html_url stringlengths 51 51 | title stringlengths 6 280 | comments stringlengths 67 24.7k | body stringlengths 51 36.2k | __index_level_0__ int64 1 1.17k | comment_length int64 16 1.45k | text stringlengths 190 38.3k | embeddings list |
|---|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/5946 | IndexError Not Solving -> IndexError: Invalid key: ?? is out of bounds for size 0 or ?? | > Looks related to https://discuss.huggingface.co/t/indexerror-invalid-key-16-is-out-of-bounds-for-size-0/14298/4?u=lhoestq
The problem has not been solved, I have tried this before, but the problem is the same | ### Describe the bug
in <cell line: 1>:1 │
│ │
│ /usr/local/lib/python3.10/dist-packages/transformers/trainer.py:1537 in train ... | 102 | 22 | IndexError Not Solving -> IndexError: Invalid key: ?? is out of bounds for size 0 or ??
### Describe the bug
in <cell line: 1>:1 │
│ │
│ /usr... | [
-1.0899585485458374,
-0.6860926747322083,
-0.3947448432445526,
1.7805007696151733,
-0.10308399051427841,
-1.1954777240753174,
0.2851788103580475,
-1.0154169797897339,
1.3759500980377197,
-0.6906192302703857,
0.2353612333536148,
-1.5166146755218506,
0.45380547642707825,
-0.43396854400634766... |
https://github.com/huggingface/datasets/issues/5946 | IndexError Not Solving -> IndexError: Invalid key: ?? is out of bounds for size 0 or ?? | data = data["train"].shuffle().map(generate_and_tokenize_prompt, batched = False) # change this line to -
data["train"] = data["train"].shuffle().map(generate_and_tokenize_prompt, batched = False)
After doing this change you code should run fine. | ### Describe the bug
in <cell line: 1>:1 │
│ │
│ /usr/local/lib/python3.10/dist-packages/transformers/trainer.py:1537 in train ... | 102 | 27 | IndexError Not Solving -> IndexError: Invalid key: ?? is out of bounds for size 0 or ??
### Describe the bug
in <cell line: 1>:1 │
│ │
│ /usr... | [
-1.0899585485458374,
-0.6860926747322083,
-0.3947448432445526,
1.7805007696151733,
-0.10308399051427841,
-1.1954777240753174,
0.2851788103580475,
-1.0154169797897339,
1.3759500980377197,
-0.6906192302703857,
0.2353612333536148,
-1.5166146755218506,
0.45380547642707825,
-0.43396854400634766... |
https://github.com/huggingface/datasets/issues/5946 | IndexError Not Solving -> IndexError: Invalid key: ?? is out of bounds for size 0 or ?? | > >
>
> @syngokhan did u solve it? I am desperate
refer to my earlier comment. you will find the solution. | ### Describe the bug
in <cell line: 1>:1 │
│ │
│ /usr/local/lib/python3.10/dist-packages/transformers/trainer.py:1537 in train ... | 102 | 22 | IndexError Not Solving -> IndexError: Invalid key: ?? is out of bounds for size 0 or ??
### Describe the bug
in <cell line: 1>:1 │
│ │
│ /usr... | [
-1.0899585485458374,
-0.6860926747322083,
-0.3947448432445526,
1.7805007696151733,
-0.10308399051427841,
-1.1954777240753174,
0.2851788103580475,
-1.0154169797897339,
1.3759500980377197,
-0.6906192302703857,
0.2353612333536148,
-1.5166146755218506,
0.45380547642707825,
-0.43396854400634766... |
https://github.com/huggingface/datasets/issues/5945 | Failing to upload dataset to the hub | Hi ! Feel free to re-run your code later, it will resume automatically where you left | ### Describe the bug
Trying to upload a dataset of hundreds of thousands of audio samples (the total volume is not very large, 60 gb) to the hub with push_to_hub, it doesn't work.
From time to time one piece of the data (parquet) gets pushed and then I get RemoteDisconnected even though my internet is stable.
Please... | 103 | 16 | Failing to upload dataset to the hub
### Describe the bug
Trying to upload a dataset of hundreds of thousands of audio samples (the total volume is not very large, 60 gb) to the hub with push_to_hub, it doesn't work.
From time to time one piece of the data (parquet) gets pushed and then I get RemoteDisconnected eve... | [
-1.1463006734848022,
-0.9852508902549744,
-0.9576606154441833,
1.5194764137268066,
-0.22411711513996124,
-1.3026936054229736,
0.07107631117105484,
-1.0489076375961304,
1.5510239601135254,
-0.8261783123016357,
0.3836766481399536,
-1.6459275484085083,
0.04675637185573578,
-0.5636143088340759... |
https://github.com/huggingface/datasets/issues/5945 | Failing to upload dataset to the hub | Alternatively you can save your dataset in parquet files locally and upload them to the hub manually
```python
from tqdm import tqdm
num_shards = 60
for index in tqdm(range(num_shards)):
ds.shard(num_shards=num_shards, index=index, contiguous=True).to_parquet(f"{index:05d}.parquet")
```` | ### Describe the bug
Trying to upload a dataset of hundreds of thousands of audio samples (the total volume is not very large, 60 gb) to the hub with push_to_hub, it doesn't work.
From time to time one piece of the data (parquet) gets pushed and then I get RemoteDisconnected even though my internet is stable.
Please... | 103 | 33 | Failing to upload dataset to the hub
### Describe the bug
Trying to upload a dataset of hundreds of thousands of audio samples (the total volume is not very large, 60 gb) to the hub with push_to_hub, it doesn't work.
From time to time one piece of the data (parquet) gets pushed and then I get RemoteDisconnected eve... | [
-1.177137017250061,
-1.0190166234970093,
-0.8515946269035339,
1.5512192249298096,
-0.15509049594402313,
-1.2829962968826294,
0.11301140487194061,
-1.0518345832824707,
1.5453767776489258,
-0.8601767420768738,
0.4678318500518799,
-1.6691434383392334,
0.08537034690380096,
-0.6075124144554138,... |
https://github.com/huggingface/datasets/issues/5941 | Load Data Sets Too Slow In Train Seq2seq Model | already did，but not useful for step Generating train split，it works in step "Resolving data files" & "Downloading data files" | ### Describe the bug
step 'Generating train split' in load_dataset is too slow：
### Steps to reproduce the bug
Data： own data，16K16B Mono wav
Oficial Script:[ run_speech_recognition_seq2seq.py](https://github... | 104 | 19 | Load Data Sets Too Slow In Train Seq2seq Model
### Describe the bug
step 'Generating train split' in load_dataset is too slow：
### Steps to reproduce the bug
Data： own data，16K16B Mono wav
Oficial Script:[ ... | [
-1.2872120141983032,
-0.934897780418396,
-0.618711531162262,
1.4699480533599854,
-0.1538279503583908,
-1.258852481842041,
0.13311150670051575,
-0.9876823425292969,
1.557150959968567,
-0.7559544444084167,
0.30356916785240173,
-1.6126487255096436,
-0.007835671305656433,
-0.5946030616760254,
... |
https://github.com/huggingface/datasets/issues/5941 | Load Data Sets Too Slow In Train Seq2seq Model | We need more info about the issue to provide help.
Can you interrupt the process (with `num_proc=None`) after the `load_dataset` call when the slowdown occurs? So we can know what part of the code is causing it.
The `audiofolder` \ `imagefolder` with metadata is not performant for large datasets. Luckily, we can... | ### Describe the bug
step 'Generating train split' in load_dataset is too slow：
### Steps to reproduce the bug
Data： own data，16K16B Mono wav
Oficial Script:[ run_speech_recognition_seq2seq.py](https://github... | 104 | 101 | Load Data Sets Too Slow In Train Seq2seq Model
### Describe the bug
step 'Generating train split' in load_dataset is too slow：
### Steps to reproduce the bug
Data： own data，16K16B Mono wav
Oficial Script:[ ... | [
-1.2872120141983032,
-0.934897780418396,
-0.618711531162262,
1.4699480533599854,
-0.1538279503583908,
-1.258852481842041,
0.13311150670051575,
-0.9876823425292969,
1.557150959968567,
-0.7559544444084167,
0.30356916785240173,
-1.6126487255096436,
-0.007835671305656433,
-0.5946030616760254,
... |
https://github.com/huggingface/datasets/issues/5941 | Load Data Sets Too Slow In Train Seq2seq Model | Can you interrupt the process (with num_proc=None) after the load_dataset call when the slowdown occurs? So we can know what part of the code is causing it.
（I'll try this operation）
The audiofolder \ imagefolder with metadata is not performant for large datasets. Luckily, we can make them much faster if drop the nes... | ### Describe the bug
step 'Generating train split' in load_dataset is too slow：
### Steps to reproduce the bug
Data： own data，16K16B Mono wav
Oficial Script:[ run_speech_recognition_seq2seq.py](https://github... | 104 | 140 | Load Data Sets Too Slow In Train Seq2seq Model
### Describe the bug
step 'Generating train split' in load_dataset is too slow：
### Steps to reproduce the bug
Data： own data，16K16B Mono wav
Oficial Script:[ ... | [
-1.2872120141983032,
-0.934897780418396,
-0.618711531162262,
1.4699480533599854,
-0.1538279503583908,
-1.258852481842041,
0.13311150670051575,
-0.9876823425292969,
1.557150959968567,
-0.7559544444084167,
0.30356916785240173,
-1.6126487255096436,
-0.007835671305656433,
-0.5946030616760254,
... |
https://github.com/huggingface/datasets/issues/5941 | Load Data Sets Too Slow In Train Seq2seq Model | Can you interrupt the process (with num_proc=None) after the load_dataset call when the slowdown occurs? So we can know what part of the code is causing it.
================================================================================
Here is the log：
[load_dataset.log](https://github.com/huggingface/datasets/fil... | ### Describe the bug
step 'Generating train split' in load_dataset is too slow：
### Steps to reproduce the bug
Data： own data，16K16B Mono wav
Oficial Script:[ run_speech_recognition_seq2seq.py](https://github... | 104 | 43 | Load Data Sets Too Slow In Train Seq2seq Model
### Describe the bug
step 'Generating train split' in load_dataset is too slow：
### Steps to reproduce the bug
Data： own data，16K16B Mono wav
Oficial Script:[ ... | [
-1.2872120141983032,
-0.934897780418396,
-0.618711531162262,
1.4699480533599854,
-0.1538279503583908,
-1.258852481842041,
0.13311150670051575,
-0.9876823425292969,
1.557150959968567,
-0.7559544444084167,
0.30356916785240173,
-1.6126487255096436,
-0.007835671305656433,
-0.5946030616760254,
... |
https://github.com/huggingface/datasets/issues/5941 | Load Data Sets Too Slow In Train Seq2seq Model | In the meantime, it's better to use Dataset.from_generator (requires replacing the load_dataset calls in the transformers script with Dataset.from_generator) or write a dataset loading script for large datasets.
================================================================================
I tried ‘Dataset. from_ge... | ### Describe the bug
step 'Generating train split' in load_dataset is too slow：
### Steps to reproduce the bug
Data： own data，16K16B Mono wav
Oficial Script:[ run_speech_recognition_seq2seq.py](https://github... | 104 | 43 | Load Data Sets Too Slow In Train Seq2seq Model
### Describe the bug
step 'Generating train split' in load_dataset is too slow：
### Steps to reproduce the bug
Data： own data，16K16B Mono wav
Oficial Script:[ ... | [
-1.2872120141983032,
-0.934897780418396,
-0.618711531162262,
1.4699480533599854,
-0.1538279503583908,
-1.258852481842041,
0.13311150670051575,
-0.9876823425292969,
1.557150959968567,
-0.7559544444084167,
0.30356916785240173,
-1.6126487255096436,
-0.007835671305656433,
-0.5946030616760254,
... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | Hi @AntreasAntoniou , sorry to know you are facing this issue. To help debugging it, could you tell me:
- What is the total dataset size?
- Is it always failing on the same shard or is the hanging problem happening randomly?
- Were you able to save the dataset as parquet locally? This would help us determine if the ... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 81 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | One trick that can also help is to check the traceback when you kill your python process: it will show where in the code it was hanging | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 27 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | Right. So I did the trick @lhoestq suggested. Here is where things seem to hang
```
Error while uploading 'data/train-00120-of-00195-466c2dbab2eb9989.parquet' to the Hub.
Pushing split train to the Hub. ... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 556 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | @Wauplin
>What is the total dataset size?
There are three variants, and the random hanging happens on all three. The sizes are 2TB, 1TB, and 200GB.
>Is it always failing on the same shard or is the hanging problem happening randomly?
It seems to be very much random, as restarting can help move past the pr... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 101 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | Hmm it looks like an issue with TQDM lock. Maybe you can try updating TQDM ? | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 16 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | I am using the latest version of tqdm
```
⬢ [Docker] ❯ pip install tqdm --upgrade
Requirement already satisfied: tqdm in /opt/conda/envs/main/lib/python3.10/site-packages (4.65.0)
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 54 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | I tried trying to catch the hanging issue in action again
```
Pushing dataset shards to the dataset hub: 65%|█████████████████████████████████████████████████████████████████▊ | 127/195 [2:28:02<1:19:15, 69.94s/it]
Error while upload... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 867 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | I'm on my phone so can't help that much. What I'd advice to do is to [save_to_disk](https://huggingface.co/docs/datasets/package_reference/main_classes#save_to_disk) if it's not already done and then upload the files/folder to the Hub separately. You can find what you need in the [upload guide](https://huggingface.co/d... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 58 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | In your last stacktrace it interrupted while embedding external content - in case your dataset in made of images or audio files that live on your disk. Is it the case ? | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 32 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | It's maybe related to https://github.com/apache/arrow/issues/34455: are you using ArrayND features ?
Also what's your `pyarrow` version ? Could you try updating to >= 12.0.1 ? | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 25 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | I was using pyarrow == 12.0.0
I am not explicitly using ArrayND features, unless the hub API automatically converts my files to such. | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 23 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | You can also try to reduce the `max_shard_size` - Sometimes parquet has a hard time working with data bigger than 2GB | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 21 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | So, updating the pyarrow seems to help. It can still throw errors here and there but I can retry when that happens. It's better than hanging.
However, I am a bit confused about something. I have uploaded my datasets, but while earlier I could see all three sets, now I can only see 1. What's going on?
https://hugg... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 83 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | It's a bug on our side, I'll update the dataset viewer ;)
Thanks for reporting ! | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 16 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | Apparently this happened because of bad modifications in the README.md split metadata.
I fixed them in this PR: https://huggingface.co/datasets/Antreas/TALI-base/discussions/1 | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 19 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | @lhoestq It's a bit odd that when uploading a dataset, one set at a time "train", "val", "test", the push_to_hub function overwrites the readme and removes differently named sets from previous commits. i.e., you push "val", all is well. Then you push "test", and the "val" entry disappears from the readme, while the dat... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 56 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | Also, just found another related issue. One of the many that make things hang or fail when pushing to hub.
In the following code:
```python
train_generator = lambda: data_generator("train", percentage=1.0)
val_generator = lambda: data_generator("val")
test_generator = lambda: data_generator("test")
... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 738 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | > @lhoestq It's a bit odd that when uploading a dataset, one set at a time "train", "val", "test", the push_to_hub function overwrites the readme and removes differently named sets from previous commits. i.e., you push "val", all is well. Then you push "test", and the "val" entry disappears from the readme, while the d... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 74 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | > I have a while loop that forces retries, but it seems that the progress itself is randomly getting lost as well. Any ideas on how to improve this? It has been blocking me for way too long.
Could you also print the cause of the error (`e.__cause__`) ? Or show the full stack trace when the error happens ?
This woul... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 73 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | > Should I build the parquet manually and then push manually as well? If I do things manually, how can I ensure my dataset works properly with "stream=True"?
Parquet is supported out of the box ^^
If you want to make sure it works as expected you can try locally first:
```python
ds = load_dataset("path/to/local... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 57 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | @lhoestq @AntreasAntoniou I transferred this issue to the `datasets` repository as the questions and answers are more related to this repo. Hope it can help other users find the bug and fixes more easily (like updating [tqdm](https://github.com/huggingface/datasets/issues/5990#issuecomment-1607120204) and [pyarrow](htt... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 99 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | > @lhoestq @AntreasAntoniou I transferred this issue to the datasets repository as the questions and answers are more related to this repo. Hope it can help other users find the bug and fixes more easily (like updating https://github.com/huggingface/datasets/issues/5990#issuecomment-1607120204 and https://github.com/hu... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 133 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | > As I've already said in other discussions, I would not recommend pushing files saved with save_to_disk to the Hub but save to parquet shards and upload them instead. The Hub does not support datasets saved with save_to_disk, which is meant for disk only.
Well noted, thanks. That part was not clear to me :) | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 55 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | Sorry for not replying in a few days, I was on leave. :)
So, here are more information as to the error that causes some of the delay
```bash
Pushing Antreas/TALI-tiny to hub
Attempting to push to hub
Pushing split train to the Hub.
Creating parquet from Arrow format: 100%|████████████████████████████████████... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 228 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | So, other than the random connection drops here and there, any idea why the progress does not continue where it left off?
```bash
Pushing split train to the Hub.
Creating parquet from Arrow format: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████... | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 352 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5990 | Pushing a large dataset on the hub consistently hangs | If the any shard is missing on the Hub, it will re-upload it. It looks like the 30th shard was missing on the Hub in your case.
It also means that the other files up to the 77th that were successfully uploaded won't be uploaded again.
cc @mariosasko who might know better | ### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over the past week, and despite my best efforts to try and catc... | 105 | 52 | Pushing a large dataset on the hub consistently hangs
### Describe the bug
Once I have locally built a large dataset that I want to push to hub, I use the recommended approach of .push_to_hub to get the dataset on the hub, and after pushing a few shards, it consistently hangs. This has happened over 40 times over th... | [
-1.256646752357483,
-0.9809012413024902,
-0.6407181620597839,
1.5306622982025146,
-0.21641655266284943,
-1.1815036535263062,
0.15102152526378632,
-1.068782091140747,
1.5249862670898438,
-0.8863497972488403,
0.297909140586853,
-1.5170899629592896,
-0.010666148737072945,
-0.5834827423095703,... |
https://github.com/huggingface/datasets/issues/5936 | Sequence of array not supported for most dtype | Related, `float16` is the only dtype not supported by `Array2D` (probably by every `ArrayND`):
```python
from datasets import Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
"int8", # ok
"int16", # ok
"int32", # ok
"int64", # ok
"uint8", # ok
... | ### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
"int8", # failed
"int16", # failed
... | 106 | 91 | Sequence of array not supported for most dtype
### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
... | [
-1.2726014852523804,
-0.8982098698616028,
-0.754351019859314,
1.5242360830307007,
-0.19428840279579163,
-1.113892674446106,
0.17027276754379272,
-1.1304137706756592,
1.5939068794250488,
-0.7255213260650635,
0.27409541606903076,
-1.6660664081573486,
-0.005884177982807159,
-0.591681301593780... |
https://github.com/huggingface/datasets/issues/5936 | Sequence of array not supported for most dtype | Here's something I can't explain:
When an array is encoded in the `from_dict` method, the numpy array is converted to a list (thus losing the original dtype, which is transfromed to the nearest builtin Python type)
https://github.com/huggingface/datasets/blob/6ee61e6e695b1df9f232d47faf3a5e2b30b33737/src/datasets/... | ### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
"int8", # failed
"int16", # failed
... | 106 | 132 | Sequence of array not supported for most dtype
### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
... | [
-1.2726014852523804,
-0.8982098698616028,
-0.754351019859314,
1.5242360830307007,
-0.19428840279579163,
-1.113892674446106,
0.17027276754379272,
-1.1304137706756592,
1.5939068794250488,
-0.7255213260650635,
0.27409541606903076,
-1.6660664081573486,
-0.005884177982807159,
-0.591681301593780... |
https://github.com/huggingface/datasets/issues/5936 | Sequence of array not supported for most dtype | Arrow only support 1d numpy arrays, so we convert multidim arrays to lists of 1s arrays (and keep the dtype).
Though you noticed that it's concerting to lists and lose the dtype. If it's the case then it's a bug. | ### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
"int8", # failed
"int16", # failed
... | 106 | 40 | Sequence of array not supported for most dtype
### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
... | [
-1.2726014852523804,
-0.8982098698616028,
-0.754351019859314,
1.5242360830307007,
-0.19428840279579163,
-1.113892674446106,
0.17027276754379272,
-1.1304137706756592,
1.5939068794250488,
-0.7255213260650635,
0.27409541606903076,
-1.6660664081573486,
-0.005884177982807159,
-0.591681301593780... |
https://github.com/huggingface/datasets/issues/5936 | Sequence of array not supported for most dtype | Ok the conversion to list shouldn't be there indeed ! Could you open a PR to remove it ? | ### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
"int8", # failed
"int16", # failed
... | 106 | 19 | Sequence of array not supported for most dtype
### Describe the bug
Create a dataset composed of sequence of array fails for most dtypes (see code below).
### Steps to reproduce the bug
```python
from datasets import Sequence, Array2D, Features, Dataset
import numpy as np
for dtype in [
"bool", # ok
... | [
-1.2726014852523804,
-0.8982098698616028,
-0.754351019859314,
1.5242360830307007,
-0.19428840279579163,
-1.113892674446106,
0.17027276754379272,
-1.1304137706756592,
1.5939068794250488,
-0.7255213260650635,
0.27409541606903076,
-1.6660664081573486,
-0.005884177982807159,
-0.591681301593780... |
https://github.com/huggingface/datasets/issues/5931 | `datasets.map` not reusing cached copy by default | This can happen when a map transform cannot be hashed deterministically (e.g., an object referenced by the transform changes its state after the first call - an issue with fast tokenizers). The solution is to provide `cache_file_name` in the `map` call to check this file for the cached result instead of relying on the ... | ### Describe the bug
When I load the dataset from local directory, it's cached copy is picked up after first time. However, for `map` operation, the operation is applied again and cached copy is not picked up. Is there any way to pick cached copy instead of processing it again? The only solution I could think of was... | 107 | 57 | `datasets.map` not reusing cached copy by default
### Describe the bug
When I load the dataset from local directory, it's cached copy is picked up after first time. However, for `map` operation, the operation is applied again and cached copy is not picked up. Is there any way to pick cached copy instead of process... | [
-1.3139508962631226,
-0.9539834260940552,
-0.5751308798789978,
1.482445478439331,
-0.20235255360603333,
-1.1960197687149048,
0.21385622024536133,
-1.1024669408798218,
1.6944544315338135,
-0.8689805269241333,
0.33893150091171265,
-1.649861454963684,
0.046380672603845596,
-0.6254940032958984... |
https://github.com/huggingface/datasets/issues/5929 | Importing PyTorch reduces multiprocessing performance for map | Hi! The times match when I run this code locally or on Colab.
Also, we use `multiprocess`, not `multiprocessing`, for parallelization, and torch's `__init__.py` (executed on `import torch` ) slightly modifies the latter. | ### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import datasets
datasets.disable_caching()
from datasets import Da... | 109 | 33 | Importing PyTorch reduces multiprocessing performance for map
### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import... | [
-1.2972315549850464,
-0.9371899366378784,
-0.5583590269088745,
1.5140435695648193,
-0.21326544880867004,
-1.1232210397720337,
0.12382470071315765,
-1.0957438945770264,
1.605454683303833,
-0.7892005443572998,
0.2743966579437256,
-1.6092616319656372,
0.05693559721112251,
-0.5055386424064636,... |
https://github.com/huggingface/datasets/issues/5929 | Importing PyTorch reduces multiprocessing performance for map | Hey Mariosasko,
Thanks for looking into it. We further did some investigations after your comment and figured out it's only affecting some hardware/software configurations with the `pytorch` installation of `conda-forge`. Based on this we found the following issue in PyTorch: https://github.com/pytorch/pytorch/issue... | ### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import datasets
datasets.disable_caching()
from datasets import Da... | 109 | 77 | Importing PyTorch reduces multiprocessing performance for map
### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import... | [
-1.3170827627182007,
-0.9440229535102844,
-0.5832527279853821,
1.5125045776367188,
-0.19861438870429993,
-1.1227771043777466,
0.1241239681839943,
-1.0682389736175537,
1.6109813451766968,
-0.8030138611793518,
0.2515172064304352,
-1.6242655515670776,
0.06468179821968079,
-0.47204259037971497... |
https://github.com/huggingface/datasets/issues/5927 | `IndexError` when indexing `Sequence` of `Array2D` with `None` values | Easy fix would be to add:
```python
null_indices -= np.arange(len(null_indices))
```
before L279, but I'm not sure it's the most intuitive way to fix it. | ### Describe the bug
Having `None` values in a `Sequence` of `ArrayND` fails.
### Steps to reproduce the bug
```python
from datasets import Array2D, Dataset, Features, Sequence
data = [
[
[[0]],
None,
None,
]
]
feature = Sequence(Array2D((1, 1), dtype="int64"))
dataset =... | 110 | 25 | `IndexError` when indexing `Sequence` of `Array2D` with `None` values
### Describe the bug
Having `None` values in a `Sequence` of `ArrayND` fails.
### Steps to reproduce the bug
```python
from datasets import Array2D, Dataset, Features, Sequence
data = [
[
[[0]],
None,
None,
... | [
-1.210868239402771,
-0.8622393608093262,
-0.7345375418663025,
1.4423794746398926,
-0.07342106103897095,
-1.3733819723129272,
0.15904313325881958,
-1.0515152215957642,
1.6494793891906738,
-0.7620460391044617,
0.2587561011314392,
-1.7206271886825562,
-0.0957385003566742,
-0.5657087564468384,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Based on https://github.com/rapidsai/cudf/issues/10187, this probably means your `pyarrow` installation is not compatible with `datasets`.
Can you please execute the following commands in the terminal and paste the output here?
```
conda list | grep arrow
```
```
python -c "import pyarrow; print(pyarrow.__file... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 43 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > Based on [rapidsai/cudf#10187](https://github.com/rapidsai/cudf/issues/10187), this probably means your `pyarrow` installation is not compatible with `datasets`.
>
> Can you please execute the following commands in the terminal and paste the output here?
>
> ```
> conda list | grep arrow
> ```
>
> ```
> p... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 78 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | RuntimeError: Failed to import transformers.trainer because of the following error (look up to see its traceback):
pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility. Expected 88 from C header, got 72 from PyObject | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 32 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | I got the same error, pyarrow 12.0.0 released May/2023 (https://pypi.org/project/pyarrow/) is not compatible, running `pip install pyarrow==11.0.0` to force install the previous version solved the problem.
Do we need to update dependencies? | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 32 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Please note that our CI properly passes all tests with `pyarrow-12.0.0`, for Python 3.7 and Python 3.10, for Ubuntu and Windows: see for example https://github.com/huggingface/datasets/actions/runs/5157324334/jobs/9289582291 | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 25 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | For conda with python3.8.16 this solved my problem! thanks!
> I got the same error, pyarrow 12.0.0 released May/2023 (https://pypi.org/project/pyarrow/) is not compatible, running `pip install pyarrow==11.0.0` to force install the previous version solved the problem.
>
> Do we need to update dependencies? I can w... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 57 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Thanks for replying. I am not sure about those environments but it seems like pyarrow-12.0.0 does not work for conda with python 3.8.16.
> Please note that our CI properly passes all tests with `pyarrow-12.0.0`, for Python 3.7 and Python 3.10, for Ubuntu and Windows: see for example https://github.com/huggingface/d... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 49 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Got the same error with:
```
arrow-cpp 11.0.0 py310h7516544_0
pyarrow 12.0.0 pypi_0 pypi
python 3.10.11 h7a1cb2a_2
datasets 2.13.0 pyhd8ed1ab_0 conda-forge
``` | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 21 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > I got the same error, pyarrow 12.0.0 released May/2023 (https://pypi.org/project/pyarrow/) is not compatible, running `pip install pyarrow==11.0.0` to force install the previous version solved the problem.
>
> Do we need to update dependencies?
This solved the issue for me as well. | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 43 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > I got the same error, pyarrow 12.0.0 released May/2023 (https://pypi.org/project/pyarrow/) is not compatible, running `pip install pyarrow==11.0.0` to force install the previous version solved the problem.
>
> Do we need to update dependencies?
Solved it for me also | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 40 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | > 基于 [rapidsai/cudf#10187](https://github.com/rapidsai/cudf/issues/10187)，这可能意味着您的安装与 不兼容。`pyarrow``datasets`
>
> 您能否在终端中执行以下命令并将输出粘贴到此处？
>
> ```
> conda list | grep arrow
> ```
>
> ```
> python -c "import pyarrow; print(pyarrow.__file__)"
> ```
arrow-cpp 11.0.0 py310h7516544_0 ... | ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 37 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5923 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility | Got the same problem with
arrow-cpp 11.0.0 py310h1fc3239_0
pyarrow 12.0.1 pypi_0 pypi
miniforge3/envs/mlp/lib/python3.10/site-packages/pyarrow/__init__.py
Reverting back to pyarrow 11 solved the problem.
| ### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
File "/Users/edward/opt/anaconda3/envs/cs235/lib/python3.9/site-packages/datasets/__init__.py", line 43, in <module>... | 112 | 21 | Cannot import datasets - ValueError: pyarrow.lib.IpcWriteOptions size changed, may indicate binary incompatibility
### Describe the bug
When trying to import datasets, I get a pyarrow ValueError:
Traceback (most recent call last):
File "/Users/edward/test/test.py", line 1, in <module>
import datasets
... | [
-1.1750595569610596,
-0.872355043888092,
-0.6893664002418518,
1.387781023979187,
-0.05072424188256264,
-1.2870230674743652,
0.0344497412443161,
-1.0810635089874268,
1.4963840246200562,
-0.7009853720664978,
0.2459050863981247,
-1.6988246440887451,
-0.17471174895763397,
-0.39148375391960144,... |
https://github.com/huggingface/datasets/issues/5922 | Length of table does not accurately reflect the split | As already replied by @lhoestq (private channel):
> `.train_test_split` (as well as `.shard`, `.select`) doesn't create a new arrow table to save time and disk space. Instead, it uses an indices mapping on top of the table that locate which examples are part of train or test. | ### Describe the bug
I load a Huggingface Dataset and do `train_test_split`. I'm expecting the underlying table for the dataset to also be split, but it's not.
### Steps to reproduce the bug
### Expected behavior... | 113 | 47 | Length of table does not accurately reflect the split
### Describe the bug
I load a Huggingface Dataset and do `train_test_split`. I'm expecting the underlying table for the dataset to also be split, but it's not.
### Steps to reproduce the bug
. The dataset contains 50 million text-image pairs, but an error occurred. | Thanks for reporting, @cjt222.
What is the structure of your JSON files. Please note that it is normally simpler if the data file format is JSON-Lines instead. | ### Describe the bug
File "/home/kas/.conda/envs/diffusers/lib/python3.7/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
Downloading and preparing dataset json/default to /home/kas/diffusers/examples/dreambooth/cache_data/datasets/json/default-acf423d8c6ef99d0/0.0.0/e347ab1c932092252e717ff3f94... | 115 | 27 | I tried to load a custom dataset using the following statement: dataset = load_dataset('json', data_files=data_files). The dataset contains 50 million text-image pairs, but an error occurred.
### Describe the bug
File "/home/kas/.conda/envs/diffusers/lib/python3.7/site-packages/datasets/builder.py", line 1858, in _p... | [
-1.214315414428711,
-0.9003573060035706,
-0.7741171717643738,
1.475507140159607,
-0.09832651913166046,
-1.224456787109375,
0.10411228984594345,
-1.0862165689468384,
1.5122780799865723,
-0.6888920664787292,
0.23147977888584137,
-1.6943081617355347,
0.01101731788367033,
-0.47393232583999634,... |
https://github.com/huggingface/datasets/issues/5913 | I tried to load a custom dataset using the following statement: dataset = load_dataset('json', data_files=data_files). The dataset contains 50 million text-image pairs, but an error occurred. | > Thanks for reporting, @cjt222.
>
> What is the structure of your JSON files. Please note that it is normally simpler if the data file format is JSON-Lines instead.
Thanks! I have encountered similar problems. I modify the json format from list to line and works! | ### Describe the bug
File "/home/kas/.conda/envs/diffusers/lib/python3.7/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
Downloading and preparing dataset json/default to /home/kas/diffusers/examples/dreambooth/cache_data/datasets/json/default-acf423d8c6ef99d0/0.0.0/e347ab1c932092252e717ff3f94... | 115 | 47 | I tried to load a custom dataset using the following statement: dataset = load_dataset('json', data_files=data_files). The dataset contains 50 million text-image pairs, but an error occurred.
### Describe the bug
File "/home/kas/.conda/envs/diffusers/lib/python3.7/site-packages/datasets/builder.py", line 1858, in _p... | [
-1.214315414428711,
-0.9003573060035706,
-0.7741171717643738,
1.475507140159607,
-0.09832651913166046,
-1.224456787109375,
0.10411228984594345,
-1.0862165689468384,
1.5122780799865723,
-0.6888920664787292,
0.23147977888584137,
-1.6943081617355347,
0.01101731788367033,
-0.47393232583999634,... |
https://github.com/huggingface/datasets/issues/5912 | Missing elements in `map` a batched dataset | Hi ! in your code batching is **only used within** `map`, to process examples in batch. The dataset itself however is not batched and returns elements one by one.
To iterate on batches, you can do
```python
for batch in dataset.iter(batch_size=8):
...
``` | ### Describe the bug
As outlined [here](https://discuss.huggingface.co/t/length-error-using-map-with-datasets/40969/3?u=sachin), the following collate function drops 5 out of possible 6 elements in the batch (it is 6 because out of the eight, two are bad links in laion). A reproducible [kaggle kernel ](https://www.kag... | 116 | 43 | Missing elements in `map` a batched dataset
### Describe the bug
As outlined [here](https://discuss.huggingface.co/t/length-error-using-map-with-datasets/40969/3?u=sachin), the following collate function drops 5 out of possible 6 elements in the batch (it is 6 because out of the eight, two are bad links in laion). A... | [
-1.2613688707351685,
-0.9045363068580627,
-0.7689740657806396,
1.5484023094177246,
-0.15282121300697327,
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0.18357080221176147,
-1.1153026819229126,
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0.3649711310863495,
-1.625902771949768,
0.048905737698078156,
-0.5768985152244568,
... |
https://github.com/huggingface/datasets/issues/5910 | Cannot use both set_format and set_transform | Currently, it's not possible to chain `set_format`/`set_transform` calls (plus, this is a breaking change if we decide to implement it), so I see two possible solutions:
* using `set_format`/`set_transform` for the 1st transform and then passing the transformed example/batch to the 2nd transform
* implementing and re... | ### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.
### Steps to reproduce the bug
```
from... | 117 | 69 | Cannot use both set_format and set_transform
### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.... | [
-1.1962045431137085,
-0.9554942846298218,
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1.5405189990997314,
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0.1379733830690384,
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1.6740038394927979,
-0.8126764893531799,
0.36410877108573914,
-1.669192910194397,
0.017796795815229416,
-0.5807246565818787... |
https://github.com/huggingface/datasets/issues/5910 | Cannot use both set_format and set_transform | Hey Mario,
Thanks, for getting back to me. the toDouble was just an example my real life case requires many more transforms.
What do you mean by:
> using set_format/set_transform for the 1st transform and then passing the transformed example/batch to the 2nd transform
How would that go, I thought you can't chai... | ### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.
### Steps to reproduce the bug
```
from... | 117 | 86 | Cannot use both set_format and set_transform
### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.... | [
-1.1929880380630493,
-0.9725824594497681,
-0.711422324180603,
1.56049382686615,
-0.15872026979923248,
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0.12541748583316803,
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1.6653180122375488,
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0.33287307620048523,
-1.6364455223083496,
0.04797825217247009,
-0.5497223734855652,
... |
https://github.com/huggingface/datasets/issues/5910 | Cannot use both set_format and set_transform | > How would that go, I thought you can't chain them?
Yes, they cannot be chained. This is what I meant:
```python
ds.set_transform(first_transform)
# calling the 2nd transform on each accessed batch
second_transform(ds[2:3])
```
> As for the custom formatter, is it possible to reference an existing formatter... | ### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.
### Steps to reproduce the bug
```
from... | 117 | 74 | Cannot use both set_format and set_transform
### Describe the bug
I need to process some data using the set_transform method but I also need the data to be formatted for pytorch before processing it.
I don't see anywhere in the documentation something that says that both methods cannot be used at the same time.... | [
-1.168801188468933,
-0.9402036666870117,
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1.5810835361480713,
-0.16430777311325073,
-1.255759358406067,
0.12602271139621735,
-1.0644527673721313,
1.696113109588623,
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0.3384011685848236,
-1.6515110731124878,
0.04300512373447418,
-0.5639449954032898,
... |
https://github.com/huggingface/datasets/issues/5908 | Unbearably slow sorting on big mapped datasets | Hi ! `shard` currently returns a slow dataset by default, with examples evenly distributed in the dataset.
You can get a fast dataset using `contiguous=True` (which should be the default imo):
```python
dataset = dataset.shard(10, 0, contiguous=True)
```
This way you don't need to flatten_indices() and sort ... | ### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially with bigger datasets (wasn't able to sort 700k lin... | 118 | 52 | Unbearably slow sorting on big mapped datasets
### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially w... | [
-1.2905364036560059,
-0.9583756327629089,
-0.620995044708252,
1.4027750492095947,
-0.1813255399465561,
-1.1900031566619873,
0.13535702228546143,
-1.025447130203247,
1.6899755001068115,
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0.28892964124679565,
-1.6771329641342163,
0.04762488231062889,
-0.5541487336158752,
... |
https://github.com/huggingface/datasets/issues/5908 | Unbearably slow sorting on big mapped datasets | @lhoestq
> contiguous=True (which should be the default imo)
For `IterableDataset`, it's not possible to implement contiguous sharding without knowing the number of examples in advance, so setting the default value to `contiguous=True` would result in an inconsistency between `Dataset` and `IterableDataset` (whe... | ### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially with bigger datasets (wasn't able to sort 700k lin... | 118 | 46 | Unbearably slow sorting on big mapped datasets
### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially w... | [
-1.2704607248306274,
-0.9528551697731018,
-0.6407310366630554,
1.445859670639038,
-0.13518880307674408,
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0.1405484825372696,
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-0.8348231315612793,
0.31354185938835144,
-1.6874817609786987,
0.04302075132727623,
-0.5347610712051392,... |
https://github.com/huggingface/datasets/issues/5908 | Unbearably slow sorting on big mapped datasets | Actually sharded iterable datasets are made of sub iterables that generally yield contiguous data no ? So in a way it's possible to shard an iterable dataset contiguously.
If the dataset is made of one shard it's indeed not possible to shard it contiguously though | ### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially with bigger datasets (wasn't able to sort 700k lin... | 118 | 45 | Unbearably slow sorting on big mapped datasets
### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially w... | [
-1.2956740856170654,
-0.9560195207595825,
-0.6549262404441833,
1.4137053489685059,
-0.1566047966480255,
-1.1755940914154053,
0.12435031682252884,
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1.6702497005462646,
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0.27757954597473145,
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0.04029139131307602,
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... |
https://github.com/huggingface/datasets/issues/5908 | Unbearably slow sorting on big mapped datasets | > Actually sharded iterable datasets are made of sub iterables that generally yield contiguous data no ? So in a way it's possible to shard an iterable dataset contiguously.
But sharding an iterable dataset by sharding its `gen_kwargs` would still yield approximate shards(not equal to `Dataset.shard`), no? | ### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially with bigger datasets (wasn't able to sort 700k lin... | 118 | 47 | Unbearably slow sorting on big mapped datasets
### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially w... | [
-1.286099910736084,
-0.947054386138916,
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1.3852754831314087,
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0.034982822835445404,
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... |
https://github.com/huggingface/datasets/issues/5908 | Unbearably slow sorting on big mapped datasets | I understand the issue doesn't exist with non-mapped datasets, but if flattening is so much more efficient than sorting the indices, that's an issue in itself.
There are plenty of issues people posted for which the root cause turns out to be the same. It seems like mapped datasets are terribly inefficient. I think I s... | ### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially with bigger datasets (wasn't able to sort 700k lin... | 118 | 82 | Unbearably slow sorting on big mapped datasets
### Describe the bug
For me, with ~40k lines, sorting took 3.5 seconds on a flattened dataset (including the flatten operation) and 22.7 seconds on a mapped dataset (right after sharding), which is about x5 slowdown. Moreover, it seems like it slows down exponentially w... | [
-1.3209213018417358,
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1.3790735006332397,
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0.03741684928536415,
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... |
https://github.com/huggingface/datasets/issues/5905 | Offer an alternative to Iterable Dataset that allows lazy loading and processing while skipping batches efficiently | We plan to improve this eventually (see https://github.com/huggingface/datasets/issues/5454 and https://github.com/huggingface/datasets/issues/5380).
> Is it possible to lazily load samples of a mapped dataset ? I'm used to [dataset scripts](https://huggingface.co/docs/datasets/dataset_script), maybe something can b... | ### Feature request
I would like a way to resume training from a checkpoint without waiting for a very long time when using an iterable dataset.
### Motivation
I am training models on the speech-recognition task. I have very large datasets that I can't comfortably store on a disk and also quite computationally... | 119 | 151 | Offer an alternative to Iterable Dataset that allows lazy loading and processing while skipping batches efficiently
### Feature request
I would like a way to resume training from a checkpoint without waiting for a very long time when using an iterable dataset.
### Motivation
I am training models on the speec... | [
-1.3023881912231445,
-0.971327543258667,
-0.7936956286430359,
1.3595514297485352,
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-1.2680957317352295,
0.10471782833337784,
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1.689953088760376,
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0.2486770749092102,
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0.05559813976287842,
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... |
https://github.com/huggingface/datasets/issues/5895 | The dir name and split strings are confused when loading ArmelR/stack-exchange-instruction dataset | Thanks for reporting, @DongHande.
I think the issue is caused by the metadata in the dataset card: in the header of the `README.md`, they state that the dataset has 4 splits ("finetune", "reward", "rl", "evaluation").
```yaml
splits:
- name: finetune
num_bytes: 6674567576
num_examples: 300000... | ### Describe the bug
When I load the ArmelR/stack-exchange-instruction dataset, I encounter a bug that may be raised by confusing the dir name string and the split string about the dataset.
When I use the script "datasets.load_dataset('ArmelR/stack-exchange-instruction', data_dir="data/finetune", split="train", ... | 121 | 122 | The dir name and split strings are confused when loading ArmelR/stack-exchange-instruction dataset
### Describe the bug
When I load the ArmelR/stack-exchange-instruction dataset, I encounter a bug that may be raised by confusing the dir name string and the split string about the dataset.
When I use the script ... | [
-1.2114895582199097,
-0.9616886973381042,
-0.63692307472229,
1.3751533031463623,
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1.505510926246643,
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0.20670625567436218,
-1.7175835371017456,
-0.13693691790103912,
-0.4112592935562134,
... |
https://github.com/huggingface/datasets/issues/5892 | User access requests with manual review do not notify the dataset owner | I think this has been addressed.
Please open a new issue if you are still not getting notified. | ### Describe the bug
When a user access requests are enabled, and new requests are set to Manual Review, the dataset owner should be notified of the pending requests. However, instead, currently nothing happens, and so the dataset request can go unanswered for quite some time until the owner happens to check that part... | 122 | 18 | User access requests with manual review do not notify the dataset owner
### Describe the bug
When a user access requests are enabled, and new requests are set to Manual Review, the dataset owner should be notified of the pending requests. However, instead, currently nothing happens, and so the dataset request can go... | [
-1.118501901626587,
-1.001804232597351,
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1.3394150733947754,
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0.16991223394870758,
-1.6423394680023193,
-0.022839628159999847,
-0.631849348545074... |
https://github.com/huggingface/datasets/issues/5887 | HuggingsFace dataset example give error | Nice catch @donhuvy, that's because some models don't need the `token_type_ids`, as in this case, as the example is using `distilbert-base-cased`, and according to the DistilBert documentation at https://huggingface.co/transformers/v3.0.2/model_doc/distilbert.html, `DistilBert doesn’t have token_type_ids, you don’t nee... | ### Describe the bug
### Steps to reproduce the bug
Use link as reference document written https://c... | 123 | 107 | HuggingsFace dataset example give error
### Describe the bug
### Steps to reproduce the bug
Use li... | [
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1.451823115348816,
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1.626806616783142,
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0.42705410718917847,
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0.03695901483297348,
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https://github.com/huggingface/datasets/issues/5887 | HuggingsFace dataset example give error | This has been addressed in #5902.
The Quicktour notebook is deprecated now - please use the notebook version of the [Quickstart doc page](https://huggingface.co/docs/datasets/main/en/quickstart) instead ("Open in Colab" button). | ### Describe the bug
### Steps to reproduce the bug
Use link as reference document written https://c... | 123 | 28 | HuggingsFace dataset example give error
### Describe the bug
### Steps to reproduce the bug
Use li... | [
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https://github.com/huggingface/datasets/issues/5886 | Use work-stealing algorithm when parallel computing | Alternatively we could set the number of shards to be a factor than the number of processes (current they're equal) - this way it will be less likely to end up with a shard that is significantly slower than all the other ones. | ### Feature request
when i used Dataset.map api to process data concurrently, i found that
it gets slower and slower as it gets closer to completion. Then i read the source code of arrow_dataset.py and found that it shard the dataset and use multiprocessing pool to execute each shard.It may cause the slowest task ... | 124 | 43 | Use work-stealing algorithm when parallel computing
### Feature request
when i used Dataset.map api to process data concurrently, i found that
it gets slower and slower as it gets closer to completion. Then i read the source code of arrow_dataset.py and found that it shard the dataset and use multiprocessing poo... | [
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https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | Hi!
You want to use `push_to_hub` (creates Parquet files) instead of `save_to_disk` (creates Arrow files) when creating a Hub dataset. Parquet is designed for long-term storage and takes less space than the Arrow format, and, most importantly, `load_dataset` can parse it, which should fix the viewer.
Regarding ... | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 125 | 142 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
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https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | One issue here is that Dataset.from_generator can work well for the non 'infinite sampling' version of the dataset. The training set for example is often sampled dynamically given the video files that I have uploaded. I worry that storing the video data as binary means that I'll end up duplicating a lot of the data. Fu... | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 125 | 73 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
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https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | > storing video data as anything but .mp4
What I mean by storing as `datasets.Value("binary")` is embedding raw MP4 bytes in the Arrow table, but, indeed, this would waste a lot of space if there are duplicates.
So I see two options:
* if one video is not mapped to too many samples, you can embed the video bytes... | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 125 | 159 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
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https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | @mariosasko Right. If I want my dataset to be streamable, what are the necessary requirements to achieve that within the context of .mp4 binaries like we have here? I guess your second point here would not support that right? | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 125 | 39 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
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https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | The streaming would work, but the video paths would require using `fsspec.open` to get the content. | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 125 | 16 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
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https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | Not yet. The (open source) tooling for video is not great in terms of ease of use/performance, so we are discussing internally the best way to support it (one option is creating a new library for video IO, but this will require a lot of work) | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 125 | 46 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
-1.185950756072998,
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https://github.com/huggingface/datasets/issues/5888 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset | True. I spend a good 4 months just mixing and matching existing solutions so I could get performance that would not IO bound my model training.
This is what I ended up with, in case it's useful
https://github.com/AntreasAntoniou/TALI/blob/045cf9e5aa75b1bf2c6d5351fb910fa10e3ff32c/tali/data/data_plus.py#L85 | **Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines images, text, audio and video. Now, I could very easily upload a dataset made via datase... | 125 | 38 | A way to upload and visualize .mp4 files (millions of them) as part of a dataset
**Is your feature request related to a problem? Please describe.**
I recently chose to use huggingface hub as the home for a large multi modal dataset I've been building. https://huggingface.co/datasets/Antreas/TALI
It combines image... | [
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https://github.com/huggingface/datasets/issues/5881 | Split dataset by node: index error when sharding iterable dataset | cc @lhoestq in case you have any ideas here! Might need a multi-host set-up to debug (can give you access to a JAX one if you need) | ### Describe the bug
Context: we're splitting an iterable dataset by node and then passing it to a torch data loader with multiple workers
When we iterate over it for 5 steps, we don't get an error
When we instead iterate over it for 8 steps, we get an `IndexError` when fetching the data if we have too many wo... | 127 | 27 | Split dataset by node: index error when sharding iterable dataset
### Describe the bug
Context: we're splitting an iterable dataset by node and then passing it to a torch data loader with multiple workers
When we iterate over it for 5 steps, we don't get an error
When we instead iterate over it for 8 steps, ... | [
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https://github.com/huggingface/datasets/issues/5880 | load_dataset from s3 file system through streaming can't not iterate data | This sounds related to #5281.
Can you try passing `storage_options=s3_client.storage_options` instead passing it to `use_auth_token=` ? | ### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-45b5-ac68-4e7c664c2ed0">
<img width="1144" alt="image" src="https://github.c... | 128 | 16 | load_dataset from s3 file system through streaming can't not iterate data
### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-... | [
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https://github.com/huggingface/datasets/issues/5880 | load_dataset from s3 file system through streaming can't not iterate data | I tried `storage_options` before, but it doesn't work, I checked our source code and I found that we even didn't pass this parameter to the following process. if I use `storage_options` instead of `use_auth_token`, then I also need to change another place of the code. the last line of `streaming_download_manager.py`. o... | ### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-45b5-ac68-4e7c664c2ed0">
<img width="1144" alt="image" src="https://github.c... | 128 | 70 | load_dataset from s3 file system through streaming can't not iterate data
### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-... | [
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... |
https://github.com/huggingface/datasets/issues/5880 | load_dataset from s3 file system through streaming can't not iterate data | Cloud storage support is still experimental indeed and you can expect some bugs.
I think we need to pass the storage options anywhere use_auth_token is passed in indeed. Let me know if you'd be interested in contributing a fix ! | ### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-45b5-ac68-4e7c664c2ed0">
<img width="1144" alt="image" src="https://github.c... | 128 | 40 | load_dataset from s3 file system through streaming can't not iterate data
### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-... | [
-1.225001573562622,
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... |
https://github.com/huggingface/datasets/issues/5880 | load_dataset from s3 file system through streaming can't not iterate data | Oh, that's great, I really like to fix it. because datasets is really useful and most of our projects need to use it, but we can store our data on the internet due to security reasons. fix it not only make our own work more efficient but also can benefit others who use it. | ### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-45b5-ac68-4e7c664c2ed0">
<img width="1144" alt="image" src="https://github.c... | 128 | 54 | load_dataset from s3 file system through streaming can't not iterate data
### Describe the bug
I have a JSON file in my s3 file system(minio), I can use load_dataset to get the file link, but I can't iterate it
<img width="816" alt="image" src="https://github.com/huggingface/datasets/assets/59083384/cc0778d3-36f3-... | [
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... |
https://github.com/huggingface/datasets/issues/5878 | Prefetching for IterableDataset | Very cool! Do you have a link to the code that you're using to eagerly fetch the data? Would also be interested in hacking around something here for pre-fetching iterable datasets | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk... | 129 | 31 | Prefetching for IterableDataset
### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required whe... | [
-1.271242380142212,
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... |
https://github.com/huggingface/datasets/issues/5878 | Prefetching for IterableDataset | I ended up just switching back to the pytorch dataloader and using it's multiprocessing functionality to handle this :(. I'm just not that familiar with python multiprocessing to get something to work in jupyter (kept having weird behaviors happening with zombies living after the cell finished). | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk... | 129 | 46 | Prefetching for IterableDataset
### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required whe... | [
-1.220917820930481,
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1.466491937637329,
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... |
https://github.com/huggingface/datasets/issues/5878 | Prefetching for IterableDataset | Ultimately settled on using webdataset to circumvent huggingface datasets entirely. Would definitely switch back if: https://github.com/huggingface/datasets/issues/5337 was resolved. | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk... | 129 | 18 | Prefetching for IterableDataset
### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required whe... | [
-1.2153074741363525,
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0.05381225049495697,
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https://github.com/huggingface/datasets/issues/5878 | Prefetching for IterableDataset | Hi! You can combine `datasets` with `torchdata` to prefetch `IterableDataset`'s samples:
```python
from datasets import load_dataset
from torchdata.datapipes.iter import IterableWrapper, HuggingFaceHubReader
from torch.utils.data import DataLoader
ds = load_dataset("sst", split="train", streaming=True)
# proces... | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk... | 129 | 47 | Prefetching for IterableDataset
### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required whe... | [
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-0.4805092513561249,
... |
https://github.com/huggingface/datasets/issues/5878 | Prefetching for IterableDataset | Hey @mariosasko! Thanks for the tip here - introducing prefetch with `torchdata` didn't really give me any performance difference vs not prefetching, but the concept is definitely one that could be really beneficial. Are there any benchmarks that show the speed-up you can get with `torchdata`'s prefetch just for compar... | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk... | 129 | 50 | Prefetching for IterableDataset
### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required whe... | [
-1.2148624658584595,
-0.9804335236549377,
-0.8782618641853333,
1.4629179239273071,
-0.17375557124614716,
-1.1947301626205444,
0.0796777680516243,
-1.1399915218353271,
1.6754252910614014,
-0.8502100110054016,
0.3184136748313904,
-1.6461998224258423,
0.08585613965988159,
-0.5049746632575989,... |
https://github.com/huggingface/datasets/issues/5877 | Request for text deduplication feature | The "exact match" deduplication will be possible when we resolve https://github.com/huggingface/datasets/issues/2514 (first, https://github.com/apache/arrow/issues/30950 needs to be addressed on the Arrow side). In the meantime, you can use Polars or DuckDB (e.g., via [datasets-sql](https://github.com/mariosasko/datase... | ### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.com/google-research/deduplicate-text-datase... | 130 | 47 | Request for text deduplication feature
### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.co... | [
-1.1709834337234497,
-0.9297122955322266,
-0.8974321484565735,
1.5005226135253906,
-0.10602199286222458,
-1.307770848274231,
0.10306137800216675,
-0.9186413884162903,
1.5724055767059326,
-0.7990024089813232,
0.34464287757873535,
-1.7102205753326416,
0.00363814365118742,
-0.5331831574440002... |
https://github.com/huggingface/datasets/issues/5877 | Request for text deduplication feature | I have been using polars to remove duplicates but it would be nice to do it directly in pyarrow.
For example,
1. Read dataset with pyarrow
2. Use scan_pyarrow_dataset() with Polars to create a LazyFrame
3. Use sort and unique to remove duplicates based on a subset of columns
4. Convert to table and save data w... | ### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.com/google-research/deduplicate-text-datase... | 130 | 104 | Request for text deduplication feature
### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.co... | [
-1.2370171546936035,
-0.9691077470779419,
-0.8257652521133423,
1.4187049865722656,
-0.19961251318454742,
-1.2766376733779907,
0.10543016344308853,
-1.102431297302246,
1.66205894947052,
-0.8634591102600098,
0.31656914949417114,
-1.5635490417480469,
0.0969298854470253,
-0.5174001455307007,
... |
https://github.com/huggingface/datasets/issues/5876 | Incompatibility with DataLab | Indeed, `clobber=True` (with a warning if the existing protocol will be overwritten) should fix the issue, but maybe a better solution is to register our compression filesystem before the script is executed and unregister them afterward. WDYT @lhoestq @albertvillanova? | ### Describe the bug
Hello,
I am currently working on a project where both [DataLab](https://github.com/ExpressAI/DataLab) and [datasets](https://github.com/huggingface/datasets) are subdependencies.
I noticed that I cannot import both libraries, as they both register FileSystems in `fsspec`, expecting the FileSyste... | 131 | 39 | Incompatibility with DataLab
### Describe the bug
Hello,
I am currently working on a project where both [DataLab](https://github.com/ExpressAI/DataLab) and [datasets](https://github.com/huggingface/datasets) are subdependencies.
I noticed that I cannot import both libraries, as they both register FileSystems in `f... | [
-1.3235520124435425,
-0.8967524170875549,
-0.5762975215911865,
1.3693373203277588,
-0.06261253356933594,
-1.24762761592865,
0.08170504868030548,
-1.0611730813980103,
1.7106448411941528,
-0.8065423369407654,
0.24225544929504395,
-1.7274513244628906,
0.054623737931251526,
-0.5989668369293213... |
https://github.com/huggingface/datasets/issues/5876 | Incompatibility with DataLab | I think we should use clobber and show a warning if it overwrote a registered filesystem indeed ! This way the user can re-register the filesystems if needed. Though they should probably be compatible (and maybe do the exact same thing) so I wouldn't de-register the `datasets` filesystems | ### Describe the bug
Hello,
I am currently working on a project where both [DataLab](https://github.com/ExpressAI/DataLab) and [datasets](https://github.com/huggingface/datasets) are subdependencies.
I noticed that I cannot import both libraries, as they both register FileSystems in `fsspec`, expecting the FileSyste... | 131 | 48 | Incompatibility with DataLab
### Describe the bug
Hello,
I am currently working on a project where both [DataLab](https://github.com/ExpressAI/DataLab) and [datasets](https://github.com/huggingface/datasets) are subdependencies.
I noticed that I cannot import both libraries, as they both register FileSystems in `f... | [
-1.3235520124435425,
-0.8967524170875549,
-0.5762975215911865,
1.3693373203277588,
-0.06261253356933594,
-1.24762761592865,
0.08170504868030548,
-1.0611730813980103,
1.7106448411941528,
-0.8065423369407654,
0.24225544929504395,
-1.7274513244628906,
0.054623737931251526,
-0.5989668369293213... |
https://github.com/huggingface/datasets/issues/5874 | Using as_dataset on a "parquet" builder | Hi! You can refer to [this doc](https://huggingface.co/docs/datasets/filesystems#load-and-save-your-datasets-using-your-cloud-storage-filesystem) to see the intended usage (basically, it skips the Arrow -> Parquet conversion step in `ds = load_dataset(...); ds.to_parquet("path/to/parquet")`) and allows writing Parquet ... | ### Describe the bug
I used a custom builder to ``download_and_prepare`` a dataset. The first (very minor) issue is that the doc seems to suggest ``download_and_prepare`` will return the dataset, while it does not ([builder.py](https://github.com/huggingface/datasets/blob/main/src/datasets/builder.py#L718-L738)).
```... | 133 | 104 | Using as_dataset on a "parquet" builder
### Describe the bug
I used a custom builder to ``download_and_prepare`` a dataset. The first (very minor) issue is that the doc seems to suggest ``download_and_prepare`` will return the dataset, while it does not ([builder.py](https://github.com/huggingface/datasets/blob/ma... | [
-1.1747794151306152,
-0.8651508688926697,
-0.6452351808547974,
1.5011615753173828,
-0.11358693987131119,
-1.3477064371109009,
0.15903188288211823,
-1.0846970081329346,
1.7358369827270508,
-0.7666627764701843,
0.34405216574668884,
-1.6224406957626343,
0.007860351353883743,
-0.60045844316482... |
https://github.com/huggingface/datasets/issues/5871 | data configuration hash suffix depends on uncanonicalized data_dir | Indeed, it makes sense to normalize `data_dir`. Feel free to submit a PR (this can be "fixed" [here](https://github.com/huggingface/datasets/blob/89f775226321ba94e5bf4670a323c0fb44f5f65c/src/datasets/builder.py#L173)) | ### Describe the bug
I am working with the `recipe_nlg` dataset, which requires manual download. Once it's downloaded, I've noticed that the hash in the custom data configuration is different if I add a trailing `/` to my `data_dir`. It took me a while to notice that the hashes were different, and to understand that... | 134 | 18 | data configuration hash suffix depends on uncanonicalized data_dir
### Describe the bug
I am working with the `recipe_nlg` dataset, which requires manual download. Once it's downloaded, I've noticed that the hash in the custom data configuration is different if I add a trailing `/` to my `data_dir`. It took me a w... | [
-1.159549355506897,
-0.9545087218284607,
-0.8072333931922913,
1.4055579900741577,
-0.07978649437427521,
-1.1871358156204224,
0.15875309705734253,
-1.0666435956954956,
1.6769993305206299,
-0.6768544912338257,
0.23950590193271637,
-1.7272834777832031,
-0.03943215310573578,
-0.632664442062377... |
https://github.com/huggingface/datasets/issues/5870 | Behaviour difference between datasets.map and IterableDatasets.map | PS - some work is definitely needed for 'special cases' docs, not explanations, just usages of 'functions' under mixture of special cases, like a combination of custom databuilder + iterable dataset for large size + dynamic .map() application. | ### Describe the bug
All the examples in all the docs mentioned throughout huggingface datasets correspond to datasets object, and not IterableDatasets object. At one point of time, they might have been in sync, but the code for datasets version >=2.9.0 is very different as compared to the docs.
I basically need to ... | 135 | 38 | Behaviour difference between datasets.map and IterableDatasets.map
### Describe the bug
All the examples in all the docs mentioned throughout huggingface datasets correspond to datasets object, and not IterableDatasets object. At one point of time, they might have been in sync, but the code for datasets version >=2.... | [
-1.271490216255188,
-1.061184048652649,
-0.6920825242996216,
1.3646483421325684,
-0.23317208886146545,
-1.1623080968856812,
0.1243559792637825,
-1.1511949300765991,
1.5991405248641968,
-0.8199964165687561,
0.2599809169769287,
-1.6468255519866943,
-0.05293817073106766,
-0.5666168332099915,
... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | Hi @PhilippeMoussalli thanks for opening a detailed issue. It seems the issue is more related to the `datasets` library so I'll ping @lhoestq @mariosasko on this one :)
(edit: also can one of you move the issue to the datasets repo? Thanks in advance 🙏) | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 136 | 45 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-1.1553672552108765,
-0.8704099059104919,
-0.8205088376998901,
1.4618592262268066,
-0.13831359148025513,
-1.3031227588653564,
0.08137144148349762,
-1.077457070350647,
1.7212998867034912,
-0.7961846590042114,
0.25587376952171326,
-1.7589480876922607,
-0.05134357139468193,
-0.533249974250793... |
https://github.com/huggingface/datasets/issues/5869 | Image Encoding Issue when submitting a Parquet Dataset | Hi ! The `Image()` info is stored in the **schema metadata**. More precisely there should be a "huggingface" field in the schema metadata that contains the `datasets` feature type of each column.
To fix your issue, you can use the same schema as the original Parquet files to write the new ones. You can also get the ... | ### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (HF) filesystem using Dask with the following code snippet... | 136 | 95 | Image Encoding Issue when submitting a Parquet Dataset
### Describe the bug
Hello,
I'd like to report an issue related to pushing a dataset represented as a Parquet file to a dataset repository using Dask. Here are the details:
We attempted to load an example dataset in Parquet format from the Hugging Face (... | [
-1.1553672552108765,
-0.8704099059104919,
-0.8205088376998901,
1.4618592262268066,
-0.13831359148025513,
-1.3031227588653564,
0.08137144148349762,
-1.077457070350647,
1.7212998867034912,
-0.7961846590042114,
0.25587376952171326,
-1.7589480876922607,
-0.05134357139468193,
-0.533249974250793... |
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