.6254383325576782,
-0.7256696820259094,
0.34879013895988464,
-1.631890058517456,
0.012324993498623371,
-0.5837557315826416,
... |
https://github.com/huggingface/datasets/issues/5761 | One or several metadata.jsonl were found, but not in the same directory or in a parent directory | Also, when generated from a zip archive, the dataset contains only a few images. In my case, 20 versus 2000+ contained in the archive. The generation from folders works as expected. | ### Describe the bug
An attempt to generate a dataset from a zip archive using imagefolder and metadata.jsonl does not lead to the expected result. Tried all possible locations of the json file: the file in the archive is ignored (generated dataset contains only images), the file next to the archive like [here](http... | 193 | 31 | One or several metadata.jsonl were found, but not in the same directory or in a parent directory
### Describe the bug
An attempt to generate a dataset from a zip archive using imagefolder and metadata.jsonl does not lead to the expected result. Tried all possible locations of the json file: the file in the archive... | [
-1.209661841392517,
-0.8102579116821289,
-0.6038259267807007,
1.490384817123413,
0.03481699898838997,
-1.4131840467453003,
0.09134402871131897,
-0.9125491976737976,
1.663573145866394,
-0.9149445295333862,
0.3563386797904968,
-1.6670163869857788,
0.13531334698200226,
-0.7037384510040283,
... |
https://github.com/huggingface/datasets/issues/5761 | One or several metadata.jsonl were found, but not in the same directory or in a parent directory | Thanks for reporting, @blghtr.
You should include the `metadata.jsonl` in your ZIP archives, at the root level directory.
I agree that our documentation is not clear enough. Maybe we could improve it. | ### Describe the bug
An attempt to generate a dataset from a zip archive using imagefolder and metadata.jsonl does not lead to the expected result. Tried all possible locations of the json file: the file in the archive is ignored (generated dataset contains only images), the file next to the archive like [here](http... | 193 | 32 | One or several metadata.jsonl were found, but not in the same directory or in a parent directory
### Describe the bug
An attempt to generate a dataset from a zip archive using imagefolder and metadata.jsonl does not lead to the expected result. Tried all possible locations of the json file: the file in the archive... | [
-1.209661841392517,
-0.8102579116821289,
-0.6038259267807007,
1.490384817123413,
0.03481699898838997,
-1.4131840467453003,
0.09134402871131897,
-0.9125491976737976,
1.663573145866394,
-0.9149445295333862,
0.3563386797904968,
-1.6670163869857788,
0.13531334698200226,
-0.7037384510040283,
... |
https://github.com/huggingface/datasets/issues/5761 | One or several metadata.jsonl were found, but not in the same directory or in a parent directory | You can find a dummy dataset example here: https://huggingface.co/datasets/albertvillanova/tmp-imagefolder-metadata
```
tmp-imagefolder-metadata/
└── data/
├── train.zip
└── valid.zip
```
where, the directory structure within the `train.zip` archive is:
```
metadata.jsonl
train/
├── bharatanaty... | ### Describe the bug
An attempt to generate a dataset from a zip archive using imagefolder and metadata.jsonl does not lead to the expected result. Tried all possible locations of the json file: the file in the archive is ignored (generated dataset contains only images), the file next to the archive like [here](http... | 193 | 54 | One or several metadata.jsonl were found, but not in the same directory or in a parent directory
### Describe the bug
An attempt to generate a dataset from a zip archive using imagefolder and metadata.jsonl does not lead to the expected result. Tried all possible locations of the json file: the file in the archive... | [
-1.209661841392517,
-0.8102579116821289,
-0.6038259267807007,
1.490384817123413,
0.03481699898838997,
-1.4131840467453003,
0.09134402871131897,
-0.9125491976737976,
1.663573145866394,
-0.9149445295333862,
0.3563386797904968,
-1.6670163869857788,
0.13531334698200226,
-0.7037384510040283,
... |
https://github.com/huggingface/datasets/issues/5760 | Multi-image loading in Imagefolder dataset | Supporting this could be useful (I remember a use-case for this on the Hub). Do you agree @polinaeterna?
Implementing this should be possible if we iterate over metadata files and build image/audio file paths instead of iterating over image/audio files and looking for the corresponding entries in metadata files. | ### Feature request
Extend the `imagefolder` dataloading script to support loading multiple images per dataset entry.
This only really makes sense if a metadata file is present.
Currently you can use the following format (example `metadata.jsonl`:
```
{'file_name': 'path_to_image.png', 'metadata': ...}
...
`... | 194 | 49 | Multi-image loading in Imagefolder dataset
### Feature request
Extend the `imagefolder` dataloading script to support loading multiple images per dataset entry.
This only really makes sense if a metadata file is present.
Currently you can use the following format (example `metadata.jsonl`:
```
{'file_name': ... | [
-1.186087727546692,
-0.9723941087722778,
-0.8205204606056213,
1.470719814300537,
-0.2228822261095047,
-1.3096250295639038,
0.17784889042377472,
-1.1011343002319336,
1.7495099306106567,
-0.9506685137748718,
0.3123093247413635,
-1.6374276876449585,
0.0869799479842186,
-0.6287729144096375,
... |
https://github.com/huggingface/datasets/issues/5760 | Multi-image loading in Imagefolder dataset | I've build a similar feature from scratch and would be interested to combine it with the datasets package.
My solution works something like this:
Interpret the first element of each column as a file path. If the path exists and is a file, (try to) load the files for the entire column. Thereby, one isn't restricted ... | ### Feature request
Extend the `imagefolder` dataloading script to support loading multiple images per dataset entry.
This only really makes sense if a metadata file is present.
Currently you can use the following format (example `metadata.jsonl`:
```
{'file_name': 'path_to_image.png', 'metadata': ...}
...
`... | 194 | 97 | Multi-image loading in Imagefolder dataset
### Feature request
Extend the `imagefolder` dataloading script to support loading multiple images per dataset entry.
This only really makes sense if a metadata file is present.
Currently you can use the following format (example `metadata.jsonl`:
```
{'file_name': ... | [
-1.213863492012024,
-0.9794521331787109,
-0.8510636687278748,
1.4789533615112305,
-0.16551458835601807,
-1.274858832359314,
0.11515790224075317,
-1.1478337049484253,
1.7242285013198853,
-0.8889589905738831,
0.2950459420681,
-1.6864246129989624,
0.05266019329428673,
-0.6685431003570557,
-... |
https://github.com/huggingface/datasets/issues/5759 | Can I load in list of list of dict format? | Thanks for reporting, @LZY-the-boys.
Could you please give more details about what is your intended dataset structure? What are the names of the columns and the value of each row?
Currently, the JSON-Lines format is supported:
- Each line correspond to one row of the dataset
- Each line is composed of one JSON ... | ### Feature request
my jsonl dataset has following format:
```
[{'input':xxx, 'output':xxx},{'input:xxx,'output':xxx},...]
[{'input':xxx, 'output':xxx},{'input:xxx,'output':xxx},...]
```
I try to use `datasets.load_dataset('json', data_files=path)` or `datasets.Dataset.from_json`, it raises
```
File "site-p... | 195 | 74 | Can I load in list of list of dict format?
### Feature request
my jsonl dataset has following format:
```
[{'input':xxx, 'output':xxx},{'input:xxx,'output':xxx},...]
[{'input':xxx, 'output':xxx},{'input:xxx,'output':xxx},...]
```
I try to use `datasets.load_dataset('json', data_files=path)` or `datasets.Data... | [
-1.2257397174835205,
-0.9827357530593872,
-0.6612416505813599,
1.4746675491333008,
-0.14010222256183624,
-1.2278847694396973,
0.164842426776886,
-1.0968141555786133,
1.714120626449585,
-0.8183811902999878,
0.18215544521808624,
-1.7052286863327026,
-0.008861989714205265,
-0.5882065296173096... |
https://github.com/huggingface/datasets/issues/5756 | Calling shuffle on a IterableDataset with streaming=True, gives "ValueError: cannot reshape array" | Thanks, this appears to have fixed the issue.
I've created a PR for the same change in the mnist dataset: https://huggingface.co/datasets/mnist/discussions/3/files | ### Describe the bug
When calling shuffle on a IterableDataset with streaming=True, I get the following error:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/administrator/Documents/Projects/huggingface/jax-diffusers-sprint-consistency-models/virtualenv/lib/python3.1... | 196 | 21 | Calling shuffle on a IterableDataset with streaming=True, gives "ValueError: cannot reshape array"
### Describe the bug
When calling shuffle on a IterableDataset with streaming=True, I get the following error:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/administ... | [
-1.2316917181015015,
-0.9483445882797241,
-0.6746276617050171,
1.4856078624725342,
-0.055223386734724045,
-1.3221584558486938,
0.15637320280075073,
-0.9741907119750977,
1.5275156497955322,
-0.7414683699607849,
0.31699270009994507,
-1.7013713121414185,
-0.058053143322467804,
-0.543770670890... |
https://github.com/huggingface/datasets/issues/5753 | [IterableDatasets] Add column followed by interleave datasets gives bogus outputs | Problem with the code snippet! Using global vars and functions was not a good idea with iterable datasets!
If we update to:
```python
from datasets import load_dataset
original_dataset = load_dataset("librispeech_asr", "clean", split="validation", streaming=True)
# now add a new column to our streaming datas... | ### Describe the bug
If we add a new column to our iterable dataset using the hack described in #5752, when we then interleave datasets the new column is pinned to one value.
### Steps to reproduce the bug
What we're going to do here is:
1. Load an iterable dataset in streaming mode (`original_dataset`)
2. A... | 198 | 235 | [IterableDatasets] Add column followed by interleave datasets gives bogus outputs
### Describe the bug
If we add a new column to our iterable dataset using the hack described in #5752, when we then interleave datasets the new column is pinned to one value.
### Steps to reproduce the bug
What we're going to d... | [
-1.3051925897598267,
-0.8824840784072876,
-0.7891518473625183,
1.4508460760116577,
-0.16551750898361206,
-1.1660054922103882,
0.19871339201927185,
-1.1297521591186523,
1.6660099029541016,
-0.8249762058258057,
0.3997577428817749,
-1.6987557411193848,
0.026242636144161224,
-0.560241460800170... |
https://github.com/huggingface/datasets/issues/5752 | Streaming dataset looses `.feature` method after `.add_column` | I believe the issue resides in this line:
https://github.com/huggingface/datasets/blob/7c3a9b057c476c40d157bd7a5d57f49066239df0/src/datasets/iterable_dataset.py#L1415
If we pass the **new** features of the dataset to the `.map` method we can return the features after adding a column, e.g.:
```python
from datasets... | ### Describe the bug
After appending a new column to a streaming dataset using `.add_column`, we can no longer access the list of dataset features using the `.feature` method.
### Steps to reproduce the bug
```python
from datasets import load_dataset
original_dataset = load_dataset("librispeech_asr", "clean", sp... | 199 | 133 | Streaming dataset looses `.feature` method after `.add_column`
### Describe the bug
After appending a new column to a streaming dataset using `.add_column`, we can no longer access the list of dataset features using the `.feature` method.
### Steps to reproduce the bug
```python
from datasets import load_dataset
... | [
-1.1994818449020386,
-0.7978154420852661,
-0.6096169948577881,
1.4507285356521606,
-0.018946077674627304,
-1.4118489027023315,
0.13118764758110046,
-0.8869804739952087,
1.7090446949005127,
-0.9088021516799927,
0.3055391311645508,
-1.7455086708068848,
0.031036552041769028,
-0.67025351524353... |
https://github.com/huggingface/datasets/issues/5750 | Fail to create datasets from a generator when using Google Big Query | `from_generator` expects a generator function, not a generator object, so this should work:
```python
from datasets import Dataset
from google.cloud import bigquery
client = bigquery.Client()
def gen()
# Perform a query.
QUERY = (
'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_20... | ### Describe the bug
Creating a dataset from a generator using `Dataset.from_generator()` fails if the generator is the [Google Big Query Python client](https://cloud.google.com/python/docs/reference/bigquery/latest). The problem is that the Big Query client is not pickable. And the function `create_config_id` tries t... | 200 | 70 | Fail to create datasets from a generator when using Google Big Query
### Describe the bug
Creating a dataset from a generator using `Dataset.from_generator()` fails if the generator is the [Google Big Query Python client](https://cloud.google.com/python/docs/reference/bigquery/latest). The problem is that the Big Qu... | [
-1.1602425575256348,
-0.9704848527908325,
-0.7141411900520325,
1.5880135297775269,
-0.15210165083408356,
-1.299296498298645,
0.14538878202438354,
-1.081978678703308,
1.7068805694580078,
-0.8078023791313171,
0.3324308395385742,
-1.667130708694458,
0.09479494392871857,
-0.5644509792327881,
... |
https://github.com/huggingface/datasets/issues/5750 | Fail to create datasets from a generator when using Google Big Query | @mariosasko your code was incomplete, so I tried to fix it:
```py
from datasets import Dataset
from google.cloud import bigquery
client = bigquery.Client()
def gen():
# Perform a query.
QUERY = (
'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` '
'WHERE state = "T... | ### Describe the bug
Creating a dataset from a generator using `Dataset.from_generator()` fails if the generator is the [Google Big Query Python client](https://cloud.google.com/python/docs/reference/bigquery/latest). The problem is that the Big Query client is not pickable. And the function `create_config_id` tries t... | 200 | 128 | Fail to create datasets from a generator when using Google Big Query
### Describe the bug
Creating a dataset from a generator using `Dataset.from_generator()` fails if the generator is the [Google Big Query Python client](https://cloud.google.com/python/docs/reference/bigquery/latest). The problem is that the Big Qu... | [
-1.1789183616638184,
-0.9633180499076843,
-0.7198936343193054,
1.59357488155365,
-0.15438123047351837,
-1.2759674787521362,
0.1383015364408493,
-1.0713728666305542,
1.6924629211425781,
-0.7986466288566589,
0.3237428367137909,
-1.6632311344146729,
0.10667881369590759,
-0.5385645031929016,
... |
https://github.com/huggingface/datasets/issues/5750 | Fail to create datasets from a generator when using Google Big Query | It does matter: this function expects a generator function, as stated in the docs.
This should work:
```python
from datasets import Dataset
from google.cloud import bigquery
def gen():
client = bigquery.Client()
# Perform a query.
QUERY = (
'SELECT name FROM `bigquery-public-data.usa_na... | ### Describe the bug
Creating a dataset from a generator using `Dataset.from_generator()` fails if the generator is the [Google Big Query Python client](https://cloud.google.com/python/docs/reference/bigquery/latest). The problem is that the Big Query client is not pickable. And the function `create_config_id` tries t... | 200 | 128 | Fail to create datasets from a generator when using Google Big Query
### Describe the bug
Creating a dataset from a generator using `Dataset.from_generator()` fails if the generator is the [Google Big Query Python client](https://cloud.google.com/python/docs/reference/bigquery/latest). The problem is that the Big Qu... | [
-1.1777536869049072,
-0.9725047945976257,
-0.7136372327804565,
1.5906951427459717,
-0.15301071107387543,
-1.295021653175354,
0.1304517537355423,
-1.074754238128662,
1.7167811393737793,
-0.806781530380249,
0.3186870217323303,
-1.6626815795898438,
0.10338040441274643,
-0.5449557304382324,
... |
https://github.com/huggingface/datasets/issues/5750 | Fail to create datasets from a generator when using Google Big Query | Thank you @mariosasko . Your last code is working indeed. Curiously, the important detail here was to wrap the client instantiation within the generator itself. If the line `client = bigquery.Client()` is moved outside, then the error is back.
I see now also your point in regard to the generator being a generator fu... | ### Describe the bug
Creating a dataset from a generator using `Dataset.from_generator()` fails if the generator is the [Google Big Query Python client](https://cloud.google.com/python/docs/reference/bigquery/latest). The problem is that the Big Query client is not pickable. And the function `create_config_id` tries t... | 200 | 62 | Fail to create datasets from a generator when using Google Big Query
### Describe the bug
Creating a dataset from a generator using `Dataset.from_generator()` fails if the generator is the [Google Big Query Python client](https://cloud.google.com/python/docs/reference/bigquery/latest). The problem is that the Big Qu... | [
-1.1811081171035767,
-0.9616960287094116,
-0.7690979838371277,
1.5323928594589233,
-0.14209146797657013,
-1.2693719863891602,
0.13528288900852203,
-1.0998899936676025,
1.7323766946792603,
-0.7927662134170532,
0.3175896108150482,
-1.6636838912963867,
0.09437628090381622,
-0.5398527979850769... |
https://github.com/huggingface/datasets/issues/5749 | AttributeError: 'Version' object has no attribute 'match' | I got the same error, and the official website for visual genome is down. Did you solve this problem? | ### Describe the bug
When I run
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descriptions_v1.2.0')
AttributeError: 'Version' object has no attribute 'match'
### Steps to reproduce the bug
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descripti... | 201 | 19 | AttributeError: 'Version' object has no attribute 'match'
### Describe the bug
When I run
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descriptions_v1.2.0')
AttributeError: 'Version' object has no attribute 'match'
### Steps to reproduce the bug
from datasets import load_dat... | [
-1.2199641466140747,
-0.8849989175796509,
-0.4521122872829437,
1.3732024431228638,
-0.02820592187345028,
-1.3224425315856934,
0.126606747508049,
-0.8853461146354675,
1.5554863214492798,
-0.8962793350219727,
0.21222303807735443,
-1.7204601764678955,
0.05587225407361984,
-0.6369990110397339,... |
https://github.com/huggingface/datasets/issues/5749 | AttributeError: 'Version' object has no attribute 'match' | Apart form data host server being down, there is an additional issue with the `datasets` library introduced by this PR:
- #5238
I am working to fix it. | ### Describe the bug
When I run
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descriptions_v1.2.0')
AttributeError: 'Version' object has no attribute 'match'
### Steps to reproduce the bug
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descripti... | 201 | 28 | AttributeError: 'Version' object has no attribute 'match'
### Describe the bug
When I run
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descriptions_v1.2.0')
AttributeError: 'Version' object has no attribute 'match'
### Steps to reproduce the bug
from datasets import load_dat... | [
-1.2199641466140747,
-0.8849989175796509,
-0.4521122872829437,
1.3732024431228638,
-0.02820592187345028,
-1.3224425315856934,
0.126606747508049,
-0.8853461146354675,
1.5554863214492798,
-0.8962793350219727,
0.21222303807735443,
-1.7204601764678955,
0.05587225407361984,
-0.6369990110397339,... |
https://github.com/huggingface/datasets/issues/5749 | AttributeError: 'Version' object has no attribute 'match' | For the issue with their data host server being down, I have opened a discussion in the "Community" tab of the Hub dataset: https://huggingface.co/datasets/visual_genome/discussions/3
Let's continue the discussion there. | ### Describe the bug
When I run
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descriptions_v1.2.0')
AttributeError: 'Version' object has no attribute 'match'
### Steps to reproduce the bug
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descripti... | 201 | 29 | AttributeError: 'Version' object has no attribute 'match'
### Describe the bug
When I run
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descriptions_v1.2.0')
AttributeError: 'Version' object has no attribute 'match'
### Steps to reproduce the bug
from datasets import load_dat... | [
-1.2199641466140747,
-0.8849989175796509,
-0.4521122872829437,
1.3732024431228638,
-0.02820592187345028,
-1.3224425315856934,
0.126606747508049,
-0.8853461146354675,
1.5554863214492798,
-0.8962793350219727,
0.21222303807735443,
-1.7204601764678955,
0.05587225407361984,
-0.6369990110397339,... |
https://github.com/huggingface/datasets/issues/5749 | AttributeError: 'Version' object has no attribute 'match' | The authors just replied to us with their new URL: https://homes.cs.washington.edu/~ranjay/visualgenome/
We have fixed the datasets loading script, which is operative again. | ### Describe the bug
When I run
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descriptions_v1.2.0')
AttributeError: 'Version' object has no attribute 'match'
### Steps to reproduce the bug
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descripti... | 201 | 22 | AttributeError: 'Version' object has no attribute 'match'
### Describe the bug
When I run
from datasets import load_dataset
data = load_dataset("visual_genome", 'region_descriptions_v1.2.0')
AttributeError: 'Version' object has no attribute 'match'
### Steps to reproduce the bug
from datasets import load_dat... | [
-1.2199641466140747,
-0.8849989175796509,
-0.4521122872829437,
1.3732024431228638,
-0.02820592187345028,
-1.3224425315856934,
0.126606747508049,
-0.8853461146354675,
1.5554863214492798,
-0.8962793350219727,
0.21222303807735443,
-1.7204601764678955,
0.05587225407361984,
-0.6369990110397339,... |
https://github.com/huggingface/datasets/issues/5744 | [BUG] With Pandas 2.0.0, `load_dataset` raises `TypeError: read_csv() got an unexpected keyword argument 'mangle_dupe_cols'` | Thanks for reporting, @keyboardAnt.
We haven't noticed any crash in our CI tests. Could you please indicate specifically the `load_dataset` command that crashes in your side, so that we can reproduce it? | The `load_dataset` function with Pandas `1.5.3` has no issue (just a FutureWarning) but crashes with Pandas `2.0.0`.
For your convenience, I opened a draft Pull Request to fix it quickly: https://github.com/huggingface/datasets/pull/5745
---
* The FutureWarning mentioned above:
```
FutureWarning: the 'mangle_... | 202 | 32 | [BUG] With Pandas 2.0.0, `load_dataset` raises `TypeError: read_csv() got an unexpected keyword argument 'mangle_dupe_cols'`
The `load_dataset` function with Pandas `1.5.3` has no issue (just a FutureWarning) but crashes with Pandas `2.0.0`.
For your convenience, I opened a draft Pull Request to fix it quickly: http... | [
-1.1840198040008545,
-0.9789693355560303,
-0.7929209470748901,
1.5074223279953003,
-0.11499737203121185,
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0.13432368636131287,
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1.7249536514282227,
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0.41408878564834595,
-1.7120393514633179,
-0.05658727139234543,
-0.678351104259491... |
https://github.com/huggingface/datasets/issues/5743 | dataclass.py in virtual environment is overriding the stdlib module "dataclasses" | We no longer depend on `dataclasses` (for almost a year), so I don't think our package is the problematic one.
I think it makes more sense to raise this issue in the `dataclasses` repo: https://github.com/ericvsmith/dataclasses. | ### Describe the bug
"e:\Krish_naik\FSDSRegression\venv\Lib\dataclasses.py" is overriding the stdlib module "dataclasses"
### Steps to reproduce the bug
module issue
### Expected behavior
overriding the stdlib module "dataclasses"
### Environment info
VS code | 203 | 35 | dataclass.py in virtual environment is overriding the stdlib module "dataclasses"
### Describe the bug
"e:\Krish_naik\FSDSRegression\venv\Lib\dataclasses.py" is overriding the stdlib module "dataclasses"
### Steps to reproduce the bug
module issue
### Expected behavior
overriding the stdlib module "dataclasse... | [
-1.0500757694244385,
-0.9146837592124939,
-0.8437395691871643,
1.5728400945663452,
-0.12189023196697235,
-1.3173366785049438,
0.2661341428756714,
-1.0739164352416992,
1.6791114807128906,
-0.7407525777816772,
0.2066497504711151,
-1.699449062347412,
-0.02530619129538536,
-0.4475930333137512,... |
https://github.com/huggingface/datasets/issues/5739 | weird result during dataset split when data path starts with `/data` | hi!
I think you can run python from `/data/train/raw/` directory and load dataset as `load_dataset("code_contests")` to mitigate this issue as a workaround.
@ericxsun Do you want to open a PR to fix the regex? As you already found the solution :) | ### Describe the bug
The regex defined here https://github.com/huggingface/datasets/blob/f2607935c4e45c70c44fcb698db0363ca7ba83d4/src/datasets/utils/py_utils.py#L158
will cause a weird result during dataset split when data path starts with `/data`
### Steps to reproduce the bug
1. clone dataset into local path
... | 204 | 41 | weird result during dataset split when data path starts with `/data`
### Describe the bug
The regex defined here https://github.com/huggingface/datasets/blob/f2607935c4e45c70c44fcb698db0363ca7ba83d4/src/datasets/utils/py_utils.py#L158
will cause a weird result during dataset split when data path starts with `/da... | [
-1.219397783279419,
-0.8116105198860168,
-0.7386140823364258,
1.5036342144012451,
-0.010847043246030807,
-1.2460169792175293,
0.045154087245464325,
-1.0038526058197021,
1.6462818384170532,
-0.7914738059043884,
0.2931199073791504,
-1.767613172531128,
-0.10710494220256805,
-0.636674106121063... |
https://github.com/huggingface/datasets/issues/5739 | weird result during dataset split when data path starts with `/data` | > hi! I think you can run python from `/data/train/raw/` directory and load dataset as `load_dataset("code_contests")` to mitigate this issue as a workaround. @ericxsun Do you want to open a PR to fix the regex? As you already found the solution :)
Sure, please see https://github.com/huggingface/datasets/pull/5748 ... | ### Describe the bug
The regex defined here https://github.com/huggingface/datasets/blob/f2607935c4e45c70c44fcb698db0363ca7ba83d4/src/datasets/utils/py_utils.py#L158
will cause a weird result during dataset split when data path starts with `/data`
### Steps to reproduce the bug
1. clone dataset into local path
... | 204 | 47 | weird result during dataset split when data path starts with `/data`
### Describe the bug
The regex defined here https://github.com/huggingface/datasets/blob/f2607935c4e45c70c44fcb698db0363ca7ba83d4/src/datasets/utils/py_utils.py#L158
will cause a weird result during dataset split when data path starts with `/da... | [
-1.219397783279419,
-0.8116105198860168,
-0.7386140823364258,
1.5036342144012451,
-0.010847043246030807,
-1.2460169792175293,
0.045154087245464325,
-1.0038526058197021,
1.6462818384170532,
-0.7914738059043884,
0.2931199073791504,
-1.767613172531128,
-0.10710494220256805,
-0.636674106121063... |
https://github.com/huggingface/datasets/issues/5739 | weird result during dataset split when data path starts with `/data` | I think `string_to_dict` is ok, and that the issue is that it gets `'/data2/train/raw/code_contests/data/test-00000-of-00001-9c49eeff30aacaa8.parquet'` as input instead of `'data/test-00000-of-00001-9c49eeff30aacaa8.parquet'`. The path should be relative to the directory being loaded by `load_dataset` | ### Describe the bug
The regex defined here https://github.com/huggingface/datasets/blob/f2607935c4e45c70c44fcb698db0363ca7ba83d4/src/datasets/utils/py_utils.py#L158
will cause a weird result during dataset split when data path starts with `/data`
### Steps to reproduce the bug
1. clone dataset into local path
... | 204 | 31 | weird result during dataset split when data path starts with `/data`
### Describe the bug
The regex defined here https://github.com/huggingface/datasets/blob/f2607935c4e45c70c44fcb698db0363ca7ba83d4/src/datasets/utils/py_utils.py#L158
will cause a weird result during dataset split when data path starts with `/da... | [
-1.219397783279419,
-0.8116105198860168,
-0.7386140823364258,
1.5036342144012451,
-0.010847043246030807,
-1.2460169792175293,
0.045154087245464325,
-1.0038526058197021,
1.6462818384170532,
-0.7914738059043884,
0.2931199073791504,
-1.767613172531128,
-0.10710494220256805,
-0.636674106121063... |
https://github.com/huggingface/datasets/issues/5738 | load_dataset("text","dataset.txt") loads the wrong dataset! | You need to provide a text file as `data_files`, not as a configuration:
```python
my_dataset = load_dataset("text", data_files="TextFile.txt")
```
Otherwise, since `data_files` is `None`, it picks up Colab's sample datasets from the `content` dir. | ### Describe the bug
I am trying to load my own custom text dataset using the load_dataset function. My dataset is a bunch of ordered text, think along the lines of shakespeare plays. However, after I load the dataset and I inspect it, the dataset is a table with a bunch of latitude and longitude values! What in th... | 205 | 34 | load_dataset("text","dataset.txt") loads the wrong dataset!
### Describe the bug
I am trying to load my own custom text dataset using the load_dataset function. My dataset is a bunch of ordered text, think along the lines of shakespeare plays. However, after I load the dataset and I inspect it, the dataset is a ta... | [
-1.1189857721328735,
-0.9436991810798645,
-0.8247067928314209,
1.3786360025405884,
-0.22442679107189178,
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0.18883627653121948,
-1.1409183740615845,
1.6936867237091064,
-0.9340497255325317,
0.2550179362297058,
-1.7659624814987183,
0.0692157968878746,
-0.5596188306808472,... |
https://github.com/huggingface/datasets/issues/5737 | ClassLabel Error | Hi, you can use the `cast_column` function to change the feature type from a `Value(int64)` to `ClassLabel`:
```py
dataset = dataset.cast_column("label", ClassLabel(names=["label_1", "label_2", "label_3"]))
print(dataset.features)
{'text': Value(dtype='string', id=None),
'label': ClassLabel(names=['label_1', 'l... | ### Describe the bug
I still getting the error "call() takes 1 positional argument but 2 were given" even after ensuring that the value being passed to the label object is a single value and that the ClassLabel object has been created with the correct number of label classes
### Steps to reproduce the bug
from... | 206 | 34 | ClassLabel Error
### Describe the bug
I still getting the error "call() takes 1 positional argument but 2 were given" even after ensuring that the value being passed to the label object is a single value and that the ClassLabel object has been created with the correct number of label classes
### Steps to repro... | [
-1.243262767791748,
-0.9444183707237244,
-0.7507571578025818,
1.6136642694473267,
-0.2208191305398941,
-1.0991207361221313,
0.14698971807956696,
-1.1070612668991089,
1.6098380088806152,
-0.7835369110107422,
0.24456560611724854,
-1.648578405380249,
-0.012350648641586304,
-0.6137617826461792... |
https://github.com/huggingface/datasets/issues/5736 | FORCE_REDOWNLOAD raises "Directory not empty" exception on second run | Hi ! I couldn't reproduce your issue :/
It seems that `shutil.rmtree` failed. It is supposed to work even if the directory is not empty, but you still end up with `OSError: [Errno 39] Directory not empty:`. Can you make sure another process is not using this directory at the same time ? | ### Describe the bug
Running `load_dataset(..., download_mode=datasets.DownloadMode.FORCE_REDOWNLOAD)` twice raises a `Directory not empty` exception on the second run.
### Steps to reproduce the bug
I cannot test this on datasets v2.11.0 due to #5711, but this happens in v2.10.1.
1. Set up a script `my_dataset.p... | 207 | 53 | FORCE_REDOWNLOAD raises "Directory not empty" exception on second run
### Describe the bug
Running `load_dataset(..., download_mode=datasets.DownloadMode.FORCE_REDOWNLOAD)` twice raises a `Directory not empty` exception on the second run.
### Steps to reproduce the bug
I cannot test this on datasets v2.11.0 due to... | [
-1.1953952312469482,
-0.929840087890625,
-0.665449321269989,
1.4092156887054443,
-0.14482204616069794,
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0.15087050199508667,
-1.0500991344451904,
1.6761659383773804,
-0.7755241990089417,
0.21376854181289673,
-1.6455949544906616,
-0.08541421592235565,
-0.4852448105812073... |
https://github.com/huggingface/datasets/issues/5732 | Enwik8 should support the standard split | The Enwik8 pipeline is not present in this codebase, and is hosted elsewhere. I have opened a PR [there](https://huggingface.co/datasets/enwik8/discussions/4) instead. | ### Feature request
The HuggingFace Datasets library currently supports two BuilderConfigs for Enwik8. One config yields individual lines as examples, while the other config yields the entire dataset as a single example. Both support only a monolithic split: it is all grouped as "train".
The HuggingFace Datasets l... | 208 | 20 | Enwik8 should support the standard split
### Feature request
The HuggingFace Datasets library currently supports two BuilderConfigs for Enwik8. One config yields individual lines as examples, while the other config yields the entire dataset as a single example. Both support only a monolithic split: it is all grouped... | [
-1.2371957302093506,
-0.936003565788269,
-0.7482637166976929,
1.3958410024642944,
-0.1406141221523285,
-1.2569221258163452,
0.13435989618301392,
-1.0947506427764893,
1.6611647605895996,
-0.7288448214530945,
0.2676408588886261,
-1.7059106826782227,
-0.012029415927827358,
-0.5493984222412109... |
https://github.com/huggingface/datasets/issues/5727 | load_dataset fails with FileNotFound error on Windows | Hi! Can you please paste the entire error stack trace, not only the last few lines? | ### Describe the bug
Although I can import and run the datasets library in a Colab environment, I cannot successfully load any data on my own machine (Windows 10) despite following the install steps:
(1) create conda environment
(2) activate environment
(3) install with: ``conda` install -c huggingface -c conda-... | 209 | 16 | load_dataset fails with FileNotFound error on Windows
### Describe the bug
Although I can import and run the datasets library in a Colab environment, I cannot successfully load any data on my own machine (Windows 10) despite following the install steps:
(1) create conda environment
(2) activate environment
(3)... | [
-1.2770172357559204,
-0.9197495579719543,
-0.7580211758613586,
1.4451946020126343,
-0.17076341807842255,
-1.3406909704208374,
0.10580836981534958,
-1.0527589321136475,
1.7266324758529663,
-0.8303958773612976,
0.23863640427589417,
-1.6874346733093262,
0.08473846316337585,
-0.602720558643341... |
https://github.com/huggingface/datasets/issues/5727 | load_dataset fails with FileNotFound error on Windows | `----> 1 dataset = datasets.load_dataset("glue", "ax")
File ~\anaconda3\envs\huggingface\Lib\site-packages\datasets\load.py:1767, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision... | ### Describe the bug
Although I can import and run the datasets library in a Colab environment, I cannot successfully load any data on my own machine (Windows 10) despite following the install steps:
(1) create conda environment
(2) activate environment
(3) install with: ``conda` install -c huggingface -c conda-... | 209 | 217 | load_dataset fails with FileNotFound error on Windows
### Describe the bug
Although I can import and run the datasets library in a Colab environment, I cannot successfully load any data on my own machine (Windows 10) despite following the install steps:
(1) create conda environment
(2) activate environment
(3)... | [
-1.2770172357559204,
-0.9197495579719543,
-0.7580211758613586,
1.4451946020126343,
-0.17076341807842255,
-1.3406909704208374,
0.10580836981534958,
-1.0527589321136475,
1.7266324758529663,
-0.8303958773612976,
0.23863640427589417,
-1.6874346733093262,
0.08473846316337585,
-0.602720558643341... |
https://github.com/huggingface/datasets/issues/5727 | load_dataset fails with FileNotFound error on Windows | Okay, this is the issue:
```
FileNotFoundError: [WinError 3] The system cannot find the path specified:
'C:\\Users\\...\\.cache\\huggingface'
```
I don't remember seeing this error before.
I guess it could happen in a multi-process environment if one of the processes deletes the `datasets` cache as the othe... | ### Describe the bug
Although I can import and run the datasets library in a Colab environment, I cannot successfully load any data on my own machine (Windows 10) despite following the install steps:
(1) create conda environment
(2) activate environment
(3) install with: ``conda` install -c huggingface -c conda-... | 209 | 80 | load_dataset fails with FileNotFound error on Windows
### Describe the bug
Although I can import and run the datasets library in a Colab environment, I cannot successfully load any data on my own machine (Windows 10) despite following the install steps:
(1) create conda environment
(2) activate environment
(3)... | [
-1.2770172357559204,
-0.9197495579719543,
-0.7580211758613586,
1.4451946020126343,
-0.17076341807842255,
-1.3406909704208374,
0.10580836981534958,
-1.0527589321136475,
1.7266324758529663,
-0.8303958773612976,
0.23863640427589417,
-1.6874346733093262,
0.08473846316337585,
-0.602720558643341... |
https://github.com/huggingface/datasets/issues/5725 | How to limit the number of examples in dataset, for testing? | Hi! You can use the `nrows` parameter for this:
```python
data = load_dataset("json", data_files=data_path, nrows=10)
``` | ### Describe the bug
I am using this command:
`data = load_dataset("json", data_files=data_path)`
However, I want to add a parameter, to limit the number of loaded examples to be 10, for development purposes, but can't find this simple parameter.
### Steps to reproduce the bug
In the description.
### Expected beh... | 211 | 16 | How to limit the number of examples in dataset, for testing?
### Describe the bug
I am using this command:
`data = load_dataset("json", data_files=data_path)`
However, I want to add a parameter, to limit the number of loaded examples to be 10, for development purposes, but can't find this simple parameter.
### St... | [
-1.1022915840148926,
-0.8567841649055481,
-0.7513408660888672,
1.6503745317459106,
-0.1348848044872284,
-1.2660845518112183,
0.22829993069171906,
-1.094260573387146,
1.6975762844085693,
-0.8379931449890137,
0.28831642866134644,
-1.6608378887176514,
0.04450902342796326,
-0.6675934195518494,... |
https://github.com/huggingface/datasets/issues/5725 | How to limit the number of examples in dataset, for testing? | I misread the format in which the dataset is stored - the `nrows` parameter works for CSV, but not JSON.
This means the only option is first to create a DataFrame and then convert it to a Dataset object:
```python
import pandas as pd
from datasets import Dataset
df = pd.read_json(data_path, lines=True, nrows=... | ### Describe the bug
I am using this command:
`data = load_dataset("json", data_files=data_path)`
However, I want to add a parameter, to limit the number of loaded examples to be 10, for development purposes, but can't find this simple parameter.
### Steps to reproduce the bug
In the description.
### Expected beh... | 211 | 57 | How to limit the number of examples in dataset, for testing?
### Describe the bug
I am using this command:
`data = load_dataset("json", data_files=data_path)`
However, I want to add a parameter, to limit the number of loaded examples to be 10, for development purposes, but can't find this simple parameter.
### St... | [
-1.1809309720993042,
-0.9155998826026917,
-0.7503301501274109,
1.5849159955978394,
-0.13664761185646057,
-1.3292261362075806,
0.1778264343738556,
-1.117719054222107,
1.717626929283142,
-0.9138863682746887,
0.2740040719509125,
-1.7142506837844849,
0.055442702025175095,
-0.6459029316902161,
... |
https://github.com/huggingface/datasets/issues/5724 | Error after shuffling streaming IterableDatasets with downloaded dataset | Moving `"en"` to the end of the path instead of passing it as a config name should fix the error:
```python
import datasets
dataset = datasets.load_dataset('/path/to/your/data/dir/en', streaming=True, split='train')
dataset = dataset.shuffle(buffer_size=10_000, seed=42)
next(iter(dataset))
```
PS: https://gith... | ### Describe the bug
I downloaded the C4 dataset, and used streaming IterableDatasets to read it. Everything went normal until I used `dataset = dataset.shuffle(seed=42, buffer_size=10_000)` to shuffle the dataset. Shuffled dataset will throw the following error when it is used by `next(iter(dataset))`:
```
File "/d... | 212 | 54 | Error after shuffling streaming IterableDatasets with downloaded dataset
### Describe the bug
I downloaded the C4 dataset, and used streaming IterableDatasets to read it. Everything went normal until I used `dataset = dataset.shuffle(seed=42, buffer_size=10_000)` to shuffle the dataset. Shuffled dataset will throw t... | [
-1.2737857103347778,
-0.9381715655326843,
-0.6803872585296631,
1.3376641273498535,
-0.13045163452625275,
-1.3006811141967773,
0.20212818682193756,
-1.04757821559906,
1.5604774951934814,
-0.7111883163452148,
0.159285768866539,
-1.6583572626113892,
-0.1482614427804947,
-0.43704476952552795,
... |
https://github.com/huggingface/datasets/issues/5722 | Distributed Training Error on Customized Dataset | Hmm the error doesn't seem related to data loading.
Regarding `split_dataset_by_node`: it's generally used to split an iterable dataset (e.g. when streaming) in pytorch DDP. It's not needed if you use a regular dataset since the pytorch DataLoader already assigns a subset of the dataset indices to each node. | Hi guys, recently I tried to use `datasets` to train a dual encoder.
I finish my own datasets according to the nice [tutorial](https://huggingface.co/docs/datasets/v2.11.0/en/dataset_script)
Here are my code:
```python
class RetrivalDataset(datasets.GeneratorBasedBuilder):
"""CrossEncoder dataset."""
B... | 213 | 49 | Distributed Training Error on Customized Dataset
Hi guys, recently I tried to use `datasets` to train a dual encoder.
I finish my own datasets according to the nice [tutorial](https://huggingface.co/docs/datasets/v2.11.0/en/dataset_script)
Here are my code:
```python
class RetrivalDataset(datasets.GeneratorBased... | [
-1.3063890933990479,
-1.014308214187622,
-0.6957640647888184,
1.4547462463378906,
-0.24241700768470764,
-1.0963528156280518,
0.19008687138557434,
-1.122454285621643,
1.6499240398406982,
-0.7355639338493347,
0.380498468875885,
-1.6156622171401978,
0.0129916463047266,
-0.5391196012496948,
... |
https://github.com/huggingface/datasets/issues/5720 | Streaming IterableDatasets do not work with torch DataLoaders | I'm experiencing the same problem that @jlehrer1. I was able to reproduce it with a very small example:
```py
from datasets import Dataset, load_dataset, load_dataset_builder
from torch.utils.data import DataLoader
def my_gen():
for i in range(1, 4):
yield {"a": i}
# Saving the dataset as a p... | ### Describe the bug
When using streaming datasets set up with train/val split using `.skip()` and `.take()`, the following error occurs when iterating over a torch dataloader:
```
File "/Users/julian/miniconda3/envs/sims/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 363, in __iter__
self.... | 214 | 129 | Streaming IterableDatasets do not work with torch DataLoaders
### Describe the bug
When using streaming datasets set up with train/val split using `.skip()` and `.take()`, the following error occurs when iterating over a torch dataloader:
```
File "/Users/julian/miniconda3/envs/sims/lib/python3.9/site-packages/t... | [
-1.178139328956604,
-0.9114153981208801,
-0.7017797827720642,
1.5412392616271973,
-0.1086544394493103,
-1.2789701223373413,
0.12293124943971634,
-0.9090158939361572,
1.4955908060073853,
-0.6685280799865723,
0.22464752197265625,
-1.588659644126892,
-0.19427348673343658,
-0.49374836683273315... |
https://github.com/huggingface/datasets/issues/5720 | Streaming IterableDatasets do not work with torch DataLoaders | I cannot reproduce this error, not even with your MRE @ivanprado (your env appears to be the same as Colab's, and your code runs there without issues). | ### Describe the bug
When using streaming datasets set up with train/val split using `.skip()` and `.take()`, the following error occurs when iterating over a torch dataloader:
```
File "/Users/julian/miniconda3/envs/sims/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 363, in __iter__
self.... | 214 | 27 | Streaming IterableDatasets do not work with torch DataLoaders
### Describe the bug
When using streaming datasets set up with train/val split using `.skip()` and `.take()`, the following error occurs when iterating over a torch dataloader:
```
File "/Users/julian/miniconda3/envs/sims/lib/python3.9/site-packages/t... | [
-1.178139328956604,
-0.9114153981208801,
-0.7017797827720642,
1.5412392616271973,
-0.1086544394493103,
-1.2789701223373413,
0.12293124943971634,
-0.9090158939361572,
1.4955908060073853,
-0.6685280799865723,
0.22464752197265625,
-1.588659644126892,
-0.19427348673343658,
-0.49374836683273315... |
https://github.com/huggingface/datasets/issues/5720 | Streaming IterableDatasets do not work with torch DataLoaders | @mariosasko you are right, it works on Colab. I digged deeper and found that the problem arises when the multiprocessing method is set to be `spawn`. This code reproduces the problem in Colab:
```py
from datasets import Dataset, load_dataset, load_dataset_builder
from torch.utils.data import DataLoader
import mul... | ### Describe the bug
When using streaming datasets set up with train/val split using `.skip()` and `.take()`, the following error occurs when iterating over a torch dataloader:
```
File "/Users/julian/miniconda3/envs/sims/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 363, in __iter__
self.... | 214 | 124 | Streaming IterableDatasets do not work with torch DataLoaders
### Describe the bug
When using streaming datasets set up with train/val split using `.skip()` and `.take()`, the following error occurs when iterating over a torch dataloader:
```
File "/Users/julian/miniconda3/envs/sims/lib/python3.9/site-packages/t... | [
-1.178139328956604,
-0.9114153981208801,
-0.7017797827720642,
1.5412392616271973,
-0.1086544394493103,
-1.2789701223373413,
0.12293124943971634,
-0.9090158939361572,
1.4955908060073853,
-0.6685280799865723,
0.22464752197265625,
-1.588659644126892,
-0.19427348673343658,
-0.49374836683273315... |
https://github.com/huggingface/datasets/issues/5720 | Streaming IterableDatasets do not work with torch DataLoaders | So is there a way to fix this by changing the `mp` method? This is blocking any usage of the `datasets` library for me | ### Describe the bug
When using streaming datasets set up with train/val split using `.skip()` and `.take()`, the following error occurs when iterating over a torch dataloader:
```
File "/Users/julian/miniconda3/envs/sims/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 363, in __iter__
self.... | 214 | 24 | Streaming IterableDatasets do not work with torch DataLoaders
### Describe the bug
When using streaming datasets set up with train/val split using `.skip()` and `.take()`, the following error occurs when iterating over a torch dataloader:
```
File "/Users/julian/miniconda3/envs/sims/lib/python3.9/site-packages/t... | [
-1.178139328956604,
-0.9114153981208801,
-0.7017797827720642,
1.5412392616271973,
-0.1086544394493103,
-1.2789701223373413,
0.12293124943971634,
-0.9090158939361572,
1.4955908060073853,
-0.6685280799865723,
0.22464752197265625,
-1.588659644126892,
-0.19427348673343658,
-0.49374836683273315... |
https://github.com/huggingface/datasets/issues/5720 | Streaming IterableDatasets do not work with torch DataLoaders | @jlehrer1 can you try adding `mp.set_start_method('fork')` at the beginning of your code? Maybe this helps you. Keep us posted. | ### Describe the bug
When using streaming datasets set up with train/val split using `.skip()` and `.take()`, the following error occurs when iterating over a torch dataloader:
```
File "/Users/julian/miniconda3/envs/sims/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 363, in __iter__
self.... | 214 | 19 | Streaming IterableDatasets do not work with torch DataLoaders
### Describe the bug
When using streaming datasets set up with train/val split using `.skip()` and `.take()`, the following error occurs when iterating over a torch dataloader:
```
File "/Users/julian/miniconda3/envs/sims/lib/python3.9/site-packages/t... | [
-1.178139328956604,
-0.9114153981208801,
-0.7017797827720642,
1.5412392616271973,
-0.1086544394493103,
-1.2789701223373413,
0.12293124943971634,
-0.9090158939361572,
1.4955908060073853,
-0.6685280799865723,
0.22464752197265625,
-1.588659644126892,
-0.19427348673343658,
-0.49374836683273315... |
https://github.com/huggingface/datasets/issues/5719 | Array2D feature creates a list of list instead of a numpy array | Hi!
You need to set the format to `np` before indexing the dataset to get NumPy arrays:
```python
features = Features(dict(seq=Array2D((2,2), 'float32')))
ds = Dataset.from_dict(dict(seq=[np.random.rand(2,2)]), features=features)
ds.set_format("np")
a = ds[0]['seq']
```
> I think it should not be the ex... | ### Describe the bug
I'm not sure if this is expected behavior or not. When I create a 2D array using `Array2D`, the data has list type instead of numpy array. I think it should not be the expected behavior especially when I feed a numpy array as input to the data creation function. Why is it converting my array int... | 215 | 172 | Array2D feature creates a list of list instead of a numpy array
### Describe the bug
I'm not sure if this is expected behavior or not. When I create a 2D array using `Array2D`, the data has list type instead of numpy array. I think it should not be the expected behavior especially when I feed a numpy array as inpu... | [
-1.2951023578643799,
-0.891772449016571,
-0.74828040599823,
1.4550156593322754,
-0.13182206451892853,
-1.254961609840393,
0.11482946574687958,
-1.0367920398712158,
1.7142430543899536,
-0.8507708311080933,
0.3687160313129425,
-1.6596955060958862,
0.19670423865318298,
-0.649299144744873,
-... |
https://github.com/huggingface/datasets/issues/5719 | Array2D feature creates a list of list instead of a numpy array | Current behavior when indexing the dataset:
- Using `Array((2,2))` returns a list of lists.
- Using `Array((None,2))` returns a numpy array.
Don't you think this is kind of unexpected behavior from end-user perspective?
As a user, I expect that when I use `Array2D`, the behavior needs to be consistent even if I ... | ### Describe the bug
I'm not sure if this is expected behavior or not. When I create a 2D array using `Array2D`, the data has list type instead of numpy array. I think it should not be the expected behavior especially when I feed a numpy array as input to the data creation function. Why is it converting my array int... | 215 | 152 | Array2D feature creates a list of list instead of a numpy array
### Describe the bug
I'm not sure if this is expected behavior or not. When I create a 2D array using `Array2D`, the data has list type instead of numpy array. I think it should not be the expected behavior especially when I feed a numpy array as inpu... | [
-1.3034080266952515,
-0.8863217234611511,
-0.7366203665733337,
1.4487640857696533,
-0.12153633683919907,
-1.2546308040618896,
0.11706940084695816,
-1.0130683183670044,
1.7305867671966553,
-0.8401386141777039,
0.36504673957824707,
-1.6523691415786743,
0.18636450171470642,
-0.655825853347778... |
https://github.com/huggingface/datasets/issues/5717 | Errror when saving to disk a dataset of images | Looks like as long as the number of shards makes a batch lower than 1000 images it works. In my training set I have 40K images. If I use `num_shards=40` (batch of 1000 images) I get the error, but if I update it to `num_shards=50` (batch of 800 images) it works.
I will be happy to share my dataset privately if it ca... | ### Describe the bug
Hello!
I have an issue when I try to save on disk my dataset of images. The error I get is:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 1442, in save_... | 216 | 67 | Errror when saving to disk a dataset of images
### Describe the bug
Hello!
I have an issue when I try to save on disk my dataset of images. The error I get is:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-package... | [
-1.1648489236831665,
-0.8666452765464783,
-0.726670503616333,
1.4068650007247925,
-0.13274896144866943,
-1.3223906755447388,
0.05514451488852501,
-1.0130778551101685,
1.4621919393539429,
-0.6920582056045532,
0.15534962713718414,
-1.6286884546279907,
-0.1294914335012436,
-0.4892106950283050... |
https://github.com/huggingface/datasets/issues/5717 | Errror when saving to disk a dataset of images | Hi! I didn't manage to reproduce this behavior, so sharing the dataset with us would help a lot.
> My dataset is around 50K images, is this error might be due to a bad image?
This shouldn't be the case as we save raw data to disk without decoding it. | ### Describe the bug
Hello!
I have an issue when I try to save on disk my dataset of images. The error I get is:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 1442, in save_... | 216 | 50 | Errror when saving to disk a dataset of images
### Describe the bug
Hello!
I have an issue when I try to save on disk my dataset of images. The error I get is:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-package... | [
-1.1648489236831665,
-0.8666452765464783,
-0.726670503616333,
1.4068650007247925,
-0.13274896144866943,
-1.3223906755447388,
0.05514451488852501,
-1.0130778551101685,
1.4621919393539429,
-0.6920582056045532,
0.15534962713718414,
-1.6286884546279907,
-0.1294914335012436,
-0.4892106950283050... |
https://github.com/huggingface/datasets/issues/5717 | Errror when saving to disk a dataset of images | OK, thanks! The dataset is currently hosted on a gcs bucket. How would you like to proceed for sharing the link? | ### Describe the bug
Hello!
I have an issue when I try to save on disk my dataset of images. The error I get is:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 1442, in save_... | 216 | 21 | Errror when saving to disk a dataset of images
### Describe the bug
Hello!
I have an issue when I try to save on disk my dataset of images. The error I get is:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jplu/miniconda3/envs/image-xp/lib/python3.10/site-package... | [
-1.1648489236831665,
-0.8666452765464783,
-0.726670503616333,
1.4068650007247925,
-0.13274896144866943,
-1.3223906755447388,
0.05514451488852501,
-1.0130778551101685,
1.4621919393539429,
-0.6920582056045532,
0.15534962713718414,
-1.6286884546279907,
-0.1294914335012436,
-0.4892106950283050... |
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