html_url stringlengths 51 51 | comments stringlengths 67 24.7k | title stringlengths 6 280 | body stringlengths 51 36.2k | comment_length int64 16 1.45k | text stringlengths 190 38.3k | embeddings list |
|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/1856 | @lhoestq Hi! I encounter the same error when loading `yelp_review_full`.
```
from datasets import load_dataset
dataset_yp = load_dataset("yelp_review_full")
```
When you say the "Quota Exceeded from Google drive". Is this a quota from the dataset owner? or the quota from our (the runner) Google Drive? | load_dataset("amazon_polarity") NonMatchingChecksumError | Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback ... | 45 | load_dataset("amazon_polarity") NonMatchingChecksumError
Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
----------------------------------------------------------------------... | [
-0.06117354333400726,
0.14232732355594635,
-0.10863210260868073,
0.22138375043869019,
0.12633641064167023,
0.1217508614063263,
0.245276540517807,
0.01037982851266861,
0.3931342661380768,
0.10966624319553375,
-0.13955889642238617,
-0.02014491893351078,
0.03638170287013054,
0.025238007307052... |
https://github.com/huggingface/datasets/issues/1856 | > When you say the "Quota Exceeded from Google drive". Is this a quota from the dataset owner? or the quota from our (the runner) Google Drive?
Each file on Google Drive can be downloaded only a certain amount of times per day because of a quota. The quota is reset every day. So if too many people download the datas... | load_dataset("amazon_polarity") NonMatchingChecksumError | Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback ... | 127 | load_dataset("amazon_polarity") NonMatchingChecksumError
Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
----------------------------------------------------------------------... | [
-0.13494262099266052,
0.047477781772613525,
-0.11106196790933609,
0.2588097155094147,
0.062481969594955444,
-0.03678257018327713,
0.2863384485244751,
0.011993391439318657,
0.3435027003288269,
0.2581290602684021,
0.07673422247171402,
-0.03757923096418381,
0.0030820854008197784,
0.0379523113... |
https://github.com/huggingface/datasets/issues/1856 | @lhoestq Gotcha, that is quite problematic...for what it's worth, I've had no issues with the other datasets I tried, such as `yelp_reviews_full` and `amazon_reviews_multi`. | load_dataset("amazon_polarity") NonMatchingChecksumError | Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback ... | 24 | load_dataset("amazon_polarity") NonMatchingChecksumError
Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
----------------------------------------------------------------------... | [
-0.19478663802146912,
0.05544725060462952,
-0.0836697518825531,
0.15782232582569122,
0.1719485968351364,
0.08044286072254181,
0.23757320642471313,
0.09915164113044739,
0.24161997437477112,
-0.013613887131214142,
-0.08398203551769257,
0.06070072203874588,
-0.003998162224888802,
-0.141038656... |
https://github.com/huggingface/datasets/issues/1856 | Same issue today with "big_patent", though the symptoms are slightly different.
When running
```py
from datasets import load_dataset
load_dataset("big_patent", split="validation")
```
I get the following
`FileNotFoundError: Local file \huggingface\datasets\downloads\6159313604f4f2c01e7d1cac52139343b6c07f73... | load_dataset("amazon_polarity") NonMatchingChecksumError | Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback ... | 230 | load_dataset("amazon_polarity") NonMatchingChecksumError
Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
----------------------------------------------------------------------... | [
-0.1977473497390747,
0.16995781660079956,
-0.05109279230237007,
0.23982182145118713,
0.14944016933441162,
-0.05001053214073181,
0.26483970880508423,
0.22645068168640137,
0.318641722202301,
0.06029542535543442,
-0.06212681531906128,
0.007255226373672485,
-0.004848897457122803,
-0.1367183774... |
https://github.com/huggingface/datasets/issues/1856 | A similar issue arises when trying to stream the dataset
```python
>>> from datasets import load_dataset
>>> iter_dset = load_dataset("amazon_polarity", split="test", streaming=True)
>>> iter(iter_dset).__next__()
---------------------------------------------------------------------------
ValueError ... | load_dataset("amazon_polarity") NonMatchingChecksumError | Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback ... | 430 | load_dataset("amazon_polarity") NonMatchingChecksumError
Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
----------------------------------------------------------------------... | [
-0.3396334648132324,
0.020067602396011353,
-0.046227674931287766,
0.17625856399536133,
0.13730300962924957,
0.08595189452171326,
0.19963882863521576,
0.13551568984985352,
0.2324957251548767,
0.08524835854768753,
-0.04402138665318489,
0.07850921154022217,
-0.02695854753255844,
-0.0893353074... |
https://github.com/huggingface/datasets/issues/1856 | This error still happens, but for a different reason now: Google Drive returns a warning instead of the dataset. | load_dataset("amazon_polarity") NonMatchingChecksumError | Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback ... | 19 | load_dataset("amazon_polarity") NonMatchingChecksumError
Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
----------------------------------------------------------------------... | [
-0.28189346194267273,
0.1576433777809143,
-0.06837515532970428,
0.09960294514894485,
0.10807443410158157,
0.16043893992900848,
0.46409910917282104,
0.08679676055908203,
0.2902541160583496,
0.1448865830898285,
0.05735684186220169,
-0.029875747859477997,
-0.10137246549129486,
0.0111130625009... |
https://github.com/huggingface/datasets/issues/1856 | Hi ! Thanks for reporting. Google Drive changed the way to bypass the warning message recently.
The latest release `1.18.4` fixes this for datasets loaded in a regular way.
We opened a PR to fix this recently for streaming mode at #3843 - we'll do a new release once the fix is merged :) | load_dataset("amazon_polarity") NonMatchingChecksumError | Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback ... | 54 | load_dataset("amazon_polarity") NonMatchingChecksumError
Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
----------------------------------------------------------------------... | [
-0.34371891617774963,
0.09665457904338837,
-0.05536678433418274,
0.09807907044887543,
0.15954197943210602,
0.13036420941352844,
0.4060622751712799,
0.10624471306800842,
0.27967533469200134,
0.1851273477077484,
0.01667291671037674,
-0.04572874307632446,
-0.05456998944282532,
0.0795310139656... |
https://github.com/huggingface/datasets/issues/1854 | Hi @sshleifer.
I am not sure of understanding the need of the `add_item` approach...
By just reading your "Desired API" section, I would say you could (nearly) get it with a 1-column Dataset:
```python
data = {"input_ids": [np.array([4,4,2]), np.array([8,6,5,5,2]), np.array([3,3,31,5])]}
ds = Dataset.from_dict... | Feature Request: Dataset.add_item | I'm trying to integrate `huggingface/datasets` functionality into `fairseq`, which requires (afaict) being able to build a dataset through an `add_item` method, such as https://github.com/pytorch/fairseq/blob/master/fairseq/data/indexed_dataset.py#L318, as opposed to loading all the text into arrow, and then `dataset.m... | 48 | Feature Request: Dataset.add_item
I'm trying to integrate `huggingface/datasets` functionality into `fairseq`, which requires (afaict) being able to build a dataset through an `add_item` method, such as https://github.com/pytorch/fairseq/blob/master/fairseq/data/indexed_dataset.py#L318, as opposed to loading all the ... | [
-0.2646303176879883,
0.1603153645992279,
-0.045890599489212036,
0.13861563801765442,
-0.025281131267547607,
0.12017001956701279,
0.15693825483322144,
0.10714055597782135,
0.05867066979408264,
0.04408618062734604,
0.10954879224300385,
0.5823288559913635,
-0.15739110112190247,
0.138007074594... |
https://github.com/huggingface/datasets/issues/1854 | Hi @sshleifer :)
We don't have methods like `Dataset.add_batch` or `Dataset.add_entry/add_item` yet.
But that's something we'll add pretty soon. Would an API that looks roughly like this help ? Do you have suggestions ?
```python
import numpy as np
from datasets import Dataset
tokenized = [np.array([4,4,2]),... | Feature Request: Dataset.add_item | I'm trying to integrate `huggingface/datasets` functionality into `fairseq`, which requires (afaict) being able to build a dataset through an `add_item` method, such as https://github.com/pytorch/fairseq/blob/master/fairseq/data/indexed_dataset.py#L318, as opposed to loading all the text into arrow, and then `dataset.m... | 92 | Feature Request: Dataset.add_item
I'm trying to integrate `huggingface/datasets` functionality into `fairseq`, which requires (afaict) being able to build a dataset through an `add_item` method, such as https://github.com/pytorch/fairseq/blob/master/fairseq/data/indexed_dataset.py#L318, as opposed to loading all the ... | [
-0.2646303176879883,
0.1603153645992279,
-0.045890599489212036,
0.13861563801765442,
-0.025281131267547607,
0.12017001956701279,
0.15693825483322144,
0.10714055597782135,
0.05867066979408264,
0.04408618062734604,
0.10954879224300385,
0.5823288559913635,
-0.15739110112190247,
0.138007074594... |
https://github.com/huggingface/datasets/issues/1849 | @patrickvonplaten Could you please help me with how the output text has to be represented in the data? TIMIT has Words, Phonemes and texts. Also has lot on info on the speaker and the dialect. Could you please help me? An example of how to arrange it would be super helpful!
| Add TIMIT | ## Adding a Dataset
- **Name:** *TIMIT*
- **Description:** *The TIMIT corpus of read speech has been designed to provide speech data for the acquisition of acoustic-phonetic knowledge and for the development and evaluation of automatic speech recognition systems*
- **Paper:** *Homepage*: http://groups.inf.ed.ac.uk... | 51 | Add TIMIT
## Adding a Dataset
- **Name:** *TIMIT*
- **Description:** *The TIMIT corpus of read speech has been designed to provide speech data for the acquisition of acoustic-phonetic knowledge and for the development and evaluation of automatic speech recognition systems*
- **Paper:** *Homepage*: http://groups.... | [
0.07334105670452118,
-0.31102389097213745,
-0.1762830913066864,
0.18871550261974335,
0.08587662130594254,
-0.10724179446697235,
0.11768986284732819,
0.06328698992729187,
-0.42619043588638306,
-0.13589197397232056,
-0.2996532618999481,
0.13682134449481964,
-0.07004351913928986,
0.3138225078... |
https://github.com/huggingface/datasets/issues/1849 | Hey @vrindaprabhu - sure I'll help you :-) Could you open a first PR for TIMIT where you copy-paste more or less the `librispeech_asr` script: https://github.com/huggingface/datasets/blob/28be129db862ec89a87ac9349c64df6b6118aff4/datasets/librispeech_asr/librispeech_asr.py#L93 (obviously replacing all the naming and lin... | Add TIMIT | ## Adding a Dataset
- **Name:** *TIMIT*
- **Description:** *The TIMIT corpus of read speech has been designed to provide speech data for the acquisition of acoustic-phonetic knowledge and for the development and evaluation of automatic speech recognition systems*
- **Paper:** *Homepage*: http://groups.inf.ed.ac.uk... | 85 | Add TIMIT
## Adding a Dataset
- **Name:** *TIMIT*
- **Description:** *The TIMIT corpus of read speech has been designed to provide speech data for the acquisition of acoustic-phonetic knowledge and for the development and evaluation of automatic speech recognition systems*
- **Paper:** *Homepage*: http://groups.... | [
-0.2446836531162262,
-0.47310495376586914,
-0.17479516565799713,
0.05118837207555771,
0.12573319673538208,
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0.07210523635149002,
0.21556340157985687,
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0.12188804149627686,
-0.3020026683807373,
0.19129154086112976,
-0.3662654459476471,
0.164516687393... |
https://github.com/huggingface/datasets/issues/1849 | I am sorry! I created the PR [#1903](https://github.com/huggingface/datasets/pull/1903#). Requesting your comments! CircleCI tests are failing, will address them along with your comments! | Add TIMIT | ## Adding a Dataset
- **Name:** *TIMIT*
- **Description:** *The TIMIT corpus of read speech has been designed to provide speech data for the acquisition of acoustic-phonetic knowledge and for the development and evaluation of automatic speech recognition systems*
- **Paper:** *Homepage*: http://groups.inf.ed.ac.uk... | 22 | Add TIMIT
## Adding a Dataset
- **Name:** *TIMIT*
- **Description:** *The TIMIT corpus of read speech has been designed to provide speech data for the acquisition of acoustic-phonetic knowledge and for the development and evaluation of automatic speech recognition systems*
- **Paper:** *Homepage*: http://groups.... | [
-0.24184945225715637,
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0.07103137671947479,
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0.1323649287223816,
0.13229098916053772,
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0.21849307417869568,
-0.34164854884147644,
0.18533466756343842,
-0.22746425867080688,
0.2172825336... |
https://github.com/huggingface/datasets/issues/1844 | Hi ! You're right this can can useful.
This should be easy to add, so feel free to give it a try if you want to contribute :)
I think we just need to add it to the _generate_examples method of the OpenSubtitles dataset builder [here](https://github.com/huggingface/datasets/blob/master/datasets/open_subtitles/open_sub... | Update Open Subtitles corpus with original sentence IDs | Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media id, subtitle file id and sentence id), therefore somewhat a... | 46 | Update Open Subtitles corpus with original sentence IDs
Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media i... | [
0.2011132836341858,
0.16045275330543518,
-0.04834141954779625,
-0.20894046127796173,
-0.13016581535339355,
0.2428107112646103,
0.27112480998039246,
0.25712406635284424,
-0.2969913184642792,
-0.03867379575967789,
-0.31456395983695984,
0.24536383152008057,
0.21585606038570404,
-0.07630865275... |
https://github.com/huggingface/datasets/issues/1844 | Hey @lhoestq , absolutely yes! Just one question before I start implementing. The ids found in the zip file have this format:
(the following is line `22497315` of the `ids` file of the `de-en` dump)
`de/2017/7006210/7063319.xml.gz en/2017/7006210/7050201.xml.gz 335 339 340` (every space is actually a tab, ... | Update Open Subtitles corpus with original sentence IDs | Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media id, subtitle file id and sentence id), therefore somewhat a... | 217 | Update Open Subtitles corpus with original sentence IDs
Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media i... | [
0.2530395984649658,
0.2482583224773407,
-0.013386771082878113,
-0.12635403871536255,
-0.2649044096469879,
0.16548413038253784,
0.2578911781311035,
0.21786944568157196,
-0.33855217695236206,
-0.11331011354923248,
-0.31917354464530945,
0.32153889536857605,
0.1591855138540268,
-0.148518964648... |
https://github.com/huggingface/datasets/issues/1844 | I like the idea of having `year`, `imdbId` and `subtitleId` as columns for filtering for example.
And for the `sentenceIds` a list of integers is fine. | Update Open Subtitles corpus with original sentence IDs | Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media id, subtitle file id and sentence id), therefore somewhat a... | 26 | Update Open Subtitles corpus with original sentence IDs
Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media i... | [
0.20258626341819763,
0.15204814076423645,
-0.046398334205150604,
-0.21518029272556305,
-0.20975884795188904,
0.22186347842216492,
0.2927144765853882,
0.3270958662033081,
-0.280744731426239,
-0.08636625111103058,
-0.3423934280872345,
0.1748223751783371,
0.18115729093551636,
-0.1334892511367... |
https://github.com/huggingface/datasets/issues/1844 | Something like this? (adapted from [here](https://github.com/huggingface/datasets/blob/master/datasets/open_subtitles/open_subtitles.py#L114))
```python
result = (
sentence_counter,
{
"id": str(sentence_counter),
"meta": {
"year": year,
"imdbId": imdb_id,
"subtitleId... | Update Open Subtitles corpus with original sentence IDs | Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media id, subtitle file id and sentence id), therefore somewhat a... | 79 | Update Open Subtitles corpus with original sentence IDs
Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media i... | [
0.22097843885421753,
0.03477446734905243,
-0.0174860917031765,
-0.15179531276226044,
-0.20496004819869995,
0.31040942668914795,
0.3499246835708618,
0.23899126052856445,
-0.4182049632072449,
-0.1190219521522522,
-0.3992200195789337,
0.27171069383621216,
0.22531980276107788,
-0.1207069754600... |
https://github.com/huggingface/datasets/issues/1843 | That's awesome! Actually, I just noticed that this dataset might become a bit too big!
MuST-C is the main dataset used for IWSLT19 and should probably be added as a standalone dataset. Would you be interested also in adding `datasets/MuST-C` instead?
Description:
_MuST-C is a multilingual speech translation cor... | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 188 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
-0.2875131666660309,
0.17527487874031067,
-0.05233759805560112,
-0.01608116924762726,
-0.10274019092321396,
0.04134617745876312,
0.032245926558971405,
0.15731306374073029,
-0.354458212852478,
0.2396768033504486,
-0.2381986677646637,
-0.11117681115865707,
-0.19824476540088654,
0.10468833893... |
https://github.com/huggingface/datasets/issues/1843 | Hi @patrickvonplaten
I have tried downloading this dataset, but the connection seems to reset all the time. I have tried it via the browser, wget, and using gdown . But it gives me an error message. _"The server is busy or down, pls try again"_ (rephrasing the message here)
I have completed adding 4 datasets in th... | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 90 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.12572956085205078,
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-0.3189474046230316,
0.10233308374881744,
0.1398473381... |
https://github.com/huggingface/datasets/issues/1843 | @skyprince999, I think I'm getting the same error you're getting :-/
```
Sorry, you can't view or download this file at this time.
Too many users have viewed or downloaded this file recently. Please try accessing the file again later. If the file you are trying to access is particularly large or is shared with m... | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 117 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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https://github.com/huggingface/datasets/issues/1843 | Also there are huge those datasets. Think downloading MuST-C v1.2 amounts to ~ 1000GB... because there are 14 possible configs each around 60-70GB. I think users mostly will only use one of the 14 configs so that they would only need, in theory, will have to download ~60GB which is ok. But I think this functionality do... | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 64 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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https://github.com/huggingface/datasets/issues/1843 | > Also cc @lhoestq - do you think we could mirror the dataset?
Yes we can mirror it if the authors are fine with it. You can create a dataset repo on huggingface.co (possibly under the relevant org) and add the mirrored data files.
> I think users mostly will only use one of the 14 configs so that they would only... | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 110 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.254836797... |
https://github.com/huggingface/datasets/issues/1843 | I have written to the dataset authors, highlighting this issue. Waiting for their response.
Update on 25th Feb:
The authors have replied back, they are updating the download link and will revert back shortly!
```
first of all thanks a lot for being interested in MuST-C and for building the data-loader.
Be... | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 147 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.101492017... |
https://github.com/huggingface/datasets/issues/1843 | Awesome, actually @lhoestq let's just ask the authors if we should host the dataset no? They could just use our links then as well for their website - what do you think? Is it fine to use our AWS dataset storage also as external links? | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 45 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.19022242724... |
https://github.com/huggingface/datasets/issues/1843 | Yes definitely. Shall we suggest them to create a dataset repository under their org on huggingface.co ? @julien-c
The dataset is around 1TB | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 23 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.177145987... |
https://github.com/huggingface/datasets/issues/1843 | Sounds good!
Order of magnitude is storage costs ~$20 per TB per month (not including bandwidth).
Happy to provide this to the community as I feel this is an important dataset. Let us know what the authors want to do!
| MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 40 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.139333486557... |
https://github.com/huggingface/datasets/issues/1843 | Great! @skyprince999, do you think you could ping the authors here or link to this thread? I think it could be a cool idea to host the dataset on our side then | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 32 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.1762094199657... |
https://github.com/huggingface/datasets/issues/1843 | Done. They replied back, and they want to have a call over a meet/ skype. Is that possible ?
Btw @patrickvonplaten you are looped in that email (_pls check you gmail account_) | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 32 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.20483770... |
https://github.com/huggingface/datasets/issues/1843 | @gegallego there were some concerns regarding dataset usage & attribution by a for-profit company, so couldn't take it forward. Also the download links were unstable.
But I guess if you want to test the fairseq benchmarks, you can connect with them directly for downloading the dataset. | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 46 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.1664300560951233,
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0.185872882604599,
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0.05462557077407837,
-0.1191613823175... |
https://github.com/huggingface/datasets/issues/1843 | Yes, that dataset is not easy to download... I had to copy it to my Google Drive and use `rsync` to be able to download it.
However, we could add the dataset with a manual download, right? | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 37 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.0430667... |
https://github.com/huggingface/datasets/issues/1843 | yes that is possible. I couldn't unfortunately complete this PR, If you would like to add it, please feel free to do it. | MustC Speech Translation | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | 23 | MustC Speech Translation
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.... | [
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0.16874510049819946,
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0.117713861167... |
https://github.com/huggingface/datasets/issues/1842 | @mariosasko actually the "official" AMI dataset can be found here: https://huggingface.co/datasets/edinburghcstr/ami -> the old one under `datasets/ami` doesn't work and should be deleted.
The new one was tested by fine-tuning a Wav2Vec2 model on it + we uploaded all the processed audio directly into it | Add AMI Corpus | ## Adding a Dataset
- **Name:** *AMI*
- **Description:** *The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. For a gentle introduction to the corpus, see the corpus overview. To access the data, follow the directions given there. Around two-thirds of the data has been elic... | 45 | Add AMI Corpus
## Adding a Dataset
- **Name:** *AMI*
- **Description:** *The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. For a gentle introduction to the corpus, see the corpus overview. To access the data, follow the directions given there. Around two-thirds of the d... | [
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0.130823... |
https://github.com/huggingface/datasets/issues/1840 | Hey @BirgerMoell - awesome that you started working on Common Voice. Common Voice is a bit special since, there is no direct download link to download the data. In these cases we usually consider two options:
1) Find a hacky solution to extract the download link somehow from the XLM tree of the website
2) If this ... | Add common voice | ## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/dat... | 100 | Add common voice
## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www... | [
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https://github.com/huggingface/datasets/issues/1840 | I added a Work in Progress pull request (hope that is ok). I've made a card for the dataset and filled out the common_voice.py file with information about the datset (not completely).
I didn't manage to get the tagging tool working locally on my machine but will look into that later.
Left to do.
- Tag the data... | Add common voice | ## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/dat... | 66 | Add common voice
## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www... | [
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https://github.com/huggingface/datasets/issues/1840 | I saw that this current datasets package holds common voice version 6.1, how to add the new version 7.0 that is already available? | Add common voice | ## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/dat... | 23 | Add common voice
## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www... | [
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0.06251918524503... |
https://github.com/huggingface/datasets/issues/1840 | Common voice still appears to be a 6.1. Is the plan still to upgrade to 7.0? | Add common voice | ## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/dat... | 16 | Add common voice
## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www... | [
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-0.054074350... |
https://github.com/huggingface/datasets/issues/1840 | We actually already have the code and everything ready to add Common Voice 7.0 to `datasets` but are still waiting for the common voice authors to give us the green light :-)
Also gently pinging @phirework and @milupo here | Add common voice | ## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/dat... | 39 | Add common voice
## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www... | [
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-0.12001185119152069,
0.3751794695854187,
0.4150419235229492,
-0.17862603068351746,
0.24427814781665802,
-0.24192851781845093,
0.24217157065868378,
-0.1680072844028473,
0.040181696... |
https://github.com/huggingface/datasets/issues/1838 | Hi @patrickvonplaten
I can have a look to this dataset later since I am trying to add the OpenSLR dataset https://github.com/huggingface/datasets/pull/2173
Hopefully I have enough space since the compressed file is 21GB. The release 3 is even bigger: 54GB :-0 | Add tedlium | ## Adding a Dataset
- **Name:** *tedlium*
- **Description:** *The TED-LIUM 1-3 corpus is English-language TED talks, with transcriptions, sampled at 16kHz. It contains about 118 hours of speech.*
- **Paper:** Homepage: http://www.openslr.org/7/, https://lium.univ-lemans.fr/en/ted-lium2/ &, https://www.openslr.org/51... | 40 | Add tedlium
## Adding a Dataset
- **Name:** *tedlium*
- **Description:** *The TED-LIUM 1-3 corpus is English-language TED talks, with transcriptions, sampled at 16kHz. It contains about 118 hours of speech.*
- **Paper:** Homepage: http://www.openslr.org/7/, https://lium.univ-lemans.fr/en/ted-lium2/ &, https://www.... | [
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0.35040077567100525,
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-0.09178784489... |
https://github.com/huggingface/datasets/issues/1837 | @patrickvonplaten I'd like to take this, if nobody has already done it. I have added datasets before through the datasets sprint, but I feel rusty on the details, so I'll look at the guide as well as similar audio PRs (#1878 in particular comes to mind). If there is any detail I should be aware of please, let me know! ... | Add VCTK | ## Adding a Dataset
- **Name:** *VCTK*
- **Description:** *This CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents. Each speaker reads out about 400 sentences, which were selected from a newspaper, the rainbow passage and an elicitation paragraph used for the speech accent arch... | 72 | Add VCTK
## Adding a Dataset
- **Name:** *VCTK*
- **Description:** *This CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents. Each speaker reads out about 400 sentences, which were selected from a newspaper, the rainbow passage and an elicitation paragraph used for the speech ... | [
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0.20890873670578003,
-0.16260890662670135,
0.098804362118... |
https://github.com/huggingface/datasets/issues/1837 | That sounds great @jaketae - let me know if you need any help i.e. feel free to ping me on a first PR :-) | Add VCTK | ## Adding a Dataset
- **Name:** *VCTK*
- **Description:** *This CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents. Each speaker reads out about 400 sentences, which were selected from a newspaper, the rainbow passage and an elicitation paragraph used for the speech accent arch... | 24 | Add VCTK
## Adding a Dataset
- **Name:** *VCTK*
- **Description:** *This CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents. Each speaker reads out about 400 sentences, which were selected from a newspaper, the rainbow passage and an elicitation paragraph used for the speech ... | [
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0.13000781... |
https://github.com/huggingface/datasets/issues/1835 | Hey @patrickvonplaten, I have managed to download the zip on [here]( http://spandh.dcs.shef.ac.uk/chime_challenge/CHiME4/download.html) and successfully uploaded all the files on a hugging face dataset:
https://huggingface.co/datasets/ksbai123/Chime4
However I am getting this error when trying to use the dataset... | Add CHiME4 dataset | ## Adding a Dataset
- **Name:** Chime4
- **Description:** Chime4 is a dataset for automatic speech recognition. It is especially useful for evaluating models in a noisy environment and for multi-channel ASR
- **Paper:** Dataset comes from a channel: http://spandh.dcs.shef.ac.uk/chime_challenge/CHiME4/ . Results pape... | 59 | Add CHiME4 dataset
## Adding a Dataset
- **Name:** Chime4
- **Description:** Chime4 is a dataset for automatic speech recognition. It is especially useful for evaluating models in a noisy environment and for multi-channel ASR
- **Paper:** Dataset comes from a channel: http://spandh.dcs.shef.ac.uk/chime_challenge/C... | [
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0.3496352434158... |
https://github.com/huggingface/datasets/issues/1835 | Hi @KossaiSbai,
Thanks for your contribution.
As the issue is not strictly related to the `datasets` library, but to the specific implementation of the CHiME4 dataset, I have opened an issue in the Discussion tab of the dataset: https://huggingface.co/datasets/ksbai123/Chime4/discussions/2
Let's continue the dis... | Add CHiME4 dataset | ## Adding a Dataset
- **Name:** Chime4
- **Description:** Chime4 is a dataset for automatic speech recognition. It is especially useful for evaluating models in a noisy environment and for multi-channel ASR
- **Paper:** Dataset comes from a channel: http://spandh.dcs.shef.ac.uk/chime_challenge/CHiME4/ . Results pape... | 44 | Add CHiME4 dataset
## Adding a Dataset
- **Name:** Chime4
- **Description:** Chime4 is a dataset for automatic speech recognition. It is especially useful for evaluating models in a noisy environment and for multi-channel ASR
- **Paper:** Dataset comes from a channel: http://spandh.dcs.shef.ac.uk/chime_challenge/C... | [
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0.169688820... |
https://github.com/huggingface/datasets/issues/1831 | Hi ! The `dl_manager` is a `DownloadManager` object and is responsible for downloading the raw data files.
It is used by dataset builders in their `_split_generators` method to download the raw data files that are necessary to build the datasets splits.
The `Conll2003` class is a dataset builder, and so you can dow... | Some question about raw dataset download info in the project . | Hi , i review the code in
https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py
in the _split_generators function is the truly logic of download raw datasets with dl_manager
and use Conll2003 cls by use import_main_class in load_dataset function
My question is that , with this logic i... | 166 | Some question about raw dataset download info in the project .
Hi , i review the code in
https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py
in the _split_generators function is the truly logic of download raw datasets with dl_manager
and use Conll2003 cls by use import_main_class ... | [
-0.1392955183982849,
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-0.05754382535815239,
0.5315553545951843,
0.1806541383266449,
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0.12636716663837433,
-0.401090145111084,
0.19039885699748993,
-0.071718230843544,
0.5283395051956177... |
https://github.com/huggingface/datasets/issues/1831 | I am afraid that there is not a very straightforward way to get that location.
Another option, from _split_generators would be to use:
- `dl_manager._download_config.cache_dir` to get the directory where all the raw downloaded files are:
```python
download_dir = dl_manager._download_config.cache_dir
```
-... | Some question about raw dataset download info in the project . | Hi , i review the code in
https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py
in the _split_generators function is the truly logic of download raw datasets with dl_manager
and use Conll2003 cls by use import_main_class in load_dataset function
My question is that , with this logic i... | 111 | Some question about raw dataset download info in the project .
Hi , i review the code in
https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py
in the _split_generators function is the truly logic of download raw datasets with dl_manager
and use Conll2003 cls by use import_main_class ... | [
-0.1346980631351471,
-0.02914176881313324,
-0.05659553408622742,
0.5307532548904419,
0.11883687973022461,
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0.10200826823711395,
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0.04150839149951935,
0.08339448273181915,
-0.419790655374527,
0.20728333294391632,
-0.1245637834072113,
0.5449790358543... |
https://github.com/huggingface/datasets/issues/1831 | Sure it would be nice to have an easier access to these paths !
The dataset builder could have a method to return those, what do you think ?
Feel free to work on this @albertvillanova , it would be a nice addition :)
Your suggestion does work as well @albertvillanova if you complete it by specifying `etag=` to `h... | Some question about raw dataset download info in the project . | Hi , i review the code in
https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py
in the _split_generators function is the truly logic of download raw datasets with dl_manager
and use Conll2003 cls by use import_main_class in load_dataset function
My question is that , with this logic i... | 100 | Some question about raw dataset download info in the project .
Hi , i review the code in
https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py
in the _split_generators function is the truly logic of download raw datasets with dl_manager
and use Conll2003 cls by use import_main_class ... | [
-0.1199875921010971,
-0.10072723031044006,
-0.044122617691755295,
0.5240065455436707,
0.043897759169340134,
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0.11834052950143814,
0.017049528658390045,
0.011314891278743744,
0.1344253420829773,
-0.34619325399398804,
0.1511436402797699,
-0.13548901677131653,
0.5920692682... |
https://github.com/huggingface/datasets/issues/1831 | Once #1846 will be merged, the paths to the raw downloaded files will be accessible as:
```python
builder_instance.dl_manager.downloaded_paths
``` | Some question about raw dataset download info in the project . | Hi , i review the code in
https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py
in the _split_generators function is the truly logic of download raw datasets with dl_manager
and use Conll2003 cls by use import_main_class in load_dataset function
My question is that , with this logic i... | 19 | Some question about raw dataset download info in the project .
Hi , i review the code in
https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py
in the _split_generators function is the truly logic of download raw datasets with dl_manager
and use Conll2003 cls by use import_main_class ... | [
-0.2227526158094406,
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0.5368559956550598,
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0.11943285167217255,
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0.03015834093093872,
0.12580606341362,
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0.190369114279747,
-0.1131502166390419,
0.6030974388122559... |
https://github.com/huggingface/datasets/issues/1830 | Hi @wumpusman
`datasets` has a caching mechanism that allows to cache the results of `.map` so that when you want to re-run it later it doesn't recompute it again.
So when you do `.map`, what actually happens is:
1. compute the hash used to identify your `map` for the cache
2. apply your function on every batch
... | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? | This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_tokenizer(original_tokenizer,text,path="simpledata/tokenizer"):
words_u... | 116 | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer?
This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_to... | [
-0.40404707193374634,
-0.013007253408432007,
-0.10247048735618591,
0.10342950373888016,
0.14530548453330994,
-0.12255377322435379,
0.2550543248653412,
0.1890886425971985,
0.13067764043807983,
-0.006502337753772736,
-0.05422341078519821,
0.4988860785961151,
-0.1724810153245926,
-0.272759735... |
https://github.com/huggingface/datasets/issues/1830 | Hi @lhoestq ,
Thanks for the reply. It's entirely possible that is the issue. Since it's a side project I won't be looking at it till later this week, but, I'll verify it by disabling caching and hopefully I'll see the same runtime.
Appreciate the reference,
Michael | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? | This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_tokenizer(original_tokenizer,text,path="simpledata/tokenizer"):
words_u... | 47 | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer?
This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_to... | [
-0.40404707193374634,
-0.013007253408432007,
-0.10247048735618591,
0.10342950373888016,
0.14530548453330994,
-0.12255377322435379,
0.2550543248653412,
0.1890886425971985,
0.13067764043807983,
-0.006502337753772736,
-0.05422341078519821,
0.4988860785961151,
-0.1724810153245926,
-0.272759735... |
https://github.com/huggingface/datasets/issues/1830 | I believe this is an actual issue, tokenizing a ~4GB txt file went from an hour and a half to ~10 minutes when I switched from my pre-trained tokenizer(on the same dataset) to the default gpt2 tokenizer.
Both were loaded using:
```
AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)
```
I trained the ... | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? | This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_tokenizer(original_tokenizer,text,path="simpledata/tokenizer"):
words_u... | 117 | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer?
This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_to... | [
-0.40404707193374634,
-0.013007253408432007,
-0.10247048735618591,
0.10342950373888016,
0.14530548453330994,
-0.12255377322435379,
0.2550543248653412,
0.1890886425971985,
0.13067764043807983,
-0.006502337753772736,
-0.05422341078519821,
0.4988860785961151,
-0.1724810153245926,
-0.272759735... |
https://github.com/huggingface/datasets/issues/1830 | Hi @johncookds do you think this can come from one tokenizer being faster than the other one ? Can you try to compare their speed without using `datasets` just to make sure ? | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? | This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_tokenizer(original_tokenizer,text,path="simpledata/tokenizer"):
words_u... | 33 | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer?
This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_to... | [
-0.40404707193374634,
-0.013007253408432007,
-0.10247048735618591,
0.10342950373888016,
0.14530548453330994,
-0.12255377322435379,
0.2550543248653412,
0.1890886425971985,
0.13067764043807983,
-0.006502337753772736,
-0.05422341078519821,
0.4988860785961151,
-0.1724810153245926,
-0.272759735... |
https://github.com/huggingface/datasets/issues/1830 | Hi yes, I'm closing the loop here with some timings below. The issue seems to be at least somewhat/mainly with the tokenizer's themselves. Moreover legacy saves of the trainer tokenizer perform faster but differently than the new tokenizer.json saves(note nothing about the training process/adding of special tokens chan... | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? | This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_tokenizer(original_tokenizer,text,path="simpledata/tokenizer"):
words_u... | 124 | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer?
This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_to... | [
-0.40404707193374634,
-0.013007253408432007,
-0.10247048735618591,
0.10342950373888016,
0.14530548453330994,
-0.12255377322435379,
0.2550543248653412,
0.1890886425971985,
0.13067764043807983,
-0.006502337753772736,
-0.05422341078519821,
0.4988860785961151,
-0.1724810153245926,
-0.272759735... |
https://github.com/huggingface/datasets/issues/1830 | @lhoestq ,
Hi, which version of datasets has datasets.set_caching_enabled(False)? I get
module 'datasets' has no attribute 'set_caching_enabled'. To hopefully get around this, I reran my code on a new set of data, and did so only once.
@johncookds , thanks for chiming in, it looks this might be an issue of Toke... | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? | This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_tokenizer(original_tokenizer,text,path="simpledata/tokenizer"):
words_u... | 182 | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer?
This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_to... | [
-0.40404707193374634,
-0.013007253408432007,
-0.10247048735618591,
0.10342950373888016,
0.14530548453330994,
-0.12255377322435379,
0.2550543248653412,
0.1890886425971985,
0.13067764043807983,
-0.006502337753772736,
-0.05422341078519821,
0.4988860785961151,
-0.1724810153245926,
-0.272759735... |
https://github.com/huggingface/datasets/issues/1830 | Thanks for the experiments @johncookds and @wumpusman !
> Hi, which version of datasets has datasets.set_caching_enabled(False)?
Currently you have to install `datasets` from source to have this feature, but this will be available in the next release in a few days.
> I'm trying to figure out why the overhead ... | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? | This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_tokenizer(original_tokenizer,text,path="simpledata/tokenizer"):
words_u... | 157 | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer?
This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_to... | [
-0.40404707193374634,
-0.013007253408432007,
-0.10247048735618591,
0.10342950373888016,
0.14530548453330994,
-0.12255377322435379,
0.2550543248653412,
0.1890886425971985,
0.13067764043807983,
-0.006502337753772736,
-0.05422341078519821,
0.4988860785961151,
-0.1724810153245926,
-0.272759735... |
https://github.com/huggingface/datasets/issues/1830 | @lhoestq,
I just checked that previous run time was actually 3000 chars. I increased it to 6k chars, again, roughly double.
SlowTokenizer **7.4 s** to **15.7 s**
Tokenizer: **276 ms** to **616 ms**
I'll post this issue on Tokenizer, seems it hasn't quite been raised (albeit I noticed a similar issue that mig... | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? | This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_tokenizer(original_tokenizer,text,path="simpledata/tokenizer"):
words_u... | 56 | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer?
This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_to... | [
-0.40404707193374634,
-0.013007253408432007,
-0.10247048735618591,
0.10342950373888016,
0.14530548453330994,
-0.12255377322435379,
0.2550543248653412,
0.1890886425971985,
0.13067764043807983,
-0.006502337753772736,
-0.05422341078519821,
0.4988860785961151,
-0.1724810153245926,
-0.272759735... |
https://github.com/huggingface/datasets/issues/1830 | Hi,
I'm following up here as I found my exact issue. It was with saving and re-loading the tokenizer. When I trained then processed the data without saving and reloading it, it was 10x-100x faster than when I saved and re-loaded it.
Both resulted in the exact same tokenized datasets as well.
There is additionally ... | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? | This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_tokenizer(original_tokenizer,text,path="simpledata/tokenizer"):
words_u... | 93 | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer?
This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_to... | [
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0.4988860785961151,
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https://github.com/huggingface/datasets/issues/1827 | Hi @acul3
Issue #1776 talks about doing on-the-fly data pre-processing, which I think is solved in the next release as mentioned in the issue #1825. I also look forward to using this feature, though :)
I wanted to ask about on-the-fly data loading from the cache (before pre-processing). | Regarding On-the-fly Data Loading | Hi,
I was wondering if it is possible to load images/texts as a batch during the training process, without loading the entire dataset on the RAM at any given point.
Thanks,
Gunjan | 48 | Regarding On-the-fly Data Loading
Hi,
I was wondering if it is possible to load images/texts as a batch during the training process, without loading the entire dataset on the RAM at any given point.
Thanks,
Gunjan
Hi @acul3
Issue #1776 talks about doing on-the-fly data pre-processing, which I think is s... | [
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0.21161910891532898,... |
https://github.com/huggingface/datasets/issues/1827 | Hi ! Currently when you load a dataset via `load_dataset` for example, then the dataset is memory-mapped from an Arrow file on disk. Therefore there's almost no RAM usage even if your dataset contains TB of data.
Usually at training time only one batch of data at a time is loaded in memory.
Does that answer your qu... | Regarding On-the-fly Data Loading | Hi,
I was wondering if it is possible to load images/texts as a batch during the training process, without loading the entire dataset on the RAM at any given point.
Thanks,
Gunjan | 66 | Regarding On-the-fly Data Loading
Hi,
I was wondering if it is possible to load images/texts as a batch during the training process, without loading the entire dataset on the RAM at any given point.
Thanks,
Gunjan
Hi ! Currently when you load a dataset via `load_dataset` for example, then the dataset is memo... | [
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0.19639967381954193... |
https://github.com/huggingface/datasets/issues/1825 | Hi ! Looks related to #861
You are right: tokenizing a dataset using map takes a lot of space since it can store `input_ids` but also `token_type_ids`, `attention_mask` and `special_tokens_mask`. Moreover if your tokenization function returns python integers then by default they'll be stored as int64 which can take... | Datasets library not suitable for huge text datasets. | Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with tokenizer.map()) is not really thought for datasets this ... | 197 | Datasets library not suitable for huge text datasets.
Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with t... | [
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0.1473781317472458,
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0.01088544726... |
https://github.com/huggingface/datasets/issues/1825 | How recently was `set_transform` added? I am actually trying to implement it and getting an error:
`AttributeError: 'Dataset' object has no attribute 'set_transform'
`
I'm on v.1.2.1.
EDIT: Oh, wait I see now it's in the v.2.0. Whoops! This should be really useful. | Datasets library not suitable for huge text datasets. | Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with tokenizer.map()) is not really thought for datasets this ... | 43 | Datasets library not suitable for huge text datasets.
Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with t... | [
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0.09787501394748688,
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0.161734819412... |
https://github.com/huggingface/datasets/issues/1825 | Yes indeed it was added a few days ago. The code is available on master
We'll do a release next week :)
Feel free to install `datasets` from source to try it out though, I would love to have some feedbacks | Datasets library not suitable for huge text datasets. | Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with tokenizer.map()) is not really thought for datasets this ... | 41 | Datasets library not suitable for huge text datasets.
Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with t... | [
-0.4051038920879364,
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0.015502996742725372,
0.29045370221138,
0.2991151213645935,
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0.3566736578941345,
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0.051100365817546844,
0.060472242534160614,
-0.24908997118473053,
0.1777265369892120... |
https://github.com/huggingface/datasets/issues/1825 | For information: it's now available in `datasets` 1.3.0.
The 2.0 is reserved for even cooler features ;) | Datasets library not suitable for huge text datasets. | Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with tokenizer.map()) is not really thought for datasets this ... | 17 | Datasets library not suitable for huge text datasets.
Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with t... | [
-0.43452155590057373,
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0.035968124866485596,
0.05125759541988373,
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0.1889112293... |
https://github.com/huggingface/datasets/issues/1825 | Hi @alexvaca0 , we have optimized Datasets' disk usage in the latest release v1.5.
Feel free to update your Datasets version
```shell
pip install -U datasets
```
and see if it better suits your needs. | Datasets library not suitable for huge text datasets. | Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with tokenizer.map()) is not really thought for datasets this ... | 35 | Datasets library not suitable for huge text datasets.
Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with t... | [
-0.40281546115875244,
0.07713928818702698,
0.008600369095802307,
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0.030155975371599197,
0.3559311628341675,
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0.11885133385658... |
https://github.com/huggingface/datasets/issues/1821 | Hi!
Thank you for reporting this issue. I agree that the information about the exception should be more clear and explicit.
I could take on this issue.
On the meantime, as you can see from the exception stack trace, HF Datasets uses pandas to read the CSV files. You can pass arguments to `pandas.read_csv` by p... | Provide better exception message when one of many files results in an exception | I find when I process many files, i.e.
```
train_files = glob.glob('rain*.csv')
validation_files = glob.glob(validation*.csv')
datasets = load_dataset("csv", data_files=dict(train=train_files, validation=validation_files))
```
I sometimes encounter an error due to one of the files being misformed (i.e. no dat... | 129 | Provide better exception message when one of many files results in an exception
I find when I process many files, i.e.
```
train_files = glob.glob('rain*.csv')
validation_files = glob.glob(validation*.csv')
datasets = load_dataset("csv", data_files=dict(train=train_files, validation=validation_files))
```
I... | [
-0.10873319953680038,
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0.007515575736761093,
0.28152039647102356,
0.18453599512577057,
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0.14092247188091278,
0.39342939853668213,
0.22628797590732574,
0.28828567266464233,
0.2727557420730591,
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-0.27146828174... |
https://github.com/huggingface/datasets/issues/1818 | Hi ! Thanks for reporting. This was indeed a bug introduced when we moved the `json` dataset loader inside the `datasets` package (before that, the `json` loader was fetched online, as all the other dataset scripts).
This should be fixed on master now. Feel free to install `datasets` from source to try it out.
The ... | Loading local dataset raise requests.exceptions.ConnectTimeout | Load local dataset:
```
dataset = load_dataset('json', data_files=["../../data/json.json"])
train = dataset["train"]
print(train.features)
train1 = train.map(lambda x: {"labels": 1})
print(train1[:2])
```
but it raised requests.exceptions.ConnectTimeout:
```
/Users/littlely/myvirtual/tf2/bin/python3.7 /Us... | 69 | Loading local dataset raise requests.exceptions.ConnectTimeout
Load local dataset:
```
dataset = load_dataset('json', data_files=["../../data/json.json"])
train = dataset["train"]
print(train.features)
train1 = train.map(lambda x: {"labels": 1})
print(train1[:2])
```
but it raised requests.exceptions.Connec... | [
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0.35534000396728516,
0.062465522438287735,
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https://github.com/huggingface/datasets/issues/1817 | Hi !
The error you have is due to the `input_ids` column not having the same number of examples as the other columns.
Indeed you're concatenating the `input_ids` at this line:
https://github.com/LuCeHe/GenericTools/blob/431835d8e13ec24dceb5ee4dc4ae58f0e873b091/KerasTools/lm_preprocessing.py#L134
However the oth... | pyarrow.lib.ArrowInvalid: Column 1 named input_ids expected length 599 but got length 1500 | I am trying to preprocess any dataset in this package with GPT-2 tokenizer, so I need to structure the datasets as long sequences of text without padding. I've been following a couple of your tutorials and here you can find the script that is failing right at the end
https://github.com/LuCeHe/GenericTools/blob/maste... | 116 | pyarrow.lib.ArrowInvalid: Column 1 named input_ids expected length 599 but got length 1500
I am trying to preprocess any dataset in this package with GPT-2 tokenizer, so I need to structure the datasets as long sequences of text without padding. I've been following a couple of your tutorials and here you can find the... | [
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https://github.com/huggingface/datasets/issues/1811 | Thanks for adding this dataset! As far as I know `supervised_keys` is mostly a holdover from TFDS, but isn't really used, so feel free to drop it (@lhoestq or @thomwolf correct me if I'm wrong). It definitely shouldn't be blocking :) | Unable to add Multi-label Datasets | I am trying to add [CIFAR-100](https://www.cs.toronto.edu/~kriz/cifar.html) dataset. The dataset contains two labels per image - `fine label` and `coarse label`. Using just one label in supervised keys as
`supervised_keys=("img", "fine_label")` raises no issue. But trying `supervised_keys=("img", "fine_label","coarse... | 41 | Unable to add Multi-label Datasets
I am trying to add [CIFAR-100](https://www.cs.toronto.edu/~kriz/cifar.html) dataset. The dataset contains two labels per image - `fine label` and `coarse label`. Using just one label in supervised keys as
`supervised_keys=("img", "fine_label")` raises no issue. But trying `supervi... | [
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0.1535528302192688,
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0.3479330539703369... |
https://github.com/huggingface/datasets/issues/1811 | Thanks @yjernite @lhoestq
The template for new dataset makes it slightly confusing. I suppose the comment suggesting its update can be removed. | Unable to add Multi-label Datasets | I am trying to add [CIFAR-100](https://www.cs.toronto.edu/~kriz/cifar.html) dataset. The dataset contains two labels per image - `fine label` and `coarse label`. Using just one label in supervised keys as
`supervised_keys=("img", "fine_label")` raises no issue. But trying `supervised_keys=("img", "fine_label","coarse... | 22 | Unable to add Multi-label Datasets
I am trying to add [CIFAR-100](https://www.cs.toronto.edu/~kriz/cifar.html) dataset. The dataset contains two labels per image - `fine label` and `coarse label`. Using just one label in supervised keys as
`supervised_keys=("img", "fine_label")` raises no issue. But trying `supervi... | [
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0.018145859241485596,
0.1329573392868042,
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0.3479330539703369... |
https://github.com/huggingface/datasets/issues/1810 | Hi @gchhablani since Array2D doesn't support images of different sizes, I would suggest to store in the dataset the paths to the image file instead of the image data. This has the advantage of not decompressing the data (images are often compressed using jpeg, png etc.). Users can still apply `.map` to load the images ... | Add Hateful Memes Dataset | ## Add Hateful Memes Dataset
- **Name:** Hateful Memes
- **Description:** [https://ai.facebook.com/blog/hateful-memes-challenge-and-data-set]( https://ai.facebook.com/blog/hateful-memes-challenge-and-data-set)
- **Paper:** [https://arxiv.org/pdf/2005.04790.pdf](https://arxiv.org/pdf/2005.04790.pdf)
- **Data:** [Thi... | 87 | Add Hateful Memes Dataset
## Add Hateful Memes Dataset
- **Name:** Hateful Memes
- **Description:** [https://ai.facebook.com/blog/hateful-memes-challenge-and-data-set]( https://ai.facebook.com/blog/hateful-memes-challenge-and-data-set)
- **Paper:** [https://arxiv.org/pdf/2005.04790.pdf](https://arxiv.org/pdf/2005.... | [
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0.247500956... |
https://github.com/huggingface/datasets/issues/1808 | AFAIK, there is currently no built-in method on the `Dataset` object to do this.
However, a workaround is to directly use the Arrow table backing the dataset, **but it implies loading the whole dataset in memory** (correct me if I'm mistaken @lhoestq).
You can convert the Arrow table to a pandas dataframe to save t... | writing Datasets in a human readable format | Hi
I see there is a save_to_disk function to save data, but this is not human readable format, is there a way I could save a Dataset object in a human readable format to a file like json? thanks @lhoestq | 101 | writing Datasets in a human readable format
Hi
I see there is a save_to_disk function to save data, but this is not human readable format, is there a way I could save a Dataset object in a human readable format to a file like json? thanks @lhoestq
AFAIK, there is currently no built-in method on the `Dataset` obj... | [
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0.2707337737083435,
... |
https://github.com/huggingface/datasets/issues/1808 | Indeed this works as long as you have enough memory.
It would be amazing to have export options like csv, json etc. !
It should be doable to implement something that iterates through the dataset batch by batch to write to csv for example.
There is already an `export` method but currently the only export type that ... | writing Datasets in a human readable format | Hi
I see there is a save_to_disk function to save data, but this is not human readable format, is there a way I could save a Dataset object in a human readable format to a file like json? thanks @lhoestq | 61 | writing Datasets in a human readable format
Hi
I see there is a save_to_disk function to save data, but this is not human readable format, is there a way I could save a Dataset object in a human readable format to a file like json? thanks @lhoestq
Indeed this works as long as you have enough memory.
It would be... | [
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0.429017990827... |
https://github.com/huggingface/datasets/issues/1805 | Hi ! Indeed we used to require mapping functions to be picklable with `pickle` or `dill` in order to cache the resulting datasets. And FAISS indexes are not picklable unfortunately.
But since #1703 this is no longer required (the caching will simply be disabled). This change will be available in the next release of ... | can't pickle SwigPyObject objects when calling dataset.get_nearest_examples from FAISS index | So, I have the following instances in my dataset
```
{'question': 'An astronomer observes that a planet rotates faster after a meteorite impact. Which is the most likely effect of
this increase in rotation?',
'answer': 'C',
'example_id': 'ARCCH_Mercury_7175875',
'options':[{'option_context': 'One effect of ... | 63 | can't pickle SwigPyObject objects when calling dataset.get_nearest_examples from FAISS index
So, I have the following instances in my dataset
```
{'question': 'An astronomer observes that a planet rotates faster after a meteorite impact. Which is the most likely effect of
this increase in rotation?',
'answer'... | [
0.06904204189777374,
-0.38878411054611206,
-0.0696357935667038,
0.24682532250881195,
0.16422626376152039,
0.02776406705379486,
0.1784280389547348,
0.05411216616630554,
0.40896546840667725,
0.5476053357124329,
-0.05009919032454491,
0.4959973692893982,
0.115793377161026,
-0.12733493745326996... |
https://github.com/huggingface/datasets/issues/1805 | I totally forgot to answer this issue, I'm so sorry.
I was able to get it working by installing `datasets` from source. Huge thanks! | can't pickle SwigPyObject objects when calling dataset.get_nearest_examples from FAISS index | So, I have the following instances in my dataset
```
{'question': 'An astronomer observes that a planet rotates faster after a meteorite impact. Which is the most likely effect of
this increase in rotation?',
'answer': 'C',
'example_id': 'ARCCH_Mercury_7175875',
'options':[{'option_context': 'One effect of ... | 24 | can't pickle SwigPyObject objects when calling dataset.get_nearest_examples from FAISS index
So, I have the following instances in my dataset
```
{'question': 'An astronomer observes that a planet rotates faster after a meteorite impact. Which is the most likely effect of
this increase in rotation?',
'answer'... | [
0.06904204189777374,
-0.38878411054611206,
-0.0696357935667038,
0.24682532250881195,
0.16422626376152039,
0.02776406705379486,
0.1784280389547348,
0.05411216616630554,
0.40896546840667725,
0.5476053357124329,
-0.05009919032454491,
0.4959973692893982,
0.115793377161026,
-0.12733493745326996... |
https://github.com/huggingface/datasets/issues/1803 | Hello, @lhoestq / @gaceladri : We have been seeing similar behavior with bigger datasets, where querying time increases. Are you folks aware of any solution that fixes this problem yet? | Querying examples from big datasets is slower than small datasets | After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_dataset("bookcorpus", split="train[:50%]")
b100 = load_dataset("bookcorp... | 30 | Querying examples from big datasets is slower than small datasets
After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_datas... | [
-0.4054940938949585,
0.05864456295967102,
-0.07997146993875504,
0.13153260946273804,
-0.07969397306442261,
-0.1776915192604065,
0.24417473375797272,
0.4918093979358673,
-0.2313987761735916,
0.1801937222480774,
0.08149372041225433,
0.055089276283979416,
0.12508581578731537,
-0.1007568240165... |
https://github.com/huggingface/datasets/issues/1803 | Hi ! I'm pretty sure that it can be fixed by using the Arrow IPC file format instead of the raw streaming format but I haven't tested yet.
I'll take a look at it soon and let you know | Querying examples from big datasets is slower than small datasets | After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_dataset("bookcorpus", split="train[:50%]")
b100 = load_dataset("bookcorp... | 39 | Querying examples from big datasets is slower than small datasets
After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_datas... | [
-0.4054940938949585,
0.05864456295967102,
-0.07997146993875504,
0.13153260946273804,
-0.07969397306442261,
-0.1776915192604065,
0.24417473375797272,
0.4918093979358673,
-0.2313987761735916,
0.1801937222480774,
0.08149372041225433,
0.055089276283979416,
0.12508581578731537,
-0.1007568240165... |
https://github.com/huggingface/datasets/issues/1803 | My workaround is to shard the dataset into splits in my ssd disk and feed the data in different training sessions. But it is a bit of a pain when we need to reload the last training session with the rest of the split with the Trainer in transformers.
I mean, when I split the training and then reloads the model and o... | Querying examples from big datasets is slower than small datasets | After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_dataset("bookcorpus", split="train[:50%]")
b100 = load_dataset("bookcorp... | 218 | Querying examples from big datasets is slower than small datasets
After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_datas... | [
-0.4054940938949585,
0.05864456295967102,
-0.07997146993875504,
0.13153260946273804,
-0.07969397306442261,
-0.1776915192604065,
0.24417473375797272,
0.4918093979358673,
-0.2313987761735916,
0.1801937222480774,
0.08149372041225433,
0.055089276283979416,
0.12508581578731537,
-0.1007568240165... |
https://github.com/huggingface/datasets/issues/1803 | I just tested and using the Arrow File format doesn't improve the speed... This will need further investigation.
My guess is that it has to iterate over the record batches or chunks of a ChunkedArray in order to retrieve elements.
However if we know in advance in which chunk the element is, and at what index it i... | Querying examples from big datasets is slower than small datasets | After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_dataset("bookcorpus", split="train[:50%]")
b100 = load_dataset("bookcorp... | 82 | Querying examples from big datasets is slower than small datasets
After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_datas... | [
-0.4054940938949585,
0.05864456295967102,
-0.07997146993875504,
0.13153260946273804,
-0.07969397306442261,
-0.1776915192604065,
0.24417473375797272,
0.4918093979358673,
-0.2313987761735916,
0.1801937222480774,
0.08149372041225433,
0.055089276283979416,
0.12508581578731537,
-0.1007568240165... |
https://github.com/huggingface/datasets/issues/1803 | I have a dataset with about 2.7 million rows (which I'm loading via `load_from_disk`), and I need to fetch around 300k (particular) rows of it, by index. Currently this is taking a really long time (~8 hours). I tried sharding the large dataset but overall it doesn't change how long it takes to fetch the desired rows.
... | Querying examples from big datasets is slower than small datasets | After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_dataset("bookcorpus", split="train[:50%]")
b100 = load_dataset("bookcorp... | 125 | Querying examples from big datasets is slower than small datasets
After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_datas... | [
-0.4054940938949585,
0.05864456295967102,
-0.07997146993875504,
0.13153260946273804,
-0.07969397306442261,
-0.1776915192604065,
0.24417473375797272,
0.4918093979358673,
-0.2313987761735916,
0.1801937222480774,
0.08149372041225433,
0.055089276283979416,
0.12508581578731537,
-0.1007568240165... |
https://github.com/huggingface/datasets/issues/1803 | Hi ! Feel free to post a message on the [forum](https://discuss.huggingface.co/c/datasets/10). I'd be happy to help you with this.
In your post on the forum, feel free to add more details about your setup:
What are column names and types of your dataset ?
How was the dataset constructed ?
Is the dataset shuffled ... | Querying examples from big datasets is slower than small datasets | After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_dataset("bookcorpus", split="train[:50%]")
b100 = load_dataset("bookcorp... | 95 | Querying examples from big datasets is slower than small datasets
After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_datas... | [
-0.4054940938949585,
0.05864456295967102,
-0.07997146993875504,
0.13153260946273804,
-0.07969397306442261,
-0.1776915192604065,
0.24417473375797272,
0.4918093979358673,
-0.2313987761735916,
0.1801937222480774,
0.08149372041225433,
0.055089276283979416,
0.12508581578731537,
-0.1007568240165... |
https://github.com/huggingface/datasets/issues/1797 | Hi ! For future references let me add a link to our discussion here : https://github.com/huggingface/datasets/issues/759#issuecomment-770684693
Let me know if you manage to fix your proxy issue or if we can do something on our end to help you :) | Connection error | Hi
I am hitting to the error, help me and thanks.
`train_data = datasets.load_dataset("xsum", split="train")`
`ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/xsum/xsum.py` | 40 | Connection error
Hi
I am hitting to the error, help me and thanks.
`train_data = datasets.load_dataset("xsum", split="train")`
`ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/xsum/xsum.py`
Hi ! For future references let me add a link to our discussion here... | [
-0.26246824860572815,
-0.4733124375343323,
-0.10554549098014832,
0.17871570587158203,
0.5621635913848877,
-0.1030881255865097,
-0.017071833834052086,
0.22683115303516388,
0.1645880490541458,
0.2273809313774109,
-0.30961042642593384,
-0.00459892675280571,
0.20449578762054443,
0.443229079246... |
https://github.com/huggingface/datasets/issues/1796 | When I use the filter on the arrow table directly, it works like butter. But I can't find a way to update the table in `Dataset` object.
```
ds_table = dataset.data.filter(mask=dataset['flag'])
``` | Filter on dataset too much slowww | I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is taking too much time. I need to filter se... | 32 | Filter on dataset too much slowww
I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is takin... | [
-0.27120888233184814,
-0.05973125994205475,
-0.11476293951272964,
-0.2779480516910553,
-0.17065051198005676,
-0.2504288852214813,
0.17076221108436584,
0.20902463793754578,
0.2598770260810852,
-0.11639678478240967,
-0.08618345856666565,
0.29582667350769043,
-0.05571427941322327,
0.406081676... |
https://github.com/huggingface/datasets/issues/1796 | Hi ! Currently the filter method reads the dataset batch by batch to write a new, filtered, arrow file on disk. Therefore all the reading + writing can take some time.
Using a mask directly on the arrow table doesn't do any read or write operation therefore it's way quicker.
Replacing the old table by the new one s... | Filter on dataset too much slowww | I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is taking too much time. I need to filter se... | 162 | Filter on dataset too much slowww
I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is takin... | [
-0.2580147981643677,
-0.12244242429733276,
-0.08642470836639404,
-0.26014676690101624,
-0.16526594758033752,
-0.24569961428642273,
0.25937482714653015,
0.2613683342933655,
0.31368905305862427,
-0.1532164216041565,
0.006636817008256912,
0.22178949415683746,
-0.11383526772260666,
0.348148077... |
https://github.com/huggingface/datasets/issues/1796 | Hi @lhoestq @ayubSubhaniya,
If there's no progress on this one, can I try working on it?
Thanks,
Gunjan | Filter on dataset too much slowww | I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is taking too much time. I need to filter se... | 18 | Filter on dataset too much slowww
I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is takin... | [
-0.22525466978549957,
-0.259549081325531,
-0.10918055474758148,
-0.21481536328792572,
-0.1230364665389061,
-0.2692412734031677,
0.2215610295534134,
0.211483895778656,
0.26342982053756714,
-0.12331388145685196,
0.027962036430835724,
0.09088105708360672,
-0.11606806516647339,
0.4082366526126... |
https://github.com/huggingface/datasets/issues/1796 | Sure @gchhablani feel free to start working on it, this would be very appreciated :)
This feature is would be really awesome, especially since arrow allows to mask really quickly and without having to rewrite the dataset on disk | Filter on dataset too much slowww | I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is taking too much time. I need to filter se... | 39 | Filter on dataset too much slowww
I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is takin... | [
-0.25473982095718384,
-0.235118567943573,
-0.10145208239555359,
-0.22573454678058624,
-0.14286470413208008,
-0.2871682941913605,
0.27946504950523376,
0.23597803711891174,
0.31276702880859375,
-0.11907678842544556,
0.06210961937904358,
0.13041609525680542,
-0.12634721398353577,
0.4224110841... |
https://github.com/huggingface/datasets/issues/1796 | No update so far, we haven't worked on this yet :/
Though PyArrow is much more stable than 3 years ago so it would be a good time to dive into this | Filter on dataset too much slowww | I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is taking too much time. I need to filter se... | 32 | Filter on dataset too much slowww
I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is takin... | [
-0.23869255185127258,
-0.136336088180542,
-0.08516345173120499,
-0.25257423520088196,
-0.060326382517814636,
-0.28717660903930664,
0.26554644107818604,
0.226846382021904,
0.10224667936563492,
-0.10796566307544708,
-0.023406727239489555,
0.13732701539993286,
-0.08909493684768677,
0.31491050... |
https://github.com/huggingface/datasets/issues/1796 | Hi @lhoestq, thanks a lot for the update!
I would like to work on this(if possible). Could you please give me some steps regarding how should I approach this? Also any references would be great! | Filter on dataset too much slowww | I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is taking too much time. I need to filter se... | 35 | Filter on dataset too much slowww
I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is takin... | [
-0.22325900197029114,
-0.23717470467090607,
-0.10137200355529785,
-0.2212727665901184,
-0.11815958470106125,
-0.2710965573787689,
0.21705058217048645,
0.20104041695594788,
0.26321887969970703,
-0.12426680326461792,
0.025943025946617126,
0.0924706757068634,
-0.1344791203737259,
0.4154342412... |
https://github.com/huggingface/datasets/issues/1796 | I just played a bit with it to make sure using `table.filter()` is fine, but actually it seems to create a new table **in memory** :/
This is an issue since it can quickly fill the RAM, and `datasets`'s role is to make sure you can load bigger-than-memory datasets. Therefore I don't think it's a good idea in the end t... | Filter on dataset too much slowww | I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is taking too much time. I need to filter se... | 134 | Filter on dataset too much slowww
I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is takin... | [
-0.26736944913864136,
-0.1310533881187439,
-0.09514777362346649,
-0.22678987681865692,
-0.08441470563411713,
-0.2332700490951538,
0.20191867649555206,
0.2510642409324646,
0.21100370585918427,
-0.16824951767921448,
-0.047437313944101334,
0.2349599301815033,
-0.0497024767100811,
0.3456452488... |
https://github.com/huggingface/datasets/issues/1790 | Hi !
Apache Beam is a framework used to define data transformation pipelines. These pipeline can then be run in many runtimes: DataFlow, Spark, Flink, etc. There also exist a local runner called the DirectRunner.
Wikipedia is a dataset that requires some parsing, so to allow the processing to be run on this kind of... | ModuleNotFoundError: No module named 'apache_beam', when specific languages. | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to lo... | 167 | ModuleNotFoundError: No module named 'apache_beam', when specific languages.
```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't k... | [
0.1911676526069641,
0.00179387629032135,
-0.004188746213912964,
0.18698346614837646,
0.27138203382492065,
0.13962078094482422,
0.42134737968444824,
0.3950366675853729,
0.22948044538497925,
0.178105890750885,
0.10769874602556229,
-0.09141640365123749,
0.05334928631782532,
-0.109246045351028... |
https://github.com/huggingface/datasets/issues/1790 | Thanks for your reply!
I understood.
I tried again with installing apache-beam, add ` beam_runner="DirectRunner"` and an anther `mwparserfromhell` is also required so I installed it.
but, it also failed. It exited 1 without error message.
```py
import datasets
# BTW, 20200501.ja doesn't exist at wikipedia, s... | ModuleNotFoundError: No module named 'apache_beam', when specific languages. | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to lo... | 279 | ModuleNotFoundError: No module named 'apache_beam', when specific languages.
```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't k... | [
0.0917947068810463,
0.07459917664527893,
0.01958591490983963,
0.2518458366394043,
0.2570837736129761,
0.0409059002995491,
0.32001692056655884,
0.34807121753692627,
0.16672636568546295,
0.19595259428024292,
0.21741509437561035,
0.04889155179262161,
-0.09746188670396805,
-0.2695733308792114,... |
https://github.com/huggingface/datasets/issues/1790 | Hi @miyamonz,
I tried replicating this issue using the same snippet used by you. I am able to download the dataset without any issues, although I stopped it in the middle because the dataset is huge.
Based on a similar issue [here](https://github.com/google-research/fixmatch/issues/23), it could be related to you... | ModuleNotFoundError: No module named 'apache_beam', when specific languages. | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to lo... | 61 | ModuleNotFoundError: No module named 'apache_beam', when specific languages.
```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't k... | [
-0.08689067512750626,
0.15441207587718964,
0.03492138162255287,
0.2511790096759796,
0.35333317518234253,
0.108371302485466,
0.3212846517562866,
0.4499049782752991,
0.3734615743160248,
0.008810274302959442,
0.10232529044151306,
0.006331883370876312,
-0.009907281026244164,
-0.022560145705938... |
https://github.com/huggingface/datasets/issues/1790 | thanks for your reply and sorry for my late response.
## environment
my local machine environment info
- Ubuntu on WSL2
`lsb_release -a`
```
No LSB modules are available.
Distributor ID: Ubuntu
Description: Ubuntu 20.04.2 LTS
Release: 20.04
Codename: focal
```
RTX 2070 super
Inside WS... | ModuleNotFoundError: No module named 'apache_beam', when specific languages. | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to lo... | 606 | ModuleNotFoundError: No module named 'apache_beam', when specific languages.
```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't k... | [
-0.01646202802658081,
-0.1208428293466568,
-0.04492597281932831,
0.1289525330066681,
0.36023736000061035,
0.01179029792547226,
0.4635162949562073,
0.39907485246658325,
0.26570284366607666,
0.2212449312210083,
0.36921608448028564,
-0.0926489308476448,
0.07885448634624481,
-0.050380244851112... |
https://github.com/huggingface/datasets/issues/1790 | I don't know if this is related, but there is this issue on the wikipedia processing that you reported at #2031 (open PR is at #2037 ) .
Does the fix your proposed at #2037 helps in your case ?
And for information, the DirectRunner of Apache Beam is not optimized for memory intensive tasks, so you must be right whe... | ModuleNotFoundError: No module named 'apache_beam', when specific languages. | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to lo... | 72 | ModuleNotFoundError: No module named 'apache_beam', when specific languages.
```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't k... | [
0.11173461377620697,
-0.00644133985042572,
0.008771087974309921,
0.3851286768913269,
0.3766981363296509,
0.09046337753534317,
0.18669427931308746,
0.43439844250679016,
0.23802952468395233,
0.12736868858337402,
0.17051434516906738,
0.02249215543270111,
-0.012138579040765762,
-0.217572897672... |
https://github.com/huggingface/datasets/issues/1790 | the #2037 doesn't solve my problem directly, but I found the point!
https://github.com/huggingface/datasets/blob/349ac4398a3bcae6356f14c5754483383a60e8a4/datasets/wikipedia/wikipedia.py#L523
this `beam.transforms.Reshuffle()` cause the memory error.
it makes sense if I consider the shuffle means. Beam's reshuffl... | ModuleNotFoundError: No module named 'apache_beam', when specific languages. | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to lo... | 111 | ModuleNotFoundError: No module named 'apache_beam', when specific languages.
```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't k... | [
0.11943495273590088,
0.11088621616363525,
0.009472917765378952,
0.429506778717041,
0.5010866522789001,
0.05407453328371048,
0.18194738030433655,
0.4008019268512726,
-0.05477750673890114,
0.3162616789340973,
0.11126869171857834,
0.027088452130556107,
-0.19562512636184692,
-0.309715747833251... |
https://github.com/huggingface/datasets/issues/1790 | The reshuffle is needed when you use parallelism.
The objective is to redistribute the articles evenly on the workers, since the `_extract_content` step generated many articles per file. By using reshuffle, we can split the processing of the articles of one file into several workers. Without reshuffle, all the article... | ModuleNotFoundError: No module named 'apache_beam', when specific languages. | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to lo... | 73 | ModuleNotFoundError: No module named 'apache_beam', when specific languages.
```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't k... | [
0.04016484320163727,
0.010121092200279236,
-0.005872771143913269,
0.12934570014476776,
-0.011950450018048286,
0.059670597314834595,
0.36614418029785156,
0.3480101227760315,
0.02297479659318924,
0.2797616124153137,
0.16045701503753662,
0.07360954582691193,
0.19807489216327667,
-0.1953659504... |
https://github.com/huggingface/datasets/issues/1790 | Maybe the reshuffle step can be added only if the runner is not a DirectRunner ? | ModuleNotFoundError: No module named 'apache_beam', when specific languages. | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to lo... | 16 | ModuleNotFoundError: No module named 'apache_beam', when specific languages.
```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't k... | [
-0.037829525768756866,
0.05178949236869812,
0.045922502875328064,
0.16189441084861755,
0.2217683047056198,
0.04954952001571655,
0.28777068853378296,
0.30324095487594604,
0.025933735072612762,
0.17993353307247162,
0.29103487730026245,
-0.0192488394677639,
0.10451503098011017,
-0.02322814986... |
https://github.com/huggingface/datasets/issues/1786 | By default, all 3 splits will be loaded if you run the following:
```python
from datasets import load_dataset
dataset = load_dataset("lambada")
print(dataset["train"])
print(dataset["valid"])
```
If you wanted to do load this manually, you could do this:
```python
from datasets import load_dataset
dat... | How to use split dataset | 
Hey,
I want to split the lambada dataset into corpus, test, train and valid txt files (like penn treebank) but I am not able to achieve this. What I am doing is, executing the lambada.py file in my pro... | 56 | How to use split dataset
Hey,
I want to split the lambada dataset into corpus, test, train and valid txt files (like penn treebank) but I am not able to achieve this. What I am doing is, executing t... | [
-0.3074783980846405,
-0.04643075168132782,
-0.06252643465995789,
0.4651073217391968,
0.1305699199438095,
0.20379097759723663,
0.27659621834754944,
0.580761730670929,
-0.4295652508735657,
0.015045840293169022,
-0.3925747275352478,
0.25409528613090515,
0.18384906649589539,
0.3340369164943695... |
https://github.com/huggingface/datasets/issues/1785 | Hi !
What do you mean by "disk_usage(".").free` can't compute on the cluster's shared disk" exactly ?
Does it return 0 ? | Not enough disk space (Needed: Unknown size) when caching on a cluster | I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dataset(dataset, cache_dir="/path/to/cluster/shared/path")
OSError: Not eno... | 22 | Not enough disk space (Needed: Unknown size) when caching on a cluster
I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dat... | [
-0.07774314284324646,
-0.4187168776988983,
-0.084621861577034,
0.2431601732969284,
-0.09701003134250641,
0.15066012740135193,
0.07053473591804504,
0.34012138843536377,
0.39623501896858215,
0.3933160901069641,
0.41839298605918884,
-0.13893109560012817,
-0.09125030785799026,
0.00389167666435... |
https://github.com/huggingface/datasets/issues/1785 | Yes, that's right. It shows 0 free space even though there is. I suspect it might have to do with permissions on the shared disk.
```python
>>> disk_usage(".")
usage(total=999999, used=999999, free=0)
``` | Not enough disk space (Needed: Unknown size) when caching on a cluster | I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dataset(dataset, cache_dir="/path/to/cluster/shared/path")
OSError: Not eno... | 32 | Not enough disk space (Needed: Unknown size) when caching on a cluster
I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dat... | [
-0.07774314284324646,
-0.4187168776988983,
-0.084621861577034,
0.2431601732969284,
-0.09701003134250641,
0.15066012740135193,
0.07053473591804504,
0.34012138843536377,
0.39623501896858215,
0.3933160901069641,
0.41839298605918884,
-0.13893109560012817,
-0.09125030785799026,
0.00389167666435... |
https://github.com/huggingface/datasets/issues/1785 | That's an interesting behavior...
Do you know any other way to get the free space that works in your case ?
Also if it's a permission issue could you try fix the permissions and let mus know if that helped ? | Not enough disk space (Needed: Unknown size) when caching on a cluster | I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dataset(dataset, cache_dir="/path/to/cluster/shared/path")
OSError: Not eno... | 41 | Not enough disk space (Needed: Unknown size) when caching on a cluster
I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dat... | [
-0.07774314284324646,
-0.4187168776988983,
-0.084621861577034,
0.2431601732969284,
-0.09701003134250641,
0.15066012740135193,
0.07053473591804504,
0.34012138843536377,
0.39623501896858215,
0.3933160901069641,
0.41839298605918884,
-0.13893109560012817,
-0.09125030785799026,
0.00389167666435... |
https://github.com/huggingface/datasets/issues/1785 | I think its an issue on the clusters end (unclear exactly why -- maybe something with docker containers?), will close the issue | Not enough disk space (Needed: Unknown size) when caching on a cluster | I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dataset(dataset, cache_dir="/path/to/cluster/shared/path")
OSError: Not eno... | 22 | Not enough disk space (Needed: Unknown size) when caching on a cluster
I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dat... | [
-0.07774314284324646,
-0.4187168776988983,
-0.084621861577034,
0.2431601732969284,
-0.09701003134250641,
0.15066012740135193,
0.07053473591804504,
0.34012138843536377,
0.39623501896858215,
0.3933160901069641,
0.41839298605918884,
-0.13893109560012817,
-0.09125030785799026,
0.00389167666435... |
https://github.com/huggingface/datasets/issues/1785 | @philippnoah I had fixed it with a small hack where I patched `has_sufficient_disk_space` to always return `True`. you can do that with an import without having to modify the `datasets` package | Not enough disk space (Needed: Unknown size) when caching on a cluster | I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dataset(dataset, cache_dir="/path/to/cluster/shared/path")
OSError: Not eno... | 31 | Not enough disk space (Needed: Unknown size) when caching on a cluster
I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dat... | [
-0.07774314284324646,
-0.4187168776988983,
-0.084621861577034,
0.2431601732969284,
-0.09701003134250641,
0.15066012740135193,
0.07053473591804504,
0.34012138843536377,
0.39623501896858215,
0.3933160901069641,
0.41839298605918884,
-0.13893109560012817,
-0.09125030785799026,
0.00389167666435... |
https://github.com/huggingface/datasets/issues/1785 | @olinguyen Thanks for the suggestion, it works but I had to to edit builder.py in the installed package. Can you please explain how were you able to do this using import? | Not enough disk space (Needed: Unknown size) when caching on a cluster | I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dataset(dataset, cache_dir="/path/to/cluster/shared/path")
OSError: Not eno... | 31 | Not enough disk space (Needed: Unknown size) when caching on a cluster
I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dat... | [
-0.07774314284324646,
-0.4187168776988983,
-0.084621861577034,
0.2431601732969284,
-0.09701003134250641,
0.15066012740135193,
0.07053473591804504,
0.34012138843536377,
0.39623501896858215,
0.3933160901069641,
0.41839298605918884,
-0.13893109560012817,
-0.09125030785799026,
0.00389167666435... |
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