html_url stringlengths 48 51 | title stringlengths 5 280 | comments stringlengths 63 51.8k | body stringlengths 0 36.2k ⌀ | comment_length int64 16 1.52k | text stringlengths 159 54.1k | embeddings listlengths 768 768 |
|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/5156 | Unable to download dataset using Azure Data Lake Gen 2 | Hi ! From the `adlfs` docs, there are two filesystems you can use:
> To use the Gen1 filesystem:
> - known_implementations[‘adl’] = {‘class’: ‘adlfs.AzureDatalakeFileSystem’}
>
> To use the Gen2 filesystem:
> - known_implementations[‘abfs’] = {‘class’: ‘adlfs.AzureBlobFileSystem’}
If I'm not mistaken you're u... | ### Describe the bug
When using the DatasetBuilder method with the credentials for the cloud storage Azure Data Lake (adl) Gen2, the following error is showed:
```
Traceback (most recent call last):
File "download_hf_dataset.py", line 143, in <module>
main()
File "download_hf_dataset.py", line 102, in mai... | 76 | Unable to download dataset using Azure Data Lake Gen 2
### Describe the bug
When using the DatasetBuilder method with the credentials for the cloud storage Azure Data Lake (adl) Gen2, the following error is showed:
```
Traceback (most recent call last):
File "download_hf_dataset.py", line 143, in <module>
... | [
0.007943641394376755,
0.22752279043197632,
0.008019868284463882,
0.23792657256126404,
0.09995664656162262,
0.1969153881072998,
0.18387220799922943,
0.19614644348621368,
-0.05162261053919792,
-0.16205672919750214,
-0.02739519439637661,
-0.006244535557925701,
0.23231925070285797,
0.115774802... |
https://github.com/huggingface/datasets/issues/5156 | Unable to download dataset using Azure Data Lake Gen 2 | Thank you @lhoestq . Great call.
Using the default class from `known_implementations` dict solved my problem
```
known_implementations[‘abfs’] = {‘class’: ‘adlfs.AzureBlobFileSystem’}
```
I'm closing this issue. | ### Describe the bug
When using the DatasetBuilder method with the credentials for the cloud storage Azure Data Lake (adl) Gen2, the following error is showed:
```
Traceback (most recent call last):
File "download_hf_dataset.py", line 143, in <module>
main()
File "download_hf_dataset.py", line 102, in mai... | 26 | Unable to download dataset using Azure Data Lake Gen 2
### Describe the bug
When using the DatasetBuilder method with the credentials for the cloud storage Azure Data Lake (adl) Gen2, the following error is showed:
```
Traceback (most recent call last):
File "download_hf_dataset.py", line 143, in <module>
... | [
0.007943641394376755,
0.22752279043197632,
0.008019868284463882,
0.23792657256126404,
0.09995664656162262,
0.1969153881072998,
0.18387220799922943,
0.19614644348621368,
-0.05162261053919792,
-0.16205672919750214,
-0.02739519439637661,
-0.006244535557925701,
0.23231925070285797,
0.115774802... |
https://github.com/huggingface/datasets/issues/5156 | Unable to download dataset using Azure Data Lake Gen 2 | > Thank you @lhoestq . Great call. Using the default class from `known_implementations` dict solved my problem
>
> ```
> known_implementations[‘abfs’] = {‘class’: ‘adlfs.AzureBlobFileSystem’}
> ```
>
> I'm closing this issue.
Hi so here `Saving serialized datasets
After you have processed your dataset, y... | ### Describe the bug
When using the DatasetBuilder method with the credentials for the cloud storage Azure Data Lake (adl) Gen2, the following error is showed:
```
Traceback (most recent call last):
File "download_hf_dataset.py", line 143, in <module>
main()
File "download_hf_dataset.py", line 102, in mai... | 66 | Unable to download dataset using Azure Data Lake Gen 2
### Describe the bug
When using the DatasetBuilder method with the credentials for the cloud storage Azure Data Lake (adl) Gen2, the following error is showed:
```
Traceback (most recent call last):
File "download_hf_dataset.py", line 143, in <module>
... | [
0.007943641394376755,
0.22752279043197632,
0.008019868284463882,
0.23792657256126404,
0.09995664656162262,
0.1969153881072998,
0.18387220799922943,
0.19614644348621368,
-0.05162261053919792,
-0.16205672919750214,
-0.02739519439637661,
-0.006244535557925701,
0.23231925070285797,
0.115774802... |
https://github.com/huggingface/datasets/issues/5153 | default Image/AudioFolder infers labels when there is no metadata files even if there is only one dir | Makes sense! For the last structure, we could count the path segments (delimited by "/" for URLs and `os.sep` for local paths) to ensure all inferred labels are on the same level. Otherwise, I think it's safe to assume they are meaningless and ignore them.
| ### Describe the bug
By default FolderBasedBuilder infers labels if there is not metadata files, even if it's meaningless (for example, they are in a single directory or in the root folder, see this repo as an example: https://huggingface.co/datasets/patrickvonplaten/audios
As this is a corner case for quick expl... | 45 | default Image/AudioFolder infers labels when there is no metadata files even if there is only one dir
### Describe the bug
By default FolderBasedBuilder infers labels if there is not metadata files, even if it's meaningless (for example, they are in a single directory or in the root folder, see this repo as an exa... | [
-0.19025085866451263,
0.02678552269935608,
0.04564252123236656,
0.46496856212615967,
0.19161538779735565,
-0.03204803913831711,
0.556429922580719,
-0.020104091614484787,
-0.00944617111235857,
0.4672832489013672,
-0.34523800015449524,
0.17693735659122467,
-0.23394906520843506,
-0.1699776947... |
https://github.com/huggingface/datasets/issues/5150 | Problems after upgrading to 2.6.1 | Hi! I can't reproduce the error following these steps. Can you please provide a reproducible example? | ### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of `Dataset`s, e.g., `DatasetDict({"tr... | 16 | Problems after upgrading to 2.6.1
### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of... | [
0.10454501211643219,
0.0607992559671402,
0.05969845876097679,
0.5349827408790588,
0.22519730031490326,
0.12659436464309692,
0.3924105167388916,
0.2159557342529297,
0.15846477448940277,
0.2107512652873993,
0.34398511052131653,
0.22761820256710052,
-0.14738380908966064,
-0.11087767779827118,... |
https://github.com/huggingface/datasets/issues/5150 | Problems after upgrading to 2.6.1 | I faced the same issue:
### Repro
```
!pip install datasets==2.6.1
import datasets as Dataset
dataset = Dataset.from_pandas(dataframe)
dataset.save_to_disk(local)
!pip install datasets==2.5.2
import datasets as Dataset
dataset = Dataset.load_from_disk(local)
```
| ### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of `Dataset`s, e.g., `DatasetDict({"tr... | 30 | Problems after upgrading to 2.6.1
### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of... | [
0.005164016038179398,
0.05801574885845184,
0.04512276127934456,
0.5168248414993286,
0.23230350017547607,
0.07308744639158249,
0.3342001438140869,
0.22718411684036255,
0.1912030279636383,
0.17448043823242188,
0.25057584047317505,
0.26578155159950256,
-0.11492929607629776,
-0.108805425465106... |
https://github.com/huggingface/datasets/issues/5150 | Problems after upgrading to 2.6.1 | I bumped into the issue too. @Lokiiiiii thanks for steps. I "solved" if for now by `pip install datasets>=2.6.1` everywhere. | ### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of `Dataset`s, e.g., `DatasetDict({"tr... | 20 | Problems after upgrading to 2.6.1
### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of... | [
-0.0006473995745182037,
0.0647660493850708,
0.03313672915101051,
0.5055516958236694,
0.2395569235086441,
0.07631459087133408,
0.3385421931743622,
0.27240437269210815,
0.1971953958272934,
0.16364777088165283,
0.2738051414489746,
0.24853959679603577,
-0.10855770856142044,
-0.0633110627532005... |
https://github.com/huggingface/datasets/issues/5150 | Problems after upgrading to 2.6.1 | Hi all,
I experienced the same issue.
Please note that the pull request is related to the IMDB example provided in the doc, and is a fix for that, in that context, to make sure that people can follow the doc example and have a working system.
It does not provide a fix for Datasets itself. | ### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of `Dataset`s, e.g., `DatasetDict({"tr... | 56 | Problems after upgrading to 2.6.1
### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of... | [
-0.02353217452764511,
0.18796074390411377,
0.036584172397851944,
0.5241067409515381,
0.17488601803779602,
0.09343991428613663,
0.40412962436676025,
0.2676888704299927,
0.18014955520629883,
0.1660766303539276,
0.2483799010515213,
0.22665992379188538,
-0.09475917369127274,
-0.068793438374996... |
https://github.com/huggingface/datasets/issues/5150 | Problems after upgrading to 2.6.1 | im getting the same error.
- using the base AWS HF container that uses a datasets <2.
- updating the AWS HF container to use dataset 2.4
| ### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of `Dataset`s, e.g., `DatasetDict({"tr... | 27 | Problems after upgrading to 2.6.1
### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of... | [
-0.045134227722883224,
0.08813954889774323,
0.07960566878318787,
0.4128674268722534,
0.16125161945819855,
0.05661221593618393,
0.3962489366531372,
0.24633632600307465,
0.2683168947696686,
0.14761196076869965,
0.24307268857955933,
0.09313531965017319,
-0.03807796537876129,
-0.03421617299318... |
https://github.com/huggingface/datasets/issues/5150 | Problems after upgrading to 2.6.1 | Same here, running on our SageMaker pipelines. It's only happening for some but not all of our saved Datasets. | ### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of `Dataset`s, e.g., `DatasetDict({"tr... | 19 | Problems after upgrading to 2.6.1
### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of... | [
-0.002203691750764847,
0.17898768186569214,
0.06423191726207733,
0.5237191319465637,
0.1632162630558014,
0.08636394888162613,
0.3798888027667999,
0.2597455680370331,
0.2343611717224121,
0.22525250911712646,
0.32204142212867737,
0.18334490060806274,
-0.16927596926689148,
-0.0096543282270431... |
https://github.com/huggingface/datasets/issues/5150 | Problems after upgrading to 2.6.1 | I am also receiving this error on Sagemaker but not locally, I have noticed that this occurs when the `.dataset/` folder does not contain a single file like:
`dataset.arrow`
but instead contains multiple files like:
`data-00000-of-00002.arrow`
`data-00001-of-00002.arrow`
I think that it may have something ... | ### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of `Dataset`s, e.g., `DatasetDict({"tr... | 160 | Problems after upgrading to 2.6.1
### Describe the bug
Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.
Context:
- Each individual dataset in the dict is created with `Dataset.from_pandas`
- The dataset_dict is create from a dict of... | [
-0.07980580627918243,
0.24414852261543274,
0.05264817550778389,
0.5432548522949219,
0.21042606234550476,
0.1146877333521843,
0.36532264947891235,
0.3461959660053253,
0.160641610622406,
0.21888881921768188,
0.3294399380683899,
0.194667786359787,
-0.2083081752061844,
-0.0751354992389679,
-... |
https://github.com/huggingface/datasets/issues/5148 | Cannot find the rvl_cdip dataset | Hi, @santule.
We have transferred all dataset scripts from GitHub to the Hugging Face Hub: https://huggingface.co/datasets
- Concretely, you have "rvl_cdip" here: https://huggingface.co/datasets/rvl_cdip
To be able to load them, you should update your `datasets` library:
```
pip install -U datasets
``` | Hi,
I am trying to use load_dataset to load the official "rvl_cdip" dataset but getting an error.
dataset = load_dataset("rvl_cdip")
Couldn't find 'rvl_cdip' on the Hugging Face Hub either: FileNotFoundError: Couldn't find the file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/rvl_cdi... | 41 | Cannot find the rvl_cdip dataset
Hi,
I am trying to use load_dataset to load the official "rvl_cdip" dataset but getting an error.
dataset = load_dataset("rvl_cdip")
Couldn't find 'rvl_cdip' on the Hugging Face Hub either: FileNotFoundError: Couldn't find the file at https://raw.githubusercontent.com/huggingfa... | [
-0.2679835259914398,
-0.46425873041152954,
-0.040703002363443375,
0.3554813265800476,
0.40039342641830444,
0.05472875386476517,
0.021672584116458893,
-0.02923392876982689,
0.08704401552677155,
0.1289827823638916,
-0.05772294104099274,
0.261880487203598,
-0.0781291276216507,
0.1051636412739... |
https://github.com/huggingface/datasets/issues/5147 | Allow ignoring kwargs inside fn_kwargs during dataset.map's fingerprinting | Hi ! In the `transformers` issue the object to not hash is a `Pool` - I think you can instantiate it inside your function instead of passing it as a parameter. It's good practice that your function and all its fn_kwargs are picklable, in case you want to parallelize `map` using `num_proc>1`
For the other case `def f... | ### Feature request
`dataset.map` accepts a `fn_kwargs` that is passed to `fn`. Currently, the whole `fn_kwargs` is used by `fingerprint_transform` to calculate the new fingerprint.
I'd like to be able to inform `fingerprint_transform` which `fn_kwargs` shoud/shouldn't be taken into account during hashing.
Of co... | 94 | Allow ignoring kwargs inside fn_kwargs during dataset.map's fingerprinting
### Feature request
`dataset.map` accepts a `fn_kwargs` that is passed to `fn`. Currently, the whole `fn_kwargs` is used by `fingerprint_transform` to calculate the new fingerprint.
I'd like to be able to inform `fingerprint_transform` whi... | [
-0.005865931510925293,
-0.06076231971383095,
-0.018343552947044373,
-0.19371993839740753,
-0.0050411708652973175,
0.1641051173210144,
0.3912358283996582,
0.16376887261867523,
0.20602382719516754,
0.034258365631103516,
0.12471693754196167,
0.36999616026878357,
-0.08079502731561661,
0.149871... |
https://github.com/huggingface/datasets/issues/5147 | Allow ignoring kwargs inside fn_kwargs during dataset.map's fingerprinting | Hi @lhoestq! Thanks for your response.
A `Pool` shouldn't be instantiated within the function, because there's a huge overhead in doing so. The main idea is that the same `Pool` should be used across all function calls. Parallel `map` is not helpful/desired in that specific scenario, because the heavy parallel compu... | ### Feature request
`dataset.map` accepts a `fn_kwargs` that is passed to `fn`. Currently, the whole `fn_kwargs` is used by `fingerprint_transform` to calculate the new fingerprint.
I'd like to be able to inform `fingerprint_transform` which `fn_kwargs` shoud/shouldn't be taken into account during hashing.
Of co... | 144 | Allow ignoring kwargs inside fn_kwargs during dataset.map's fingerprinting
### Feature request
`dataset.map` accepts a `fn_kwargs` that is passed to `fn`. Currently, the whole `fn_kwargs` is used by `fingerprint_transform` to calculate the new fingerprint.
I'd like to be able to inform `fingerprint_transform` whi... | [
-0.005865931510925293,
-0.06076231971383095,
-0.018343552947044373,
-0.19371993839740753,
-0.0050411708652973175,
0.1641051173210144,
0.3912358283996582,
0.16376887261867523,
0.20602382719516754,
0.034258365631103516,
0.12471693754196167,
0.36999616026878357,
-0.08079502731561661,
0.149871... |
https://github.com/huggingface/datasets/issues/5147 | Allow ignoring kwargs inside fn_kwargs during dataset.map's fingerprinting | > Would it be created for this specific purpose? Any downsides in just using datasets.fingerprint?
This can also go in datasets.fingerprint indeed - but maybe datasets.hashing tells more about what the register function does (i.e. register this function to have a custom hashing) ?
> And would datasets.hashing.reg... | ### Feature request
`dataset.map` accepts a `fn_kwargs` that is passed to `fn`. Currently, the whole `fn_kwargs` is used by `fingerprint_transform` to calculate the new fingerprint.
I'd like to be able to inform `fingerprint_transform` which `fn_kwargs` shoud/shouldn't be taken into account during hashing.
Of co... | 120 | Allow ignoring kwargs inside fn_kwargs during dataset.map's fingerprinting
### Feature request
`dataset.map` accepts a `fn_kwargs` that is passed to `fn`. Currently, the whole `fn_kwargs` is used by `fingerprint_transform` to calculate the new fingerprint.
I'd like to be able to inform `fingerprint_transform` whi... | [
-0.005865931510925293,
-0.06076231971383095,
-0.018343552947044373,
-0.19371993839740753,
-0.0050411708652973175,
0.1641051173210144,
0.3912358283996582,
0.16376887261867523,
0.20602382719516754,
0.034258365631103516,
0.12471693754196167,
0.36999616026878357,
-0.08079502731561661,
0.149871... |
https://github.com/huggingface/datasets/issues/5147 | Allow ignoring kwargs inside fn_kwargs during dataset.map's fingerprinting | > This can also go in datasets.fingerprint indeed - but maybe datasets.hashing tells more about what the register function does (i.e. register this function to have a custom hashing) ?
Sure, it makes sense.
---
I don't plan to work on it right now, so I'll let it unassigned in case somebody wants to join. I'll... | ### Feature request
`dataset.map` accepts a `fn_kwargs` that is passed to `fn`. Currently, the whole `fn_kwargs` is used by `fingerprint_transform` to calculate the new fingerprint.
I'd like to be able to inform `fingerprint_transform` which `fn_kwargs` shoud/shouldn't be taken into account during hashing.
Of co... | 65 | Allow ignoring kwargs inside fn_kwargs during dataset.map's fingerprinting
### Feature request
`dataset.map` accepts a `fn_kwargs` that is passed to `fn`. Currently, the whole `fn_kwargs` is used by `fingerprint_transform` to calculate the new fingerprint.
I'd like to be able to inform `fingerprint_transform` whi... | [
-0.005865931510925293,
-0.06076231971383095,
-0.018343552947044373,
-0.19371993839740753,
-0.0050411708652973175,
0.1641051173210144,
0.3912358283996582,
0.16376887261867523,
0.20602382719516754,
0.034258365631103516,
0.12471693754196167,
0.36999616026878357,
-0.08079502731561661,
0.149871... |
https://github.com/huggingface/datasets/issues/5145 | Dataset order is not deterministic with ZIP archives and `iter_files` | Thanks for reporting ! The issue doesn't come from shuffling, but from `beans` row order not being deterministic:
https://huggingface.co/datasets/beans/blob/main/beans.py uses `dl_manager.iter_files` on ZIP archives and the file order doesn't seen to be deterministic and changes across machines | ### Describe the bug
For the `beans` dataset (did not try on other), the order of samples is not the same on different machines. Tested on my local laptop, github actions machine, and ec2 instance. The three yield a different order.
### Steps to reproduce the bug
In a clean docker container or conda environmen... | 37 | Dataset order is not deterministic with ZIP archives and `iter_files`
### Describe the bug
For the `beans` dataset (did not try on other), the order of samples is not the same on different machines. Tested on my local laptop, github actions machine, and ec2 instance. The three yield a different order.
### Steps... | [
-0.021393075585365295,
0.04600512981414795,
0.010777506977319717,
0.38831663131713867,
0.00418979674577713,
-0.22980961203575134,
0.29644787311553955,
0.07253146171569824,
-0.31240716576576233,
0.24717368185520172,
0.1733967512845993,
0.6337769627571106,
0.19716888666152954,
-0.00771399028... |
https://github.com/huggingface/datasets/issues/5145 | Dataset order is not deterministic with ZIP archives and `iter_files` | This is still a bug, so I'd keep this one open if you don't mind ;) | ### Describe the bug
For the `beans` dataset (did not try on other), the order of samples is not the same on different machines. Tested on my local laptop, github actions machine, and ec2 instance. The three yield a different order.
### Steps to reproduce the bug
In a clean docker container or conda environmen... | 16 | Dataset order is not deterministic with ZIP archives and `iter_files`
### Describe the bug
For the `beans` dataset (did not try on other), the order of samples is not the same on different machines. Tested on my local laptop, github actions machine, and ec2 instance. The three yield a different order.
### Steps... | [
-0.18312685191631317,
0.15040865540504456,
-0.027092019096016884,
0.2876850962638855,
0.014623738825321198,
-0.2844901978969574,
0.2627815902233124,
0.09335668385028839,
-0.24766014516353607,
0.2108018696308136,
0.26034781336784363,
0.6107097864151001,
0.19777531921863556,
-0.0646839588880... |
https://github.com/huggingface/datasets/issues/5145 | Dataset order is not deterministic with ZIP archives and `iter_files` | Besides the linked PR, to make the loading process fully deterministic, I believe we should also sort the data files [here](https://github.com/huggingface/datasets/blob/df4bdd365f2abb695f113cbf8856a925bc70901b/src/datasets/data_files.py#L276) and [here](https://github.com/huggingface/datasets/blob/df4bdd365f2abb695f113... | ### Describe the bug
For the `beans` dataset (did not try on other), the order of samples is not the same on different machines. Tested on my local laptop, github actions machine, and ec2 instance. The three yield a different order.
### Steps to reproduce the bug
In a clean docker container or conda environmen... | 68 | Dataset order is not deterministic with ZIP archives and `iter_files`
### Describe the bug
For the `beans` dataset (did not try on other), the order of samples is not the same on different machines. Tested on my local laptop, github actions machine, and ec2 instance. The three yield a different order.
### Steps... | [
-0.17855557799339294,
0.14124345779418945,
-0.026052795350551605,
0.3417036533355713,
0.032715920358896255,
-0.29017287492752075,
0.23596049845218658,
0.09723290801048279,
-0.214439257979393,
0.1838478147983551,
0.21164555847644806,
0.6462437510490417,
0.2167438417673111,
-0.08832013607025... |
https://github.com/huggingface/datasets/issues/5145 | Dataset order is not deterministic with ZIP archives and `iter_files` | We already return the result sorted at the end of `_resolve_single_pattern_locally` and `_resolve_single_pattern_in_dataset_repository` if I'm not mistaken | ### Describe the bug
For the `beans` dataset (did not try on other), the order of samples is not the same on different machines. Tested on my local laptop, github actions machine, and ec2 instance. The three yield a different order.
### Steps to reproduce the bug
In a clean docker container or conda environmen... | 17 | Dataset order is not deterministic with ZIP archives and `iter_files`
### Describe the bug
For the `beans` dataset (did not try on other), the order of samples is not the same on different machines. Tested on my local laptop, github actions machine, and ec2 instance. The three yield a different order.
### Steps... | [
-0.1806086152791977,
0.14462769031524658,
-0.01702861115336418,
0.31182602047920227,
0.037609945982694626,
-0.3084612786769867,
0.27209702134132385,
0.1429557353258133,
-0.3288835287094116,
0.21146509051322937,
0.23483237624168396,
0.6990677714347839,
0.19552943110466003,
-0.08474083989858... |
https://github.com/huggingface/datasets/issues/5144 | Inconsistent documentation on map remove_columns | Thanks for reporting, @zhaowei-wang-nlp.
You are right, the documentation is confusing on the behavior of `remove_columns`. We should better explain it. | ### Describe the bug
The page [process](https://huggingface.co/docs/datasets/process) says this about the parameter `remove_columns` of the function `map`:
When you remove a column, it is only removed after the example has been provided to the mapped function.
So it seems that the `remove_columns` parameter remo... | 21 | Inconsistent documentation on map remove_columns
### Describe the bug
The page [process](https://huggingface.co/docs/datasets/process) says this about the parameter `remove_columns` of the function `map`:
When you remove a column, it is only removed after the example has been provided to the mapped function.
S... | [
0.2784156799316406,
-0.29798218607902527,
0.022663231939077377,
0.33704590797424316,
0.1380022168159485,
0.03696826845407486,
0.283779501914978,
-0.08477602899074554,
0.33134761452674866,
0.1609838902950287,
-0.00917185191065073,
0.3571145534515381,
0.03383171185851097,
-0.1418278366327285... |
https://github.com/huggingface/datasets/issues/5144 | Inconsistent documentation on map remove_columns | I'm closing this issue because as @mariosasko pointed out, it is a duplicate of:
- #2343 | ### Describe the bug
The page [process](https://huggingface.co/docs/datasets/process) says this about the parameter `remove_columns` of the function `map`:
When you remove a column, it is only removed after the example has been provided to the mapped function.
So it seems that the `remove_columns` parameter remo... | 16 | Inconsistent documentation on map remove_columns
### Describe the bug
The page [process](https://huggingface.co/docs/datasets/process) says this about the parameter `remove_columns` of the function `map`:
When you remove a column, it is only removed after the example has been provided to the mapped function.
S... | [
0.2650564908981323,
-0.2812565565109253,
0.024679332971572876,
0.33554911613464355,
0.14320142567157745,
0.03953517973423004,
0.27158570289611816,
-0.05271774157881737,
0.36217960715293884,
0.14966340363025665,
0.035073958337306976,
0.34748587012290955,
0.04819265380501747,
-0.161278560757... |
https://github.com/huggingface/datasets/issues/5143 | DownloadManager Git LFS support | Hey ! Actually it works, just pass the right URL ;)
The URL must be the one with “/resolve/”
e.g. https://huggingface.co/datasets/imagenet-1k/resolve/main/data/test_images.tar.gz
You can even pass a relative path to the dl_manager instead, like `dl_manager.download("data/test_images.tar.gz")` | ### Feature request
Maybe I'm mistaken but the `DownloadManager` does not support extracting git lfs files out of the box right?
Using `dl_manager.download()` or `dl_manager.download_and_extract()` still returns lfs files afaict.
Is there a good way to write a dataset loading script for a repo with lfs files?
##... | 34 | DownloadManager Git LFS support
### Feature request
Maybe I'm mistaken but the `DownloadManager` does not support extracting git lfs files out of the box right?
Using `dl_manager.download()` or `dl_manager.download_and_extract()` still returns lfs files afaict.
Is there a good way to write a dataset loading scr... | [
-0.5225303769111633,
0.3553297817707062,
-0.04971427842974663,
0.4681498408317566,
0.256860613822937,
-0.08727490901947021,
0.16220106184482574,
0.3804178237915039,
0.48680031299591064,
0.1062220111489296,
-0.2246224731206894,
0.13744805753231049,
-0.18170994520187378,
0.15916064381599426,... |
https://github.com/huggingface/datasets/issues/5137 | Align task tags in dataset metadata | I have opened PRs to fix the task_ids in all datasets within a namespace as well.
Working on task_categories... | ## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datasets
- [x] task_categories: 451 datas... | 19 | Align task tags in dataset metadata
## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datase... | [
-0.4368460774421692,
0.016752511262893677,
-0.2623390853404999,
0.06745804846286774,
0.17841649055480957,
-0.17061728239059448,
0.2457362562417984,
0.2065170854330063,
0.015394385904073715,
0.2156161069869995,
-0.037551023066043854,
0.29545581340789795,
0.013874136842787266,
0.391051411628... |
https://github.com/huggingface/datasets/issues/5137 | Align task tags in dataset metadata | For future reference: this fix had some complications
When trying to open a PR to fix the task tags, an exception was thrown if:
- the metadata contained "languages" or "licenses" (instead of "language" or "license")
- the metadata contained a non-valid language: `en-US` (instead of `en`), `no` (instead of `'no'`)... | ## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datasets
- [x] task_categories: 451 datas... | 169 | Align task tags in dataset metadata
## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datase... | [
-0.5523923635482788,
0.08546960353851318,
-0.17715725302696228,
0.08637500554323196,
0.18943241238594055,
-0.14889079332351685,
0.24858936667442322,
0.23581744730472565,
0.099764883518219,
0.2163870930671692,
-0.09413597732782364,
0.45032989978790283,
-0.009858478792011738,
0.3813338577747... |
https://github.com/huggingface/datasets/issues/5137 | Align task tags in dataset metadata | Yes, @julien-c. These are some of the feedbacks:
- Most people just thank for the fix: [cahya/librivox-indonesia](https://huggingface.co/datasets/cahya/librivox-indonesia/discussions/1#6357cd8a292a050ebd705f84), [TurkuNLP/xlsum-fi](https://huggingface.co/datasets/TurkuNLP/xlsum-fi/discussions/1#6357828aa1f8ad1c31bcbe4... | ## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datasets
- [x] task_categories: 451 datas... | 189 | Align task tags in dataset metadata
## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datase... | [
-0.4031170606613159,
0.06738302111625671,
-0.2060859054327011,
-0.03661643713712692,
0.15056931972503662,
-0.2056995928287506,
0.19062437117099762,
0.30846714973449707,
0.021493390202522278,
0.1598738133907318,
-0.20700135827064514,
0.2251671403646469,
0.08066467940807343,
0.48286437988281... |
https://github.com/huggingface/datasets/issues/5137 | Align task tags in dataset metadata | As someone with feedback on the updates (which I highly appreciate seeing included here :D), a few comments from a "user perspective":
* I think the general confusion for me was also surrounding the hierarchy; it doesn't really become super clear (even when using the tagger space) that one is a subset of the other... | ## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datasets
- [x] task_categories: 451 datas... | 216 | Align task tags in dataset metadata
## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datase... | [
-0.4204704761505127,
0.22354808449745178,
-0.19335894286632538,
-0.04848835617303848,
0.13828012347221375,
-0.07244402170181274,
0.10605517029762268,
0.2928413450717926,
-0.009969361126422882,
0.020484723150730133,
-0.15161719918251038,
0.4007692039012909,
-0.03414963558316231,
0.376885235... |
https://github.com/huggingface/datasets/issues/5137 | Align task tags in dataset metadata | Thanks to you both for your feedback! super useful! cc'ing @osanseviero too 🙂
> The datasets explorer still shows tags that are no longer valid
wait which explorer is that? is it https://huggingface.co/datasets/viewer/ ?
| ## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datasets
- [x] task_categories: 451 datas... | 34 | Align task tags in dataset metadata
## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datase... | [
-0.47998085618019104,
0.1701505482196808,
-0.18582399189472198,
0.15901131927967072,
0.14320895075798035,
-0.11162927746772766,
0.18686769902706146,
0.18362505733966827,
0.017176374793052673,
0.1275055706501007,
-0.13632506132125854,
0.30775824189186096,
-0.06249284744262695,
0.50135111808... |
https://github.com/huggingface/datasets/issues/5137 | Align task tags in dataset metadata | - Some people do not agree about current "hierarchy":
- symbolic-regression: [yoshitomo-matsubara/srsd-feynman_hard](https://huggingface.co/datasets/yoshitomo-matsubara/srsd-feynman_hard/discussions/2#63614194c12a09b8a31457cc), [yoshitomo-matsubara/srsd-feynman_medium](https://huggingface.co/datasets/yoshitomo-matsu... | ## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datasets
- [x] task_categories: 451 datas... | 21 | Align task tags in dataset metadata
## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datase... | [
-0.442884624004364,
-0.005620621144771576,
-0.19131524860858917,
0.03644504025578499,
0.07210005074739456,
-0.19481422007083893,
0.32549312710762024,
0.21850533783435822,
0.1132032722234726,
0.2021963894367218,
-0.0025847251527011395,
0.3101688325405121,
-0.02433440089225769,
0.46083092689... |
https://github.com/huggingface/datasets/issues/5137 | Align task tags in dataset metadata | @albertvillanova
Thank you for sharing our voice here!
Yes, we want `symbolic-regression` to be listed as a task. This task has been attracting attention from the machine learning/deep learning community, and unfortunately existing symbolic regression datasets are de-centralized in the community (hosted at individ... | ## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datasets
- [x] task_categories: 451 datas... | 64 | Align task tags in dataset metadata
## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datase... | [
-0.27145084738731384,
-0.0036713778972625732,
-0.18218624591827393,
-0.14358840882778168,
0.11106597632169724,
-0.010412119328975677,
0.3569692075252533,
0.09038525819778442,
0.20404158532619476,
0.06712514162063599,
0.06111757457256317,
0.3600502610206604,
-0.16980160772800446,
0.58084011... |
https://github.com/huggingface/datasets/issues/5134 | Raise ImportError instead of OSError if required extraction library is not installed | hey @mariosasko , i made a pr for this issue. Could you please review it.
Also i found multiple `OSError` in `extract.py` file which i thought could be replaced too but wasn't sure about them.
Please do tell if that also needs to be done. | According to the official Python docs, `OSError` should be thrown in the following situations:
> This exception is raised when a system function returns a system-related error, including I/O failures such as “file not found” or “disk full” (not for illegal argument types or other incidental errors).
Hence, it makes... | 45 | Raise ImportError instead of OSError if required extraction library is not installed
According to the official Python docs, `OSError` should be thrown in the following situations:
> This exception is raised when a system function returns a system-related error, including I/O failures such as “file not found” or “dis... | [
0.13113847374916077,
-0.10024960339069366,
-0.0478091761469841,
-0.041649237275123596,
-0.04420727491378784,
-0.15195387601852417,
0.048548296093940735,
0.06685023009777069,
0.18493899703025818,
0.42027950286865234,
0.11480434983968735,
0.295774906873703,
-0.12839074432849884,
0.0103116761... |
https://github.com/huggingface/datasets/issues/5133 | Tensor operation not functioning in dataset mapping | Hi! The Torch ops in your snippet are not equivalent to the NumPy ones, hence the difference. You can get the same behavior by replacing the line `feature = torch.mean(feature, dim=1)` with `feature = feature.squeeze().mean(1)` . | ## Describe the bug
I'm doing a torch.mean() operation in data preprocessing, and it's not working.
## Steps to reproduce the bug
```
from transformers import pipeline
import torch
import numpy as np
from datasets import load_dataset
device = 'cuda:0'
raw_dataset = load_dataset("glue", "sst2")
feature_extra... | 36 | Tensor operation not functioning in dataset mapping
## Describe the bug
I'm doing a torch.mean() operation in data preprocessing, and it's not working.
## Steps to reproduce the bug
```
from transformers import pipeline
import torch
import numpy as np
from datasets import load_dataset
device = 'cuda:0'
raw... | [
-0.31599900126457214,
-0.485085666179657,
0.001089518889784813,
0.2954884171485901,
0.22902525961399078,
-0.08756133913993835,
0.5998207330703735,
0.16039983928203583,
-0.09626495838165283,
0.3030318319797516,
-0.0017559886910021305,
0.3639741837978363,
0.14919818937778473,
-0.370071083307... |
https://github.com/huggingface/datasets/issues/5133 | Tensor operation not functioning in dataset mapping | > Hi! The Torch ops in your snippet are not equivalent to the NumPy ones, hence the difference. You can get the same behavior by replacing the line `feature = torch.mean(feature, dim=1)` with `feature = feature.squeeze().mean(1)` .
Thank you. | ## Describe the bug
I'm doing a torch.mean() operation in data preprocessing, and it's not working.
## Steps to reproduce the bug
```
from transformers import pipeline
import torch
import numpy as np
from datasets import load_dataset
device = 'cuda:0'
raw_dataset = load_dataset("glue", "sst2")
feature_extra... | 39 | Tensor operation not functioning in dataset mapping
## Describe the bug
I'm doing a torch.mean() operation in data preprocessing, and it's not working.
## Steps to reproduce the bug
```
from transformers import pipeline
import torch
import numpy as np
from datasets import load_dataset
device = 'cuda:0'
raw... | [
-0.3032844066619873,
-0.5189120769500732,
-0.0023396704345941544,
0.3160865902900696,
0.2063223123550415,
-0.08732113242149353,
0.5950582027435303,
0.15039870142936707,
-0.09797559678554535,
0.28440380096435547,
-0.009615662507712841,
0.3572492003440857,
0.1431005448102951,
-0.368685126304... |
https://github.com/huggingface/datasets/issues/5131 | WikiText 103 tokenizer hangs | any updates on this? It happens to me on [OpenWikiText-20%](https://huggingface.co/datasets/Bingsu/openwebtext_20p) dataset, but not on [OpenWebText-10k](https://huggingface.co/datasets/stas/openwebtext-10k). This is really strange because I don't change anything else in my running script.
transformers version 4.18.... | See issue here: https://github.com/huggingface/transformers/issues/19702 | 35 | WikiText 103 tokenizer hangs
See issue here: https://github.com/huggingface/transformers/issues/19702
any updates on this? It happens to me on [OpenWikiText-20%](https://huggingface.co/datasets/Bingsu/openwebtext_20p) dataset, but not on [OpenWebText-10k](https://huggingface.co/datasets/stas/openwebtext-10k). This... | [
0.03930788114666939,
-0.5219099521636963,
0.05311049893498421,
-0.07705706357955933,
0.3084469437599182,
-0.17780792713165283,
0.4431420564651489,
-0.07915535569190979,
-0.07170720398426056,
0.10493890941143036,
-0.11941280961036682,
0.2056075930595398,
0.129560649394989,
-0.08266098797321... |
https://github.com/huggingface/datasets/issues/5129 | unexpected `cast` or `class_encode_column` result after `rename_column` | Hi! Unfortunately, I can't reproduce this issue locally (in Python 3.7/3.10) or in Colab. I would assume this is due to a bug we fixed in the latest release, but your version is up-to-date, so I'm not sure if there is something we can do to help... | ## Describe the bug
When invoke `cast` or `class_encode_column` to a colunm renamed by `rename_column` , it will convert all the variables in this column into one variable. I also run this script in version 2.5.2, this bug does not appear. So I switched to the older version.
## Steps to reproduce the bug
```python... | 47 | unexpected `cast` or `class_encode_column` result after `rename_column`
## Describe the bug
When invoke `cast` or `class_encode_column` to a colunm renamed by `rename_column` , it will convert all the variables in this column into one variable. I also run this script in version 2.5.2, this bug does not appear. So I ... | [
0.24168212711811066,
0.03820769488811493,
-0.0036129411309957504,
0.14938554167747498,
0.9369388818740845,
0.14646252989768982,
0.3778993785381317,
0.36240869760513306,
-0.3428438603878021,
0.18796268105506897,
-0.04112548381090164,
0.36037856340408325,
-0.08040358871221542,
-0.05424144864... |
https://github.com/huggingface/datasets/issues/5129 | unexpected `cast` or `class_encode_column` result after `rename_column` | Hi, 方子东. I tried running the code with exact the same configuration (both datasets 2.5.2 and 2.6.1, python, pyarrow, pandas), but on Linux. The results seem to be the expected `{<pyarrow.Int64Scalar: 4>, <pyarrow.Int64Scalar: 2>, <pyarrow.Int64Scalar: 3>, <pyarrow.Int64Scalar: 0>, <pyarrow.Int64Scalar: 1>}`.
I don't h... | ## Describe the bug
When invoke `cast` or `class_encode_column` to a colunm renamed by `rename_column` , it will convert all the variables in this column into one variable. I also run this script in version 2.5.2, this bug does not appear. So I switched to the older version.
## Steps to reproduce the bug
```python... | 56 | unexpected `cast` or `class_encode_column` result after `rename_column`
## Describe the bug
When invoke `cast` or `class_encode_column` to a colunm renamed by `rename_column` , it will convert all the variables in this column into one variable. I also run this script in version 2.5.2, this bug does not appear. So I ... | [
0.24168212711811066,
0.03820769488811493,
-0.0036129411309957504,
0.14938554167747498,
0.9369388818740845,
0.14646252989768982,
0.3778993785381317,
0.36240869760513306,
-0.3428438603878021,
0.18796268105506897,
-0.04112548381090164,
0.36037856340408325,
-0.08040358871221542,
-0.05424144864... |
https://github.com/huggingface/datasets/issues/5129 | unexpected `cast` or `class_encode_column` result after `rename_column` | > Hi! Unfortunately, I can't reproduce this issue locally (in Python 3.7/3.10) or in Colab. I would assume this is due to a bug we fixed in the latest release, but your version is up-to-date, so I'm not sure if there is something we can do to help...
Thank you for your attention and feel sorry to take your time. Sin... | ## Describe the bug
When invoke `cast` or `class_encode_column` to a colunm renamed by `rename_column` , it will convert all the variables in this column into one variable. I also run this script in version 2.5.2, this bug does not appear. So I switched to the older version.
## Steps to reproduce the bug
```python... | 99 | unexpected `cast` or `class_encode_column` result after `rename_column`
## Describe the bug
When invoke `cast` or `class_encode_column` to a colunm renamed by `rename_column` , it will convert all the variables in this column into one variable. I also run this script in version 2.5.2, this bug does not appear. So I ... | [
0.24168212711811066,
0.03820769488811493,
-0.0036129411309957504,
0.14938554167747498,
0.9369388818740845,
0.14646252989768982,
0.3778993785381317,
0.36240869760513306,
-0.3428438603878021,
0.18796268105506897,
-0.04112548381090164,
0.36037856340408325,
-0.08040358871221542,
-0.05424144864... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | @lhoestq I tested the script without accelerator, and I confirm this is due to datasets part as this gets similar results without accelerator. | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 23 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | Hi ! You said it works on 1 GPU but doesn't wortk without accelerator - what's the difference between running on 1 GPU and running without accelerator in your case ? | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 31 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | Hi @lhoestq
thanks for coming back to me. Sorry for the confusion I made. I meant this works fine on 1 GPU, but on multi-gpu it is freezing. "accelerator" is not an issue as if you adapt the code without accelerator this still gets the same issue.
In order to test it. Please run "accelerate config", then use the set... | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 79 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | Hi @lhoestq
could you have the chance to reproduce the error by running the minimal example shared?
thanks | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 18 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | I think you need to do `train_dataset = train_dataset.with_format("torch")` to work with the DataLoader in a multiprocessing setup :)
The hang is probably caused by our streamign lib `fsspec` which doesn't work in multiprocessing out of the box - but we made it work with the PyTorch DataLoader when the dataset forma... | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 56 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | Hi @lhoestq
thanks for the response. I added the line suggested right before calling `with accelerator.main_process_first():` in the code above and I confirm this also freezes. to reproduce it please run "accelerate launch code.py". I was wondering if you could have more suggestions for me? I do not have an idea how... | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 61 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | Maybe the `fsspec` stuff need to be clearer even before - can you try to run this function at the very beginning of your script ?
```python
import fsspec
def _set_fsspec_for_multiprocess() -> None:
"""
Clear reference to the loop and thread.
This is necessary otherwise HTTPFileSystem hangs in the ML... | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 69 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | Hi @lhoestq
thank you. I tried it, I am getting `AttributeError: module 'fsspec' has no attribute 'asyn'`. which version of fsspect do you use?
I am using
```fsspec 2022.8.2 pypi_0 pypi```
thank you. | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 33 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | Hi @lhoestq
I solved `fsspec` error with this hack for now https://discuss.huggingface.co/t/attributeerror-module-fsspec-has-no-attribute-asyn/19255 but this is still freezing, I greatly appreciate if you could run this script on your side. Many thanks.
```
import fsspec
def _set_fsspec_for_multiprocess() -> N... | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 472 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | Are you using `Pytorch 1.11`? Otherwise the script freezes because of the shuffling in this line:
```
return ShufflerIterDataPipe(self, buffer_size=buffer_size)
```
`ShufflerIterDataPipe` behavior must have changed for newer Pytorch versions. But this doesn't change whether you're using streaming or not in... | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 52 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5123 | datasets freezes with streaming mode in multiple-gpu | > Are you using `Pytorch 1.11`? Otherwise the script freezes because of the shuffling in this line:
>
> ```
> return ShufflerIterDataPipe(self, buffer_size=buffer_size)
> ```
>
> `ShufflerIterDataPipe` behavior must have changed for newer Pytorch versions. But this doesn't change whether you're using st... | ## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe978afc/examples/research_projects/codeparrot/scripts/cod... | 83 | datasets freezes with streaming mode in multiple-gpu
## Describe the bug
Hi. I am using this dataloader, which is for processing large datasets in streaming mode mentioned in one of examples of huggingface. I am using it to read c4: https://github.com/huggingface/transformers/blob/b48ac1a094e572d6076b46a9e4ed3e0ebe9... | [
-0.320170134305954,
-0.31651610136032104,
-0.039002928882837296,
0.4769468307495117,
0.32108551263809204,
-0.05959709361195564,
0.370758980512619,
-0.0028037503361701965,
0.29125797748565674,
0.27730265259742737,
-0.1412859410047531,
0.06606162339448929,
-0.1297413855791092,
0.389516144990... |
https://github.com/huggingface/datasets/issues/5117 | Progress bars have color red and never completed to 100% | Hi @echatzikyriakidis, thanks for submitting the issue.
Which shell are you using exactly? I tried to run the command you sent, but I don't see colors at all 🧐
I tried from bash and zsh as well. | ## Describe the bug
Progress bars after transformative operations turn in red and never be completed to 100%
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset('rotten_tomatoes', split='test').filter(lambda o: True)
```
## Expected results
Progress bar should be 100% an... | 37 | Progress bars have color red and never completed to 100%
## Describe the bug
Progress bars after transformative operations turn in red and never be completed to 100%
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset('rotten_tomatoes', split='test').filter(lambda o: True)
... | [
-0.39734846353530884,
0.043209508061409,
-0.10254928469657898,
-0.029496580362319946,
0.3089589476585388,
-0.11117610335350037,
0.13297230005264282,
0.38976994156837463,
-0.28815367817878723,
0.09463697671890259,
0.04255276173353195,
0.5570790767669678,
0.1608472466468811,
0.19700902700424... |
https://github.com/huggingface/datasets/issues/5117 | Progress bars have color red and never completed to 100% | Got it. I [created a PR](https://github.com/huggingface/datasets/pull/5120) that fixes this issue. Turns out that the wrapping logic for the inner loop was slightly incorrect. | ## Describe the bug
Progress bars after transformative operations turn in red and never be completed to 100%
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset('rotten_tomatoes', split='test').filter(lambda o: True)
```
## Expected results
Progress bar should be 100% an... | 23 | Progress bars have color red and never completed to 100%
## Describe the bug
Progress bars after transformative operations turn in red and never be completed to 100%
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset('rotten_tomatoes', split='test').filter(lambda o: True)
... | [
-0.3259928524494171,
0.1697705090045929,
-0.08464694768190384,
-0.1609392762184143,
0.3235743045806885,
-0.1941778063774109,
0.12783411145210266,
0.3235280513763428,
-0.17735134065151215,
0.05086398124694824,
-0.04770611226558685,
0.6858978867530823,
0.3134889006614685,
0.3177017271518707,... |
https://github.com/huggingface/datasets/issues/5117 | Progress bars have color red and never completed to 100% | Hello @mariosasko
I am still facing this issue. Was this problem fixed?
I cleared the hugging face cache before running, and no error message was given. Let me know if you nee... | ## Describe the bug
Progress bars after transformative operations turn in red and never be completed to 100%
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset('rotten_tomatoes', split='test').filter(lambda o: True)
```
## Expected results
Progress bar should be 100% an... | 46 | Progress bars have color red and never completed to 100%
## Describe the bug
Progress bars after transformative operations turn in red and never be completed to 100%
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset('rotten_tomatoes', split='test').filter(lambda o: True)
... | [
-0.23909001052379608,
-0.04158295691013336,
-0.05195482447743416,
-0.052215225994586945,
0.4029645323753357,
-0.15426728129386902,
0.1198558658361435,
0.35057806968688965,
-0.1880609393119812,
-0.008815169334411621,
-0.013552581891417503,
0.43634656071662903,
0.25479012727737427,
0.3528019... |
https://github.com/huggingface/datasets/issues/5114 | load_from_disk with remote filesystem fails due to a wrong temporary local folder path | Hi Hubert! Could you please probably create a publicly available `gs://` dataset link? I think this would be easier for others to directly start to debug. | ## Describe the bug
The function load_from_disk fails when using a remote filesystem because of a wrong temporary path generation in the load_from_disk method of arrow_dataset.py:
```python
if is_remote_filesystem(fs):
src_dataset_path = extract_path_from_uri(dataset_path)
dataset_path = Dataset._build... | 26 | load_from_disk with remote filesystem fails due to a wrong temporary local folder path
## Describe the bug
The function load_from_disk fails when using a remote filesystem because of a wrong temporary path generation in the load_from_disk method of arrow_dataset.py:
```python
if is_remote_filesystem(fs):
... | [
-0.1440090388059616,
-0.26802510023117065,
0.03857989236712456,
0.34252285957336426,
0.25744205713272095,
-0.2235642671585083,
0.27048778533935547,
0.08593133091926575,
0.2562037408351898,
0.10422718524932861,
0.25353866815567017,
0.41236525774002075,
-0.27618831396102905,
-0.3879764378070... |
https://github.com/huggingface/datasets/issues/5112 | Bug with filtered indices | Thanks a lot for the swift response! For a brief moment yesterday I thought I had gone insane 🤣On 14 Oct 2022, at 15:44, Albert Villanova del Moral ***@***.***> wrote:
@PartiallyTyped, @Muennighoff: the issue is fixed.
We are planning to make a patch release today.
—Reply to this email directly, view it on GitHub, o... | ## Describe the bug
As reported by @PartiallyTyped (and by @Muennighoff):
- https://github.com/huggingface/datasets/issues/5111#issuecomment-1278652524
There is an issue with the indices of a filtered dataset.
## Steps to reproduce the bug
```python
ds = Dataset.from_dict({"num": [0, 1, 2, 3]})
ds = ds.filte... | 65 | Bug with filtered indices
## Describe the bug
As reported by @PartiallyTyped (and by @Muennighoff):
- https://github.com/huggingface/datasets/issues/5111#issuecomment-1278652524
There is an issue with the indices of a filtered dataset.
## Steps to reproduce the bug
```python
ds = Dataset.from_dict({"num": [... | [
0.03610451892018318,
-0.20418207347393036,
-0.15221655368804932,
0.2889057993888855,
0.22757285833358765,
-0.043692272156476974,
0.42200204730033875,
0.23539286851882935,
0.16573308408260345,
0.4011458158493042,
0.012838178314268589,
0.29628217220306396,
0.02044648490846157,
0.336529046297... |
https://github.com/huggingface/datasets/issues/5111 | map and filter not working properly in multiprocessing with the new release 2.6.0 | Thanks for reporting, @loubnabnl and for the additional information, @PartiallyTyped.
However, I'm not able to reproduce this issue, neither locally nor on Colab:
```
Dataset({
features: ['repo_name', 'path', 'copies', 'size', 'content', 'license', 'hash', 'line_mean', 'line_max', 'alpha_frac', 'autogenerated... | ## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc` in filter for it to work properly. This doesn't happen with `datasets` version 2.5... | 63 | map and filter not working properly in multiprocessing with the new release 2.6.0
## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc... | [
-0.29330000281333923,
-0.09082433581352234,
-0.12948650121688843,
0.18801119923591614,
-0.08888343721628189,
-0.49709072709083557,
0.2094753533601761,
0.24282652139663696,
0.20070987939834595,
0.06659423559904099,
0.037694431841373444,
0.41527029871940613,
-0.10309305042028427,
0.175759777... |
https://github.com/huggingface/datasets/issues/5111 | map and filter not working properly in multiprocessing with the new release 2.6.0 | This is the minimum reproducible example. I ran this on the premium instances of colab.
```
# !pip install datasets
import datasets
from datasets import load_dataset
ds = load_dataset("copenlu/answerable_tydiqa").filter("english".__eq__, input_columns="language")
assert all(map("english".__eq__, ds["train"]["la... | ## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc` in filter for it to work properly. This doesn't happen with `datasets` version 2.5... | 96 | map and filter not working properly in multiprocessing with the new release 2.6.0
## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc... | [
-0.29330000281333923,
-0.09082433581352234,
-0.12948650121688843,
0.18801119923591614,
-0.08888343721628189,
-0.49709072709083557,
0.2094753533601761,
0.24282652139663696,
0.20070987939834595,
0.06659423559904099,
0.037694431841373444,
0.41527029871940613,
-0.10309305042028427,
0.175759777... |
https://github.com/huggingface/datasets/issues/5111 | map and filter not working properly in multiprocessing with the new release 2.6.0 | I can reproduce the issue on my mac too
```
- `datasets` version: 2.6.0
- Platform: macOS-12.2.1-arm64-arm-64bit
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.4.3
```
But not on Colab with python 3.7, maybe related to python version? (didn't manage to install python 3.9)
```
- `datase... | ## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc` in filter for it to work properly. This doesn't happen with `datasets` version 2.5... | 69 | map and filter not working properly in multiprocessing with the new release 2.6.0
## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc... | [
-0.29330000281333923,
-0.09082433581352234,
-0.12948650121688843,
0.18801119923591614,
-0.08888343721628189,
-0.49709072709083557,
0.2094753533601761,
0.24282652139663696,
0.20070987939834595,
0.06659423559904099,
0.037694431841373444,
0.41527029871940613,
-0.10309305042028427,
0.175759777... |
https://github.com/huggingface/datasets/issues/5111 | map and filter not working properly in multiprocessing with the new release 2.6.0 | I think there are 2 different issues here:
- the one reported by @loubnabnl is related to multiprocessing in map and then filter; we should reproduce it first: I have tried with Python version 3.9.7 and I can't reproduce it either; maybe it is related to the version of PyArrow? To be checked.
- the issue reported by ... | ## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc` in filter for it to work properly. This doesn't happen with `datasets` version 2.5... | 71 | map and filter not working properly in multiprocessing with the new release 2.6.0
## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc... | [
-0.29330000281333923,
-0.09082433581352234,
-0.12948650121688843,
0.18801119923591614,
-0.08888343721628189,
-0.49709072709083557,
0.2094753533601761,
0.24282652139663696,
0.20070987939834595,
0.06659423559904099,
0.037694431841373444,
0.41527029871940613,
-0.10309305042028427,
0.175759777... |
https://github.com/huggingface/datasets/issues/5111 | map and filter not working properly in multiprocessing with the new release 2.6.0 | Could you create another issue for the @PartiallyTyped one please ?
Regarding the OP issue, I also tried on colab or locally on py3.7 or py3.10 but didn't reproduce | ## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc` in filter for it to work properly. This doesn't happen with `datasets` version 2.5... | 29 | map and filter not working properly in multiprocessing with the new release 2.6.0
## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc... | [
-0.29330000281333923,
-0.09082433581352234,
-0.12948650121688843,
0.18801119923591614,
-0.08888343721628189,
-0.49709072709083557,
0.2094753533601761,
0.24282652139663696,
0.20070987939834595,
0.06659423559904099,
0.037694431841373444,
0.41527029871940613,
-0.10309305042028427,
0.175759777... |
https://github.com/huggingface/datasets/issues/5111 | map and filter not working properly in multiprocessing with the new release 2.6.0 | I managed to reproduce your issue @loubnabnl on colab by upgrading pyarrow to 9.0.0 instead of 6.0.1 | ## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc` in filter for it to work properly. This doesn't happen with `datasets` version 2.5... | 17 | map and filter not working properly in multiprocessing with the new release 2.6.0
## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc... | [
-0.29330000281333923,
-0.09082433581352234,
-0.12948650121688843,
0.18801119923591614,
-0.08888343721628189,
-0.49709072709083557,
0.2094753533601761,
0.24282652139663696,
0.20070987939834595,
0.06659423559904099,
0.037694431841373444,
0.41527029871940613,
-0.10309305042028427,
0.175759777... |
https://github.com/huggingface/datasets/issues/5111 | map and filter not working properly in multiprocessing with the new release 2.6.0 | I managed to have a _super_ minimal reproducible example:
```python
from datasets import Dataset, concatenate_datasets
ds = concatenate_datasets([Dataset.from_dict({"a": [i]}) for i in range(10)])
ds2 = ds.map(lambda _: {}, batched=True)
assert list(ds2) == list(ds)
```
(filter uses a batched `map` under the... | ## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc` in filter for it to work properly. This doesn't happen with `datasets` version 2.5... | 42 | map and filter not working properly in multiprocessing with the new release 2.6.0
## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc... | [
-0.29330000281333923,
-0.09082433581352234,
-0.12948650121688843,
0.18801119923591614,
-0.08888343721628189,
-0.49709072709083557,
0.2094753533601761,
0.24282652139663696,
0.20070987939834595,
0.06659423559904099,
0.037694431841373444,
0.41527029871940613,
-0.10309305042028427,
0.175759777... |
https://github.com/huggingface/datasets/issues/5111 | map and filter not working properly in multiprocessing with the new release 2.6.0 | > the one reported by @loubnabnl is related to multiprocessing in map and then filter; we should reproduce it first: I have tried with Python version 3.9.7 and I can't reproduce it either; maybe it is related to the version of PyArrow? To be checked.
So finally it was related to PyArrow version! :+1: | ## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc` in filter for it to work properly. This doesn't happen with `datasets` version 2.5... | 54 | map and filter not working properly in multiprocessing with the new release 2.6.0
## Describe the bug
When mapping is used on a dataset with more than one process, there is a weird behavior when trying to use `filter` , it's like only the samples from one worker are retrieved, one needs to specify the same `num_proc... | [
-0.29330000281333923,
-0.09082433581352234,
-0.12948650121688843,
0.18801119923591614,
-0.08888343721628189,
-0.49709072709083557,
0.2094753533601761,
0.24282652139663696,
0.20070987939834595,
0.06659423559904099,
0.037694431841373444,
0.41527029871940613,
-0.10309305042028427,
0.175759777... |
https://github.com/huggingface/datasets/issues/5109 | Map caching not working for some class methods | The hash used for caching is computed by pickling recursively the function passed to `map`. Maybe some objects don't have the same hash across sessions. In particular you can check the hash of your model using
```python
from datasets.fingerprint import Hasher
obj = AutoModel.from_config(config=config, add_pooling_l... | ## Describe the bug
The cache loading is not working as expected for some class methods with a model stored in an attribute.
The new fingerprint for `_map_single` is not the same at each run. The hasher generate a different hash for the class method.
This comes from `dumps` function in `datasets.utils.py_utils` whic... | 71 | Map caching not working for some class methods
## Describe the bug
The cache loading is not working as expected for some class methods with a model stored in an attribute.
The new fingerprint for `_map_single` is not the same at each run. The hasher generate a different hash for the class method.
This comes from `... | [
0.06155886873602867,
-0.03430083394050598,
0.12326939404010773,
0.3316841125488281,
0.18914702534675598,
0.0026601552963256836,
0.5595555901527405,
0.2945951521396637,
0.2339777648448944,
-0.16494832932949066,
-0.1346816122531891,
0.5997434258460999,
-0.010526998899877071,
-0.4439959526062... |
https://github.com/huggingface/datasets/issues/5109 | Map caching not working for some class methods | Indeed, the hash is changing. The `dumps` function serialize the model object in different ways because the model object is not deterministic
```python
from datasets.utils.py_utils import dumps
obj1 = AutoModel.from_config(config=config, add_pooling_layer=False)
obj2 = AutoModel.from_config(config=config, add_pooli... | ## Describe the bug
The cache loading is not working as expected for some class methods with a model stored in an attribute.
The new fingerprint for `_map_single` is not the same at each run. The hasher generate a different hash for the class method.
This comes from `dumps` function in `datasets.utils.py_utils` whic... | 89 | Map caching not working for some class methods
## Describe the bug
The cache loading is not working as expected for some class methods with a model stored in an attribute.
The new fingerprint for `_map_single` is not the same at each run. The hasher generate a different hash for the class method.
This comes from `... | [
0.06064460799098015,
-0.0009960159659385681,
0.13304996490478516,
0.32389020919799805,
0.2014191597700119,
-0.009757772088050842,
0.6343293786048889,
0.294051855802536,
0.20974721014499664,
-0.16269390285015106,
-0.15033173561096191,
0.6095576882362366,
-0.004029073752462864,
-0.4160954952... |
https://github.com/huggingface/datasets/issues/5105 | Specifying an exisiting folder in download_and_prepare deletes everything in it | Thanks for reporting, @cakiki.
I would say the deletion of the dir is an expected behavior though... | ## Describe the bug
The builder correctly creates the `output_dir` folder if it doesn't exist, but if the folder exists everything within it is deleted. Specifying `"."` as the `output_dir` deletes everything in your current dir but also leads to **another bug** whose traceback is the following:
```
... | 17 | Specifying an exisiting folder in download_and_prepare deletes everything in it
## Describe the bug
The builder correctly creates the `output_dir` folder if it doesn't exist, but if the folder exists everything within it is deleted. Specifying `"."` as the `output_dir` deletes everything in your current dir but also... | [
-0.27821946144104004,
0.437811017036438,
-0.09798125922679901,
0.33214181661605835,
0.39338529109954834,
-0.18040987849235535,
-0.07301931083202362,
0.35373541712760925,
-0.07171329110860825,
0.32459384202957153,
-0.22473783791065216,
0.25985389947891235,
-0.1422298401594162,
-0.0067804232... |
https://github.com/huggingface/datasets/issues/5105 | Specifying an exisiting folder in download_and_prepare deletes everything in it | Thank you both for your feedback!
@albertvillanova I think I might have have the wrong mental model of what the function was meant to do. I thought it would be an API similar to the pandas `to_XX` write methods (Like the one @lhoestq mentions) so I just assumed it would download the dataframe to whichever folder I s... | ## Describe the bug
The builder correctly creates the `output_dir` folder if it doesn't exist, but if the folder exists everything within it is deleted. Specifying `"."` as the `output_dir` deletes everything in your current dir but also leads to **another bug** whose traceback is the following:
```
... | 103 | Specifying an exisiting folder in download_and_prepare deletes everything in it
## Describe the bug
The builder correctly creates the `output_dir` folder if it doesn't exist, but if the folder exists everything within it is deleted. Specifying `"."` as the `output_dir` deletes everything in your current dir but also... | [
-0.27821946144104004,
0.437811017036438,
-0.09798125922679901,
0.33214181661605835,
0.39338529109954834,
-0.18040987849235535,
-0.07301931083202362,
0.35373541712760925,
-0.07171329110860825,
0.32459384202957153,
-0.22473783791065216,
0.25985389947891235,
-0.1422298401594162,
-0.0067804232... |
https://github.com/huggingface/datasets/issues/5105 | Specifying an exisiting folder in download_and_prepare deletes everything in it | actually there's already a `download_mode` parameter that defaults to `REUSE_DATASET_IF_EXISTS` - so I guess it's just a matter of not deleting files unrelated to the dataset, and to overwrite existing dataset files if the download mode is `REUSE_CACHE_IF_EXISTS` or `FORCE_REDOWNLOAD` | ## Describe the bug
The builder correctly creates the `output_dir` folder if it doesn't exist, but if the folder exists everything within it is deleted. Specifying `"."` as the `output_dir` deletes everything in your current dir but also leads to **another bug** whose traceback is the following:
```
... | 40 | Specifying an exisiting folder in download_and_prepare deletes everything in it
## Describe the bug
The builder correctly creates the `output_dir` folder if it doesn't exist, but if the folder exists everything within it is deleted. Specifying `"."` as the `output_dir` deletes everything in your current dir but also... | [
-0.27821946144104004,
0.437811017036438,
-0.09798125922679901,
0.33214181661605835,
0.39338529109954834,
-0.18040987849235535,
-0.07301931083202362,
0.35373541712760925,
-0.07171329110860825,
0.32459384202957153,
-0.22473783791065216,
0.25985389947891235,
-0.1422298401594162,
-0.0067804232... |
https://github.com/huggingface/datasets/issues/5099 | datasets doesn't support # in data paths | `datasets` doesn't seem to urlencode the directory names here
https://github.com/huggingface/datasets/blob/7feeb5648a63b6135a8259dedc3b1e19185ee4c7/src/datasets/utils/file_utils.py#L109-L111
for example we should have
```python
from datasets.utils.file_utils import hf_hub_url
url = hf_hub_url("loubnabnl/bigc... | ## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same data is loaded properly
```python
ds = lo... | 38 | datasets doesn't support # in data paths
## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same ... | [
-0.2091766744852066,
0.1359013319015503,
-0.08399754762649536,
0.41576313972473145,
0.3824024796485901,
0.01960335671901703,
-0.0763368308544159,
0.4112899601459503,
-0.030178207904100418,
0.22143150866031647,
0.02437463216483593,
0.4805358350276947,
-0.39222806692123413,
0.288324058055877... |
https://github.com/huggingface/datasets/issues/5099 | datasets doesn't support # in data paths | @loubnabnl The dataset you linked in the description of the bug does not work and returns a 404. Where can I find the dataset to reproduce the bug? | ## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same data is loaded properly
```python
ds = lo... | 28 | datasets doesn't support # in data paths
## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same ... | [
-0.18062348663806915,
0.19160407781600952,
-0.08600079268217087,
0.47223734855651855,
0.23272131383419037,
0.13766813278198242,
0.023798078298568726,
0.35274720191955566,
-0.06538982689380646,
0.15885448455810547,
0.2941090762615204,
0.5142216682434082,
-0.4371044933795929,
0.2932413220405... |
https://github.com/huggingface/datasets/issues/5099 | datasets doesn't support # in data paths | I think you can create a dataset repository on the Hub with a dummy file containing a `#` | ## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same data is loaded properly
```python
ds = lo... | 18 | datasets doesn't support # in data paths
## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same ... | [
-0.30818721652030945,
0.1164131760597229,
-0.09123972058296204,
0.3513009548187256,
0.3450326919555664,
0.09891653805971146,
0.0209820456802845,
0.4554470181465149,
-0.03980519622564316,
0.22690436244010925,
0.11732082813978195,
0.6159343123435974,
-0.3614945709705353,
0.3803955614566803,
... |
https://github.com/huggingface/datasets/issues/5099 | datasets doesn't support # in data paths | Ah sorry it was private I just made it public, I can also help with this if needed | ## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same data is loaded properly
```python
ds = lo... | 18 | datasets doesn't support # in data paths
## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same ... | [
-0.26596444845199585,
0.15241342782974243,
-0.11883433163166046,
0.4522739052772522,
0.3733292818069458,
0.047265924513339996,
-0.03504321351647377,
0.40546268224716187,
-0.02588869072496891,
0.15918132662773132,
0.1695338487625122,
0.5867083668708801,
-0.4151313006877899,
0.38535535335540... |
https://github.com/huggingface/datasets/issues/5099 | datasets doesn't support # in data paths | @lhoestq Should I url encode also repo_id and revision parameters? I'm not sure what are the valid characters there.
Personally, I would be cautious and only url encode the path parameter. | ## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same data is loaded properly
```python
ds = lo... | 31 | datasets doesn't support # in data paths
## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same ... | [
-0.23935462534427643,
0.3422907590866089,
-0.09241901338100433,
0.4141099452972412,
0.31247687339782715,
-0.07263568788766861,
-0.06012551113963127,
0.348783940076828,
-0.17380933463573456,
0.1275741010904312,
0.21336416900157928,
0.4802649915218353,
-0.3821050822734833,
0.2710797190666199... |
https://github.com/huggingface/datasets/issues/5099 | datasets doesn't support # in data paths | These are possible solutions (assuming `from urllib.parse import quote`):
1) url encode only the path parameter:
```
# src/datasets/utils/file_utils.py
def hf_hub_url(repo_id: str, path: str, revision: Optional[str] = None) -> str:
revision = revision or config.HUB_DEFAULT_VERSION
return config.HUB_DATA... | ## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same data is loaded properly
```python
ds = lo... | 113 | datasets doesn't support # in data paths
## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same ... | [
-0.26046356558799744,
0.17757588624954224,
-0.06597240269184113,
0.3687845468521118,
0.37515151500701904,
0.022101908922195435,
-0.02405305579304695,
0.4590635895729065,
-0.059669721871614456,
0.19818353652954102,
0.056489259004592896,
0.6017807126045227,
-0.3670687675476074,
0.35972735285... |
https://github.com/huggingface/datasets/issues/5099 | datasets doesn't support # in data paths | repo_id can only contain alphanumeric characters and _- so it doesn't need to be encoded.
However I agree it's a good idea to also apply `quote` to the revision as well as in 2. ! | ## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same data is loaded properly
```python
ds = lo... | 35 | datasets doesn't support # in data paths
## Describe the bug
dataset files with `#` symbol their paths aren't read correctly.
## Steps to reproduce the bug
The data in folder `c#`of this [dataset](https://huggingface.co/datasets/loubnabnl/bigcode_csharp) can't be loaded. While the folder `c_sharp` with the same ... | [
-0.2246050238609314,
0.3217463791370392,
-0.11245283484458923,
0.36193132400512695,
0.3766547441482544,
0.013073362410068512,
-0.05143040791153908,
0.4347369968891144,
-0.1642584353685379,
0.16487079858779907,
0.17711134254932404,
0.5607144236564636,
-0.3094666302204132,
0.3385910093784332... |
https://github.com/huggingface/datasets/issues/5098 | Classes label error when loading symbolic links using imagefolder | Hi, thanks for reporting and suggesting a fix! We still need to account for `.`/`..` in the file path, so a more robust fix would be `Path(os.path.abspath(filepath))`. | **Is your feature request related to a problem? Please describe.**
Like this: #4015
When there are **symbolic links** to pictures in the data folder, the parent folder name of the **real file** will be used as the class name instead of the parent folder of the symbolic link itself. Can you give an option to decide wh... | 27 | Classes label error when loading symbolic links using imagefolder
**Is your feature request related to a problem? Please describe.**
Like this: #4015
When there are **symbolic links** to pictures in the data folder, the parent folder name of the **real file** will be used as the class name instead of the parent fol... | [
-0.26920077204704285,
0.041932687163352966,
0.03758114203810692,
0.7047107219696045,
0.2662848234176636,
0.05047309398651123,
0.4039705991744995,
0.023749690502882004,
0.361828088760376,
0.07373768091201782,
-0.06793902069330215,
0.3443042039871216,
-0.4016428291797638,
-0.3618543744087219... |
https://github.com/huggingface/datasets/issues/5098 | Classes label error when loading symbolic links using imagefolder | > Hi, thanks for reporting and suggesting a fix! We still need to account for `.`/`..` in the file path, so a more robust fix would be `Path(os.path.abspath(filepath))`.
Thanks for your reply! | **Is your feature request related to a problem? Please describe.**
Like this: #4015
When there are **symbolic links** to pictures in the data folder, the parent folder name of the **real file** will be used as the class name instead of the parent folder of the symbolic link itself. Can you give an option to decide wh... | 32 | Classes label error when loading symbolic links using imagefolder
**Is your feature request related to a problem? Please describe.**
Like this: #4015
When there are **symbolic links** to pictures in the data folder, the parent folder name of the **real file** will be used as the class name instead of the parent fol... | [
-0.2615421414375305,
0.03905549645423889,
0.040898192673921585,
0.7104774713516235,
0.2595892548561096,
0.04581959545612335,
0.41204994916915894,
0.01836313307285309,
0.3706163167953491,
0.07174430042505264,
-0.06196678429841995,
0.34097522497177124,
-0.40204137563705444,
-0.35772421956062... |
https://github.com/huggingface/datasets/issues/5097 | Fatal error with pyarrow/libarrow.so | Thanks for reporting, @catalys1.
This seems a duplicate of:
- #3310
The source of the problem is in PyArrow:
- [ARROW-15141: [C++] Fatal error condition occurred in aws_thread_launch](https://issues.apache.org/jira/browse/ARROW-15141)
- [ARROW-17501: [C++] Fatal error condition occurred in aws_thread_launch](... | ## Describe the bug
When using datasets, at the very end of my jobs the program crashes (see trace below).
It doesn't seem to affect anything, as it appears to happen as the program is closing down. Just importing `datasets` is enough to cause the error.
## Steps to reproduce the bug
This is sufficient to reprodu... | 91 | Fatal error with pyarrow/libarrow.so
## Describe the bug
When using datasets, at the very end of my jobs the program crashes (see trace below).
It doesn't seem to affect anything, as it appears to happen as the program is closing down. Just importing `datasets` is enough to cause the error.
## Steps to reproduce... | [
-0.6741321086883545,
0.38841432332992554,
0.05871608480811119,
0.14144933223724365,
0.30659735202789307,
-0.064825139939785,
0.24130423367023468,
0.09869427978992462,
-0.22348621487617493,
0.11210634559392929,
0.09991702437400818,
0.6103004813194275,
-0.010139367543160915,
0.09585616737604... |
https://github.com/huggingface/datasets/issues/5096 | Transfer some canonical datasets under an organization namespace | The transfer of the dummy dataset to the dummy org works as expected:
```python
In [1]: from datasets import load_dataset; ds = load_dataset("dummy_canonical_dataset", download_mode="force_redownload"); ds
Downloading builder script: 100%|██████████████████████████████████████████████████████████████████████████████... | As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organization namespace, we are deprecating the canonical one (and eventua... | 140 | Transfer some canonical datasets under an organization namespace
As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organi... | [
0.03601277992129326,
0.3146805763244629,
-0.013221616856753826,
0.025197602808475494,
0.16879820823669434,
0.022613786160945892,
0.24629512429237366,
0.39038974046707153,
0.057000499218702316,
0.025375306606292725,
-0.312804639339447,
-0.06983106583356857,
-0.2716740369796753,
0.0333682373... |
https://github.com/huggingface/datasets/issues/5096 | Transfer some canonical datasets under an organization namespace | Maybe we should be a bit more proactive with these transfers. There are only ≈70 canonical models, so reaching that number with datasets would be great, too. It's not easy considering the current number of ≈750 canonical datasets, but doable.
For instance, it shouldn't be too hard to transfer these datasets (partial... | As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organization namespace, we are deprecating the canonical one (and eventua... | 470 | Transfer some canonical datasets under an organization namespace
As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organi... | [
0.03601277992129326,
0.3146805763244629,
-0.013221616856753826,
0.025197602808475494,
0.16879820823669434,
0.022613786160945892,
0.24629512429237366,
0.39038974046707153,
0.057000499218702316,
0.025375306606292725,
-0.312804639339447,
-0.06983106583356857,
-0.2716740369796753,
0.0333682373... |
https://github.com/huggingface/datasets/issues/5096 | Transfer some canonical datasets under an organization namespace | Next week I can take care of some of them :) In most cases we just need to send an email to ask them if they're ok with it.
Let's coordinate on slack ? | As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organization namespace, we are deprecating the canonical one (and eventua... | 34 | Transfer some canonical datasets under an organization namespace
As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organi... | [
0.03601277992129326,
0.3146805763244629,
-0.013221616856753826,
0.025197602808475494,
0.16879820823669434,
0.022613786160945892,
0.24629512429237366,
0.39038974046707153,
0.057000499218702316,
0.025375306606292725,
-0.312804639339447,
-0.06983106583356857,
-0.2716740369796753,
0.0333682373... |
https://github.com/huggingface/datasets/issues/5096 | Transfer some canonical datasets under an organization namespace | I can also continuing working on this if we agree this has become a priority now. | As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organization namespace, we are deprecating the canonical one (and eventua... | 16 | Transfer some canonical datasets under an organization namespace
As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organi... | [
0.03601277992129326,
0.3146805763244629,
-0.013221616856753826,
0.025197602808475494,
0.16879820823669434,
0.022613786160945892,
0.24629512429237366,
0.39038974046707153,
0.057000499218702316,
0.025375306606292725,
-0.312804639339447,
-0.06983106583356857,
-0.2716740369796753,
0.0333682373... |
https://github.com/huggingface/datasets/issues/5096 | Transfer some canonical datasets under an organization namespace | cool stuff!
this morning on my side i moved huggingface.co/ctrl (a not very used model) to its rightful entity | As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organization namespace, we are deprecating the canonical one (and eventua... | 19 | Transfer some canonical datasets under an organization namespace
As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organi... | [
0.03601277992129326,
0.3146805763244629,
-0.013221616856753826,
0.025197602808475494,
0.16879820823669434,
0.022613786160945892,
0.24629512429237366,
0.39038974046707153,
0.057000499218702316,
0.025375306606292725,
-0.312804639339447,
-0.06983106583356857,
-0.2716740369796753,
0.0333682373... |
https://github.com/huggingface/datasets/issues/5096 | Transfer some canonical datasets under an organization namespace | As a previous step before transferring the datasets, we decided we should convert them to Parquet, so that the viewer does not stop working (the viewer does not support datasets with scripts).
Datasets converted to Parquet:
- [x] adversarial_qa
- [x] ai2_arc
- [x] americas_nli
- [x] anli
- [x] asset
- [x] bea... | As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organization namespace, we are deprecating the canonical one (and eventua... | 361 | Transfer some canonical datasets under an organization namespace
As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organi... | [
0.03601277992129326,
0.3146805763244629,
-0.013221616856753826,
0.025197602808475494,
0.16879820823669434,
0.022613786160945892,
0.24629512429237366,
0.39038974046707153,
0.057000499218702316,
0.025375306606292725,
-0.312804639339447,
-0.06983106583356857,
-0.2716740369796753,
0.0333682373... |
https://github.com/huggingface/datasets/issues/5096 | Transfer some canonical datasets under an organization namespace | For `c4` and `mc4` I was thinking of adding the corresponding configs to `allenai/c4` and redirect `c4` and `mc4` to `allenai/c4`. I'll open a PR on `allenai/c4` if it's good for you | As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organization namespace, we are deprecating the canonical one (and eventua... | 32 | Transfer some canonical datasets under an organization namespace
As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organi... | [
0.03601277992129326,
0.3146805763244629,
-0.013221616856753826,
0.025197602808475494,
0.16879820823669434,
0.022613786160945892,
0.24629512429237366,
0.39038974046707153,
0.057000499218702316,
0.025375306606292725,
-0.312804639339447,
-0.06983106583356857,
-0.2716740369796753,
0.0333682373... |
https://github.com/huggingface/datasets/issues/5096 | Transfer some canonical datasets under an organization namespace | @davanstrien and @lhoestq, I have shared with you this spreadsheet: https://docs.google.com/spreadsheets/d/1GvNTd1UxmtTvEFOK-Eq6E3Str4FUWQuWZsEN0WVFirs/edit?usp=sharing
This way we can take datasets by batches to contact the authors and transfer to the organizations. | As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organization namespace, we are deprecating the canonical one (and eventua... | 28 | Transfer some canonical datasets under an organization namespace
As discussed during our @huggingface/datasets meeting, we are planning to move some "canonical" dataset scripts under their corresponding organization namespace (if this does not exist).
On the contrary, if the dataset already exists under the organi... | [
0.03601277992129326,
0.3146805763244629,
-0.013221616856753826,
0.025197602808475494,
0.16879820823669434,
0.022613786160945892,
0.24629512429237366,
0.39038974046707153,
0.057000499218702316,
0.025375306606292725,
-0.312804639339447,
-0.06983106583356857,
-0.2716740369796753,
0.0333682373... |
https://github.com/huggingface/datasets/issues/5094 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock | Hi ! Could it be an Out of Memory issue that could have killed one of the processes ? can you check your memory ? | ## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `datasets.Dataset.map` spawns [a this step](https://github.com/huggingface/datase... | 25 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock
## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `dataset... | [
-0.19728319346904755,
-0.5258713364601135,
-0.059857141226530075,
0.19121290743350983,
-0.03308035433292389,
-0.03727487847208977,
0.3879684805870056,
0.10255962610244751,
0.19705474376678467,
0.15648043155670166,
0.1593065857887268,
0.5224060416221619,
-0.1971760094165802,
-0.348668515682... |
https://github.com/huggingface/datasets/issues/5094 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock | Hi! I don't think it is a memory issue. I'm monitoring the main and spawn python processes and threads with `htop` and the memory does not peak. Besides, the example I've posted above should not be that demanding in terms of memory, right? (I have 32GB of RAM). | ## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `datasets.Dataset.map` spawns [a this step](https://github.com/huggingface/datase... | 48 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock
## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `dataset... | [
-0.19728319346904755,
-0.5258713364601135,
-0.059857141226530075,
0.19121290743350983,
-0.03308035433292389,
-0.03727487847208977,
0.3879684805870056,
0.10255962610244751,
0.19705474376678467,
0.15648043155670166,
0.1593065857887268,
0.5224060416221619,
-0.1971760094165802,
-0.348668515682... |
https://github.com/huggingface/datasets/issues/5094 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock | Indeed it should be fine. I couldn't reproduce the error though - I ran your script on my side and it works fine. What version of pytorch are you using ? | ## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `datasets.Dataset.map` spawns [a this step](https://github.com/huggingface/datase... | 31 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock
## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `dataset... | [
-0.19728319346904755,
-0.5258713364601135,
-0.059857141226530075,
0.19121290743350983,
-0.03308035433292389,
-0.03727487847208977,
0.3879684805870056,
0.10255962610244751,
0.19705474376678467,
0.15648043155670166,
0.1593065857887268,
0.5224060416221619,
-0.1971760094165802,
-0.348668515682... |
https://github.com/huggingface/datasets/issues/5094 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock | I also tried on colab and it works fine 🤔
Maybe something is wrong with your installation of pytorch ? | ## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `datasets.Dataset.map` spawns [a this step](https://github.com/huggingface/datase... | 20 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock
## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `dataset... | [
-0.19728319346904755,
-0.5258713364601135,
-0.059857141226530075,
0.19121290743350983,
-0.03308035433292389,
-0.03727487847208977,
0.3879684805870056,
0.10255962610244751,
0.19705474376678467,
0.15648043155670166,
0.1593065857887268,
0.5224060416221619,
-0.1971760094165802,
-0.348668515682... |
https://github.com/huggingface/datasets/issues/5094 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock | Oh actually I just saw that you're using python 3.9
This could be related to https://github.com/huggingface/datasets/issues/4113
We'll fix that as soon as we can, in the meantime you can try to use use single process, or use an older version of python maybe ? | ## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `datasets.Dataset.map` spawns [a this step](https://github.com/huggingface/datase... | 44 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock
## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `dataset... | [
-0.19728319346904755,
-0.5258713364601135,
-0.059857141226530075,
0.19121290743350983,
-0.03308035433292389,
-0.03727487847208977,
0.3879684805870056,
0.10255962610244751,
0.19705474376678467,
0.15648043155670166,
0.1593065857887268,
0.5224060416221619,
-0.1971760094165802,
-0.348668515682... |
https://github.com/huggingface/datasets/issues/5094 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock | I tried with python 3.7 and the issue persists. In collab, which also uses 3.7 I don't get the issue, so yes I guess is something on mu side... will post it here if I manage to fix it | ## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `datasets.Dataset.map` spawns [a this step](https://github.com/huggingface/datase... | 39 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock
## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `dataset... | [
-0.19728319346904755,
-0.5258713364601135,
-0.059857141226530075,
0.19121290743350983,
-0.03308035433292389,
-0.03727487847208977,
0.3879684805870056,
0.10255962610244751,
0.19705474376678467,
0.15648043155670166,
0.1593065857887268,
0.5224060416221619,
-0.1971760094165802,
-0.348668515682... |
https://github.com/huggingface/datasets/issues/5094 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock | Hi! Which version of transformers are you using? I test the code on Colab (so python 3.7) with transformers 4.23.1, torch 1.12.1 and pyarrow 9.0.0 (also 6.x), it worked without stuck. | ## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `datasets.Dataset.map` spawns [a this step](https://github.com/huggingface/datase... | 31 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock
## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `dataset... | [
-0.19728319346904755,
-0.5258713364601135,
-0.059857141226530075,
0.19121290743350983,
-0.03308035433292389,
-0.03727487847208977,
0.3879684805870056,
0.10255962610244751,
0.19705474376678467,
0.15648043155670166,
0.1593065857887268,
0.5224060416221619,
-0.1971760094165802,
-0.348668515682... |
https://github.com/huggingface/datasets/issues/5094 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock | Hi, I have the same problem in use **datasets.IterableDatasetDict.map()**
my pytorch is 2.0.0a0+gitc263bd4
my python is 3.8.16(default, Jun 12 2023, 17:37:21)
work on aarch64 in 16 node, each node with 4*nVidia-A100-40G
every node have 4 process execute code as ↓
```
from datasets import load_dataset, interleav... | ## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `datasets.Dataset.map` spawns [a this step](https://github.com/huggingface/datase... | 447 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock
## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `dataset... | [
-0.19728319346904755,
-0.5258713364601135,
-0.059857141226530075,
0.19121290743350983,
-0.03308035433292389,
-0.03727487847208977,
0.3879684805870056,
0.10255962610244751,
0.19705474376678467,
0.15648043155670166,
0.1593065857887268,
0.5224060416221619,
-0.1971760094165802,
-0.348668515682... |
https://github.com/huggingface/datasets/issues/5094 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock | @bio-punk `IterableDatasetDict.map` does not support multiprocessing (only `DatasetDict.map` and `Dataset.map` do), so please open a new issue as this doesn't seem to be related to the original issue. | ## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `datasets.Dataset.map` spawns [a this step](https://github.com/huggingface/datase... | 28 | Multiprocessing with `Dataset.map` and `PyTorch` results in deadlock
## Describe the bug
There seems to be an issue with using multiprocessing with `datasets.Dataset.map` (i.e. setting `num_proc` to a value greater than one) combined with a function that uses `torch` under the hood. The subprocesses that `dataset... | [
-0.19728319346904755,
-0.5258713364601135,
-0.059857141226530075,
0.19121290743350983,
-0.03308035433292389,
-0.03727487847208977,
0.3879684805870056,
0.10255962610244751,
0.19705474376678467,
0.15648043155670166,
0.1593065857887268,
0.5224060416221619,
-0.1971760094165802,
-0.348668515682... |
https://github.com/huggingface/datasets/issues/5093 | Mismatch between tutoriel and doc | Hi, thanks for reporting! This line should be replaced with
```python
dataset = dataset.map(lambda examples: tokenizer(examples["text"], return_tensors="np"), batched=True)
```
for it to work (the `return_tensors` part inside the `tokenizer` call). | ## Describe the bug
In the "Process text data" tutorial, [`map` has `return_tensors` as kwarg](https://huggingface.co/docs/datasets/main/en/nlp_process#map). It does not seem to appear in the [function documentation](https://huggingface.co/docs/datasets/main/en/package_reference/main_classes#datasets.Dataset.map), nor... | 30 | Mismatch between tutoriel and doc
## Describe the bug
In the "Process text data" tutorial, [`map` has `return_tensors` as kwarg](https://huggingface.co/docs/datasets/main/en/nlp_process#map). It does not seem to appear in the [function documentation](https://huggingface.co/docs/datasets/main/en/package_reference/mai... | [
0.10698115825653076,
-0.3805322051048279,
0.052491601556539536,
0.1246366798877716,
0.06381569802761078,
-0.14597555994987488,
0.31472423672676086,
0.05504531040787697,
0.07469674944877625,
0.090373694896698,
0.13363100588321686,
0.794468879699707,
-0.037477411329746246,
-0.062331937253475... |
https://github.com/huggingface/datasets/issues/5088 | load_datasets("json", ...) don't read local .json.gz properly | Hi @junwang-wish, thanks for reporting.
Unfortunately, I'm not able to reproduce the bug. Which version of `datasets` are you using? Does the problem persist if you update `datasets`?
```shell
pip install -U datasets
``` | ## Describe the bug
I have a local file `*.json.gz` and it can be read by `pandas.read_json(lines=True)`, but cannot be read by `load_datasets("json")` (resulting in 0 lines)
## Steps to reproduce the bug
```python
fpath = '/data/junwang/.cache/general/57b6f2314cbe0bc45dda5b78f0871df2/test.json.gz'
ds_panda = Da... | 34 | load_datasets("json", ...) don't read local .json.gz properly
## Describe the bug
I have a local file `*.json.gz` and it can be read by `pandas.read_json(lines=True)`, but cannot be read by `load_datasets("json")` (resulting in 0 lines)
## Steps to reproduce the bug
```python
fpath = '/data/junwang/.cache/gener... | [
-0.003829054534435272,
-0.047457046806812286,
-0.05098037049174309,
0.4958299398422241,
0.2805570960044861,
0.06093590706586838,
0.3618413209915161,
0.34863904118537903,
0.5576652884483337,
0.03365106135606766,
-0.1139461100101471,
0.4106937646865845,
0.14960357546806335,
-0.03850224986672... |
https://github.com/huggingface/datasets/issues/5088 | load_datasets("json", ...) don't read local .json.gz properly | Thanks @albertvillanova I updated `datasets` from `2.5.1` to `2.5.2` and tested copying the `json.gz` to a different directory and my mind was blown:
```python
fpath = '/data/junwang/.cache/general/57b6f2314cbe0bc45dda5b78f0871df2/test.json.gz'
ds_panda = DatasetDict(
test=Dataset.from_pandas(
pd.rea... | ## Describe the bug
I have a local file `*.json.gz` and it can be read by `pandas.read_json(lines=True)`, but cannot be read by `load_datasets("json")` (resulting in 0 lines)
## Steps to reproduce the bug
```python
fpath = '/data/junwang/.cache/general/57b6f2314cbe0bc45dda5b78f0871df2/test.json.gz'
ds_panda = Da... | 189 | load_datasets("json", ...) don't read local .json.gz properly
## Describe the bug
I have a local file `*.json.gz` and it can be read by `pandas.read_json(lines=True)`, but cannot be read by `load_datasets("json")` (resulting in 0 lines)
## Steps to reproduce the bug
```python
fpath = '/data/junwang/.cache/gener... | [
-0.003829054534435272,
-0.047457046806812286,
-0.05098037049174309,
0.4958299398422241,
0.2805570960044861,
0.06093590706586838,
0.3618413209915161,
0.34863904118537903,
0.5576652884483337,
0.03365106135606766,
-0.1139461100101471,
0.4106937646865845,
0.14960357546806335,
-0.03850224986672... |
https://github.com/huggingface/datasets/issues/5086 | HTTPError: 404 Client Error: Not Found for url | Hi @km5ar, thanks for reporting.
This should be fixed in the notebook:
- the filename `datasets-issues-with-hf-doc-builder.jsonl` no longer exists on the repo; instead, current filename is `datasets-issues-with-comments.jsonl`
- see: https://huggingface.co/datasets/lewtun/github-issues/tree/main
Anyway, dependi... | ## Describe the bug
I was following chap 5 from huggingface course: https://huggingface.co/course/chapter5/6?fw=tf
However, I'm not able to download the datasets, with a 404 erros
<img width="1160" alt="iShot2022-10-06_15 54 50" src="https://user-images.githubusercontent.com/54015474/194406327-ae62c2f3-1da5-... | 178 | HTTPError: 404 Client Error: Not Found for url
## Describe the bug
I was following chap 5 from huggingface course: https://huggingface.co/course/chapter5/6?fw=tf
However, I'm not able to download the datasets, with a 404 erros
<img width="1160" alt="iShot2022-10-06_15 54 50" src="https://user-images.github... | [
0.041061293333768845,
-0.10149156302213669,
0.0027762483805418015,
0.39377039670944214,
0.128495991230011,
0.21601170301437378,
0.03236088156700134,
0.2607898414134979,
0.05805240944027901,
0.1501384973526001,
-0.27367040514945984,
0.06521695852279663,
-0.042441993951797485,
-0.14198367297... |
https://github.com/huggingface/datasets/issues/5086 | HTTPError: 404 Client Error: Not Found for url | Thanks for reporting @km5ar and thank you @albertvillanova for the quick solution! I'll post a fix on the source too | ## Describe the bug
I was following chap 5 from huggingface course: https://huggingface.co/course/chapter5/6?fw=tf
However, I'm not able to download the datasets, with a 404 erros
<img width="1160" alt="iShot2022-10-06_15 54 50" src="https://user-images.githubusercontent.com/54015474/194406327-ae62c2f3-1da5-... | 20 | HTTPError: 404 Client Error: Not Found for url
## Describe the bug
I was following chap 5 from huggingface course: https://huggingface.co/course/chapter5/6?fw=tf
However, I'm not able to download the datasets, with a 404 erros
<img width="1160" alt="iShot2022-10-06_15 54 50" src="https://user-images.github... | [
0.04595087841153145,
-0.22973991930484772,
-0.0069292448461055756,
0.45495253801345825,
0.1510334014892578,
0.24672609567642212,
0.008114073425531387,
0.22636844217777252,
0.12358404695987701,
0.18057358264923096,
-0.30378127098083496,
0.021852413192391396,
-0.061907075345516205,
-0.082032... |
https://github.com/huggingface/datasets/issues/5085 | Filtering on an empty dataset returns a corrupted dataset. | ~~It seems like #5043 fix (merged recently) is the root cause of such behaviour. When we empty indices mapping (because the dataset length equals to zero), we can no longer get column item like: `ds_filter_2['sentence']` which uses
`ds_filter_1._indices.column(0)`~~
**UPDATE:**
Empty datasets are returned without ... | ## Describe the bug
When filtering a dataset twice, where the first result is an empty dataset, the second dataset seems corrupted.
## Steps to reproduce the bug
```python
datasets = load_dataset("glue", "sst2")
dataset_split = datasets['validation']
ds_filter_1 = dataset_split.filter(lambda x: False) # ... | 103 | Filtering on an empty dataset returns a corrupted dataset.
## Describe the bug
When filtering a dataset twice, where the first result is an empty dataset, the second dataset seems corrupted.
## Steps to reproduce the bug
```python
datasets = load_dataset("glue", "sst2")
dataset_split = datasets['validation... | [
-0.10343395173549652,
-0.03265092521905899,
-0.040131181478500366,
0.22334840893745422,
0.05369693040847778,
0.0005477741360664368,
0.40057241916656494,
0.42343005537986755,
0.11768132448196411,
0.006940789520740509,
-0.11518204212188721,
0.22237542271614075,
0.0821421816945076,
0.07910182... |
https://github.com/huggingface/datasets/issues/5083 | Support numpy/torch/tf/jax formatting for IterableDataset | hii @lhoestq, can you assign this issue to me? Though i am new to open source still I would love to put my best foot forward. I can see there isn't anyone right now assigned to this issue. | Right now `IterableDataset` doesn't do any formatting.
In particular this code should return a numpy array:
```python
from datasets import load_dataset
ds = load_dataset("imagenet-1k", split="train", streaming=True).with_format("np")
print(next(iter(ds))["image"])
```
Right now it returns a PIL.Image.
S... | 38 | Support numpy/torch/tf/jax formatting for IterableDataset
Right now `IterableDataset` doesn't do any formatting.
In particular this code should return a numpy array:
```python
from datasets import load_dataset
ds = load_dataset("imagenet-1k", split="train", streaming=True).with_format("np")
print(next(iter(d... | [
-0.16015176475048065,
-0.29652366042137146,
-0.02708999440073967,
-0.04405905306339264,
0.29049986600875854,
-0.014095332473516464,
0.5831495523452759,
0.46640753746032715,
-0.24507053196430206,
-0.0968402773141861,
-0.08783755451440811,
0.4100490212440491,
-0.12891240417957306,
0.08979699... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.