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https://github.com/huggingface/datasets/issues/4085 | datasets.set_progress_bar_enabled(False) not working in datasets v2 | Now, I can't find any reference to set_progress_bar_enabled in the code.
I think it have been deleted | ## Describe the bug
datasets.set_progress_bar_enabled(False) not working in datasets v2
## Steps to reproduce the bug
```python
datasets.set_progress_bar_enabled(False)
```
## Expected results
datasets not using any progress bar
## Actual results
AttributeError: module 'datasets' has no attribute 'se... | 17 | datasets.set_progress_bar_enabled(False) not working in datasets v2
## Describe the bug
datasets.set_progress_bar_enabled(False) not working in datasets v2
## Steps to reproduce the bug
```python
datasets.set_progress_bar_enabled(False)
```
## Expected results
datasets not using any progress bar
## Actu... |
https://github.com/huggingface/datasets/issues/4085 | datasets.set_progress_bar_enabled(False) not working in datasets v2 | Hi @virilo,
Please note that since `datasets` version 2.0.0, we have aligned with `transformers` the management of the progress bar (among other things):
- #3897
Now, you should update your code to use `datasets.logging.disable_progress_bar`.
You have more info in our docs: [Logging methods](https://huggingfa... | ## Describe the bug
datasets.set_progress_bar_enabled(False) not working in datasets v2
## Steps to reproduce the bug
```python
datasets.set_progress_bar_enabled(False)
```
## Expected results
datasets not using any progress bar
## Actual results
AttributeError: module 'datasets' has no attribute 'se... | 43 | datasets.set_progress_bar_enabled(False) not working in datasets v2
## Describe the bug
datasets.set_progress_bar_enabled(False) not working in datasets v2
## Steps to reproduce the bug
```python
datasets.set_progress_bar_enabled(False)
```
## Expected results
datasets not using any progress bar
## Actu... |
https://github.com/huggingface/datasets/issues/4085 | datasets.set_progress_bar_enabled(False) not working in datasets v2 | One important thing for beginner like me is: from datasets.utils.logging import disable_progress_bar
Do not forget the 'utils' or you will waste a long time like me.... | ## Describe the bug
datasets.set_progress_bar_enabled(False) not working in datasets v2
## Steps to reproduce the bug
```python
datasets.set_progress_bar_enabled(False)
```
## Expected results
datasets not using any progress bar
## Actual results
AttributeError: module 'datasets' has no attribute 'se... | 26 | datasets.set_progress_bar_enabled(False) not working in datasets v2
## Describe the bug
datasets.set_progress_bar_enabled(False) not working in datasets v2
## Steps to reproduce the bug
```python
datasets.set_progress_bar_enabled(False)
```
## Expected results
datasets not using any progress bar
## Actu... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | Hi! This behavior stems from these lines:
https://github.com/huggingface/datasets/blob/b065547654efa0ec633cf373ac1512884c68b2e1/src/datasets/formatting/np_formatter.py#L45-L46
I agree we should preserve the original type whenever possible and downcast explicitly with a warning.
@lhoestq Do you remember why we ... | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 38 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | I was also wondering why the default type logic is needed. Me just deleting it is probably too naive of a solution. | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 22 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | Hmm I think the idea was to end up with the usual default precision for deep learning models - no matter how the data was stored or where it comes from.
For example in NLP we store tokens using an optimized low precision to save disk space, but when we set the format to `torch` we actually need to get `int64`. Altho... | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 123 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | Unfortunately removing it for integers is a breaking change for most `transformers` + `datasets` users for NLP (which is a common case). Removing it for floats is a breaking change for `transformers` + `datasets` for ASR as well. And it also is a breaking change for the other users relying on this behavior.
Therefor... | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 102 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | @lhoestq It should be fine to remove this conversion in Datasets 3.0, no? For now, we can warn the user (with a log message) about the future change when the default type is changed. | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 34 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | Let's see with the transformers team if it sounds reasonable ? We'd have to fix multiple example scripts though.
If it's not ok we can also explore keeping this behavior only for tokens and audio data. | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 36 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | IMO being coupled with Transformers can lead to unexpected behavior when one tries to use our lib without pairing it with Transformers, so I think it's still important to "fix" this, even if it means we will need to update Transformers' example scripts afterward.
| ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 44 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | For others that run into the same issue: A temporary workaround for me is this:
```python
def numpy_transform(batch):
return {key: np.asarray(val) for key, val in batch.items()}
dataset = dataset.with_transform(numpy_transform)
``` | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 30 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | This behavior (silent upcast from `int32` to `int64`) is also unexpected for the user in https://discuss.huggingface.co/t/standard-getitem-returns-wrong-data-type-for-arrays/62470/2 | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 16 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | Hi, I stumbled on a variation that upcasts uint8 to int64. I would expect the dtype to be the same as it was when I generated the dataset.
```
import numpy as np
import datasets as ds
foo = np.random.randint(0, 256, size=(5, 10, 10), dtype=np.uint8)
features = ds.Features({"foo": ds.Array2D((10, 10), "uint8"... | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 72 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/5517 | `with_format("numpy")` silently downcasts float64 to float32 features | workaround to remove torch upcasting
```
import datasets as ds
import torch
class FixedTorchFormatter(ds.formatting.TorchFormatter):
def _tensorize(self, value):
return torch.from_numpy(value)
ds.formatting._register_formatter(FixedTorchFormatter, "torch")
``` | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print(... | 22 | `with_format("numpy")` silently downcasts float64 to float32 features
### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.... |
https://github.com/huggingface/datasets/issues/3688 | Pyarrow version error | Hi @Zaker237, thanks for reporting.
This is weird: the error you get is only thrown if the installed pyarrow version is less than 3.0.0.
Could you please check that you install pyarrow in the same Python virtual environment where you installed datasets?
From the Python command line (or terminal) where you get ... | ## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match this condition`.
i tryed w... | 64 | Pyarrow version error
## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match this ... |
https://github.com/huggingface/datasets/issues/3688 | Pyarrow version error | hi @albertvillanova i try yesterday to create a new python environement with python 7 and try it on the environement and it worked. so i think that the error was not the package but may be jupyter notebook on conda. still yet i'm not yet sure but it worked in an environment created with venv | ## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match this condition`.
i tryed w... | 55 | Pyarrow version error
## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match this ... |
https://github.com/huggingface/datasets/issues/3688 | Pyarrow version error | OK, thanks @Zaker237 for your feedback.
I close this issue then. Please, feel free to reopen it if the problem arises again. | ## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match this condition`.
i tryed w... | 22 | Pyarrow version error
## Describe the bug
I installed datasets(version 1.17.0, 1.18.0, 1.18.3) but i'm right now nor able to import it because of pyarrow. when i try to import it, i get the following error:
`To use datasets, the module pyarrow>=3.0.0 is required, and the current version of pyarrow doesn't match this ... |
https://github.com/huggingface/datasets/issues/3331 | AttributeError: 'CommunityDatasetModuleFactoryWithoutScript' object has no attribute 'path' | Hi,
the fix was merged and will be available in the next release of `datasets`.
In the meantime, you can use it by installing `datasets` directly from master as follows:
```
pip install git+https://github.com/huggingface/datasets.git
``` | ## Describe the bug
I add a new question answering dataset to huggingface datasets manually. Here is the link: [luozhouyang/question-answering-datasets](https://huggingface.co/datasets/luozhouyang/question-answering-datasets)
But when I load the dataset, an error raised:
```bash
AttributeError: 'CommunityDatas... | 35 | AttributeError: 'CommunityDatasetModuleFactoryWithoutScript' object has no attribute 'path'
## Describe the bug
I add a new question answering dataset to huggingface datasets manually. Here is the link: [luozhouyang/question-answering-datasets](https://huggingface.co/datasets/luozhouyang/question-answering-datasets)
... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Hi ! We're using process pools for parallelism right now. I was wondering if there's a package that implements the same API as a process pool but runs with Spark under the hood ? That or something similar would be cool because users could use whatever distributed framework they want this way.
Feel free to ping us wh... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 81 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Hi, thanks for taking a look and providing your input! I don't know of such packages, and even it exists, I don't think with the process pool API it's possible to run Spark as backend properly; otherwise I understand a unified API would be preferable.
The process pool API requires splitting the workload to a fixed n... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 132 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | I see ! I think we only need an equivalent of `pool.map`. We use it to run download and conversion of data files on disk. That would require less changes in the internal code - and therefore less tests to write ;)
We also use `pool.apply_async` in some places with a `Queue` to get progress updates of the running job... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 84 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | For Spark, `rdd.map` (where `rdd` can be created by `sparkContext.parallelize`) is the most similar as `pool.map`, but it requires creating a Spark RDD first that is used for distributing the `iterable` and the actual parallelization is managed by the Spark framework; `pool.map` takes the splits of `iterable` that are ... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 127 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Indeed I think the current use of multiprocessing.Pool in `map_nested` can be rewritten to work like `sparkContext.parallelize` - without splitting the iterable.
Maybe from the user's perspective it's ok to let multiprocessing.Pool or spark distribute the load on their own, as long as it takes a list and runs jobs i... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 56 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | From your feedback, seems to me there are two paths to consider now for supporting spark's `map` function in `map_nested` now:
1. Keep the current `pool.map` implementation, and add an if statement for the spark's `map` code (which is what I did in my current PR) -- the code change is just a few lines in the `map_nest... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 185 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Yup correct ! I think it's a nice path because it would be possible for users to define whatever parallel processing backend they want. I think we still need to discuss how that would look like in the `datasets` API : how to specify it has to use the "spark" parallel backend ? And how to specify the spark session param... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 94 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Sure, please let me know if you have more updates regarding the API and implementation from the team.
For parameters we don't need to worry about setting them for Spark, because Spark will figure out the environment / number of worker nodes by itself, so it's preferable to just provide some parameter such as `use_sp... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 61 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Hi! I wanted to check in to see if there is any update from the team.
A potential change of API I can think of is change the argument to `distributed_backend=...`, which accepts `str`, such as `load_dataset(..., distributed_backend="spark")`.
Implementation wise, we can add a class / function to abstract away the... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 66 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | I found this quite interesting: https://github.com/joblib/joblib-spark with this syntax:
```python
with parallel_backend('spark', n_jobs=3):
...
```
cc @lu-wang-dl who might know better | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 21 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Joblib spark is providing Spark backend for joblib. We can implement a general parallel backend like
```
with parallel_backend("<parallel-backedn>", n_jobs=..):
```
It can support multiprocessing , spark, ray, and etc. https://joblib.readthedocs.io/en/latest/parallel.html#joblib.parallel_backend | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 31 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Thank you @lhoestq for finding this repo. I validated that it can distribute downloading jobs with Spark to arbitrary cluster worker nodes evenly with `n_jobs=-1`.
For the API, I think it makes sense to define it as
```python
load_dataset(..., parallel_backend=<str>)
```
where `parallel_backend` can be `spark`, ... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 82 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Hello @lhoestq, I wanted to follow up on my previous comment with some prototyping code that demonstrates how `map_nested` would be like if we unify `multiprocessing` and `spark` with `joblib`. The snippet hasn't hashed out the details such as dealing with `tqdm` yet.
In terms of API, the way of using multiprocessin... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 291 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Nice ! It should be quite easy to make the change then :)
I think adding spark support can actually be less than 20 lines of code and would roughly require one line of code to change in map_nested:
Maybe we can define a new `datasets.parallel` submodule that has the `parallel_backend()` context manager and a `par... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 108 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Although until we've switched to all the steps in `load_dataset` to use `datasets.parallel`, I would require the user to explicitly say which step should use Spark. Maybe something like this, but I'm not sure yet:
```python
from datasets.parallel import parallel_backend
with parallel_backend("spark", steps=["dow... | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 106 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Sounds good! I like the partial rollout idea.
So for example `map_nested` would call `parallel_map` under the hood if `num_proc != 1` or `parallel_backend` is specified right?
I would be happy to start a PR next week to explore this path. | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 41 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/5798 | Support parallelized downloading and processing in load_dataset with Spark | Awesome ! I think map_nested can call `parallel_map()` if num_proc > 1, and `parallel_map` can be responsible to use Pool.map by default or joblib. | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up ... | 24 | Support parallelized downloading and processing in load_dataset with Spark
### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python... |
https://github.com/huggingface/datasets/issues/6350 | Different objects are returned from calls that should be returning the same kind of object. | `load_dataset` returns a `DatasetDict` object unless `split` is defined, in which case it returns a `Dataset` (or a list of datasets if `split` is a list). We've discussed dropping `DatasetDict` from the API in https://github.com/huggingface/datasets/issues/5189 to always return the same type in `load_dataset` and sup... | ### Describe the bug
1. dataset = load_dataset("togethercomputer/RedPajama-Data-1T-Sample", cache_dir=training_args.cache_dir, split='train[:1%]')
2. dataset = load_dataset("togethercomputer/RedPajama-Data-1T-Sample", cache_dir=training_args.cache_dir)
The only difference I would expect these cal... | 82 | Different objects are returned from calls that should be returning the same kind of object.
### Describe the bug
1. dataset = load_dataset("togethercomputer/RedPajama-Data-1T-Sample", cache_dir=training_args.cache_dir, split='train[:1%]')
2. dataset = load_dataset("togethercomputer/RedPajama-Data-1T... |
https://github.com/huggingface/datasets/issues/6350 | Different objects are returned from calls that should be returning the same kind of object. | > `load_dataset` returns a `DatasetDict` object unless `split` is defined, in which case it returns a `Dataset` (or a list of datasets if `split` is a list). We've discussed dropping `DatasetDict` from the API in #5189 to always return the same type in `load_dataset` and support datasets without (explicit) splits. IIRC... | ### Describe the bug
1. dataset = load_dataset("togethercomputer/RedPajama-Data-1T-Sample", cache_dir=training_args.cache_dir, split='train[:1%]')
2. dataset = load_dataset("togethercomputer/RedPajama-Data-1T-Sample", cache_dir=training_args.cache_dir)
The only difference I would expect these cal... | 153 | Different objects are returned from calls that should be returning the same kind of object.
### Describe the bug
1. dataset = load_dataset("togethercomputer/RedPajama-Data-1T-Sample", cache_dir=training_args.cache_dir, split='train[:1%]')
2. dataset = load_dataset("togethercomputer/RedPajama-Data-1T... |
https://github.com/huggingface/datasets/issues/5586 | .sort() is broken when used after .filter(), only in 2.10.0 | Thanks for reporting and thanks @mariosasko for fixing ! We just did a patch release `2.10.1` with the fix | ### Describe the bug
Hi, thank you for your support!
It seems like the addition of multiple key sort (#5502) in 2.10.0 broke the `.sort()` method.
After filtering a dataset with `.filter()`, the `.sort()` seems to refer to the query_table index of the previous unfiltered dataset, resulting in an IndexError.
... | 19 | .sort() is broken when used after .filter(), only in 2.10.0
### Describe the bug
Hi, thank you for your support!
It seems like the addition of multiple key sort (#5502) in 2.10.0 broke the `.sort()` method.
After filtering a dataset with `.filter()`, the `.sort()` seems to refer to the query_table index of the... |
https://github.com/huggingface/datasets/issues/7517 | Image Feature in Datasets Library Fails to Handle bytearray Objects from Spark DataFrames | Hi ! The `Image()` type accepts either
- a `bytes` object containing the image bytes
- a `str` object containing the image path
- a `PIL.Image` object
but it doesn't support `bytearray`, maybe you can convert to `bytes` beforehand ? | ### Describe the bug
When using `IterableDataset.from_spark()` with a Spark DataFrame containing image data, the `Image` feature class fails to properly process this data type, causing an `AttributeError: 'bytearray' object has no attribute 'get'`
### Steps to reproduce the bug
1. Create a Spark DataFrame with a col... | 40 | Image Feature in Datasets Library Fails to Handle bytearray Objects from Spark DataFrames
### Describe the bug
When using `IterableDataset.from_spark()` with a Spark DataFrame containing image data, the `Image` feature class fails to properly process this data type, causing an `AttributeError: 'bytearray' object has n... |
https://github.com/huggingface/datasets/issues/7517 | Image Feature in Datasets Library Fails to Handle bytearray Objects from Spark DataFrames | Hi @lhoestq,
converting to bytes is certainly possible and would work around the error. However, the core issue is that `Dataset` and `IterableDataset` behave differently with the features.
I’d be happy to work on a fix for this issue. | ### Describe the bug
When using `IterableDataset.from_spark()` with a Spark DataFrame containing image data, the `Image` feature class fails to properly process this data type, causing an `AttributeError: 'bytearray' object has no attribute 'get'`
### Steps to reproduce the bug
1. Create a Spark DataFrame with a col... | 39 | Image Feature in Datasets Library Fails to Handle bytearray Objects from Spark DataFrames
### Describe the bug
When using `IterableDataset.from_spark()` with a Spark DataFrame containing image data, the `Image` feature class fails to properly process this data type, causing an `AttributeError: 'bytearray' object has n... |
https://github.com/huggingface/datasets/issues/7517 | Image Feature in Datasets Library Fails to Handle bytearray Objects from Spark DataFrames | I see, that's an issue indeed. Feel free to ping me if I can help with reviews or any guidance
If it can help, the code that takes a Spark DataFrame and iterates on the rows for `IterableDataset` is here:
https://github.com/huggingface/datasets/blob/6a96bf313085d7538a999b929a550e14e1d406c9/src/datasets/packaged_modu... | ### Describe the bug
When using `IterableDataset.from_spark()` with a Spark DataFrame containing image data, the `Image` feature class fails to properly process this data type, causing an `AttributeError: 'bytearray' object has no attribute 'get'`
### Steps to reproduce the bug
1. Create a Spark DataFrame with a col... | 41 | Image Feature in Datasets Library Fails to Handle bytearray Objects from Spark DataFrames
### Describe the bug
When using `IterableDataset.from_spark()` with a Spark DataFrame containing image data, the `Image` feature class fails to properly process this data type, causing an `AttributeError: 'bytearray' object has n... |
https://github.com/huggingface/datasets/issues/4115 | ImageFolder add option to ignore some folders like '.ipynb_checkpoints' | Maybe it would be nice to ignore private dirs like this one (ones starting with `.`) by default.
CC @mariosasko | **Is your feature request related to a problem? Please describe.**
I sometimes like to peek at the dataset images from jupyterlab. thus '.ipynb_checkpoints' folder appears where my dataset is and (just realized) leads to accidental duplicate image additions. I think this is an easy enough thing to miss especially if t... | 20 | ImageFolder add option to ignore some folders like '.ipynb_checkpoints'
**Is your feature request related to a problem? Please describe.**
I sometimes like to peek at the dataset images from jupyterlab. thus '.ipynb_checkpoints' folder appears where my dataset is and (just realized) leads to accidental duplicate image... |
https://github.com/huggingface/datasets/issues/4115 | ImageFolder add option to ignore some folders like '.ipynb_checkpoints' | Maybe we can add a `ignore_hidden_files` flag to the builder configs of our packaged loaders (to be consistent across all of them), wdyt @lhoestq @albertvillanova? | **Is your feature request related to a problem? Please describe.**
I sometimes like to peek at the dataset images from jupyterlab. thus '.ipynb_checkpoints' folder appears where my dataset is and (just realized) leads to accidental duplicate image additions. I think this is an easy enough thing to miss especially if t... | 25 | ImageFolder add option to ignore some folders like '.ipynb_checkpoints'
**Is your feature request related to a problem? Please describe.**
I sometimes like to peek at the dataset images from jupyterlab. thus '.ipynb_checkpoints' folder appears where my dataset is and (just realized) leads to accidental duplicate image... |
https://github.com/huggingface/datasets/issues/4115 | ImageFolder add option to ignore some folders like '.ipynb_checkpoints' | I think they should always ignore them actually ! Not sure if adding a flag would be helpful | **Is your feature request related to a problem? Please describe.**
I sometimes like to peek at the dataset images from jupyterlab. thus '.ipynb_checkpoints' folder appears where my dataset is and (just realized) leads to accidental duplicate image additions. I think this is an easy enough thing to miss especially if t... | 18 | ImageFolder add option to ignore some folders like '.ipynb_checkpoints'
**Is your feature request related to a problem? Please describe.**
I sometimes like to peek at the dataset images from jupyterlab. thus '.ipynb_checkpoints' folder appears where my dataset is and (just realized) leads to accidental duplicate image... |
https://github.com/huggingface/datasets/issues/4115 | ImageFolder add option to ignore some folders like '.ipynb_checkpoints' | @lhoestq But what if the user explicitly requests those files via regex?
`glob.glob` ignores hidden files (files starting with ".") by default unless they are explicitly requested, but fsspec's `glob` doesn't follow this behavior, which is probably a bug, so maybe we can raise an issue or open a PR in their repo? | **Is your feature request related to a problem? Please describe.**
I sometimes like to peek at the dataset images from jupyterlab. thus '.ipynb_checkpoints' folder appears where my dataset is and (just realized) leads to accidental duplicate image additions. I think this is an easy enough thing to miss especially if t... | 53 | ImageFolder add option to ignore some folders like '.ipynb_checkpoints'
**Is your feature request related to a problem? Please describe.**
I sometimes like to peek at the dataset images from jupyterlab. thus '.ipynb_checkpoints' folder appears where my dataset is and (just realized) leads to accidental duplicate image... |
https://github.com/huggingface/datasets/issues/4115 | ImageFolder add option to ignore some folders like '.ipynb_checkpoints' | > @lhoestq But what if the user explicitly requests those files via regex?
Usually hidden files are meant to be ignored. If they are data files, they must be placed outside a hidden directory in the first place right ? I think it's more sensible to explain this than adding a flag.
> glob.glob ignores hidden files... | **Is your feature request related to a problem? Please describe.**
I sometimes like to peek at the dataset images from jupyterlab. thus '.ipynb_checkpoints' folder appears where my dataset is and (just realized) leads to accidental duplicate image additions. I think this is an easy enough thing to miss especially if t... | 145 | ImageFolder add option to ignore some folders like '.ipynb_checkpoints'
**Is your feature request related to a problem? Please describe.**
I sometimes like to peek at the dataset images from jupyterlab. thus '.ipynb_checkpoints' folder appears where my dataset is and (just realized) leads to accidental duplicate image... |
https://github.com/huggingface/datasets/issues/5543 | the pile datasets url seems to change back | Thanks for reporting, @wjfwzzc.
I am transferring this issue to the corresponding dataset on the Hub: https://huggingface.co/datasets/bookcorpusopen/discussions/1 | ### Describe the bug
in #3627, the host url of the pile dataset became `https://mystic.the-eye.eu`. Now the new url is broken, but `https://the-eye.eu` seems to work again.
### Steps to reproduce the bug
```python3
from datasets import load_dataset
dataset = load_dataset("bookcorpusopen")
```
shows
```python3
... | 17 | the pile datasets url seems to change back
### Describe the bug
in #3627, the host url of the pile dataset became `https://mystic.the-eye.eu`. Now the new url is broken, but `https://the-eye.eu` seems to work again.
### Steps to reproduce the bug
```python3
from datasets import load_dataset
dataset = load_dataset(... |
https://github.com/huggingface/datasets/issues/5543 | the pile datasets url seems to change back | Thank you. All fixes are done:
- [x] https://huggingface.co/datasets/bookcorpusopen/discussions/2
- [x] https://huggingface.co/datasets/the_pile/discussions/1
- [x] https://huggingface.co/datasets/the_pile_books3/discussions/1
- [x] https://huggingface.co/datasets/the_pile_openwebtext2/discussions/2
- [x] https://... | ### Describe the bug
in #3627, the host url of the pile dataset became `https://mystic.the-eye.eu`. Now the new url is broken, but `https://the-eye.eu` seems to work again.
### Steps to reproduce the bug
```python3
from datasets import load_dataset
dataset = load_dataset("bookcorpusopen")
```
shows
```python3
... | 21 | the pile datasets url seems to change back
### Describe the bug
in #3627, the host url of the pile dataset became `https://mystic.the-eye.eu`. Now the new url is broken, but `https://the-eye.eu` seems to work again.
### Steps to reproduce the bug
```python3
from datasets import load_dataset
dataset = load_dataset(... |
https://github.com/huggingface/datasets/issues/4981 | Can't create a dataset with `float16` features | Hi @dconathan, thanks for reporting.
We rely on Arrow as a backend, and as far as I know currently support for `float16` in Arrow is not fully implemented in Python (C++), hence the `ArrowNotImplementedError` you get.
See, e.g.: https://arrow.apache.org/docs/status.html?highlight=float16#data-types | ## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried older versions of `pyarrow` as well with the same e... | 39 | Can't create a dataset with `float16` features
## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried olde... |
https://github.com/huggingface/datasets/issues/4981 | Can't create a dataset with `float16` features | Thanks for the link…. didn’t realize arrow didn’t support it yet. Should it be removed from https://huggingface.co/docs/datasets/v2.4.0/en/package_reference/main_classes#datasets.Value until Arrow supports it? | ## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried older versions of `pyarrow` as well with the same e... | 21 | Can't create a dataset with `float16` features
## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried olde... |
https://github.com/huggingface/datasets/issues/4981 | Can't create a dataset with `float16` features | Yes, you are right: maybe we should either remove it from our docs or add a comment explaining the issue.
The thing is that in Arrow it is partially supported: you can create `float16` values, but you can't cast them from/to other types. And current implementation of `Value` always tries to perform a cast from `floa... | ## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried older versions of `pyarrow` as well with the same e... | 58 | Can't create a dataset with `float16` features
## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried olde... |
https://github.com/huggingface/datasets/issues/4981 | Can't create a dataset with `float16` features | Would you accept a PR to fix this? @lhoestq Do you have an idea of how hard it would be to fix? | ## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried older versions of `pyarrow` as well with the same e... | 22 | Can't create a dataset with `float16` features
## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried olde... |
https://github.com/huggingface/datasets/issues/4981 | Can't create a dataset with `float16` features | I think the issue comes mostly from pyarrow not supporting `float16` completely.
For example you stil can't cast from/to `float16`
```python
import numpy as np
import pyarrow as pa
pa.array(range(5)).cast(pa.float16())
# ArrowNotImplementedError: Unsupported cast from int64 to halffloat using function cast_ha... | ## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried older versions of `pyarrow` as well with the same e... | 75 | Can't create a dataset with `float16` features
## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried olde... |
https://github.com/huggingface/datasets/issues/4981 | Can't create a dataset with `float16` features | Hmm it seems like we can either:
1. try to fix pyarrow upstream
2. half-support float16 with some workaround to make sure we don't ever do casting internally
| ## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried older versions of `pyarrow` as well with the same e... | 28 | Can't create a dataset with `float16` features
## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried olde... |
https://github.com/huggingface/datasets/issues/4981 | Can't create a dataset with `float16` features | This seems to be fixed now. Not sure if all operations are supported, but at least creating the dataset is supported. | ## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried older versions of `pyarrow` as well with the same e... | 21 | Can't create a dataset with `float16` features
## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried olde... |
https://github.com/huggingface/datasets/issues/4977 | Providing dataset size | Hi @sashavor, thanks for your suggestion.
Until now we have the CLI command
```
datasets-cli test datasets/<your-dataset-folder> --save_infos --all_configs
```
that generates the `dataset_infos.json` with the size of the downloaded dataset, among other information.
We are currently in the middle of removing ... | **Is your feature request related to a problem? Please describe.**
Especially for big datasets like [LAION](https://huggingface.co/datasets/laion/laion2B-en/), it's hard to know exactly the downloaded size (because there are many files and you don't have their exact size when downloaded).
**Describe the solution yo... | 78 | Providing dataset size
**Is your feature request related to a problem? Please describe.**
Especially for big datasets like [LAION](https://huggingface.co/datasets/laion/laion2B-en/), it's hard to know exactly the downloaded size (because there are many files and you don't have their exact size when downloaded).
**D... |
https://github.com/huggingface/datasets/issues/4977 | Providing dataset size | Additionally, the download size can be inferred by doing HEAD requests to the files to be downloaded. And for files hosted on the hub you can even get the file sizes using the Hub API | **Is your feature request related to a problem? Please describe.**
Especially for big datasets like [LAION](https://huggingface.co/datasets/laion/laion2B-en/), it's hard to know exactly the downloaded size (because there are many files and you don't have their exact size when downloaded).
**Describe the solution yo... | 35 | Providing dataset size
**Is your feature request related to a problem? Please describe.**
Especially for big datasets like [LAION](https://huggingface.co/datasets/laion/laion2B-en/), it's hard to know exactly the downloaded size (because there are many files and you don't have their exact size when downloaded).
**D... |
https://github.com/huggingface/datasets/issues/4977 | Providing dataset size | Amazing @albertvillanova ! I think just having that information visible in the dataset info (without having to do any requests/additional coding) would be really useful :hugs: | **Is your feature request related to a problem? Please describe.**
Especially for big datasets like [LAION](https://huggingface.co/datasets/laion/laion2B-en/), it's hard to know exactly the downloaded size (because there are many files and you don't have their exact size when downloaded).
**Describe the solution yo... | 26 | Providing dataset size
**Is your feature request related to a problem? Please describe.**
Especially for big datasets like [LAION](https://huggingface.co/datasets/laion/laion2B-en/), it's hard to know exactly the downloaded size (because there are many files and you don't have their exact size when downloaded).
**D... |
https://github.com/huggingface/datasets/issues/5675 | Filter datasets by language code | The dataset still can be found, if instead of using the search form you just enter the language code in the url, like https://huggingface.co/datasets?language=language:myv.
But of course having a more complete list of languages in the search form (or just a fallback to the language codes, if they are missing from t... | Hi! I use the language search field on https://huggingface.co/datasets
However, some of the datasets tagged by ISO language code are not accessible by this search form.
For example, [myv_ru_2022](https://huggingface.co/datasets/slone/myv_ru_2022) is has `myv` language tag but it is not included in Languages search fo... | 59 | Filter datasets by language code
Hi! I use the language search field on https://huggingface.co/datasets
However, some of the datasets tagged by ISO language code are not accessible by this search form.
For example, [myv_ru_2022](https://huggingface.co/datasets/slone/myv_ru_2022) is has `myv` language tag but it is no... |
https://github.com/huggingface/datasets/issues/5675 | Filter datasets by language code | Thanks @mariosasko!
Do you think it is possible to turn this into a more scalable pipeline? Such as:
1. Looping through all the datasets on the hub and collecting the set of all their language codes;
2. Selecting the codes not covered yet in `Language.ts`
3. Looking up their codes at https://iso639-3.sil.org/code_t... | Hi! I use the language search field on https://huggingface.co/datasets
However, some of the datasets tagged by ISO language code are not accessible by this search form.
For example, [myv_ru_2022](https://huggingface.co/datasets/slone/myv_ru_2022) is has `myv` language tag but it is not included in Languages search fo... | 62 | Filter datasets by language code
Hi! I use the language search field on https://huggingface.co/datasets
However, some of the datasets tagged by ISO language code are not accessible by this search form.
For example, [myv_ru_2022](https://huggingface.co/datasets/slone/myv_ru_2022) is has `myv` language tag but it is no... |
https://github.com/huggingface/datasets/issues/5675 | Filter datasets by language code | @avidale This has been discussed in https://github.com/huggingface/datasets/issues/4881, so also feel free to share your opinion there. | Hi! I use the language search field on https://huggingface.co/datasets
However, some of the datasets tagged by ISO language code are not accessible by this search form.
For example, [myv_ru_2022](https://huggingface.co/datasets/slone/myv_ru_2022) is has `myv` language tag but it is not included in Languages search fo... | 16 | Filter datasets by language code
Hi! I use the language search field on https://huggingface.co/datasets
However, some of the datasets tagged by ISO language code are not accessible by this search form.
For example, [myv_ru_2022](https://huggingface.co/datasets/slone/myv_ru_2022) is has `myv` language tag but it is no... |
https://github.com/huggingface/datasets/issues/3831 | when using to_tf_dataset with shuffle is true, not all completed batches are made | Hi @greenned, this is expected behaviour for `to_tf_dataset`. By default, we drop the smaller 'remainder' batch during training (i.e. when `shuffle=True`). If you really want to keep that batch, you can set `drop_remainder=False` when calling `to_tf_dataset()`. | ## Describe the bug
when converting a dataset to tf_dataset by using to_tf_dataset with shuffle true, the remainder is not converted to one batch
## Steps to reproduce the bug
this is the sample code below
https://colab.research.google.com/drive/1_oRXWsR38ElO1EYF9ayFoCU7Ou1AAej4?usp=sharing
## Expected resul... | 36 | when using to_tf_dataset with shuffle is true, not all completed batches are made
## Describe the bug
when converting a dataset to tf_dataset by using to_tf_dataset with shuffle true, the remainder is not converted to one batch
## Steps to reproduce the bug
this is the sample code below
https://colab.research.goo... |
https://github.com/huggingface/datasets/issues/4742 | Dummy data nowhere to be found | Hi @BramVanroy, thanks for reporting.
First of all, please note that you do not need the dummy data: this was the case when we were adding datasets to the `datasets` library (on this GitHub repo), so that we could test the correct loading of all datasets with our CI. However, this is no longer the case for datasets ... | ## Describe the bug
To finalize my dataset, I wanted to create dummy data as per the guide and I ran
```shell
datasets-cli dummy_data datasets/hebban-reviews --auto_generate
```
where hebban-reviews is [this repo](https://huggingface.co/datasets/BramVanroy/hebban-reviews). And even though the scripts runs an... | 139 | Dummy data nowhere to be found
## Describe the bug
To finalize my dataset, I wanted to create dummy data as per the guide and I ran
```shell
datasets-cli dummy_data datasets/hebban-reviews --auto_generate
```
where hebban-reviews is [this repo](https://huggingface.co/datasets/BramVanroy/hebban-reviews). And ... |
https://github.com/huggingface/datasets/issues/3730 | Checksum Error when loading multi-news dataset | Thanks for reporting @byw2.
We are fixing it.
In the meantime, you can load the dataset by passing `ignore_verifications=True`:
```python
dataset = load_dataset("multi_news", ignore_verifications=True) | ## Describe the bug
When using the load_dataset function from datasets module to load the Multi-News dataset, does not load the dataset but throws Checksum Error instead.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("multi_news")
```
## Expected results
... | 24 | Checksum Error when loading multi-news dataset
## Describe the bug
When using the load_dataset function from datasets module to load the Multi-News dataset, does not load the dataset but throws Checksum Error instead.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_datase... |
https://github.com/huggingface/datasets/issues/3788 | Only-data dataset loaded unexpectedly as validation split | I see two options:
1. drop the "dev" keyword since it can be considered too generic
2. improve the pattern to something more reasonable, e.g. asking for a separator before and after "dev"
```python
["*[ ._-]dev[ ._-]*", "dev[ ._-]*"]
```
I think 2. is nice. If we agree on this one we can even decide to require ... | ## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`. | 67 | Only-data dataset loaded unexpectedly as validation split
## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`.
... |
https://github.com/huggingface/datasets/issues/3788 | Only-data dataset loaded unexpectedly as validation split | Yes, I had something like that on mind: "dev" not being part of a word.
```
"[^a-zA-Z]dev[^a-zA-Z]" | ## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`. | 17 | Only-data dataset loaded unexpectedly as validation split
## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`.
... |
https://github.com/huggingface/datasets/issues/3788 | Only-data dataset loaded unexpectedly as validation split | Is there a reason why we want that regex? It feels like something that'll still be an issue for some weird case. "my_dataset_dev" doesn't match your regex, "my_dataset_validation" doesn't either ... Why not always "train" unless specified? | ## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`. | 37 | Only-data dataset loaded unexpectedly as validation split
## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`.
... |
https://github.com/huggingface/datasets/issues/3788 | Only-data dataset loaded unexpectedly as validation split | The regex is needed as part of our effort to make datasets configurable without code. In particular we define some generic dataset repository structures that users can follow
> ```
> "[^a-zA-Z]*dev[^a-zA-Z]*"
> ```
unfortunately our glob doesn't support "^":
https://github.com/fsspec/filesystem_spec/blob/3e... | ## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`. | 41 | Only-data dataset loaded unexpectedly as validation split
## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`.
... |
https://github.com/huggingface/datasets/issues/3788 | Only-data dataset loaded unexpectedly as validation split | > "my_dataset_dev" doesn't match your regex, "my_dataset_validation" doesn't either ... Why not always "train" unless specified?
And `my_dataset_dev.foo` would match the pattern, and we also have the same pattern but for the "validation" keyword so `my_dataset_validation.foo` would work too | ## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`. | 39 | Only-data dataset loaded unexpectedly as validation split
## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`.
... |
https://github.com/huggingface/datasets/issues/3788 | Only-data dataset loaded unexpectedly as validation split | > The regex is needed as part of our effort to make datasets configurable without code
This feels like coding with the filename ^^' | ## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`. | 24 | Only-data dataset loaded unexpectedly as validation split
## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`.
... |
https://github.com/huggingface/datasets/issues/3788 | Only-data dataset loaded unexpectedly as validation split | This is still much easier than having to write a full dataset script right ? :p | ## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`. | 16 | Only-data dataset loaded unexpectedly as validation split
## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`.
... |
https://github.com/huggingface/datasets/issues/4988 | Add `IterableDataset.from_generator` to the API | Thanks @hamid-vakilzadeh ! Let us know if you have some questions or if we can help | We've just added `Dataset.from_generator` to the API. It would also be cool to add `IterableDataset.from_generator` to support creating an iterable dataset from a generator.
cc @lhoestq | 16 | Add `IterableDataset.from_generator` to the API
We've just added `Dataset.from_generator` to the API. It would also be cool to add `IterableDataset.from_generator` to support creating an iterable dataset from a generator.
cc @lhoestq
Thanks @hamid-vakilzadeh ! Let us know if you have some questions or if we can hel... |
https://github.com/huggingface/datasets/issues/7079 | HfHubHTTPError: 500 Server Error: Internal Server Error for url: | Also impacted by this issue in many of my datasets (though not all) - in my case, this also seems to affect datasets that have been updated recently. Git cloning and the web interface still work:
- https://huggingface.co/api/datasets/acmc/cheat_reduced
- https://huggingface.co/api/datasets/acmc/ghostbuster_reuter_red... | ### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussion about it here, but I'm not sure anyone from huggingface have s... | 52 | HfHubHTTPError: 500 Server Error: Internal Server Error for url:
### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussi... |
https://github.com/huggingface/datasets/issues/7079 | HfHubHTTPError: 500 Server Error: Internal Server Error for url: | Same here. I cannot download the HelpSteer2 dataset: https://huggingface.co/datasets/nvidia/HelpSteer2 which has been uploaded about a month ago | ### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussion about it here, but I'm not sure anyone from huggingface have s... | 17 | HfHubHTTPError: 500 Server Error: Internal Server Error for url:
### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussi... |
https://github.com/huggingface/datasets/issues/7079 | HfHubHTTPError: 500 Server Error: Internal Server Error for url: | > Hey how to download these datasets using git cloning?
You'll find a guide [here](https://huggingface.co/docs/hub/en/datasets-downloading) 👍🏻 | ### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussion about it here, but I'm not sure anyone from huggingface have s... | 16 | HfHubHTTPError: 500 Server Error: Internal Server Error for url:
### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussi... |
https://github.com/huggingface/datasets/issues/7079 | HfHubHTTPError: 500 Server Error: Internal Server Error for url: | same here for all datsets in the sentence-tramsformers repo and related collections.
same issue with dataset that i recently uploaded on my repo.
seems that the upload date of the datset is not relevat (getting this issue with both old datasets and newer ones)
for some reason, i was able to get the dataset by tu... | ### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussion about it here, but I'm not sure anyone from huggingface have s... | 413 | HfHubHTTPError: 500 Server Error: Internal Server Error for url:
### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussi... |
https://github.com/huggingface/datasets/issues/7079 | HfHubHTTPError: 500 Server Error: Internal Server Error for url: | Hi I'm getting the same error with this [dataset](https://huggingface.co/datasets/huggan/smithsonian_butterflies_subset)
Working on the course of stable diffusion , trying to run this [notebook](https://colab.research.google.com/github/huggingface/diffusion-models-class/blob/main/unit1/01_introduction_to_diffusers.ip... | ### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussion about it here, but I'm not sure anyone from huggingface have s... | 52 | HfHubHTTPError: 500 Server Error: Internal Server Error for url:
### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussi... |
https://github.com/huggingface/datasets/issues/4782 | pyarrow.lib.ArrowCapacityError: array cannot contain more than 2147483646 bytes, have 2147483648 | Thanks for reporting @conceptofmind.
Could you please give details about your environment?
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- Platform:
- Python version:
- PyArrow version:
``` | ## Describe the bug
Following the example in CodeParrot, I receive an array size limitation error when deduplicating larger datasets.
## Steps to reproduce the bug
```python
dataset_name = "the_pile"
ds = load_dataset(dataset_name, split="train")
ds = ds.map(preprocess, num_proc=num_workers)
uniques = set(ds.u... | 42 | pyarrow.lib.ArrowCapacityError: array cannot contain more than 2147483646 bytes, have 2147483648
## Describe the bug
Following the example in CodeParrot, I receive an array size limitation error when deduplicating larger datasets.
## Steps to reproduce the bug
```python
dataset_name = "the_pile"
ds = load_datase... |
https://github.com/huggingface/datasets/issues/4782 | pyarrow.lib.ArrowCapacityError: array cannot contain more than 2147483646 bytes, have 2147483648 | Hi @albertvillanova ,
Here is the environment information:
```
- `datasets` version: 2.3.2
- Platform: Linux-5.4.0-122-generic-x86_64-with-glibc2.27
- Python version: 3.9.12
- PyArrow version: 7.0.0
- Pandas version: 1.4.2
```
Thanks,
Enrico | ## Describe the bug
Following the example in CodeParrot, I receive an array size limitation error when deduplicating larger datasets.
## Steps to reproduce the bug
```python
dataset_name = "the_pile"
ds = load_dataset(dataset_name, split="train")
ds = ds.map(preprocess, num_proc=num_workers)
uniques = set(ds.u... | 31 | pyarrow.lib.ArrowCapacityError: array cannot contain more than 2147483646 bytes, have 2147483648
## Describe the bug
Following the example in CodeParrot, I receive an array size limitation error when deduplicating larger datasets.
## Steps to reproduce the bug
```python
dataset_name = "the_pile"
ds = load_datase... |
https://github.com/huggingface/datasets/issues/4782 | pyarrow.lib.ArrowCapacityError: array cannot contain more than 2147483646 bytes, have 2147483648 | I think this issue is solved here https://discuss.huggingface.co/t/minhash-deduplication/19992/12?u=loubnabnl, this only happens for very large datasets we will update it in CodeParrot code | ## Describe the bug
Following the example in CodeParrot, I receive an array size limitation error when deduplicating larger datasets.
## Steps to reproduce the bug
```python
dataset_name = "the_pile"
ds = load_dataset(dataset_name, split="train")
ds = ds.map(preprocess, num_proc=num_workers)
uniques = set(ds.u... | 22 | pyarrow.lib.ArrowCapacityError: array cannot contain more than 2147483646 bytes, have 2147483648
## Describe the bug
Following the example in CodeParrot, I receive an array size limitation error when deduplicating larger datasets.
## Steps to reproduce the bug
```python
dataset_name = "the_pile"
ds = load_datase... |
https://github.com/huggingface/datasets/issues/4782 | pyarrow.lib.ArrowCapacityError: array cannot contain more than 2147483646 bytes, have 2147483648 | Hi @loubnabnl,
Yes, the issue is solved in the discussion thread.
I will close this issue.
Thank you again for all of your help.
Enrico | ## Describe the bug
Following the example in CodeParrot, I receive an array size limitation error when deduplicating larger datasets.
## Steps to reproduce the bug
```python
dataset_name = "the_pile"
ds = load_dataset(dataset_name, split="train")
ds = ds.map(preprocess, num_proc=num_workers)
uniques = set(ds.u... | 25 | pyarrow.lib.ArrowCapacityError: array cannot contain more than 2147483646 bytes, have 2147483648
## Describe the bug
Following the example in CodeParrot, I receive an array size limitation error when deduplicating larger datasets.
## Steps to reproduce the bug
```python
dataset_name = "the_pile"
ds = load_datase... |
https://github.com/huggingface/datasets/issues/7443 | index error when num_shards > len(dataset) | Actually, looking at the code a bit more carefully, maybe an even better solution is to explicitly set `num_shards=len(self)` somewhere inside both `push_to_hub()` and `save_to_disk()` when these functions are invoked with `num_shards > len(dataset)`. | In `ds.push_to_hub()` and `ds.save_to_disk()`, `num_shards` must be smaller than or equal to the number of rows in the dataset, but currently this is not checked anywhere inside these functions. Attempting to invoke these functions with `num_shards > len(dataset)` should raise an informative `ValueError`.
I frequently... | 34 | index error when num_shards > len(dataset)
In `ds.push_to_hub()` and `ds.save_to_disk()`, `num_shards` must be smaller than or equal to the number of rows in the dataset, but currently this is not checked anywhere inside these functions. Attempting to invoke these functions with `num_shards > len(dataset)` should raise... |
https://github.com/huggingface/datasets/issues/5778 | Schrödinger's dataset_dict | Hi ! Passing `data_files="path/test.json"` is equivalent to `data_files={"train": ["path/test.json"]}`, that's why you end up with a train split. If you don't pass `data_files=`, then split names are inferred from the data files names | ### Describe the bug
If you use load_dataset('json', data_files="path/test.json"), it will return DatasetDict({train:...}).
And if you use load_dataset("path"), it will return DatasetDict({test:...}).
Why can't the output behavior be unified?
### Steps to reproduce the bug
as description above.
### Expected b... | 33 | Schrödinger's dataset_dict
### Describe the bug
If you use load_dataset('json', data_files="path/test.json"), it will return DatasetDict({train:...}).
And if you use load_dataset("path"), it will return DatasetDict({test:...}).
Why can't the output behavior be unified?
### Steps to reproduce the bug
as descrip... |
https://github.com/huggingface/datasets/issues/4911 | [Tests] Ensure `datasets` supports renamed repositories | You could also switch to using `huggingface_hub` more directly, where such a guarantee is already tested =)
cc @Wauplin | On https://hf.co/datasets you can rename a dataset (or sometimes move it to another user/org). The website handles redirections correctly and AFAIK `datasets` does as well.
However it would be nice to have an integration test to make sure we don't break support for renamed datasets.
To implement this we can use t... | 19 | [Tests] Ensure `datasets` supports renamed repositories
On https://hf.co/datasets you can rename a dataset (or sometimes move it to another user/org). The website handles redirections correctly and AFAIK `datasets` does as well.
However it would be nice to have an integration test to make sure we don't break support... |
https://github.com/huggingface/datasets/issues/4911 | [Tests] Ensure `datasets` supports renamed repositories | Hi! @lhoestq, I'd love to work on this issue as part of my ongoing contributions to `datasets`.
I'm planning to implement an integration test that ensures `load_dataset()` works even after a dataset repo is renamed or moved. I can work locally and interact with the `/api/repos/move` endpoint, using either `huggingface... | On https://hf.co/datasets you can rename a dataset (or sometimes move it to another user/org). The website handles redirections correctly and AFAIK `datasets` does as well.
However it would be nice to have an integration test to make sure we don't break support for renamed datasets.
To implement this we can use t... | 126 | [Tests] Ensure `datasets` supports renamed repositories
On https://hf.co/datasets you can rename a dataset (or sometimes move it to another user/org). The website handles redirections correctly and AFAIK `datasets` does as well.
However it would be nice to have an integration test to make sure we don't break support... |
https://github.com/huggingface/datasets/issues/7757 | Add support for `.conll` file format in datasets | That would be cool ! feel free to ping me if I can help reviewing a PR | ### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification problems.
Right now `.conll` datasets need to be manu... | 17 | Add support for `.conll` file format in datasets
### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification probl... |
https://github.com/huggingface/datasets/issues/7757 | Add support for `.conll` file format in datasets | hey @namesarnav , are you still planning to PR this? happy to coordinate or take it on otherwise. looks like a clean
packaged_modules/conll/ builder following the csv/json/text pattern.
@lhoestq , thanks for the pre-review offer. if @namesarnav has moved on, i can pick this up and ping you for review. | ### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification problems.
Right now `.conll` datasets need to be manu... | 50 | Add support for `.conll` file format in datasets
### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification probl... |
https://github.com/huggingface/datasets/issues/7757 | Add support for `.conll` file format in datasets | hey @CrypticCortex , ngl i got too busy with uni and i actually forgot about this haha, if you'd like we can work together on it.
this feature is something i really needed at the time. | ### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification problems.
Right now `.conll` datasets need to be manu... | 36 | Add support for `.conll` file format in datasets
### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification probl... |
https://github.com/huggingface/datasets/issues/7757 | Add support for `.conll` file format in datasets | hey @namesarnav glad you're back. happy to pair....was thinking i scaffold the packaged_modules/conll/ builder (mirroring csv/text shape) and you weigh in on the column-mapping defaults since you've worked with these formats more. but lmk if you want to split it differently or just stay in the review loop.
| ### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification problems.
Right now `.conll` datasets need to be manu... | 48 | Add support for `.conll` file format in datasets
### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification probl... |
https://github.com/huggingface/datasets/issues/7757 | Add support for `.conll` file format in datasets | @CrypticCortex yeah sure, go ahead. use text as base since that is more relevant to regular conll files, lmk when you get that done! | ### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification problems.
Right now `.conll` datasets need to be manu... | 24 | Add support for `.conll` file format in datasets
### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification probl... |
https://github.com/huggingface/datasets/issues/7757 | Add support for `.conll` file format in datasets | @namesarnav done — pr at [#8219](https://github.com/huggingface/datasets/pull/8219) . text-builder shape worked well as you suggested. supports both .conll and .conllu extensions out of the box, with the conll-u variant pre-applying comment_prefix="#". 14 tests cover conll-2003 / 2000 / u + edge cases (docstart, tail s... | ### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification problems.
Right now `.conll` datasets need to be manu... | 65 | Add support for `.conll` file format in datasets
### Feature request
I’d like to request native support in the Hugging Face datasets library for reading .conll files (CoNLL format). This format is widely used in NLP tasks, especially for Named Entity Recognition (NER), POS tagging, and other token classification probl... |
https://github.com/huggingface/datasets/issues/4732 | Document better that loading a dataset passing its name does not use the local script | Thanks for the feedback!
I think since this issue is closely related to loading, I can add a clearer explanation under [Load > local loading script](https://huggingface.co/docs/datasets/main/en/loading#local-loading-script). | As reported by @TrentBrick here https://github.com/huggingface/datasets/issues/4725#issuecomment-1191858596, it could be more clear that loading a dataset by passing its name does not use the (modified) local script of it.
What he did:
- he installed `datasets` from source
- he modified locally `datasets/the_pile/... | 26 | Document better that loading a dataset passing its name does not use the local script
As reported by @TrentBrick here https://github.com/huggingface/datasets/issues/4725#issuecomment-1191858596, it could be more clear that loading a dataset by passing its name does not use the (modified) local script of it.
What he ... |
https://github.com/huggingface/datasets/issues/4732 | Document better that loading a dataset passing its name does not use the local script | That makes sense but I think having a line about it under https://huggingface.co/docs/datasets/installation#source the "source" header here would be useful. My mental model of `pip install -e .` does not include the fact that the source files aren't actually being used. | As reported by @TrentBrick here https://github.com/huggingface/datasets/issues/4725#issuecomment-1191858596, it could be more clear that loading a dataset by passing its name does not use the (modified) local script of it.
What he did:
- he installed `datasets` from source
- he modified locally `datasets/the_pile/... | 41 | Document better that loading a dataset passing its name does not use the local script
As reported by @TrentBrick here https://github.com/huggingface/datasets/issues/4725#issuecomment-1191858596, it could be more clear that loading a dataset by passing its name does not use the (modified) local script of it.
What he ... |
https://github.com/huggingface/datasets/issues/4732 | Document better that loading a dataset passing its name does not use the local script | Thanks for sharing your perspective. I think the `load_dataset` function is the only one that pulls from GitHub, and since this use-case is very specific, I don't think we need to include such a broad clarification in the Installation section.
Feel free to check out the linked PR and let me know if it needs any addi... | As reported by @TrentBrick here https://github.com/huggingface/datasets/issues/4725#issuecomment-1191858596, it could be more clear that loading a dataset by passing its name does not use the (modified) local script of it.
What he did:
- he installed `datasets` from source
- he modified locally `datasets/the_pile/... | 59 | Document better that loading a dataset passing its name does not use the local script
As reported by @TrentBrick here https://github.com/huggingface/datasets/issues/4725#issuecomment-1191858596, it could be more clear that loading a dataset by passing its name does not use the (modified) local script of it.
What he ... |
https://github.com/huggingface/datasets/issues/7291 | Why return_tensors='pt' doesn't work？ | Hi ! `datasets` uses Arrow as storage backend which is agnostic to deep learning frameworks like torch. If you want to get torch tensors back, you need to do `dataset = dataset.with_format("torch")` | ### Describe the bug
I tried to add input_ids to dataset with map(), and I used the return_tensors='pt', but why I got the callback with the type of List？
### Steps to reproduce the bug
, and I used the return_tensors='pt', but why I got the callback with the type of List？
### Steps to reproduce the bug
... |
https://github.com/huggingface/datasets/issues/7291 | Why return_tensors='pt' doesn't work？ | > Hi ! `datasets` uses Arrow as storage backend which is agnostic to deep learning frameworks like torch. If you want to get torch tensors back, you need to do `dataset = dataset.with_format("torch")`
It does work! Thanks for your suggestion! | ### Describe the bug
I tried to add input_ids to dataset with map(), and I used the return_tensors='pt', but why I got the callback with the type of List？
### Steps to reproduce the bug
, and I used the return_tensors='pt', but why I got the callback with the type of List？
### Steps to reproduce the bug
... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | Does "number of shards" refer to the total number of data?
my config:
nproc_per_node=2
ds=ds['train'] = load_dataset(streaming=True).take(50000)
I'm test again: in prepare_data(), data have the same for each GPU
| There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 29 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the da... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | The number of shards is `ds.n_shards`. It corresponds generally to the number of files the dataset is made of, to be able to distribute to several nodes.
**You don't end up with the same data per GPU**. But all the samples are going through your preprocessing function you pass to map. They are just skipped afterward... | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 64 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the da... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | For each GPU, although see the same data in prepare_data(), the actual training data will not be the same in the end.
Is my understanding correct?
Where can I print the actual training data for each GPU? | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 37 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the da... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | > For each GPU, although see the same data in prepare_data(), the actual training data will not be the same in the end.
Is my understanding correct?
Yes exactly :)
> Where can I print the actual training data for each GPU?
You should call print in the data_collator | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 49 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the da... |
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