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/1785 | I was able to patch the builder code in my notebook before the load data call and it works.
```
import datasets
datasets.builder.has_sufficient_disk_space = lambda needed_bytes, directory='.': True
``` | 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... | 29 | 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/1784 | Hi !
The `json` dataset script does support this format. For example loading a dataset with this format works on my side:
```json
{"key1":11, "key2":12, "key3":13}
{"key1":21, "key2":22, "key3":23}
```
Can you show the full stacktrace please ? Also which version of datasets and pyarrow are you using ?
| JSONDecodeError on JSON with multiple lines | Hello :),
I have been trying to load data using a JSON file. Based on the [docs](https://huggingface.co/docs/datasets/loading_datasets.html#json-files), the following format is supported:
```json
{"key1":11, "key2":12, "key3":13}
{"key1":21, "key2":22, "key3":23}
```
But, when I try loading a dataset with th... | 49 | JSONDecodeError on JSON with multiple lines
Hello :),
I have been trying to load data using a JSON file. Based on the [docs](https://huggingface.co/docs/datasets/loading_datasets.html#json-files), the following format is supported:
```json
{"key1":11, "key2":12, "key3":13}
{"key1":21, "key2":22, "key3":23}
`... | [
0.07569876313209534,
-0.004834562540054321,
-0.02928275801241398,
0.4874003529548645,
0.35478273034095764,
0.14951950311660767,
0.46156513690948486,
0.06345660239458084,
0.15875336527824402,
0.01879093423485756,
0.16414324939250946,
0.2806328237056732,
-0.04647203907370567,
0.2131014764308... |
https://github.com/huggingface/datasets/issues/1784 | Hi Quentin!
I apologize for bothering you. There was some issue with my pyarrow version as far as I understand. I don't remember the exact version I was using as I didn't check it.
I repeated it with `datasets 1.2.1` and `pyarrow 2.0.0` and it worked.
Closing this issue. Again, sorry for the bother.
Thanks... | JSONDecodeError on JSON with multiple lines | Hello :),
I have been trying to load data using a JSON file. Based on the [docs](https://huggingface.co/docs/datasets/loading_datasets.html#json-files), the following format is supported:
```json
{"key1":11, "key2":12, "key3":13}
{"key1":21, "key2":22, "key3":23}
```
But, when I try loading a dataset with th... | 56 | JSONDecodeError on JSON with multiple lines
Hello :),
I have been trying to load data using a JSON file. Based on the [docs](https://huggingface.co/docs/datasets/loading_datasets.html#json-files), the following format is supported:
```json
{"key1":11, "key2":12, "key3":13}
{"key1":21, "key2":22, "key3":23}
`... | [
0.11187902092933655,
-0.06495442986488342,
-0.01278349757194519,
0.5094956755638123,
0.3668513000011444,
0.14520782232284546,
0.41166651248931885,
0.06978583335876465,
0.11648783087730408,
0.07758285850286484,
0.12275223433971405,
0.31399959325790405,
-0.013312682509422302,
0.1743165701627... |
https://github.com/huggingface/datasets/issues/1783 | Hi @ChewKokWah,
We're working on it! In the meantime, you can still find the dataset explorer at the following URL: https://huggingface.co/datasets/viewer/ | Dataset Examples Explorer | In the Older version of the Dataset, there are a useful Dataset Explorer that allow user to visualize the examples (training, test and validation) of a particular dataset, it is no longer there in current version.
Hope HuggingFace can re-enable the feature that at least allow viewing of the first 20 examples of a ... | 21 | Dataset Examples Explorer
In the Older version of the Dataset, there are a useful Dataset Explorer that allow user to visualize the examples (training, test and validation) of a particular dataset, it is no longer there in current version.
Hope HuggingFace can re-enable the feature that at least allow viewing of ... | [
-0.3861370086669922,
-0.38739824295043945,
-0.06188453733921051,
0.2974123954772949,
0.15671506524085999,
0.2989474833011627,
0.08448299765586853,
0.35528379678726196,
-0.06431098282337189,
0.3763420879840851,
0.0037852004170417786,
0.2994420826435089,
-0.29005733132362366,
0.5288336873054... |
https://github.com/huggingface/datasets/issues/1783 | Glad to see that it still exist, this existing one is more than good enough for me, it is feature rich, simple to use and concise.
Hope similar feature can be retain in the future version. | Dataset Examples Explorer | In the Older version of the Dataset, there are a useful Dataset Explorer that allow user to visualize the examples (training, test and validation) of a particular dataset, it is no longer there in current version.
Hope HuggingFace can re-enable the feature that at least allow viewing of the first 20 examples of a ... | 36 | Dataset Examples Explorer
In the Older version of the Dataset, there are a useful Dataset Explorer that allow user to visualize the examples (training, test and validation) of a particular dataset, it is no longer there in current version.
Hope HuggingFace can re-enable the feature that at least allow viewing of ... | [
-0.362871915102005,
-0.4238748848438263,
-0.04691287875175476,
0.30837878584861755,
0.1272350251674652,
0.2346739023923874,
0.17101484537124634,
0.37074342370033264,
-0.04600534215569496,
0.3754509687423706,
0.03735940903425217,
0.24077291786670685,
-0.31069350242614746,
0.5867729187011719... |
https://github.com/huggingface/datasets/issues/1781 | Hi ! I'm not able to reproduce the issue. Can you try restarting your runtime ?
The PyExtensionType is available in pyarrow starting 0.17.1 iirc. If restarting your runtime doesn't fix this, can you try updating pyarrow ?
```
pip install pyarrow --upgrade
``` | AttributeError: module 'pyarrow' has no attribute 'PyExtensionType' during import | I'm using Colab. And suddenly this morning, there is this error. Have a look below!
| 44 | AttributeError: module 'pyarrow' has no attribute 'PyExtensionType' during import
I'm using Colab. And suddenly this morning, there is this error. Have a look below!
| 46 | AttributeError: module 'pyarrow' has no attribute 'PyExtensionType' during import
I'm using Colab. And suddenly this morning, there is this error. Have a look below!
.
Also now the colab runtime refresh the pyarrow version automatically after the update from pip (previously you needed to restart your runtime).
I guess wha... | AttributeError: module 'pyarrow' has no attribute 'PyExtensionType' during import | I'm using Colab. And suddenly this morning, there is this error. Have a look below!
| 72 | AttributeError: module 'pyarrow' has no attribute 'PyExtensionType' during import
I'm using Colab. And suddenly this morning, there is this error. Have a look below!
| 22 | AttributeError: module 'pyarrow' has no attribute 'PyExtensionType' during import
I'm using Colab. And suddenly this morning, there is this error. Have a look below!
? | [Question & Bug Report] Can we preprocess a dataset on the fly? | I know we can use `Datasets.map` to preprocess a dataset, but I'm using it with very large corpus which generates huge cache file (several TB cache from a 400 GB text file). I have no disk large enough to save it. Can we preprocess a dataset on the fly without generating cache?
BTW, I tried raising `writer_batch_si... | 18 | [Question & Bug Report] Can we preprocess a dataset on the fly?
I know we can use `Datasets.map` to preprocess a dataset, but I'm using it with very large corpus which generates huge cache file (several TB cache from a 400 GB text file). I have no disk large enough to save it. Can we preprocess a dataset on the fly ... | [
-0.39039647579193115,
-0.19714805483818054,
-0.07739086449146271,
-0.003824125975370407,
0.3977739214897156,
0.3356426954269409,
0.2610037326812744,
0.2968968152999878,
-0.08464117348194122,
0.13276726007461548,
0.06934817880392075,
0.12865349650382996,
-0.13560129702091217,
0.228865534067... |
https://github.com/huggingface/datasets/issues/1776 | It's a text file with many lines (about 1B) of Chinese sentences. I use it to train language model using https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm_wwm.py | [Question & Bug Report] Can we preprocess a dataset on the fly? | I know we can use `Datasets.map` to preprocess a dataset, but I'm using it with very large corpus which generates huge cache file (several TB cache from a 400 GB text file). I have no disk large enough to save it. Can we preprocess a dataset on the fly without generating cache?
BTW, I tried raising `writer_batch_si... | 21 | [Question & Bug Report] Can we preprocess a dataset on the fly?
I know we can use `Datasets.map` to preprocess a dataset, but I'm using it with very large corpus which generates huge cache file (several TB cache from a 400 GB text file). I have no disk large enough to save it. Can we preprocess a dataset on the fly ... | [
-0.37494993209838867,
-0.3105447590351105,
-0.02535618655383587,
0.07814666628837585,
0.41907650232315063,
0.3276046812534332,
0.2523878514766693,
0.24938946962356567,
-0.11202418804168701,
0.06025981903076172,
-0.042174097150564194,
0.08074943721294403,
-0.1185981035232544,
0.167781472206... |
https://github.com/huggingface/datasets/issues/1776 | Indeed I will submit a PR in a fez days to enable processing on-the-fly :)
This can be useful in language modeling for tokenization, padding etc.
| [Question & Bug Report] Can we preprocess a dataset on the fly? | I know we can use `Datasets.map` to preprocess a dataset, but I'm using it with very large corpus which generates huge cache file (several TB cache from a 400 GB text file). I have no disk large enough to save it. Can we preprocess a dataset on the fly without generating cache?
BTW, I tried raising `writer_batch_si... | 26 | [Question & Bug Report] Can we preprocess a dataset on the fly?
I know we can use `Datasets.map` to preprocess a dataset, but I'm using it with very large corpus which generates huge cache file (several TB cache from a 400 GB text file). I have no disk large enough to save it. Can we preprocess a dataset on the fly ... | [
-0.3806301951408386,
-0.196968212723732,
-0.0746241956949234,
-0.0068639107048511505,
0.40077751874923706,
0.3399394750595093,
0.2778782844543457,
0.26342710852622986,
-0.09953583776950836,
0.14619982242584229,
0.13427726924419403,
0.18493780493736267,
-0.14211782813072205,
0.2875472009181... |
https://github.com/huggingface/datasets/issues/1776 | Hi @acul3,
Please look at the discussion on a related Issue #1825. I think using `set_transform` after building from source should do. | [Question & Bug Report] Can we preprocess a dataset on the fly? | I know we can use `Datasets.map` to preprocess a dataset, but I'm using it with very large corpus which generates huge cache file (several TB cache from a 400 GB text file). I have no disk large enough to save it. Can we preprocess a dataset on the fly without generating cache?
BTW, I tried raising `writer_batch_si... | 22 | [Question & Bug Report] Can we preprocess a dataset on the fly?
I know we can use `Datasets.map` to preprocess a dataset, but I'm using it with very large corpus which generates huge cache file (several TB cache from a 400 GB text file). I have no disk large enough to save it. Can we preprocess a dataset on the fly ... | [
-0.4329625368118286,
-0.14976264536380768,
-0.021089915186166763,
0.011729542165994644,
0.48501795530319214,
0.27308791875839233,
0.3065052628517151,
0.2762749493122101,
-0.17471271753311157,
0.10266131162643433,
0.09820536524057388,
0.19635455310344696,
-0.08684192597866058,
0.24604503810... |
https://github.com/huggingface/datasets/issues/1775 | It seems that selecting a subset of colums directly from the dataset, i.e., dataset["column"], is slow. | Efficient ways to iterate the dataset | For a large dataset that does not fits the memory, how can I select only a subset of features from each example?
If I iterate over the dataset and then select the subset of features one by one, the resulted memory usage will be huge. Any ways to solve this?
Thanks | 16 | Efficient ways to iterate the dataset
For a large dataset that does not fits the memory, how can I select only a subset of features from each example?
If I iterate over the dataset and then select the subset of features one by one, the resulted memory usage will be huge. Any ways to solve this?
Thanks
It seem... | [
-0.27262118458747864,
-0.3842427134513855,
-0.09381940960884094,
0.3328416347503662,
-0.06488355994224548,
0.06871724873781204,
-0.08692649006843567,
0.2765878736972809,
0.15681496262550354,
0.18535180389881134,
0.10415720194578171,
0.09687267988920212,
0.07577332854270935,
0.1713013052940... |
https://github.com/huggingface/datasets/issues/1774 | Hi ! Thanks for reporting.
I am working on changes in the way data are sliced from arrow. I can probably fix your issue with the changes I'm doing.
If you have some code to reproduce the issue it would be nice so I can make sure that this case will be supported :)
I'll make a PR in a few days | is it possible to make slice to be more compatible like python list and numpy? | Hi,
see below error:
```
AssertionError: Requested slice [:10000000000000000] incompatible with 20 examples.
``` | 62 | is it possible to make slice to be more compatible like python list and numpy?
Hi,
see below error:
```
AssertionError: Requested slice [:10000000000000000] incompatible with 20 examples.
```
Hi ! Thanks for reporting.
I am working on changes in the way data are sliced from arrow. I can probably fix your issue... | [
0.004519253969192505,
-0.06874559074640274,
-0.24153316020965576,
0.0569712370634079,
0.4289461672306061,
-0.3012438416481018,
0.126703143119812,
0.3713269829750061,
-0.13171713054180145,
0.4324043393135071,
-0.014954861253499985,
0.7657302618026733,
-0.07993336021900177,
0.285709917545318... |
https://github.com/huggingface/datasets/issues/1773 | Looks like an issue with your csv file. Did you use the right delimiter ?
Apparently at line 37 the CSV reader from pandas reads 2 fields instead of 1. | bug in loading datasets | Hi,
I need to load a dataset, I use these commands:
```
from datasets import load_dataset
dataset = load_dataset('csv', data_files={'train': 'sick/train.csv',
'test': 'sick/test.csv',
'validation': 'sick/validation.csv'})
prin... | 30 | bug in loading datasets
Hi,
I need to load a dataset, I use these commands:
```
from datasets import load_dataset
dataset = load_dataset('csv', data_files={'train': 'sick/train.csv',
'test': 'sick/test.csv',
'validation': 's... | [
-0.2842666506767273,
-0.2714766263961792,
-0.14631566405296326,
0.46084830164909363,
0.3019689917564392,
0.2408371865749359,
0.08345673978328705,
0.5121127367019653,
0.07644975185394287,
0.05858132615685463,
-0.0004539676010608673,
-0.2665967047214508,
-0.10810254514217377,
0.2536355853080... |
https://github.com/huggingface/datasets/issues/1773 | Note that you can pass any argument you would pass to `pandas.read_csv` as kwargs to `load_dataset`. For example you can do
```python
from datasets import load_dataset
dataset = load_dataset('csv', data_files=data_files, sep="\t")
```
for example to use a tab separator.
You can see the full list of arguments ... | bug in loading datasets | Hi,
I need to load a dataset, I use these commands:
```
from datasets import load_dataset
dataset = load_dataset('csv', data_files={'train': 'sick/train.csv',
'test': 'sick/test.csv',
'validation': 'sick/validation.csv'})
prin... | 64 | bug in loading datasets
Hi,
I need to load a dataset, I use these commands:
```
from datasets import load_dataset
dataset = load_dataset('csv', data_files={'train': 'sick/train.csv',
'test': 'sick/test.csv',
'validation': 's... | [
-0.2842666506767273,
-0.2714766263961792,
-0.14631566405296326,
0.46084830164909363,
0.3019689917564392,
0.2408371865749359,
0.08345673978328705,
0.5121127367019653,
0.07644975185394287,
0.05858132615685463,
-0.0004539676010608673,
-0.2665967047214508,
-0.10810254514217377,
0.2536355853080... |
https://github.com/huggingface/datasets/issues/1771 | Indeed in 1.2.1 the script to process csv file is downloaded. Starting from the next release though we include the csv processing directly in the library.
See PR #1726
We'll do a new release soon :) | Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.1/datasets/csv/csv.py | Hi,
When I load_dataset from local csv files, below error happened, looks raw.githubusercontent.com was blocked by the chinese government. But why it need to download csv.py? should it include when pip install the dataset?
```
Traceback (most recent call last):
File "/home/tom/pyenv/pystory/lib/python3.6/site-p... | 36 | Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.1/datasets/csv/csv.py
Hi,
When I load_dataset from local csv files, below error happened, looks raw.githubusercontent.com was blocked by the chinese government. But why it need to download csv.py? should it include when pip install the dataset... | [
-0.09555321931838989,
-0.2019757479429245,
-0.1823531985282898,
0.09957481920719147,
0.19236546754837036,
-0.011418059468269348,
0.28100278973579407,
0.18599048256874084,
0.2537333071231842,
0.2542535960674286,
0.08921867609024048,
-0.19674775004386902,
0.23854665458202362,
0.0940236672759... |
https://github.com/huggingface/datasets/issues/1770 | Hi ! Currently we don't have a way to `zip` datasets but we plan to add this soon :)
For now you'll need to use `map` to add the fields from one dataset to the other. See the comment here for more info : https://github.com/huggingface/datasets/issues/853#issuecomment-727872188 | how can I combine 2 dataset with different/same features? | to combine 2 dataset by one-one map like ds = zip(ds1, ds2):
ds1: {'text'}, ds2: {'text'}, combine ds:{'src', 'tgt'}
or different feature:
ds1: {'src'}, ds2: {'tgt'}, combine ds:{'src', 'tgt'} | 45 | how can I combine 2 dataset with different/same features?
to combine 2 dataset by one-one map like ds = zip(ds1, ds2):
ds1: {'text'}, ds2: {'text'}, combine ds:{'src', 'tgt'}
or different feature:
ds1: {'src'}, ds2: {'tgt'}, combine ds:{'src', 'tgt'}
Hi ! Currently we don't have a way to `zip` datasets but we p... | [
-0.3618091642856598,
-0.49644747376441956,
-0.06872190535068512,
0.12175968289375305,
0.06972834467887878,
0.3581109046936035,
-0.09224564582109451,
0.22106251120567322,
-0.03528471663594246,
0.01387014240026474,
-0.32467448711395264,
0.40964922308921814,
0.06939108669757843,
0.73989146947... |
https://github.com/huggingface/datasets/issues/1770 | Good to hear.
Currently I did not use map , just fetch src and tgt from the 2 dataset and merge them.
It will be a release if you can deal with it at the backend.
Thanks. | how can I combine 2 dataset with different/same features? | to combine 2 dataset by one-one map like ds = zip(ds1, ds2):
ds1: {'text'}, ds2: {'text'}, combine ds:{'src', 'tgt'}
or different feature:
ds1: {'src'}, ds2: {'tgt'}, combine ds:{'src', 'tgt'} | 37 | how can I combine 2 dataset with different/same features?
to combine 2 dataset by one-one map like ds = zip(ds1, ds2):
ds1: {'text'}, ds2: {'text'}, combine ds:{'src', 'tgt'}
or different feature:
ds1: {'src'}, ds2: {'tgt'}, combine ds:{'src', 'tgt'}
Good to hear.
Currently I did not use map , just fetch src a... | [
-0.3885655999183655,
-0.49409496784210205,
-0.14069348573684692,
0.018540311604738235,
-0.022465519607067108,
0.2798510193824768,
-0.17467927932739258,
0.3226885199546814,
-0.051088400185108185,
0.00889318436384201,
-0.19251945614814758,
0.6096799969673157,
0.09996669739484787,
0.546512544... |
https://github.com/huggingface/datasets/issues/1770 | Hi! You can rename the columns and concatenate the datasets along `axis=1` to get the desired result as follows:
```python
ds1 = ds1.rename_column("text", "src")
ds2 = ds2.rename_column("text", "tgt")
ds = datasets.concatenate_datasets(["ds1", "ds2"], axis=1)
``` | how can I combine 2 dataset with different/same features? | to combine 2 dataset by one-one map like ds = zip(ds1, ds2):
ds1: {'text'}, ds2: {'text'}, combine ds:{'src', 'tgt'}
or different feature:
ds1: {'src'}, ds2: {'tgt'}, combine ds:{'src', 'tgt'} | 34 | how can I combine 2 dataset with different/same features?
to combine 2 dataset by one-one map like ds = zip(ds1, ds2):
ds1: {'text'}, ds2: {'text'}, combine ds:{'src', 'tgt'}
or different feature:
ds1: {'src'}, ds2: {'tgt'}, combine ds:{'src', 'tgt'}
Hi! You can rename the columns and concatenate the datasets a... | [
-0.24798810482025146,
-0.36750876903533936,
-0.07628364861011505,
0.053400926291942596,
0.1394849568605423,
0.43359237909317017,
0.14354324340820312,
0.2733105421066284,
-0.058588657528162,
0.00196877121925354,
-0.28868067264556885,
0.5887386798858643,
0.051432184875011444,
0.6056704521179... |
https://github.com/huggingface/datasets/issues/1769 | Hi ! What version of python and datasets do you have ? And also what version of dill and pickle ? | _pickle.PicklingError: Can't pickle typing.Union[str, NoneType]: it's not the same object as typing.Union when calling datasets.map with num_proc=2 | It may be a bug of multiprocessing with Datasets, when I disable the multiprocessing by set num_proc to None, everything works fine.
The script I use is https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm_wwm.py
Script args:
```
--model_name_or_path
../../../model/chine... | 21 | _pickle.PicklingError: Can't pickle typing.Union[str, NoneType]: it's not the same object as typing.Union when calling datasets.map with num_proc=2
It may be a bug of multiprocessing with Datasets, when I disable the multiprocessing by set num_proc to None, everything works fine.
The script I use is https://github... | [
-0.2903599143028259,
-0.29742884635925293,
0.11324459314346313,
0.19037097692489624,
0.16615881025791168,
-0.05221021920442581,
0.332113653421402,
0.23036344349384308,
0.299395889043808,
0.280150830745697,
0.016717076301574707,
0.3376862406730652,
-0.11104443669319153,
0.21741409599781036,... |
https://github.com/huggingface/datasets/issues/1769 | > Hi ! What version of python and datasets do you have ? And also what version of dill and pickle ?
python==3.6.10
datasets==1.2.1
dill==0.3.2
pickle.format_version==4.0 | _pickle.PicklingError: Can't pickle typing.Union[str, NoneType]: it's not the same object as typing.Union when calling datasets.map with num_proc=2 | It may be a bug of multiprocessing with Datasets, when I disable the multiprocessing by set num_proc to None, everything works fine.
The script I use is https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm_wwm.py
Script args:
```
--model_name_or_path
../../../model/chine... | 26 | _pickle.PicklingError: Can't pickle typing.Union[str, NoneType]: it's not the same object as typing.Union when calling datasets.map with num_proc=2
It may be a bug of multiprocessing with Datasets, when I disable the multiprocessing by set num_proc to None, everything works fine.
The script I use is https://github... | [
-0.2903599143028259,
-0.29742884635925293,
0.11324459314346313,
0.19037097692489624,
0.16615881025791168,
-0.05221021920442581,
0.332113653421402,
0.23036344349384308,
0.299395889043808,
0.280150830745697,
0.016717076301574707,
0.3376862406730652,
-0.11104443669319153,
0.21741409599781036,... |
https://github.com/huggingface/datasets/issues/1769 | Multiprocessing in python require all the functions to be picklable. More specifically, functions need to be picklable with `dill`.
However objects like `typing.Union[str, NoneType]` are not picklable in python <3.7.
Can you try to update your python version to python>=3.7 ?
| _pickle.PicklingError: Can't pickle typing.Union[str, NoneType]: it's not the same object as typing.Union when calling datasets.map with num_proc=2 | It may be a bug of multiprocessing with Datasets, when I disable the multiprocessing by set num_proc to None, everything works fine.
The script I use is https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm_wwm.py
Script args:
```
--model_name_or_path
../../../model/chine... | 41 | _pickle.PicklingError: Can't pickle typing.Union[str, NoneType]: it's not the same object as typing.Union when calling datasets.map with num_proc=2
It may be a bug of multiprocessing with Datasets, when I disable the multiprocessing by set num_proc to None, everything works fine.
The script I use is https://github... | [
-0.2903599143028259,
-0.29742884635925293,
0.11324459314346313,
0.19037097692489624,
0.16615881025791168,
-0.05221021920442581,
0.332113653421402,
0.23036344349384308,
0.299395889043808,
0.280150830745697,
0.016717076301574707,
0.3376862406730652,
-0.11104443669319153,
0.21741409599781036,... |
https://github.com/huggingface/datasets/issues/1766 | Hi ! To avoid collisions you can specify a `experiment_id` when instantiating your metric using `load_metric`. It will replace "default_experiment" with the experiment id that you provide in the arrow filename.
Also when two `experiment_id` collide we're supposed to detect it using our locking mechanism. Not sure w... | Issues when run two programs compute the same metrics | I got the following error when running two different programs that both compute sacreblue metrics. It seems that both read/and/write to the same location (.cache/huggingface/metrics/sacrebleu/default/default_experiment-1-0.arrow) where it caches the batches:
```
File "train_matching_min.py", line 160, in <module>ch... | 69 | Issues when run two programs compute the same metrics
I got the following error when running two different programs that both compute sacreblue metrics. It seems that both read/and/write to the same location (.cache/huggingface/metrics/sacrebleu/default/default_experiment-1-0.arrow) where it caches the batches:
``... | [
-0.36117398738861084,
-0.1505342572927475,
-0.043187644332647324,
0.3872225284576416,
0.2670593857765198,
-0.10684049874544144,
0.08155118674039841,
0.30455482006073,
-0.14090171456336975,
0.21661502122879028,
-0.37607645988464355,
-0.013459578156471252,
0.08526716381311417,
0.005195192992... |
https://github.com/huggingface/datasets/issues/1766 | Thank you for your response. I fixed the issue by set "keep_in_memory=True" when load_metric.
I cannot share the entire source code but below is the wrapper I wrote:
```python
class Evaluation:
def __init__(self, metric='sacrebleu'):
# self.metric = load_metric(metric, keep_in_memory=True)
... | Issues when run two programs compute the same metrics | I got the following error when running two different programs that both compute sacreblue metrics. It seems that both read/and/write to the same location (.cache/huggingface/metrics/sacrebleu/default/default_experiment-1-0.arrow) where it caches the batches:
```
File "train_matching_min.py", line 160, in <module>ch... | 94 | Issues when run two programs compute the same metrics
I got the following error when running two different programs that both compute sacreblue metrics. It seems that both read/and/write to the same location (.cache/huggingface/metrics/sacrebleu/default/default_experiment-1-0.arrow) where it caches the batches:
``... | [
-0.36117398738861084,
-0.1505342572927475,
-0.043187644332647324,
0.3872225284576416,
0.2670593857765198,
-0.10684049874544144,
0.08155118674039841,
0.30455482006073,
-0.14090171456336975,
0.21661502122879028,
-0.37607645988464355,
-0.013459578156471252,
0.08526716381311417,
0.005195192992... |
https://github.com/huggingface/datasets/issues/1765 | Instead of:
```python
dataloader = torch.utils.data.DataLoader(encoded_dataset, batch_sampler=32)
```
It should be:
```python
dataloader = torch.utils.data.DataLoader(encoded_dataset, batch_size=32)
```
`batch_sampler` accepts a Sampler object or an Iterable, so you get an error. | Error iterating over Dataset with DataLoader | I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tensor([[ 101, 178, 1198, 1400, 1714, 22233, 2... | 30 | Error iterating over Dataset with DataLoader
I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tenso... | [
-0.23792923986911774,
0.05545620620250702,
-0.04567085579037666,
0.20573335886001587,
0.15317991375923157,
0.00014128535985946655,
0.7921317219734192,
0.3068523705005646,
0.02113104611635208,
0.15271268784999847,
0.04679575562477112,
0.23042592406272888,
-0.2809545397758484,
-0.24164384603... |
https://github.com/huggingface/datasets/issues/1765 | @mariosasko I thought that would fix it, but now I'm getting a different error:
```
/usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py:851: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly no... | Error iterating over Dataset with DataLoader | I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tensor([[ 101, 178, 1198, 1400, 1714, 22233, 2... | 169 | Error iterating over Dataset with DataLoader
I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tenso... | [
-0.23792923986911774,
0.05545620620250702,
-0.04567085579037666,
0.20573335886001587,
0.15317991375923157,
0.00014128535985946655,
0.7921317219734192,
0.3068523705005646,
0.02113104611635208,
0.15271268784999847,
0.04679575562477112,
0.23042592406272888,
-0.2809545397758484,
-0.24164384603... |
https://github.com/huggingface/datasets/issues/1765 | Yes, padding is an answer.
This can be solved easily by passing a callable to the collate_fn arg of DataLoader that adds padding. | Error iterating over Dataset with DataLoader | I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tensor([[ 101, 178, 1198, 1400, 1714, 22233, 2... | 23 | Error iterating over Dataset with DataLoader
I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tenso... | [
-0.23792923986911774,
0.05545620620250702,
-0.04567085579037666,
0.20573335886001587,
0.15317991375923157,
0.00014128535985946655,
0.7921317219734192,
0.3068523705005646,
0.02113104611635208,
0.15271268784999847,
0.04679575562477112,
0.23042592406272888,
-0.2809545397758484,
-0.24164384603... |
https://github.com/huggingface/datasets/issues/1765 | dataloader = torch.utils.data.DataLoader(encoded_dataset, batch_size=4)
batch = next(iter(dataloader))
getting
ValueError: cannot reshape array of size 8192 into shape (1,512,4)
I had put padding as 2048 for encoded_dataset
kindly help | Error iterating over Dataset with DataLoader | I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tensor([[ 101, 178, 1198, 1400, 1714, 22233, 2... | 28 | Error iterating over Dataset with DataLoader
I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tenso... | [
-0.23792923986911774,
0.05545620620250702,
-0.04567085579037666,
0.20573335886001587,
0.15317991375923157,
0.00014128535985946655,
0.7921317219734192,
0.3068523705005646,
0.02113104611635208,
0.15271268784999847,
0.04679575562477112,
0.23042592406272888,
-0.2809545397758484,
-0.24164384603... |
https://github.com/huggingface/datasets/issues/1765 | data_loader_val = torch.utils.data.DataLoader(val_dataset, batch_size=32, shuffle=True, drop_last=False, num_workers=0)
dataiter = iter(data_loader_val)
images, _ = next(dataiter)
getting -> TypeError: 'list' object is not callable
Cannot iterate through the data. Kindly suggest. | Error iterating over Dataset with DataLoader | I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tensor([[ 101, 178, 1198, 1400, 1714, 22233, 2... | 29 | Error iterating over Dataset with DataLoader
I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tenso... | [
-0.23792923986911774,
0.05545620620250702,
-0.04567085579037666,
0.20573335886001587,
0.15317991375923157,
0.00014128535985946655,
0.7921317219734192,
0.3068523705005646,
0.02113104611635208,
0.15271268784999847,
0.04679575562477112,
0.23042592406272888,
-0.2809545397758484,
-0.24164384603... |
https://github.com/huggingface/datasets/issues/1762 | Hi ! You can get CUDA tensors with
```python
dataset.set_format("torch", columns=columns, device="cuda")
```
Indeed `set_format` passes the `**kwargs` to `torch.tensor` | Unable to format dataset to CUDA Tensors | Hi,
I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.
I tried this, but Dataset doesn't suppor... | 20 | Unable to format dataset to CUDA Tensors
Hi,
I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.
... | [
-0.22562196850776672,
-0.44279399514198303,
-0.07967899739742279,
0.18397201597690582,
0.5433498620986938,
0.388572633266449,
0.5336815714836121,
0.3345809578895569,
-0.009671077132225037,
0.14275792241096497,
-0.08334511518478394,
0.24232380092144012,
-0.2235851138830185,
0.09736358374357... |
https://github.com/huggingface/datasets/issues/1762 | Hi @lhoestq,
Thanks a lot. Is this true for all format types?
As in, for 'torch', I can have `**kwargs` to `torch.tensor` and for 'tf' those args are passed to `tf.Tensor`, and the same for 'numpy' and 'pandas'? | Unable to format dataset to CUDA Tensors | Hi,
I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.
I tried this, but Dataset doesn't suppor... | 38 | Unable to format dataset to CUDA Tensors
Hi,
I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.
... | [
-0.19142469763755798,
-0.49535396695137024,
-0.06351520866155624,
0.14305107295513153,
0.5737582445144653,
0.3578239679336548,
0.6109964847564697,
0.37510183453559875,
-0.006469152867794037,
0.09331344813108444,
-0.18430906534194946,
0.23856405913829803,
-0.18889376521110535,
0.20827412605... |
https://github.com/huggingface/datasets/issues/1762 | Yes the keywords arguments are passed to the convert function like `np.array`, `torch.tensor` or `tensorflow.ragged.constant`.
We don't support the kwargs for pandas on the other hand. | Unable to format dataset to CUDA Tensors | Hi,
I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.
I tried this, but Dataset doesn't suppor... | 26 | Unable to format dataset to CUDA Tensors
Hi,
I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.
... | [
-0.23399686813354492,
-0.4713834226131439,
-0.05872572585940361,
0.1454276740550995,
0.5945419669151306,
0.38140007853507996,
0.5536247491836548,
0.34862279891967773,
0.020402178168296814,
0.08473792672157288,
-0.1387399435043335,
0.34072190523147583,
-0.17577965557575226,
0.14769113063812... |
https://github.com/huggingface/datasets/issues/1762 | Thanks @lhoestq,
Would it be okay if I added this to the docs and made a PR? | Unable to format dataset to CUDA Tensors | Hi,
I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.
I tried this, but Dataset doesn't suppor... | 17 | Unable to format dataset to CUDA Tensors
Hi,
I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.
... | [
-0.20760861039161682,
-0.44932761788368225,
-0.08087827265262604,
0.14295923709869385,
0.5672459006309509,
0.3796422779560089,
0.5310694575309753,
0.33096617460250854,
-0.01816534250974655,
0.14095787703990936,
-0.07886835932731628,
0.2365306317806244,
-0.22309881448745728,
0.1325979530811... |
https://github.com/huggingface/datasets/issues/1759 | Hi !
From what pickle file fo you get this ?
I guess you mean the dataset loaded using `load_dataset` ? | wikipedia dataset incomplete | Hey guys,
I am using the https://github.com/huggingface/datasets/tree/master/datasets/wikipedia dataset.
Unfortunately, I found out that there is an incompleteness for the German dataset.
For reasons unknown to me, the number of inhabitants has been removed from many pages:
Thorey-sur-Ouche has 128 inhabitants a... | 21 | wikipedia dataset incomplete
Hey guys,
I am using the https://github.com/huggingface/datasets/tree/master/datasets/wikipedia dataset.
Unfortunately, I found out that there is an incompleteness for the German dataset.
For reasons unknown to me, the number of inhabitants has been removed from many pages:
Thorey-... | [
0.12411230057477951,
0.09065628051757812,
-0.06485240906476974,
0.439008504152298,
-0.14518509805202484,
0.13518105447292328,
0.14004500210285187,
-0.09932897984981537,
0.33159226179122925,
0.1742718517780304,
0.18785691261291504,
-0.05558618903160095,
0.3833341896533966,
-0.37142890691757... |
https://github.com/huggingface/datasets/issues/1759 | yes sorry, I used the `load_dataset`function and saved the data to a pickle file so I don't always have to reload it and are able to work offline. | wikipedia dataset incomplete | Hey guys,
I am using the https://github.com/huggingface/datasets/tree/master/datasets/wikipedia dataset.
Unfortunately, I found out that there is an incompleteness for the German dataset.
For reasons unknown to me, the number of inhabitants has been removed from many pages:
Thorey-sur-Ouche has 128 inhabitants a... | 28 | wikipedia dataset incomplete
Hey guys,
I am using the https://github.com/huggingface/datasets/tree/master/datasets/wikipedia dataset.
Unfortunately, I found out that there is an incompleteness for the German dataset.
For reasons unknown to me, the number of inhabitants has been removed from many pages:
Thorey-... | [
0.06431587040424347,
0.08949476480484009,
-0.059721238911151886,
0.44190940260887146,
-0.1323367953300476,
0.10839974135160446,
0.1577170491218567,
-0.12213249504566193,
0.27500733733177185,
0.1589430272579193,
0.17383414506912231,
-0.13584297895431519,
0.40387678146362305,
-0.407072454690... |
https://github.com/huggingface/datasets/issues/1759 | The wikipedia articles are processed using the `mwparserfromhell` library. Even if it works well in most cases, such issues can happen unfortunately. You can find the repo here: https://github.com/earwig/mwparserfromhell
There also exist other datasets based on wikipedia that were processed differently (and are ofte... | wikipedia dataset incomplete | Hey guys,
I am using the https://github.com/huggingface/datasets/tree/master/datasets/wikipedia dataset.
Unfortunately, I found out that there is an incompleteness for the German dataset.
For reasons unknown to me, the number of inhabitants has been removed from many pages:
Thorey-sur-Ouche has 128 inhabitants a... | 48 | wikipedia dataset incomplete
Hey guys,
I am using the https://github.com/huggingface/datasets/tree/master/datasets/wikipedia dataset.
Unfortunately, I found out that there is an incompleteness for the German dataset.
For reasons unknown to me, the number of inhabitants has been removed from many pages:
Thorey-... | [
0.14578306674957275,
0.16513071954250336,
-0.06042158603668213,
0.4512959420681,
-0.17796377837657928,
0.14228938519954681,
0.13256841897964478,
-0.05997845157980919,
0.22113293409347534,
0.13739435374736786,
0.1483725756406784,
-0.06448652595281601,
0.4038360118865967,
-0.4707549512386322... |
https://github.com/huggingface/datasets/issues/1758 | Hi !
I tried your code on my side and I was able to workaround this issue by waiting a few seconds before querying the index.
Maybe this is because the index is not updated yet on the ElasticSearch side ? | dataset.search() (elastic) cannot reliably retrieve search results | I am trying to use elastic search to retrieve the indices of items in the dataset in their precise order, given shuffled training indices.
The problem I have is that I cannot retrieve reliable results with my data on my first search. I have to run the search **twice** to get the right answer.
I am indexing data t... | 41 | dataset.search() (elastic) cannot reliably retrieve search results
I am trying to use elastic search to retrieve the indices of items in the dataset in their precise order, given shuffled training indices.
The problem I have is that I cannot retrieve reliable results with my data on my first search. I have to run ... | [
0.2319183200597763,
-0.018109649419784546,
-0.12120530754327774,
0.16620609164237976,
0.1539812535047531,
-0.3275492489337921,
-0.124026820063591,
0.11519446223974228,
-0.25622543692588806,
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-0.09199905395507812,
-0.01856211945414543,
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-0.550327062... |
https://github.com/huggingface/datasets/issues/1758 | Thanks for the feedback! I added a 30 second "sleep" and that seemed to work well! | dataset.search() (elastic) cannot reliably retrieve search results | I am trying to use elastic search to retrieve the indices of items in the dataset in their precise order, given shuffled training indices.
The problem I have is that I cannot retrieve reliable results with my data on my first search. I have to run the search **twice** to get the right answer.
I am indexing data t... | 16 | dataset.search() (elastic) cannot reliably retrieve search results
I am trying to use elastic search to retrieve the indices of items in the dataset in their precise order, given shuffled training indices.
The problem I have is that I cannot retrieve reliable results with my data on my first search. I have to run ... | [
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https://github.com/huggingface/datasets/issues/1757 | @dspoka Please check the following link : https://github.com/thunlp/FewRel
This link mentions two versions of the datasets. Also, this one seems to be the official link.
I am assuming this is the correct link and implementing based on the same. | FewRel | ## Adding a Dataset
- **Name:** FewRel
- **Description:** Large-Scale Supervised Few-Shot Relation Classification Dataset
- **Paper:** @inproceedings{han2018fewrel,
title={FewRel:A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation},
auth... | 39 | FewRel
## Adding a Dataset
- **Name:** FewRel
- **Description:** Large-Scale Supervised Few-Shot Relation Classification Dataset
- **Paper:** @inproceedings{han2018fewrel,
title={FewRel:A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation},
... | [
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https://github.com/huggingface/datasets/issues/1755 | Thanks for the input! I gave that a try by adding this after my selection / reordering operations, but before the big computation task of `score_squad`
```
examples = examples.flatten_indices()
features = features.flatten_indices()
```
That helped quite a bit! | Using select/reordering datasets slows operations down immensely | I am using portions of HF's helpful work in preparing / scoring the SQuAD 2.0 data. The problem I have is that after using `select` to re-ordering the dataset, computations slow down immensely where the total scoring process on 131k training examples would take maybe 3 minutes, now take over an hour.
The below examp... | 39 | Using select/reordering datasets slows operations down immensely
I am using portions of HF's helpful work in preparing / scoring the SQuAD 2.0 data. The problem I have is that after using `select` to re-ordering the dataset, computations slow down immensely where the total scoring process on 131k training examples wo... | [
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https://github.com/huggingface/datasets/issues/1747 | Hi :)
The slicing API from https://huggingface.co/docs/datasets/splits.html doesn't shuffle the data.
You can shuffle and then take a subset of your dataset with
```python
# shuffle and take the first 100 examples
dataset = dataset.shuffle(seed=42).select(range(100))
```
You can find more information about sh... | datasets slicing with seed | Hi
I need to slice a dataset with random seed, I looked into documentation here https://huggingface.co/docs/datasets/splits.html
I could not find a seed option, could you assist me please how I can get a slice for different seeds?
thank you.
@lhoestq | 50 | datasets slicing with seed
Hi
I need to slice a dataset with random seed, I looked into documentation here https://huggingface.co/docs/datasets/splits.html
I could not find a seed option, could you assist me please how I can get a slice for different seeds?
thank you.
@lhoestq
Hi :)
The slicing API from h... | [
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0.09934696555137634,
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0.73511481285095... |
https://github.com/huggingface/datasets/issues/1747 | thank you so much
On Mon, Jan 18, 2021 at 3:17 PM Quentin Lhoest <notifications@github.com>
wrote:
> Hi :)
> The slicing API doesn't shuffle the data.
> You can shuffle and then take a subset of your dataset with
>
> # shuffle and take the first 100 examplesdataset = dataset.shuffle(seed=42).select(range(100))
>
> Yo... | datasets slicing with seed | Hi
I need to slice a dataset with random seed, I looked into documentation here https://huggingface.co/docs/datasets/splits.html
I could not find a seed option, could you assist me please how I can get a slice for different seeds?
thank you.
@lhoestq | 103 | datasets slicing with seed
Hi
I need to slice a dataset with random seed, I looked into documentation here https://huggingface.co/docs/datasets/splits.html
I could not find a seed option, could you assist me please how I can get a slice for different seeds?
thank you.
@lhoestq
thank you so much
On Mon, Jan... | [
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0.680880069732... |
https://github.com/huggingface/datasets/issues/1745 | From the description given in the dataset script for `wsc.fixed`:
```
This version fixes issues where the spans are not actually substrings of the text.
``` | difference between wsc and wsc.fixed for superglue | Hi
I see two versions of wsc in superglue, and I am not sure what is the differences and which one is the original one. could you help to discuss the differences? thanks @lhoestq | 26 | difference between wsc and wsc.fixed for superglue
Hi
I see two versions of wsc in superglue, and I am not sure what is the differences and which one is the original one. could you help to discuss the differences? thanks @lhoestq
From the description given in the dataset script for `wsc.fixed`:
```
This version... | [
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0.19692444801330566,
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0.10971897840499878,
0.19315862... |
https://github.com/huggingface/datasets/issues/1743 | Currently it's only possible to define the features for the two columns `references` and `predictions`.
The data for these columns can then be passed to `metric.add_batch` and `metric.compute`.
Instead of defining more columns `text`, `offset_mapping` and `ground` you must include them in either references and predic... | Issue while Creating Custom Metric | Hi Team,
I am trying to create a custom metric for my training as follows, where f1 is my own metric:
```python
def _info(self):
# TODO: Specifies the datasets.MetricInfo object
return datasets.MetricInfo(
# This is the description that will appear on the metrics page.
... | 151 | Issue while Creating Custom Metric
Hi Team,
I am trying to create a custom metric for my training as follows, where f1 is my own metric:
```python
def _info(self):
# TODO: Specifies the datasets.MetricInfo object
return datasets.MetricInfo(
# This is the description that will ap... | [
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0.10693050175905228,
0.198286235332489,
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0.2997828722000122,
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0.23833191394805908,
-0.17814356088638306,
0.140640318393... |
https://github.com/huggingface/datasets/issues/1743 | Hi @lhoestq,
I am doing text segmentation and the metric is effectively dice score on character offsets. So I need to pass the actual spans and I want to be able to get the spans based on predictions using offset_mapping.
Including them in references seems like a good idea. I'll try it out and get back to you. If... | Issue while Creating Custom Metric | Hi Team,
I am trying to create a custom metric for my training as follows, where f1 is my own metric:
```python
def _info(self):
# TODO: Specifies the datasets.MetricInfo object
return datasets.MetricInfo(
# This is the description that will appear on the metrics page.
... | 75 | Issue while Creating Custom Metric
Hi Team,
I am trying to create a custom metric for my training as follows, where f1 is my own metric:
```python
def _info(self):
# TODO: Specifies the datasets.MetricInfo object
return datasets.MetricInfo(
# This is the description that will ap... | [
-0.23883530497550964,
-0.30202004313468933,
-0.145783931016922,
0.1864611804485321,
0.41935160756111145,
-0.038418710231781006,
0.10693050175905228,
0.198286235332489,
0.051829420030117035,
0.2997828722000122,
-0.055739909410476685,
0.23833191394805908,
-0.17814356088638306,
0.140640318393... |
https://github.com/huggingface/datasets/issues/1733 | Hello @juliahane, which config of GLUE causes you trouble?
The URLs are defined in the dataset script source code: https://github.com/huggingface/datasets/blob/master/datasets/glue/glue.py | connection issue with glue, what is the data url for glue? | Hi
my codes sometimes fails due to connection issue with glue, could you tell me how I can have the URL datasets library is trying to read GLUE from to test the machines I am working on if there is an issue on my side or not
thanks | 20 | connection issue with glue, what is the data url for glue?
Hi
my codes sometimes fails due to connection issue with glue, could you tell me how I can have the URL datasets library is trying to read GLUE from to test the machines I am working on if there is an issue on my side or not
thanks
Hello @juliahane, whi... | [
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0.011869058012962341,
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0.2993859350681305,
0.30105993151664734,
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0.20354098081588745,
0.08158134669065475,
0.1122899129986763,
0.12633660435676575,
0.06428935378789902,
-0.06481548398733139,
0.2632436156272888,
0.19455525279045... |
https://github.com/huggingface/datasets/issues/1731 | Hi @yangp725,
The SWDA has been added very recently and has not been released yet, thus it is not available in the `1.2.0` version of 🤗`datasets`.
You can still access it by installing the latest version of the library (master branch), by following instructions in [this issue](https://github.com/huggingface/datasets... | Couldn't reach swda.py | ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.0/datasets/swda/swda.py
| 54 | Couldn't reach swda.py
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.0/datasets/swda/swda.py
Hi @yangp725,
The SWDA has been added very recently and has not been released yet, thus it is not available in the `1.2.0` version of 🤗`datasets`.
You can still access it by... | [
-0.23621448874473572,
-0.3874821066856384,
-0.15831847488880157,
-0.004699505865573883,
0.3615033030509949,
-0.02269960194826126,
-0.06851688772439957,
0.22510334849357605,
0.026332512497901917,
0.2184050977230072,
-0.12052067369222641,
-0.007295917719602585,
0.009890798479318619,
0.333948... |
https://github.com/huggingface/datasets/issues/1729 | Hi @ZurMaD!
Thanks for your interest in 🤗 `datasets`. Support for image datasets is at an early stage, with CIFAR-10 added in #1617
MNIST is also on the way: #1730
If you feel like adding another image dataset, I would advise starting by reading the [ADD_NEW_DATASET.md](https://github.com/huggingface/datasets/b... | Is there support for Deep learning datasets? | I looked around this repository and looking the datasets I think that there's no support for images-datasets. Or am I missing something? For example to add a repo like this https://github.com/DZPeru/fish-datasets | 55 | Is there support for Deep learning datasets?
I looked around this repository and looking the datasets I think that there's no support for images-datasets. Or am I missing something? For example to add a repo like this https://github.com/DZPeru/fish-datasets
Hi @ZurMaD!
Thanks for your interest in 🤗 `datasets`. Su... | [
-0.24644456803798676,
-0.07323779165744781,
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-0.09773353487253189,
0.28045958280563354,
0.03026410937309265,
0.22501856088638306,
0.08640428632497787,
0.08424592018127441,
0.24715213477611542,
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0.028118882328271866,
-0.30469053983688354,
0.34195035... |
https://github.com/huggingface/datasets/issues/1728 | Hi @ameet-1997,
I think what you are looking for is the `concatenate_datasets` function: https://huggingface.co/docs/datasets/processing.html?highlight=concatenate#concatenate-several-datasets
For your use case, I would use the [`map` method](https://huggingface.co/docs/datasets/processing.html?highlight=concatenat... | Add an entry to an arrow dataset | Is it possible to add an entry to a dataset object?
**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**
For example, say we have the following code:
``` python
from datasets import load_dataset
# Load a dataset and print the first examples in the training s... | 43 | Add an entry to an arrow dataset
Is it possible to add an entry to a dataset object?
**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**
For example, say we have the following code:
``` python
from datasets import load_dataset
# Load a dataset and print t... | [
0.1183498203754425,
0.12276783585548401,
-0.05486101657152176,
-0.021853938698768616,
0.19739365577697754,
0.3098829984664917,
0.17081791162490845,
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0.26461178064346313,
0.5609716176986694,
-0.20104458928108215,
0.0916973873972... |
https://github.com/huggingface/datasets/issues/1728 | That's a great idea! Thank you so much!
When I try that solution, I get the following error when I try to concatenate `datasets` and `modified_dataset`. I have also attached the output I get when I print out those two variables. Am I missing something?
Code:
``` python
combined_dataset = concatenate_datasets([d... | Add an entry to an arrow dataset | Is it possible to add an entry to a dataset object?
**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**
For example, say we have the following code:
``` python
from datasets import load_dataset
# Load a dataset and print the first examples in the training s... | 123 | Add an entry to an arrow dataset
Is it possible to add an entry to a dataset object?
**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**
For example, say we have the following code:
``` python
from datasets import load_dataset
# Load a dataset and print t... | [
0.09493996202945709,
0.27810633182525635,
-0.039204180240631104,
0.023057326674461365,
0.24360966682434082,
0.3778875470161438,
0.28039854764938354,
-0.15852811932563782,
-0.2577435374259949,
-0.07451803982257843,
0.3132963478565216,
0.5345354080200195,
-0.15967896580696106,
0.000742249190... |
https://github.com/huggingface/datasets/issues/1728 | You should do `combined_dataset = concatenate_datasets([datasets['train'], modified_dataset['train']])`
Didn't we talk about returning a Dataset instead of a DatasetDict with load_dataset and no split provided @lhoestq? Not sure it's the way to go but I'm wondering if it's not simpler for some use-cases. | Add an entry to an arrow dataset | Is it possible to add an entry to a dataset object?
**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**
For example, say we have the following code:
``` python
from datasets import load_dataset
# Load a dataset and print the first examples in the training s... | 42 | Add an entry to an arrow dataset
Is it possible to add an entry to a dataset object?
**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**
For example, say we have the following code:
``` python
from datasets import load_dataset
# Load a dataset and print t... | [
0.11457251757383347,
0.22762224078178406,
-0.06840571016073227,
-0.025123603641986847,
0.15373197197914124,
0.2710112929344177,
0.22679883241653442,
-0.10380686074495316,
0.01638675481081009,
-0.05275929719209671,
0.30326300859451294,
0.5584481954574585,
-0.2891288101673126,
0.047076150774... |
https://github.com/huggingface/datasets/issues/1728 | > Didn't we talk about returning a Dataset instead of a DatasetDict with load_dataset and no split provided @lhoestq? Not sure it's the way to go but I'm wondering if it's not simpler for some use-cases.
My opinion is that users should always know in advance what type of objects they're going to get. Otherwise the d... | Add an entry to an arrow dataset | Is it possible to add an entry to a dataset object?
**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**
For example, say we have the following code:
``` python
from datasets import load_dataset
# Load a dataset and print the first examples in the training s... | 96 | Add an entry to an arrow dataset
Is it possible to add an entry to a dataset object?
**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**
For example, say we have the following code:
``` python
from datasets import load_dataset
# Load a dataset and print t... | [
0.14892315864562988,
0.20325042307376862,
-0.05366974323987961,
0.00512422900646925,
0.1111600399017334,
0.07312706112861633,
0.273730993270874,
-0.08799425512552261,
0.0876799151301384,
0.021720994263887405,
0.34230026602745056,
0.4724983274936676,
-0.32354527711868286,
0.0745656266808509... |
https://github.com/huggingface/datasets/issues/1727 | And I have the same error with TF 2.4.1. I believe this issue should be reopened. Any ideas?! | BLEURT score calculation raises UnrecognizedFlagError | Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
```
from datasets import load_metric
bleurt = load_me... | 18 | BLEURT score calculation raises UnrecognizedFlagError
Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
... | [
-0.3299121856689453,
-0.39836809039115906,
0.04140743613243103,
0.40009573101997375,
0.3001841604709625,
-0.22759121656417847,
0.27419713139533997,
0.2562865912914276,
0.005499333143234253,
0.2942809462547302,
-0.012273009866476059,
0.02246919274330139,
-0.08508650958538055,
0.046141445636... |
https://github.com/huggingface/datasets/issues/1727 | I'm seeing the same issue with TF 2.4.1 when running the following in https://colab.research.google.com/github/huggingface/datasets/blob/master/notebooks/Overview.ipynb:
```
!pip install git+https://github.com/google-research/bleurt.git
references = ["foo bar baz", "one two three"]
bleurt_metric = load_metric('bleu... | BLEURT score calculation raises UnrecognizedFlagError | Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
```
from datasets import load_metric
bleurt = load_me... | 39 | BLEURT score calculation raises UnrecognizedFlagError
Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
... | [
-0.3299121856689453,
-0.39836809039115906,
0.04140743613243103,
0.40009573101997375,
0.3001841604709625,
-0.22759121656417847,
0.27419713139533997,
0.2562865912914276,
0.005499333143234253,
0.2942809462547302,
-0.012273009866476059,
0.02246919274330139,
-0.08508650958538055,
0.046141445636... |
https://github.com/huggingface/datasets/issues/1727 | @aleSuglia @oscartackstrom - Are you getting the error when running your code in a Jupyter notebook ?
I tried reproducing this error again, and was unable to do so from the python command line console in a virtual environment similar to the one I originally used (and unfortunately no longer have access to) when I fi... | BLEURT score calculation raises UnrecognizedFlagError | Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
```
from datasets import load_metric
bleurt = load_me... | 112 | BLEURT score calculation raises UnrecognizedFlagError
Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
... | [
-0.3299121856689453,
-0.39836809039115906,
0.04140743613243103,
0.40009573101997375,
0.3001841604709625,
-0.22759121656417847,
0.27419713139533997,
0.2562865912914276,
0.005499333143234253,
0.2942809462547302,
-0.012273009866476059,
0.02246919274330139,
-0.08508650958538055,
0.046141445636... |
https://github.com/huggingface/datasets/issues/1727 | This happens when running the notebook on colab. The issue seems to be that colab populates sys.argv with arguments not handled by bleurt.
Running this before calling bleurt fixes it:
```
import sys
sys.argv = sys.argv[:1]
```
Not the most elegant solution. Perhaps it needs to be fixed in the bleurt code itse... | BLEURT score calculation raises UnrecognizedFlagError | Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
```
from datasets import load_metric
bleurt = load_me... | 71 | BLEURT score calculation raises UnrecognizedFlagError
Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
... | [
-0.3299121856689453,
-0.39836809039115906,
0.04140743613243103,
0.40009573101997375,
0.3001841604709625,
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0.27419713139533997,
0.2562865912914276,
0.005499333143234253,
0.2942809462547302,
-0.012273009866476059,
0.02246919274330139,
-0.08508650958538055,
0.046141445636... |
https://github.com/huggingface/datasets/issues/1727 | I got the error when running it from the command line. It looks more like an error that should be fixed in the BLEURT codebase. | BLEURT score calculation raises UnrecognizedFlagError | Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
```
from datasets import load_metric
bleurt = load_me... | 25 | BLEURT score calculation raises UnrecognizedFlagError
Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
... | [
-0.3299121856689453,
-0.39836809039115906,
0.04140743613243103,
0.40009573101997375,
0.3001841604709625,
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0.27419713139533997,
0.2562865912914276,
0.005499333143234253,
0.2942809462547302,
-0.012273009866476059,
0.02246919274330139,
-0.08508650958538055,
0.046141445636... |
https://github.com/huggingface/datasets/issues/1725 | You should rephrase your question or give more examples and details on what you want to do.
it’s not possible to understand it and help you with only this information. | load the local dataset | your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this problem!
thanks a lot! | 30 | load the local dataset
your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this prob... | [
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0.013498842716217041,
-0.10371392965316772,
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0.14708101749420166,
0.2700249254703522,
0.2880047857761383,
0.43632379174232483,
0.05448279529809952,
0.11620237678289413,
0.49470603466033936,
-0.07456570863723755,
0.2974508702754... |
https://github.com/huggingface/datasets/issues/1725 | sorry for that.
i want to know how could i load the train set and the test set from the local ,which api or function should i use .
| load the local dataset | your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this problem!
thanks a lot! | 29 | load the local dataset
your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this prob... | [
-0.31747061014175415,
0.06382003426551819,
-0.09525936841964722,
0.0737694799900055,
0.11967436969280243,
0.1557239592075348,
0.1555572897195816,
0.31872010231018066,
0.500864565372467,
0.061446480453014374,
0.16420230269432068,
0.43741554021835327,
-0.12088161706924438,
0.4828321039676666... |
https://github.com/huggingface/datasets/issues/1725 | thanks a lot
i find that the problem is i dont use vpn...
so i have to keep my net work even if i want to load the local data ? | load the local dataset | your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this problem!
thanks a lot! | 31 | load the local dataset
your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this prob... | [
-0.22625842690467834,
0.07263937592506409,
-0.050760071724653244,
0.02983066253364086,
0.11851228028535843,
0.06380331516265869,
0.27888503670692444,
0.2106349766254425,
0.41184747219085693,
0.13368786871433258,
0.12616345286369324,
0.4746665954589844,
0.07140642404556274,
0.47200232744216... |
https://github.com/huggingface/datasets/issues/1725 | Hi! `json` is a packaged dataset now, which means its script comes with the library and doesn't require an internet connection. | load the local dataset | your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this problem!
thanks a lot! | 21 | load the local dataset
your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this prob... | [
-0.31056851148605347,
0.15771819651126862,
-0.06468944251537323,
-0.06711780279874802,
0.21515482664108276,
0.1641663908958435,
0.36720436811447144,
0.382459431886673,
0.5427061915397644,
0.0918329581618309,
0.23480269312858582,
0.5336471199989319,
-0.06277057528495789,
0.3432738482952118,... |
https://github.com/huggingface/datasets/issues/1724 | Hi @lkcao !
Your issue is indeed related to `datasets`. In addition to installing the package manually, you will need to download the `text.py` script on your server. You'll find it (under `datasets/datasets/text`: https://github.com/huggingface/datasets/blob/master/datasets/text/text.py.
Then you can change the line... | could not run models on a offline server successfully | Hi, I really need your help about this.
I am trying to fine-tuning a RoBERTa on a remote server, which is strictly banning internet. I try to install all the packages by hand and try to run run_mlm.py on the server. It works well on colab, but when I try to run it on this offline server, it shows:
 directly in the `datasets` package so that they can be used offline | could not run models on a offline server successfully | Hi, I really need your help about this.
I am trying to fine-tuning a RoBERTa on a remote server, which is strictly banning internet. I try to install all the packages by hand and try to run run_mlm.py on the server. It works well on colab, but when I try to run it on this offline server, it shows:
 are now part of the `datasets` package since #1726 :)
You can now use them offline
```python
datasets = load_dataset('text', data_files=data_files)
```
We'll do a new release soon | could not run models on a offline server successfully | Hi, I really need your help about this.
I am trying to fine-tuning a RoBERTa on a remote server, which is strictly banning internet. I try to install all the packages by hand and try to run run_mlm.py on the server. It works well on colab, but when I try to run it on this offline server, it shows:
 are now part of the `datasets` package since #1726 :)
> You can now use them offline
>
> ```python
> datasets = load_dataset('text', data_files=data_files)
> ```
>
> We'll do a new release soon
so the new version release now? | could not run models on a offline server successfully | Hi, I really need your help about this.
I am trying to fine-tuning a RoBERTa on a remote server, which is strictly banning internet. I try to install all the packages by hand and try to run run_mlm.py on the server. It works well on colab, but when I try to run it on this offline server, it shows:
I tried to use `cache_file_names` and wasn't sure how, I tried to give it the following:
```
tokenized_datasets = tokenized_datasets.map(
group_texts,
batched=True,
num_proc=60,
load_from_cache_file=True,
cache_file_names={k: f'.cache/{str(... | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 229 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1718 | The documentation says
```
cache_file_names (`Optional[Dict[str, str]]`, defaults to `None`): Provide the name of a cache file to use to store the
results of the computation instead of the automatically generated cache file name.
You have to provide one :obj:`cache_file_name` per dataset in the dataset dict... | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 90 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1718 | Managed to get `cache_file_names` working and caching works well with it
Had to make a small modification for it to work:
```
cache_file_names = {k: f'tokenized_and_grouped_{str(k)}.arrow' for k in tokenized_datasets}
``` | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 31 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1718 | Another comment on `cache_file_names`, it doesn't save the produced cached files in the dataset's cache folder, it requires to give a path to an existing directory for it to work.
I can confirm that this is how it works in `datasets==1.1.3` | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 41 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1718 | Oh yes indeed ! Maybe we need to update the docstring to mention that it is a path | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 18 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1718 | I upgraded to the latest version and I encountered some strange behaviour, the script I posted in the OP doesn't trigger recalculation, however, if I add the following change it does trigger partial recalculation, I am not sure if its something wrong on my machine or a bug:
```
from datasets import load_dataset
from... | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 136 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1718 | This is because the `group_texts` line definition changes (it is defined 3 lines later than in the previous call). Currently if a function is moved elsewhere in a script we consider it to be different.
Not sure this is actually a good idea to keep this behavior though. We had this as a security in the early developm... | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 86 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1718 | Sounds great, thank you for your quick responses and help! Looking forward for the next release. | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 16 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1718 | I am having a similar issue where only the grouped files are loaded from cache while the tokenized ones aren't. I can confirm both datasets are being stored to file, but only the grouped version is loaded from cache. Not sure what might be going on. But I've tried to remove all kinds of non deterministic behaviour, but... | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 274 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1718 | This error happened to me too, when I tried to supply my own fingerprint to `map()` via the `new_fingerprint` arg.
Edit: realized it was because my path was weird and had colons and brackets and slashes in it, since one of the variable values I included in the fingerprint was a dataset split like "train[:10%]". I fi... | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 72 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1718 | Good catch @jxmorris12, maybe we should do additional checks on the valid characters for fingerprints ! Would you like to contribute this ?
I think this can be added here, when we set the fingerprint(s) that are passed `map`:
https://github.com/huggingface/datasets/blob/25bb7c9cbf519fbbf9abf3898083b529e7762705/sr... | Possible cache miss in datasets | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | 81 | Possible cache miss in datasets
Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function alway... | [
-0.19303953647613525,
0.1210537701845169,
0.05009517818689346,
0.19009359180927277,
0.007696783170104027,
0.036921143531799316,
-0.016854984685778618,
0.23034992814064026,
0.01673281192779541,
-0.10844335705041885,
0.10299848020076752,
0.41397133469581604,
0.22491182386875153,
-0.111724227... |
https://github.com/huggingface/datasets/issues/1717 | Hi Dave,
You are more than welcome to open a PR to make these changes! 🤗
You will find the relevant information about opening a PR in the [contributing guide](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md) and in the [dataset addition guide](https://github.com/huggingface/datasets/blob/master/A... | SciFact dataset - minor changes | Hi,
SciFact dataset creator here. First of all, thanks for adding the dataset to Huggingface, much appreciated!
I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
It also looks like the dataset is being downloa... | 44 | SciFact dataset - minor changes
Hi,
SciFact dataset creator here. First of all, thanks for adding the dataset to Huggingface, much appreciated!
I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
It also looks... | [
0.15889379382133484,
-0.19734877347946167,
-0.06765363365411758,
0.14704018831253052,
0.1484656184911728,
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-0.20454971492290497,
-0.04013639688491821,
0.0873413234949112,
-0.09037934243679047,
-0.0821840763092041,
0.015894927084445953,
-0.008538665249943733,
0.49486884... |
https://github.com/huggingface/datasets/issues/1717 | > I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
Sure ! Also feel free to ping us for reviews or if we can help :)
> It also looks like the dataset is being downloaded directly from Huggingface's Google cloud ... | SciFact dataset - minor changes | Hi,
SciFact dataset creator here. First of all, thanks for adding the dataset to Huggingface, much appreciated!
I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
It also looks like the dataset is being downloa... | 91 | SciFact dataset - minor changes
Hi,
SciFact dataset creator here. First of all, thanks for adding the dataset to Huggingface, much appreciated!
I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
It also looks... | [
0.17509648203849792,
-0.16272060573101044,
-0.13827097415924072,
0.16952334344387054,
0.1716015785932541,
-0.10548392683267593,
-0.010719187557697296,
0.033970773220062256,
0.21871836483478546,
0.04157533869147301,
-0.17465108633041382,
0.02215476706624031,
-0.0037147440016269684,
0.515472... |
https://github.com/huggingface/datasets/issues/1717 |
> > I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
>
> Sure ! Also feel free to ping us for reviews or if we can help :)
>
OK! We're organizing a [shared task](https://sdproc.org/2021/sharedtasks.html#sciv... | SciFact dataset - minor changes | Hi,
SciFact dataset creator here. First of all, thanks for adding the dataset to Huggingface, much appreciated!
I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
It also looks like the dataset is being downloa... | 152 | SciFact dataset - minor changes
Hi,
SciFact dataset creator here. First of all, thanks for adding the dataset to Huggingface, much appreciated!
I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
It also looks... | [
0.1659245789051056,
-0.16320905089378357,
-0.10141003876924515,
0.25287064909935,
0.16676755249500275,
-0.11696125566959381,
-0.011766349896788597,
0.06558152288198471,
0.25607749819755554,
0.053932905197143555,
-0.1586158573627472,
0.03160080686211586,
0.02210395783185959,
0.4208246767520... |
https://github.com/huggingface/datasets/issues/1713 | Great! Did you guys have a timeframe in mind for the next release?
Thank you for all the great work in developing this library. | Installation using conda | Will a conda package for installing datasets be added to the huggingface conda channel? I have installed transformers using conda and would like to use the datasets library to use some of the scripts in the transformers/examples folder but am unable to do so at the moment as datasets can only be installed using pip and... | 24 | Installation using conda
Will a conda package for installing datasets be added to the huggingface conda channel? I have installed transformers using conda and would like to use the datasets library to use some of the scripts in the transformers/examples folder but am unable to do so at the moment as datasets can only... | [
-0.05395727604627609,
-0.03765840828418732,
-0.18016193807125092,
0.17618189752101898,
0.19111645221710205,
-0.1741129755973816,
0.16255345940589905,
-0.06701388210058212,
-0.3270973861217499,
-0.22117768228054047,
-0.22946697473526,
0.05975136533379555,
-0.18898950517177582,
0.51048421859... |
https://github.com/huggingface/datasets/issues/1713 | I think we can have `datasets` on conda by next week. Will see what I can do! | Installation using conda | Will a conda package for installing datasets be added to the huggingface conda channel? I have installed transformers using conda and would like to use the datasets library to use some of the scripts in the transformers/examples folder but am unable to do so at the moment as datasets can only be installed using pip and... | 17 | Installation using conda
Will a conda package for installing datasets be added to the huggingface conda channel? I have installed transformers using conda and would like to use the datasets library to use some of the scripts in the transformers/examples folder but am unable to do so at the moment as datasets can only... | [
-0.014954030513763428,
-0.0426131933927536,
-0.12364751845598221,
0.1562698483467102,
0.2540787160396576,
-0.00923290103673935,
0.1276860386133194,
-0.13031841814517975,
-0.2962277829647064,
-0.2111261785030365,
-0.23479008674621582,
0.0809221938252449,
-0.14033786952495575,
0.627656817436... |
https://github.com/huggingface/datasets/issues/1713 | `datasets` has been added to the huggingface channel thanks to @LysandreJik :)
It depends on conda-forge though
```
conda install -c huggingface -c conda-forge datasets
``` | Installation using conda | Will a conda package for installing datasets be added to the huggingface conda channel? I have installed transformers using conda and would like to use the datasets library to use some of the scripts in the transformers/examples folder but am unable to do so at the moment as datasets can only be installed using pip and... | 26 | Installation using conda
Will a conda package for installing datasets be added to the huggingface conda channel? I have installed transformers using conda and would like to use the datasets library to use some of the scripts in the transformers/examples folder but am unable to do so at the moment as datasets can only... | [
-0.029604226350784302,
-0.03997485339641571,
-0.10899733006954193,
0.18604201078414917,
0.23940646648406982,
-0.044519200921058655,
0.11317209154367447,
-0.10590070486068726,
-0.33142438530921936,
-0.3028704524040222,
-0.2650929391384125,
0.10409043729305267,
-0.13574816286563873,
0.530663... |
https://github.com/huggingface/datasets/issues/1710 | I haven't tested C4 on my side so there so there may be a few bugs in the code/adjustments to make.
Here it looks like in c4.py, line 190 one of the `files_to_download` is `'/'` which is invalid.
Valid files are paths to local files or URLs to remote files. | IsADirectoryError when trying to download C4 | **TLDR**:
I fail to download C4 and see a stacktrace originating in `IsADirectoryError` as an explanation for failure.
How can the problem be fixed?
**VERBOSE**:
I use Python version 3.7 and have the following dependencies listed in my project:
```
datasets==1.2.0
apache-beam==2.26.0
```
When runn... | 50 | IsADirectoryError when trying to download C4
**TLDR**:
I fail to download C4 and see a stacktrace originating in `IsADirectoryError` as an explanation for failure.
How can the problem be fixed?
**VERBOSE**:
I use Python version 3.7 and have the following dependencies listed in my project:
```
dataset... | [
-0.21100109815597534,
-0.016682371497154236,
0.0020137764513492584,
0.23881208896636963,
0.30036306381225586,
0.011594295501708984,
0.08793196082115173,
0.2422642856836319,
-0.10572299361228943,
0.09686098992824554,
-0.19106709957122803,
-0.09682224690914154,
-0.30837905406951904,
-0.03787... |
https://github.com/huggingface/datasets/issues/1706 | Hi ! Is this an issue you have with `openwebtext` specifically or also with other datasets ?
It looks like the downloaded file is corrupted and can't be extracted using `tarfile`.
Could you try loading it again with
```python
import datasets
datasets.load_dataset("openwebtext", download_mode="force_redownload")... | Error when downloading a large dataset on slow connection. | I receive the following error after about an hour trying to download the `openwebtext` dataset.
The code used is:
```python
import datasets
datasets.load_dataset("openwebtext")
```
> Traceback (most recent call last): ... | 44 | Error when downloading a large dataset on slow connection.
I receive the following error after about an hour trying to download the `openwebtext` dataset.
The code used is:
```python
import datasets
datasets.load_dataset("openwebtext")
```
> Traceback (most recent call last): ... | [
-0.49100780487060547,
0.027840033173561096,
-0.10269356518983841,
0.2193085253238678,
0.21971487998962402,
0.11000144481658936,
0.1182752400636673,
0.479827880859375,
0.05374225974082947,
0.00582711398601532,
-0.16624687612056732,
-0.10805191099643707,
-0.02068866603076458,
0.0919340401887... |
https://github.com/huggingface/datasets/issues/1701 | Thanks for reporting.
We should indeed add all the missing dummy_data.zip and also the dataset_infos.json at least for lm1b, reclor and wikihow.
For c4 I haven't tested the script and I think we'll require some optimizations regarding beam datasets before processing it.
| Some datasets miss dataset_infos.json or dummy_data.zip | While working on dataset REAME generation script at https://github.com/madlag/datasets_readme_generator , I noticed that some datasets miss a dataset_infos.json :
```
c4
lm1b
reclor
wikihow
```
And some does not have a dummy_data.zip :
```
kor_nli
math_dataset
mlqa
ms_marco
newsgroup
qa4mre
qanga... | 42 | Some datasets miss dataset_infos.json or dummy_data.zip
While working on dataset REAME generation script at https://github.com/madlag/datasets_readme_generator , I noticed that some datasets miss a dataset_infos.json :
```
c4
lm1b
reclor
wikihow
```
And some does not have a dummy_data.zip :
```
kor_n... | [
0.13598933815956116,
0.27314889430999756,
-0.046183992177248,
0.2401539385318756,
0.28582763671875,
0.34397268295288086,
0.21809348464012146,
0.003397710621356964,
-0.04679156839847565,
0.03129434585571289,
0.19417878985404968,
0.06412886083126068,
-0.007530549541115761,
0.1257325410842895... |
https://github.com/huggingface/datasets/issues/1701 | Closing since the dummy data generation is deprecated now (and the issue with missing metadata seems to be addressed). | Some datasets miss dataset_infos.json or dummy_data.zip | While working on dataset REAME generation script at https://github.com/madlag/datasets_readme_generator , I noticed that some datasets miss a dataset_infos.json :
```
c4
lm1b
reclor
wikihow
```
And some does not have a dummy_data.zip :
```
kor_nli
math_dataset
mlqa
ms_marco
newsgroup
qa4mre
qanga... | 19 | Some datasets miss dataset_infos.json or dummy_data.zip
While working on dataset REAME generation script at https://github.com/madlag/datasets_readme_generator , I noticed that some datasets miss a dataset_infos.json :
```
c4
lm1b
reclor
wikihow
```
And some does not have a dummy_data.zip :
```
kor_n... | [
0.10084167122840881,
0.20143625140190125,
-0.061809055507183075,
0.2740953862667084,
0.21796104311943054,
0.35636767745018005,
0.23157338798046112,
0.10757631063461304,
-0.1837213635444641,
-0.03773093968629837,
0.17453189194202423,
0.09594365954399109,
0.09989148378372192,
-0.015732936561... |
https://github.com/huggingface/datasets/issues/1687 | We could do something. There is a part of `.info` which is split specific (cache files, split instructions) but maybe if could be made to work. | Question: Shouldn't .info be a part of DatasetDict? | Currently, only `Dataset` contains the .info or .features, but as many datasets contains standard splits (train, test) and thus the underlying information is the same (or at least should be) across the datasets.
For instance:
```
>>> ds = datasets.load_dataset("conll2002", "es")
>>> ds.info
Traceback (most rece... | 26 | Question: Shouldn't .info be a part of DatasetDict?
Currently, only `Dataset` contains the .info or .features, but as many datasets contains standard splits (train, test) and thus the underlying information is the same (or at least should be) across the datasets.
For instance:
```
>>> ds = datasets.load_dataset... | [
0.09181149303913116,
-0.13298554718494415,
-0.060103338211774826,
0.3179161250591278,
0.11598154902458191,
0.28523093461990356,
0.4842666685581207,
0.10404083132743835,
0.1170903742313385,
-0.021073922514915466,
0.11989378929138184,
-0.012208044528961182,
0.11281299591064453,
0.57232689857... |
https://github.com/huggingface/datasets/issues/1687 | Yes this was kinda the idea I was going for. DatasetDict.info would be the shared info amongs the datasets (maybe even some info on how they differ). | Question: Shouldn't .info be a part of DatasetDict? | Currently, only `Dataset` contains the .info or .features, but as many datasets contains standard splits (train, test) and thus the underlying information is the same (or at least should be) across the datasets.
For instance:
```
>>> ds = datasets.load_dataset("conll2002", "es")
>>> ds.info
Traceback (most rece... | 27 | Question: Shouldn't .info be a part of DatasetDict?
Currently, only `Dataset` contains the .info or .features, but as many datasets contains standard splits (train, test) and thus the underlying information is the same (or at least should be) across the datasets.
For instance:
```
>>> ds = datasets.load_dataset... | [
0.10923460125923157,
-0.18634097278118134,
-0.05223241075873375,
0.32486385107040405,
0.10438555479049683,
0.2396508902311325,
0.4616633653640747,
0.018087156116962433,
0.07692927122116089,
0.019750025123357773,
0.16768735647201538,
0.0010693855583667755,
0.09683974087238312,
0.54612797498... |
https://github.com/huggingface/datasets/issues/1686 | One the PR is merged the fix will be available in the next release of `datasets`.
If you don't want to wait the next release you can still load the script from the master branch with
```python
load_dataset("dane", script_version="master")
``` | Dataset Error: DaNE contains empty samples at the end | The dataset DaNE, contains empty samples at the end. It is naturally easy to remove using a filter but should probably not be there, to begin with as it can cause errors.
```python
>>> import datasets
[...]
>>> dataset = datasets.load_dataset("dane")
[...]
>>> dataset["test"][-1]
{'dep_ids': [], 'dep_labels': ... | 40 | Dataset Error: DaNE contains empty samples at the end
The dataset DaNE, contains empty samples at the end. It is naturally easy to remove using a filter but should probably not be there, to begin with as it can cause errors.
```python
>>> import datasets
[...]
>>> dataset = datasets.load_dataset("dane")
[...]
... | [
-0.1232689917087555,
-0.15057799220085144,
-0.20778268575668335,
-0.0634230524301529,
0.27672088146209717,
0.1347072422504425,
0.3861129879951477,
0.3464494049549103,
0.22405390441417694,
0.2550486922264099,
0.14272978901863098,
0.24621163308620453,
-0.10214133560657501,
0.1205542534589767... |
https://github.com/huggingface/datasets/issues/1683 | Looks like the mapping function returns a dictionary with a 768-dim array in the `embeddings` field. Since the map is batched, we actually expect the `embeddings` field to be an array of shape (batch_size, 768) to have one embedding per example in the batch.
To fix that can you try to remove one of the `[0]` ? In my... | `ArrowInvalid` occurs while running `Dataset.map()` function for DPRContext | It seems to fail the final batch ):
steps to reproduce:
```
from datasets import load_dataset
from elasticsearch import Elasticsearch
import torch
from transformers import file_utils, set_seed
from transformers import DPRContextEncoder, DPRContextEncoderTokenizerFast
MAX_SEQ_LENGTH = 256
ctx_encoder = DPRCon... | 68 | `ArrowInvalid` occurs while running `Dataset.map()` function for DPRContext
It seems to fail the final batch ):
steps to reproduce:
```
from datasets import load_dataset
from elasticsearch import Elasticsearch
import torch
from transformers import file_utils, set_seed
from transformers import DPRContextEncod... | [
-0.5113663077354431,
-0.340737521648407,
-0.12627188861370087,
0.06084979698061943,
0.07763765752315521,
0.14176729321479797,
-0.018711749464273453,
0.2698066234588623,
-0.26221463084220886,
0.04919598251581192,
0.110806405544281,
0.5883790850639343,
-0.030782146379351616,
-0.1317680925130... |
https://github.com/huggingface/datasets/issues/1681 | Hi @KennethEnevoldsen ,
I think the issue might be that this dataset was added during the community sprint and has not been released yet. It will be available with the v2 of datasets.
For now, you should be able to load the datasets after installing the latest (master) version of datasets using pip:
pip install git+... | Dataset "dane" missing | the `dane` dataset appear to be missing in the latest version (1.1.3).
```python
>>> import datasets
>>> datasets.__version__
'1.1.3'
>>> "dane" in datasets.list_datasets()
True
```
As we can see it should be present, but doesn't seem to be findable when using `load_dataset`.
```python
>>> datasets.load... | 56 | Dataset "dane" missing
the `dane` dataset appear to be missing in the latest version (1.1.3).
```python
>>> import datasets
>>> datasets.__version__
'1.1.3'
>>> "dane" in datasets.list_datasets()
True
```
As we can see it should be present, but doesn't seem to be findable when using `load_dataset`.
```... | [
-0.006653293967247009,
-0.06125681847333908,
-0.09929947555065155,
0.12845203280448914,
0.2658339738845825,
0.2934045195579529,
0.464662104845047,
0.1487022042274475,
0.28402286767959595,
0.08272825181484222,
0.13032877445220947,
0.04085895046591759,
-0.09202349185943604,
-0.12458764761686... |
https://github.com/huggingface/datasets/issues/1681 | The `dane` dataset was added recently, that's why it wasn't available yet. We did an intermediate release today just before the v2.0.
To load it you can just update `datasets`
```
pip install --upgrade datasets
```
and then you can load `dane` with
```python
from datasets import load_dataset
dataset = l... | Dataset "dane" missing | the `dane` dataset appear to be missing in the latest version (1.1.3).
```python
>>> import datasets
>>> datasets.__version__
'1.1.3'
>>> "dane" in datasets.list_datasets()
True
```
As we can see it should be present, but doesn't seem to be findable when using `load_dataset`.
```python
>>> datasets.load... | 52 | Dataset "dane" missing
the `dane` dataset appear to be missing in the latest version (1.1.3).
```python
>>> import datasets
>>> datasets.__version__
'1.1.3'
>>> "dane" in datasets.list_datasets()
True
```
As we can see it should be present, but doesn't seem to be findable when using `load_dataset`.
```... | [
-0.006653293967247009,
-0.06125681847333908,
-0.09929947555065155,
0.12845203280448914,
0.2658339738845825,
0.2934045195579529,
0.464662104845047,
0.1487022042274475,
0.28402286767959595,
0.08272825181484222,
0.13032877445220947,
0.04085895046591759,
-0.09202349185943604,
-0.12458764761686... |
https://github.com/huggingface/datasets/issues/1679 | cc100 was added recently, that's why it wasn't available yet.
To load it you can just update `datasets`
```
pip install --upgrade datasets
```
and then you can load `cc100` with
```python
from datasets import load_dataset
lang = "en"
dataset = load_dataset("cc100", lang=lang, split="train")
``` | Can't import cc100 dataset | There is some issue to import cc100 dataset.
```
from datasets import load_dataset
dataset = load_dataset("cc100")
```
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/cc100/cc100.py
During handling of the above exception, another exception occur... | 45 | Can't import cc100 dataset
There is some issue to import cc100 dataset.
```
from datasets import load_dataset
dataset = load_dataset("cc100")
```
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/cc100/cc100.py
During handling of the above excep... | [
-0.2749533951282501,
-0.34881553053855896,
-0.16288651525974274,
0.23452971875667572,
0.37639716267585754,
0.14574553072452545,
0.08866671472787857,
0.02463938668370247,
0.015882059931755066,
0.20677600800991058,
-0.12557508051395416,
0.058415062725543976,
0.022705141454935074,
0.319436639... |
https://github.com/huggingface/datasets/issues/1675 | The pile dataset would be very nice.
Benchmarks show that pile trained models achieve better results than most of actually trained models | Add the 800GB Pile dataset? | ## Adding a Dataset
- **Name:** The Pile
- **Description:** The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. See [here](https://twitter.com/nabla_theta/status/1345130408170541056?s=20) for the Twitter announcement
- **Paper:*... | 22 | Add the 800GB Pile dataset?
## Adding a Dataset
- **Name:** The Pile
- **Description:** The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. See [here](https://twitter.com/nabla_theta/status/1345130408170541056?s=20) for the Twi... | [
-0.32521480321884155,
0.21306736767292023,
-0.1506744921207428,
0.13712839782238007,
0.0009426521137356758,
0.2578675448894501,
0.14345303177833557,
0.24660275876522064,
-0.030717920511960983,
-0.06392881274223328,
-0.15774507820606232,
0.14879468083381653,
-0.5934293866157532,
0.184142947... |
https://github.com/huggingface/datasets/issues/1675 | The pile can very easily be added and adapted using this [tfds implementation](https://github.com/EleutherAI/The-Pile/blob/master/the_pile/tfds_pile.py) from the repo.
However, the question is whether you'd be ok with 800GB+ cached in your local disk, since the tfds implementation was designed to offload the storag... | Add the 800GB Pile dataset? | ## Adding a Dataset
- **Name:** The Pile
- **Description:** The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. See [here](https://twitter.com/nabla_theta/status/1345130408170541056?s=20) for the Twitter announcement
- **Paper:*... | 45 | Add the 800GB Pile dataset?
## Adding a Dataset
- **Name:** The Pile
- **Description:** The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. See [here](https://twitter.com/nabla_theta/status/1345130408170541056?s=20) for the Twi... | [
-0.305496484041214,
0.06998559832572937,
-0.16041815280914307,
0.1612253487110138,
0.058335207402706146,
0.2056465744972229,
0.16649316251277924,
0.15289704501628876,
0.09870210289955139,
0.03799181431531906,
-0.2099473625421524,
-0.0474000908434391,
-0.5426977872848511,
0.1175633221864700... |
https://github.com/huggingface/datasets/issues/1675 | With the dataset streaming feature (see #2375) it will be more convenient to play with such big datasets :)
I'm currently adding C4 (see #2511 ) but I can probably start working on this afterwards | Add the 800GB Pile dataset? | ## Adding a Dataset
- **Name:** The Pile
- **Description:** The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. See [here](https://twitter.com/nabla_theta/status/1345130408170541056?s=20) for the Twitter announcement
- **Paper:*... | 35 | Add the 800GB Pile dataset?
## Adding a Dataset
- **Name:** The Pile
- **Description:** The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. See [here](https://twitter.com/nabla_theta/status/1345130408170541056?s=20) for the Twi... | [
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0.15567854046821594,
0.017111150547862053,
0.17151418328285217,
0.08797838538885117,
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0.019485119730234146,
-0.15745967626571655,
0.14085692167282104,
-0.5226860642433167,
0.192629545927047... |
https://github.com/huggingface/datasets/issues/1675 | Hi folks! Just wanted to follow up on this -- would be really nice to get the Pile on HF Datasets... unclear if it would be easy to also add partitions of the Pile subject to the original 22 datasets used, but that would be nice too! | Add the 800GB Pile dataset? | ## Adding a Dataset
- **Name:** The Pile
- **Description:** The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. See [here](https://twitter.com/nabla_theta/status/1345130408170541056?s=20) for the Twitter announcement
- **Paper:*... | 47 | Add the 800GB Pile dataset?
## Adding a Dataset
- **Name:** The Pile
- **Description:** The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. See [here](https://twitter.com/nabla_theta/status/1345130408170541056?s=20) for the Twi... | [
-0.2462540566921234,
0.1785697042942047,
-0.10752715170383453,
0.20753338932991028,
-0.06281895190477371,
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0.15014353394508362,
0.18070292472839355,
0.10750549286603928,
-0.0014593526721000671,
-0.3454720377922058,
0.09751681238412857,
-0.4746154248714447,
0.25449481606... |
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