html_url stringlengths 48 51 | title stringlengths 5 280 | comments stringlengths 63 51.8k | body stringlengths 0 36.2k ⌀ | comment_length int64 16 1.52k | text stringlengths 159 54.1k | embeddings listlengths 768 768 |
|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/6089 | AssertionError: daemonic processes are not allowed to have children | > We could add a "threads" parallel backend to `datasets.parallel.parallel_backend` to support downloading with threads but note that `download_and_extract` also decompresses archives, and this is a CPU-intensive task, which is not ideal for (Python) threads (good for IO-intensive tasks).
Great! Download takes more ... | ### Describe the bug
When I load_dataset with num_proc > 0 in a deamon process, I got an error:
```python
File "/Users/codingl2k1/Work/datasets/src/datasets/download/download_manager.py", line 564, in download_and_extract
return self.extract(self.download(url_or_urls))
^^^^^^^^^^^^^^^^^
File "/Users... | 58 | AssertionError: daemonic processes are not allowed to have children
### Describe the bug
When I load_dataset with num_proc > 0 in a deamon process, I got an error:
```python
File "/Users/codingl2k1/Work/datasets/src/datasets/download/download_manager.py", line 564, in download_and_extract
return self.extr... | [
-0.5046077370643616,
-0.41358450055122375,
-0.15014885365962982,
0.4784199595451355,
0.1318594366312027,
-0.006352901458740234,
0.22309695184230804,
-0.05357160046696663,
-0.0247789453715086,
0.07532718032598495,
0.13872188329696655,
0.24004310369491577,
-0.2916395962238312,
-0.12241759151... |
https://github.com/huggingface/datasets/issues/6086 | Support `fsspec` in `Dataset.to_<format>` methods | I'm assuming this should just cover `to_csv`, `to_parquet`, and `to_json`, right? As `to_list` and `to_dict` just return Python objects, `to_pandas` returns a `pandas.DataFrame` and `to_sql` just inserts into a SQL DB, is that right? | Supporting this should be fairly easy.
Requested on the forum [here](https://discuss.huggingface.co/t/how-can-i-convert-a-loaded-dataset-in-to-a-parquet-file-and-save-it-to-the-s3/48353). | 34 | Support `fsspec` in `Dataset.to_<format>` methods
Supporting this should be fairly easy.
Requested on the forum [here](https://discuss.huggingface.co/t/how-can-i-convert-a-loaded-dataset-in-to-a-parquet-file-and-save-it-to-the-s3/48353).
I'm assuming this should just cover `to_csv`, `to_parquet`, and `to_json`, ... | [
-0.22816504538059235,
-0.20701062679290771,
-0.07345107197761536,
0.013687685132026672,
0.3130878806114197,
-0.09484143555164337,
-0.029510851949453354,
0.19544264674186707,
-0.05052902549505234,
-0.05537717044353485,
-0.12054097652435303,
0.4630905091762543,
0.01380886696279049,
0.9158241... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | When the process starts to hang, can you interrupt it with CTRL + C and paste the error stack trace here? | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 21 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.12034155428409576,
-0.06106922775506973,
-0.05394645035266876,
0.29939770698547363,
-0.0075555890798568726,
0.13879653811454773,
0.3968620002269745,
0.22607295215129852,
-0.03234626352787018,
0.2422584593296051,
0.014716611243784428,
0.3595842123031616,
-0.005157136358320713,
0.19013662... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | Thanks @mariosasko for your prompt response, here's the stack trace:
```
KeyboardInterrupt Traceback (most recent call last)
Cell In[12], line 4
2 t = time.time()
3 iter_ = 0
----> 4 for batch in train_dataloader:
5 #batch_proc = streaming_obj.collect_streaming_dat... | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 308 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.11611801385879517,
-0.08128397166728973,
-0.03265773132443428,
0.27752193808555603,
0.005241136997938156,
0.10193123668432236,
0.4178648889064789,
0.2360876053571701,
-0.0588974691927433,
0.2419949173927307,
0.033153973519802094,
0.31277570128440857,
-0.008137241937220097,
0.18140929937... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | Update: If i let it run, it eventually fails with:
```
RuntimeError Traceback (most recent call last)
Cell In[16], line 4
2 t = time.time()
3 iter_ = 0
----> 4 for batch in train_dataloader:
5 #batch_proc = streaming_obj.collect_streaming_data_batch(batch)
... | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 416 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.1563848853111267,
-0.04011803865432739,
-0.026112090796232224,
0.27627280354499817,
0.0020155515521764755,
0.09724234789609909,
0.4256720244884491,
0.24761535227298737,
-0.07167793065309525,
0.2194664478302002,
0.021227069199085236,
0.33242067694664,
-0.02397504448890686,
0.189560621976... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | PyTorch tensors cannot store `Decimal` objects. Casting the column with decimals to `float` should fix the issue. | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 17 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.09444297850131989,
-0.06475373357534409,
-0.029098303988575935,
0.3447765111923218,
0.04791253060102463,
0.09503508359193802,
0.45834895968437195,
0.2557198405265808,
-0.0722559243440628,
0.2827421724796295,
-0.019446847960352898,
0.35102713108062744,
-0.0015756366774439812,
0.125242084... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | I already have cast in collate_fn, in which I perform .astype(float) for each numerical field.
On the same instance, I installed a conda env with python 3.6, and this works well.
Sample:
```
def streaming_data_collate_fn(batch):
df = pd.DataFrame.from_dict(batch)
feat_vals = torch.FloatTensor(np.nan_t... | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 42 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.06654274463653564,
-0.02089744806289673,
-0.018205003812909126,
0.259533554315567,
0.08013083785772324,
0.0900522992014885,
0.473732590675354,
0.23492825031280518,
-0.06655088067054749,
0.2405540645122528,
-0.01982230320572853,
0.3410205841064453,
0.03522254899144173,
0.1359455138444900... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | `collate_fn` is applied after the `torch` formatting step, so I think the only option when working with an `IterableDataset` is to remove the `with_format` call and perform the conversion from Python values to PyTorch tensors in `collate_fn`. The standard `Dataset` supports `with_format("numpy")`, which should make thi... | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 48 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.09866772592067719,
-0.05150693655014038,
-0.0060966890305280685,
0.25379228591918945,
0.03468255698680878,
0.12388598173856735,
0.5064866542816162,
0.27355942130088806,
-0.14257481694221497,
0.21018089354038239,
-0.024298863485455513,
0.3711855411529541,
0.0008322000503540039,
0.1366596... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | Thanks!
Python 3.10 conda-env: After replacing with_format("torch") with with_format("numpy"), the error went away. However, it was still taking over 2 minutes to load a very small batch of 64 samples with num_workers set to 32. Once I removed with_format call altogether, it is finishing in 11 seconds.
Python 3.6 ... | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 83 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.087595134973526,
-0.05146826058626175,
-0.008220763877034187,
0.2627723813056946,
0.07494160532951355,
0.032871171832084656,
0.5292813777923584,
0.29862651228904724,
-0.16207551956176758,
0.18641173839569092,
-0.0485047921538353,
0.42074963450431824,
-0.007070318795740604,
0.08174891769... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | Can you share the `datasets` and `torch` versions installed in these conda envs?
> Once I removed with_format call altogether, it is finishing in 11 seconds.
Hmm, that's surprising. What are your dataset's `.features`? | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 34 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.09469516575336456,
-0.07855184376239777,
-0.025267140939831734,
0.2823977470397949,
-0.0035468265414237976,
0.10885124653577805,
0.43466904759407043,
0.26948973536491394,
-0.0667296051979065,
0.20157024264335632,
-0.0014982549473643303,
0.3665716052055359,
-0.0019920850172638893,
0.1998... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | Python 3.6:
datasets.__version__ 2.4.0
torch.__version__ 1.10.1+cu102
Python 3.10:
datasets.__version__ 2.14.0
torch.__version__ 2.0.0
Anonymized features are of the form (subset shown here):
{
'string_feature_i': Value(dtype='string', id=None),
'numerical_feature_i': Value(dtype='decimal128(38, 0)', id=N... | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 46 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.10414494574069977,
-0.06336086988449097,
-0.03020908497273922,
0.2883920669555664,
0.0075524915009737015,
0.10713665932416916,
0.44242048263549805,
0.2390352338552475,
-0.07540088146924973,
0.23192623257637024,
0.004603263456374407,
0.38680028915405273,
0.022636644542217255,
0.164019912... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | One more thing, in python 3.10 based kernel, interestingly increasing num_workers seem to be increasing the runtime of iterating I was trying out. In python 3.10 kernel execution, I do not even see multiple CPU cores spiking unlike in 3.6.
512 batch size on 32 workers executes in 2.4 seconds on python 3.6 kernel, wh... | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 61 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.1618717759847641,
-0.11623475700616837,
-0.05073045194149017,
0.24418897926807404,
-0.047889284789562225,
0.04484961926937103,
0.5003330111503601,
0.24632807075977325,
-0.09249958395957947,
0.25677400827407837,
0.011409665457904339,
0.4652772545814514,
-0.047021735459566116,
0.148621603... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | **Update**: It seems the latency part is more of a multiprocessing issue with torch and some host specific issue, and I had to scourge through relevant pytorch issues, when I stumbled across these threads:
1. https://github.com/pytorch/pytorch/issues/102494
2. https://github.com/pytorch/pytorch/issues/102269
3. http... | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 87 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.1282348930835724,
-0.16303855180740356,
-0.03323454409837723,
0.22006115317344666,
-0.08479119837284088,
0.044966258108615875,
0.4441736340522766,
0.2328474521636963,
-0.08224599063396454,
0.19713321328163147,
0.04701299965381622,
0.3833540081977844,
0.020228806883096695,
-0.00336618348... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | I'm facing a similar situation in the local VS Code.
Datasets version 2.14.4
Torch 2.0.1+cu118
Same code runs without issues in Colab
```
from datasets import load_dataset
dataset = load_dataset("Supermaxman/esa-hubble", streaming=True)
sample = next(iter(dataset["train"]))
```
is stuck for minutes.... | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 155 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.15123406052589417,
-0.03259515017271042,
-0.02845512516796589,
0.23572959005832672,
-0.027844958007335663,
0.07383473962545395,
0.3774380385875702,
0.20796845853328705,
-0.021897586062550545,
0.385067880153656,
-0.012811973690986633,
0.3522011339664459,
-0.008928348310291767,
0.16393548... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | @osanseviero I assume the `self._sslobj.read(len, buffer)` line comes from the built-in `ssl` module, so this probably has something to do with your network. Please open a new issue with the full stack trace in case you haven't resolved this yet. | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 40 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.08103130757808685,
-0.013380534946918488,
-0.036693647503852844,
0.2710031270980835,
-0.03732561320066452,
0.0885935053229332,
0.45809710025787354,
0.20576384663581848,
-0.0007539670914411545,
0.2618664801120758,
0.0385136678814888,
0.29885172843933105,
0.03217671066522598,
0.2101486027... |
https://github.com/huggingface/datasets/issues/6079 | Iterating over DataLoader based on HF datasets is stuck forever | Ran into same issue after upgrading to pytorch-2.0. Disabling KMP_AFFINITY as mentioned above worked for me. Thanks!
| ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What shou... | 17 | Iterating over DataLoader based on HF datasets is stuck forever
### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is wo... | [
-0.05018563196063042,
-0.09019803255796432,
-0.02637721598148346,
0.24758650362491608,
-0.0008604787290096283,
0.02632962167263031,
0.3614424467086792,
0.22580324113368988,
-0.08515036106109619,
0.23723386228084564,
0.032829396426677704,
0.40315142273902893,
-0.04841122776269913,
0.1293270... |
https://github.com/huggingface/datasets/issues/6078 | resume_download with streaming=True | Currently, it's not possible to efficiently resume streaming after an error. Eventually, we plan to support this for Parquet (see https://github.com/huggingface/datasets/issues/5380). | ### Describe the bug
I used:
```
dataset = load_dataset(
"oscar-corpus/OSCAR-2201",
token=True,
language="fr",
streaming=True,
split="train"
)
```
Unfortunately, the server had a problem during the training process. I saved the step my training stopped at.
But how can I resume download f... | 21 | resume_download with streaming=True
### Describe the bug
I used:
```
dataset = load_dataset(
"oscar-corpus/OSCAR-2201",
token=True,
language="fr",
streaming=True,
split="train"
)
```
Unfortunately, the server had a problem during the training process. I saved the step my training stoppe... | [
-0.4960499703884125,
-0.22135543823242188,
0.09422238171100616,
0.04180407524108887,
0.2625921964645386,
-0.0770002007484436,
-0.12203124165534973,
-0.01835404708981514,
0.010030895471572876,
0.11760860681533813,
0.050583191215991974,
0.10911090672016144,
0.029635418206453323,
0.3978592455... |
https://github.com/huggingface/datasets/issues/6077 | Mapping gets stuck at 99% | The `MAX_MAP_BATCH_SIZE = 1_000_000_000` hack is bad as it loads the entire dataset into RAM when performing `.map`. Instead, it's best to use `.iter(batch_size)` to iterate over the data batches and compute `mean` for each column. (`stddev` can be computed in another pass).
Also, these arrays are big, so it makes s... | ### Describe the bug
Hi !
I'm currently working with a large (~150GB) unnormalized dataset at work.
The dataset is available on a read-only filesystem internally, and I use a [loading script](https://huggingface.co/docs/datasets/dataset_script) to retreive it.
I want to normalize the features of the dataset, ... | 62 | Mapping gets stuck at 99%
### Describe the bug
Hi !
I'm currently working with a large (~150GB) unnormalized dataset at work.
The dataset is available on a read-only filesystem internally, and I use a [loading script](https://huggingface.co/docs/datasets/dataset_script) to retreive it.
I want to normalize t... | [
-0.2388804703950882,
-0.42039424180984497,
0.11454983055591583,
0.013677917420864105,
0.3820091485977173,
-0.026951275765895844,
-0.09978540241718292,
0.2806102931499481,
0.2809220254421234,
0.42724764347076416,
-0.14177918434143066,
0.3004532754421234,
0.17234168946743011,
-0.092543408274... |
https://github.com/huggingface/datasets/issues/6077 | Mapping gets stuck at 99% | Hi @mariosasko !
I agree, it's an ugly hack, but it was convenient since the resulting `mean_std` could be cached by the library. For my large dataset (which doesn't fit in RAM), I'm actually using something similar to what you suggested. I got rid of the first mapping in the above scripts and replaced it with an it... | ### Describe the bug
Hi !
I'm currently working with a large (~150GB) unnormalized dataset at work.
The dataset is available on a read-only filesystem internally, and I use a [loading script](https://huggingface.co/docs/datasets/dataset_script) to retreive it.
I want to normalize the features of the dataset, ... | 67 | Mapping gets stuck at 99%
### Describe the bug
Hi !
I'm currently working with a large (~150GB) unnormalized dataset at work.
The dataset is available on a read-only filesystem internally, and I use a [loading script](https://huggingface.co/docs/datasets/dataset_script) to retreive it.
I want to normalize t... | [
-0.2388804703950882,
-0.42039424180984497,
0.11454983055591583,
0.013677917420864105,
0.3820091485977173,
-0.026951275765895844,
-0.09978540241718292,
0.2806102931499481,
0.2809220254421234,
0.42724764347076416,
-0.14177918434143066,
0.3004532754421234,
0.17234168946743011,
-0.092543408274... |
https://github.com/huggingface/datasets/issues/6077 | Mapping gets stuck at 99% | Have you tried to reduce `batch_size`/`writer_batch_size` in the 2nd `.map`? Also, can you interrupt the process when it gets stuck and share the error stack trace? | ### Describe the bug
Hi !
I'm currently working with a large (~150GB) unnormalized dataset at work.
The dataset is available on a read-only filesystem internally, and I use a [loading script](https://huggingface.co/docs/datasets/dataset_script) to retreive it.
I want to normalize the features of the dataset, ... | 26 | Mapping gets stuck at 99%
### Describe the bug
Hi !
I'm currently working with a large (~150GB) unnormalized dataset at work.
The dataset is available on a read-only filesystem internally, and I use a [loading script](https://huggingface.co/docs/datasets/dataset_script) to retreive it.
I want to normalize t... | [
-0.2388804703950882,
-0.42039424180984497,
0.11454983055591583,
0.013677917420864105,
0.3820091485977173,
-0.026951275765895844,
-0.09978540241718292,
0.2806102931499481,
0.2809220254421234,
0.42724764347076416,
-0.14177918434143066,
0.3004532754421234,
0.17234168946743011,
-0.092543408274... |
https://github.com/huggingface/datasets/issues/6077 | Mapping gets stuck at 99% | I think `batch_size/writer_batch_size` is already at its lowest in the 2nd `.map` since `batched=False` implies `batch_size=1` and `len(ds) = 1000 = writer_batch_size`.
Here is also a bunch of stack traces when I interrupted the process:
<details>
<summary>stack trace 1</summary>
```python
(pyg)[d623204@ro... | ### Describe the bug
Hi !
I'm currently working with a large (~150GB) unnormalized dataset at work.
The dataset is available on a read-only filesystem internally, and I use a [loading script](https://huggingface.co/docs/datasets/dataset_script) to retreive it.
I want to normalize the features of the dataset, ... | 1,454 | Mapping gets stuck at 99%
### Describe the bug
Hi !
I'm currently working with a large (~150GB) unnormalized dataset at work.
The dataset is available on a read-only filesystem internally, and I use a [loading script](https://huggingface.co/docs/datasets/dataset_script) to retreive it.
I want to normalize t... | [
-0.2388804703950882,
-0.42039424180984497,
0.11454983055591583,
0.013677917420864105,
0.3820091485977173,
-0.026951275765895844,
-0.09978540241718292,
0.2806102931499481,
0.2809220254421234,
0.42724764347076416,
-0.14177918434143066,
0.3004532754421234,
0.17234168946743011,
-0.092543408274... |
https://github.com/huggingface/datasets/issues/6075 | Error loading music files using `load_dataset` | This code behaves as expected on my local machine or in Colab. Which version of `soundfile` do you have installed? MP3 requires `soundfile>=0.12.1`. | ### Describe the bug
I tried to load a music file using `datasets.load_dataset()` from the repository - https://huggingface.co/datasets/susnato/pop2piano_real_music_test
I got the following error -
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/susnato/anaconda3/en... | 23 | Error loading music files using `load_dataset`
### Describe the bug
I tried to load a music file using `datasets.load_dataset()` from the repository - https://huggingface.co/datasets/susnato/pop2piano_real_music_test
I got the following error -
```
Traceback (most recent call last):
File "<stdin>", line 1... | [
-0.23908647894859314,
0.018336161971092224,
-0.09103678166866302,
0.46061939001083374,
0.4076109528541565,
-0.08961306512355804,
0.20931801199913025,
0.24716612696647644,
-0.10778580605983734,
0.07141643762588501,
-0.3074873387813568,
0.444944828748703,
-0.031737372279167175,
-0.1055335775... |
https://github.com/huggingface/datasets/issues/6073 | version2.3.2 load_dataset()data_files can't include .xxxx in path | Version 2.3.2 is over one year old, so please use the latest release (2.14.0) to get the expected behavior. Version 2.3.2 does not contain some fixes we made to fix resolving hidden files/directories (starting with a dot). | ### Describe the bug
First, I cd workdir.
Then, I just use load_dataset("json", data_file={"train":"/a/b/c/.d/train/train.json", "test":"/a/b/c/.d/train/test.json"})
that couldn't work and
<FileNotFoundError: Unable to find
'/a/b/c/.d/train/train.jsonl' at
/a/b/c/.d/>
And I debug, it is fine in version2.1.2... | 37 | version2.3.2 load_dataset()data_files can't include .xxxx in path
### Describe the bug
First, I cd workdir.
Then, I just use load_dataset("json", data_file={"train":"/a/b/c/.d/train/train.json", "test":"/a/b/c/.d/train/test.json"})
that couldn't work and
<FileNotFoundError: Unable to find
'/a/b/c/.d/train/tr... | [
-0.07166016101837158,
0.4233100414276123,
-0.05782254785299301,
0.46117913722991943,
0.17863178253173828,
0.13693565130233765,
0.2276168018579483,
0.3537435531616211,
0.06425751745700836,
-0.15938116610050201,
0.18695907294750214,
0.5130404233932495,
-0.0992254987359047,
0.1076414063572883... |
https://github.com/huggingface/datasets/issues/6071 | storage_options provided to load_dataset not fully piping through since datasets 2.14.0 | Hi ! Thanks for reporting, I opened a PR to fix this
What filesystem are you using ? | ### Describe the bug
Since the latest release of `datasets` (`2.14.0`), custom filesystem `storage_options` passed to `load_dataset()` do not seem to propagate through all the way - leading to problems if loading data files that need those options to be set.
I think this is because of the new `_prepare_path_and_sto... | 18 | storage_options provided to load_dataset not fully piping through since datasets 2.14.0
### Describe the bug
Since the latest release of `datasets` (`2.14.0`), custom filesystem `storage_options` passed to `load_dataset()` do not seem to propagate through all the way - leading to problems if loading data files that ... | [
-0.15290424227714539,
-0.011342160403728485,
-0.0035984087735414505,
0.1689012348651886,
0.1570984125137329,
-0.12320028245449066,
0.09978185594081879,
0.07052542269229889,
-0.2103186547756195,
-0.010081857442855835,
-0.05347342789173126,
0.3284134864807129,
-0.01689298450946808,
0.2652380... |
https://github.com/huggingface/datasets/issues/6071 | storage_options provided to load_dataset not fully piping through since datasets 2.14.0 | Hi @lhoestq ! Thank you so much 🙌
It's a bit of a custom setup, but in practice I am using a [pyarrow.fs.S3FileSystem](https://arrow.apache.org/docs/python/generated/pyarrow.fs.S3FileSystem.html) (wrapped in a `fsspec.implementations.arrow.ArrowFSWrapper` [to make it](https://arrow.apache.org/docs/python/filesyste... | ### Describe the bug
Since the latest release of `datasets` (`2.14.0`), custom filesystem `storage_options` passed to `load_dataset()` do not seem to propagate through all the way - leading to problems if loading data files that need those options to be set.
I think this is because of the new `_prepare_path_and_sto... | 86 | storage_options provided to load_dataset not fully piping through since datasets 2.14.0
### Describe the bug
Since the latest release of `datasets` (`2.14.0`), custom filesystem `storage_options` passed to `load_dataset()` do not seem to propagate through all the way - leading to problems if loading data files that ... | [
-0.15290424227714539,
-0.011342160403728485,
-0.0035984087735414505,
0.1689012348651886,
0.1570984125137329,
-0.12320028245449066,
0.09978185594081879,
0.07052542269229889,
-0.2103186547756195,
-0.010081857442855835,
-0.05347342789173126,
0.3284134864807129,
-0.01689298450946808,
0.2652380... |
https://github.com/huggingface/datasets/issues/6069 | KeyError: dataset has no key "image" | You can list the dataset's columns with `ds.column_names` before `.map` to check whether the dataset has an `image` column. If it doesn't, then this is a bug. Otherwise, please paste the line with the `.map` call.
| ### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset. When I printed out the example_batch ... | 36 | KeyError: dataset has no key "image"
### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset... | [
-0.32401198148727417,
-0.15878283977508545,
-0.011707793921232224,
0.12749545276165009,
0.21714608371257782,
0.11436022073030472,
0.4323761761188507,
0.18996253609657288,
0.20589525997638702,
0.12764689326286316,
0.33117449283599854,
0.35847941040992737,
-0.33052578568458557,
0.02167779393... |
https://github.com/huggingface/datasets/issues/6069 | KeyError: dataset has no key "image" | This is the piece of code I am running:
```
data_transforms = utils.get_data_augmentation(args)
image_dataset = utils.load_image_dataset(args.dataset)
def resize(examples):
examples["pixel_values"] = [image.convert("RGB").resize((300, 300)) for image in examples["image"]]
return examples
def preproce... | ### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset. When I printed out the example_batch ... | 1,035 | KeyError: dataset has no key "image"
### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset... | [
-0.22105185687541962,
-0.05650898069143295,
-0.060585517436265945,
0.10834081470966339,
0.2632572054862976,
0.1530718207359314,
0.47241756319999695,
0.2116657942533493,
0.12337958812713623,
0.16673406958580017,
0.2963007390499115,
0.31560662388801575,
-0.33497437834739685,
0.09006076306104... |
https://github.com/huggingface/datasets/issues/6069 | KeyError: dataset has no key "image" | The `remove_columns=["image"]` argument in the `.map` call removes the `image` column from the output, so drop this argument to preserve it. | ### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset. When I printed out the example_batch ... | 21 | KeyError: dataset has no key "image"
### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset... | [
-0.315396249294281,
-0.1061716303229332,
-0.01786620169878006,
0.12197808176279068,
0.21011845767498016,
0.11844345182180405,
0.4634915888309479,
0.20816485583782196,
0.21189354360103607,
0.12302280217409134,
0.30953651666641235,
0.3759862184524536,
-0.3384236991405487,
0.01839578337967395... |
https://github.com/huggingface/datasets/issues/6069 | KeyError: dataset has no key "image" | The problem is not with the removal of the image key. The bug is why only the labels are sent to be process, instead of all the featues or dictionary keys.
P.S. I just dropped the removal argument as you've suggested, but that didn't solve the problem, because only the labels are being sent to be processed | ### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset. When I printed out the example_batch ... | 57 | KeyError: dataset has no key "image"
### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset... | [
-0.17238695919513702,
-0.16476114094257355,
-0.010105390101671219,
0.16590508818626404,
0.17817983031272888,
0.1107020452618599,
0.40471282601356506,
0.2250402718782425,
0.16491904854774475,
0.19509533047676086,
0.3144141733646393,
0.3826318383216858,
-0.3329390287399292,
0.066406339406967... |
https://github.com/huggingface/datasets/issues/6069 | KeyError: dataset has no key "image" | All the `image_dataset.column_names` after the `map` call should also be present in `preprocess_train `/`preprocess_val` unless (input) `columns` in `set_transform` are specified.
If that's not the case, we need a full reproducer (not snippets) with the environment info. | ### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset. When I printed out the example_batch ... | 37 | KeyError: dataset has no key "image"
### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset... | [
-0.3361896872520447,
-0.09481362253427505,
-0.013615678064525127,
0.11722642928361893,
0.2425266057252884,
0.10842419415712357,
0.4697721302509308,
0.2000844031572342,
0.1968294233083725,
0.1282198429107666,
0.3283745050430298,
0.38420748710632324,
-0.3407844603061676,
0.03303402662277222,... |
https://github.com/huggingface/datasets/issues/6069 | KeyError: dataset has no key "image" | I have resolved the error after including a collate function as indicated in the Quick Start session of the Datasets docs.:
Here is what I did:
```
data_transforms = utils.get_data_augmentation(args)
image_dataset = utils.load_image_dataset(args.dataset)
def preprocess_train(example_batch):
example_batch[... | ### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset. When I printed out the example_batch ... | 139 | KeyError: dataset has no key "image"
### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset... | [
-0.189932182431221,
-0.05999205261468887,
-0.01674068719148636,
0.15395531058311462,
0.30590397119522095,
0.2208966314792633,
0.5759837627410889,
0.20979993045330048,
-0.06959941983222961,
0.17101134359836578,
0.22148264944553375,
0.3101060390472412,
-0.3101203143596649,
0.0187277030199766... |
https://github.com/huggingface/datasets/issues/6066 | AttributeError: '_tqdm_cls' object has no attribute '_lock' | Hi ! I opened https://github.com/huggingface/datasets/pull/6067 to add the missing `_lock`
We'll do a patch release soon, but feel free to install `datasets` from source in the meantime | ### Describe the bug
```python
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-packages/datasets/load.py", line 1034, in get_module
data_files = DataFilesDict.from_patterns(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-p... | 27 | AttributeError: '_tqdm_cls' object has no attribute '_lock'
### Describe the bug
```python
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-packages/datasets/load.py", line 1034, in get_module
data_files = DataFilesDict.from_patterns(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "... | [
-0.17624354362487793,
-0.28966188430786133,
-0.08112603425979614,
0.21007438004016876,
0.23333759605884552,
-0.10606656968593597,
0.3419617712497711,
0.3747365474700928,
-0.07112058997154236,
0.045171499252319336,
-0.052811406552791595,
0.3634183704853058,
-0.19713012874126434,
0.045730687... |
https://github.com/huggingface/datasets/issues/6066 | AttributeError: '_tqdm_cls' object has no attribute '_lock' | I have tested the latest main, it does not work.
I add more logs to reproduce this issue, it looks like a multi threading bug:
```python
@contextmanager
def ensure_lock(tqdm_class, lock_name=""):
"""get (create if necessary) and then restore `tqdm_class`'s lock"""
import os
import threading
... | ### Describe the bug
```python
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-packages/datasets/load.py", line 1034, in get_module
data_files = DataFilesDict.from_patterns(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-p... | 184 | AttributeError: '_tqdm_cls' object has no attribute '_lock'
### Describe the bug
```python
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-packages/datasets/load.py", line 1034, in get_module
data_files = DataFilesDict.from_patterns(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "... | [
-0.17624354362487793,
-0.28966188430786133,
-0.08112603425979614,
0.21007438004016876,
0.23333759605884552,
-0.10606656968593597,
0.3419617712497711,
0.3747365474700928,
-0.07112058997154236,
0.045171499252319336,
-0.052811406552791595,
0.3634183704853058,
-0.19713012874126434,
0.045730687... |
https://github.com/huggingface/datasets/issues/6066 | AttributeError: '_tqdm_cls' object has no attribute '_lock' | Maybe it is a bug of tqdm? I think simply use `try ... except AttributeError ...` wraps `del tqdm_class._lock` should work. | ### Describe the bug
```python
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-packages/datasets/load.py", line 1034, in get_module
data_files = DataFilesDict.from_patterns(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-p... | 21 | AttributeError: '_tqdm_cls' object has no attribute '_lock'
### Describe the bug
```python
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-packages/datasets/load.py", line 1034, in get_module
data_files = DataFilesDict.from_patterns(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "... | [
-0.17624354362487793,
-0.28966188430786133,
-0.08112603425979614,
0.21007438004016876,
0.23333759605884552,
-0.10606656968593597,
0.3419617712497711,
0.3747365474700928,
-0.07112058997154236,
0.045171499252319336,
-0.052811406552791595,
0.3634183704853058,
-0.19713012874126434,
0.045730687... |
https://github.com/huggingface/datasets/issues/6066 | AttributeError: '_tqdm_cls' object has no attribute '_lock' | Yes it looks like a bug on their end indeed, do you want to open a PR on tqdm ?
Let me see if I can find a workaround in the meantime | ### Describe the bug
```python
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-packages/datasets/load.py", line 1034, in get_module
data_files = DataFilesDict.from_patterns(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-p... | 32 | AttributeError: '_tqdm_cls' object has no attribute '_lock'
### Describe the bug
```python
File "/Users/codingl2k1/.pyenv/versions/3.11.4/lib/python3.11/site-packages/datasets/load.py", line 1034, in get_module
data_files = DataFilesDict.from_patterns(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "... | [
-0.17624354362487793,
-0.28966188430786133,
-0.08112603425979614,
0.21007438004016876,
0.23333759605884552,
-0.10606656968593597,
0.3419617712497711,
0.3747365474700928,
-0.07112058997154236,
0.045171499252319336,
-0.052811406552791595,
0.3634183704853058,
-0.19713012874126434,
0.045730687... |
https://github.com/huggingface/datasets/issues/6060 | Dataset.map() execute twice when in PyTorch DDP mode | Sorry for asking a duplicate question about `num_proc`, I searched the forum and find the solution.
But I still can't make the trick with `torch.distributed.barrier()` to only map at the main process work. The [post on forum]( https://discuss.huggingface.co/t/slow-processing-with-map-when-using-deepspeed-or-fairscal... | ### Describe the bug
I use `torchrun --standalone --nproc_per_node=2 train.py` to start training. And write the code following the [docs](https://huggingface.co/docs/datasets/process#distributed-usage). The trick about using `torch.distributed.barrier()` to only execute map at the main process doesn't always work. W... | 40 | Dataset.map() execute twice when in PyTorch DDP mode
### Describe the bug
I use `torchrun --standalone --nproc_per_node=2 train.py` to start training. And write the code following the [docs](https://huggingface.co/docs/datasets/process#distributed-usage). The trick about using `torch.distributed.barrier()` to only... | [
-0.32103079557418823,
-0.7901479601860046,
0.07416689395904541,
0.47603583335876465,
0.19198888540267944,
-0.20305147767066956,
0.33363714814186096,
-0.0628698319196701,
0.286129355430603,
0.10323995351791382,
0.09885290265083313,
0.4266767203807831,
0.10860054194927216,
-0.270735383033752... |
https://github.com/huggingface/datasets/issues/6060 | Dataset.map() execute twice when in PyTorch DDP mode | If it does the `map` twice then it means the hash of your map function is not some same between your two processes.
Can you make sure your map functions have the same hash in different processes ?
```python
from datasets.fingerprint import Hasher
print(Hasher.hash(lambda x: cut_reorder_keys(x, num_stations_li... | ### Describe the bug
I use `torchrun --standalone --nproc_per_node=2 train.py` to start training. And write the code following the [docs](https://huggingface.co/docs/datasets/process#distributed-usage). The trick about using `torch.distributed.barrier()` to only execute map at the main process doesn't always work. W... | 95 | Dataset.map() execute twice when in PyTorch DDP mode
### Describe the bug
I use `torchrun --standalone --nproc_per_node=2 train.py` to start training. And write the code following the [docs](https://huggingface.co/docs/datasets/process#distributed-usage). The trick about using `torch.distributed.barrier()` to only... | [
-0.32103079557418823,
-0.7901479601860046,
0.07416689395904541,
0.47603583335876465,
0.19198888540267944,
-0.20305147767066956,
0.33363714814186096,
-0.0628698319196701,
0.286129355430603,
0.10323995351791382,
0.09885290265083313,
0.4266767203807831,
0.10860054194927216,
-0.270735383033752... |
https://github.com/huggingface/datasets/issues/6060 | Dataset.map() execute twice when in PyTorch DDP mode | Thanks for help! I find the fingerprint between processes don't have same hash:
```
Rank 0: Gpu 0 cut_reorder_keys fingerprint c7f47f40e9a67657
Rank 0: Gpu 0 random_shift fingerprint 240a0ce79831e7d4
Rank 1: Gpu 1 cut_reorder_keys fingerprint 20edd3d9cf284001
Rank 1: Gpu 1 random_shift fingerprint 819f7c1c18e773... | ### Describe the bug
I use `torchrun --standalone --nproc_per_node=2 train.py` to start training. And write the code following the [docs](https://huggingface.co/docs/datasets/process#distributed-usage). The trick about using `torch.distributed.barrier()` to only execute map at the main process doesn't always work. W... | 90 | Dataset.map() execute twice when in PyTorch DDP mode
### Describe the bug
I use `torchrun --standalone --nproc_per_node=2 train.py` to start training. And write the code following the [docs](https://huggingface.co/docs/datasets/process#distributed-usage). The trick about using `torch.distributed.barrier()` to only... | [
-0.32103079557418823,
-0.7901479601860046,
0.07416689395904541,
0.47603583335876465,
0.19198888540267944,
-0.20305147767066956,
0.33363714814186096,
-0.0628698319196701,
0.286129355430603,
0.10323995351791382,
0.09885290265083313,
0.4266767203807831,
0.10860054194927216,
-0.270735383033752... |
https://github.com/huggingface/datasets/issues/6060 | Dataset.map() execute twice when in PyTorch DDP mode | I finally figure it out. The fingerprint of the function will change if other key-value pairs change in `args` even the `args.num_stations_list` is not changed.
```python
lambda x: cut_reorder_keys(x, num_stations_list=args.num_stations_list, is_pad=True, is_train=True)
```
My `args` contains the key `rank` whi... | ### Describe the bug
I use `torchrun --standalone --nproc_per_node=2 train.py` to start training. And write the code following the [docs](https://huggingface.co/docs/datasets/process#distributed-usage). The trick about using `torch.distributed.barrier()` to only execute map at the main process doesn't always work. W... | 86 | Dataset.map() execute twice when in PyTorch DDP mode
### Describe the bug
I use `torchrun --standalone --nproc_per_node=2 train.py` to start training. And write the code following the [docs](https://huggingface.co/docs/datasets/process#distributed-usage). The trick about using `torch.distributed.barrier()` to only... | [
-0.32103079557418823,
-0.7901479601860046,
0.07416689395904541,
0.47603583335876465,
0.19198888540267944,
-0.20305147767066956,
0.33363714814186096,
-0.0628698319196701,
0.286129355430603,
0.10323995351791382,
0.09885290265083313,
0.4266767203807831,
0.10860054194927216,
-0.270735383033752... |
https://github.com/huggingface/datasets/issues/6059 | Provide ability to load label mappings from file | I would like this also as I have been working with a dataset with hierarchical classes. In fact, I encountered this very issue when trying to define the dataset with a script. I couldn't find a work around and reverted to hard coding the class names in the readme yaml.
@david-waterworth do you envision also being ab... | ### Feature request
My task is classification of a dataset containing a large label set that includes a hierarchy. Even ignoring the hierarchy I'm not able to find an example using `datasets` where the label names aren't hard-coded. This works find for classification of a handful of labels but ideally there would be... | 65 | Provide ability to load label mappings from file
### Feature request
My task is classification of a dataset containing a large label set that includes a hierarchy. Even ignoring the hierarchy I'm not able to find an example using `datasets` where the label names aren't hard-coded. This works find for classificatio... | [
-0.23057903349399567,
0.43088358640670776,
0.06760111451148987,
0.6072050333023071,
0.2155102789402008,
0.08691208809614182,
0.3997461199760437,
0.3549935221672058,
0.2451525330543518,
0.1859813779592514,
-0.130423441529274,
0.39898958802223206,
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0.10869807749986649,
0... |
https://github.com/huggingface/datasets/issues/6059 | Provide ability to load label mappings from file | @danielduckworth yes I did need to do that (but I ended up ditching datasets as it looks like this is a "wont fix"). | ### Feature request
My task is classification of a dataset containing a large label set that includes a hierarchy. Even ignoring the hierarchy I'm not able to find an example using `datasets` where the label names aren't hard-coded. This works find for classification of a handful of labels but ideally there would be... | 23 | Provide ability to load label mappings from file
### Feature request
My task is classification of a dataset containing a large label set that includes a hierarchy. Even ignoring the hierarchy I'm not able to find an example using `datasets` where the label names aren't hard-coded. This works find for classificatio... | [
-0.23057903349399567,
0.43088358640670776,
0.06760111451148987,
0.6072050333023071,
0.2155102789402008,
0.08691208809614182,
0.3997461199760437,
0.3549935221672058,
0.2451525330543518,
0.1859813779592514,
-0.130423441529274,
0.39898958802223206,
-0.254896342754364,
0.10869807749986649,
0... |
https://github.com/huggingface/datasets/issues/6059 | Provide ability to load label mappings from file | @david-waterworth Hmm, that's a shame. What are you using now? Also, I’m curious to know about the work you’re doing that involves hierarchical classes, if you don’t mind sharing. | ### Feature request
My task is classification of a dataset containing a large label set that includes a hierarchy. Even ignoring the hierarchy I'm not able to find an example using `datasets` where the label names aren't hard-coded. This works find for classification of a handful of labels but ideally there would be... | 29 | Provide ability to load label mappings from file
### Feature request
My task is classification of a dataset containing a large label set that includes a hierarchy. Even ignoring the hierarchy I'm not able to find an example using `datasets` where the label names aren't hard-coded. This works find for classificatio... | [
-0.23057903349399567,
0.43088358640670776,
0.06760111451148987,
0.6072050333023071,
0.2155102789402008,
0.08691208809614182,
0.3997461199760437,
0.3549935221672058,
0.2451525330543518,
0.1859813779592514,
-0.130423441529274,
0.39898958802223206,
-0.254896342754364,
0.10869807749986649,
0... |
https://github.com/huggingface/datasets/issues/6058 | laion-coco download error | This can also mean one of the files was not downloaded correctly.
We log an erroneous file's name before raising the reader's error, so this is how you can find the problematic file. Then, you should delete it and call `load_dataset` again.
(I checked all the uploaded files, and they seem to be valid Parquet file... | ### Describe the bug
The full trace:
```
/home/bian/anaconda3/envs/sd/lib/python3.10/site-packages/datasets/load.py:1744: FutureWarning: 'ignore_verifications' was de
precated in favor of 'verification_mode' in version 2.9.1 and will be removed in 3.0.0.
You can remove this warning by passing 'verification_mode=no... | 67 | laion-coco download error
### Describe the bug
The full trace:
```
/home/bian/anaconda3/envs/sd/lib/python3.10/site-packages/datasets/load.py:1744: FutureWarning: 'ignore_verifications' was de
precated in favor of 'verification_mode' in version 2.9.1 and will be removed in 3.0.0.
You can remove this warning by p... | [
-0.15487737953662872,
-0.2053687572479248,
0.004702892154455185,
0.2853047847747803,
0.23897741734981537,
-0.14961348474025726,
-0.010636117309331894,
0.27262720465660095,
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-0.002077333629131317,
-0.06044921278953552,
0.6115537285804749,
-0.06062483787536621,
0.3097845... |
https://github.com/huggingface/datasets/issues/6057 | Why is the speed difference of gen example so big? | Hi!
It's hard to explain this behavior without more information. Can you profile the slower version with the following code
```python
import cProfile, pstats
from datasets import load_dataset
with cProfile.Profile() as profiler:
ds = load_dataset(...)
stats = pstats.Stats(profiler).sort_stats("cumtime"... | ```python
def _generate_examples(self, metadata_path, images_dir, conditioning_images_dir):
with open(metadata_path, 'r') as file:
metadata = json.load(file)
for idx, item in enumerate(metadata):
image_path = item.get('image_path')
text_content = item.get('tex... | 44 | Why is the speed difference of gen example so big?
```python
def _generate_examples(self, metadata_path, images_dir, conditioning_images_dir):
with open(metadata_path, 'r') as file:
metadata = json.load(file)
for idx, item in enumerate(metadata):
image_path = item.get('i... | [
-0.20529842376708984,
-0.3432776629924774,
-0.09249891340732574,
0.23858214914798737,
0.20685581862926483,
0.04926350712776184,
0.2642042636871338,
0.3207882344722748,
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0.2926475405693054,
0.5328459739685059,
0.21491014957427979,
-0.04361525550484657,
0.108022771775722... |
https://github.com/huggingface/datasets/issues/6051 | Skipping shard in the remote repo and resume upload | Hi! `_select_contiguous` fetches a (zero-copy) slice of the dataset's Arrow table to build a shard, so I don't think this part is the problem. To me, the issue seems to be the step where we embed external image files' bytes (a lot of file reads). You can use `.map` with multiprocessing to perform this step before `push... | ### Describe the bug
For some reason when I try to resume the upload of my dataset, it is very slow to reach the index of the shard from which to resume the uploading.
From my understanding, the problem is in this part of the code:
arrow_dataset.py
```python
for index, shard in logging.tqdm(
enume... | 111 | Skipping shard in the remote repo and resume upload
### Describe the bug
For some reason when I try to resume the upload of my dataset, it is very slow to reach the index of the shard from which to resume the uploading.
From my understanding, the problem is in this part of the code:
arrow_dataset.py
```python... | [
-0.3791671097278595,
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0.09748871624469757,
-0.04825696349143982,
0.002400001510977745,
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0.3753836452960968,
0.1487511396408081,
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0.21819643676280975,
0.30581262707710266,
0.3561643660068512,
0.16858717799186707,
-0.1499090194702... |
https://github.com/huggingface/datasets/issues/6051 | Skipping shard in the remote repo and resume upload | Hi, thanks, this solution saves some time.
But can't we avoid embedding all external image files bytes with each push, skipping the images that have already been pushed into the repo?
Edit: Ok I missed the part of cache it manually on the disk the first time, this solves the problem. Thank you | ### Describe the bug
For some reason when I try to resume the upload of my dataset, it is very slow to reach the index of the shard from which to resume the uploading.
From my understanding, the problem is in this part of the code:
arrow_dataset.py
```python
for index, shard in logging.tqdm(
enume... | 53 | Skipping shard in the remote repo and resume upload
### Describe the bug
For some reason when I try to resume the upload of my dataset, it is very slow to reach the index of the shard from which to resume the uploading.
From my understanding, the problem is in this part of the code:
arrow_dataset.py
```python... | [
-0.32499897480010986,
-0.07473821938037872,
0.0636654794216156,
0.04388701170682907,
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0.4119350016117096,
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0.24161304533481598,
0.26046234369277954,
0.25967657566070557,
0.14979690313339233,
-0.140339463949... |
https://github.com/huggingface/datasets/issues/6048 | when i use datasets.load_dataset, i encounter the http connect error! | The `audiofolder` loader is not available in version `2.3.2`, hence the error. Please run the `pip install -U datasets` command to update the `datasets` installation to make `load_dataset("audiofolder", ...)` work. | ### Describe the bug
`common_voice_test = load_dataset("audiofolder", data_dir="./dataset/",cache_dir="./cache",split=datasets.Split.TEST)`
when i run the code above, i got the error as below:
--------------------------------------------
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/... | 30 | when i use datasets.load_dataset, i encounter the http connect error!
### Describe the bug
`common_voice_test = load_dataset("audiofolder", data_dir="./dataset/",cache_dir="./cache",split=datasets.Split.TEST)`
when i run the code above, i got the error as below:
--------------------------------------------
Connec... | [
-0.47941604256629944,
0.13001763820648193,
0.048481207340955734,
0.24561132490634918,
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0.028838932514190674,
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0.16833677887916565,
-0.1597470343... |
https://github.com/huggingface/datasets/issues/6046 | Support proxy and user-agent in fsspec calls | You can reply "#self-assign" to this issue to automatically get assigned to it :)
Let me know if you have any questions or if I can help | Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage_options`.
Though ideally the `HfFileSystem`... | 27 | Support proxy and user-agent in fsspec calls
Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage... | [
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0.343361496925354,
-0.40745311975479126,
0.044297561049461365,
0.27715572714805603,
0.417585521... |
https://github.com/huggingface/datasets/issues/6046 | Support proxy and user-agent in fsspec calls | Actually i am quite new to figure it out how everything goes and done
> You can reply "#self-assign" to this issue to automatically get assigned to it :)
> Let me know if you have any questions or if I can help
when i wrote #self-assign it automatically got converted to some number is it correct or i have done ... | Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage_options`.
Though ideally the `HfFileSystem`... | 80 | Support proxy and user-agent in fsspec calls
Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage... | [
-0.18757739663124084,
-0.25471335649490356,
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0.2528078258037567,
0.4866552352... |
https://github.com/huggingface/datasets/issues/6046 | Support proxy and user-agent in fsspec calls | Ah yea github tries to replace the #self-assign with an issue link. I guess you can try to copy-paste instead to see if it works
Anyway let me assign you manually | Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage_options`.
Though ideally the `HfFileSystem`... | 31 | Support proxy and user-agent in fsspec calls
Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage... | [
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0.2056722790002823,
0.22914643585681915,
0.42696708440780... |
https://github.com/huggingface/datasets/issues/6046 | Support proxy and user-agent in fsspec calls | thanks a lot @lhoestq ! though i have a very lil idea of the issue, i am new. as i said before, but gonna try my best shot to do it.
can you please suggest some tips or anything from your side, how basically we approach it will be really helpfull.
Will try my best! | Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage_options`.
Though ideally the `HfFileSystem`... | 55 | Support proxy and user-agent in fsspec calls
Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage... | [
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0.289785236120224,
-0.40862515568733215,
0.09876830130815506,
0.2533799111843109,
0.43592146039... |
https://github.com/huggingface/datasets/issues/6046 | Support proxy and user-agent in fsspec calls | The HfFileSystem from the `huggingface_hub` package can already read the HTTP_PROXY and HTTPS_PROXY environment variables. So the remaining thing missing is the `user_agent` that the user may include in a `DownloadConfig` object. The user agent can be used for regular http calls but also calls to the HfFileSystem.
-... | Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage_options`.
Though ideally the `HfFileSystem`... | 86 | Support proxy and user-agent in fsspec calls
Since we switched to the new HfFileSystem we no longer apply user's proxy and user-agent.
Using the HTTP_PROXY and HTTPS_PROXY environment variables works though since we use aiohttp to call the HF Hub.
This can be implemented in `_prepare_single_hop_path_and_storage... | [
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-0.016341475769877434,
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0.29788440465927124,
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0.009544987231492996,
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0.4224054217338562,
0.19645920395851135,
-0.5797526240348816,
0.039395201951265335,
0.0445692352950573,
0.56522548... |
https://github.com/huggingface/datasets/issues/6043 | Compression kwargs have no effect when saving datasets as csv | Hello @exs-avianello, I have reproduced the bug successfully and have understood the problem. But I am confused regarding this part of the statement, "`pandas.DataFrame.to_csv` is always called with a buf-like `path_or_buf`".
Can you please elaborate on it?
Thanks! | ### Describe the bug
Attempting to save a dataset as a compressed csv file, the compression kwargs provided to `.to_csv()` that get piped to panda's `pandas.DataFrame.to_csv` do not have any effect - resulting in the dataset not getting compressed.
A warning is raised if explicitly providing a `compression` kwarg, ... | 38 | Compression kwargs have no effect when saving datasets as csv
### Describe the bug
Attempting to save a dataset as a compressed csv file, the compression kwargs provided to `.to_csv()` that get piped to panda's `pandas.DataFrame.to_csv` do not have any effect - resulting in the dataset not getting compressed.
A w... | [
-0.13724297285079956,
0.02748769521713257,
-0.018048088997602463,
-0.14137516915798187,
0.333095908164978,
0.2379491925239563,
0.3183326721191406,
0.37501099705696106,
-0.1385553777217865,
0.20809578895568848,
0.17708706855773926,
0.29512932896614075,
-0.058476269245147705,
-0.053730301558... |
https://github.com/huggingface/datasets/issues/6043 | Compression kwargs have no effect when saving datasets as csv | Hi @aryanxk02 ! Sure, what I actually meant is that when passing a path-like `path_or_buf` here
https://github.com/huggingface/datasets/blob/14f6edd9222e577dccb962ed5338b79b73502fa5/src/datasets/arrow_dataset.py#L4708-L4714
it gets converted to a file object behind the scenes here
https://github.com/huggingfa... | ### Describe the bug
Attempting to save a dataset as a compressed csv file, the compression kwargs provided to `.to_csv()` that get piped to panda's `pandas.DataFrame.to_csv` do not have any effect - resulting in the dataset not getting compressed.
A warning is raised if explicitly providing a `compression` kwarg, ... | 52 | Compression kwargs have no effect when saving datasets as csv
### Describe the bug
Attempting to save a dataset as a compressed csv file, the compression kwargs provided to `.to_csv()` that get piped to panda's `pandas.DataFrame.to_csv` do not have any effect - resulting in the dataset not getting compressed.
A w... | [
-0.13724297285079956,
0.02748769521713257,
-0.018048088997602463,
-0.14137516915798187,
0.333095908164978,
0.2379491925239563,
0.3183326721191406,
0.37501099705696106,
-0.1385553777217865,
0.20809578895568848,
0.17708706855773926,
0.29512932896614075,
-0.058476269245147705,
-0.053730301558... |
https://github.com/huggingface/datasets/issues/6043 | Compression kwargs have no effect when saving datasets as csv | @exs-avianello When `path_or_buf` is set to None, the `to_csv()` method will return the CSV data as a string instead of saving it to a file. Hence the compression doesn't take place. I think setting `path_or_buf=self.path_or_buf` should work. What you say? | ### Describe the bug
Attempting to save a dataset as a compressed csv file, the compression kwargs provided to `.to_csv()` that get piped to panda's `pandas.DataFrame.to_csv` do not have any effect - resulting in the dataset not getting compressed.
A warning is raised if explicitly providing a `compression` kwarg, ... | 40 | Compression kwargs have no effect when saving datasets as csv
### Describe the bug
Attempting to save a dataset as a compressed csv file, the compression kwargs provided to `.to_csv()` that get piped to panda's `pandas.DataFrame.to_csv` do not have any effect - resulting in the dataset not getting compressed.
A w... | [
-0.13724297285079956,
0.02748769521713257,
-0.018048088997602463,
-0.14137516915798187,
0.333095908164978,
0.2379491925239563,
0.3183326721191406,
0.37501099705696106,
-0.1385553777217865,
0.20809578895568848,
0.17708706855773926,
0.29512932896614075,
-0.058476269245147705,
-0.053730301558... |
https://github.com/huggingface/datasets/issues/6038 | File "/home/zhizhou/anaconda3/envs/pytorch/lib/python3.10/site-packages/datasets/builder.py", line 992, in _download_and_prepare if str(split_generator.split_info.name).lower() == "all": AttributeError: 'str' object has no attribute 'split_info'. Did you mean: 'splitlines'? | Instead of writing the loading script, you can use the built-in loader to [load JSON files](https://huggingface.co/docs/datasets/loading#json):
```python
from datasets import load_dataset
ds = load_dataset("json", data_files={"train": os.path.join(data_dir["train"]), "dev": os.path.join(data_dir["dev"])})
``` | Hi, I use the code below to load local file
```
def _split_generators(self, dl_manager):
# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
# If several configurations are possible (listed in BUILDER_CONFIGS), the configurati... | 29 | File "/home/zhizhou/anaconda3/envs/pytorch/lib/python3.10/site-packages/datasets/builder.py", line 992, in _download_and_prepare if str(split_generator.split_info.name).lower() == "all": AttributeError: 'str' object has no attribute 'split_info'. Did you mean: 'splitlines'?
Hi, I use the code below to load loca... | [
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0.14907023310661316,
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0.40986794233322144,
0.32805049419403076,
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0.43193957209587097,
0.4054521322250366,
0.09521950781345367,
0.30330950021743774,
0.20488519966602325,
0.14702971279621124,
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0.17259991168975... |
https://github.com/huggingface/datasets/issues/6037 | Documentation links to examples are broken | These docs are outdated (version 1.2.1 is over two years old). Please refer to [this](https://huggingface.co/docs/datasets/dataset_script) version instead.
Initially, we hosted datasets in this repo, but now you can find them [on the HF Hub](https://huggingface.co/datasets) (e.g. the [`ag_news`](https://huggingface.... | ### Describe the bug
The links at the bottom of [add_dataset](https://huggingface.co/docs/datasets/v1.2.1/add_dataset.html) to examples of specific datasets are all broken, for example
- text classification: [ag_news](https://github.com/huggingface/datasets/blob/master/datasets/ag_news/ag_news.py) (original data ... | 38 | Documentation links to examples are broken
### Describe the bug
The links at the bottom of [add_dataset](https://huggingface.co/docs/datasets/v1.2.1/add_dataset.html) to examples of specific datasets are all broken, for example
- text classification: [ag_news](https://github.com/huggingface/datasets/blob/master... | [
0.023814212530851364,
-0.09865827113389969,
0.03794043883681297,
0.19491174817085266,
0.12027594447135925,
0.12439770251512527,
0.19488351047039032,
0.2199343889951706,
0.011479754000902176,
0.05286344140768051,
-0.055786848068237305,
0.08662964403629303,
-0.07946711778640747,
0.1870860159... |
https://github.com/huggingface/datasets/issues/6034 | load_dataset hangs on WSL | Even if a dataset is cached, we still make requests to check whether the cache is up-to-date. [This](https://huggingface.co/docs/datasets/v2.13.1/en/loading#offline) section in the docs explains how to avoid them and directly load the cached version. | ### Describe the bug
load_dataset simply hangs. It happens once every ~5 times, and interestingly hangs for a multiple of 5 minutes (hangs for 5/10/15 minutes). Using the profiler in PyCharm shows that it spends the time at <method 'connect' of '_socket.socket' objects>. However, a local cache is available so I am not... | 33 | load_dataset hangs on WSL
### Describe the bug
load_dataset simply hangs. It happens once every ~5 times, and interestingly hangs for a multiple of 5 minutes (hangs for 5/10/15 minutes). Using the profiler in PyCharm shows that it spends the time at <method 'connect' of '_socket.socket' objects>. However, a local ca... | [
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0.1359594315290451,
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0.5331799983978271,
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0.7224938273429871,
0.03790576756000519,
0.1282070279121399,
0.10376717150211334,
0.30889639258384705,
0.14097093045711517... |
https://github.com/huggingface/datasets/issues/6034 | load_dataset hangs on WSL | Thanks - that works! However it doesn't resolve the original issue (but I am not sure if it is a WSL problem) | ### Describe the bug
load_dataset simply hangs. It happens once every ~5 times, and interestingly hangs for a multiple of 5 minutes (hangs for 5/10/15 minutes). Using the profiler in PyCharm shows that it spends the time at <method 'connect' of '_socket.socket' objects>. However, a local cache is available so I am not... | 22 | load_dataset hangs on WSL
### Describe the bug
load_dataset simply hangs. It happens once every ~5 times, and interestingly hangs for a multiple of 5 minutes (hangs for 5/10/15 minutes). Using the profiler in PyCharm shows that it spends the time at <method 'connect' of '_socket.socket' objects>. However, a local ca... | [
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0.1685941517353058,
0.16317249834537506,
0.2954546809196472,
0.064079701900482... |
https://github.com/huggingface/datasets/issues/6034 | load_dataset hangs on WSL | We use `requests` to make HTTP requests (and `aiohttp` in the streaming mode), so I don't think we can provide much help regarding the socket issue (it probably has something to do with WSL). | ### Describe the bug
load_dataset simply hangs. It happens once every ~5 times, and interestingly hangs for a multiple of 5 minutes (hangs for 5/10/15 minutes). Using the profiler in PyCharm shows that it spends the time at <method 'connect' of '_socket.socket' objects>. However, a local cache is available so I am not... | 34 | load_dataset hangs on WSL
### Describe the bug
load_dataset simply hangs. It happens once every ~5 times, and interestingly hangs for a multiple of 5 minutes (hangs for 5/10/15 minutes). Using the profiler in PyCharm shows that it spends the time at <method 'connect' of '_socket.socket' objects>. However, a local ca... | [
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0.03590309992432594,
0.10654602944850922,
0.2100633829832077,
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0.5049698352813721,
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0.6805390119552612,
0.01739136129617691,
0.11339011043310165,
0.14148923754692078,
0.3411608040332794,
0.0357728973031044,
... |
https://github.com/huggingface/datasets/issues/6032 | DownloadConfig.proxies not work when load_dataset_builder calling HfApi.dataset_info | `HfApi` comes from the `huggingface_hub` package. You can use [this](https://huggingface.co/docs/huggingface_hub/v0.16.3/en/package_reference/utilities#huggingface_hub.configure_http_backend) utility to change the `huggingface_hub`'s `Session` proxies (see the example).
We plan to implement https://github.com/huggin... | ### Describe the bug
```python
download_config = DownloadConfig(proxies={'https': '<my proxy>'})
builder = load_dataset_builder(..., download_config=download_config)
```
But, when getting the dataset_info from HfApi, the http requests not using the proxies.
### Steps to reproduce the bug
1. Setup proxies i... | 32 | DownloadConfig.proxies not work when load_dataset_builder calling HfApi.dataset_info
### Describe the bug
```python
download_config = DownloadConfig(proxies={'https': '<my proxy>'})
builder = load_dataset_builder(..., download_config=download_config)
```
But, when getting the dataset_info from HfApi, the htt... | [
-0.21935895085334778,
-0.31487125158309937,
0.06531679630279541,
0.3223288655281067,
0.29418671131134033,
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0.21879905462265015,
-0.057646024972200394,
-0.08462768793106079,
-0.013216361403465271,
-0.3229539692401886,
-0.06117996200919151,
0.4231877326965332,
0.36726793... |
https://github.com/huggingface/datasets/issues/6032 | DownloadConfig.proxies not work when load_dataset_builder calling HfApi.dataset_info | @mariosasko are you saying if I do the following:
```
def backend_factory() -> requests.Session:
session = requests.Session()
session.proxies = {
"https": "127.0.0.1:8887",
"http": "127.0.0.1:8887",
}
session.verify = "/etc/ssl/certs/ca-certificates.crt"
return session
... | ### Describe the bug
```python
download_config = DownloadConfig(proxies={'https': '<my proxy>'})
builder = load_dataset_builder(..., download_config=download_config)
```
But, when getting the dataset_info from HfApi, the http requests not using the proxies.
### Steps to reproduce the bug
1. Setup proxies i... | 199 | DownloadConfig.proxies not work when load_dataset_builder calling HfApi.dataset_info
### Describe the bug
```python
download_config = DownloadConfig(proxies={'https': '<my proxy>'})
builder = load_dataset_builder(..., download_config=download_config)
```
But, when getting the dataset_info from HfApi, the htt... | [
-0.2879650592803955,
-0.09048698842525482,
0.062012676149606705,
0.2935779094696045,
0.23151029646396637,
-0.19603276252746582,
0.47543320059776306,
-0.017514623701572418,
-0.1941140741109848,
-0.08183430135250092,
-0.21388939023017883,
-0.08288484811782837,
0.509202778339386,
0.1340788006... |
https://github.com/huggingface/datasets/issues/6032 | DownloadConfig.proxies not work when load_dataset_builder calling HfApi.dataset_info | `huggingface_hub.configure_http_backend` works for `transformers` because they only use the `huggingface_hub` lib for downloads. Our download logic is a bit more complex (e.g., we also support downloading non-Hub files), so we are not aligned with them yet. In the meantime, it's best to use the env vars. | ### Describe the bug
```python
download_config = DownloadConfig(proxies={'https': '<my proxy>'})
builder = load_dataset_builder(..., download_config=download_config)
```
But, when getting the dataset_info from HfApi, the http requests not using the proxies.
### Steps to reproduce the bug
1. Setup proxies i... | 46 | DownloadConfig.proxies not work when load_dataset_builder calling HfApi.dataset_info
### Describe the bug
```python
download_config = DownloadConfig(proxies={'https': '<my proxy>'})
builder = load_dataset_builder(..., download_config=download_config)
```
But, when getting the dataset_info from HfApi, the htt... | [
-0.2718684673309326,
-0.31287360191345215,
0.07217483222484589,
0.2777329087257385,
0.28893572092056274,
-0.19712373614311218,
0.2673003077507019,
-0.08293774724006653,
-0.0851227343082428,
-0.01037551462650299,
-0.32631367444992065,
-0.03736462816596031,
0.43747177720069885,
0.34515744447... |
https://github.com/huggingface/datasets/issues/6032 | DownloadConfig.proxies not work when load_dataset_builder calling HfApi.dataset_info | @mariosasko I fully understand that the logic for dataset is different. I see 2 issues with the current implementation of the env variables:
- having the same https_proxy/http_prox/no_proxy env variables for all tools is not good in some case. For example I have 2 differents proxy server. In 2019 we had discussion w... | ### Describe the bug
```python
download_config = DownloadConfig(proxies={'https': '<my proxy>'})
builder = load_dataset_builder(..., download_config=download_config)
```
But, when getting the dataset_info from HfApi, the http requests not using the proxies.
### Steps to reproduce the bug
1. Setup proxies i... | 146 | DownloadConfig.proxies not work when load_dataset_builder calling HfApi.dataset_info
### Describe the bug
```python
download_config = DownloadConfig(proxies={'https': '<my proxy>'})
builder = load_dataset_builder(..., download_config=download_config)
```
But, when getting the dataset_info from HfApi, the htt... | [
-0.2724524140357971,
-0.1954692006111145,
0.027852557599544525,
0.20180076360702515,
0.2376095950603485,
-0.28152039647102356,
0.5187769532203674,
0.05172602832317352,
-0.041373804211616516,
0.06968019902706146,
-0.17300494015216827,
0.11520985513925552,
0.4824943542480469,
0.2368428558111... |
https://github.com/huggingface/datasets/issues/6025 | Using a dataset for a use other than it was intended for. | I've opened a PR with a fix. In the meantime, you can avoid the error by deleting `task_templates` with `dataset.info.task_templates = None` before the `interleave_datasets` call.
` | ### Describe the bug
Hi, I want to use the rotten tomatoes dataset but for a task other than classification, but when I interleave the dataset, it throws ```'ValueError: Column label is not present in features.'```. It seems that the label_col must be there in the dataset for some reason?
Here is the full stacktra... | 27 | Using a dataset for a use other than it was intended for.
### Describe the bug
Hi, I want to use the rotten tomatoes dataset but for a task other than classification, but when I interleave the dataset, it throws ```'ValueError: Column label is not present in features.'```. It seems that the label_col must be there i... | [
0.04401044920086861,
0.1051892638206482,
0.04210076853632927,
0.271170049905777,
0.4153468608856201,
0.40644606947898865,
0.6712467670440674,
0.12305933237075806,
0.37308964133262634,
0.13794007897377014,
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0.2542686462402344,
0.011830683797597885,
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... |
https://github.com/huggingface/datasets/issues/6020 | Inconsistent "The features can't be aligned" error when combining map, multiprocessing, and variable length outputs | This scenario currently requires explicitly passing the target features (to avoid the error):
```python
import datasets
...
features = dataset.features
features["output"] = = [{"test": datasets.Value("int64")}]
test2 = dataset.map(lambda row, idx: test_func(row, idx), with_indices=True, num_proc=32, features... | ### Describe the bug
I'm using a dataset with map and multiprocessing to run a function that returned a variable length list of outputs. This output list may be empty. Normally this is handled fine, but there is an edge case that crops up when using multiprocessing. In some cases, an empty list result ends up in a dat... | 36 | Inconsistent "The features can't be aligned" error when combining map, multiprocessing, and variable length outputs
### Describe the bug
I'm using a dataset with map and multiprocessing to run a function that returned a variable length list of outputs. This output list may be empty. Normally this is handled fine, bu... | [
-0.2229905128479004,
-0.335707426071167,
-0.05927114933729172,
0.1883198320865631,
0.1620415896177292,
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0.4985237121582031,
0.06349752843379974,
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0.07977113127708435,
0.3565216660499573,
0.2385641634464264,
-0.0017630523070693016,
0.279044151306152... |
https://github.com/huggingface/datasets/issues/6020 | Inconsistent "The features can't be aligned" error when combining map, multiprocessing, and variable length outputs | I just encountered the same error in the same situation (multiprocessing with variable length outputs).
The funny (or dangerous?) thing is, that this error only showed up when testing with a small test dataset (16 examples, ValueError with `num_proc` >1) but the same code works fine for the full dataset (~70k exampl... | ### Describe the bug
I'm using a dataset with map and multiprocessing to run a function that returned a variable length list of outputs. This output list may be empty. Normally this is handled fine, but there is an edge case that crops up when using multiprocessing. In some cases, an empty list result ends up in a dat... | 100 | Inconsistent "The features can't be aligned" error when combining map, multiprocessing, and variable length outputs
### Describe the bug
I'm using a dataset with map and multiprocessing to run a function that returned a variable length list of outputs. This output list may be empty. Normally this is handled fine, bu... | [
-0.2229905128479004,
-0.335707426071167,
-0.05927114933729172,
0.1883198320865631,
0.1620415896177292,
-0.1879776120185852,
0.4985237121582031,
0.06349752843379974,
-0.009108362719416618,
0.07977113127708435,
0.3565216660499573,
0.2385641634464264,
-0.0017630523070693016,
0.279044151306152... |
https://github.com/huggingface/datasets/issues/6014 | Request to Share/Update Dataset Viewer Code | Hi ! The huggingface/dataset-viewer code was not maintained anymore because we switched to a new dataset viewer that is deployed available for each dataset the Hugging Face website.
What are you using this old repository for ? |
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of documentation of that attribute.
Request:
I k... | 37 | Request to Share/Update Dataset Viewer Code
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of docu... | [
-0.18576379120349884,
0.04342000186443329,
-0.05034683644771576,
0.34636425971984863,
0.0627560019493103,
0.13257750868797302,
0.10639741271734238,
0.3743211030960083,
-0.06356143951416016,
0.17300695180892944,
-0.2012244313955307,
0.15556076169013977,
-0.08831065893173218,
0.1680247634649... |
https://github.com/huggingface/datasets/issues/6014 | Request to Share/Update Dataset Viewer Code | I think these parts are outdated:
* https://github.com/huggingface/datasets-viewer/blob/8efad8eae313a891f713469983bf4c744786f26e/run.py#L126-L131
* https://github.com/huggingface/datasets-viewer/blob/8efad8eae313a891f713469983bf4c744786f26e/run.py#L145-L150
To make the viewer work, the first one should be replac... |
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of documentation of that attribute.
Request:
I k... | 87 | Request to Share/Update Dataset Viewer Code
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of docu... | [
-0.25805845856666565,
-0.015305012464523315,
-0.02590107172727585,
0.33421534299850464,
0.14130879938602448,
0.17428895831108093,
0.17373082041740417,
0.4034422039985657,
-0.04206863045692444,
0.14834578335285187,
-0.16766896843910217,
0.22764699161052704,
-0.14093898236751556,
0.206836983... |
https://github.com/huggingface/datasets/issues/6014 | Request to Share/Update Dataset Viewer Code | > The dataset viewer on the Hugging Face website is incredibly useful
@mariosasko i think @lilyorlilypad wants to run the new dataset-viewer, not the old one |
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of documentation of that attribute.
Request:
I k... | 26 | Request to Share/Update Dataset Viewer Code
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of docu... | [
-0.27421343326568604,
0.07217858731746674,
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0.3316424489021301,
0.006425380706787109,
0.12299644201993942,
0.10355931520462036,
0.4018329679965973,
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0.2205033302307129,
-0.21188001334667206,
0.2641458809375763,
-0.11946781724691391,
0.2302787750959... |
https://github.com/huggingface/datasets/issues/6014 | Request to Share/Update Dataset Viewer Code | > wants to run the new dataset-viewer, not the old one
Thanks for the clarification for me. I do want to run the new dataset-viewer. |
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of documentation of that attribute.
Request:
I k... | 25 | Request to Share/Update Dataset Viewer Code
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of docu... | [
-0.26142677664756775,
0.04871746897697449,
-0.04760851711034775,
0.3212714195251465,
-0.004702135920524597,
0.13446781039237976,
0.0914936512708664,
0.36667507886886597,
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0.21518801152706146,
-0.21123361587524414,
0.23290039598941803,
-0.1249937191605568,
0.2289770394... |
https://github.com/huggingface/datasets/issues/6014 | Request to Share/Update Dataset Viewer Code | It should be possible to run it locally using the HF datasets-server API (docs [here](https://huggingface.co/docs/datasets-server)) but the front end part is not open source (yet ?)
The back-end is open source though if you're interested: https://github.com/huggingface/datasets-server
It automatically converts data... |
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of documentation of that attribute.
Request:
I k... | 54 | Request to Share/Update Dataset Viewer Code
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of docu... | [
-0.3023461401462555,
-0.039006151258945465,
-0.020467743277549744,
0.2967481017112732,
0.009397780522704124,
0.13059893250465393,
0.0453820675611496,
0.38922399282455444,
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0.1952628195285797,
-0.2966969311237335,
0.22623898088932037,
-0.1591140627861023,
0.38273450732... |
https://github.com/huggingface/datasets/issues/6014 | Request to Share/Update Dataset Viewer Code | the new frontend would probably be hard to open source, as is, as it's quite intertwined with the Hub's code.
However, at some point it would be amazing to have a community-driven open source implementation of a frontend to datasets-server! |
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of documentation of that attribute.
Request:
I k... | 40 | Request to Share/Update Dataset Viewer Code
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of docu... | [
-0.3248501420021057,
-0.059220895171165466,
-0.09017603099346161,
0.27208662033081055,
-0.060776062309741974,
0.03568772226572037,
0.15050993859767914,
0.34016814827919006,
0.12809468805789948,
0.19909483194351196,
-0.3107962906360626,
0.23992475867271423,
-0.18274010717868805,
0.426730453... |
https://github.com/huggingface/datasets/issues/6014 | Request to Share/Update Dataset Viewer Code | For the frontend viewer, see https://github.com/huggingface/datasets/issues/6139.
Also mentioned in https://github.com/huggingface/datasets-server/issues/213 and https://github.com/huggingface/datasets-server/issues/441
Closing as a duplicate of https://github.com/huggingface/datasets/issues/6139 |
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of documentation of that attribute.
Request:
I k... | 18 | Request to Share/Update Dataset Viewer Code
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of docu... | [
-0.23733484745025635,
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0.10088923573493958,
0.34784752130508423,
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0.18915942311286926,
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0.21624311804771423,
-0.1487387865781784,
0.312807381153... |
https://github.com/huggingface/datasets/issues/6013 | [FR] `map` should reuse unchanged columns from the previous dataset to avoid disk usage | You can use the `remove_columns` parameter in `map` to avoid duplicating the columns (and save disk space) and then concatenate the original dataset with the map result:
```python
from datasets import concatenate_datasets
# dummy example
ds_new = ds.map(lambda x: {"new_col": x["col"] + 2}, remove_columns=ds.column_... | ### Feature request
Currently adding a new column with `map` will cause all the data in the dataset to be duplicated and stored/cached on the disk again. It should reuse unchanged columns.
### Motivation
This allows having datasets with different columns but sharing some basic columns. Currently, these datasets wou... | 93 | [FR] `map` should reuse unchanged columns from the previous dataset to avoid disk usage
### Feature request
Currently adding a new column with `map` will cause all the data in the dataset to be duplicated and stored/cached on the disk again. It should reuse unchanged columns.
### Motivation
This allows having dat... | [
-0.2323707789182663,
-0.22844350337982178,
-0.17978732287883759,
0.04431470111012459,
0.08519688248634338,
0.3523919880390167,
0.1729741245508194,
0.528941810131073,
0.36176013946533203,
0.08009155839681625,
-0.21657496690750122,
0.5258408188819885,
0.004911593161523342,
0.1566589176654815... |
https://github.com/huggingface/datasets/issues/6012 | [FR] Transform Chaining, Lazy Mapping | You can use `with_transform` to get a new dataset object.
Support for lazy `map` has already been discussed [here](https://github.com/huggingface/datasets/issues/3385) a little bit. Personally, I'm not a fan, as this would make `map` even more complex. | ### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the dataset is requested.
The API should look ... | 35 | [FR] Transform Chaining, Lazy Mapping
### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the datas... | [
-0.24778230488300323,
-0.4162163734436035,
-0.17038147151470184,
-0.06715802848339081,
-0.0025982558727264404,
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-0.03812460973858833,
0.40684834122657776,
0.2943812906742096,
0.18187548220157623,
-0.06886462867259979,
0.42894870042800903,
-0.22558295726776123,
0.358406... |
https://github.com/huggingface/datasets/issues/6012 | [FR] Transform Chaining, Lazy Mapping | > You can use `with_transform` to get a new dataset object.
>
> Support for lazy `map` has already been discussed [here](https://github.com/huggingface/datasets/issues/3385) a little bit. Personally, I'm not a fan, as this would make `map` even more complex.
I read about IterableDataset, and it seems to have lazy... | ### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the dataset is requested.
The API should look ... | 71 | [FR] Transform Chaining, Lazy Mapping
### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the datas... | [
-0.27461275458335876,
-0.4056375324726105,
-0.1270228624343872,
-0.0834740400314331,
0.027343885973095894,
0.07320728152990341,
-0.0010264180600643158,
0.3469204604625702,
0.15508490800857544,
0.04703850299119949,
-0.1103539764881134,
0.3395669162273407,
-0.2917414605617523,
0.275373160839... |
https://github.com/huggingface/datasets/issues/6012 | [FR] Transform Chaining, Lazy Mapping | > I read about IterableDataset, and it seems to have lazy mapping. But I can't figure out how to convert an IterableDataset into a normal one when needed.
You must cache an `IterableDataset` to disk to load it as a `Dataset`. One way to do this is with `Dataset.from_generator`:
```python
from functools import part... | ### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the dataset is requested.
The API should look ... | 92 | [FR] Transform Chaining, Lazy Mapping
### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the datas... | [
-0.23495735228061676,
-0.32557356357574463,
-0.16109183430671692,
-0.18144196271896362,
0.10616957396268845,
0.13453632593154907,
0.05579795688390732,
0.4533076584339142,
0.008160348981618881,
-0.04647892713546753,
0.01055005844682455,
0.4062657952308655,
-0.383439302444458,
0.171448767185... |
https://github.com/huggingface/datasets/issues/6012 | [FR] Transform Chaining, Lazy Mapping | I wonder if it would be beneficial to have a dedicated method to do that ? Maybe a `.save_to_disk()` so that the user can reload the resulting dataset later ? | ### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the dataset is requested.
The API should look ... | 30 | [FR] Transform Chaining, Lazy Mapping
### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the datas... | [
-0.1378847360610962,
-0.2570561170578003,
-0.16355741024017334,
-0.2913748621940613,
0.0028413981199264526,
0.06371340900659561,
-0.05337003245949745,
0.3641149699687958,
0.09568753838539124,
0.07889712601900101,
0.04469800740480423,
0.5188761353492737,
-0.3693695366382599,
0.1335511803627... |
https://github.com/huggingface/datasets/issues/6012 | [FR] Transform Chaining, Lazy Mapping | > ```python
> from functools import partial
> from datasets import Dataset
>
> def gen_from_iterable_dataset(iterable_ds)
> yield from iterable_ds
>
> ds = Dataset.from_generator(partial(gen_from_iterable_dataset, iterable_ds), features=iterable_ds.features})
> ```
@mariosasko With these complex mappin... | ### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the dataset is requested.
The API should look ... | 44 | [FR] Transform Chaining, Lazy Mapping
### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the datas... | [
-0.006097901612520218,
-0.42071229219436646,
-0.15540745854377747,
-0.06829307973384857,
0.06173672527074814,
0.19080334901809692,
0.02012288197875023,
0.4010327160358429,
0.13905228674411774,
-0.03475162386894226,
0.12666432559490204,
0.21405458450317383,
-0.3584165871143341,
0.1618133783... |
https://github.com/huggingface/datasets/issues/6012 | [FR] Transform Chaining, Lazy Mapping | The params passed to `Dataset.from_generator` will be used to compute the hash (`partial` encapsulates the `iterable_ds` value, so changing it will also change the hash) | ### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the dataset is requested.
The API should look ... | 25 | [FR] Transform Chaining, Lazy Mapping
### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the datas... | [
-0.2502358555793762,
-0.2847062349319458,
-0.1987450122833252,
-0.03752274811267853,
0.08460214734077454,
-0.01908019930124283,
0.06320126354694366,
0.40587395429611206,
0.15362338721752167,
0.22613492608070374,
0.16613809764385223,
0.45469486713409424,
-0.36086052656173706,
0.225989475846... |
https://github.com/huggingface/datasets/issues/6012 | [FR] Transform Chaining, Lazy Mapping | Hi, I think this feature would be very useful. I want to concatenate large datasets with heterogeneous columns. I dislike `map` since I don't want multiple copy of that datasets locally. I tried to use "set_transform" on each dataset to convert it to a standard features format, but `datasets.concatenate_datasets` ignor... | ### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the dataset is requested.
The API should look ... | 74 | [FR] Transform Chaining, Lazy Mapping
### Feature request
Currently using a `map` call processes and duplicates the whole dataset, which takes both time and disk space.
The solution is to allow lazy mapping, which is essentially a saved chain of transforms that are applied on the fly whenever a slice of the datas... | [
-0.44856005907058716,
-0.21093851327896118,
0.009915970265865326,
-0.20319347083568573,
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0.23192811012268066,
0.18682855367660522,
0.45677390694618225,
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-0.2656952142715454,
0.27904820442199707,
-0.0351531021296978,
0.08542140... |
https://github.com/huggingface/datasets/issues/6011 | Documentation: wiki_dpr Dataset has no metric_type for Faiss Index | Hi! You can do `ds.get_index("embeddings").faiss_index.metric_type` to get the metric type and then match the result with the FAISS metric [enum](https://github.com/facebookresearch/faiss/blob/43d86e30736ede853c384b24667fc3ab897d6ba9/faiss/MetricType.h#L22-L36) (should be L2). | ### Describe the bug
After loading `wiki_dpr` using:
```py
ds = load_dataset(path='wiki_dpr', name='psgs_w100.multiset.compressed', split='train')
print(ds.get_index("embeddings").metric_type) # prints nothing because the value is None
```
the index does not have a defined `metric_type`. This is an issue because ... | 23 | Documentation: wiki_dpr Dataset has no metric_type for Faiss Index
### Describe the bug
After loading `wiki_dpr` using:
```py
ds = load_dataset(path='wiki_dpr', name='psgs_w100.multiset.compressed', split='train')
print(ds.get_index("embeddings").metric_type) # prints nothing because the value is None
```
the i... | [
-0.36273178458213806,
-0.5373350381851196,
0.06526792049407959,
0.3944724202156067,
0.3347804546356201,
0.13995018601417542,
0.3388691544532776,
0.33496665954589844,
0.38180679082870483,
0.3302499055862427,
0.13445782661437988,
0.2328336238861084,
0.18522213399410248,
-0.1447066217660904,
... |
https://github.com/huggingface/datasets/issues/6011 | Documentation: wiki_dpr Dataset has no metric_type for Faiss Index | Ah! Thank you for pointing this out. FYI: the enum indicates it's using the inner product. Using `torch.inner` or `torch.dot` still produces a discrepancy compared to the built-in score. I think this is because of the compression/quantization that occurs with the FAISS index. | ### Describe the bug
After loading `wiki_dpr` using:
```py
ds = load_dataset(path='wiki_dpr', name='psgs_w100.multiset.compressed', split='train')
print(ds.get_index("embeddings").metric_type) # prints nothing because the value is None
```
the index does not have a defined `metric_type`. This is an issue because ... | 43 | Documentation: wiki_dpr Dataset has no metric_type for Faiss Index
### Describe the bug
After loading `wiki_dpr` using:
```py
ds = load_dataset(path='wiki_dpr', name='psgs_w100.multiset.compressed', split='train')
print(ds.get_index("embeddings").metric_type) # prints nothing because the value is None
```
the i... | [
-0.36273178458213806,
-0.5373350381851196,
0.06526792049407959,
0.3944724202156067,
0.3347804546356201,
0.13995018601417542,
0.3388691544532776,
0.33496665954589844,
0.38180679082870483,
0.3302499055862427,
0.13445782661437988,
0.2328336238861084,
0.18522213399410248,
-0.1447066217660904,
... |
https://github.com/huggingface/datasets/issues/6010 | Improve `Dataset`'s string representation | Yes, feel free to work on this.
You can check the PyArrow Table `__repr__` and Polars DataFrame `__repr__`/`_repr_html_` implementations for some pointers/ideas. | Currently, `Dataset.__repr__` outputs a dataset's column names and the number of rows. We could improve it by printing its features and the first few rows.
We should also implement `_repr_html_` to have a rich HTML representation in notebooks/Streamlit. | 22 | Improve `Dataset`'s string representation
Currently, `Dataset.__repr__` outputs a dataset's column names and the number of rows. We could improve it by printing its features and the first few rows.
We should also implement `_repr_html_` to have a rich HTML representation in notebooks/Streamlit.
Yes, feel free to... | [
-0.26115238666534424,
-0.06325656175613403,
-0.13544955849647522,
0.18778547644615173,
0.4518064856529236,
0.0696428045630455,
0.07831285893917084,
0.4281676113605499,
-0.25408488512039185,
0.0606195405125618,
-0.212770015001297,
0.42051488161087036,
0.17750640213489532,
0.2843798995018005... |
https://github.com/huggingface/datasets/issues/6010 | Improve `Dataset`'s string representation | @mariosasko are there any other similar issues that I could work on? I see this has been already solved. | Currently, `Dataset.__repr__` outputs a dataset's column names and the number of rows. We could improve it by printing its features and the first few rows.
We should also implement `_repr_html_` to have a rich HTML representation in notebooks/Streamlit. | 19 | Improve `Dataset`'s string representation
Currently, `Dataset.__repr__` outputs a dataset's column names and the number of rows. We could improve it by printing its features and the first few rows.
We should also implement `_repr_html_` to have a rich HTML representation in notebooks/Streamlit.
@mariosasko are t... | [
-0.24637500941753387,
-0.0939534604549408,
-0.15906314551830292,
0.2803182601928711,
0.4878693222999573,
0.09331364184617996,
0.081155925989151,
0.46818289160728455,
-0.20165389776229858,
0.05637352168560028,
0.0302964448928833,
0.23728081583976746,
0.06472806632518768,
0.32773154973983765... |
https://github.com/huggingface/datasets/issues/6008 | Dataset.from_generator consistently freezes at ~1000 rows | By default, we write data to disk (so it can be memory-mapped) every 1000 rows/samples. You can control this with the `writer_batch_size` parameter. Also, when working with fixed-size arrays, the `ArrayXD` feature types yield better performance (e.g., in your case, `features=datasets.Features({"i": datasets.Array3D(sha... | ### Describe the bug
Whenever I try to create a dataset which contains images using `Dataset.from_generator`, it freezes around 996 rows. I suppose it has something to do with memory consumption, but there's more memory available. I
Somehow it worked a few times but mostly this makes the datasets library much more ... | 64 | Dataset.from_generator consistently freezes at ~1000 rows
### Describe the bug
Whenever I try to create a dataset which contains images using `Dataset.from_generator`, it freezes around 996 rows. I suppose it has something to do with memory consumption, but there's more memory available. I
Somehow it worked a few... | [
-0.2339242845773697,
0.08639436960220337,
-0.02167588099837303,
0.5308255553245544,
0.2555151581764221,
0.06502681225538254,
0.182708278298378,
0.12610264122486115,
0.018689483404159546,
0.1380024403333664,
0.36856281757354736,
0.07000739127397537,
-0.11341311782598495,
-0.0435231775045394... |
https://github.com/huggingface/datasets/issues/6008 | Dataset.from_generator consistently freezes at ~1000 rows | > By default, we write data to disk (so it can be memory-mapped) every 1000 rows/samples. You can control this with the `writer_batch_size` parameter. Also, when working with fixed-size arrays, the `ArrayXD` feature types yield better performance (e.g., in your case, `features=datasets.Features({"i": datasets.Array3D(s... | ### Describe the bug
Whenever I try to create a dataset which contains images using `Dataset.from_generator`, it freezes around 996 rows. I suppose it has something to do with memory consumption, but there's more memory available. I
Somehow it worked a few times but mostly this makes the datasets library much more ... | 101 | Dataset.from_generator consistently freezes at ~1000 rows
### Describe the bug
Whenever I try to create a dataset which contains images using `Dataset.from_generator`, it freezes around 996 rows. I suppose it has something to do with memory consumption, but there's more memory available. I
Somehow it worked a few... | [
-0.2846595048904419,
0.239802747964859,
-0.03189597651362419,
0.5401877164840698,
0.27455562353134155,
0.07768196612596512,
0.22943243384361267,
0.1456352174282074,
-0.06428156048059464,
0.14791373908519745,
0.4732198119163513,
0.16201145946979523,
-0.09623213112354279,
-0.1689427495002746... |
https://github.com/huggingface/datasets/issues/6007 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset | This error means that one of the int32 (`Value("int32")`) columns in the dataset has a value that is out of the valid (int32) range.
I'll open a PR to print the name of a problematic column to make debugging such errors easier. | ### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encountered the error: "OverflowError: Python int too large to convert to C long"
The error look something like... | 42 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset
### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encounter... | [
-0.42730045318603516,
-0.3950994908809662,
-0.02665611356496811,
0.3553202748298645,
0.3509588837623596,
-0.004374183714389801,
0.10522277653217316,
0.331129789352417,
0.31195196509361267,
0.1922844648361206,
-0.027331490069627762,
0.16219580173492432,
-0.11134413629770279,
0.0895871296525... |
https://github.com/huggingface/datasets/issues/6007 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset | I am afraid int32 is not the reason for this error.
I have submitted a commit to use int64 for all ints in the dataset:
https://huggingface.co/datasets/liwu/MNBVC/commit/857ac00d9eab96a6708ad6a82bd9001686042a9e
and I have updated my env to the latest datasets release:
Copy-and-paste the text below in your GitHu... | ### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encountered the error: "OverflowError: Python int too large to convert to C long"
The error look something like... | 763 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset
### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encounter... | [
-0.42730045318603516,
-0.3950994908809662,
-0.02665611356496811,
0.3553202748298645,
0.3509588837623596,
-0.004374183714389801,
0.10522277653217316,
0.331129789352417,
0.31195196509361267,
0.1922844648361206,
-0.027331490069627762,
0.16219580173492432,
-0.11134413629770279,
0.0895871296525... |
https://github.com/huggingface/datasets/issues/6007 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset | `simhash` is the problematic column - it has values such as `18329103420363166823` that are out of the int64 range. You can fix this by setting the feature type to `Value("string")` (it's advised to use this type for hash values in general)
> Besides, it works fine when I am using streamed dataset.
Streaming yiel... | ### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encountered the error: "OverflowError: Python int too large to convert to C long"
The error look something like... | 75 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset
### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encounter... | [
-0.42730045318603516,
-0.3950994908809662,
-0.02665611356496811,
0.3553202748298645,
0.3509588837623596,
-0.004374183714389801,
0.10522277653217316,
0.331129789352417,
0.31195196509361267,
0.1922844648361206,
-0.027331490069627762,
0.16219580173492432,
-0.11134413629770279,
0.0895871296525... |
https://github.com/huggingface/datasets/issues/6007 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset | i am using uint64 for simhash
uint64 ranges up to about 3.69E19.
18329103420363166823 is less than this value.
moreover, our simhash algorithm use 64 bits. it should fit in uint64.
| ### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encountered the error: "OverflowError: Python int too large to convert to C long"
The error look something like... | 30 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset
### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encounter... | [
-0.42730045318603516,
-0.3950994908809662,
-0.02665611356496811,
0.3553202748298645,
0.3509588837623596,
-0.004374183714389801,
0.10522277653217316,
0.331129789352417,
0.31195196509361267,
0.1922844648361206,
-0.027331490069627762,
0.16219580173492432,
-0.11134413629770279,
0.0895871296525... |
https://github.com/huggingface/datasets/issues/6007 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset | You are right. I overlooked the feature type.
This is a reproducer:
```python
import pyarrow as pa
from datasets.arrow_writer import TypedSequence
pa.array(TypedSequence([18329103420363166823], type=Value("uint64")))
```
`pa.array([18329103420363166823])` also fails with the same error, so it seems PyArrow... | ### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encountered the error: "OverflowError: Python int too large to convert to C long"
The error look something like... | 114 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset
### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encounter... | [
-0.42730045318603516,
-0.3950994908809662,
-0.02665611356496811,
0.3553202748298645,
0.3509588837623596,
-0.004374183714389801,
0.10522277653217316,
0.331129789352417,
0.31195196509361267,
0.1922844648361206,
-0.027331490069627762,
0.16219580173492432,
-0.11134413629770279,
0.0895871296525... |
https://github.com/huggingface/datasets/issues/6007 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset | Thank you for checking this issue in detail.
However, it seems that using `np.uint64(simhash)` does not work. The same issue still exists.
https://huggingface.co/datasets/liwu/MNBVC/commit/1e44f1e400b7e61052647d44c99cdae3bae9c830
Anyway, we decide to use string type for these simhash values. Hope pyarrow can f... | ### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encountered the error: "OverflowError: Python int too large to convert to C long"
The error look something like... | 41 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset
### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encounter... | [
-0.42730045318603516,
-0.3950994908809662,
-0.02665611356496811,
0.3553202748298645,
0.3509588837623596,
-0.004374183714389801,
0.10522277653217316,
0.331129789352417,
0.31195196509361267,
0.1922844648361206,
-0.027331490069627762,
0.16219580173492432,
-0.11134413629770279,
0.0895871296525... |
https://github.com/huggingface/datasets/issues/6007 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset | May be something read your training data line by line.
Then your training data just only one line.
It is so large.
I guess.
| ### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encountered the error: "OverflowError: Python int too large to convert to C long"
The error look something like... | 24 | Get an error "OverflowError: Python int too large to convert to C long" when loading a large dataset
### Describe the bug
When load a large dataset with the following code
```python
from datasets import load_dataset
dataset = load_dataset("liwu/MNBVC", 'news_peoples_daily', split='train')
```
We encounter... | [
-0.42730045318603516,
-0.3950994908809662,
-0.02665611356496811,
0.3553202748298645,
0.3509588837623596,
-0.004374183714389801,
0.10522277653217316,
0.331129789352417,
0.31195196509361267,
0.1922844648361206,
-0.027331490069627762,
0.16219580173492432,
-0.11134413629770279,
0.0895871296525... |
https://github.com/huggingface/datasets/issues/5997 | extend the map function so it can wrap around long text that does not fit in the context window | I just noticed the [docs](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L2881C11-L2881C200) say:
>If batched is `True` and `batch_size` is `n > 1`, then the function takes a batch of `n` examples as input and can return a batch with `n` examples, or with an arbitrary number of examp... | ### Feature request
I understand `dataset` provides a [`map`](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L2849) function. This function in turn takes in a callable that is used to tokenize the text on which a model is trained. Frequently this text will not fit within a models's con... | 49 | extend the map function so it can wrap around long text that does not fit in the context window
### Feature request
I understand `dataset` provides a [`map`](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L2849) function. This function in turn takes in a callable that is used to toke... | [
-0.3404633402824402,
0.035428255796432495,
-0.08898572623729706,
0.043310217559337616,
0.17575743794441223,
-0.049312230199575424,
0.30036666989326477,
0.36894625425338745,
-0.09006552398204803,
-0.17397652566432953,
0.09924719482660294,
0.5054343342781067,
-0.03185432031750679,
0.32149383... |
https://github.com/huggingface/datasets/issues/5997 | extend the map function so it can wrap around long text that does not fit in the context window | All the values in a batch must be of the same length. So one solution is dropping all the input columns:
```python
data = data.map(lambda samples: tokenizer(samples["text"], max_length=tokenizer.model_max_length, truncation=True, stride=4, return_overflowing_tokens=True), batched=True, remove_columns=data.column_name... | ### Feature request
I understand `dataset` provides a [`map`](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L2849) function. This function in turn takes in a callable that is used to tokenize the text on which a model is trained. Frequently this text will not fit within a models's con... | 46 | extend the map function so it can wrap around long text that does not fit in the context window
### Feature request
I understand `dataset` provides a [`map`](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L2849) function. This function in turn takes in a callable that is used to toke... | [
-0.3404633402824402,
0.035428255796432495,
-0.08898572623729706,
0.043310217559337616,
0.17575743794441223,
-0.049312230199575424,
0.30036666989326477,
0.36894625425338745,
-0.09006552398204803,
-0.17397652566432953,
0.09924719482660294,
0.5054343342781067,
-0.03185432031750679,
0.32149383... |
https://github.com/huggingface/datasets/issues/5993 | ValueError: Table schema does not match schema used to create file | We'll do a new release of `datasets` soon to make the fix available :)
In the meantime you can use `datasets` from source (main) | ### Describe the bug
Saving a dataset as parquet fails with a `ValueError: Table schema does not match schema used to create file` if the dataset was obtained out of a `.select_columns()` call with columns selected out of order.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset... | 24 | ValueError: Table schema does not match schema used to create file
### Describe the bug
Saving a dataset as parquet fails with a `ValueError: Table schema does not match schema used to create file` if the dataset was obtained out of a `.select_columns()` call with columns selected out of order.
### Steps to reprod... | [
-0.2826022505760193,
-0.036040544509887695,
0.04691923037171364,
0.3035893440246582,
0.12757623195648193,
0.07862845808267593,
-0.09735161066055298,
0.29069283604621887,
0.07794839143753052,
0.22120481729507446,
0.3267451524734497,
0.6393990516662598,
-0.09413168579339981,
0.41772845387458... |
https://github.com/huggingface/datasets/issues/5989 | Set a rule on the config and split names | in this case we need to decide what to do with the existing datasets with white space characters (there shouldn't be a lot of them I think) | > should we actually allow characters like spaces? maybe it's better to add validation for whitespace symbols and directly in datasets and raise
https://github.com/huggingface/datasets-server/issues/853
| 27 | Set a rule on the config and split names
> should we actually allow characters like spaces? maybe it's better to add validation for whitespace symbols and directly in datasets and raise
https://github.com/huggingface/datasets-server/issues/853
in this case we need to decide what to do with the existing dataset... | [
-0.059814613312482834,
-0.041503727436065674,
-0.08315175771713257,
0.05934183672070503,
0.19995617866516113,
-0.1714780628681183,
0.4647015929222107,
0.13817772269248962,
0.13507820665836334,
0.22843343019485474,
-0.12750552594661713,
-0.20322945713996887,
-0.012206715531647205,
0.4376854... |
https://github.com/huggingface/datasets/issues/5988 | ConnectionError: Couldn't reach dataset_infos.json | Unfortunately, I can't reproduce the error. What does the following code return for you?
```python
import requests
from huggingface_hub import hf_hub_url
r = requests.get(hf_hub_url("codeparrot/codeparrot-clean-train", "dataset_infos.json", repo_type="dataset"))
```
Also, can you provide more info about your ne... | ### Describe the bug
I'm trying to load codeparrot/codeparrot-clean-train, but get the following error:
ConnectionError: Couldn't reach https://huggingface.co/datasets/codeparrot/codeparrot-clean-train/resolve/main/dataset_infos.json (ConnectionError(ProtocolError('Connection aborted.', ConnectionResetError(104, 'C... | 39 | ConnectionError: Couldn't reach dataset_infos.json
### Describe the bug
I'm trying to load codeparrot/codeparrot-clean-train, but get the following error:
ConnectionError: Couldn't reach https://huggingface.co/datasets/codeparrot/codeparrot-clean-train/resolve/main/dataset_infos.json (ConnectionError(ProtocolErr... | [
-0.3649469316005707,
-0.220248743891716,
-0.050982750952243805,
0.3098018765449524,
0.1473006308078766,
-0.14014975726604462,
-0.03622337803244591,
0.34880319237709045,
0.2515791952610016,
0.1794556826353073,
-0.2331954687833786,
0.24075721204280853,
0.3046640455722809,
0.2398938089609146,... |
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