html_url stringlengths 51 51 | comments stringlengths 67 24.7k | title stringlengths 6 280 | body stringlengths 51 36.2k | comment_length int64 16 1.45k | text stringlengths 190 38.3k | embeddings list |
|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/6311 | Thanks for reporting! We've spotted the bugs with the `array.values` handling and are fixing them in https://github.com/huggingface/datasets/pull/6283 (should be part of the next release). | cast_column to Sequence with length=4 occur exception raise in datasets/table.py:2146 | ### Describe the bug
i load a dataset from local csv file which has 187383612 examples, then use `map` to generate new columns for test.
here is my code :
```
import os
from datasets import load_dataset
from datasets.features import Sequence, Value
def add_new_path(example):
example["ais_bbox"] =... | 24 | cast_column to Sequence with length=4 occur exception raise in datasets/table.py:2146
### Describe the bug
i load a dataset from local csv file which has 187383612 examples, then use `map` to generate new columns for test.
here is my code :
```
import os
from datasets import load_dataset
from datasets.fe... | [
-0.22929179668426514,
-0.11489871144294739,
-0.02320384792983532,
0.21615716814994812,
0.5230922102928162,
0.17112109065055847,
0.44043073058128357,
0.48009565472602844,
0.3565998077392578,
0.0004348158836364746,
0.361715704202652,
0.2731039226055145,
-0.14019687473773956,
-0.0546882823109... |
https://github.com/huggingface/datasets/issues/6311 | > Thanks for reporting! We've spotted the bugs with the `array.values` handling and are fixing them in #6283 (should be part of the next release).
i encounter another exception while cast_column to type `Sequence(feature={"points": Array2D(shape=(-1, 2), dtype="int64"), "label": ClassLabel(num_classes=num_classes, n... | cast_column to Sequence with length=4 occur exception raise in datasets/table.py:2146 | ### Describe the bug
i load a dataset from local csv file which has 187383612 examples, then use `map` to generate new columns for test.
here is my code :
```
import os
from datasets import load_dataset
from datasets.features import Sequence, Value
def add_new_path(example):
example["ais_bbox"] =... | 440 | cast_column to Sequence with length=4 occur exception raise in datasets/table.py:2146
### Describe the bug
i load a dataset from local csv file which has 187383612 examples, then use `map` to generate new columns for test.
here is my code :
```
import os
from datasets import load_dataset
from datasets.fe... | [
-0.22929179668426514,
-0.11489871144294739,
-0.02320384792983532,
0.21615716814994812,
0.5230922102928162,
0.17112109065055847,
0.44043073058128357,
0.48009565472602844,
0.3565998077392578,
0.0004348158836364746,
0.361715704202652,
0.2731039226055145,
-0.14019687473773956,
-0.0546882823109... |
https://github.com/huggingface/datasets/issues/6311 | `Incompatible storage type for extension<arrow.py_extension_type<Array2DExtensionType>>: expected list<item: list<item: double>>, got list<item: double>`
if i change `Array2D(shape=(-1, 2), dtype="int64")` to `Sequence(Value("int64"))` , every thing goes well. but my data is 2D int list | cast_column to Sequence with length=4 occur exception raise in datasets/table.py:2146 | ### Describe the bug
i load a dataset from local csv file which has 187383612 examples, then use `map` to generate new columns for test.
here is my code :
```
import os
from datasets import load_dataset
from datasets.features import Sequence, Value
def add_new_path(example):
example["ais_bbox"] =... | 32 | cast_column to Sequence with length=4 occur exception raise in datasets/table.py:2146
### Describe the bug
i load a dataset from local csv file which has 187383612 examples, then use `map` to generate new columns for test.
here is my code :
```
import os
from datasets import load_dataset
from datasets.fe... | [
-0.22929179668426514,
-0.11489871144294739,
-0.02320384792983532,
0.21615716814994812,
0.5230922102928162,
0.17112109065055847,
0.44043073058128357,
0.48009565472602844,
0.3565998077392578,
0.0004348158836364746,
0.361715704202652,
0.2731039226055145,
-0.14019687473773956,
-0.0546882823109... |
https://github.com/huggingface/datasets/issues/6311 | i test Sequence(ClassLabel) is ok if one column is label list. but it is not ok in nested column such as `Sequence(feature= {"points": Sequence(Value("int32")), "label": Sequence(ClassLabel(num_classes....)))`. in this case i need override ClassLabels. encode_example as i given above. | cast_column to Sequence with length=4 occur exception raise in datasets/table.py:2146 | ### Describe the bug
i load a dataset from local csv file which has 187383612 examples, then use `map` to generate new columns for test.
here is my code :
```
import os
from datasets import load_dataset
from datasets.features import Sequence, Value
def add_new_path(example):
example["ais_bbox"] =... | 38 | cast_column to Sequence with length=4 occur exception raise in datasets/table.py:2146
### Describe the bug
i load a dataset from local csv file which has 187383612 examples, then use `map` to generate new columns for test.
here is my code :
```
import os
from datasets import load_dataset
from datasets.fe... | [
-0.22929179668426514,
-0.11489871144294739,
-0.02320384792983532,
0.21615716814994812,
0.5230922102928162,
0.17112109065055847,
0.44043073058128357,
0.48009565472602844,
0.3565998077392578,
0.0004348158836364746,
0.361715704202652,
0.2731039226055145,
-0.14019687473773956,
-0.0546882823109... |
https://github.com/huggingface/datasets/issues/6308 | This (Windows) issue was fixed in `fsspec` in https://github.com/fsspec/filesystem_spec/pull/1275. So, to avoid the error, update the `fsspec` installation with `pip install -U fsspec`. | module 'resource' has no attribute 'error' | ### Describe the bug
just run import:
`from datasets import load_dataset`
and then:
```
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\__init__.py", line 22, in <module>
from .arrow_dataset import Dataset
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\arrow... | 23 | module 'resource' has no attribute 'error'
### Describe the bug
just run import:
`from datasets import load_dataset`
and then:
```
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\__init__.py", line 22, in <module>
from .arrow_dataset import Dataset
File "C:\ProgramData\anaconda... | [
-0.3986871838569641,
-0.19148069620132446,
-0.12688815593719482,
0.3200543522834778,
0.6016736626625061,
-0.017333589494228363,
0.11214470118284225,
0.34752100706100464,
-0.19669853150844574,
0.062872976064682,
0.0392395481467247,
0.4419638514518738,
-0.10753051936626434,
-0.14714926481246... |
https://github.com/huggingface/datasets/issues/6308 | > This (Windows) issue was fixed in `fsspec` in [fsspec/filesystem_spec#1275](https://github.com/fsspec/filesystem_spec/pull/1275). So, to avoid the error, update the `fsspec` installation with `pip install -U fsspec`.
after I run `pip install -U fsspec`
it occurs a new error:
```
ERROR: pip's dependency resolv... | module 'resource' has no attribute 'error' | ### Describe the bug
just run import:
`from datasets import load_dataset`
and then:
```
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\__init__.py", line 22, in <module>
from .arrow_dataset import Dataset
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\arrow... | 77 | module 'resource' has no attribute 'error'
### Describe the bug
just run import:
`from datasets import load_dataset`
and then:
```
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\__init__.py", line 22, in <module>
from .arrow_dataset import Dataset
File "C:\ProgramData\anaconda... | [
-0.3986871838569641,
-0.19148069620132446,
-0.12688815593719482,
0.3200543522834778,
0.6016736626625061,
-0.017333589494228363,
0.11214470118284225,
0.34752100706100464,
-0.19669853150844574,
0.062872976064682,
0.0392395481467247,
0.4419638514518738,
-0.10753051936626434,
-0.14714926481246... |
https://github.com/huggingface/datasets/issues/6308 | The `fsspec<2023.9.0` upper bound will be removed in the next release. The `ResourceError` fix is also present in version 2023.6.0, so use that version in the meantime (`pip install fsspec==2023.6.0`). | module 'resource' has no attribute 'error' | ### Describe the bug
just run import:
`from datasets import load_dataset`
and then:
```
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\__init__.py", line 22, in <module>
from .arrow_dataset import Dataset
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\arrow... | 30 | module 'resource' has no attribute 'error'
### Describe the bug
just run import:
`from datasets import load_dataset`
and then:
```
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\__init__.py", line 22, in <module>
from .arrow_dataset import Dataset
File "C:\ProgramData\anaconda... | [
-0.3986871838569641,
-0.19148069620132446,
-0.12688815593719482,
0.3200543522834778,
0.6016736626625061,
-0.017333589494228363,
0.11214470118284225,
0.34752100706100464,
-0.19669853150844574,
0.062872976064682,
0.0392395481467247,
0.4419638514518738,
-0.10753051936626434,
-0.14714926481246... |
https://github.com/huggingface/datasets/issues/6308 | > The `fsspec<2023.9.0` upper bound will be removed in the next release. The `ResourceError` fix is also present in version 2023.6.0, so use that version in the meantime (`pip install fsspec==2023.6.0`).
thanks for reply！ | module 'resource' has no attribute 'error' | ### Describe the bug
just run import:
`from datasets import load_dataset`
and then:
```
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\__init__.py", line 22, in <module>
from .arrow_dataset import Dataset
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\arrow... | 34 | module 'resource' has no attribute 'error'
### Describe the bug
just run import:
`from datasets import load_dataset`
and then:
```
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\__init__.py", line 22, in <module>
from .arrow_dataset import Dataset
File "C:\ProgramData\anaconda... | [
-0.3986871838569641,
-0.19148069620132446,
-0.12688815593719482,
0.3200543522834778,
0.6016736626625061,
-0.017333589494228363,
0.11214470118284225,
0.34752100706100464,
-0.19669853150844574,
0.062872976064682,
0.0392395481467247,
0.4419638514518738,
-0.10753051936626434,
-0.14714926481246... |
https://github.com/huggingface/datasets/issues/6306 | more information：
```
File "text2vec\__init__.py", line 8, in <module>
File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
File "PyInstaller\loader\pyimod02... | pyinstaller : OSError: could not get source code | ### Describe the bug
I ran a package with pyinstaller and got the following error：
### Steps to reproduce the bug
```
...
File "datasets\__init__.py", line 52, in <module>
File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
File "<frozen importlib._bootstrap>", line 1006, in _find_an... | 232 | pyinstaller : OSError: could not get source code
### Describe the bug
I ran a package with pyinstaller and got the following error：
### Steps to reproduce the bug
```
...
File "datasets\__init__.py", line 52, in <module>
File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
File "<fr... | [
-0.3243016004562378,
0.07443571090698242,
-0.07170689105987549,
0.27683448791503906,
0.45608460903167725,
-0.20892037451267242,
0.5486605763435364,
0.31559014320373535,
-0.3889833688735962,
0.24571028351783752,
0.0660596415400505,
0.4091797471046448,
-0.2875100374221802,
0.1656084954738617... |
https://github.com/huggingface/datasets/issues/6306 | > > '
>
> thanks,I solve it.it's about pyinstaller.
I encountered the same error, how to solve it? | pyinstaller : OSError: could not get source code | ### Describe the bug
I ran a package with pyinstaller and got the following error：
### Steps to reproduce the bug
```
...
File "datasets\__init__.py", line 52, in <module>
File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
File "<frozen importlib._bootstrap>", line 1006, in _find_an... | 19 | pyinstaller : OSError: could not get source code
### Describe the bug
I ran a package with pyinstaller and got the following error：
### Steps to reproduce the bug
```
...
File "datasets\__init__.py", line 52, in <module>
File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
File "<fr... | [
-0.3243016004562378,
0.07443571090698242,
-0.07170689105987549,
0.27683448791503906,
0.45608460903167725,
-0.20892037451267242,
0.5486605763435364,
0.31559014320373535,
-0.3889833688735962,
0.24571028351783752,
0.0660596415400505,
0.4091797471046448,
-0.2875100374221802,
0.1656084954738617... |
https://github.com/huggingface/datasets/issues/6303 | You can find the reasoning behind this naming scheme [here](https://github.com/huggingface/transformers/pull/16343#discussion_r931182168).
This point has been raised several times, so I'd be okay with starting with `00001-` (also to be consistent with the `transformers` sharding), but I'm not sure @lhoestq agrees. | Parquet uploads off-by-one naming scheme | ### Describe the bug
I noticed this numbering scheme not matching up in a different project and wanted to raise it as an issue for discussion, what is the actual proper way to have these stored?
<img width="425" alt="image" src="https://github.com/huggingface/datasets/assets/1981179/3ffa2144-7c9a-446f-b521-a5e9db71... | 39 | Parquet uploads off-by-one naming scheme
### Describe the bug
I noticed this numbering scheme not matching up in a different project and wanted to raise it as an issue for discussion, what is the actual proper way to have these stored?
<img width="425" alt="image" src="https://github.com/huggingface/datasets/asse... | [
0.24610058963298798,
-0.06340596079826355,
0.0809183269739151,
0.5036103129386902,
0.06562738865613937,
-0.12215150892734528,
0.3042208254337311,
-0.08270291984081268,
-0.20878185331821442,
0.159028559923172,
0.35009947419166565,
0.20905762910842896,
0.11546795070171356,
0.2804762423038482... |
https://github.com/huggingface/datasets/issues/6303 | We start at 0 in `datasets` for consistency with Apache Spark, Apache Beam, Dask and others.
Also note `transformers` isn't a good reference on this topic. I talked with the maintainers when they added shards but it was already released this way. Though we found that there is a backward-compatible way in `transforme... | Parquet uploads off-by-one naming scheme | ### Describe the bug
I noticed this numbering scheme not matching up in a different project and wanted to raise it as an issue for discussion, what is the actual proper way to have these stored?
<img width="425" alt="image" src="https://github.com/huggingface/datasets/assets/1981179/3ffa2144-7c9a-446f-b521-a5e9db71... | 67 | Parquet uploads off-by-one naming scheme
### Describe the bug
I noticed this numbering scheme not matching up in a different project and wanted to raise it as an issue for discussion, what is the actual proper way to have these stored?
<img width="425" alt="image" src="https://github.com/huggingface/datasets/asse... | [
0.24610058963298798,
-0.06340596079826355,
0.0809183269739151,
0.5036103129386902,
0.06562738865613937,
-0.12215150892734528,
0.3042208254337311,
-0.08270291984081268,
-0.20878185331821442,
0.159028559923172,
0.35009947419166565,
0.20905762910842896,
0.11546795070171356,
0.2804762423038482... |
https://github.com/huggingface/datasets/issues/6303 | Makes sense to start at 0 for plenty of good reasons so I'm on board.
What about the second part `-of-0000X`? With single commit PR #6269 just getting merged, there was a note about issues with 100+ file edits https://github.com/huggingface/datasets/pull/6269#issuecomment-1755428581.
That would be my last remain... | Parquet uploads off-by-one naming scheme | ### Describe the bug
I noticed this numbering scheme not matching up in a different project and wanted to raise it as an issue for discussion, what is the actual proper way to have these stored?
<img width="425" alt="image" src="https://github.com/huggingface/datasets/assets/1981179/3ffa2144-7c9a-446f-b521-a5e9db71... | 93 | Parquet uploads off-by-one naming scheme
### Describe the bug
I noticed this numbering scheme not matching up in a different project and wanted to raise it as an issue for discussion, what is the actual proper way to have these stored?
<img width="425" alt="image" src="https://github.com/huggingface/datasets/asse... | [
0.24610058963298798,
-0.06340596079826355,
0.0809183269739151,
0.5036103129386902,
0.06562738865613937,
-0.12215150892734528,
0.3042208254337311,
-0.08270291984081268,
-0.20878185331821442,
0.159028559923172,
0.35009947419166565,
0.20905762910842896,
0.11546795070171356,
0.2804762423038482... |
https://github.com/huggingface/datasets/issues/6302 | `writer._num_bytes` is updated every `writer_batch_size`-th call to the `write` method (default `writer_batch_size` is 1000 (examples)). You should be able to see the update by passing a smaller `writer_batch_size` to the `load_dataset_builder`.
We could improve this by supporting the string `writer_batch_size` vers... | ArrowWriter/ParquetWriter `write` method does not increase `_num_bytes` and hence datasets not sharding at `max_shard_size` | ### Describe the bug
An example from [1], does not work when limiting shards with `max_shard_size`.
Try the following example with low `max_shard_size`, such as:
```python
builder.download_and_prepare(output_dir, storage_options=storage_options, file_format="parquet", max_shard_size="10MB")
```
The reason f... | 59 | ArrowWriter/ParquetWriter `write` method does not increase `_num_bytes` and hence datasets not sharding at `max_shard_size`
### Describe the bug
An example from [1], does not work when limiting shards with `max_shard_size`.
Try the following example with low `max_shard_size`, such as:
```python
builder.downlo... | [
-0.21688036620616913,
-0.32925087213516235,
0.040966473519802094,
0.35702764987945557,
-0.010450192727148533,
-0.2793327271938324,
0.1783680021762848,
-0.06482735276222229,
-0.11833866685628891,
0.05089190602302551,
0.21760544180870056,
0.0646483302116394,
-0.09433740377426147,
0.318702906... |
https://github.com/huggingface/datasets/issues/6294 | It looks to be the same issue as the one reported in https://discuss.huggingface.co/t/indexerror-invalid-key-16-is-out-of-bounds-for-size-0.
Can you check the length of `train_dataset` before the `train_sampler = self._get_train_sampler()` (and after `_remove_unused_columns`) line? | IndexError: Invalid key is out of bounds for size 0 despite having a populated dataset | ### Describe the bug
I am encountering an `IndexError` when trying to access data from a DataLoader which wraps around a dataset I've loaded using the `datasets` library. The error suggests that the dataset size is `0`, but when I check the length and print the dataset, it's clear that it has `1166` entries.
### Step... | 29 | IndexError: Invalid key is out of bounds for size 0 despite having a populated dataset
### Describe the bug
I am encountering an `IndexError` when trying to access data from a DataLoader which wraps around a dataset I've loaded using the `datasets` library. The error suggests that the dataset size is `0`, but when I... | [
-0.18687286972999573,
0.07448868453502655,
-0.002622019499540329,
0.4387747645378113,
0.02467706799507141,
0.019085943698883057,
0.5693433880805969,
0.3245084583759308,
0.36027199029922485,
0.2870757579803467,
0.16168470680713654,
0.13154295086860657,
-0.33575376868247986,
0.14254388213157... |
https://github.com/huggingface/datasets/issues/6292 | Hi! Can you provide a code that reproduces the issue?
Also, which version of `datasets` are you using? You can check this by running `python -c "import datasets; print(datasets.__version__)"` inside the env. We added support for "float images" in `datasets 2.9`. | how to load the image of dtype float32 or float64 | _FEATURES = datasets.Features(
{
"image": datasets.Image(),
"text": datasets.Value("string"),
},
)
The datasets builder seems only support the unit8 data. How to load the float dtype data? | 41 | how to load the image of dtype float32 or float64
_FEATURES = datasets.Features(
{
"image": datasets.Image(),
"text": datasets.Value("string"),
},
)
The datasets builder seems only support the unit8 data. How to load the float dtype data?
Hi! Can you provide a code that reproduces the... | [
-0.3456231653690338,
-0.2985003888607025,
-0.10477280616760254,
0.603319525718689,
0.50831139087677,
0.1976892352104187,
0.32766076922416687,
0.18763986229896545,
0.057741984724998474,
0.02569972351193428,
-0.1285153329372406,
-0.022169915959239006,
-0.14426574110984802,
0.2175162583589553... |
https://github.com/huggingface/datasets/issues/6290 | Yea I think waiting for #6269 would be best, or branching from it. For reference, this [PR](https://github.com/LAION-AI/Discord-Scrapers/pull/2) is progressing pretty well which will do similar using the hf hub for our LAION dataset bot https://github.com/LAION-AI/Discord-Scrapers/pull/2. | Incremental dataset (e.g. `.push_to_hub(..., append=True)`) | ### Feature request
Have the possibility to do `ds.push_to_hub(..., append=True)`.
### Motivation
Requested in this [comment](https://huggingface.co/datasets/laion/dalle-3-dataset/discussions/3#65252597c4edc168202a5eaa) and
this [comment](https://huggingface.co/datasets/laion/dalle-3-dataset/discussions/4#6524f675... | 35 | Incremental dataset (e.g. `.push_to_hub(..., append=True)`)
### Feature request
Have the possibility to do `ds.push_to_hub(..., append=True)`.
### Motivation
Requested in this [comment](https://huggingface.co/datasets/laion/dalle-3-dataset/discussions/3#65252597c4edc168202a5eaa) and
this [comment](https://huggin... | [
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0.54919523000... |
https://github.com/huggingface/datasets/issues/6288 | A duplicate of https://github.com/huggingface/datasets/issues/4796.
We could get this for free by implementing the `Image` feature as an extension type, as shown in [this](https://colab.research.google.com/drive/1Uzm_tXVpGTwbzleDConWcNjacwO1yxE4?usp=sharing) Colab (example with UUIDs).
| Dataset.from_pandas with a DataFrame of PIL.Images | Currently type inference doesn't know what to do with a Pandas Series of PIL.Image objects, though it would be nice to get a Dataset with the Image type this way | 27 | Dataset.from_pandas with a DataFrame of PIL.Images
Currently type inference doesn't know what to do with a Pandas Series of PIL.Image objects, though it would be nice to get a Dataset with the Image type this way
A duplicate of https://github.com/huggingface/datasets/issues/4796.
We could get this for free by im... | [
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https://github.com/huggingface/datasets/issues/6288 | +1 to this
Calling this line with a df that contains a PIL image (as they are returned from load_dataset)
`ds = Dataset.from_pandas(df)`
Results in this error:
`ArrowInvalid: ('Could not convert <PIL.PngImagePlugin.PngImageFile image mode=RGB size=1024x1024 at 0x2B41F2D70> with type PngImageFile: did not recognize ... | Dataset.from_pandas with a DataFrame of PIL.Images | Currently type inference doesn't know what to do with a Pandas Series of PIL.Image objects, though it would be nice to get a Dataset with the Image type this way | 60 | Dataset.from_pandas with a DataFrame of PIL.Images
Currently type inference doesn't know what to do with a Pandas Series of PIL.Image objects, though it would be nice to get a Dataset with the Image type this way
+1 to this
Calling this line with a df that contains a PIL image (as they are returned from load_datas... | [
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https://github.com/huggingface/datasets/issues/6287 | There is no "text" column in the `amazon_reviews_multi`, hence the `KeyError`. You can get the column names by running `dataset.column_names`. | map() not recognizing "text" | ### Describe the bug
The [map() documentation](https://huggingface.co/docs/datasets/v2.14.5/en/package_reference/main_classes#datasets.Dataset.map) reads:
`
ds = ds.map(lambda x: tokenizer(x['text'], truncation=True, padding=True), batched=True)`
I have been trying to reproduce it in my code as:
`tokenizedData... | 20 | map() not recognizing "text"
### Describe the bug
The [map() documentation](https://huggingface.co/docs/datasets/v2.14.5/en/package_reference/main_classes#datasets.Dataset.map) reads:
`
ds = ds.map(lambda x: tokenizer(x['text'], truncation=True, padding=True), batched=True)`
I have been trying to reproduce it i... | [
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https://github.com/huggingface/datasets/issues/6285 | You should be able to load the images by modifying the `load_dataset` call like this:
```python
dataset = load_dataset("imagefolder", data_dir="/content/datasets/PotholeDetectionYOLOv8-1")
```
The `imagefolder` builder expects the image files to be in `path/label/image_file` (e.g. .`.../train/dog/image_1.jpg`), s... | TypeError: expected str, bytes or os.PathLike object, not dict | ### Describe the bug
my dataset is in form : train- image /n -labels
and tried the code:
```
from datasets import load_dataset
data_files = {
"train": "/content/datasets/PotholeDetectionYOLOv8-1/train/",
"validation": "/content/datasets/PotholeDetectionYOLOv8-1/valid/",
"test": "/content/dat... | 62 | TypeError: expected str, bytes or os.PathLike object, not dict
### Describe the bug
my dataset is in form : train- image /n -labels
and tried the code:
```
from datasets import load_dataset
data_files = {
"train": "/content/datasets/PotholeDetectionYOLOv8-1/train/",
"validation": "/content/datase... | [
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0.21652670204639435,
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0.20537492632865906,
0.06611413508653641,
0.478313148021698,
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0.12190347909927368,... |
https://github.com/huggingface/datasets/issues/6285 | > You should be able to load the images by modifying the `load_dataset` call like this:
>
> ```python
> dataset = load_dataset("imagefolder", data_dir="/content/datasets/PotholeDetectionYOLOv8-1")
> ```
>
> The `imagefolder` builder expects the image files to be in `path/label/image_file` (e.g. .`.../train/dog/... | TypeError: expected str, bytes or os.PathLike object, not dict | ### Describe the bug
my dataset is in form : train- image /n -labels
and tried the code:
```
from datasets import load_dataset
data_files = {
"train": "/content/datasets/PotholeDetectionYOLOv8-1/train/",
"validation": "/content/datasets/PotholeDetectionYOLOv8-1/valid/",
"test": "/content/dat... | 81 | TypeError: expected str, bytes or os.PathLike object, not dict
### Describe the bug
my dataset is in form : train- image /n -labels
and tried the code:
```
from datasets import load_dataset
data_files = {
"train": "/content/datasets/PotholeDetectionYOLOv8-1/train/",
"validation": "/content/datase... | [
-0.08925832808017731,
-0.10927513986825943,
0.024575650691986084,
0.3565120995044708,
0.614642858505249,
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0.21652670204639435,
0.32387787103652954,
0.1509816199541092,
0.20537492632865906,
0.06611413508653641,
0.478313148021698,
-0.4957769513130188,
0.12190347909927368,... |
https://github.com/huggingface/datasets/issues/6285 | As explained in my previous comment, you need to define metadata files to load the labels or update the paths to be in the format `train/label/image` (`train- image /n -labels` is not supported by the loader). | TypeError: expected str, bytes or os.PathLike object, not dict | ### Describe the bug
my dataset is in form : train- image /n -labels
and tried the code:
```
from datasets import load_dataset
data_files = {
"train": "/content/datasets/PotholeDetectionYOLOv8-1/train/",
"validation": "/content/datasets/PotholeDetectionYOLOv8-1/valid/",
"test": "/content/dat... | 36 | TypeError: expected str, bytes or os.PathLike object, not dict
### Describe the bug
my dataset is in form : train- image /n -labels
and tried the code:
```
from datasets import load_dataset
data_files = {
"train": "/content/datasets/PotholeDetectionYOLOv8-1/train/",
"validation": "/content/datase... | [
-0.08925832808017731,
-0.10927513986825943,
0.024575650691986084,
0.3565120995044708,
0.614642858505249,
0.05151888728141785,
0.21652670204639435,
0.32387787103652954,
0.1509816199541092,
0.20537492632865906,
0.06611413508653641,
0.478313148021698,
-0.4957769513130188,
0.12190347909927368,... |
https://github.com/huggingface/datasets/issues/6285 | I downloaded my file after annotating using roboflow . It gives train-
images, labels , test- images, labels , valid- images, labels . I hope it
gives you an idea of the dataset . Please advise on this dataset
On Tue, Oct 10, 2023 at 18:12 Mario Šaško ***@***.***> wrote:
> As explained in my previous comment, ... | TypeError: expected str, bytes or os.PathLike object, not dict | ### Describe the bug
my dataset is in form : train- image /n -labels
and tried the code:
```
from datasets import load_dataset
data_files = {
"train": "/content/datasets/PotholeDetectionYOLOv8-1/train/",
"validation": "/content/datasets/PotholeDetectionYOLOv8-1/valid/",
"test": "/content/dat... | 125 | TypeError: expected str, bytes or os.PathLike object, not dict
### Describe the bug
my dataset is in form : train- image /n -labels
and tried the code:
```
from datasets import load_dataset
data_files = {
"train": "/content/datasets/PotholeDetectionYOLOv8-1/train/",
"validation": "/content/datase... | [
-0.08925832808017731,
-0.10927513986825943,
0.024575650691986084,
0.3565120995044708,
0.614642858505249,
0.05151888728141785,
0.21652670204639435,
0.32387787103652954,
0.1509816199541092,
0.20537492632865906,
0.06611413508653641,
0.478313148021698,
-0.4957769513130188,
0.12190347909927368,... |
https://github.com/huggingface/datasets/issues/6280 | Thanks for the quick response @mariosasko! I just installed your branch via `poetry add 'git+https://github.com/huggingface/datasets#fix-array_values'` and I can confirm it works on the example provided.
Follow up question for you, should `None`s be supported in these types of features as they are in others?
For... | Couldn't cast array of type fixed_size_list to Sequence(Value(float64)) | ### Describe the bug
I have a dataset with an embedding column, when I try to map that dataset I get the following exception:
```
Traceback (most recent call last):
File "/Users/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 3189, in map
for rank, done, content... | 234 | Couldn't cast array of type fixed_size_list to Sequence(Value(float64))
### Describe the bug
I have a dataset with an embedding column, when I try to map that dataset I get the following exception:
```
Traceback (most recent call last):
File "/Users/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/... | [
-0.014731407165527344,
-0.6136932373046875,
0.010602809488773346,
0.0606437511742115,
0.691925585269928,
0.2248997539281845,
0.3206327557563782,
0.5348027944564819,
0.3054993152618408,
0.07003742456436157,
0.2205769568681717,
0.42197325825691223,
-0.24774007499217987,
-0.15707050263881683,... |
https://github.com/huggingface/datasets/issues/6280 | This part of PyArrow is buggy and inconsistent regarding features implemented across the types, so the only option is to operate on the Arrow buffer level to fix issues such as the above one. | Couldn't cast array of type fixed_size_list to Sequence(Value(float64)) | ### Describe the bug
I have a dataset with an embedding column, when I try to map that dataset I get the following exception:
```
Traceback (most recent call last):
File "/Users/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 3189, in map
for rank, done, content... | 34 | Couldn't cast array of type fixed_size_list to Sequence(Value(float64))
### Describe the bug
I have a dataset with an embedding column, when I try to map that dataset I get the following exception:
```
Traceback (most recent call last):
File "/Users/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/... | [
-0.014731407165527344,
-0.6136932373046875,
0.010602809488773346,
0.0606437511742115,
0.691925585269928,
0.2248997539281845,
0.3206327557563782,
0.5348027944564819,
0.3054993152618408,
0.07003742456436157,
0.2205769568681717,
0.42197325825691223,
-0.24774007499217987,
-0.15707050263881683,... |
https://github.com/huggingface/datasets/issues/6280 | Ok - can you take the POC I did [here](https://github.com/huggingface/datasets/commit/15443098e9ce053943172f7ec6fce3769d7dff6e)? Happy to turn this into an actual PR but would appreciate feedback on the implementation before I take another pass! | Couldn't cast array of type fixed_size_list to Sequence(Value(float64)) | ### Describe the bug
I have a dataset with an embedding column, when I try to map that dataset I get the following exception:
```
Traceback (most recent call last):
File "/Users/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 3189, in map
for rank, done, content... | 30 | Couldn't cast array of type fixed_size_list to Sequence(Value(float64))
### Describe the bug
I have a dataset with an embedding column, when I try to map that dataset I get the following exception:
```
Traceback (most recent call last):
File "/Users/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/... | [
-0.014731407165527344,
-0.6136932373046875,
0.010602809488773346,
0.0606437511742115,
0.691925585269928,
0.2248997539281845,
0.3206327557563782,
0.5348027944564819,
0.3054993152618408,
0.07003742456436157,
0.2205769568681717,
0.42197325825691223,
-0.24774007499217987,
-0.15707050263881683,... |
https://github.com/huggingface/datasets/issues/6279 | This is exactly what I was looking for. It would also be very useful for me :-) | Batched IterableDataset | ### Feature request
Hi,
could you add an implementation of a batched `IterableDataset`. It already support an option to do batch iteration via `.iter(batch_size=...)` but this cannot be used in combination with a torch `DataLoader` since it just returns an iterator.
### Motivation
The current implementation load... | 17 | Batched IterableDataset
### Feature request
Hi,
could you add an implementation of a batched `IterableDataset`. It already support an option to do batch iteration via `.iter(batch_size=...)` but this cannot be used in combination with a torch `DataLoader` since it just returns an iterator.
### Motivation
The c... | [
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0.10285609215... |
https://github.com/huggingface/datasets/issues/6277 | `evaluate.load("paws-x", "es")` throws the error because there is no such metric in the `evaluate` lib.
So, this is unrelated to our lib. | FileNotFoundError: Couldn't find a module script at /content/paws-x/paws-x.py. Module 'paws-x' doesn't exist on the Hugging Face Hub either. | ### Describe the bug
I'm encountering a "FileNotFoundError" while attempting to use the "paws-x" dataset to retrain the DistilRoBERTa-base model. The error message is as follows:
FileNotFoundError: Couldn't find a module script at /content/paws-x/paws-x.py. Module 'paws-x' doesn't exist on the Hugging Face Hub eit... | 22 | FileNotFoundError: Couldn't find a module script at /content/paws-x/paws-x.py. Module 'paws-x' doesn't exist on the Hugging Face Hub either.
### Describe the bug
I'm encountering a "FileNotFoundError" while attempting to use the "paws-x" dataset to retrain the DistilRoBERTa-base model. The error message is as follow... | [
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0.42050763964653015,
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0.37824612855911255,
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0.1366032361984253,
-0.07175462692975998,
0.091070927679538... |
https://github.com/huggingface/datasets/issues/6276 | Since you are using Windows, maybe moving the `map` call inside `if __name__ == "__main__"` can fix the issue:
```python
if __name__ == "__main__":
common_voice = common_voice.map(prepare_dataset, remove_columns=common_voice.column_names["train"], num_proc=4)
```
Otherwise, the only solution is to set `num_... | I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error | ### Describe the bug
I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error, i'm following the steps in this blog post
https://huggingface.co/blog/fine-tune-whisper
I tried google collab and it works but because I'm on the free version the training ... | 38 | I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error
### Describe the bug
I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error, i'm following the steps in this blog post
https://hugg... | [
-0.05113082751631737,
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0.10620424896478653,
0.22932514548301697,
0.37092652916908264,
0.1690148264169693,
0.1730194091796875,
0.33574602007865906,
0.06762866675853729,
0.22165171802043915,
-0.4041449725627899,
0.15247999131679535,
-0.10573357343673706,
0.26564562320709... |
https://github.com/huggingface/datasets/issues/6276 | > Since you are using Windows, maybe moving the `map` call inside `if __name__ == "__main__"` can fix the issue:
>
> ```python
> if __name__ == "__main__":
> common_voice = common_voice.map(prepare_dataset, remove_columns=common_voice.column_names["train"], num_proc=4)
> ```
>
> Otherwise, the only solutio... | I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error | ### Describe the bug
I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error, i'm following the steps in this blog post
https://huggingface.co/blog/fine-tune-whisper
I tried google collab and it works but because I'm on the free version the training ... | 100 | I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error
### Describe the bug
I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error, i'm following the steps in this blog post
https://hugg... | [
-0.05113082751631737,
-0.24175772070884705,
0.10620424896478653,
0.22932514548301697,
0.37092652916908264,
0.1690148264169693,
0.1730194091796875,
0.33574602007865906,
0.06762866675853729,
0.22165171802043915,
-0.4041449725627899,
0.15247999131679535,
-0.10573357343673706,
0.26564562320709... |
https://github.com/huggingface/datasets/issues/6276 | Firstly, you didn't define feature_extractor variable. Secondly, it is large nlp model. Hence you should use proper gpu, otherwise your machine's cpu will be overclock and you can do nothing. | I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error | ### Describe the bug
I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error, i'm following the steps in this blog post
https://huggingface.co/blog/fine-tune-whisper
I tried google collab and it works but because I'm on the free version the training ... | 30 | I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error
### Describe the bug
I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error, i'm following the steps in this blog post
https://hugg... | [
-0.05113082751631737,
-0.24175772070884705,
0.10620424896478653,
0.22932514548301697,
0.37092652916908264,
0.1690148264169693,
0.1730194091796875,
0.33574602007865906,
0.06762866675853729,
0.22165171802043915,
-0.4041449725627899,
0.15247999131679535,
-0.10573357343673706,
0.26564562320709... |
https://github.com/huggingface/datasets/issues/6275 | Hi! The process of contributing a dataset is explained here: https://huggingface.co/docs/datasets/upload_dataset. Also, check https://huggingface.co/docs/datasets/image_dataset for a more detailed explanation of how to share an image dataset. | Would like to Contribute a dataset | I have a dataset of 2500 images that can be used for color-blind machine-learning algorithms. Since , there was no dataset available online , I made this dataset myself and would like to contribute this now to community | 26 | Would like to Contribute a dataset
I have a dataset of 2500 images that can be used for color-blind machine-learning algorithms. Since , there was no dataset available online , I made this dataset myself and would like to contribute this now to community
Hi! The process of contributing a dataset is explained here: ... | [
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0.11698678135871887,
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0.0649142861366272,
0.0920683741569519,
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0.23023587465286255,
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0.067618228495121,
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0.28108650445... |
https://github.com/huggingface/datasets/issues/6274 | Please tell me if the above info is not enough for solving the problem. I will then make my dataset public temporarily so that you can really reproduce the bug. | FileNotFoundError for dataset with multiple builder config | ### Describe the bug
When there is only one config and only the dataset name is entered when using datasets.load_dataset(), it works fine. But if I create a second builder_config for my dataset and enter the config name when using datasets.load_dataset(), the following error will happen.
FileNotFoundError: [Errno 2... | 30 | FileNotFoundError for dataset with multiple builder config
### Describe the bug
When there is only one config and only the dataset name is entered when using datasets.load_dataset(), it works fine. But if I create a second builder_config for my dataset and enter the config name when using datasets.load_dataset(), th... | [
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-0.19434937834739685,
0.28827038407325745,
0.07692147046327591,
0.031066328287124634,
-0.15260234475135803,
-0.20774042606... |
https://github.com/huggingface/datasets/issues/6273 | @lhoestq @albertvillanova @lewtun I don't think we are allowed to host these data files on the Hub (due to DMCA), which means the only option is to use a different dataset in the course (and to re-record the video 🙂), no? | Broken Link to PubMed Abstracts dataset . | ### Describe the bug
The link provided for the dataset is broken,
data_files =
[https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst](url)
The
### Steps to reproduce the bug
Steps to reproduce:
1) Head over to [https://huggingface.co/learn/nlp-course/chapt... | 41 | Broken Link to PubMed Abstracts dataset .
### Describe the bug
The link provided for the dataset is broken,
data_files =
[https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst](url)
The
### Steps to reproduce the bug
Steps to reproduce:
1) Head over to [h... | [
-0.13592590391635895,
0.2072862982749939,
0.02040146291255951,
0.06155046820640564,
-0.1800803542137146,
0.10274598002433777,
0.35781750082969666,
0.40044793486595154,
-0.03925119712948799,
-0.14947360754013062,
0.15373943746089935,
0.28599804639816284,
0.00019788742065429688,
0.1266424953... |
https://github.com/huggingface/datasets/issues/6273 | Keeping the video is maybe fine, we can add a note on youtube to suggest to load a dataset with a different name. Maybe C4 ? And update the code snippets on the website ? | Broken Link to PubMed Abstracts dataset . | ### Describe the bug
The link provided for the dataset is broken,
data_files =
[https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst](url)
The
### Steps to reproduce the bug
Steps to reproduce:
1) Head over to [https://huggingface.co/learn/nlp-course/chapt... | 35 | Broken Link to PubMed Abstracts dataset .
### Describe the bug
The link provided for the dataset is broken,
data_files =
[https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst](url)
The
### Steps to reproduce the bug
Steps to reproduce:
1) Head over to [h... | [
-0.04150284081697464,
0.3160797953605652,
-0.021375423297286034,
-0.03278052806854248,
-0.0857972502708435,
0.026594944298267365,
0.33419814705848694,
0.4359488785266876,
-0.18444597721099854,
-0.18531033396720886,
0.19457286596298218,
0.27567416429519653,
0.03499675542116165,
0.1650611758... |
https://github.com/huggingface/datasets/issues/6273 | Maybe you want to try it with the PUBMED dataset that I reproduced based on the The [PubMed Abstract GitHub Site](http://github.com/thoppe/The-Pile-PubMed) and uploaded on the HuggingFace:
```
from datasets import load_dataset
pubmed_dataset = load_dataset("hwang2006/PUBMED_title_abstracts_2020_baseline")
pubmed_... | Broken Link to PubMed Abstracts dataset . | ### Describe the bug
The link provided for the dataset is broken,
data_files =
[https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst](url)
The
### Steps to reproduce the bug
Steps to reproduce:
1) Head over to [https://huggingface.co/learn/nlp-course/chapt... | 63 | Broken Link to PubMed Abstracts dataset .
### Describe the bug
The link provided for the dataset is broken,
data_files =
[https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst](url)
The
### Steps to reproduce the bug
Steps to reproduce:
1) Head over to [h... | [
0.053189292550086975,
0.2400374561548233,
0.01789788529276848,
-0.11713257431983948,
0.03730643913149834,
0.05982741713523865,
0.2670304775238037,
0.4082258343696594,
-0.0903175100684166,
-0.08971862494945526,
0.06688192486763,
0.3428689241409302,
0.02864374965429306,
0.05629585683345795,
... |
https://github.com/huggingface/datasets/issues/6272 | I think it's best to drop duplicates with a `set` (as a temporary fix) and improve the patterns when/if https://github.com/fsspec/filesystem_spec/pull/1382 gets merged. @lhoestq Do you have some other ideas? | Duplicate `data_files` when named `<split>/<split>.parquet` | e.g. with `u23429/stock_1_minute_ticker`
```ipython
In [1]: from datasets import *
In [2]: b = load_dataset_builder("u23429/stock_1_minute_ticker")
Downloading readme: 100%|██████████████████████████| 627/627 [00:00<00:00, 246kB/s]
In [3]: b.config.data_files
Out[3]:
{NamedSplit('train'): ['hf://datasets/... | 29 | Duplicate `data_files` when named `<split>/<split>.parquet`
e.g. with `u23429/stock_1_minute_ticker`
```ipython
In [1]: from datasets import *
In [2]: b = load_dataset_builder("u23429/stock_1_minute_ticker")
Downloading readme: 100%|██████████████████████████| 627/627 [00:00<00:00, 246kB/s]
In [3]: b.confi... | [
-0.30908650159835815,
-0.11631924659013748,
-0.11791282892227173,
0.39790865778923035,
0.30234766006469727,
0.1111975759267807,
0.3349858820438385,
0.4634609818458557,
0.019552171230316162,
0.3075334429740906,
-0.10650788247585297,
0.324413001537323,
-0.08251963555812836,
0.258166432380676... |
https://github.com/huggingface/datasets/issues/6272 | Alternatively we could just use this no ?
```python
if config.FSSPEC_VERSION < version.parse("2023.9.0"):
KEYWORDS_IN_PATH_NAME_BASE_PATTERNS = [
"{keyword}[{sep}/]**",
"**[{sep}]{keyword}[{sep}/]**",
"**/{keyword}[{sep}/]**",
]
else:
KEYWORDS_IN_PATH_NAME_BASE_PATTERNS = ... | Duplicate `data_files` when named `<split>/<split>.parquet` | e.g. with `u23429/stock_1_minute_ticker`
```ipython
In [1]: from datasets import *
In [2]: b = load_dataset_builder("u23429/stock_1_minute_ticker")
Downloading readme: 100%|██████████████████████████| 627/627 [00:00<00:00, 246kB/s]
In [3]: b.config.data_files
Out[3]:
{NamedSplit('train'): ['hf://datasets/... | 66 | Duplicate `data_files` when named `<split>/<split>.parquet`
e.g. with `u23429/stock_1_minute_ticker`
```ipython
In [1]: from datasets import *
In [2]: b = load_dataset_builder("u23429/stock_1_minute_ticker")
Downloading readme: 100%|██████████████████████████| 627/627 [00:00<00:00, 246kB/s]
In [3]: b.confi... | [
-0.30908650159835815,
-0.11631924659013748,
-0.11791282892227173,
0.39790865778923035,
0.30234766006469727,
0.1111975759267807,
0.3349858820438385,
0.4634609818458557,
0.019552171230316162,
0.3075334429740906,
-0.10650788247585297,
0.324413001537323,
-0.08251963555812836,
0.258166432380676... |
https://github.com/huggingface/datasets/issues/6272 | Arf `"**/*/{keyword}[{sep}/]**"` does return `data/keyword.txt` in latest `fsspec` but not in `glob.glob`
EDIT: actually forgot to set `recursive=True` | Duplicate `data_files` when named `<split>/<split>.parquet` | e.g. with `u23429/stock_1_minute_ticker`
```ipython
In [1]: from datasets import *
In [2]: b = load_dataset_builder("u23429/stock_1_minute_ticker")
Downloading readme: 100%|██████████████████████████| 627/627 [00:00<00:00, 246kB/s]
In [3]: b.config.data_files
Out[3]:
{NamedSplit('train'): ['hf://datasets/... | 18 | Duplicate `data_files` when named `<split>/<split>.parquet`
e.g. with `u23429/stock_1_minute_ticker`
```ipython
In [1]: from datasets import *
In [2]: b = load_dataset_builder("u23429/stock_1_minute_ticker")
Downloading readme: 100%|██████████████████████████| 627/627 [00:00<00:00, 246kB/s]
In [3]: b.confi... | [
-0.30908650159835815,
-0.11631924659013748,
-0.11791282892227173,
0.39790865778923035,
0.30234766006469727,
0.1111975759267807,
0.3349858820438385,
0.4634609818458557,
0.019552171230316162,
0.3075334429740906,
-0.10650788247585297,
0.324413001537323,
-0.08251963555812836,
0.258166432380676... |
https://github.com/huggingface/datasets/issues/6272 | > I think it's best to drop duplicates with a set (as a temporary fix)
I started https://github.com/huggingface/datasets/pull/6278 to use DataFilesSet objects instead of DataFilesList | Duplicate `data_files` when named `<split>/<split>.parquet` | e.g. with `u23429/stock_1_minute_ticker`
```ipython
In [1]: from datasets import *
In [2]: b = load_dataset_builder("u23429/stock_1_minute_ticker")
Downloading readme: 100%|██████████████████████████| 627/627 [00:00<00:00, 246kB/s]
In [3]: b.config.data_files
Out[3]:
{NamedSplit('train'): ['hf://datasets/... | 25 | Duplicate `data_files` when named `<split>/<split>.parquet`
e.g. with `u23429/stock_1_minute_ticker`
```ipython
In [1]: from datasets import *
In [2]: b = load_dataset_builder("u23429/stock_1_minute_ticker")
Downloading readme: 100%|██████████████████████████| 627/627 [00:00<00:00, 246kB/s]
In [3]: b.confi... | [
-0.30908650159835815,
-0.11631924659013748,
-0.11791282892227173,
0.39790865778923035,
0.30234766006469727,
0.1111975759267807,
0.3349858820438385,
0.4634609818458557,
0.019552171230316162,
0.3075334429740906,
-0.10650788247585297,
0.324413001537323,
-0.08251963555812836,
0.258166432380676... |
https://github.com/huggingface/datasets/issues/6270 | `gen_kwargs` should be a `dict`, as stated in the docstring, but you are passing a `list`.
So, to fix the error, replace the list of dicts with a dict of lists (and slightly modify the generator function):
```python
from pathlib import Path
import datasets
def process_yaml(files):
for f in files:
... | Dataset.from_generator raises with sharded gen_args | ### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards in `gen_kwargs`.
```
So I'd expect that if gen_kwar... | 74 | Dataset.from_generator raises with sharded gen_args
### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards... | [
-0.15784285962581635,
-0.10980907082557678,
-0.023734301328659058,
0.26803869009017944,
0.4730006158351898,
-0.033754147589206696,
0.549604058265686,
0.1978403627872467,
-0.1852407455444336,
0.12854865193367004,
0.3643640875816345,
0.3822571337223053,
-0.16803902387619019,
0.01155213266611... |
https://github.com/huggingface/datasets/issues/6270 | That runs, and because my dataset is small, it's what I did to get past the problem.
However, it does not produce a sharded dataset. From the doc string I expect there ought to be a way to call from_generator such that num_shards in the resulting data set is equal to the number of items in the list.
The part of the ... | Dataset.from_generator raises with sharded gen_args | ### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards in `gen_kwargs`.
```
So I'd expect that if gen_kwar... | 108 | Dataset.from_generator raises with sharded gen_args
### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards... | [
-0.15784285962581635,
-0.10980907082557678,
-0.023734301328659058,
0.26803869009017944,
0.4730006158351898,
-0.033754147589206696,
0.549604058265686,
0.1978403627872467,
-0.1852407455444336,
0.12854865193367004,
0.3643640875816345,
0.3822571337223053,
-0.16803902387619019,
0.01155213266611... |
https://github.com/huggingface/datasets/issues/6270 | The sharding mentioned here refers to using this function with `num_proc` (multiprocessing splits the `kwargs` into shards and passes them to the generator function)
> That runs, and because my dataset is small, it's what I did to get past the problem.
`from_generator` generates a memory-mapped dataset (can be la... | Dataset.from_generator raises with sharded gen_args | ### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards in `gen_kwargs`.
```
So I'd expect that if gen_kwar... | 72 | Dataset.from_generator raises with sharded gen_args
### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards... | [
-0.15784285962581635,
-0.10980907082557678,
-0.023734301328659058,
0.26803869009017944,
0.4730006158351898,
-0.033754147589206696,
0.549604058265686,
0.1978403627872467,
-0.1852407455444336,
0.12854865193367004,
0.3643640875816345,
0.3822571337223053,
-0.16803902387619019,
0.01155213266611... |
https://github.com/huggingface/datasets/issues/6270 | It sounds like you are saying that num_proc affects the form of gen_kwargs.
Are you saying that for non-zero num_proc gen_kwargs should be a list whose length is the same as num_proc?
Or are you saying that for non-zero num_proc, gen_kwargs should be a dict whose elements are lists the length of num_proc?
| Dataset.from_generator raises with sharded gen_args | ### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards in `gen_kwargs`.
```
So I'd expect that if gen_kwar... | 53 | Dataset.from_generator raises with sharded gen_args
### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards... | [
-0.15784285962581635,
-0.10980907082557678,
-0.023734301328659058,
0.26803869009017944,
0.4730006158351898,
-0.033754147589206696,
0.549604058265686,
0.1978403627872467,
-0.1852407455444336,
0.12854865193367004,
0.3643640875816345,
0.3822571337223053,
-0.16803902387619019,
0.01155213266611... |
https://github.com/huggingface/datasets/issues/6270 | I ran some tests. So, it looks like with num_proc greater than 1, gen_kwargs is expected to be a dict of lists. It calls the generator also with a dict of lists, but the lists are split.
I.E. if my original has `gen_kwargs=dict(a=[0,1,2])`, then my generator might get called with `gen_kwalrgs=dict([0])`.
That all m... | Dataset.from_generator raises with sharded gen_args | ### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards in `gen_kwargs`.
```
So I'd expect that if gen_kwar... | 139 | Dataset.from_generator raises with sharded gen_args
### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards... | [
-0.15784285962581635,
-0.10980907082557678,
-0.023734301328659058,
0.26803869009017944,
0.4730006158351898,
-0.033754147589206696,
0.549604058265686,
0.1978403627872467,
-0.1852407455444336,
0.12854865193367004,
0.3643640875816345,
0.3822571337223053,
-0.16803902387619019,
0.01155213266611... |
https://github.com/huggingface/datasets/issues/6270 | Okay, that was fun; I took a dive through the dataset code and feel like I have a much better understanding.
Here is my understanding of the behavior:
* max_proc is an upper limit on the number of shards that `from_generator` produces
* If `max_proc` is greater than 1, then all lists in *gen_kwargs* must be the same... | Dataset.from_generator raises with sharded gen_args | ### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards in `gen_kwargs`.
```
So I'd expect that if gen_kwar... | 161 | Dataset.from_generator raises with sharded gen_args
### Describe the bug
According to the docs of Datasets.from_generator:
```
gen_kwargs(`dict`, *optional*):
Keyword arguments to be passed to the `generator` callable.
You can define a sharded dataset by passing the list of shards... | [
-0.15784285962581635,
-0.10980907082557678,
-0.023734301328659058,
0.26803869009017944,
0.4730006158351898,
-0.033754147589206696,
0.549604058265686,
0.1978403627872467,
-0.1852407455444336,
0.12854865193367004,
0.3643640875816345,
0.3822571337223053,
-0.16803902387619019,
0.01155213266611... |
https://github.com/huggingface/datasets/issues/6267 | You can use a `Sequence(ClassLabel(...))` feature type to represent a list of labels, and `cast_column`/`cast` to perform the "string to label" conversion (`class_encode_column` does support nested fields), e.g., in your case:
```python
from datasets import Dataset, Sequence, ClassLabel
data = {
'text': ['one'... | Multi label class encoding | ### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like to encode:
```
data = {
... | 66 | Multi label class encoding
### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like... | [
0.13402794301509857,
0.1659838855266571,
0.07211393117904663,
0.2635546326637268,
0.344813734292984,
0.13794733583927155,
0.7133165597915649,
-0.18815426528453827,
0.0459604486823082,
-0.022461630403995514,
0.12441209703683853,
0.4255562126636505,
-0.25185367465019226,
0.558788537979126,
... |
https://github.com/huggingface/datasets/issues/6267 | Great! Can you elaborate on "class_encode_column does support nested fields"? Do you mean that there is a way to `class_encode_column` on a Sequence? | Multi label class encoding | ### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like to encode:
```
data = {
... | 23 | Multi label class encoding
### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like... | [
0.13402794301509857,
0.1659838855266571,
0.07211393117904663,
0.2635546326637268,
0.344813734292984,
0.13794733583927155,
0.7133165597915649,
-0.18815426528453827,
0.0459604486823082,
-0.022461630403995514,
0.12441209703683853,
0.4255562126636505,
-0.25185367465019226,
0.558788537979126,
... |
https://github.com/huggingface/datasets/issues/6267 | Sorry, I'm still not following. Are you saying that there currently exists a way to call `class_encode_column` on a `Sequence(ClassLabel)` type? Or that the underlying data structures support it and a contribution of a method to do that would be welcome? | Multi label class encoding | ### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like to encode:
```
data = {
... | 41 | Multi label class encoding
### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like... | [
0.13402794301509857,
0.1659838855266571,
0.07211393117904663,
0.2635546326637268,
0.344813734292984,
0.13794733583927155,
0.7133165597915649,
-0.18815426528453827,
0.0459604486823082,
-0.022461630403995514,
0.12441209703683853,
0.4255562126636505,
-0.25185367465019226,
0.558788537979126,
... |
https://github.com/huggingface/datasets/issues/6267 | `class_encode_column ` currently does not support `Sequence(ClassLabel)`. Implementing support for this would be a nice contribution.
In the meantime, this limitation can be circumvented by fetching (unique) labels and calling `.cast_column(col, Sequence(ClassLabel(names=labels)))`. | Multi label class encoding | ### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like to encode:
```
data = {
... | 32 | Multi label class encoding
### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like... | [
0.13402794301509857,
0.1659838855266571,
0.07211393117904663,
0.2635546326637268,
0.344813734292984,
0.13794733583927155,
0.7133165597915649,
-0.18815426528453827,
0.0459604486823082,
-0.022461630403995514,
0.12441209703683853,
0.4255562126636505,
-0.25185367465019226,
0.558788537979126,
... |
https://github.com/huggingface/datasets/issues/6267 | Ok makes sense, can you take a look at the POC implementation I did [here](https://github.com/huggingface/datasets/commit/15443098e9ce053943172f7ec6fce3769d7dff6e)? Happy to take another pass / submit as a PR but would be helpful if I got a thumbs up that this was directionally correct with respect to implementation /... | Multi label class encoding | ### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like to encode:
```
data = {
... | 46 | Multi label class encoding
### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like... | [
0.13402794301509857,
0.1659838855266571,
0.07211393117904663,
0.2635546326637268,
0.344813734292984,
0.13794733583927155,
0.7133165597915649,
-0.18815426528453827,
0.0459604486823082,
-0.022461630403995514,
0.12441209703683853,
0.4255562126636505,
-0.25185367465019226,
0.558788537979126,
... |
https://github.com/huggingface/datasets/issues/6267 | There is no need to introduce a new type (`MultiLabel`) for this feature. Also, I think we can keep the logic inside a single method instead of separating the two cases.
Maybe https://github.com/huggingface/datasets/pull/4277 can help with the implementation. We extended `align_labels_with_mapping` to support `Seque... | Multi label class encoding | ### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like to encode:
```
data = {
... | 53 | Multi label class encoding
### Feature request
I have a multi label dataset and I'd like to be able to class encode the column and store the mapping directly in the features just as I can with a single label column. `class_encode_column` currently does not support multi labels.
Here's an example of what I'd like... | [
0.13402794301509857,
0.1659838855266571,
0.07211393117904663,
0.2635546326637268,
0.344813734292984,
0.13794733583927155,
0.7133165597915649,
-0.18815426528453827,
0.0459604486823082,
-0.022461630403995514,
0.12441209703683853,
0.4255562126636505,
-0.25185367465019226,
0.558788537979126,
... |
https://github.com/huggingface/datasets/issues/6261 | `JourneyDB/JourneyDB` is a gated dataset, so this error means you are not authenticated to access it, either by using an invalid token or by not agreeing to the terms in the dialog on the dataset page.
> I believe is due to the fact that doesn't work with .tgz files.
Indeed, the dataset's data files structure is ... | Can't load a dataset | ### Describe the bug
Can't seem to load the JourneyDB dataset.
It throws the following error:
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
Cell In[15], line 2
1 # If the dataset is gated/priv... | 84 | Can't load a dataset
### Describe the bug
Can't seem to load the JourneyDB dataset.
It throws the following error:
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
Cell In[15], line 2
1 # If th... | [
-0.40633130073547363,
-0.12175323814153671,
-0.026935188099741936,
0.4848688840866089,
0.4381573498249054,
0.12115108966827393,
0.25170496106147766,
0.23180124163627625,
-0.07087205350399017,
-0.11361230909824371,
-0.18910205364227295,
0.0730496346950531,
-0.13830894231796265,
0.3248365521... |
https://github.com/huggingface/datasets/issues/6261 | > JourneyDB/JourneyDB is a gated dataset, so this error means you are not authenticated to access it, either by using an invalid token or by not agreeing to the terms in the dialog on the dataset page.´
I did authentication with:
```
from huggingface_hub import notebook_login
notebook_login()
```
Isn't that... | Can't load a dataset | ### Describe the bug
Can't seem to load the JourneyDB dataset.
It throws the following error:
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
Cell In[15], line 2
1 # If the dataset is gated/priv... | 99 | Can't load a dataset
### Describe the bug
Can't seem to load the JourneyDB dataset.
It throws the following error:
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
Cell In[15], line 2
1 # If th... | [
-0.40633130073547363,
-0.12175323814153671,
-0.026935188099741936,
0.4848688840866089,
0.4381573498249054,
0.12115108966827393,
0.25170496106147766,
0.23180124163627625,
-0.07087205350399017,
-0.11361230909824371,
-0.18910205364227295,
0.0730496346950531,
-0.13830894231796265,
0.3248365521... |
https://github.com/huggingface/datasets/issues/6261 | Have you accepted the terms in the dialog [here](https://huggingface.co/datasets/JourneyDB/JourneyDB)?
IIRC Kaggle preinstalls an outdated `datasets` version, so it's also a good idea to update it before importing `datasets` (and do the same for `huggingface_hub`) | Can't load a dataset | ### Describe the bug
Can't seem to load the JourneyDB dataset.
It throws the following error:
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
Cell In[15], line 2
1 # If the dataset is gated/priv... | 34 | Can't load a dataset
### Describe the bug
Can't seem to load the JourneyDB dataset.
It throws the following error:
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
Cell In[15], line 2
1 # If th... | [
-0.40633130073547363,
-0.12175323814153671,
-0.026935188099741936,
0.4848688840866089,
0.4381573498249054,
0.12115108966827393,
0.25170496106147766,
0.23180124163627625,
-0.07087205350399017,
-0.11361230909824371,
-0.18910205364227295,
0.0730496346950531,
-0.13830894231796265,
0.3248365521... |
https://github.com/huggingface/datasets/issues/6260 | Hi! Unfortunately, the current behavior is to delete the downloaded data when this error happens. So, I've opened a PR that removes the problematic import to avoid losing data due to `apache_beam` not being installed (we host the preprocessed version of `natual_questions` on the HF GCS, so requiring `apache_beam` in th... | REUSE_DATASET_IF_EXISTS don't work | ### Describe the bug
I use the following code to download natural_question dataset. Even though I have completely download it, the next time I run this code, the new download procedure will start and cover the original /data/lxy/NQ
config=datasets.DownloadConfig(resume_download=True,max_retries=100,cache_dir=r'/da... | 55 | REUSE_DATASET_IF_EXISTS don't work
### Describe the bug
I use the following code to download natural_question dataset. Even though I have completely download it, the next time I run this code, the new download procedure will start and cover the original /data/lxy/NQ
config=datasets.DownloadConfig(resume_downloa... | [
-0.12890778481960297,
-0.1194736510515213,
0.07241126149892807,
0.5413785576820374,
0.29882538318634033,
-0.18821358680725098,
0.042946361005306244,
0.15610699355602264,
0.19228515028953552,
-0.13517247140407562,
-0.047027964144945145,
0.22609251737594604,
-0.1140713021159172,
0.1977853327... |
https://github.com/huggingface/datasets/issues/6260 | Thanks for your reply. I met another question that I set `export HF_DATASETS_CACHE=/data/lxy/.cache` , but each time I run load_datasets, the datasets module still looking for NQ in the wrong default cache dir '/home/lxy/.cache' 。How to avoid this incorrect behavior. I am sure HF_DATASETS_CACHE was set correctly since ... | REUSE_DATASET_IF_EXISTS don't work | ### Describe the bug
I use the following code to download natural_question dataset. Even though I have completely download it, the next time I run this code, the new download procedure will start and cover the original /data/lxy/NQ
config=datasets.DownloadConfig(resume_download=True,max_retries=100,cache_dir=r'/da... | 76 | REUSE_DATASET_IF_EXISTS don't work
### Describe the bug
I use the following code to download natural_question dataset. Even though I have completely download it, the next time I run this code, the new download procedure will start and cover the original /data/lxy/NQ
config=datasets.DownloadConfig(resume_downloa... | [
-0.134069561958313,
-0.13712142407894135,
0.07219859957695007,
0.5493248701095581,
0.29133012890815735,
-0.18467098474502563,
0.04954855144023895,
0.15654130280017853,
0.1943472921848297,
-0.1361657828092575,
-0.04950104281306267,
0.22159229218959808,
-0.10119201987981796,
0.20472568273544... |
https://github.com/huggingface/datasets/issues/6260 | You need to set this variable before the `datasets` import. Then, you can use `import datasets; datasets.config.HF_DATASETS_CACHE` to verify the cache location. | REUSE_DATASET_IF_EXISTS don't work | ### Describe the bug
I use the following code to download natural_question dataset. Even though I have completely download it, the next time I run this code, the new download procedure will start and cover the original /data/lxy/NQ
config=datasets.DownloadConfig(resume_download=True,max_retries=100,cache_dir=r'/da... | 22 | REUSE_DATASET_IF_EXISTS don't work
### Describe the bug
I use the following code to download natural_question dataset. Even though I have completely download it, the next time I run this code, the new download procedure will start and cover the original /data/lxy/NQ
config=datasets.DownloadConfig(resume_downloa... | [
-0.14463192224502563,
-0.13387562334537506,
0.07233297824859619,
0.5405831336975098,
0.28377199172973633,
-0.18812668323516846,
0.03885795176029205,
0.1619945466518402,
0.19530384242534637,
-0.1288692057132721,
-0.04892313480377197,
0.21878160536289215,
-0.10770003497600555,
0.198762178421... |
https://github.com/huggingface/datasets/issues/6259 | Thanks for reporting this issue! We should be able to avoid this by making our `glob` patterns more precise. In the meantime, you can load the dataset by directly assigning splits to the data files:
```python
from datasets import load_dataset
ds = load_dataset("parquet", data_files={"train": "testing123/train/outpu... | Duplicated Rows When Loading Parquet Files from Root Directory with Subdirectories | ### Describe the bug
When parquet files are saved in "train" and "val" subdirectories under a root directory, and datasets are then loaded using `load_dataset("parquet", data_dir="root_directory")`, the resulting dataset has duplicated rows for both the training and validation sets.
### Steps to reproduce the bug... | 48 | Duplicated Rows When Loading Parquet Files from Root Directory with Subdirectories
### Describe the bug
When parquet files are saved in "train" and "val" subdirectories under a root directory, and datasets are then loaded using `load_dataset("parquet", data_dir="root_directory")`, the resulting dataset has duplica... | [
0.07662573456764221,
-0.0835937038064003,
0.09032228589057922,
0.7221016883850098,
0.19889137148857117,
0.22331413626670837,
0.21559706330299377,
0.19769978523254395,
-0.14783155918121338,
0.04660504311323166,
0.019547127187252045,
0.2700917422771454,
-0.021230950951576233,
0.1860109567642... |
https://github.com/huggingface/datasets/issues/6257 | how is your dataset structured? (file types, how many commits and files are you trying to push, etc) | HfHubHTTPError - exceeded our hourly quotas for action: commit | ### Describe the bug
I try to upload a very large dataset of images, and get the following error:
```
File /fsx-multigen/yuvalkirstain/miniconda/envs/pickapic/lib/python3.10/site-packages/huggingface_hub/hf_api.py:2712, in HfApi.create_commit(self, repo_id, operations, commit_message, commit_description, token, repo... | 18 | HfHubHTTPError - exceeded our hourly quotas for action: commit
### Describe the bug
I try to upload a very large dataset of images, and get the following error:
```
File /fsx-multigen/yuvalkirstain/miniconda/envs/pickapic/lib/python3.10/site-packages/huggingface_hub/hf_api.py:2712, in HfApi.create_commit(self, rep... | [
-0.03922600299119949,
-0.22926321625709534,
-0.018464691936969757,
0.09591218829154968,
0.08189208805561066,
-0.20637744665145874,
-0.14135736227035522,
0.3770289123058319,
0.12479234486818314,
0.24446263909339905,
-0.03737182170152664,
-0.36246365308761597,
-0.03629541024565697,
0.3728710... |
https://github.com/huggingface/datasets/issues/6257 | I succeeded in uploading it after several attempts with an hour gap between each attempt (inconvenient but worked). The final dataset is [here](https://huggingface.co/datasets/yuvalkirstain/pickapic_v2), code and context to the dataset can be found [here](https://github.com/yuvalkirstain/PickScore/).
I can close the i... | HfHubHTTPError - exceeded our hourly quotas for action: commit | ### Describe the bug
I try to upload a very large dataset of images, and get the following error:
```
File /fsx-multigen/yuvalkirstain/miniconda/envs/pickapic/lib/python3.10/site-packages/huggingface_hub/hf_api.py:2712, in HfApi.create_commit(self, repo_id, operations, commit_message, commit_description, token, repo... | 54 | HfHubHTTPError - exceeded our hourly quotas for action: commit
### Describe the bug
I try to upload a very large dataset of images, and get the following error:
```
File /fsx-multigen/yuvalkirstain/miniconda/envs/pickapic/lib/python3.10/site-packages/huggingface_hub/hf_api.py:2712, in HfApi.create_commit(self, rep... | [
-0.03922600299119949,
-0.22926321625709534,
-0.018464691936969757,
0.09591218829154968,
0.08189208805561066,
-0.20637744665145874,
-0.14135736227035522,
0.3770289123058319,
0.12479234486818314,
0.24446263909339905,
-0.03737182170152664,
-0.36246365308761597,
-0.03629541024565697,
0.3728710... |
https://github.com/huggingface/datasets/issues/6257 | We could fix this by creating a single commit for all the (Parquet) shards in `push_to_hub` instead of one commit per shard, as we currently do.
@Wauplin Any updates on the 2-step commit process suggested by you that we need to implement this? | HfHubHTTPError - exceeded our hourly quotas for action: commit | ### Describe the bug
I try to upload a very large dataset of images, and get the following error:
```
File /fsx-multigen/yuvalkirstain/miniconda/envs/pickapic/lib/python3.10/site-packages/huggingface_hub/hf_api.py:2712, in HfApi.create_commit(self, repo_id, operations, commit_message, commit_description, token, repo... | 43 | HfHubHTTPError - exceeded our hourly quotas for action: commit
### Describe the bug
I try to upload a very large dataset of images, and get the following error:
```
File /fsx-multigen/yuvalkirstain/miniconda/envs/pickapic/lib/python3.10/site-packages/huggingface_hub/hf_api.py:2712, in HfApi.create_commit(self, rep... | [
-0.03922600299119949,
-0.22926321625709534,
-0.018464691936969757,
0.09591218829154968,
0.08189208805561066,
-0.20637744665145874,
-0.14135736227035522,
0.3770289123058319,
0.12479234486818314,
0.24446263909339905,
-0.03737182170152664,
-0.36246365308761597,
-0.03629541024565697,
0.3728710... |
https://github.com/huggingface/datasets/issues/6257 | > Any updates on the 2-step commit process suggested by you that we need to implement this?
Re-prioritizing this, sorry. Will let you know but probably can be done this week. | HfHubHTTPError - exceeded our hourly quotas for action: commit | ### Describe the bug
I try to upload a very large dataset of images, and get the following error:
```
File /fsx-multigen/yuvalkirstain/miniconda/envs/pickapic/lib/python3.10/site-packages/huggingface_hub/hf_api.py:2712, in HfApi.create_commit(self, repo_id, operations, commit_message, commit_description, token, repo... | 31 | HfHubHTTPError - exceeded our hourly quotas for action: commit
### Describe the bug
I try to upload a very large dataset of images, and get the following error:
```
File /fsx-multigen/yuvalkirstain/miniconda/envs/pickapic/lib/python3.10/site-packages/huggingface_hub/hf_api.py:2712, in HfApi.create_commit(self, rep... | [
-0.03922600299119949,
-0.22926321625709534,
-0.018464691936969757,
0.09591218829154968,
0.08189208805561066,
-0.20637744665145874,
-0.14135736227035522,
0.3770289123058319,
0.12479234486818314,
0.24446263909339905,
-0.03737182170152664,
-0.36246365308761597,
-0.03629541024565697,
0.3728710... |
https://github.com/huggingface/datasets/issues/6256 | Can you share the error message?
Also, it would help if you could check whether `huggingface_hub`'s download behaves the same:
```python
from huggingface_hub import snapshot_download
snapshot_download("trec", repo_type="dataset", cache_dir='/path/to/my/dir)
```
In the next major release, we aim to switch to `... | load_dataset() function's cache_dir does not seems to work | ### Describe the bug
datasets version: 2.14.5
when trying to run the following command
trec = load_dataset('trec', split='train[:1000]', cache_dir='/path/to/my/dir')
I keep getting error saying the command does not have permission to the default cache directory on my macbook pro machine.
It seems the cache_... | 62 | load_dataset() function's cache_dir does not seems to work
### Describe the bug
datasets version: 2.14.5
when trying to run the following command
trec = load_dataset('trec', split='train[:1000]', cache_dir='/path/to/my/dir')
I keep getting error saying the command does not have permission to the default cache... | [
-0.2581050992012024,
-0.31126868724823,
0.074449323117733,
0.35234326124191284,
0.2933734655380249,
0.11308468878269196,
0.23795555531978607,
0.019046060740947723,
0.20983633399009705,
0.013005431741476059,
-0.3450019359588623,
0.17233601212501526,
0.018657244741916656,
0.04272048175334930... |
https://github.com/huggingface/datasets/issues/6252 | Indeed, it makes sense to do this by default.
In the meantime, you can use `.with_transform` to transpose the images when accessing them:
```python
import PIL.ImageOps
def exif_transpose_transform(batch):
batch["image"] = [PIL.ImageOps.exif_transpose(image) for image in batch["image"]]
return batch
... | exif_transpose not done to Image (PIL problem) | ### Feature request
I noticed that some of my images loaded using PIL have some metadata related to exif that can rotate them when loading.
Since the dataset.features.Image uses PIL for loading, the loaded image may be rotated (width and height will be inverted) thus for tasks as object detection and layoutLM this ca... | 41 | exif_transpose not done to Image (PIL problem)
### Feature request
I noticed that some of my images loaded using PIL have some metadata related to exif that can rotate them when loading.
Since the dataset.features.Image uses PIL for loading, the loaded image may be rotated (width and height will be inverted) thus f... | [
-0.20519578456878662,
-0.5333442687988281,
-0.02346695214509964,
-0.1588098257780075,
0.04967682063579559,
-0.08434915542602539,
0.47783219814300537,
-0.1194605603814125,
-0.10909018665552139,
0.23618438839912415,
0.25112542510032654,
0.2896171510219574,
0.05245703086256981,
0.356875509023... |
https://github.com/huggingface/datasets/issues/6252 | This operation sets some `Image` attributes to `None` (`.format`, `.filename`, etc.), causing our tests to fail, so I think we should wait for Datasets 3.0 to make this change. In version 3.0, storing image paths will be replaced by embedding image bytes, so there will be fewer instances where we use the `.filename` at... | exif_transpose not done to Image (PIL problem) | ### Feature request
I noticed that some of my images loaded using PIL have some metadata related to exif that can rotate them when loading.
Since the dataset.features.Image uses PIL for loading, the loaded image may be rotated (width and height will be inverted) thus for tasks as object detection and layoutLM this ca... | 54 | exif_transpose not done to Image (PIL problem)
### Feature request
I noticed that some of my images loaded using PIL have some metadata related to exif that can rotate them when loading.
Since the dataset.features.Image uses PIL for loading, the loaded image may be rotated (width and height will be inverted) thus f... | [
-0.23128995299339294,
-0.4324098229408264,
-0.013056017458438873,
-0.1380266398191452,
0.02748856693506241,
-0.08289014548063278,
0.439321905374527,
-0.12239617109298706,
-0.18614964187145233,
0.2433623969554901,
0.29795029759407043,
0.31367823481559753,
-0.007348254323005676,
0.4450425505... |
https://github.com/huggingface/datasets/issues/6246 | I think it's an issue with the code.
Specifically:
```python
dataset = dataset['train'].add_column("/workspace/data", new_column)
```
Now `dataset` is the train set with a new column.
To fix this, you can do:
```python
dataset['train'] = dataset['train'].add_column("/workspace/data", new_column)
``` | Add new column to dataset | ### Describe the bug
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[<ipython-input-9-bd197b36b6a0>](https://localhost:8080/#) in <cell line: 1>()
----> 1 dataset['train']['/workspace/data']
3 frames
[/... | 37 | Add new column to dataset
### Describe the bug
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[<ipython-input-9-bd197b36b6a0>](https://localhost:8080/#) in <cell line: 1>()
----> 1 dataset['train']['/work... | [
-0.052789218723773956,
-0.019655153155326843,
0.050946254283189774,
0.018657661974430084,
0.31316566467285156,
0.2104775607585907,
0.6760562062263489,
0.4645121693611145,
0.15509802103042603,
0.10611668229103088,
0.08632168173789978,
0.4922831058502197,
-0.18300923705101013,
0.182266980409... |
https://github.com/huggingface/datasets/issues/6246 | > I think it's an issue with the code.
>
> Specifically:
>
> ```python
> dataset = dataset['train'].add_column("/workspace/data", new_column)
> ```
>
> Now `dataset` is the train set with a new column. To fix this, you can do:
>
> ```python
> dataset['train'] = dataset['train'].add_column("/workspace/dat... | Add new column to dataset | ### Describe the bug
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[<ipython-input-9-bd197b36b6a0>](https://localhost:8080/#) in <cell line: 1>()
----> 1 dataset['train']['/workspace/data']
3 frames
[/... | 77 | Add new column to dataset
### Describe the bug
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[<ipython-input-9-bd197b36b6a0>](https://localhost:8080/#) in <cell line: 1>()
----> 1 dataset['train']['/work... | [
-0.06994634866714478,
-0.01698148250579834,
0.05168754979968071,
0.024547219276428223,
0.3096671402454376,
0.20680584013462067,
0.6639566421508789,
0.47558239102363586,
0.14351102709770203,
0.09803667664527893,
0.09017430245876312,
0.5036664605140686,
-0.2043507993221283,
0.188844949007034... |
https://github.com/huggingface/datasets/issues/6246 | I think there is a slight misunderstanding.
```python
new_column = ["mask"] * len(dataset["train"])
dataset['train'] = dataset['train'].add_column("/workspace/data", new_column)
```
adds a column with the string `mask` to your dataset.
If you're trying to load the images `"mask_{idx}.png"` in your dataset, you ... | Add new column to dataset | ### Describe the bug
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[<ipython-input-9-bd197b36b6a0>](https://localhost:8080/#) in <cell line: 1>()
----> 1 dataset['train']['/workspace/data']
3 frames
[/... | 96 | Add new column to dataset
### Describe the bug
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[<ipython-input-9-bd197b36b6a0>](https://localhost:8080/#) in <cell line: 1>()
----> 1 dataset['train']['/work... | [
-0.09843655675649643,
-0.027869805693626404,
0.023789644241333008,
0.10551737248897552,
0.2503960132598877,
0.15773145854473114,
0.7520943880081177,
0.3964082598686218,
0.21604499220848083,
0.17301049828529358,
-0.00021330267190933228,
0.3614157438278198,
-0.1275089979171753,
0.19663101434... |
https://github.com/huggingface/datasets/issues/6246 | > I think there is a slight misunderstanding.
>
> ```python
> new_column = ["mask"] * len(dataset["train"])
> dataset['train'] = dataset['train'].add_column("/workspace/data", new_column)
> ```
>
> adds a column with the string `mask` to your dataset. If you're trying to load the images `"mask_{idx}.png"` in y... | Add new column to dataset | ### Describe the bug
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[<ipython-input-9-bd197b36b6a0>](https://localhost:8080/#) in <cell line: 1>()
----> 1 dataset['train']['/workspace/data']
3 frames
[/... | 146 | Add new column to dataset
### Describe the bug
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[<ipython-input-9-bd197b36b6a0>](https://localhost:8080/#) in <cell line: 1>()
----> 1 dataset['train']['/work... | [
-0.09255671501159668,
-0.028486624360084534,
0.03623872995376587,
0.011011213064193726,
0.20684005320072174,
0.1633591651916504,
0.7571380734443665,
0.42502832412719727,
0.15506741404533386,
0.17447206377983093,
0.06612684577703476,
0.3907855451107025,
-0.12782692909240723,
0.2320630401372... |
https://github.com/huggingface/datasets/issues/6242 | While this issue may seem specific, it led to a silent problem in my workflow that took days to diagnose. If this feature is not intended to be supported, an error should be raised when encountering this configuration to prevent such issues. | Data alteration when loading dataset with unspecified inner sequence length | ### Describe the bug
When a dataset saved with a specified inner sequence length is loaded without specifying that length, the original data is altered and becomes inconsistent.
### Steps to reproduce the bug
```python
from datasets import Dataset, Features, Value, Sequence, load_dataset
# Repository ID
repo_id... | 42 | Data alteration when loading dataset with unspecified inner sequence length
### Describe the bug
When a dataset saved with a specified inner sequence length is loaded without specifying that length, the original data is altered and becomes inconsistent.
### Steps to reproduce the bug
```python
from datasets impor... | [
-0.03762386739253998,
-0.21157673001289368,
-0.10051356256008148,
0.3131217062473297,
0.245096355676651,
-0.11110161989927292,
0.29890602827072144,
0.12334597110748291,
-0.0025643929839134216,
0.268387109041214,
-0.008875593543052673,
0.34870365262031555,
0.08487316220998764,
0.16277542710... |
https://github.com/huggingface/datasets/issues/6242 | Thanks for reporting! This is a MRE:
```python
import pyarrow as pa
from datasets.table import cast_array_to_feature
from datasets import Sequence, Value
data = [
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]],
[[7.0, 8.0, 9.0], [10.0, 11.0, 12.0]],
]
arr = pa.array(data, pa.list_(pa.list_(pa.float32(), 3)))
ca... | Data alteration when loading dataset with unspecified inner sequence length | ### Describe the bug
When a dataset saved with a specified inner sequence length is loaded without specifying that length, the original data is altered and becomes inconsistent.
### Steps to reproduce the bug
```python
from datasets import Dataset, Features, Value, Sequence, load_dataset
# Repository ID
repo_id... | 52 | Data alteration when loading dataset with unspecified inner sequence length
### Describe the bug
When a dataset saved with a specified inner sequence length is loaded without specifying that length, the original data is altered and becomes inconsistent.
### Steps to reproduce the bug
```python
from datasets impor... | [
-0.03762386739253998,
-0.21157673001289368,
-0.10051356256008148,
0.3131217062473297,
0.245096355676651,
-0.11110161989927292,
0.29890602827072144,
0.12334597110748291,
-0.0025643929839134216,
0.268387109041214,
-0.008875593543052673,
0.34870365262031555,
0.08487316220998764,
0.16277542710... |
https://github.com/huggingface/datasets/issues/6240 | What type of dataset are you using in this script? `torch.utils.data.Dataset` or `datasets.Dataset`? Please share the `datasets` package version if it's the latter. Otherwise, it's better to move this issue to the `accelerate` repo. | Dataloader stuck on multiple GPUs | ### Describe the bug
I am trying to get CLIP to fine-tuning with my code.
When I tried to run it on multiple GPUs using accelerate, I encountered the following phenomenon.
- Validation dataloader stuck in 2nd epoch only on multi-GPU
Specifically, when the "for inputs in valid_loader:" process is finished, it does... | 34 | Dataloader stuck on multiple GPUs
### Describe the bug
I am trying to get CLIP to fine-tuning with my code.
When I tried to run it on multiple GPUs using accelerate, I encountered the following phenomenon.
- Validation dataloader stuck in 2nd epoch only on multi-GPU
Specifically, when the "for inputs in valid_l... | [
-0.16673842072486877,
-0.19584006071090698,
0.012823913246393204,
0.01672077551484108,
0.09490471333265305,
-0.1398051530122757,
0.6904860138893127,
0.1713944971561432,
-0.05128742381930351,
0.23313216865062714,
0.16659069061279297,
0.3453610837459564,
0.22014600038528442,
0.24625796079635... |
https://github.com/huggingface/datasets/issues/6240 | Very sorry, I thought I had a repo in `accelerate!`
I will close this issue and repo the issue in the appropriate place. | Dataloader stuck on multiple GPUs | ### Describe the bug
I am trying to get CLIP to fine-tuning with my code.
When I tried to run it on multiple GPUs using accelerate, I encountered the following phenomenon.
- Validation dataloader stuck in 2nd epoch only on multi-GPU
Specifically, when the "for inputs in valid_loader:" process is finished, it does... | 23 | Dataloader stuck on multiple GPUs
### Describe the bug
I am trying to get CLIP to fine-tuning with my code.
When I tried to run it on multiple GPUs using accelerate, I encountered the following phenomenon.
- Validation dataloader stuck in 2nd epoch only on multi-GPU
Specifically, when the "for inputs in valid_l... | [
-0.11724366247653961,
-0.1557527482509613,
0.0050024352967739105,
0.020393963903188705,
0.10015542060136795,
-0.15935344994068146,
0.6699702739715576,
0.13958662748336792,
-0.05459371209144592,
0.24758201837539673,
0.15198692679405212,
0.3250676691532135,
0.2378477156162262,
0.262586474418... |
https://github.com/huggingface/datasets/issues/6239 | I think this is the same issue as https://github.com/huggingface/datasets/issues/4776. Maybe installing `ffmpeg` can fix it:
```python
add-apt-repository -y ppa:savoury1/ffmpeg4
apt-get -qq install -y ffmpeg
```
However, the best solution is to use a newer version of `datasets`. In the recent releases, we've rep... | Load local audio data doesn't work | ### Describe the bug
I get a RuntimeError from the following code:
```python
audio_dataset = Dataset.from_dict({"audio": ["/kaggle/input/bengaliai-speech/train_mp3s/000005f3362c.mp3"]}).cast_column("audio", Audio())
audio_dataset[0]
```
### Traceback
<details>
```python
RuntimeError ... | 53 | Load local audio data doesn't work
### Describe the bug
I get a RuntimeError from the following code:
```python
audio_dataset = Dataset.from_dict({"audio": ["/kaggle/input/bengaliai-speech/train_mp3s/000005f3362c.mp3"]}).cast_column("audio", Audio())
audio_dataset[0]
```
### Traceback
<details>
`... | [
-0.43105602264404297,
-0.04621385037899017,
-0.00726998969912529,
0.417654424905777,
0.4488195478916168,
-0.18288666009902954,
0.4197095036506653,
0.24208593368530273,
-0.02707613632082939,
0.2821232080459595,
-0.36705154180526733,
0.6166728734970093,
-0.25378915667533875,
-0.0641502216458... |
https://github.com/huggingface/datasets/issues/6238 | `filter` treats the function's output as a (selection) mask - `True` keeps the sample, and `False` drops it. In your case, `bool(0)` evaluates to `False`, so dropping the first sample is the correct behavior. | `dataset.filter` ALWAYS removes the first item from the dataset when using batched=True | ### Describe the bug
If you call batched=True when calling `filter`, the first item is _always_ filtered out, regardless of the filter condition.
### Steps to reproduce the bug
Here's a minimal example:
```python
def filter_batch_always_true(batch, indices):
print("First index being passed into this filte... | 34 | `dataset.filter` ALWAYS removes the first item from the dataset when using batched=True
### Describe the bug
If you call batched=True when calling `filter`, the first item is _always_ filtered out, regardless of the filter condition.
### Steps to reproduce the bug
Here's a minimal example:
```python
def filt... | [
-0.24889422953128815,
-0.23401862382888794,
-0.17137563228607178,
-0.16107843816280365,
-0.19181180000305176,
-0.058566316962242126,
0.37126728892326355,
0.14128737151622772,
0.08032993972301483,
0.0980878621339798,
0.05337975174188614,
0.37346380949020386,
0.03651496767997742,
0.276137888... |
https://github.com/huggingface/datasets/issues/6237 | [This](https://huggingface.co/docs/datasets/nlp_process#map) is the most performant way to tokenize a dataset (`batched=True, num_proc=None, return_tensors="np"`)
If`tokenizer.is_fast` returns `True`, `num_proc` must be `None/1` to benefit from the fast tokenizers' parallelism (the fast tokenizers are implemented i... | Tokenization with multiple workers is too slow | I am trying to tokenize a few million documents with multiple workers but the tokenization process is taking forever.
Code snippet:
```
raw_datasets.map(
encode_function,
batched=False,
num_proc=args.preprocessing_num_workers,
load_from_cache_file=not args.ove... | 43 | Tokenization with multiple workers is too slow
I am trying to tokenize a few million documents with multiple workers but the tokenization process is taking forever.
Code snippet:
```
raw_datasets.map(
encode_function,
batched=False,
num_proc=args.preprocessing_num_worker... | [
-0.2808173894882202,
0.08872613310813904,
-0.14150390028953552,
-0.0760219395160675,
-0.20636089146137238,
-0.18386691808700562,
0.5079349875450134,
0.36032289266586304,
-0.09700481593608856,
0.15296486020088196,
0.1711222231388092,
0.19517117738723755,
-0.0392419770359993,
-0.249726906418... |
https://github.com/huggingface/datasets/issues/6236 | Hey! You can implement this yourself, just:
1) Create the dataset with `to_tf_dataset()` with `shuffle=False`
2) Add an `unbatch()` at the end (or use batch_size=1)
3) Add a `shuffle()` to the resulting dataset with your desired buffer size
4) Add a `batch()` at the end again to re-batch your dataset.
Note tha... | Support buffer shuffle for to_tf_dataset | ### Feature request
I'm using to_tf_dataset to convert a large dataset to tf.data.Dataset and use Keras fit to train model.
Currently, to_tf_dataset only supports full size shuffle, which can be very slow on large dataset.
tf.data.Dataset support buffer shuffle by default.
shuffle(
buffer_size, seed=None, r... | 118 | Support buffer shuffle for to_tf_dataset
### Feature request
I'm using to_tf_dataset to convert a large dataset to tf.data.Dataset and use Keras fit to train model.
Currently, to_tf_dataset only supports full size shuffle, which can be very slow on large dataset.
tf.data.Dataset support buffer shuffle by default... | [
-0.37784263491630554,
-0.26851511001586914,
-0.005736783146858215,
-0.11381540447473526,
0.3517449200153351,
0.323432594537735,
0.061275798827409744,
0.49831336736679077,
-0.07993004471063614,
0.4037872552871704,
-0.35117051005363464,
0.30224907398223877,
-0.475032776594162,
0.237854078412... |
https://github.com/huggingface/datasets/issues/6236 | Thanks for your reply! @Rocketknight1
"We don't actually shuffle the entire dataset in-memory, using tf.data.Dataset.shuffle()! Instead, we shuffle an index array and then load from the dataset with that."
In such case, there will be random access to dataset data during shuffling. When the dataset is large, the perf... | Support buffer shuffle for to_tf_dataset | ### Feature request
I'm using to_tf_dataset to convert a large dataset to tf.data.Dataset and use Keras fit to train model.
Currently, to_tf_dataset only supports full size shuffle, which can be very slow on large dataset.
tf.data.Dataset support buffer shuffle by default.
shuffle(
buffer_size, seed=None, r... | 76 | Support buffer shuffle for to_tf_dataset
### Feature request
I'm using to_tf_dataset to convert a large dataset to tf.data.Dataset and use Keras fit to train model.
Currently, to_tf_dataset only supports full size shuffle, which can be very slow on large dataset.
tf.data.Dataset support buffer shuffle by default... | [
-0.3856085538864136,
-0.2946014702320099,
0.0037971511483192444,
-0.04990128427743912,
0.3307363986968994,
0.3635885715484619,
0.05948565527796745,
0.5427847504615784,
-0.11980366706848145,
0.3561812937259674,
-0.34272798895835876,
0.3405897617340088,
-0.425658255815506,
0.1936900019645691... |
https://github.com/huggingface/datasets/issues/6229 | From what I see, `MMSegInferencer` supports NumPy arrays, so replace the line `image_path = example['image']` with `image_path = np.array(example['image'])` to fix the issue (`example["image"]` is a `PIL.Image` object). | Apply inference on all images in the dataset | ### Describe the bug
```
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
Cell In[14], line 11
9 for idx, example in enumerate(dataset['train']):
10 image_path = example['image']
---> 11 mask... | 28 | Apply inference on all images in the dataset
### Describe the bug
```
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
Cell In[14], line 11
9 for idx, example in enumerate(dataset['train']):
10 ... | [
-0.16085383296012878,
-0.25083857774734497,
-0.12638023495674133,
0.06236794963479042,
0.177998349070549,
-0.13726964592933655,
0.46878403425216675,
0.2857837378978729,
-0.16836467385292053,
0.47970694303512573,
0.05943524092435837,
0.309304416179657,
-0.1869792491197586,
-0.23190489411354... |
https://github.com/huggingface/datasets/issues/6229 | > From what I see, `MMSegInferencer` supports NumPy arrays, so replace the line `image_path = example['image']` with `image_path = np.array(example['image'])` to fix the issue (`example["image"]` is a `PIL.Image` object).
Thanks @mariosasko for your reply...
i tried :
```
# Define a function to apply the code to ... | Apply inference on all images in the dataset | ### Describe the bug
```
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
Cell In[14], line 11
9 for idx, example in enumerate(dataset['train']):
10 image_path = example['image']
---> 11 mask... | 638 | Apply inference on all images in the dataset
### Describe the bug
```
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
Cell In[14], line 11
9 for idx, example in enumerate(dataset['train']):
10 ... | [
-0.16085383296012878,
-0.25083857774734497,
-0.12638023495674133,
0.06236794963479042,
0.177998349070549,
-0.13726964592933655,
0.46878403425216675,
0.2857837378978729,
-0.16836467385292053,
0.47970694303512573,
0.05943524092435837,
0.309304416179657,
-0.1869792491197586,
-0.23190489411354... |
https://github.com/huggingface/datasets/issues/6221 | Not a fan of pickling this sort of stuff either.
Note that users can also share the code in their dataset documentation. | Support saving datasets with custom formatting | Requested in https://discuss.huggingface.co/t/using-set-transform-on-a-dataset-leads-to-an-exception/53036.
I am not sure if supporting this is the best idea for the following reasons:
>For this to work, we would have to pickle a custom transform, which means the transform and the objects it references need to be... | 22 | Support saving datasets with custom formatting
Requested in https://discuss.huggingface.co/t/using-set-transform-on-a-dataset-leads-to-an-exception/53036.
I am not sure if supporting this is the best idea for the following reasons:
>For this to work, we would have to pickle a custom transform, which means the t... | [
-0.23778676986694336,
-0.09020714461803436,
0.0006607063114643097,
0.07739213854074478,
0.36724480986595154,
0.11472795903682709,
0.30022862553596497,
0.0956723690032959,
-0.20880524814128876,
0.014439713209867477,
-0.13830327987670898,
0.07821661233901978,
-0.34521082043647766,
0.46991348... |
https://github.com/huggingface/datasets/issues/6217 | We need to implement the `Image` type as a PyArrow extension type (to allow us to override the Python conversion) for this to work as expected. For now, it's best to use your approach indeed. | `Dataset.to_dict()` ignore `decode=True` with Image feature | ### Describe the bug
`Dataset.to_dict` seems to ignore the decoding instruction passed in features.
### Steps to reproduce the bug
```python
import datasets
import numpy as np
from PIL import Image
img = np.random.randint(0, 256, (5, 5, 3), dtype=np.uint8)
img = Image.fromarray(img)
features = datasets.Fea... | 35 | `Dataset.to_dict()` ignore `decode=True` with Image feature
### Describe the bug
`Dataset.to_dict` seems to ignore the decoding instruction passed in features.
### Steps to reproduce the bug
```python
import datasets
import numpy as np
from PIL import Image
img = np.random.randint(0, 256, (5, 5, 3), dtype=np... | [
0.0348966121673584,
-0.20412680506706238,
-0.11633122712373734,
0.20876918733119965,
0.2717641592025757,
0.20352843403816223,
0.19232070446014404,
0.39373579621315,
-0.03279522433876991,
0.1958099752664566,
0.15691202878952026,
0.6271664500236511,
0.05341333895921707,
0.28227800130844116,
... |
https://github.com/huggingface/datasets/issues/6212 | Hi @exs-avianello, is it really needed? Note you can alternatively use `pathlib.Path` among others as it follows:
```python
import datasets
from pathlib import Path
# save a parquet file at ~/path/to/data.parquet
data_files = Path.home() / "path/to/data.parquet"
dataset = datasets.load_dataset("parquet", da... | Tilde (~) is not supported for data_files | ### Describe the bug
Attempting to `load_dataset` from a path starting with `~` (as a shorthand for the user's home directory) seems not to be fully working - at least as far as the `parquet` dataset builder is concerned.
(the same file can be loaded correctly if providing its absolute path instead)
I think that... | 41 | Tilde (~) is not supported for data_files
### Describe the bug
Attempting to `load_dataset` from a path starting with `~` (as a shorthand for the user's home directory) seems not to be fully working - at least as far as the `parquet` dataset builder is concerned.
(the same file can be loaded correctly if providin... | [
-0.4094029664993286,
0.05227942764759064,
0.030013274401426315,
0.43264785408973694,
0.4441775977611542,
-0.0865611881017685,
0.15651258826255798,
0.17398977279663086,
0.12685751914978027,
0.09496255218982697,
0.10140696913003922,
0.2661038041114807,
-0.2220899760723114,
0.2229696214199066... |
https://github.com/huggingface/datasets/issues/6212 | Hi @alvarobartt !
This is definitely just a "nice to have" and I am personally more than happy to just use absolute paths client-side. I just wanted to flag it up in case it can help improve the package even more 🙌 It might not be immediately obvious from the stack trace that the error is triggered by the `~` in t... | Tilde (~) is not supported for data_files | ### Describe the bug
Attempting to `load_dataset` from a path starting with `~` (as a shorthand for the user's home directory) seems not to be fully working - at least as far as the `parquet` dataset builder is concerned.
(the same file can be loaded correctly if providing its absolute path instead)
I think that... | 63 | Tilde (~) is not supported for data_files
### Describe the bug
Attempting to `load_dataset` from a path starting with `~` (as a shorthand for the user's home directory) seems not to be fully working - at least as far as the `parquet` dataset builder is concerned.
(the same file can be loaded correctly if providin... | [
-0.4094029664993286,
0.05227942764759064,
0.030013274401426315,
0.43264785408973694,
0.4441775977611542,
-0.0865611881017685,
0.15651258826255798,
0.17398977279663086,
0.12685751914978027,
0.09496255218982697,
0.10140696913003922,
0.2661038041114807,
-0.2220899760723114,
0.2229696214199066... |
https://github.com/huggingface/datasets/issues/6206 | I solved the problem by modifying the "self DEFAULT_WRITER_BATCH_SIZE" in "class MyDataset (datasets. GeneratorBasedBuilder) : __init__" | When calling load_dataset, raise error: pyarrow.lib.ArrowInvalid: offset overflow while concatenating arrays | ### Describe the bug
When calling load_dataset, raise error
```
Traceback (most recent call last):
File "/home/aihao/miniconda3/envs/torch/lib/python3.11/site-packages/datasets/builder.py", line 1694, in _pre
pare_split_single ... | 16 | When calling load_dataset, raise error: pyarrow.lib.ArrowInvalid: offset overflow while concatenating arrays
### Describe the bug
When calling load_dataset, raise error
```
Traceback (most recent call last):
File "/home/aihao/minico... | [
-0.4871370792388916,
-0.0712931826710701,
-0.06189573183655739,
0.5471633672714233,
0.14621853828430176,
-0.06050470471382141,
0.3858751058578491,
0.27677014470100403,
-0.508307695388794,
0.2028869092464447,
0.12906524538993835,
0.4395868480205536,
0.10653211176395416,
-0.03990921005606651... |
https://github.com/huggingface/datasets/issues/6203 | (cross-posting from the linked DVC issue)
I think this should already work out of the box with the current `datasets` and `dvc.api` releases by passing the correct `storage_options` into the datasets calls. `storage_options` is essentially just the kwargs dict that gets passed to the fsspec fs constructor.
The ma... | Support loading from a DVC remote repository | ### Feature request
Adding support for loading a file from a DVC repository, tracked remotely on a SCM.
### Motivation
DVC is a popular version control system to version and manage datasets. The files are stored on a remote object storage platform, but they are tracked using Git. Integration with DVC is possible thr... | 175 | Support loading from a DVC remote repository
### Feature request
Adding support for loading a file from a DVC repository, tracked remotely on a SCM.
### Motivation
DVC is a popular version control system to version and manage datasets. The files are stored on a remote object storage platform, but they are tracked ... | [
-0.1739344596862793,
0.18651391565799713,
0.04655923694372177,
-0.03338225558400154,
0.27074846625328064,
-0.36072176694869995,
0.2354198694229126,
0.035695672035217285,
0.10046906769275665,
-0.09577052295207977,
0.07728295773267746,
0.40473347902297974,
-0.15993854403495789,
0.41130471229... |
https://github.com/huggingface/datasets/issues/6203 | Hi @pmrowla Thank you for your help, that's very helpful, I was indeed using `fsspec` incorrectly here. There is still an issue with `datasets`:
```python
import datasets
dataset = datasets.load_dataset("json", data_files="dvc://folder/file.jsonl", storage_options={"url": "https://gitlab.com/repo/folder/"})
```
... | Support loading from a DVC remote repository | ### Feature request
Adding support for loading a file from a DVC repository, tracked remotely on a SCM.
### Motivation
DVC is a popular version control system to version and manage datasets. The files are stored on a remote object storage platform, but they are tracked using Git. Integration with DVC is possible thr... | 327 | Support loading from a DVC remote repository
### Feature request
Adding support for loading a file from a DVC repository, tracked remotely on a SCM.
### Motivation
DVC is a popular version control system to version and manage datasets. The files are stored on a remote object storage platform, but they are tracked ... | [
-0.14952722191810608,
0.13017386198043823,
0.03631466627120972,
-0.03125686198472977,
0.2512752413749695,
-0.36142194271087646,
0.25599178671836853,
0.04165944829583168,
0.11361847817897797,
-0.09889458119869232,
0.1056753396987915,
0.35265541076660156,
-0.17089712619781494,
0.396522045135... |
https://github.com/huggingface/datasets/issues/6203 | For the record, there was a `dvc.api.DVCFileSystem` bug which is fixed in DVC `main` and will be available in the next DVC release.
To use DVC with `datasets` you just need to pass the Git/DVC repo `url` in `storage_options` as discussed above.
(note that this requires having both `datasets` and `dvc` installed i... | Support loading from a DVC remote repository | ### Feature request
Adding support for loading a file from a DVC repository, tracked remotely on a SCM.
### Motivation
DVC is a popular version control system to version and manage datasets. The files are stored on a remote object storage platform, but they are tracked using Git. Integration with DVC is possible thr... | 130 | Support loading from a DVC remote repository
### Feature request
Adding support for loading a file from a DVC repository, tracked remotely on a SCM.
### Motivation
DVC is a popular version control system to version and manage datasets. The files are stored on a remote object storage platform, but they are tracked ... | [
-0.17393767833709717,
0.17896315455436707,
0.0372188538312912,
-0.04128967598080635,
0.2395937144756317,
-0.3132011592388153,
0.2638843059539795,
0.054811906069517136,
0.09661697596311569,
-0.07596766948699951,
0.07595217972993851,
0.39492619037628174,
-0.17496736347675323,
0.3543426394462... |
https://github.com/huggingface/datasets/issues/6202 | https://github.com/huggingface/datasets/blob/main/setup.py#L236
Currently has the highest version at 0.3.25; Not sure if there is any reason for this, other than that was the tested version? | avoid downgrading jax version | ### Feature request
Whenever I `pip install datasets[jax]` it downgrades jax to version 0.3.25. I seem to be able to install this library first then upgrade jax back to version 0.4.13.
### Motivation
It would be nice to not overwrite currently installed version of jax if possible.
### Your contribution
I... | 24 | avoid downgrading jax version
### Feature request
Whenever I `pip install datasets[jax]` it downgrades jax to version 0.3.25. I seem to be able to install this library first then upgrade jax back to version 0.4.13.
### Motivation
It would be nice to not overwrite currently installed version of jax if possibl... | [
0.03834281861782074,
-0.03251977264881134,
-0.018348224461078644,
-0.1174321174621582,
0.26987597346305847,
0.1588345170021057,
-0.025461025536060333,
0.6368866562843323,
0.027017757296562195,
0.12465295195579529,
0.15229052305221558,
0.279801607131958,
-0.06330268830060959,
0.471864461898... |
https://github.com/huggingface/datasets/issues/6199 | Hugging Face's datasets library may prioritize remote configurations. Make sure there are no conflicting configurations causing the library to prefer downloading data
May be try debugging
raw_datasets = load_dataset('json', data_files=data_files)
print(raw_datasets)
| Use load_dataset for local json files, but it not works | ### Describe the bug
when I use load_dataset to load my local datasets，it always goes to Hugging Face to download the data instead of loading the local dataset.
### Steps to reproduce the bug
`raw_datasets = load_dataset(
‘json’,
data_files=data_files)`
### Expected behavior
`
### Expected behavior
` fails with a `ValueError` since the latest `pandas` [release](https://pandas.pydata.org/docs/dev/whatsnew/v2.1.0.html) (`2.1.0`)
In their latest release we have:
> Improved error handling when using [DataFrame.to_json()](https://pandas.pydata.org/docs/dev/refere... | 20 | ValueError: 'index=True' is only valid when 'orient' is 'split', 'table', 'index', or 'columns'
### Describe the bug
Saving a dataset `.to_json()` fails with a `ValueError` since the latest `pandas` [release](https://pandas.pydata.org/docs/dev/whatsnew/v2.1.0.html) (`2.1.0`)
In their latest release we have:
> ... | [
0.0543651282787323,
0.21008306741714478,
-0.012207593768835068,
0.14300532639026642,
0.22878742218017578,
0.2148909717798233,
0.5008203983306885,
0.5437043905258179,
-0.07516998052597046,
0.08667115867137909,
-0.2040853500366211,
0.5609626770019531,
0.0017831027507781982,
-0.05196439474821... |
https://github.com/huggingface/datasets/issues/6195 | realized that need to pass the path at `cache_file_name` like
```python
tokenized_datasets = raw_datasets["train"].map(
tokenize_function,
batched=True,
num_proc=data_args.preprocessing_num_workers,
remove_columns=[text_column_name],
... | Force to reuse cache at given path | ### Describe the bug
I have run the official example of MLM like:
```bash
python run_mlm.py \
--model_name_or_path roberta-base \
--dataset_name togethercomputer/RedPajama-Data-1T \
--dataset_config_name arxiv \
--per_device_train_batch_size 10 \
--preprocessing_num_workers 20 ... | 32 | Force to reuse cache at given path
### Describe the bug
I have run the official example of MLM like:
```bash
python run_mlm.py \
--model_name_or_path roberta-base \
--dataset_name togethercomputer/RedPajama-Data-1T \
--dataset_config_name arxiv \
--per_device_train_batch_size 10 \
... | [
-0.0019599124789237976,
0.21225914359092712,
0.11871518194675446,
0.13832400739192963,
0.15499252080917358,
-0.021354787051677704,
0.43014252185821533,
0.15119801461696625,
0.028692856431007385,
-0.08496592938899994,
-0.05548159405589104,
0.5933548808097839,
-0.19288857281208038,
-0.147448... |
https://github.com/huggingface/datasets/issues/6195 | Thank you so much! I went through a lot of issues before finding similar experiences here. I have to say that the [docs](https://huggingface.co/docs/datasets/v2.11.0/en/package_reference/main_classes#datasets.Dataset.map) of `.map()` is really misleading, probably making people think that just assigning the file name t... | Force to reuse cache at given path | ### Describe the bug
I have run the official example of MLM like:
```bash
python run_mlm.py \
--model_name_or_path roberta-base \
--dataset_name togethercomputer/RedPajama-Data-1T \
--dataset_config_name arxiv \
--per_device_train_batch_size 10 \
--preprocessing_num_workers 20 ... | 42 | Force to reuse cache at given path
### Describe the bug
I have run the official example of MLM like:
```bash
python run_mlm.py \
--model_name_or_path roberta-base \
--dataset_name togethercomputer/RedPajama-Data-1T \
--dataset_config_name arxiv \
--per_device_train_batch_size 10 \
... | [
-0.0019599124789237976,
0.21225914359092712,
0.11871518194675446,
0.13832400739192963,
0.15499252080917358,
-0.021354787051677704,
0.43014252185821533,
0.15119801461696625,
0.028692856431007385,
-0.08496592938899994,
-0.05548159405589104,
0.5933548808097839,
-0.19288857281208038,
-0.147448... |
https://github.com/huggingface/datasets/issues/6194 | The `fingerprint` parameter serves a slightly different purpose - we use it to inject a new fingerprint after transforming a `Dataset` (computed from the previous fingerprint + transform + transform args), e.g., to be able to compute the cache file for a transform. There is no concept of `fingerprint` before a `Dataset... | Support custom fingerprinting with `Dataset.from_generator` | ### Feature request
When using `Dataset.from_generator`, the generator is hashed when building the fingerprint. Similar to `.map`, it would be interesting to let the user bypass this hashing by accepting a `fingerprint` argument to `.from_generator`.
### Motivation
Using the `.from_generator` constructor with ... | 119 | Support custom fingerprinting with `Dataset.from_generator`
### Feature request
When using `Dataset.from_generator`, the generator is hashed when building the fingerprint. Similar to `.map`, it would be interesting to let the user bypass this hashing by accepting a `fingerprint` argument to `.from_generator`.
#... | [
-0.37626779079437256,
0.12814950942993164,
0.07224499434232712,
0.08254784345626831,
0.030975818634033203,
0.048969365656375885,
0.46350806951522827,
0.19914063811302185,
0.04077352583408356,
0.3023551106452942,
0.10347207635641098,
0.359960675239563,
-0.3150944411754608,
0.393513113260269... |
https://github.com/huggingface/datasets/issues/6194 | Adding +1 here:
If the generator needs to access some external resources or state, then it's not always straightforward to make it pickle-able. So I'd like to be able to override how the default cache key derivation needs to pickle the generator (and of course, I'd accept responsibility for that part of cache consis... | Support custom fingerprinting with `Dataset.from_generator` | ### Feature request
When using `Dataset.from_generator`, the generator is hashed when building the fingerprint. Similar to `.map`, it would be interesting to let the user bypass this hashing by accepting a `fingerprint` argument to `.from_generator`.
### Motivation
Using the `.from_generator` constructor with ... | 65 | Support custom fingerprinting with `Dataset.from_generator`
### Feature request
When using `Dataset.from_generator`, the generator is hashed when building the fingerprint. Similar to `.map`, it would be interesting to let the user bypass this hashing by accepting a `fingerprint` argument to `.from_generator`.
#... | [
-0.20553195476531982,
0.264360249042511,
0.09052132070064545,
0.10795579850673676,
-0.10179486870765686,
-0.042616620659828186,
0.43080437183380127,
0.2865421175956726,
0.1000044122338295,
0.22101201117038727,
0.3442264795303345,
0.5742281675338745,
-0.228618785738945,
0.23749396204948425,... |
https://github.com/huggingface/datasets/issues/6194 | Silly hack incoming:
```python
import uuid
class _DatasetGeneratorPickleHack:
def __init__(self, generator, generator_id=None):
self.generator = generator
self.generator_id = (
generator_id if generator_id is not None else str(uuid.uuid4())
)
def __call__(self,... | Support custom fingerprinting with `Dataset.from_generator` | ### Feature request
When using `Dataset.from_generator`, the generator is hashed when building the fingerprint. Similar to `.map`, it would be interesting to let the user bypass this hashing by accepting a `fingerprint` argument to `.from_generator`.
### Motivation
Using the `.from_generator` constructor with ... | 82 | Support custom fingerprinting with `Dataset.from_generator`
### Feature request
When using `Dataset.from_generator`, the generator is hashed when building the fingerprint. Similar to `.map`, it would be interesting to let the user bypass this hashing by accepting a `fingerprint` argument to `.from_generator`.
#... | [
-0.36780858039855957,
0.21587952971458435,
0.03805328905582428,
0.02745182067155838,
0.016834227368235588,
-0.03290639817714691,
0.5063583850860596,
0.18545609712600708,
0.1344025433063507,
0.3427473306655884,
0.11656101047992706,
0.5043578147888184,
-0.3798723816871643,
0.278560996055603,... |
https://github.com/huggingface/datasets/issues/6194 | I'd like some way to do this too. I find that sometimes the hash doesn't cover enough, and that the dataset is not regenerated even when underlying data has changed, and by supplying a custom fingerprint I could do a better job of controlling when my dataset is regenerated. | Support custom fingerprinting with `Dataset.from_generator` | ### Feature request
When using `Dataset.from_generator`, the generator is hashed when building the fingerprint. Similar to `.map`, it would be interesting to let the user bypass this hashing by accepting a `fingerprint` argument to `.from_generator`.
### Motivation
Using the `.from_generator` constructor with ... | 49 | Support custom fingerprinting with `Dataset.from_generator`
### Feature request
When using `Dataset.from_generator`, the generator is hashed when building the fingerprint. Similar to `.map`, it would be interesting to let the user bypass this hashing by accepting a `fingerprint` argument to `.from_generator`.
#... | [
-0.30125513672828674,
0.2775108516216278,
0.06664708256721497,
0.02324117347598076,
-0.1204926073551178,
0.03203746676445007,
0.5140148997306824,
0.18703512847423553,
0.022674553096294403,
0.288601279258728,
0.3510569930076599,
0.367605984210968,
-0.3413662612438202,
0.3644355535507202,
... |
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