html_url stringlengths 48 51 | title stringlengths 5 280 | comments stringlengths 63 51.8k | body stringlengths 0 36.2k ⌀ | comment_length int64 16 1.52k | text stringlengths 159 54.1k | embeddings listlengths 768 768 |
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https://github.com/huggingface/datasets/issues/3761 | Know your data for HF hub | Hi @Muhtasham you should take a look at https://huggingface.co/blog/data-measurements-tool and accompanying demo app at https://huggingface.co/spaces/huggingface/data-measurements-tool
We would be interested in your feedback. cc @meg-huggingface @sashavor @yjernite | **Is your feature request related to a problem? Please describe.**
Would be great to see be able to understand datasets with the goal of improving data quality, and helping mitigate fairness and bias issues.
**Describe the solution you'd like**
Something like https://knowyourdata.withgoogle.com/ for HF hub | 26 | Know your data for HF hub
**Is your feature request related to a problem? Please describe.**
Would be great to see be able to understand datasets with the goal of improving data quality, and helping mitigate fairness and bias issues.
**Describe the solution you'd like**
Something like https://knowyourdata.withg... | [
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https://github.com/huggingface/datasets/issues/3760 | Unable to view the Gradio flagged call back dataset | Hi @kingabzpro.
I think you need to create a loading script that creates the dataset from the CSV file and the image paths.
As example, you could have a look at the Food-101 dataset: https://huggingface.co/datasets/food101
- Loading script: https://huggingface.co/datasets/food101/blob/main/food101.py
Once the... | ## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The dataset is also not showing the link with the app https://h... | 54 | Unable to view the Gradio flagged call back dataset
## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The datas... | [
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0.42670151591300... |
https://github.com/huggingface/datasets/issues/3760 | Unable to view the Gradio flagged call back dataset | @albertvillanova I don't think this is the issue. I have created another dataset with similar files and format and it works. https://huggingface.co/datasets/kingabzpro/savtadepth-flags-V2 | ## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The dataset is also not showing the link with the app https://h... | 22 | Unable to view the Gradio flagged call back dataset
## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The datas... | [
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https://github.com/huggingface/datasets/issues/3760 | Unable to view the Gradio flagged call back dataset | Yes, you are right, that was not the issue.
Just take into account that sometimes the viewer can take some time until it shows the preview of the dataset.
After some time, yours is finally properly shown: https://huggingface.co/datasets/kingabzpro/savtadepth-flags | ## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The dataset is also not showing the link with the app https://h... | 38 | Unable to view the Gradio flagged call back dataset
## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The datas... | [
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https://github.com/huggingface/datasets/issues/3760 | Unable to view the Gradio flagged call back dataset | The problem was resolved by deleted the dataset and creating new one with similar name and then clicking on flag button. | ## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The dataset is also not showing the link with the app https://h... | 21 | Unable to view the Gradio flagged call back dataset
## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The datas... | [
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https://github.com/huggingface/datasets/issues/3758 | head_qa file missing | We usually find issues with files hosted at Google Drive...
In this case we download the Google Drive Virus scan warning instead of the data file. | ## Describe the bug
A file for the `head_qa` dataset is missing (https://drive.google.com/u/0/uc?export=download&id=1a_95N5zQQoUCq8IBNVZgziHbeM-QxG2t/HEAD_EN/train_HEAD_EN.json)
## Steps to reproduce the bug
```python
>>> from datasets import load_dataset
>>> load_dataset("head_qa", name="en")
```
## Expec... | 26 | head_qa file missing
## Describe the bug
A file for the `head_qa` dataset is missing (https://drive.google.com/u/0/uc?export=download&id=1a_95N5zQQoUCq8IBNVZgziHbeM-QxG2t/HEAD_EN/train_HEAD_EN.json)
## Steps to reproduce the bug
```python
>>> from datasets import load_dataset
>>> load_dataset("head_qa", name... | [
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... |
https://github.com/huggingface/datasets/issues/3756 | Images get decoded when using `map()` with `input_columns` argument on a dataset | Hi! If I'm not mistaken, this behavior is intentional, but I agree it could be more intuitive.
@albertvillanova Do you remember why you decided not to decode columns in the `Audio` feature PR when `input_columns` is not `None`? IMO we should decode those columns, and we don't even have to use lazy structures here be... | ## Describe the bug
The `datasets.features.Image` feature class decodes image data by default. Expectedly, when indexing a dataset or using the `map()` method, images are returned as PIL Image instances.
However, when calling `map()` and setting a specific data column with the `input_columns` argument, the image ... | 68 | Images get decoded when using `map()` with `input_columns` argument on a dataset
## Describe the bug
The `datasets.features.Image` feature class decodes image data by default. Expectedly, when indexing a dataset or using the `map()` method, images are returned as PIL Image instances.
However, when calling `map(... | [
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https://github.com/huggingface/datasets/issues/3756 | Images get decoded when using `map()` with `input_columns` argument on a dataset | I think I excluded to decorate the function when `input_columns` were passed as a quick fix for some non-passing tests:
- https://github.com/huggingface/datasets/pull/2324/commits/9d7c3e8fa53e23ec636859b4407eeec904b1b3f9
That PR was quite complex and I decided to focus on the main feature requests, leaving refinem... | ## Describe the bug
The `datasets.features.Image` feature class decodes image data by default. Expectedly, when indexing a dataset or using the `map()` method, images are returned as PIL Image instances.
However, when calling `map()` and setting a specific data column with the `input_columns` argument, the image ... | 92 | Images get decoded when using `map()` with `input_columns` argument on a dataset
## Describe the bug
The `datasets.features.Image` feature class decodes image data by default. Expectedly, when indexing a dataset or using the `map()` method, images are returned as PIL Image instances.
However, when calling `map(... | [
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https://github.com/huggingface/datasets/issues/3755 | Cannot preview dataset | Thanks for reporting. The dataset viewer depends on some backend treatments, and for now, they might take some hours to get processed. We're working on improving it. | ## Dataset viewer issue for '*rubrix/news*'
**Link:https://huggingface.co/datasets/rubrix/news** *link to the dataset viewer page*
Cannot see the dataset preview:
```
Status code: 400
Exception: Status400Error
Message: Not found. Cache is waiting to be refreshed.
```
Am I the one who added thi... | 27 | Cannot preview dataset
## Dataset viewer issue for '*rubrix/news*'
**Link:https://huggingface.co/datasets/rubrix/news** *link to the dataset viewer page*
Cannot see the dataset preview:
```
Status code: 400
Exception: Status400Error
Message: Not found. Cache is waiting to be refreshed.
```
A... | [
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https://github.com/huggingface/datasets/issues/3753 | Expanding streaming capabilities | Cool ! `filter` will be very useful. There can be a filter that you can apply on a streaming dataset:
```python
load_dataset(..., streaming=True).filter(lambda x: x["lang"] == "sw")
```
Otherwise if you want to apply a filter on the source files that are going to be used for streaming, the logic has to be impIeme... | Some ideas for a few features that could be useful when working with large datasets in streaming mode.
## `filter` for `IterableDataset`
Adding filtering to streaming datasets would be useful in several scenarios:
- filter a dataset with many languages for a subset of languages
- filter a dataset for specific li... | 160 | Expanding streaming capabilities
Some ideas for a few features that could be useful when working with large datasets in streaming mode.
## `filter` for `IterableDataset`
Adding filtering to streaming datasets would be useful in several scenarios:
- filter a dataset with many languages for a subset of languages
... | [
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https://github.com/huggingface/datasets/issues/3753 | Expanding streaming capabilities | Regarding conversion, I'd also ask for some kind of equivalent to `save_to_disk` for an `IterableDataset`.
Similarly to the streaming to hub idea, my use case would be to define a sequence of dataset transforms via `.map()`, using an `IterableDataset` as the input (so processing could start without doing whole downl... | Some ideas for a few features that could be useful when working with large datasets in streaming mode.
## `filter` for `IterableDataset`
Adding filtering to streaming datasets would be useful in several scenarios:
- filter a dataset with many languages for a subset of languages
- filter a dataset for specific li... | 60 | Expanding streaming capabilities
Some ideas for a few features that could be useful when working with large datasets in streaming mode.
## `filter` for `IterableDataset`
Adding filtering to streaming datasets would be useful in several scenarios:
- filter a dataset with many languages for a subset of languages
... | [
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https://github.com/huggingface/datasets/issues/3753 | Expanding streaming capabilities | That makes sense @athewsey , thanks for the suggestion :)
Maybe instead of the `to_disk` we could simply have `save_to_disk` instead:
```python
streaming_dataset.save_to_disk("path/to/my/dataset/dir")
on_disk_dataset = load_from_disk("path/to/my/dataset/dir")
in_memory_dataset = Dataset.from_list(list(streamin... | Some ideas for a few features that could be useful when working with large datasets in streaming mode.
## `filter` for `IterableDataset`
Adding filtering to streaming datasets would be useful in several scenarios:
- filter a dataset with many languages for a subset of languages
- filter a dataset for specific li... | 38 | Expanding streaming capabilities
Some ideas for a few features that could be useful when working with large datasets in streaming mode.
## `filter` for `IterableDataset`
Adding filtering to streaming datasets would be useful in several scenarios:
- filter a dataset with many languages for a subset of languages
... | [
-0.6017637848854065,
-0.342872679233551,
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0.09503386914730072,
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0.19569797813892365,
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0.5236798524856567,... |
https://github.com/huggingface/datasets/issues/3753 | Expanding streaming capabilities | So far are implemented: `IterableDataset.filter()` and `Dataset.to_iterable_dataset()`.
Still missing: `IterableDataset.push_to_hub()` - though there is a hack to write on disk and then push to hub using
```python
ds_on_disk = Dataset.from_generator(streaming_ds.__iter__) # stream to disk
ds_on_disk.push_to_hu... | Some ideas for a few features that could be useful when working with large datasets in streaming mode.
## `filter` for `IterableDataset`
Adding filtering to streaming datasets would be useful in several scenarios:
- filter a dataset with many languages for a subset of languages
- filter a dataset for specific li... | 36 | Expanding streaming capabilities
Some ideas for a few features that could be useful when working with large datasets in streaming mode.
## `filter` for `IterableDataset`
Adding filtering to streaming datasets would be useful in several scenarios:
- filter a dataset with many languages for a subset of languages
... | [
-0.6017637848854065,
-0.342872679233551,
-0.17725646495819092,
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0.09503386914730072,
-0.0295092910528183,
0.0078958198428154,
0.4271875023841858,
0.2996821701526642,
0.1316363662481308,
-0.24636714160442352,
0.19569797813892365,
-0.3171161115169525,
0.5236798524856567,... |
https://github.com/huggingface/datasets/issues/3739 | Pubmed dataset does not work in streaming mode | Thanks for reporting, @abhi-mosaic (related to #3655).
Please note that `xml.etree.ElementTree.parse` already supports streaming:
- #3476
No need to refactor to use `open`/`xopen`. Is is enough with importing the package `as ET` (instead of `as etree`). | ## Describe the bug
Trying to use the `pubmed` dataset with `streaming=True` fails.
## Steps to reproduce the bug
```python
import datasets
pubmed_train = datasets.load_dataset('pubmed', split='train', streaming=True)
print (next(iter(pubmed_train)))
```
## Expected results
I would expect to see the first ... | 36 | Pubmed dataset does not work in streaming mode
## Describe the bug
Trying to use the `pubmed` dataset with `streaming=True` fails.
## Steps to reproduce the bug
```python
import datasets
pubmed_train = datasets.load_dataset('pubmed', split='train', streaming=True)
print (next(iter(pubmed_train)))
```
## E... | [
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https://github.com/huggingface/datasets/issues/3738 | For data-only datasets, streaming and non-streaming don't behave the same | Note that we might change the heuristic and create a different config per file, at least in that case. | See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets as ds
iterable_dataset = ds.load_dataset("huggingface/transformers-metadat... | 19 | For data-only datasets, streaming and non-streaming don't behave the same
See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets... | [
-0.1471761018037796,
-0.6080199480056763,
0.002013992518186569,
0.25075602531433105,
0.35946547985076904,
0.013917997479438782,
0.1687212735414505,
0.2110687643289566,
0.0835052877664566,
0.08174446225166321,
-0.3420368731021881,
0.17021232843399048,
-0.11890649050474167,
0.303690314292907... |
https://github.com/huggingface/datasets/issues/3738 | For data-only datasets, streaming and non-streaming don't behave the same | Hi @severo, thanks for reporting.
Yes, this happens because when non-streaming, a cast of all data is done in order to "concatenate" it all into a single dataset (thus the error), while this casting is not done while yielding item by item in streaming mode.
Maybe in streaming mode we should keep the schema (infer... | See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets as ds
iterable_dataset = ds.load_dataset("huggingface/transformers-metadat... | 74 | For data-only datasets, streaming and non-streaming don't behave the same
See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets... | [
-0.1483689397573471,
-0.5971014499664307,
0.0425090529024601,
0.30266034603118896,
0.44494253396987915,
0.034307435154914856,
0.09386201202869415,
0.22743399441242218,
-0.019862575456500053,
0.12076082825660706,
-0.28129544854164124,
0.16324304044246674,
-0.13695795834064484,
0.26528668403... |
https://github.com/huggingface/datasets/issues/3738 | For data-only datasets, streaming and non-streaming don't behave the same | Why do we want to concatenate the files? Is it the expected behavior for most datasets that lack a script and dataset info? | See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets as ds
iterable_dataset = ds.load_dataset("huggingface/transformers-metadat... | 23 | For data-only datasets, streaming and non-streaming don't behave the same
See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets... | [
-0.1206139624118805,
-0.5383895635604858,
0.05156758800148964,
0.170586958527565,
0.3425414562225342,
0.11740117520093918,
0.22001303732395172,
0.19887562096118927,
-0.087235227227211,
0.18944966793060303,
-0.3170534372329712,
0.10434246063232422,
-0.01308619137853384,
0.2876330018043518,
... |
https://github.com/huggingface/datasets/issues/3738 | For data-only datasets, streaming and non-streaming don't behave the same | These files are two different dataset configurations since they don't share the same schema.
IMO the streaming mode should fail in this case, as @albertvillanova said.
There is one challenge though: inferring the schema from the first example is not robust enough in the general case - especially if some fields ar... | See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets as ds
iterable_dataset = ds.load_dataset("huggingface/transformers-metadat... | 67 | For data-only datasets, streaming and non-streaming don't behave the same
See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets... | [
-0.24125999212265015,
-0.5383825898170471,
0.02704993262887001,
0.20546691119670868,
0.2709468603134155,
0.009080685675144196,
0.1926286816596985,
0.06340727210044861,
0.07024607062339783,
-0.07957005500793457,
-0.3011707067489624,
0.06835544854402542,
-0.2525921165943146,
0.36796993017196... |
https://github.com/huggingface/datasets/issues/3738 | For data-only datasets, streaming and non-streaming don't behave the same | OK. So, if we make the streaming also fail, the dataset https://huggingface.co/datasets/huggingface/transformers-metadata will never be [viewable](https://github.com/huggingface/datasets-preview-backend/issues/144) (be it using streaming or fallback to downloading the files), right?
| See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets as ds
iterable_dataset = ds.load_dataset("huggingface/transformers-metadat... | 27 | For data-only datasets, streaming and non-streaming don't behave the same
See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets... | [
-0.14785946905612946,
-0.44949695467948914,
-0.07414171099662781,
0.21037867665290833,
0.21058869361877441,
0.052201591432094574,
0.0881877988576889,
0.09130343794822693,
-0.04079173505306244,
0.04632670432329178,
-0.3037818372249603,
0.05750623717904091,
-0.22364242374897003,
0.2118002325... |
https://github.com/huggingface/datasets/issues/3738 | For data-only datasets, streaming and non-streaming don't behave the same | Yes, until we have a way for the user to specify explicitly that those two files are different configurations.
We can maybe have some rule to detect this automatically, maybe checking the first line of each file ? That would mean that for dataset of 10,000+ files we would have to verify every single one of them just... | See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets as ds
iterable_dataset = ds.load_dataset("huggingface/transformers-metadat... | 77 | For data-only datasets, streaming and non-streaming don't behave the same
See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets... | [
-0.30824705958366394,
-0.5184178352355957,
-0.03824286162853241,
0.3086872100830078,
0.23990653455257416,
-0.17774538695812225,
0.15990039706230164,
0.22859619557857513,
0.031077198684215546,
0.14849837124347687,
-0.31343117356300354,
0.07603003084659576,
-0.23141686618328094,
0.3043785691... |
https://github.com/huggingface/datasets/issues/3738 | For data-only datasets, streaming and non-streaming don't behave the same | i think requiring the user to specify that those two files are different configurations is in that case perfectly reasonable.
(Maybe at some point we could however detect this type of case and prompt them to define a config mapping etc) | See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets as ds
iterable_dataset = ds.load_dataset("huggingface/transformers-metadat... | 41 | For data-only datasets, streaming and non-streaming don't behave the same
See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets... | [
-0.2233445644378662,
-0.4214347302913666,
-0.0021985508501529694,
0.13391707837581635,
0.23012080788612366,
-0.0035508722066879272,
0.2808355987071991,
0.16709376871585846,
0.09981317818164825,
0.2093735635280609,
-0.28858914971351624,
0.11029200255870819,
-0.13433758914470673,
0.236663177... |
https://github.com/huggingface/datasets/issues/3738 | For data-only datasets, streaming and non-streaming don't behave the same | OK, so, before closing the issue, what do you think should be done?
> Maybe in streaming mode we should keep the schema (inferred from the first item) and throw an exception if a subsequent item does not conform to the inferred schema?
or nothing? | See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets as ds
iterable_dataset = ds.load_dataset("huggingface/transformers-metadat... | 45 | For data-only datasets, streaming and non-streaming don't behave the same
See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets... | [
-0.1384042650461197,
-0.4757504463195801,
0.053856853395700455,
0.2831658720970154,
0.3996581435203552,
0.01131846010684967,
0.060753095895051956,
0.20395627617835999,
0.011116720736026764,
0.010574452579021454,
-0.1794576644897461,
0.12958168983459473,
-0.26061394810676575,
0.304591834545... |
https://github.com/huggingface/datasets/issues/3738 | For data-only datasets, streaming and non-streaming don't behave the same | We should at least raise an error if a new sample has column names that are missing, or if it has extra columns. No need to check for the type for now.
I'm in favor of having an error especially because we want to avoid silent issues as much as possible - i.e. when something goes wrong (when schemas don't match or s... | See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets as ds
iterable_dataset = ds.load_dataset("huggingface/transformers-metadat... | 79 | For data-only datasets, streaming and non-streaming don't behave the same
See https://huggingface.co/datasets/huggingface/transformers-metadata: it only contains two JSON files.
In streaming mode, the files are concatenated, and thus the rows might be dictionaries with different keys:
```python
import datasets... | [
-0.1809254288673401,
-0.5316243171691895,
0.031650856137275696,
0.06017812713980675,
0.32635223865509033,
0.00845307856798172,
0.18688896298408508,
0.2202480137348175,
0.09264631569385529,
0.20878657698631287,
-0.16341999173164368,
0.050650645047426224,
-0.20153991878032684,
0.245684698224... |
https://github.com/huggingface/datasets/issues/3735 | Performance of `datasets` at scale | The most surprising part to me is the saving time. Wondering if it could be due to compression (`ParquetWriter` uses SNAPPY compression by default; it can be turned off with `to_parquet(..., compression=None)`). | # Performance of `datasets` at 1TB scale
## What is this?
During the processing of a large dataset I monitored the performance of the `datasets` library to see if there are any bottlenecks. The insights of this analysis could guide the decision making to improve the performance of the library.
## Dataset
The da... | 32 | Performance of `datasets` at scale
# Performance of `datasets` at 1TB scale
## What is this?
During the processing of a large dataset I monitored the performance of the `datasets` library to see if there are any bottlenecks. The insights of this analysis could guide the decision making to improve the performance ... | [
-0.4659070372581482,
-0.03345155715942383,
-0.1042620986700058,
0.18151339888572693,
0.09017282724380493,
0.04111830145120621,
0.17511098086833954,
0.30042290687561035,
0.1423732191324234,
-0.020190834999084473,
0.07610449939966202,
0.19214096665382385,
-0.03616265580058098,
0.574963033199... |
https://github.com/huggingface/datasets/issues/3735 | Performance of `datasets` at scale | +1 to what @mariosasko mentioned. Also, @lvwerra did you parallelize `to_parquet` using similar approach in #2747? (we used multiprocessing at the shard level). I'm working on a similar PR to add multi_proc in `to_parquet` which might give you further speed up.
Stas benchmarked his approach and mine in this [gist](ht... | # Performance of `datasets` at 1TB scale
## What is this?
During the processing of a large dataset I monitored the performance of the `datasets` library to see if there are any bottlenecks. The insights of this analysis could guide the decision making to improve the performance of the library.
## Dataset
The da... | 63 | Performance of `datasets` at scale
# Performance of `datasets` at 1TB scale
## What is this?
During the processing of a large dataset I monitored the performance of the `datasets` library to see if there are any bottlenecks. The insights of this analysis could guide the decision making to improve the performance ... | [
-0.4659070372581482,
-0.03345155715942383,
-0.1042620986700058,
0.18151339888572693,
0.09017282724380493,
0.04111830145120621,
0.17511098086833954,
0.30042290687561035,
0.1423732191324234,
-0.020190834999084473,
0.07610449939966202,
0.19214096665382385,
-0.03616265580058098,
0.574963033199... |
https://github.com/huggingface/datasets/issues/3735 | Performance of `datasets` at scale | @mariosasko I did not turn it off but I can try the next time - I have to run the pipeline again, anyway.
@bhavitvyamalik Yes, I also sharded the dataset and used multiprocessing to save each shard. I'll have a closer look at your approach, too. | # Performance of `datasets` at 1TB scale
## What is this?
During the processing of a large dataset I monitored the performance of the `datasets` library to see if there are any bottlenecks. The insights of this analysis could guide the decision making to improve the performance of the library.
## Dataset
The da... | 46 | Performance of `datasets` at scale
# Performance of `datasets` at 1TB scale
## What is this?
During the processing of a large dataset I monitored the performance of the `datasets` library to see if there are any bottlenecks. The insights of this analysis could guide the decision making to improve the performance ... | [
-0.4659070372581482,
-0.03345155715942383,
-0.1042620986700058,
0.18151339888572693,
0.09017282724380493,
0.04111830145120621,
0.17511098086833954,
0.30042290687561035,
0.1423732191324234,
-0.020190834999084473,
0.07610449939966202,
0.19214096665382385,
-0.03616265580058098,
0.574963033199... |
https://github.com/huggingface/datasets/issues/3735 | Performance of `datasets` at scale | Is there a way to read from the cache files directly as a dataset in its own | # Performance of `datasets` at 1TB scale
## What is this?
During the processing of a large dataset I monitored the performance of the `datasets` library to see if there are any bottlenecks. The insights of this analysis could guide the decision making to improve the performance of the library.
## Dataset
The da... | 17 | Performance of `datasets` at scale
# Performance of `datasets` at 1TB scale
## What is this?
During the processing of a large dataset I monitored the performance of the `datasets` library to see if there are any bottlenecks. The insights of this analysis could guide the decision making to improve the performance ... | [
-0.4659070372581482,
-0.03345155715942383,
-0.1042620986700058,
0.18151339888572693,
0.09017282724380493,
0.04111830145120621,
0.17511098086833954,
0.30042290687561035,
0.1423732191324234,
-0.020190834999084473,
0.07610449939966202,
0.19214096665382385,
-0.03616265580058098,
0.574963033199... |
https://github.com/huggingface/datasets/issues/3730 | Checksum Error when loading multi-news dataset | Thanks for reporting @byw2.
We are fixing it.
In the meantime, you can load the dataset by passing `ignore_verifications=True`:
```python
dataset = load_dataset("multi_news", ignore_verifications=True) | ## Describe the bug
When using the load_dataset function from datasets module to load the Multi-News dataset, does not load the dataset but throws Checksum Error instead.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("multi_news")
```
## Expected results
... | 24 | Checksum Error when loading multi-news dataset
## Describe the bug
When using the load_dataset function from datasets module to load the Multi-News dataset, does not load the dataset but throws Checksum Error instead.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_data... | [
-0.20598426461219788,
0.11974714696407318,
-0.05310001224279404,
0.32886505126953125,
0.1786070466041565,
0.048946790397167206,
0.3487614691257477,
0.2491249293088913,
0.2209574431180954,
0.00421585887670517,
-0.020120589062571526,
0.13272623717784882,
0.07971002161502838,
0.24589170515537... |
https://github.com/huggingface/datasets/issues/3729 | Wrong number of examples when loading a text dataset | Hi @kg-nlp, thanks for reporting.
That is weird... I guess we would need some sample data file where this behavior appears to reproduce the bug for further investigation... | ## Describe the bug
when I use load_dataset to read a txt file I find that the number of the samples is incorrect
## Steps to reproduce the bug
```
fr = open('train.txt','r',encoding='utf-8').readlines()
print(len(fr)) # 1199637
datasets = load_dataset('text', data_files={'train': ['train.txt']}, streaming... | 28 | Wrong number of examples when loading a text dataset
## Describe the bug
when I use load_dataset to read a txt file I find that the number of the samples is incorrect
## Steps to reproduce the bug
```
fr = open('train.txt','r',encoding='utf-8').readlines()
print(len(fr)) # 1199637
datasets = load_dataset... | [
-0.06052640452980995,
-0.24175813794136047,
-0.03442132845520973,
0.48381704092025757,
0.06591614335775375,
0.02623872458934784,
0.5079739689826965,
0.04723528027534485,
-0.023038756102323532,
0.18746845424175262,
0.4448873996734619,
0.18947719037532806,
0.07577656209468842,
0.025592142716... |
https://github.com/huggingface/datasets/issues/3729 | Wrong number of examples when loading a text dataset | ok, I found the reason why that two results are not same.
there is /u2029 in the text, the datasets will split sentence according to the /u2029,but when I use open function will not do that .
so I want to know which function shell do that
thanks | ## Describe the bug
when I use load_dataset to read a txt file I find that the number of the samples is incorrect
## Steps to reproduce the bug
```
fr = open('train.txt','r',encoding='utf-8').readlines()
print(len(fr)) # 1199637
datasets = load_dataset('text', data_files={'train': ['train.txt']}, streaming... | 48 | Wrong number of examples when loading a text dataset
## Describe the bug
when I use load_dataset to read a txt file I find that the number of the samples is incorrect
## Steps to reproduce the bug
```
fr = open('train.txt','r',encoding='utf-8').readlines()
print(len(fr)) # 1199637
datasets = load_dataset... | [
-0.11797744035720825,
-0.31096574664115906,
-0.0979497879743576,
0.5308281779289246,
-0.2185829132795334,
-0.2745322287082672,
0.4456658363342285,
-0.09811486303806305,
-0.09774923324584961,
0.2998819649219513,
0.19979315996170044,
0.19970500469207764,
0.22520242631435394,
0.08371881395578... |
https://github.com/huggingface/datasets/issues/3720 | Builder Configuration Update Required on Common Voice Dataset | Hi @aasem, thanks for reporting.
Please note that currently Commom Voice is hosted on our Hub as a community dataset by the Mozilla Foundation. See all Common Voice versions here: https://huggingface.co/mozilla-foundation
Maybe we should add an explaining note in our "legacy" Common Voice canonical script? What d... | Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found. I checked the source file here for the languages support:
ht... | 52 | Builder Configuration Update Required on Common Voice Dataset
Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found.... | [
-0.2856743037700653,
0.1739172637462616,
0.0023721661418676376,
-0.15214931964874268,
0.17979256808757782,
0.17955553531646729,
0.036190859973430634,
0.18139781057834625,
-0.46385133266448975,
0.1273629516363144,
0.09287213534116745,
-0.051489897072315216,
-0.04037579149007797,
-0.25951817... |
https://github.com/huggingface/datasets/issues/3720 | Builder Configuration Update Required on Common Voice Dataset | Thank you, @albertvillanova, for the quick response. I am not sure about the exact flow but I guess adding the following lines under the `_Languages` dictionary definition in [common_voice.py](https://github.com/huggingface/datasets/blob/master/datasets/common_voice/common_voice.py) might resolve the issue. I guess the... | Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found. I checked the source file here for the languages support:
ht... | 66 | Builder Configuration Update Required on Common Voice Dataset
Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found.... | [
-0.29083582758903503,
0.005558297038078308,
0.020420856773853302,
-0.0029066577553749084,
0.21368247270584106,
0.13129141926765442,
0.00759478285908699,
0.22258998453617096,
-0.380075067281723,
0.2097702920436859,
0.12131337076425552,
-0.05676203593611717,
-0.12005314975976944,
-0.06592711... |
https://github.com/huggingface/datasets/issues/3720 | Builder Configuration Update Required on Common Voice Dataset | @aasem for compliance reasons, we are no longer updating the `common_voice.py` script.
We agreed with Mozilla Foundation to use their community datasets instead, which will ask you to accept their terms of use:
```
You need to share your contact information to access this dataset.
This repository is publicly ac... | Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found. I checked the source file here for the languages support:
ht... | 192 | Builder Configuration Update Required on Common Voice Dataset
Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found.... | [
-0.2701788544654846,
0.18464946746826172,
0.021617930382490158,
-0.04671455919742584,
0.2218095064163208,
0.13419082760810852,
0.0782257542014122,
0.26119372248649597,
-0.3444998264312744,
0.20424342155456543,
0.08358855545520782,
0.0007253875373862684,
-0.055036045610904694,
-0.2131642550... |
https://github.com/huggingface/datasets/issues/3720 | Builder Configuration Update Required on Common Voice Dataset | @albertvillanova
>Maybe we should add an explaining note in our "legacy" Common Voice canonical script?
Yes, I agree we should have a deprecation notice in the canonical script to redirect users to the new script. | Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found. I checked the source file here for the languages support:
ht... | 35 | Builder Configuration Update Required on Common Voice Dataset
Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found.... | [
-0.3522530794143677,
0.10331860184669495,
0.02012266218662262,
-0.13264434039592743,
0.17105381190776825,
0.17201891541481018,
0.06308212131261826,
0.27318787574768066,
-0.30633172392845154,
0.15582646429538727,
0.16807614266872406,
-0.04260115325450897,
-0.16027240455150604,
-0.0915837287... |
https://github.com/huggingface/datasets/issues/3720 | Builder Configuration Update Required on Common Voice Dataset | @albertvillanova,
I now get the following error after downloading my access token from the huggingface and passing it to `load_dataset` call:
`AttributeError: 'DownloadManager' object has no attribute 'download_config'`
Any quick pointer on how it might be resolved? | Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found. I checked the source file here for the languages support:
ht... | 37 | Builder Configuration Update Required on Common Voice Dataset
Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found.... | [
-0.3459947109222412,
0.1322571337223053,
0.054721686989068985,
0.12855365872383118,
0.2149554044008255,
0.1292428970336914,
-0.05094834044575691,
0.12706686556339264,
-0.24479302763938904,
0.23972827196121216,
0.026499101892113686,
-0.15096090734004974,
-0.15113885700702667,
-0.02139007858... |
https://github.com/huggingface/datasets/issues/3720 | Builder Configuration Update Required on Common Voice Dataset | @aasem What version of `datasets` are you using? We renamed that attribute from `_download_config` to `download_conig` fairly recently, so updating to the newest version should resolve the issue:
```
pip install -U datasets
``` | Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found. I checked the source file here for the languages support:
ht... | 34 | Builder Configuration Update Required on Common Voice Dataset
Missing language in Common Voice dataset
**Link:** https://huggingface.co/datasets/common_voice
I tried to call the Urdu dataset using `load_dataset("common_voice", "ur", split="train+validation")` but couldn't due to builder configuration not found.... | [
-0.4302417039871216,
0.014460325241088867,
-0.006632164120674133,
-0.019177615642547607,
0.29997003078460693,
0.13268429040908813,
-0.04748347029089928,
0.2533233165740967,
-0.24364204704761505,
0.2547217011451721,
0.11823796480894089,
0.04076673462986946,
-0.10102228820323944,
-0.07043406... |
https://github.com/huggingface/datasets/issues/3717 | wrong condition in `Features ClassLabel encode_example` | Hi @Tudyx,
Please note that in Python, the boolean NOT operator (`not`) has lower precedence than comparison operators (`<=`, `<`), thus the expression you mention is equivalent to:
```python
not (-1 <= example_data < self.num_classes)
```
Also note that as expected, the exception is raised if:
- `example_d... | ## Describe the bug
The `encode_example` function in *features.py* seems to have a wrong condition.
```python
if not -1 <= example_data < self.num_classes:
raise ValueError(f"Class label {example_data:d} greater than configured num_classes {self.num_classes}")
```
## Expected results
The `not - 1` co... | 71 | wrong condition in `Features ClassLabel encode_example`
## Describe the bug
The `encode_example` function in *features.py* seems to have a wrong condition.
```python
if not -1 <= example_data < self.num_classes:
raise ValueError(f"Class label {example_data:d} greater than configured num_classes {self.num_... | [
0.1392001211643219,
-0.11683483421802521,
-0.04643397778272629,
0.2833450436592102,
0.22576768696308136,
-0.09283696860074997,
0.22754710912704468,
0.24462483823299408,
-0.18541304767131805,
0.016368038952350616,
0.3163583278656006,
0.33227646350860596,
-0.21806931495666504,
0.417782157659... |
https://github.com/huggingface/datasets/issues/3708 | Loading JSON gets stuck with many workers/threads | Hi ! Note that it does `block_size *= 2` until `block_size > len(batch)`, so it doesn't loop indefinitely. What do you mean by "get stuck indefinitely" then ? Is this the actual call to `paj.read_json` that hangs ?
> increasing the `chunksize` argument decreases the chance of getting stuck
Could you share the val... | ## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following script to reproduce the issue:
```python
from dat... | 78 | Loading JSON gets stuck with many workers/threads
## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following... | [
-0.2772899866104126,
-0.18320442736148834,
-0.10265117883682251,
0.19064389169216156,
0.13199660181999207,
-0.06906939297914505,
0.42680642008781433,
0.25223931670188904,
0.29133129119873047,
0.18143394589424133,
0.18074795603752136,
0.5573155283927917,
0.11018436402082443,
-0.272552520036... |
https://github.com/huggingface/datasets/issues/3708 | Loading JSON gets stuck with many workers/threads | To clarify, I don't think it loops indefinitely but the `paj.read_json` gets stuck after the first try. That's why I think it could be an issue with a lock somewhere.
Using `load_dataset(..., chunksize=40<<20)` worked without errors. | ## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following script to reproduce the issue:
```python
from dat... | 36 | Loading JSON gets stuck with many workers/threads
## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following... | [
-0.2772899866104126,
-0.18320442736148834,
-0.10265117883682251,
0.19064389169216156,
0.13199660181999207,
-0.06906939297914505,
0.42680642008781433,
0.25223931670188904,
0.29133129119873047,
0.18143394589424133,
0.18074795603752136,
0.5573155283927917,
0.11018436402082443,
-0.272552520036... |
https://github.com/huggingface/datasets/issues/3708 | Loading JSON gets stuck with many workers/threads | @lhoestq I encountered another related issue. I use load_dataset() for my json data and set_transform() for preprocessing. But it hangs at the end of the epoch if `dataloader_num_workers>=1`. It appears to be working fine with num_worker=0, but it's slow.
```
train_dataset = datasets.load_dataset("json",
... | ## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following script to reproduce the issue:
```python
from dat... | 49 | Loading JSON gets stuck with many workers/threads
## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following... | [
-0.2772899866104126,
-0.18320442736148834,
-0.10265117883682251,
0.19064389169216156,
0.13199660181999207,
-0.06906939297914505,
0.42680642008781433,
0.25223931670188904,
0.29133129119873047,
0.18143394589424133,
0.18074795603752136,
0.5573155283927917,
0.11018436402082443,
-0.272552520036... |
https://github.com/huggingface/datasets/issues/3708 | Loading JSON gets stuck with many workers/threads | I couldn't I think your problem is unrelated to this issue @memray
Indeed this issue discusses a bug when doing `load_dataset`, while your case has to do with the dataloader in a multiprocessing setup. Can you open a new issue and provide more details (share your env and what psg_parse_fn does) ? | ## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following script to reproduce the issue:
```python
from dat... | 52 | Loading JSON gets stuck with many workers/threads
## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following... | [
-0.2772899866104126,
-0.18320442736148834,
-0.10265117883682251,
0.19064389169216156,
0.13199660181999207,
-0.06906939297914505,
0.42680642008781433,
0.25223931670188904,
0.29133129119873047,
0.18143394589424133,
0.18074795603752136,
0.5573155283927917,
0.11018436402082443,
-0.272552520036... |
https://github.com/huggingface/datasets/issues/3708 | Loading JSON gets stuck with many workers/threads | I also encountered a similar issue when loading a 190GB dataset of jsonl files (255 files with less than 1Gb) where it got stuck for over 20h at tables generation (fig below), increasing the `chunksize` with `load_dataset(..., chunksize=40<<20)` fixed the issue
<img width="560" alt="image" src="https://user-images.g... | ## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following script to reproduce the issue:
```python
from dat... | 45 | Loading JSON gets stuck with many workers/threads
## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following... | [
-0.2772899866104126,
-0.18320442736148834,
-0.10265117883682251,
0.19064389169216156,
0.13199660181999207,
-0.06906939297914505,
0.42680642008781433,
0.25223931670188904,
0.29133129119873047,
0.18143394589424133,
0.18074795603752136,
0.5573155283927917,
0.11018436402082443,
-0.272552520036... |
https://github.com/huggingface/datasets/issues/3708 | Loading JSON gets stuck with many workers/threads | > @lhoestq I encountered another related issue. I use load_dataset() for my json data and set_transform() for preprocessing. But it hangs at the end of the epoch if `dataloader_num_workers>=1`. It appears to be working fine with num_worker=0, but it's slow.
>
> ```
> train_dataset = datasets.load_dataset("json",
... | ## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following script to reproduce the issue:
```python
from dat... | 132 | Loading JSON gets stuck with many workers/threads
## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following... | [
-0.2772899866104126,
-0.18320442736148834,
-0.10265117883682251,
0.19064389169216156,
0.13199660181999207,
-0.06906939297914505,
0.42680642008781433,
0.25223931670188904,
0.29133129119873047,
0.18143394589424133,
0.18074795603752136,
0.5573155283927917,
0.11018436402082443,
-0.272552520036... |
https://github.com/huggingface/datasets/issues/3708 | Loading JSON gets stuck with many workers/threads | I can confirm the issue using datasets (2.12.0) with the following code and Accelerate (0.20.3) env:
````
trainDataloader = DataLoader(trainSplit, batch_size=args.train_batch_size, shuffle=True)
evalDataloader = DataLoader(validSplit, batch_size=args.valid_batch_size) // Here is where it gets stuck.
````
````
-... | ## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following script to reproduce the issue:
```python
from dat... | 164 | Loading JSON gets stuck with many workers/threads
## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following... | [
-0.2772899866104126,
-0.18320442736148834,
-0.10265117883682251,
0.19064389169216156,
0.13199660181999207,
-0.06906939297914505,
0.42680642008781433,
0.25223931670188904,
0.29133129119873047,
0.18143394589424133,
0.18074795603752136,
0.5573155283927917,
0.11018436402082443,
-0.272552520036... |
https://github.com/huggingface/datasets/issues/3708 | Loading JSON gets stuck with many workers/threads | I think your issue is related to `accelerate`, feel free to open an issue there: https://github.com/huggingface/accelerate/issues
`Dataset` objects generally work fine with the torch DataLoader, idk what `accelerate` does that could make it get stuck. | ## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following script to reproduce the issue:
```python
from dat... | 35 | Loading JSON gets stuck with many workers/threads
## Describe the bug
Loading a JSON dataset with `load_dataset` can get stuck when running on a machine with many CPUs. This is especially an issue when loading a large dataset on a large machine.
## Steps to reproduce the bug
I originally created the following... | [
-0.2772899866104126,
-0.18320442736148834,
-0.10265117883682251,
0.19064389169216156,
0.13199660181999207,
-0.06906939297914505,
0.42680642008781433,
0.25223931670188904,
0.29133129119873047,
0.18143394589424133,
0.18074795603752136,
0.5573155283927917,
0.11018436402082443,
-0.272552520036... |
https://github.com/huggingface/datasets/issues/3707 | `.select`: unexpected behavior with `indices` | Hi! Currently, we compute the final index as `index % len(dset)`. I agree this behavior is somewhat unexpected and that it would be more appropriate to raise an error instead (this is what `df.iloc` in Pandas does, for instance).
@albertvillanova @lhoestq wdyt? | ## Describe the bug
The `.select` method will not throw when sending `indices` bigger than the dataset length; `indices` will be wrapped instead. This behavior is not documented anywhere, and is not intuitive.
## Steps to reproduce the bug
```python
from datasets import Dataset
ds = Dataset.from_dict({"text": [... | 42 | `.select`: unexpected behavior with `indices`
## Describe the bug
The `.select` method will not throw when sending `indices` bigger than the dataset length; `indices` will be wrapped instead. This behavior is not documented anywhere, and is not intuitive.
## Steps to reproduce the bug
```python
from datasets i... | [
-0.14067944884300232,
-0.22004061937332153,
-0.016400668770074844,
0.4212479591369629,
0.08051306754350662,
-0.0664442926645279,
0.3318192660808563,
0.1800905466079712,
0.22601184248924255,
0.3523017466068268,
0.055006176233291626,
0.5035144686698914,
0.24901850521564484,
0.055146194994449... |
https://github.com/huggingface/datasets/issues/3707 | `.select`: unexpected behavior with `indices` | I agree. I think `index % len(dset)` was used to support negative indices.
I think this needs to be fixed in `datasets.formatting.formatting._check_valid_index_key` if I'm not mistaken | ## Describe the bug
The `.select` method will not throw when sending `indices` bigger than the dataset length; `indices` will be wrapped instead. This behavior is not documented anywhere, and is not intuitive.
## Steps to reproduce the bug
```python
from datasets import Dataset
ds = Dataset.from_dict({"text": [... | 26 | `.select`: unexpected behavior with `indices`
## Describe the bug
The `.select` method will not throw when sending `indices` bigger than the dataset length; `indices` will be wrapped instead. This behavior is not documented anywhere, and is not intuitive.
## Steps to reproduce the bug
```python
from datasets i... | [
-0.1581113338470459,
-0.2566550374031067,
-0.03184891492128372,
0.34394264221191406,
0.06200988590717316,
-0.11534824967384338,
0.21475188434123993,
0.15043526887893677,
0.047420989722013474,
0.17876982688903809,
0.023443033918738365,
0.4659055769443512,
0.11044954508543015,
0.206328913569... |
https://github.com/huggingface/datasets/issues/3706 | Unable to load dataset 'big_patent' | Hi @ankitk2109,
Have you tried passing the split name with the keyword `split=`? See e.g. an example in our Quick Start docs: https://huggingface.co/docs/datasets/quickstart.html#load-the-dataset-and-model
```python
ds = load_dataset("big_patent", "d", split="validation") | ## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFoundError}Local file ..\huggingface\dat... | 29 | Unable to load dataset 'big_patent'
## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFo... | [
-0.2909577786922455,
-0.44364190101623535,
-0.03627193346619606,
0.4938032031059265,
0.34715038537979126,
0.168075293302536,
0.11011752486228943,
0.2599291503429413,
0.12326636910438538,
0.01313801109790802,
-0.3273754119873047,
0.04128440469503403,
-0.07397891581058502,
0.4042492508888244... |
https://github.com/huggingface/datasets/issues/3706 | Unable to load dataset 'big_patent' | Hi @albertvillanova,
Thanks for your response.
Yes, I tried the `split='validation'` as well. But getting the same issue. | ## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFoundError}Local file ..\huggingface\dat... | 18 | Unable to load dataset 'big_patent'
## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFo... | [
-0.28484633564949036,
-0.06062144786119461,
-0.063939169049263,
0.5759012699127197,
0.2154281884431839,
0.12280838936567307,
0.23104867339134216,
0.4681130647659302,
0.16158777475357056,
0.026663027703762054,
-0.234244242310524,
0.04546754062175751,
-0.015703167766332626,
0.167709976434707... |
https://github.com/huggingface/datasets/issues/3706 | Unable to load dataset 'big_patent' | I'm sorry, but I can't reproduce your problem:
```python
In [5]: ds = load_dataset("big_patent", "d", split="validation")
Downloading and preparing dataset big_patent/d (download: 6.01 GiB, generated: 169.61 MiB, post-processed: Unknown size, total: 6.17 GiB) to .../.cache/big_patent/d/1.0.0/bdefa7c0b39fba8bba1c6331... | ## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFoundError}Local file ..\huggingface\dat... | 72 | Unable to load dataset 'big_patent'
## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFo... | [
-0.3682876229286194,
-0.07301953434944153,
-0.0981641411781311,
0.48668086528778076,
0.2612975239753723,
0.10870485752820969,
0.1902628391981125,
0.45334288477897644,
0.13285064697265625,
0.05079057812690735,
-0.14896470308303833,
0.040835022926330566,
-0.04699631780385971,
0.1007055565714... |
https://github.com/huggingface/datasets/issues/3706 | Unable to load dataset 'big_patent' | Maybe you had a connection issue while downloading the file and this was corrupted?
Our cache system uses the file you downloaded first time.
If so, you could try forcing redownload of the file with:
```python
ds = load_dataset("big_patent", "d", split="validation", download_mode="force_redownload") | ## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFoundError}Local file ..\huggingface\dat... | 42 | Unable to load dataset 'big_patent'
## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFo... | [
-0.32430216670036316,
-0.06346441805362701,
-0.09108039736747742,
0.4624115228652954,
0.2718912363052368,
0.1327952742576599,
0.17785097658634186,
0.3625103533267975,
0.21146269142627716,
0.013644777238368988,
-0.1294030249118805,
0.031082211062312126,
-0.010853826068341732,
0.059187054634... |
https://github.com/huggingface/datasets/issues/3706 | Unable to load dataset 'big_patent' | I am able to download the dataset with ``` download_mode="force_redownload"```. As you mentioned it was an issue with the cached version which was failed earlier due to a network issue. I am closing the issue now, once again thank you. | ## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFoundError}Local file ..\huggingface\dat... | 40 | Unable to load dataset 'big_patent'
## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFo... | [
-0.29007527232170105,
-0.03358732908964157,
-0.061299435794353485,
0.5121248960494995,
0.2357623428106308,
0.11991851776838303,
0.2026655077934265,
0.41820603609085083,
0.14938883483409882,
-0.05368085205554962,
-0.13018383085727692,
-0.0023702604230493307,
-0.022968586534261703,
0.0843352... |
https://github.com/huggingface/datasets/issues/3704 | OSCAR-2109 datasets are misaligned and truncated | Hi @adrianeboyd, thanks for reporting.
There is indeed a bug in that community dataset:
Line:
```python
metadata_and_text_files = list(zip(metadata_files, text_files))
```
should be replaced with
```python
metadata_and_text_files = list(zip(sorted(metadata_files), sorted(text_files)))
```
I am going to c... | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the par... | 51 | OSCAR-2109 datasets are misaligned and truncated
## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few exampl... | [
-0.379007488489151,
0.35093584656715393,
0.01644602045416832,
0.5407816171646118,
-0.1386849284172058,
0.014725901186466217,
0.2296266108751297,
0.37006452679634094,
-0.30476540327072144,
-0.09907041490077972,
0.03619241714477539,
-0.06419703364372253,
0.1635015457868576,
-0.06320275366306... |
https://github.com/huggingface/datasets/issues/3704 | OSCAR-2109 datasets are misaligned and truncated | That fix is part of it, but it's clearly not the only issue.
I also already contacted the OSCAR creators, but I reported it here because it looked like huggingface members were the main authors in the git history. Is there a better place to have reported this? | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the par... | 48 | OSCAR-2109 datasets are misaligned and truncated
## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few exampl... | [
-0.379007488489151,
0.35093584656715393,
0.01644602045416832,
0.5407816171646118,
-0.1386849284172058,
0.014725901186466217,
0.2296266108751297,
0.37006452679634094,
-0.30476540327072144,
-0.09907041490077972,
0.03619241714477539,
-0.06419703364372253,
0.1635015457868576,
-0.06320275366306... |
https://github.com/huggingface/datasets/issues/3704 | OSCAR-2109 datasets are misaligned and truncated | Hello,
We've had an issue that could be linked to this one here: https://github.com/oscar-corpus/corpus/issues/15.
I have been spot checking the source (`.txt`/`.jsonl`) files for a while, and have not found issues, especially in the start/end of corpora (but I conceed that more integration testing would be neces... | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the par... | 118 | OSCAR-2109 datasets are misaligned and truncated
## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few exampl... | [
-0.379007488489151,
0.35093584656715393,
0.01644602045416832,
0.5407816171646118,
-0.1386849284172058,
0.014725901186466217,
0.2296266108751297,
0.37006452679634094,
-0.30476540327072144,
-0.09907041490077972,
0.03619241714477539,
-0.06419703364372253,
0.1635015457868576,
-0.06320275366306... |
https://github.com/huggingface/datasets/issues/3704 | OSCAR-2109 datasets are misaligned and truncated | I'm happy to move the discussion to the other repo!
Merely sorting the files only **maybe** fixes the processing of the first part. If the first part contains non-unix newlines, it will still be misaligned/truncated, and all the following parts will be truncated with incorrect text offsets and metadata due the offse... | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the par... | 55 | OSCAR-2109 datasets are misaligned and truncated
## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few exampl... | [
-0.379007488489151,
0.35093584656715393,
0.01644602045416832,
0.5407816171646118,
-0.1386849284172058,
0.014725901186466217,
0.2296266108751297,
0.37006452679634094,
-0.30476540327072144,
-0.09907041490077972,
0.03619241714477539,
-0.06419703364372253,
0.1635015457868576,
-0.06320275366306... |
https://github.com/huggingface/datasets/issues/3704 | OSCAR-2109 datasets are misaligned and truncated | Hi @Uinelj, This is a total noobs question but how can I integrate that bugfix into my code? I reinstalled the datasets library this time from source. Should that have fixed the issue? I am still facing the misalignment issue. Do I need to download the dataset from scratch? | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the par... | 49 | OSCAR-2109 datasets are misaligned and truncated
## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few exampl... | [
-0.379007488489151,
0.35093584656715393,
0.01644602045416832,
0.5407816171646118,
-0.1386849284172058,
0.014725901186466217,
0.2296266108751297,
0.37006452679634094,
-0.30476540327072144,
-0.09907041490077972,
0.03619241714477539,
-0.06419703364372253,
0.1635015457868576,
-0.06320275366306... |
https://github.com/huggingface/datasets/issues/3704 | OSCAR-2109 datasets are misaligned and truncated | Sorry @norakassner for the late reply.
There are indeed several issues creating the misalignment, as @adrianeboyd cleverly pointed out:
- https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/commit/3cd7e95aa1799b73c5ea8afc3989635f3e19b86b fixed one of them
- but there are still others to be fixed | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the par... | 34 | OSCAR-2109 datasets are misaligned and truncated
## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few exampl... | [
-0.379007488489151,
0.35093584656715393,
0.01644602045416832,
0.5407816171646118,
-0.1386849284172058,
0.014725901186466217,
0.2296266108751297,
0.37006452679634094,
-0.30476540327072144,
-0.09907041490077972,
0.03619241714477539,
-0.06419703364372253,
0.1635015457868576,
-0.06320275366306... |
https://github.com/huggingface/datasets/issues/3704 | OSCAR-2109 datasets are misaligned and truncated | Normally, the issues should be fixed now:
- Fix offset initialization for each file: https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/commit/1ad9b7bfe00798a9258a923b887bb1c8d732b833
- Disable default universal newline support: https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/commit/0c2f307d3167f03632f50... | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the par... | 35 | OSCAR-2109 datasets are misaligned and truncated
## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few exampl... | [
-0.379007488489151,
0.35093584656715393,
0.01644602045416832,
0.5407816171646118,
-0.1386849284172058,
0.014725901186466217,
0.2296266108751297,
0.37006452679634094,
-0.30476540327072144,
-0.09907041490077972,
0.03619241714477539,
-0.06419703364372253,
0.1635015457868576,
-0.06320275366306... |
https://github.com/huggingface/datasets/issues/3704 | OSCAR-2109 datasets are misaligned and truncated | Thanks for the updates!
The purist in me would still like to have the rstrip not strip additional characters from the original text (unicode whitespace mainly in practice, I think), but the differences are extremely small in practice and it doesn't actually matter for my current task:
```python
text = "".join([t... | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the par... | 56 | OSCAR-2109 datasets are misaligned and truncated
## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few exampl... | [
-0.379007488489151,
0.35093584656715393,
0.01644602045416832,
0.5407816171646118,
-0.1386849284172058,
0.014725901186466217,
0.2296266108751297,
0.37006452679634094,
-0.30476540327072144,
-0.09907041490077972,
0.03619241714477539,
-0.06419703364372253,
0.1635015457868576,
-0.06320275366306... |
https://github.com/huggingface/datasets/issues/3703 | ImportError: To be able to use this metric, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance' | Hi! Some of our metrics require additional dependencies to work. In your case, simply installing the `seqeval` package with `pip install seqeval` should resolve the issue. | hi :
I want to use the seqeval indicator because of direct load_ When metric ('seqeval '), it will prompt that the network connection fails. So I downloaded the seqeval Py to load locally. Loading code: metric = load_ metric(path='mymetric/seqeval/seqeval.py')
But tips:
Traceback (most recent call last):
File... | 26 | ImportError: To be able to use this metric, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance'
hi :
I want to use the seqeval indicator because of direct load_ When metric ('seqeval '), it will prompt that the network connection fails. So I downloaded the seqeval Py t... | [
-0.197947695851326,
-0.026132240891456604,
-0.046070173382759094,
0.048713989555835724,
0.2330714613199234,
-0.09667966514825821,
0.3034621775150299,
-0.0408191941678524,
0.1501881182193756,
0.2724969983100891,
-0.026502536609768867,
0.4663181006908417,
-0.1179603561758995,
-0.069747589528... |
https://github.com/huggingface/datasets/issues/3703 | ImportError: To be able to use this metric, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance' | > Hi! Some of our metrics require additional dependencies to work. In your case, simply installing the `seqeval` package with `pip install seqeval` should resolve the issue.
I installed seqeval, but still reported the same error. That's too bad.
| hi :
I want to use the seqeval indicator because of direct load_ When metric ('seqeval '), it will prompt that the network connection fails. So I downloaded the seqeval Py to load locally. Loading code: metric = load_ metric(path='mymetric/seqeval/seqeval.py')
But tips:
Traceback (most recent call last):
File... | 39 | ImportError: To be able to use this metric, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance'
hi :
I want to use the seqeval indicator because of direct load_ When metric ('seqeval '), it will prompt that the network connection fails. So I downloaded the seqeval Py t... | [
-0.20251406729221344,
-0.02795187383890152,
-0.046689920127391815,
0.047643713653087616,
0.22935093939304352,
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0.30647334456443787,
-0.04071475937962532,
0.1468656361103058,
0.27649083733558655,
-0.025231918320059776,
0.4661175310611725,
-0.11892586201429367,
-0.066972151... |
https://github.com/huggingface/datasets/issues/3703 | ImportError: To be able to use this metric, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance' | > > Hi! Some of our metrics require additional dependencies to work. In your case, simply installing the `seqeval` package with `pip install seqeval` should resolve the issue.
> > I installed seqeval, but still reported the same error. That's too bad.
Same issue here. What should I do to fix this error? Please help... | hi :
I want to use the seqeval indicator because of direct load_ When metric ('seqeval '), it will prompt that the network connection fails. So I downloaded the seqeval Py to load locally. Loading code: metric = load_ metric(path='mymetric/seqeval/seqeval.py')
But tips:
Traceback (most recent call last):
File... | 57 | ImportError: To be able to use this metric, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance'
hi :
I want to use the seqeval indicator because of direct load_ When metric ('seqeval '), it will prompt that the network connection fails. So I downloaded the seqeval Py t... | [
-0.20180603861808777,
-0.02735234797000885,
-0.04756743833422661,
0.04849603772163391,
0.23044028878211975,
-0.09998485445976257,
0.3054770231246948,
-0.041361380368471146,
0.1490330994129181,
0.27797701954841614,
-0.024893388152122498,
0.46552589535713196,
-0.11869300156831741,
-0.0632172... |
https://github.com/huggingface/datasets/issues/3703 | ImportError: To be able to use this metric, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance' | I tried to install **seqeval** package through anaconda instead of pip:
`conda install -c conda-forge seqeval`
It worked for me! | hi :
I want to use the seqeval indicator because of direct load_ When metric ('seqeval '), it will prompt that the network connection fails. So I downloaded the seqeval Py to load locally. Loading code: metric = load_ metric(path='mymetric/seqeval/seqeval.py')
But tips:
Traceback (most recent call last):
File... | 20 | ImportError: To be able to use this metric, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance'
hi :
I want to use the seqeval indicator because of direct load_ When metric ('seqeval '), it will prompt that the network connection fails. So I downloaded the seqeval Py t... | [
-0.20874692499637604,
0.03729201853275299,
-0.04659486189484596,
0.07232887297868729,
0.24121516942977905,
-0.055881768465042114,
0.2564864456653595,
-0.06052471324801445,
0.14196860790252686,
0.2192426323890686,
-0.05916895717382431,
0.44640204310417175,
-0.09567573666572571,
-0.005928598... |
https://github.com/huggingface/datasets/issues/3700 | Unable to load a dataset | Hi! `load_dataset` is intended to be used to load a canonical dataset (`wikipedia`), a packaged dataset (`csv`, `json`, ...) or a dataset hosted on the Hub. For local datasets saved with `save_to_disk("path/to/dataset")`, use `load_from_disk("path/to/dataset")`. | ## Describe the bug
Unable to load a dataset from Huggingface that I have just saved.
## Steps to reproduce the bug
On Google colab
`! pip install datasets `
`from datasets import load_dataset`
`my_path = "wiki_dataset"`
`dataset = load_dataset('wikipedia', "20200501.fr")`
`dataset.save_to_disk(my_path)`
`... | 34 | Unable to load a dataset
## Describe the bug
Unable to load a dataset from Huggingface that I have just saved.
## Steps to reproduce the bug
On Google colab
`! pip install datasets `
`from datasets import load_dataset`
`my_path = "wiki_dataset"`
`dataset = load_dataset('wikipedia', "20200501.fr")`
`datase... | [
-0.2790256142616272,
-0.29675570130348206,
0.041175905615091324,
0.626777172088623,
0.33209776878356934,
0.1287168562412262,
0.21450549364089966,
-0.003690488636493683,
0.315826416015625,
0.10092559456825256,
-0.23978771269321442,
0.3568316698074341,
-0.08903179317712784,
0.312253683805465... |
https://github.com/huggingface/datasets/issues/3688 | Pyarrow version error | Hi @Zaker237, thanks for reporting.
This is weird: the error you get is only thrown if the installed pyarrow version is less than 3.0.0.
Could you please check that you install pyarrow in the same Python virtual environment where you installed datasets?
From the Python command line (or terminal) where you get ... | ## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match this condition`.
i tryed w... | 64 | Pyarrow version error
## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match thi... | [
-0.42563366889953613,
0.22376024723052979,
-0.006954016163945198,
0.12079282104969025,
0.05905291438102722,
0.04665123671293259,
0.18775349855422974,
0.3738028407096863,
-0.26324498653411865,
-0.09773287177085876,
0.1039726659655571,
0.30188727378845215,
-0.16923603415489197,
-0.0959772393... |
https://github.com/huggingface/datasets/issues/3688 | Pyarrow version error | hi @albertvillanova i try yesterday to create a new python environement with python 7 and try it on the environement and it worked. so i think that the error was not the package but may be jupyter notebook on conda. still yet i'm not yet sure but it worked in an environment created with venv | ## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match this condition`.
i tryed w... | 55 | Pyarrow version error
## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match thi... | [
-0.42563366889953613,
0.22376024723052979,
-0.006954016163945198,
0.12079282104969025,
0.05905291438102722,
0.04665123671293259,
0.18775349855422974,
0.3738028407096863,
-0.26324498653411865,
-0.09773287177085876,
0.1039726659655571,
0.30188727378845215,
-0.16923603415489197,
-0.0959772393... |
https://github.com/huggingface/datasets/issues/3688 | Pyarrow version error | OK, thanks @Zaker237 for your feedback.
I close this issue then. Please, feel free to reopen it if the problem arises again. | ## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match this condition`.
i tryed w... | 22 | Pyarrow version error
## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match thi... | [
-0.42563366889953613,
0.22376024723052979,
-0.006954016163945198,
0.12079282104969025,
0.05905291438102722,
0.04665123671293259,
0.18775349855422974,
0.3738028407096863,
-0.26324498653411865,
-0.09773287177085876,
0.1039726659655571,
0.30188727378845215,
-0.16923603415489197,
-0.0959772393... |
https://github.com/huggingface/datasets/issues/3687 | Can't get the text data when calling to_tf_dataset | You are correct that `to_tf_dataset` only handles numerical columns right now, yes, though this is a limitation we might remove in future! The main reason we do this is that our models mostly do not include the tokenizer as a model layer, because it's very difficult to compile some of them in TF. So the "normal" Huggin... | I am working with the SST2 dataset, and am using TensorFlow 2.5
I'd like to convert it to a `tf.data.Dataset` by calling the `to_tf_dataset` method.
The following snippet is what I am using to achieve this:
```
from datasets import load_dataset
from transformers import DefaultDataCollator
data_collator = Defa... | 96 | Can't get the text data when calling to_tf_dataset
I am working with the SST2 dataset, and am using TensorFlow 2.5
I'd like to convert it to a `tf.data.Dataset` by calling the `to_tf_dataset` method.
The following snippet is what I am using to achieve this:
```
from datasets import load_dataset
from transforme... | [
0.30687639117240906,
-0.24205148220062256,
0.06828035414218903,
0.3844337463378906,
0.31130450963974,
0.120692677795887,
0.34276872873306274,
0.4319317638874054,
-0.14188791811466217,
0.14070266485214233,
-0.0737772062420845,
-0.037952736020088196,
0.03761741518974304,
0.36453738808631897,... |
https://github.com/huggingface/datasets/issues/3687 | Can't get the text data when calling to_tf_dataset | Thanks for the quick follow-up to my issue.
For my use-case, instead of the built-in tokenizers I wanted to use the `TextVectorization` layer to map from strings to integers. To achieve this, I came up with the following solution:
```
from datasets import load_dataset
from transformers import DefaultDataCollato... | I am working with the SST2 dataset, and am using TensorFlow 2.5
I'd like to convert it to a `tf.data.Dataset` by calling the `to_tf_dataset` method.
The following snippet is what I am using to achieve this:
```
from datasets import load_dataset
from transformers import DefaultDataCollator
data_collator = Defa... | 212 | Can't get the text data when calling to_tf_dataset
I am working with the SST2 dataset, and am using TensorFlow 2.5
I'd like to convert it to a `tf.data.Dataset` by calling the `to_tf_dataset` method.
The following snippet is what I am using to achieve this:
```
from datasets import load_dataset
from transforme... | [
0.30687639117240906,
-0.24205148220062256,
0.06828035414218903,
0.3844337463378906,
0.31130450963974,
0.120692677795887,
0.34276872873306274,
0.4319317638874054,
-0.14188791811466217,
0.14070266485214233,
-0.0737772062420845,
-0.037952736020088196,
0.03761741518974304,
0.36453738808631897,... |
https://github.com/huggingface/datasets/issues/3687 | Can't get the text data when calling to_tf_dataset | > For the future, however, it'd be more convenient to get the string data, since I am also inspecting the dataset (longest sentence, shortest sentence), which is more challenging when working with integer or float.
Yes, I agree, so let's keep this issue open. | I am working with the SST2 dataset, and am using TensorFlow 2.5
I'd like to convert it to a `tf.data.Dataset` by calling the `to_tf_dataset` method.
The following snippet is what I am using to achieve this:
```
from datasets import load_dataset
from transformers import DefaultDataCollator
data_collator = Defa... | 44 | Can't get the text data when calling to_tf_dataset
I am working with the SST2 dataset, and am using TensorFlow 2.5
I'd like to convert it to a `tf.data.Dataset` by calling the `to_tf_dataset` method.
The following snippet is what I am using to achieve this:
```
from datasets import load_dataset
from transforme... | [
0.30687639117240906,
-0.24205148220062256,
0.06828035414218903,
0.3844337463378906,
0.31130450963974,
0.120692677795887,
0.34276872873306274,
0.4319317638874054,
-0.14188791811466217,
0.14070266485214233,
-0.0737772062420845,
-0.037952736020088196,
0.03761741518974304,
0.36453738808631897,... |
https://github.com/huggingface/datasets/issues/3687 | Can't get the text data when calling to_tf_dataset | Going to close this now - methods like `to_tf_dataset` and `prepare_tf_dataset` now support string data, and have done for a while! If anyone sees this and is encountering issues with string data in those methods, please file a new issue! | I am working with the SST2 dataset, and am using TensorFlow 2.5
I'd like to convert it to a `tf.data.Dataset` by calling the `to_tf_dataset` method.
The following snippet is what I am using to achieve this:
```
from datasets import load_dataset
from transformers import DefaultDataCollator
data_collator = Defa... | 40 | Can't get the text data when calling to_tf_dataset
I am working with the SST2 dataset, and am using TensorFlow 2.5
I'd like to convert it to a `tf.data.Dataset` by calling the `to_tf_dataset` method.
The following snippet is what I am using to achieve this:
```
from datasets import load_dataset
from transforme... | [
0.30687639117240906,
-0.24205148220062256,
0.06828035414218903,
0.3844337463378906,
0.31130450963974,
0.120692677795887,
0.34276872873306274,
0.4319317638874054,
-0.14188791811466217,
0.14070266485214233,
-0.0737772062420845,
-0.037952736020088196,
0.03761741518974304,
0.36453738808631897,... |
https://github.com/huggingface/datasets/issues/3686 | `Translation` features cannot be `flatten`ed | Thanks for reporting, @SBrandeis! Some additional feature types that don't behave as expected when flattened: `Audio`, `Image` and `TranslationVariableLanguages` | ## Describe the bug
(`Dataset.flatten`)[https://github.com/huggingface/datasets/blob/master/src/datasets/arrow_dataset.py#L1265] fails for columns with feature (`Translation`)[https://github.com/huggingface/datasets/blob/3edbeb0ec6519b79f1119adc251a1a6b379a2c12/src/datasets/features/translation.py#L8]
## Steps to... | 19 | `Translation` features cannot be `flatten`ed
## Describe the bug
(`Dataset.flatten`)[https://github.com/huggingface/datasets/blob/master/src/datasets/arrow_dataset.py#L1265] fails for columns with feature (`Translation`)[https://github.com/huggingface/datasets/blob/3edbeb0ec6519b79f1119adc251a1a6b379a2c12/src/data... | [
0.09993539750576019,
-0.5199524164199829,
0.01243588700890541,
0.32758045196533203,
0.3463021516799927,
0.06023598462343216,
0.32208603620529175,
0.18556560575962067,
0.08876015245914459,
0.15184247493743896,
0.033876799046993256,
0.6146895289421082,
0.2447861135005951,
0.2951706051826477,... |
https://github.com/huggingface/datasets/issues/3679 | Download datasets from a private hub | Hi ! For information one can set the environment variable `HF_ENDPOINT` (default is `https://huggingface.co`) if they want to use a private hub.
We may need to coordinate with the other libraries to have a consistent way of changing the hub endpoint | In the context of a private hub deployment, customers would like to use load_dataset() to load datasets from their hub, not from the public hub. This doesn't seem to be configurable at the moment and it would be nice to add this feature.
The obvious workaround is to clone the repo first and then load it from local s... | 41 | Download datasets from a private hub
In the context of a private hub deployment, customers would like to use load_dataset() to load datasets from their hub, not from the public hub. This doesn't seem to be configurable at the moment and it would be nice to add this feature.
The obvious workaround is to clone the r... | [
-0.4606109857559204,
0.07715161144733429,
0.030620679259300232,
0.17081600427627563,
-0.21131625771522522,
-0.10570517182350159,
0.5121505856513977,
0.25443533062934875,
0.48193567991256714,
0.2293822467327118,
-0.5677492022514343,
0.19762834906578064,
0.2814866602420807,
0.280497908592224... |
https://github.com/huggingface/datasets/issues/3677 | Discovery cannot be streamed anymore | Seems like a regression from https://github.com/huggingface/datasets/pull/2843
Or maybe it's an issue with the hosting. I don't think so, though, because https://www.dropbox.com/s/aox84z90nyyuikz/discovery.zip seems to work as expected
| ## Describe the bug
A clear and concise description of what the bug is.
## Steps to reproduce the bug
```python
from datasets import load_dataset
iterable_dataset = load_dataset("discovery", name="discovery", split="train", streaming=True)
list(iterable_dataset.take(1))
```
## Expected results
The first ... | 26 | Discovery cannot be streamed anymore
## Describe the bug
A clear and concise description of what the bug is.
## Steps to reproduce the bug
```python
from datasets import load_dataset
iterable_dataset = load_dataset("discovery", name="discovery", split="train", streaming=True)
list(iterable_dataset.take(1))
`... | [
-0.3655183017253876,
-0.07335560768842697,
-0.03228265047073364,
-0.0026661306619644165,
0.1506631076335907,
-0.12500840425491333,
0.15002813935279846,
0.44874221086502075,
-0.0735849142074585,
0.11445628851652145,
-0.2661014199256897,
0.32796719670295715,
-0.2113560289144516,
0.1654208153... |
https://github.com/huggingface/datasets/issues/3677 | Discovery cannot be streamed anymore | Hi @severo, thanks for reporting.
Some servers do not support HTTP range requests, and those are required to stream some file formats (like ZIP in this case).
Let me try to propose a workaround. | ## Describe the bug
A clear and concise description of what the bug is.
## Steps to reproduce the bug
```python
from datasets import load_dataset
iterable_dataset = load_dataset("discovery", name="discovery", split="train", streaming=True)
list(iterable_dataset.take(1))
```
## Expected results
The first ... | 34 | Discovery cannot be streamed anymore
## Describe the bug
A clear and concise description of what the bug is.
## Steps to reproduce the bug
```python
from datasets import load_dataset
iterable_dataset = load_dataset("discovery", name="discovery", split="train", streaming=True)
list(iterable_dataset.take(1))
`... | [
-0.3655183017253876,
-0.07335560768842697,
-0.03228265047073364,
-0.0026661306619644165,
0.1506631076335907,
-0.12500840425491333,
0.15002813935279846,
0.44874221086502075,
-0.0735849142074585,
0.11445628851652145,
-0.2661014199256897,
0.32796719670295715,
-0.2113560289144516,
0.1654208153... |
https://github.com/huggingface/datasets/issues/3676 | `None` replaced by `[]` after first batch in map | It looks like this is because of this behavior in pyarrow:
```python
import pyarrow as pa
arr = pa.array([None, [0]])
reconstructed_arr = pa.ListArray.from_arrays(arr.offsets, arr.values)
print(reconstructed_arr.to_pylist())
# [[], [0]]
```
It seems that `arr.offsets` can reconstruct the array properly, but... | Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# b
# 0 [None, [0]]
# 1 [[], [0]]
# ... | 89 | `None` replaced by `[]` after first batch in map
Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# ... | [
-0.11368593573570251,
-0.19141465425491333,
-0.02992108277976513,
0.07822027802467346,
0.41042566299438477,
-0.0416080616414547,
0.6156222224235535,
0.07213100790977478,
-0.09820187091827393,
0.10662639886140823,
-0.1036108136177063,
0.34902405738830566,
0.17367129027843475,
-0.41751071810... |
https://github.com/huggingface/datasets/issues/3676 | `None` replaced by `[]` after first batch in map | The offsets don't have nulls because they don't include the validity bitmap from `arr.buffers()[0]`, which is used to say which values are null and which values are non-null.
Though the validity bitmap also seems to be wrong:
```python
bin(int(arr.buffers()[0].hex(), 16))
# '0b10'
# it should be 0b110 - 1 corres... | Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# b
# 0 [None, [0]]
# 1 [[], [0]]
# ... | 158 | `None` replaced by `[]` after first batch in map
Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# ... | [
-0.035823509097099304,
-0.2432299107313156,
-0.0416242778301239,
0.17266660928726196,
0.3844224810600281,
0.04327645152807236,
0.6972996592521667,
0.22392916679382324,
-0.003290994092822075,
0.14428043365478516,
-0.08464359492063522,
0.3390793204307556,
0.08805384486913681,
-0.258638262748... |
https://github.com/huggingface/datasets/issues/3676 | `None` replaced by `[]` after first batch in map | FYI the behavior is the same with:
- `datasets` version: 1.18.3
- Platform: Linux-5.8.0-50-generic-x86_64-with-debian-bullseye-sid
- Python version: 3.7.11
- PyArrow version: 6.0.1
but not with:
- `datasets` version: 1.8.0
- Platform: Linux-4.18.0-305.40.2.el8_4.x86_64-x86_64-with-redhat-8.4-Ootpa
- Python ... | Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# b
# 0 [None, [0]]
# 1 [[], [0]]
# ... | 57 | `None` replaced by `[]` after first batch in map
Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# ... | [
-0.12034514546394348,
-0.4828743636608124,
-0.0233134925365448,
0.09089779853820801,
0.4305689334869385,
0.06814727932214737,
0.6334287524223328,
0.144831582903862,
0.20208381116390228,
0.10193803161382675,
-0.08555296808481216,
0.33414778113365173,
0.12605451047420502,
-0.1297750324010849... |
https://github.com/huggingface/datasets/issues/3676 | `None` replaced by `[]` after first batch in map | Thanks for the insights @PaulLerner !
I found a way to workaround this issue for the code example presented in this issue.
Note that empty lists will still appear when you explicitly `cast` a list of lists that contain None values like [None, [0]] to a new feature type (e.g. to change the integer precision). In t... | Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# b
# 0 [None, [0]]
# 1 [[], [0]]
# ... | 87 | `None` replaced by `[]` after first batch in map
Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# ... | [
-0.07429349422454834,
-0.4457454979419708,
-0.059510115534067154,
0.07773666828870773,
0.5046237111091614,
0.01523514837026596,
0.6655241250991821,
0.2754402160644531,
0.27864745259284973,
0.22147992253303528,
-0.09790289402008057,
0.28979700803756714,
0.05287555977702141,
0.04777747392654... |
https://github.com/huggingface/datasets/issues/3676 | `None` replaced by `[]` after first batch in map | Hi! I feel like I’m missing something in your answer, *what* is the workaround? Is it fixed in some `datasets` version? | Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# b
# 0 [None, [0]]
# 1 [[], [0]]
# ... | 21 | `None` replaced by `[]` after first batch in map
Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# ... | [
-0.17061229050159454,
-0.4563409388065338,
-0.030878672376275063,
0.07734821736812592,
0.3964781165122986,
0.03542870283126831,
0.624072790145874,
0.09380260109901428,
0.22939929366111755,
0.10524192452430725,
-0.0233194250613451,
0.3047327399253845,
0.12613143026828766,
-0.027818713337183... |
https://github.com/huggingface/datasets/issues/3676 | `None` replaced by `[]` after first batch in map | `pa.ListArray.from_arrays` returns empty lists instead of None values. The workaround I added inside `datasets` simply consists in not using `pa.ListArray.from_arrays` :)
Once this PR [here ](https://github.com/huggingface/datasets/pull/4282)is merged, we'll release a new version of `datasets` that currectly returns... | Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# b
# 0 [None, [0]]
# 1 [[], [0]]
# ... | 69 | `None` replaced by `[]` after first batch in map
Sometimes `None` can be replaced by `[]` when running map:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": range(4)})
ds = ds.map(lambda x: {"b": [[None, [0]]]}, batched=True, batch_size=1, remove_columns=["a"])
print(ds.to_pandas())
# ... | [
-0.17446023225784302,
-0.4929961562156677,
-0.046375926584005356,
0.11255967617034912,
0.4351009726524353,
0.006763719022274017,
0.5256833434104919,
0.170755997300148,
0.28161856532096863,
0.17880578339099884,
-0.1322394460439682,
0.3388400077819824,
0.10317698866128922,
-0.067227847874164... |
https://github.com/huggingface/datasets/issues/3673 | `load_dataset("snli")` is different from dataset viewer | Yes, we decided to replace the encoded label with the corresponding label when possible in the dataset viewer. But
1. maybe it's the wrong default
2. we could find a way to show both (with a switch, or showing both ie. `0 (neutral)`).
| ## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded dataset shows the encoded labels (i.e., 0, 1, 2).
Is t... | 43 | `load_dataset("snli")` is different from dataset viewer
## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded... | [
-0.03930531442165375,
-0.1823728084564209,
-0.0017421804368495941,
0.4216579794883728,
0.014207445085048676,
-0.08085222542285919,
0.5498268604278564,
0.020397726446390152,
0.2802700996398926,
0.2657591998577118,
-0.42183342576026917,
0.5688483119010925,
0.18862473964691162,
0.180640116333... |
https://github.com/huggingface/datasets/issues/3673 | `load_dataset("snli")` is different from dataset viewer | Hi @severo,
Thanks for clarifying.
I think this default is a bit counterintuitive for the user. However, this is a personal opinion that might not be general. I think it is nice to have the actual (non-encoded) labels in the viewer. On the other hand, it would be nice to match what the user sees with what they g... | ## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded dataset shows the encoded labels (i.e., 0, 1, 2).
Is t... | 103 | `load_dataset("snli")` is different from dataset viewer
## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded... | [
-0.14739400148391724,
-0.23011252284049988,
0.022925693541765213,
0.30645787715911865,
0.10548382997512817,
-0.07960755378007889,
0.6571472883224487,
0.03179209679365158,
0.2773873805999756,
0.36313676834106445,
-0.29464447498321533,
0.5051847696304321,
0.17237743735313416,
0.1997696459293... |
https://github.com/huggingface/datasets/issues/3673 | `load_dataset("snli")` is different from dataset viewer | Thanks for the 👍 in https://github.com/huggingface/datasets/issues/3673#issuecomment-1029008349 @mariosasko @gary149 @pietrolesci, but as I proposed various solutions, it's not clear to me which you prefer. Could you write your preferences as a comment?
_(note for myself: one idea per comment in the future)_ | ## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded dataset shows the encoded labels (i.e., 0, 1, 2).
Is t... | 41 | `load_dataset("snli")` is different from dataset viewer
## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded... | [
-0.1536535620689392,
-0.24081438779830933,
-0.002418011426925659,
0.4605819582939148,
0.078947514295578,
-0.04535554721951485,
0.5275527238845825,
0.06676901876926422,
0.320016086101532,
0.2510015368461609,
-0.41402024030685425,
0.5160107016563416,
0.12621238827705383,
0.34899821877479553,... |
https://github.com/huggingface/datasets/issues/3673 | `load_dataset("snli")` is different from dataset viewer | As I am working with seq2seq, I prefer having the label in string form rather than numeric. So the viewer is fine and the underlying dataset should be "decoded" (from int to str). In this way, the user does not have to search for a mapping `int -> original name` (even though is trivial to find, I reckon). Also, encodin... | ## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded dataset shows the encoded labels (i.e., 0, 1, 2).
Is t... | 69 | `load_dataset("snli")` is different from dataset viewer
## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded... | [
0.036471154540777206,
0.00393424928188324,
0.010773848742246628,
0.49785321950912476,
0.022497177124023438,
-0.02089245244860649,
0.45482945442199707,
0.10887685418128967,
0.185509592294693,
0.050316184759140015,
-0.4681445062160492,
0.47530120611190796,
0.03385331854224205,
0.160325825214... |
https://github.com/huggingface/datasets/issues/3673 | `load_dataset("snli")` is different from dataset viewer | I like the idea of "0 (neutral)". The label name can even be greyed to make it clear that it's not part of the actual item in the dataset, it's just the meaning. | ## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded dataset shows the encoded labels (i.e., 0, 1, 2).
Is t... | 33 | `load_dataset("snli")` is different from dataset viewer
## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded... | [
-0.06567847728729248,
-0.24349752068519592,
-0.001020088791847229,
0.435577392578125,
0.005562027916312218,
-0.05187864601612091,
0.5364519357681274,
0.019029419869184494,
0.27891024947166443,
0.2169722616672516,
-0.3383783996105194,
0.5619640946388245,
0.08601974695920944,
0.1822408288717... |
https://github.com/huggingface/datasets/issues/3673 | `load_dataset("snli")` is different from dataset viewer | Proposals by @gary149. Which one do you prefer? Please vote with the thumbs
- 👍
- 👎
![image (1)](https://user-images.githubusercontent.com/1676121/152388061-32d95e42-cade-4ae4-9a77-7365... | ## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded dataset shows the encoded labels (i.e., 0, 1, 2).
Is t... | 20 | `load_dataset("snli")` is different from dataset viewer
## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded... | [
-0.13024578988552094,
-0.18308202922344208,
-0.02521340921521187,
0.5175072550773621,
-0.0003676377236843109,
-0.049284569919109344,
0.5257973074913025,
0.08876989781856537,
0.24616938829421997,
0.18687765300273895,
-0.3800659477710724,
0.5411992073059082,
0.10301819443702698,
0.2068627774... |
https://github.com/huggingface/datasets/issues/3673 | `load_dataset("snli")` is different from dataset viewer | It's [live](https://huggingface.co/datasets/glue/viewer/cola/train):
<img width="1126" alt="Capture d’écran 2022-02-14 à 10 26 03" src="https://user-images.githubusercontent.com/1676121/153836716-25f6205b-96af-42d8-880a-7c09cb24c420.png">
Thanks all for the help to improve the UI! | ## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded dataset shows the encoded labels (i.e., 0, 1, 2).
Is t... | 21 | `load_dataset("snli")` is different from dataset viewer
## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded... | [
-0.006443105638027191,
-0.24289751052856445,
0.01970844343304634,
0.6077646017074585,
0.07320703566074371,
0.005316510796546936,
0.5198222994804382,
0.013118108734488487,
0.2602270245552063,
0.2141699492931366,
-0.47028085589408875,
0.5367410182952881,
0.159767284989357,
0.2426189929246902... |
https://github.com/huggingface/datasets/issues/3668 | Couldn't cast array of type string error with cast_column | Hi ! I wasn't able to reproduce the error, are you still experiencing this ? I tried calling `cast_column` on a string column containing paths.
If you manage to share a reproducible code example that would be perfect | ## Describe the bug
In OVH cloud during Huggingface Robust-speech-recognition event on a AI training notebook instance using jupyter lab and running jupyter notebook When using the dataset.cast_column("audio",Audio(sampling_rate=16_000))
method I get error
![image](https://user-images.githubusercontent.com/25264... | 38 | Couldn't cast array of type string error with cast_column
## Describe the bug
In OVH cloud during Huggingface Robust-speech-recognition event on a AI training notebook instance using jupyter lab and running jupyter notebook When using the dataset.cast_column("audio",Audio(sampling_rate=16_000))
method I get er... | [
-0.21336017549037933,
-0.27319589257240295,
0.08020232617855072,
0.061794213950634,
0.5655031204223633,
-0.13900959491729736,
0.4365328550338745,
0.4131576418876648,
-0.03908953815698624,
0.08744701743125916,
-0.22466616332530975,
0.2103300392627716,
-0.19933119416236877,
0.203095540404319... |
https://github.com/huggingface/datasets/issues/3668 | Couldn't cast array of type string error with cast_column | Hi,
I think my team mate got this solved. Clolsing it for now and will reopen if I experience this again.
Thanks :) | ## Describe the bug
In OVH cloud during Huggingface Robust-speech-recognition event on a AI training notebook instance using jupyter lab and running jupyter notebook When using the dataset.cast_column("audio",Audio(sampling_rate=16_000))
method I get error
![image](https://user-images.githubusercontent.com/25264... | 23 | Couldn't cast array of type string error with cast_column
## Describe the bug
In OVH cloud during Huggingface Robust-speech-recognition event on a AI training notebook instance using jupyter lab and running jupyter notebook When using the dataset.cast_column("audio",Audio(sampling_rate=16_000))
method I get er... | [
-0.21336017549037933,
-0.27319589257240295,
0.08020232617855072,
0.061794213950634,
0.5655031204223633,
-0.13900959491729736,
0.4365328550338745,
0.4131576418876648,
-0.03908953815698624,
0.08744701743125916,
-0.22466616332530975,
0.2103300392627716,
-0.19933119416236877,
0.203095540404319... |
https://github.com/huggingface/datasets/issues/3668 | Couldn't cast array of type string error with cast_column | Hi @R4ZZ3,
If it is not too much of a bother, can you please help me how to resolve this error? I am exactly getting the same error where I am going as per the documentation guideline:
`my_audio_dataset = my_audio_dataset.cast_column("audio_paths", Audio())`
where `"audio_paths"` is a dataset column (feature) ... | ## Describe the bug
In OVH cloud during Huggingface Robust-speech-recognition event on a AI training notebook instance using jupyter lab and running jupyter notebook When using the dataset.cast_column("audio",Audio(sampling_rate=16_000))
method I get error
![image](https://user-images.githubusercontent.com/25264... | 59 | Couldn't cast array of type string error with cast_column
## Describe the bug
In OVH cloud during Huggingface Robust-speech-recognition event on a AI training notebook instance using jupyter lab and running jupyter notebook When using the dataset.cast_column("audio",Audio(sampling_rate=16_000))
method I get er... | [
-0.21336017549037933,
-0.27319589257240295,
0.08020232617855072,
0.061794213950634,
0.5655031204223633,
-0.13900959491729736,
0.4365328550338745,
0.4131576418876648,
-0.03908953815698624,
0.08744701743125916,
-0.22466616332530975,
0.2103300392627716,
-0.19933119416236877,
0.203095540404319... |
https://github.com/huggingface/datasets/issues/3668 | Couldn't cast array of type string error with cast_column | I was having the same issue with this code:
```
dataset = dataset.map(
lambda batch: {"full_path" : os.path.join(self.data_path, batch["path"])},
num_procs = 4
)
my_audio_dataset = dataset.cast_column("full_path", Audio(sampling_rate=16_000))
```
Removing the "num_procs" argument fixed it somehow.
... | ## Describe the bug
In OVH cloud during Huggingface Robust-speech-recognition event on a AI training notebook instance using jupyter lab and running jupyter notebook When using the dataset.cast_column("audio",Audio(sampling_rate=16_000))
method I get error
![image](https://user-images.githubusercontent.com/25264... | 41 | Couldn't cast array of type string error with cast_column
## Describe the bug
In OVH cloud during Huggingface Robust-speech-recognition event on a AI training notebook instance using jupyter lab and running jupyter notebook When using the dataset.cast_column("audio",Audio(sampling_rate=16_000))
method I get er... | [
-0.21336017549037933,
-0.27319589257240295,
0.08020232617855072,
0.061794213950634,
0.5655031204223633,
-0.13900959491729736,
0.4365328550338745,
0.4131576418876648,
-0.03908953815698624,
0.08744701743125916,
-0.22466616332530975,
0.2103300392627716,
-0.19933119416236877,
0.203095540404319... |
https://github.com/huggingface/datasets/issues/3663 | [Audio] Path of Common Voice cannot be used for audio loading anymore | Having talked to @lhoestq, I see that this feature is no longer supported.
I really don't think this was a good idea. It is a major breaking change and one for which we don't even have a working solution at the moment, which is bad for PyTorch as we don't want to force people to have `datasets` decode audio files a... | ## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(ds[0]["audio"]["path"])
load(ds[0]["path"])
```
## Expected results
... | 522 | [Audio] Path of Common Voice cannot be used for audio loading anymore
## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(d... | [
-0.35958433151245117,
-0.1635095328092575,
0.10925140976905823,
0.09242779016494751,
0.1691349744796753,
-0.2649870216846466,
0.5073250532150269,
0.045520853251218796,
-0.08687879145145416,
0.3616396188735962,
-0.45575958490371704,
0.6036258935928345,
-0.18728798627853394,
-0.4732159674167... |
https://github.com/huggingface/datasets/issues/3663 | [Audio] Path of Common Voice cannot be used for audio loading anymore | Agree that we need to have access to the original sound files. Few days ago I was looking for these original files because I suspected there is bug in the audio resampling (confirmed in https://github.com/huggingface/datasets/issues/3662) and I want to do my own resampling to workaround the bug, which is now not possib... | ## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(ds[0]["audio"]["path"])
load(ds[0]["path"])
```
## Expected results
... | 61 | [Audio] Path of Common Voice cannot be used for audio loading anymore
## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(d... | [
-0.2235470563173294,
-0.25080686807632446,
0.05817733332514763,
0.3293778896331787,
0.17340800166130066,
-0.2104950249195099,
0.20992662012577057,
0.12101784348487854,
-0.15212301909923553,
0.36737996339797974,
-0.6560893654823303,
0.3635476231575012,
-0.13726454973220825,
-0.4980191588401... |
https://github.com/huggingface/datasets/issues/3663 | [Audio] Path of Common Voice cannot be used for audio loading anymore | @patrickvonplaten
> The other solution of providing a path-like object derived from the bytes stocked in the .array file is not nearly as user-friendly, but better than nothing
Just to clarify, here you describe the approach that uses the `Audio.decode` attribute to access the underlying bytes?
> The official e... | ## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(ds[0]["audio"]["path"])
load(ds[0]["path"])
```
## Expected results
... | 180 | [Audio] Path of Common Voice cannot be used for audio loading anymore
## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(d... | [
-0.23844973742961884,
-0.24992311000823975,
-0.004361661151051521,
0.20158728957176208,
0.3130868077278137,
-0.23257103562355042,
0.394971638917923,
0.11096601188182831,
-0.06445099413394928,
0.47054606676101685,
-0.3877638280391693,
0.6395118236541748,
-0.2136877030134201,
-0.497500061988... |
https://github.com/huggingface/datasets/issues/3663 | [Audio] Path of Common Voice cannot be used for audio loading anymore | Related to this discussion: in https://github.com/huggingface/datasets/pull/3664#issuecomment-1031866858 I propose how we could change `iter_archive` to work for streaming and also return local paths (as it used too !). I'd love your opinions on this | ## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(ds[0]["audio"]["path"])
load(ds[0]["path"])
```
## Expected results
... | 33 | [Audio] Path of Common Voice cannot be used for audio loading anymore
## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(d... | [
-0.4006459414958954,
-0.1878708004951477,
0.1284468173980713,
0.30239808559417725,
0.14650879800319672,
-0.3337065577507019,
0.3811359703540802,
0.10974302887916565,
0.04849935695528984,
0.29123228788375854,
-0.472140371799469,
0.48588085174560547,
-0.2812138497829437,
-0.2401290088891983,... |
https://github.com/huggingface/datasets/issues/3663 | [Audio] Path of Common Voice cannot be used for audio loading anymore | > @patrickvonplaten
>
> > The other solution of providing a path-like object derived from the bytes stocked in the .array file is not nearly as user-friendly, but better than nothing
>
> Just to clarify, here you describe the approach that uses the `Audio.decode` attribute to access the underlying bytes?
Yes! ... | ## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(ds[0]["audio"]["path"])
load(ds[0]["path"])
```
## Expected results
... | 436 | [Audio] Path of Common Voice cannot be used for audio loading anymore
## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(d... | [
-0.23320640623569489,
-0.252346396446228,
-0.008109457790851593,
0.19817091524600983,
0.30640363693237305,
-0.2232053577899933,
0.3953647315502167,
0.10804206132888794,
-0.08172808587551117,
0.462327778339386,
-0.3875495195388794,
0.6493380069732666,
-0.19506260752677917,
-0.50394546985626... |
https://github.com/huggingface/datasets/issues/3663 | [Audio] Path of Common Voice cannot be used for audio loading anymore | From https://github.com/huggingface/datasets/pull/3736 the Common Voice dataset now gives access to the local audio files as before | ## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(ds[0]["audio"]["path"])
load(ds[0]["path"])
```
## Expected results
... | 16 | [Audio] Path of Common Voice cannot be used for audio loading anymore
## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(d... | [
-0.30104300379753113,
-0.3545650839805603,
0.05535611882805824,
0.22826264798641205,
0.2375389039516449,
-0.1576322466135025,
0.398414671421051,
0.09137996286153793,
-0.02924608439207077,
0.41323041915893555,
-0.5055301189422607,
0.49444958567619324,
-0.09787896275520325,
-0.37988004088401... |
https://github.com/huggingface/datasets/issues/3663 | [Audio] Path of Common Voice cannot be used for audio loading anymore | I understand the argument that it is bad to have a breaking change. How to deal with the introduction of breaking changes is a topic of its own and not sure how you want to deal with that (or is the policy this is never allowed, and there must be a `load_dataset_v2` or so if you really want to introduce a breaking chan... | ## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(ds[0]["audio"]["path"])
load(ds[0]["path"])
```
## Expected results
... | 336 | [Audio] Path of Common Voice cannot be used for audio loading anymore
## Describe the bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchaudio import load
ds = load_dataset("common_voice", "ab", split="train")
# both of the following commands fail at the moment
load(d... | [
-0.4296571612358093,
-0.18280735611915588,
0.01872987300157547,
0.01621636375784874,
0.12771841883659363,
-0.22412902116775513,
0.33386334776878357,
0.13780471682548523,
-0.1267738789319992,
0.32250848412513733,
-0.31793278455734253,
0.49608832597732544,
-0.17527732253074646,
-0.5265270471... |
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