html_url stringlengths 48 51 | title stringlengths 5 280 | comments stringlengths 63 51.8k | body stringlengths 0 36.2k ⌀ | comment_length int64 16 1.52k | text stringlengths 159 54.1k | embeddings listlengths 768 768 |
|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/5987 | Why max_shard_size is not supported in load_dataset and passed to download_and_prepare | Can you explain your use case for `max_shard_size`?
On some systems, there is a limit to the size of a memory-mapped file, so we could consider exposing this parameter in `load_dataset`. | ### Describe the bug
https://github.com/huggingface/datasets/blob/a8a797cc92e860c8d0df71e0aa826f4d2690713e/src/datasets/load.py#L1809
What I can to is break the `load_dataset` and use `load_datset_builder` + `download_and_prepare` instead.
### Steps to reproduce the bug
https://github.com/huggingface/datasets/blo... | 31 | Why max_shard_size is not supported in load_dataset and passed to download_and_prepare
### Describe the bug
https://github.com/huggingface/datasets/blob/a8a797cc92e860c8d0df71e0aa826f4d2690713e/src/datasets/load.py#L1809
What I can to is break the `load_dataset` and use `load_datset_builder` + `download_and_prepa... | [
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0.2664555311203003,
0.028241224586963654,
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0.1789389401... |
https://github.com/huggingface/datasets/issues/5987 | Why max_shard_size is not supported in load_dataset and passed to download_and_prepare | In my use case, users may choose a proper size to balance the cost and benefit of using large shard size. (On azure blob or hdfs which may automatically download the shard from background) | ### Describe the bug
https://github.com/huggingface/datasets/blob/a8a797cc92e860c8d0df71e0aa826f4d2690713e/src/datasets/load.py#L1809
What I can to is break the `load_dataset` and use `load_datset_builder` + `download_and_prepare` instead.
### Steps to reproduce the bug
https://github.com/huggingface/datasets/blo... | 34 | Why max_shard_size is not supported in load_dataset and passed to download_and_prepare
### Describe the bug
https://github.com/huggingface/datasets/blob/a8a797cc92e860c8d0df71e0aa826f4d2690713e/src/datasets/load.py#L1809
What I can to is break the `load_dataset` and use `load_datset_builder` + `download_and_prepa... | [
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0.08890246599912643,
0.3084559440... |
https://github.com/huggingface/datasets/issues/5987 | Why max_shard_size is not supported in load_dataset and passed to download_and_prepare | But `load_dataset` doesn't support caching (and reading) Arrow datasets from remote storage.
`load_datset_builder` + `download_and_prepare` is not equal to `load_dataset`. The latter has one more step, `builder.as_dataset`, that memory-maps Arrow files, which only works for local files. | ### Describe the bug
https://github.com/huggingface/datasets/blob/a8a797cc92e860c8d0df71e0aa826f4d2690713e/src/datasets/load.py#L1809
What I can to is break the `load_dataset` and use `load_datset_builder` + `download_and_prepare` instead.
### Steps to reproduce the bug
https://github.com/huggingface/datasets/blo... | 37 | Why max_shard_size is not supported in load_dataset and passed to download_and_prepare
### Describe the bug
https://github.com/huggingface/datasets/blob/a8a797cc92e860c8d0df71e0aa826f4d2690713e/src/datasets/load.py#L1809
What I can to is break the `load_dataset` and use `load_datset_builder` + `download_and_prepa... | [
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0.11105682700... |
https://github.com/huggingface/datasets/issues/5987 | Why max_shard_size is not supported in load_dataset and passed to download_and_prepare | Thanks. So if I want to use `IterableDataset` and control the size of single arrow file, how should I organize the data loader? Maybe `load_dataset_build` + `download_and_prepare` + `builder.as_dataset` + `dataset.to_iterable_dataset`? | ### Describe the bug
https://github.com/huggingface/datasets/blob/a8a797cc92e860c8d0df71e0aa826f4d2690713e/src/datasets/load.py#L1809
What I can to is break the `load_dataset` and use `load_datset_builder` + `download_and_prepare` instead.
### Steps to reproduce the bug
https://github.com/huggingface/datasets/blo... | 31 | Why max_shard_size is not supported in load_dataset and passed to download_and_prepare
### Describe the bug
https://github.com/huggingface/datasets/blob/a8a797cc92e860c8d0df71e0aa826f4d2690713e/src/datasets/load.py#L1809
What I can to is break the `load_dataset` and use `load_datset_builder` + `download_and_prepa... | [
-0.3947969377040863,
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0.2065712809562683,
-0.006453440524637699,
-0.10002316534519196,
-0.12214674800634384,
0.3273208737... |
https://github.com/huggingface/datasets/issues/5987 | Why max_shard_size is not supported in load_dataset and passed to download_and_prepare | Yes, this should work.
I think we can expose `max_shard_size` in `load_dataset`, so feel free to open a PR. | ### Describe the bug
https://github.com/huggingface/datasets/blob/a8a797cc92e860c8d0df71e0aa826f4d2690713e/src/datasets/load.py#L1809
What I can to is break the `load_dataset` and use `load_datset_builder` + `download_and_prepare` instead.
### Steps to reproduce the bug
https://github.com/huggingface/datasets/blo... | 19 | Why max_shard_size is not supported in load_dataset and passed to download_and_prepare
### Describe the bug
https://github.com/huggingface/datasets/blob/a8a797cc92e860c8d0df71e0aa826f4d2690713e/src/datasets/load.py#L1809
What I can to is break the `load_dataset` and use `load_datset_builder` + `download_and_prepa... | [
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0.24466393887996674,
-0.04459383338689804,
-0.10497264564037323,
0.028703942894935608,
0.31513512134... |
https://github.com/huggingface/datasets/issues/5985 | Cannot reuse tokenizer object for dataset map | This is a known issue: https://github.com/huggingface/datasets/issues/3847.
Fixing this requires significant work - rewriting the `tokenizers` lib to make them immutable.
The current solution is to pass `cache_file_name` to `map` to use that file for caching or calling a tokenizer before `map` (with the same set ... | ### Describe the bug
Related to https://github.com/huggingface/transformers/issues/24441. Not sure if this is a tokenizer issue or caching issue, so filing in both.
Passing the tokenizer to the dataset map function causes the tokenizer to be fingerprinted weirdly. After calling the tokenizer with arguments like pad... | 54 | Cannot reuse tokenizer object for dataset map
### Describe the bug
Related to https://github.com/huggingface/transformers/issues/24441. Not sure if this is a tokenizer issue or caching issue, so filing in both.
Passing the tokenizer to the dataset map function causes the tokenizer to be fingerprinted weirdly. Aft... | [
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https://github.com/huggingface/datasets/issues/5984 | AutoSharding IterableDataset's when num_workers > 1 | For this to be possible, we would have to switch from the "Streaming" Arrow format to the "Random Access" (IPC/Feather) format, which allows reading arbitrary record batches (explained [here](https://arrow.apache.org/docs/python/ipc.html)). We could then use these batches to construct shards.
@lhoestq @albertvillano... | ### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
Too many dataloader workers: 2 (max is dataset.n_shard... | 86 | AutoSharding IterableDataset's when num_workers > 1
### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
... | [
-0.4180947244167328,
-0.1018841415643692,
-0.1456301063299179,
0.07439683377742767,
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0.6748948693275452,
0.18633094429969788,
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0.19728821516036987,
0.0617266446352005,
0.15588414669036865,
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-0.268018305301666... |
https://github.com/huggingface/datasets/issues/5984 | AutoSharding IterableDataset's when num_workers > 1 | Alternatively we could support multiprocessing map for iterable datasets and let the user do the CPU intensive task there ?
This way it would work on arrow data but also on any iterable dataset | ### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
Too many dataloader workers: 2 (max is dataset.n_shard... | 34 | AutoSharding IterableDataset's when num_workers > 1
### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
... | [
-0.4086936414241791,
-0.19826120138168335,
-0.14433157444000244,
0.12288492918014526,
-0.23263712227344513,
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0.595722496509552,
0.1270076483488083,
-0.023237178102135658,
0.24934926629066467,
0.1239146962761879,
0.30391815304756165,
-0.30772507190704346,
-0.149492308497... |
https://github.com/huggingface/datasets/issues/5984 | AutoSharding IterableDataset's when num_workers > 1 | > For this to be possible, we would have to switch from the "Streaming" Arrow format to the "Random Access" (IPC/Feather) format, which allows reading arbitrary record batches (explained [here](https://arrow.apache.org/docs/python/ipc.html)). We could then use these batches to construct shards.
>
> @lhoestq @albertv... | ### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
Too many dataloader workers: 2 (max is dataset.n_shard... | 166 | AutoSharding IterableDataset's when num_workers > 1
### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
... | [
-0.41506555676460266,
-0.11562807857990265,
-0.14575710892677307,
0.08082850277423859,
-0.2902185916900635,
-0.17778006196022034,
0.6815128326416016,
0.20298537611961365,
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0.19864997267723083,
0.05041089653968811,
0.16098451614379883,
-0.2835124433040619,
-0.2805774509... |
https://github.com/huggingface/datasets/issues/5984 | AutoSharding IterableDataset's when num_workers > 1 | > Could you explain why you'd need to change the arrow format?
This way workers have random access to the location of the file where its dataset subset starts. Currently we're using the Arrow streaming format which doesn't include the metadata of the record batches offsets. This is needed here to efficiently split a... | ### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
Too many dataloader workers: 2 (max is dataset.n_shard... | 60 | AutoSharding IterableDataset's when num_workers > 1
### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
... | [
-0.4426667392253876,
-0.20271041989326477,
-0.12075890600681305,
0.07688793540000916,
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0.6777271032333374,
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0.24222159385681152,
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https://github.com/huggingface/datasets/issues/5984 | AutoSharding IterableDataset's when num_workers > 1 | > > Could you explain why you'd need to change the arrow format?
>
> This way workers have random access to the location of the file where its dataset subset starts. Currently we're using the Arrow streaming format which doesn't include the metadata of the record batches offsets. This is needed here to efficiently s... | ### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
Too many dataloader workers: 2 (max is dataset.n_shard... | 158 | AutoSharding IterableDataset's when num_workers > 1
### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
... | [
-0.4670998454093933,
-0.17912635207176208,
-0.11632892489433289,
0.049152862280607224,
-0.2605697512626648,
-0.1728026121854782,
0.6774321794509888,
0.16799156367778778,
-0.0823461264371872,
0.2368314266204834,
0.11716002970933914,
0.24954700469970703,
-0.23069214820861816,
-0.202722176909... |
https://github.com/huggingface/datasets/issues/5984 | AutoSharding IterableDataset's when num_workers > 1 | > For instance, using pyArrow, you could use RecordBatchStreamReader to zero-copy iterate over records with read_next_batch and then only initiate the next step for records modulo worker shard.
That works indeed ! And what we meant is that you can make it even faster to instantiate. Indeed using RecordBatchStreamRea... | ### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
Too many dataloader workers: 2 (max is dataset.n_shard... | 110 | AutoSharding IterableDataset's when num_workers > 1
### Feature request
Minimal Example
```
import torch
from datasets import IterableDataset
d = IterableDataset.from_file(<file_name>)
dl = torch.utils.data.dataloader.DataLoader(d,num_workers=3)
for sample in dl:
print(sample)
```
Warning:
... | [
-0.5463468432426453,
-0.06826039403676987,
-0.12397490441799164,
0.021309081465005875,
-0.28132373094558716,
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0.6526509523391724,
0.1736842691898346,
0.033735036849975586,
0.2698054015636444,
0.10144916921854019,
0.2158355414867401,
-0.35457417368888855,
-0.25760689377... |
https://github.com/huggingface/datasets/issues/5982 | 404 on Datasets Documentation Page | This wasn’t working for me a bit earlier, but it looks to be back up now | ### Describe the bug
Getting a 404 from the Hugging Face Datasets docs page:
https://huggingface.co/docs/datasets/index
### Steps to reproduce the bug
1. Go to URL https://huggingface.co/docs/datasets/index
2. Notice 404 not found
### Expected behavior
URL should either show docs or redirect to new location
#... | 16 | 404 on Datasets Documentation Page
### Describe the bug
Getting a 404 from the Hugging Face Datasets docs page:
https://huggingface.co/docs/datasets/index
### Steps to reproduce the bug
1. Go to URL https://huggingface.co/docs/datasets/index
2. Notice 404 not found
### Expected behavior
URL should either sho... | [
0.23589254915714264,
-0.0897054374217987,
-0.03821307420730591,
0.1904316544532776,
0.17235994338989258,
0.229668527841568,
0.03032407909631729,
0.17348486185073853,
-0.08624786883592606,
0.11428413540124893,
-0.048721104860305786,
-0.02713678404688835,
-0.05816887319087982,
0.071298532187... |
https://github.com/huggingface/datasets/issues/5982 | 404 on Datasets Documentation Page | We had a minor issue updating the docs after the latest release. It should work now :). | ### Describe the bug
Getting a 404 from the Hugging Face Datasets docs page:
https://huggingface.co/docs/datasets/index
### Steps to reproduce the bug
1. Go to URL https://huggingface.co/docs/datasets/index
2. Notice 404 not found
### Expected behavior
URL should either show docs or redirect to new location
#... | 17 | 404 on Datasets Documentation Page
### Describe the bug
Getting a 404 from the Hugging Face Datasets docs page:
https://huggingface.co/docs/datasets/index
### Steps to reproduce the bug
1. Go to URL https://huggingface.co/docs/datasets/index
2. Notice 404 not found
### Expected behavior
URL should either sho... | [
0.17083492875099182,
-0.21462565660476685,
-0.02505417726933956,
0.2500724792480469,
0.152494877576828,
0.20869526267051697,
0.030402973294258118,
0.18846730887889862,
-0.06417588889598846,
0.19951122999191284,
-0.07982710003852844,
0.026617802679538727,
-0.0725262463092804,
0.153938904404... |
https://github.com/huggingface/datasets/issues/5981 | Only two cores are getting used in sagemaker with pytorch 3.10 kernel | I think it's more likely that this issue is related to PyTorch than Datasets, as PyTorch (on import) registers functions to execute when forking a process. Maybe this is the culprit: https://github.com/pytorch/pytorch/issues/99625 | ### Describe the bug
When using the newer pytorch 3.10 kernel, only 2 cores are being used by huggingface filter and map functions. The Pytorch 3.9 kernel would use as many cores as specified in the num_proc field.
We have solved this in our own code by placing the following snippet in the code that is called insi... | 32 | Only two cores are getting used in sagemaker with pytorch 3.10 kernel
### Describe the bug
When using the newer pytorch 3.10 kernel, only 2 cores are being used by huggingface filter and map functions. The Pytorch 3.9 kernel would use as many cores as specified in the num_proc field.
We have solved this in our o... | [
-0.16755035519599915,
-0.6986504197120667,
-0.006346721202135086,
0.34194016456604004,
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0.1730157881975174,
0.061168983578681946,
0.3615242838859558,
0.22394250333309174,
-0.09223693609237671,
0.6258038282394409,
0.17458605766296387,
0.04712958633... |
https://github.com/huggingface/datasets/issues/5981 | Only two cores are getting used in sagemaker with pytorch 3.10 kernel | From reading that ticket, it may be down in mkl? Is it worth hotfixing in the meantime, with the express intention of turning it off? I know that's a horribly crufty solution, but it's also deeply frustrating to be limited to 2 cores for operations as simple as filtration. | ### Describe the bug
When using the newer pytorch 3.10 kernel, only 2 cores are being used by huggingface filter and map functions. The Pytorch 3.9 kernel would use as many cores as specified in the num_proc field.
We have solved this in our own code by placing the following snippet in the code that is called insi... | 49 | Only two cores are getting used in sagemaker with pytorch 3.10 kernel
### Describe the bug
When using the newer pytorch 3.10 kernel, only 2 cores are being used by huggingface filter and map functions. The Pytorch 3.9 kernel would use as many cores as specified in the num_proc field.
We have solved this in our o... | [
-0.16755035519599915,
-0.6986504197120667,
-0.006346721202135086,
0.34194016456604004,
-0.08470852673053741,
-0.29069221019744873,
0.1730157881975174,
0.061168983578681946,
0.3615242838859558,
0.22394250333309174,
-0.09223693609237671,
0.6258038282394409,
0.17458605766296387,
0.04712958633... |
https://github.com/huggingface/datasets/issues/5981 | Only two cores are getting used in sagemaker with pytorch 3.10 kernel | @mariosasko @mmr-crexi I had the exact same problem on my kubernetes cluster. the datasets subprocess only user 1 and 17 core | ### Describe the bug
When using the newer pytorch 3.10 kernel, only 2 cores are being used by huggingface filter and map functions. The Pytorch 3.9 kernel would use as many cores as specified in the num_proc field.
We have solved this in our own code by placing the following snippet in the code that is called insi... | 21 | Only two cores are getting used in sagemaker with pytorch 3.10 kernel
### Describe the bug
When using the newer pytorch 3.10 kernel, only 2 cores are being used by huggingface filter and map functions. The Pytorch 3.9 kernel would use as many cores as specified in the num_proc field.
We have solved this in our o... | [
-0.16755035519599915,
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0.34194016456604004,
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0.6258038282394409,
0.17458605766296387,
0.04712958633... |
https://github.com/huggingface/datasets/issues/5980 | Viewing dataset card returns “502 Bad Gateway” | Yes, it seems to be working now. In case it's helpful, the outage lasted several days. It was failing as late as yesterday morning. | The url is: https://huggingface.co/datasets/Confirm-Labs/pile_ngrams_trigrams
I am able to successfully view the “Files and versions” tab: [Confirm-Labs/pile_ngrams_trigrams at main](https://huggingface.co/datasets/Confirm-Labs/pile_ngrams_trigrams/tree/main)
Any help would be appreciated! Thanks! I hope this is ... | 24 | Viewing dataset card returns “502 Bad Gateway”
The url is: https://huggingface.co/datasets/Confirm-Labs/pile_ngrams_trigrams
I am able to successfully view the “Files and versions” tab: [Confirm-Labs/pile_ngrams_trigrams at main](https://huggingface.co/datasets/Confirm-Labs/pile_ngrams_trigrams/tree/main)
Any h... | [
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0.6164693832... |
https://github.com/huggingface/datasets/issues/5975 | Streaming Dataset behind Proxy - FileNotFoundError | Hi ! can you try to set the upper case environment variables `HTTP_PROXY` and `HTTPS_PROXY` ?
We use `aiohttp` for streaming and it uses case sensitive environment variables | ### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure to log in with `huggingface-cli login`.
```
I hav... | 28 | Streaming Dataset behind Proxy - FileNotFoundError
### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure ... | [
-0.20426923036575317,
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0.09346702694892883,
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0.3825293183326721,
0.020822659134864807,
0.13100329041481018,
0.12659212946891785,
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0.13656212389469147,
0.07379933446645737,
-0.17025944590568542,
0.20303985476493835,
0.0988144651... |
https://github.com/huggingface/datasets/issues/5975 | Streaming Dataset behind Proxy - FileNotFoundError | Hi, thanks for the quick reply.
I set the uppercase env variables with
`
os.environ['HTTP_PROXY'] = "http://example.com:xxxx"
os.environ['HTTPS_PROXY'] = "http://example.com:xxxx"
`
However, I still get the same error.
One thing that could be helpfull: When downloading a dataset without streaming i get... | ### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure to log in with `huggingface-cli login`.
```
I hav... | 62 | Streaming Dataset behind Proxy - FileNotFoundError
### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure ... | [
-0.1559554636478424,
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0.39636754989624023,
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0.11199110746383667,
0.07572492957115173,
0.031647346913814545,
0.15219254791736603,
0.08398032933473587,
-0.2124066799879074,
0.17867860198020935,
0.1644149869... |
https://github.com/huggingface/datasets/issues/5975 | Streaming Dataset behind Proxy - FileNotFoundError | Are you able to use `aiohttp` to get the file at `https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json` using your proxy ? | ### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure to log in with `huggingface-cli login`.
```
I hav... | 16 | Streaming Dataset behind Proxy - FileNotFoundError
### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure ... | [
-0.25485289096832275,
-0.0679941326379776,
0.09301556646823883,
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0.3035862445831299,
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0.1310207098722458,
0.15154777467250824,
0.00972307100892067,
0.11705359071493149,
0.04780633747577667,
-0.19018323719501495,
0.24057243764400482,
0.158457413315... |
https://github.com/huggingface/datasets/issues/5975 | Streaming Dataset behind Proxy - FileNotFoundError | It only works when passing trust_env=True when creating the ClientSession, as well as setting ssl=False.
Working Example:
```
import os
os.environ['HTTP_PROXY'] = "xyz"
os.environ['HTTPS_PROXY'] = "xyz"
import asyncio
import aiohttp
async def download_pep(url):
async with aiohttp.ClientSession(tr... | ### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure to log in with `huggingface-cli login`.
```
I hav... | 98 | Streaming Dataset behind Proxy - FileNotFoundError
### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure ... | [
-0.28758227825164795,
0.02724406123161316,
0.11844801902770996,
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0.3153189420700073,
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0.21909654140472412,
0.13560570776462555,
0.06980398297309875,
0.1013474389910698,
0.01768678054213524,
-0.15127579867839813,
0.30918818712234497,
0.1033062860369... |
https://github.com/huggingface/datasets/issues/5975 | Streaming Dataset behind Proxy - FileNotFoundError | We do pass `trust_env` as well. Could you share the full stack trace you get when streaming using `datasets` ? That could help locate where we might have forgotten to pass `trust_env` | ### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure to log in with `huggingface-cli login`.
```
I hav... | 32 | Streaming Dataset behind Proxy - FileNotFoundError
### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure ... | [
-0.2205500453710556,
-0.04736749082803726,
0.09124645590782166,
-0.10017770528793335,
0.3697274923324585,
-0.011571042239665985,
0.10142414271831512,
0.1315038651227951,
0.010005585849285126,
0.11178182810544968,
0.09104399383068085,
-0.15345293283462524,
0.20461544394493103,
0.12523008882... |
https://github.com/huggingface/datasets/issues/5975 | Streaming Dataset behind Proxy - FileNotFoundError | Is there a way to disable ssl verification when streaming a dataset. I suspect this might be the isssue with my proxy.
Here you go:
```
FileNotFoundError Traceback (most recent call last)
Cell In[8], line 3
1 from datasets import load_dataset
----> 3 ds = load_dataset("facebook... | ### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure to log in with `huggingface-cli login`.
```
I hav... | 282 | Streaming Dataset behind Proxy - FileNotFoundError
### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure ... | [
-0.24882738292217255,
-0.05979369580745697,
0.10071597993373871,
-0.1020842045545578,
0.24106338620185852,
-0.006721943616867065,
0.1711813509464264,
0.06702056527137756,
-0.02042454108595848,
0.12281379103660583,
0.11307927221059799,
-0.21383555233478546,
0.2762971520423889,
0.00673388876... |
https://github.com/huggingface/datasets/issues/5975 | Streaming Dataset behind Proxy - FileNotFoundError | > Is there a way to disable ssl verification when streaming a dataset.
I don't think so.
We use `fsspec` HTTPFileSystem implementation that is based on `aiohttp`. If you register a subclass of HTTPFileSystem that has SSL disabled by default it could work, but I wouldn't recommended it because it can raise securit... | ### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure to log in with `huggingface-cli login`.
```
I hav... | 54 | Streaming Dataset behind Proxy - FileNotFoundError
### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure ... | [
-0.2545451819896698,
-0.015846043825149536,
0.1071447879076004,
-0.10625253617763519,
0.23831477761268616,
-0.01865294575691223,
0.13900771737098694,
0.0758848488330841,
0.08188807964324951,
0.13150744140148163,
0.12248232960700989,
-0.24985411763191223,
0.3034822344779968,
0.1700652241706... |
https://github.com/huggingface/datasets/issues/5975 | Streaming Dataset behind Proxy - FileNotFoundError | Okay thanks for your help! I guess I have to figure out how to improve the proxy environment / see if I can make it work with ssl connections. | ### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure to log in with `huggingface-cli login`.
```
I hav... | 29 | Streaming Dataset behind Proxy - FileNotFoundError
### Describe the bug
When trying to stream a dataset i get the following error after a few minutes of waiting.
```
FileNotFoundError: https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/n_files.json
If the repo is private or gated, make sure ... | [
-0.22630561888217926,
-0.08385402709245682,
0.0878797322511673,
-0.11146001517772675,
0.3125814199447632,
-0.019106566905975342,
0.11751818656921387,
0.11087314784526825,
-0.0013585686683654785,
0.05213019251823425,
0.09835315495729446,
-0.17861925065517426,
0.2117951214313507,
0.142906606... |
https://github.com/huggingface/datasets/issues/5971 | Docs: make "repository structure" easier to find | Loading a local dataset also works the same way when `data_files` are not specified, so I agree we should make this info easier to discover
cc @stevhliu | The page https://huggingface.co/docs/datasets/repository_structure explains how to create a simple repository structure without a dataset script.
It's the simplest way to create a dataset and should be easier to find, particularly on the docs' first pages. | 27 | Docs: make "repository structure" easier to find
The page https://huggingface.co/docs/datasets/repository_structure explains how to create a simple repository structure without a dataset script.
It's the simplest way to create a dataset and should be easier to find, particularly on the docs' first pages.
Loading a... | [
-0.23497644066810608,
0.09987041354179382,
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0.3153049349784851,
0.13123160600662231,
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0.5910804867744446,
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0.1766022890806198,
0.1995178908109665,
0.22822009027004... |
https://github.com/huggingface/datasets/issues/5971 | Docs: make "repository structure" easier to find | @benjaminbrown038 Yes, it is. Maybe @stevhliu can give some pointers on improving this doc page's discoverability. | The page https://huggingface.co/docs/datasets/repository_structure explains how to create a simple repository structure without a dataset script.
It's the simplest way to create a dataset and should be easier to find, particularly on the docs' first pages. | 16 | Docs: make "repository structure" easier to find
The page https://huggingface.co/docs/datasets/repository_structure explains how to create a simple repository structure without a dataset script.
It's the simplest way to create a dataset and should be easier to find, particularly on the docs' first pages.
@benjamin... | [
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0.16898560523986816,
0.09326280653476715,
0.14402465522289... |
https://github.com/huggingface/datasets/issues/5971 | Docs: make "repository structure" easier to find | I think we can add a version of the [Main use-case](https://huggingface.co/docs/datasets/repository_structure#main-usecase) section to the [Share a dataset to the Hub](https://huggingface.co/docs/datasets/upload_dataset) tutorial.
Currently, it doesn't tell you *how* to structure the repository; it only tells you h... | The page https://huggingface.co/docs/datasets/repository_structure explains how to create a simple repository structure without a dataset script.
It's the simplest way to create a dataset and should be easier to find, particularly on the docs' first pages. | 77 | Docs: make "repository structure" easier to find
The page https://huggingface.co/docs/datasets/repository_structure explains how to create a simple repository structure without a dataset script.
It's the simplest way to create a dataset and should be easier to find, particularly on the docs' first pages.
I think w... | [
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0.284512460231... |
https://github.com/huggingface/datasets/issues/5970 | description disappearing from Info when Uploading a Dataset Created with `from_dict` | Here's a minimal way to reproduce the bug, for the sake of convenience.
````
from datasets import Dataset, DatasetInfo, load_dataset
episodes_dict = {"test":[1,2,3],"test2": [1,2,4]}
hugging_face_dataset = Dataset.from_dict(
episodes_dict, info=DatasetInfo(description="test_str")
)
print(hugging_face_d... | ### Describe the bug
When uploading a dataset created locally using `from_dict` with a specified `description` field. It appears before upload, but is missing after upload and re-download.
### Steps to reproduce the bug
I think the most relevant pattern in the code might be the following lines:
```
descr... | 37 | description disappearing from Info when Uploading a Dataset Created with `from_dict`
### Describe the bug
When uploading a dataset created locally using `from_dict` with a specified `description` field. It appears before upload, but is missing after upload and re-download.
### Steps to reproduce the bug
I ... | [
0.20387275516986847,
0.06310252845287323,
0.08928710222244263,
0.23943349719047546,
0.43252241611480713,
-0.08675282448530197,
0.1411249190568924,
0.22590771317481995,
-0.4692801237106323,
0.09071235358715057,
0.34117433428764343,
0.14465253055095673,
0.31798192858695984,
0.362377464771270... |
https://github.com/huggingface/datasets/issues/5970 | description disappearing from Info when Uploading a Dataset Created with `from_dict` | Thanks for reporting !
For now I would recommend uploading a separate JSON file for your metadata.
Alternatively you can upload a second configuration of the dataset containing your metadata but this feature is not released yet (though you can already use it from [here](https://github.com/huggingface/datasets/pul... | ### Describe the bug
When uploading a dataset created locally using `from_dict` with a specified `description` field. It appears before upload, but is missing after upload and re-download.
### Steps to reproduce the bug
I think the most relevant pattern in the code might be the following lines:
```
descr... | 50 | description disappearing from Info when Uploading a Dataset Created with `from_dict`
### Describe the bug
When uploading a dataset created locally using `from_dict` with a specified `description` field. It appears before upload, but is missing after upload and re-download.
### Steps to reproduce the bug
I ... | [
0.20387275516986847,
0.06310252845287323,
0.08928710222244263,
0.23943349719047546,
0.43252241611480713,
-0.08675282448530197,
0.1411249190568924,
0.22590771317481995,
-0.4692801237106323,
0.09071235358715057,
0.34117433428764343,
0.14465253055095673,
0.31798192858695984,
0.362377464771270... |
https://github.com/huggingface/datasets/issues/5968 | Common Voice datasets still need `use_auth_token=True` | The issue commes from the dataset itself and is not related to the `datasets` lib
see https://huggingface.co/datasets/mozilla-foundation/common_voice_6_1/blob/2c475b3b88e0f2e5828f830a4b91618a25ff20b7/common_voice_6_1.py#L148-L152 | ### Describe the bug
We don't need to pass `use_auth_token=True` anymore to download gated datasets or models, so the following should work if correctly logged in.
```py
from datasets import load_dataset
load_dataset("mozilla-foundation/common_voice_6_1", "tr", split="train+validation")
```
However it throw... | 17 | Common Voice datasets still need `use_auth_token=True`
### Describe the bug
We don't need to pass `use_auth_token=True` anymore to download gated datasets or models, so the following should work if correctly logged in.
```py
from datasets import load_dataset
load_dataset("mozilla-foundation/common_voice_6_1",... | [
-0.1996699571609497,
0.011859729886054993,
0.15256021916866302,
-0.005796566605567932,
0.4470815658569336,
0.052654512226581573,
0.5136600732803345,
0.12041829526424408,
0.031704582273960114,
-0.0473194420337677,
-0.5297960042953491,
0.04294753074645996,
0.03492225334048271,
-0.02998283132... |
https://github.com/huggingface/datasets/issues/5968 | Common Voice datasets still need `use_auth_token=True` | Addressed in:
* `mozilla-foundation/common_voice_1_0` [PR](https://huggingface.co/datasets/mozilla-foundation/common_voice_1_0/discussions/4)
* `mozilla-foundation/common_voice_2_0` [PR](https://huggingface.co/datasets/mozilla-foundation/common_voice_2_0/discussions/3)
* `mozilla-foundation/common_voice_3_0` [PR](... | ### Describe the bug
We don't need to pass `use_auth_token=True` anymore to download gated datasets or models, so the following should work if correctly logged in.
```py
from datasets import load_dataset
load_dataset("mozilla-foundation/common_voice_6_1", "tr", split="train+validation")
```
However it throw... | 38 | Common Voice datasets still need `use_auth_token=True`
### Describe the bug
We don't need to pass `use_auth_token=True` anymore to download gated datasets or models, so the following should work if correctly logged in.
```py
from datasets import load_dataset
load_dataset("mozilla-foundation/common_voice_6_1",... | [
-0.1996699571609497,
0.011859729886054993,
0.15256021916866302,
-0.005796566605567932,
0.4470815658569336,
0.052654512226581573,
0.5136600732803345,
0.12041829526424408,
0.031704582273960114,
-0.0473194420337677,
-0.5297960042953491,
0.04294753074645996,
0.03492225334048271,
-0.02998283132... |
https://github.com/huggingface/datasets/issues/5967 | Config name / split name lost after map with multiproc | This must be due to DatasetInfo.from_merge which drops them and is used in `concatenate_datasets`.
And you're experiencing this issue because multiprocessing does concatenate the resulting datasets from each process.
Maybe they should be kept if all the subdatasets share the same values for config_name and split | ### Describe the bug
Performing a `.map` method on a dataset loses it's config name / split name only if run with multiproc
### Steps to reproduce the bug
```python
from datasets import Audio, load_dataset
from transformers import AutoFeatureExtractor
import numpy as np
# load dummy dataset
libri = load_datas... | 46 | Config name / split name lost after map with multiproc
### Describe the bug
Performing a `.map` method on a dataset loses it's config name / split name only if run with multiproc
### Steps to reproduce the bug
```python
from datasets import Audio, load_dataset
from transformers import AutoFeatureExtractor
impor... | [
-0.3114314675331116,
-0.3305574655532837,
0.0021505169570446014,
0.09281017631292343,
0.29288196563720703,
-0.11196540296077728,
0.5943196415901184,
0.1308251917362213,
-0.08384805172681808,
0.6229398846626282,
0.04151303321123123,
0.5787533521652222,
-0.13195466995239258,
0.30740663409233... |
https://github.com/huggingface/datasets/issues/5965 | "Couldn't cast array of type" in complex datasets | Thanks for reporting!
Specifying the target features explicitly should avoid this error:
```python
dataset = dataset.map(
batch_process,
batched=True,
batch_size=1,
num_proc=1,
remove_columns=dataset.column_names,
features=datasets.Features({"texts": datasets.Sequence(datasets.Value(... | ### Describe the bug
When doing a map of a dataset with complex types, sometimes `datasets` is unable to interpret the valid schema of a returned datasets.map() function. This often comes from conflicting types, like when both empty lists and filled lists are competing for the same field value.
This is prone to hap... | 61 | "Couldn't cast array of type" in complex datasets
### Describe the bug
When doing a map of a dataset with complex types, sometimes `datasets` is unable to interpret the valid schema of a returned datasets.map() function. This often comes from conflicting types, like when both empty lists and filled lists are competi... | [
-0.39829856157302856,
-0.05690281093120575,
-0.040337610989809036,
0.17765285074710846,
0.4318234324455261,
0.22664892673492432,
0.3325989246368408,
0.331497460603714,
0.37672656774520874,
-0.01937851309776306,
0.023040397092700005,
0.34318873286247253,
-0.15088239312171936,
0.024865319952... |
https://github.com/huggingface/datasets/issues/5965 | "Couldn't cast array of type" in complex datasets | Hi @mariosasko thanks for the context, this is helpful to know. Would it be worth having some logic to generate this explicit feature specification automatically if a type annotation for a .map returns a dataclass that can be inferred?
Feels like something that would be easy to implement and could save memory / deal... | ### Describe the bug
When doing a map of a dataset with complex types, sometimes `datasets` is unable to interpret the valid schema of a returned datasets.map() function. This often comes from conflicting types, like when both empty lists and filled lists are competing for the same field value.
This is prone to hap... | 61 | "Couldn't cast array of type" in complex datasets
### Describe the bug
When doing a map of a dataset with complex types, sometimes `datasets` is unable to interpret the valid schema of a returned datasets.map() function. This often comes from conflicting types, like when both empty lists and filled lists are competi... | [
-0.39829856157302856,
-0.05690281093120575,
-0.040337610989809036,
0.17765285074710846,
0.4318234324455261,
0.22664892673492432,
0.3325989246368408,
0.331497460603714,
0.37672656774520874,
-0.01937851309776306,
0.023040397092700005,
0.34318873286247253,
-0.15088239312171936,
0.024865319952... |
https://github.com/huggingface/datasets/issues/5965 | "Couldn't cast array of type" in complex datasets | > . Would it be worth having some logic to generate this explicit feature specification automatically if a type annotation for a .map returns a dataclass that can be inferred?
Interesting proposal! Yes, we could consider doing this if the (return) type hint is `TypedDict`, and raise an error that type hints are inco... | ### Describe the bug
When doing a map of a dataset with complex types, sometimes `datasets` is unable to interpret the valid schema of a returned datasets.map() function. This often comes from conflicting types, like when both empty lists and filled lists are competing for the same field value.
This is prone to hap... | 62 | "Couldn't cast array of type" in complex datasets
### Describe the bug
When doing a map of a dataset with complex types, sometimes `datasets` is unable to interpret the valid schema of a returned datasets.map() function. This often comes from conflicting types, like when both empty lists and filled lists are competi... | [
-0.39829856157302856,
-0.05690281093120575,
-0.040337610989809036,
0.17765285074710846,
0.4318234324455261,
0.22664892673492432,
0.3325989246368408,
0.331497460603714,
0.37672656774520874,
-0.01937851309776306,
0.023040397092700005,
0.34318873286247253,
-0.15088239312171936,
0.024865319952... |
https://github.com/huggingface/datasets/issues/5965 | "Couldn't cast array of type" in complex datasets | @mariosasko Put up an initial PR to implement this proposal. Let me know your thoughts on direction and what else should be in-scope here. | ### Describe the bug
When doing a map of a dataset with complex types, sometimes `datasets` is unable to interpret the valid schema of a returned datasets.map() function. This often comes from conflicting types, like when both empty lists and filled lists are competing for the same field value.
This is prone to hap... | 24 | "Couldn't cast array of type" in complex datasets
### Describe the bug
When doing a map of a dataset with complex types, sometimes `datasets` is unable to interpret the valid schema of a returned datasets.map() function. This often comes from conflicting types, like when both empty lists and filled lists are competi... | [
-0.39829856157302856,
-0.05690281093120575,
-0.040337610989809036,
0.17765285074710846,
0.4318234324455261,
0.22664892673492432,
0.3325989246368408,
0.331497460603714,
0.37672656774520874,
-0.01937851309776306,
0.023040397092700005,
0.34318873286247253,
-0.15088239312171936,
0.024865319952... |
https://github.com/huggingface/datasets/issues/5963 | Got an error _pickle.PicklingError use Dataset.from_spark. | i got error using method from_spark when using multi-node Spark cluster. seems could only use "from_spark" in local? | python 3.9.2
Got an error _pickle.PicklingError use Dataset.from_spark.
Did the dataset import load data from spark dataframe using multi-node Spark cluster
df = spark.read.parquet(args.input_data).repartition(50)
ds = Dataset.from_spark(df, keep_in_memory=True,
cache_dir="... | 18 | Got an error _pickle.PicklingError use Dataset.from_spark.
python 3.9.2
Got an error _pickle.PicklingError use Dataset.from_spark.
Did the dataset import load data from spark dataframe using multi-node Spark cluster
df = spark.read.parquet(args.input_data).repartition(50)
ds = Dataset.from_spark... | [
-0.48843836784362793,
-0.16567078232765198,
0.023851748555898666,
0.34239310026168823,
0.2954638600349426,
-0.00167025625705719,
0.5267862677574158,
0.13773883879184723,
0.08715450763702393,
0.09700313955545425,
0.08231282234191895,
0.6951185464859009,
-0.18221792578697205,
0.5347052812576... |
https://github.com/huggingface/datasets/issues/5963 | Got an error _pickle.PicklingError use Dataset.from_spark. | cc @maddiedawson it looks like there an issue with `_validate_cache_dir` ?
It looks like the function passed to mapPartitions has a reference to the Spark dataset builder, and therefore contains the SparkContext itself.
I think it can be fixed by defining `create_cache_and_write_probe` outside the Spark dataset b... | python 3.9.2
Got an error _pickle.PicklingError use Dataset.from_spark.
Did the dataset import load data from spark dataframe using multi-node Spark cluster
df = spark.read.parquet(args.input_data).repartition(50)
ds = Dataset.from_spark(df, keep_in_memory=True,
cache_dir="... | 54 | Got an error _pickle.PicklingError use Dataset.from_spark.
python 3.9.2
Got an error _pickle.PicklingError use Dataset.from_spark.
Did the dataset import load data from spark dataframe using multi-node Spark cluster
df = spark.read.parquet(args.input_data).repartition(50)
ds = Dataset.from_spark... | [
-0.48843836784362793,
-0.16567078232765198,
0.023851748555898666,
0.34239310026168823,
0.2954638600349426,
-0.00167025625705719,
0.5267862677574158,
0.13773883879184723,
0.08715450763702393,
0.09700313955545425,
0.08231282234191895,
0.6951185464859009,
-0.18221792578697205,
0.5347052812576... |
https://github.com/huggingface/datasets/issues/5963 | Got an error _pickle.PicklingError use Dataset.from_spark. | Just saw this; thanks for flagging! Your proposed solution sounds good. I can prepare a PR | python 3.9.2
Got an error _pickle.PicklingError use Dataset.from_spark.
Did the dataset import load data from spark dataframe using multi-node Spark cluster
df = spark.read.parquet(args.input_data).repartition(50)
ds = Dataset.from_spark(df, keep_in_memory=True,
cache_dir="... | 16 | Got an error _pickle.PicklingError use Dataset.from_spark.
python 3.9.2
Got an error _pickle.PicklingError use Dataset.from_spark.
Did the dataset import load data from spark dataframe using multi-node Spark cluster
df = spark.read.parquet(args.input_data).repartition(50)
ds = Dataset.from_spark... | [
-0.48843836784362793,
-0.16567078232765198,
0.023851748555898666,
0.34239310026168823,
0.2954638600349426,
-0.00167025625705719,
0.5267862677574158,
0.13773883879184723,
0.08715450763702393,
0.09700313955545425,
0.08231282234191895,
0.6951185464859009,
-0.18221792578697205,
0.5347052812576... |
https://github.com/huggingface/datasets/issues/5963 | Got an error _pickle.PicklingError use Dataset.from_spark. | @maddiedawson can you show me the demo ,so i can test in local .before your PR | python 3.9.2
Got an error _pickle.PicklingError use Dataset.from_spark.
Did the dataset import load data from spark dataframe using multi-node Spark cluster
df = spark.read.parquet(args.input_data).repartition(50)
ds = Dataset.from_spark(df, keep_in_memory=True,
cache_dir="... | 16 | Got an error _pickle.PicklingError use Dataset.from_spark.
python 3.9.2
Got an error _pickle.PicklingError use Dataset.from_spark.
Did the dataset import load data from spark dataframe using multi-node Spark cluster
df = spark.read.parquet(args.input_data).repartition(50)
ds = Dataset.from_spark... | [
-0.48843836784362793,
-0.16567078232765198,
0.023851748555898666,
0.34239310026168823,
0.2954638600349426,
-0.00167025625705719,
0.5267862677574158,
0.13773883879184723,
0.08715450763702393,
0.09700313955545425,
0.08231282234191895,
0.6951185464859009,
-0.18221792578697205,
0.5347052812576... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | Does "number of shards" refer to the total number of data?
my config:
nproc_per_node=2
ds=ds['train'] = load_dataset(streaming=True).take(50000)
I'm test again: in prepare_data(), data have the same for each GPU
| There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 29 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the ... | [
-0.44223564863204956,
-0.3692322373390198,
-0.06835253536701202,
0.27588194608688354,
0.11674242466688156,
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0.3516828715801239,
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0.17232093214988708,
0.05940752476453781,
0.43877509236335754,
0.06595728546380997,
0.3726689815521... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | The number of shards is `ds.n_shards`. It corresponds generally to the number of files the dataset is made of, to be able to distribute to several nodes.
**You don't end up with the same data per GPU**. But all the samples are going through your preprocessing function you pass to map. They are just skipped afterward... | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 64 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the ... | [
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0.24369806051254272,
0.09345457702875137,
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0.1674361228942871,
-0.03845600038766861,
0.46263062953948975,
0.1970851719379425,
0.25770786404609... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | For each GPU, although see the same data in prepare_data(), the actual training data will not be the same in the end.
Is my understanding correct?
Where can I print the actual training data for each GPU? | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 37 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the ... | [
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0.3387421667575836,... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | > For each GPU, although see the same data in prepare_data(), the actual training data will not be the same in the end.
Is my understanding correct?
Yes exactly :)
> Where can I print the actual training data for each GPU?
You should call print in the data_collator | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 49 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the ... | [
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0.41291263699531555,
0.1829586923122406,
0.3521018028259277... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | I print out n_shards, and under multiple GPUs, this value is always 1.
Is this value correct? | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 17 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the ... | [
-0.4411477744579315,
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0.26262927055358887,
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0.09857984632253647,
0.07519344985485077,
0.29676586389541626,
0.17903953790664673,
0.308314651250... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | Yes it's correct, and it explains why you always have the same data passed to your map function (the data can't be split).
But after being passed to `map`, each GPU keeps one example out of n(GPUs) so that you don't end up with duplicate data across GPUs | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 48 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the ... | [
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0.27406230568885803,
0.09119001775979996,
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0.1096988320350647,
-0.0588264986872673,
0.4742526710033417,
0.2462736815214157,
0.3017977178096771,... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | > > For each GPU, although see the same data in prepare_data(), the actual training data will not be the same in the end.
> > Is my understanding correct?
>
> Yes exactly :)
>
> > Where can I print the actual training data for each GPU?
>
> You should call print in the data_collator
OK, when printing the t... | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 77 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the ... | [
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0.11219163239002228,
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0.06556794047355652,
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0.4010586142539978,
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0.37721979618072... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | Do we have a solution for this one? Or it's required to get "number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU" | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 33 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the ... | [
-0.4867708086967468,
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0.20005810260772705,
0.09749096632003784,
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0.38306924700737,
0.24505870044231415,
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0.131986603140831,
0.10013135522603989,
0.3976881206035614,
0.12253999710083008,
0.30259329080581665... |
https://github.com/huggingface/datasets/issues/5961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | For now it's required to have a number of shards that is a factor of the number of GPUs to not have all the workers process the same data (and then skip the right ones to not end up training on duplicate data).
It would be quite complex to implement a strategy that would utilize all the GPUs with an arbitrary number... | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's ... | 70 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway
There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the ... | [
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-0.37352192401885986,
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0.15261653065681458,
0.11911836266517639,
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0.48819032311439514,
0.2550979256629944,
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0.1438957005739212,
0.09474238753318787,
0.3893818259239197,
0.1023450568318367,
0.3299869894981... |
https://github.com/huggingface/datasets/issues/5955 | Strange bug in loading local JSON files, using load_dataset | This is the actual error:
```
Failed to read file '/home/lakala/hjc/code/pycode/glm/temp.json' with error <class 'pyarrow.lib.ArrowInvalid'>: cannot mix list and non-list, non-null values
```
Which means some samples are incorrectly formatted.
PyArrow, a storage backend that we use under the hood, requires that ... | ### Describe the bug
I am using 'load_dataset 'loads a JSON file, but I found a strange bug: an error will be reported when the length of the JSON file exceeds 160000 (uncertain exact number). I have checked the data through the following code and there are no issues. So I cannot determine the true reason for this err... | 84 | Strange bug in loading local JSON files, using load_dataset
### Describe the bug
I am using 'load_dataset 'loads a JSON file, but I found a strange bug: an error will be reported when the length of the JSON file exceeds 160000 (uncertain exact number). I have checked the data through the following code and there are... | [
-0.10791899263858795,
-0.09877708554267883,
-0.045271433889865875,
0.5462534427642822,
0.23800623416900635,
0.1058305874466896,
0.3299548625946045,
0.41471678018569946,
0.4334627091884613,
0.18027372658252716,
0.3069751262664795,
0.35449913144111633,
0.08857838064432144,
-0.136405870318412... |
https://github.com/huggingface/datasets/issues/5955 | Strange bug in loading local JSON files, using load_dataset | @mariosasko
I used the same operation to check the original data before and after slicing.
This is reflected in my code.
160000 is not a specific number.
I can also get output using 150000.
This doesn't seem to align very well with what you said.
Because if only some sample formats are incorrect.
So there shoul... | ### Describe the bug
I am using 'load_dataset 'loads a JSON file, but I found a strange bug: an error will be reported when the length of the JSON file exceeds 160000 (uncertain exact number). I have checked the data through the following code and there are no issues. So I cannot determine the true reason for this err... | 72 | Strange bug in loading local JSON files, using load_dataset
### Describe the bug
I am using 'load_dataset 'loads a JSON file, but I found a strange bug: an error will be reported when the length of the JSON file exceeds 160000 (uncertain exact number). I have checked the data through the following code and there are... | [
-0.10791899263858795,
-0.09877708554267883,
-0.045271433889865875,
0.5462534427642822,
0.23800623416900635,
0.1058305874466896,
0.3299548625946045,
0.41471678018569946,
0.4334627091884613,
0.18027372658252716,
0.3069751262664795,
0.35449913144111633,
0.08857838064432144,
-0.136405870318412... |
https://github.com/huggingface/datasets/issues/5955 | Strange bug in loading local JSON files, using load_dataset | Our JSON loader does the following in your case:
```python
import json
import pyarrow as pa
with open(file, encoding="utf-8") as f:
dataset = json.load(f)
keys = set().union(*[row.keys() for row in dataset])
mapping = {col: [row.get(col) for row in dataset] for col in keys}
pa_table = pa.Table.from_pydi... | ### Describe the bug
I am using 'load_dataset 'loads a JSON file, but I found a strange bug: an error will be reported when the length of the JSON file exceeds 160000 (uncertain exact number). I have checked the data through the following code and there are no issues. So I cannot determine the true reason for this err... | 156 | Strange bug in loading local JSON files, using load_dataset
### Describe the bug
I am using 'load_dataset 'loads a JSON file, but I found a strange bug: an error will be reported when the length of the JSON file exceeds 160000 (uncertain exact number). I have checked the data through the following code and there are... | [
-0.10791899263858795,
-0.09877708554267883,
-0.045271433889865875,
0.5462534427642822,
0.23800623416900635,
0.1058305874466896,
0.3299548625946045,
0.41471678018569946,
0.4334627091884613,
0.18027372658252716,
0.3069751262664795,
0.35449913144111633,
0.08857838064432144,
-0.136405870318412... |
https://github.com/huggingface/datasets/issues/5953 | Bad error message when trying to download gated dataset | cc @sanchit-gandhi @Vaibhavs10 @lhoestq - this is mainly for demos that use Common Voice datasets as done here: https://github.com/facebookresearch/fairseq/tree/main/examples/mms#-transformers
| ### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make sure you specified the correct `repo_id` and `repo_type`.
I... | 19 | Bad error message when trying to download gated dataset
### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make su... | [
-0.29108357429504395,
-0.24233025312423706,
0.11377005279064178,
0.28113341331481934,
0.43997102975845337,
0.13672280311584473,
0.2831527292728424,
0.18023104965686798,
0.020096030086278915,
0.15855523943901062,
-0.41839635372161865,
-0.16160741448402405,
0.038213398307561874,
0.0689690560... |
https://github.com/huggingface/datasets/issues/5953 | Bad error message when trying to download gated dataset | Hi ! the error for me is
```
FileNotFoundError: Couldn't find a dataset script at /content/mozilla-foundation/common_voice_13_0/common_voice_13_0.py or any data file in the same directory. Couldn't find 'mozilla-foundation/common_voice_13_0' on the Hugging Face Hub either: FileNotFoundError: Dataset 'mozilla-founda... | ### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make sure you specified the correct `repo_id` and `repo_type`.
I... | 75 | Bad error message when trying to download gated dataset
### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make su... | [
-0.29108357429504395,
-0.24233025312423706,
0.11377005279064178,
0.28113341331481934,
0.43997102975845337,
0.13672280311584473,
0.2831527292728424,
0.18023104965686798,
0.020096030086278915,
0.15855523943901062,
-0.41839635372161865,
-0.16160741448402405,
0.038213398307561874,
0.0689690560... |
https://github.com/huggingface/datasets/issues/5953 | Bad error message when trying to download gated dataset | Okay, I am able to reproduce @patrickvonplaten's original error: https://github.com/Vaibhavs10/scratchpad/blob/main/cv13_datasets_test.ipynb
Also not sure why it looks for `n_shards.json` | ### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make sure you specified the correct `repo_id` and `repo_type`.
I... | 18 | Bad error message when trying to download gated dataset
### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make su... | [
-0.29108357429504395,
-0.24233025312423706,
0.11377005279064178,
0.28113341331481934,
0.43997102975845337,
0.13672280311584473,
0.2831527292728424,
0.18023104965686798,
0.020096030086278915,
0.15855523943901062,
-0.41839635372161865,
-0.16160741448402405,
0.038213398307561874,
0.0689690560... |
https://github.com/huggingface/datasets/issues/5953 | Bad error message when trying to download gated dataset | Ok I see, this file is downloaded from the CV dataset script - let me investigate | ### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make sure you specified the correct `repo_id` and `repo_type`.
I... | 16 | Bad error message when trying to download gated dataset
### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make su... | [
-0.29108357429504395,
-0.24233025312423706,
0.11377005279064178,
0.28113341331481934,
0.43997102975845337,
0.13672280311584473,
0.2831527292728424,
0.18023104965686798,
0.020096030086278915,
0.15855523943901062,
-0.41839635372161865,
-0.16160741448402405,
0.038213398307561874,
0.0689690560... |
https://github.com/huggingface/datasets/issues/5953 | Bad error message when trying to download gated dataset | Ok I see: when you log out you no longer have access to the repository.
Therefore the dataset script is loaded from cache:
```
WARNING:datasets.load:Using the latest cached version of the module from /root/.cache/huggingface/modules/datasets_modules/datasets/mozilla-foundation--common_voice_13_0/22809012aac1fc9803... | ### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make sure you specified the correct `repo_id` and `repo_type`.
I... | 68 | Bad error message when trying to download gated dataset
### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make su... | [
-0.29108357429504395,
-0.24233025312423706,
0.11377005279064178,
0.28113341331481934,
0.43997102975845337,
0.13672280311584473,
0.2831527292728424,
0.18023104965686798,
0.020096030086278915,
0.15855523943901062,
-0.41839635372161865,
-0.16160741448402405,
0.038213398307561874,
0.0689690560... |
https://github.com/huggingface/datasets/issues/5950 | Support for data with instance-wise dictionary as features | Hi ! We use the Arrow columnar format under the hood, which doesn't support such dictionaries: each field must have a fixed type and exist in each sample.
Instead you can restructure your data like
```
{
"index": 0,
"keys": ["2 * x + y >= 3"],
"values": [["2 * x + y >= 3", "4 * x + 2 * y >= 6"]],
... | ### Feature request
I notice that when loading data instances with feature type of python dictionary, the dictionary keys would be broadcast so that every instance has the same set of keys. Please see an example in the Motivation section.
It is possible to avoid this behavior, i.e., load dictionary features as it i... | 87 | Support for data with instance-wise dictionary as features
### Feature request
I notice that when loading data instances with feature type of python dictionary, the dictionary keys would be broadcast so that every instance has the same set of keys. Please see an example in the Motivation section.
It is possible t... | [
0.195042222738266,
-0.34095367789268494,
0.002453343942761421,
0.29262301325798035,
0.22568663954734802,
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0.29512476921081543,
0.029160384088754654,
0.14267335832118988,
0.20322439074516296,
0.2179422527551651,
0.48196476697921753,
-0.3849047124385834,
0.75595211982727... |
https://github.com/huggingface/datasets/issues/5947 | Return the audio filename when decoding fails due to corrupt files | Hi ! The audio data don't always exist as files on disk - the blobs are often stored in the Arrow files. For now I'd suggest disabling decoding with `.cast_column("audio", Audio(decode=False))` and apply your own decoding that handles corrupted files (maybe to filter them out ?)
cc @sanchit-gandhi since it's related... | ### Feature request
Return the audio filename when the audio decoding fails. Although currently there are some checks for mp3 and opus formats with the library version there are still cases when the audio decoding could fail, eg. Corrupt file.
### Motivation
When you try to load an object file dataset and the... | 71 | Return the audio filename when decoding fails due to corrupt files
### Feature request
Return the audio filename when the audio decoding fails. Although currently there are some checks for mp3 and opus formats with the library version there are still cases when the audio decoding could fail, eg. Corrupt file.
... | [
-0.325080007314682,
0.20622238516807556,
-0.10531541705131531,
0.26571422815322876,
0.1269158124923706,
-0.31680142879486084,
-0.04729922488331795,
0.3888249099254608,
-0.3635145127773285,
0.6399993300437927,
-0.18331077694892883,
0.4741291403770447,
-0.317181259393692,
-0.2232422679662704... |
https://github.com/huggingface/datasets/issues/5947 | Return the audio filename when decoding fails due to corrupt files | Thanks @lhoestq, I wasn't aware of the decode flag. It makes more sense as you say to show a warning when there are corrupted files together with some metadata of the file that allows to filter them from the dataset.
My workaround was to catch the LibsndfileError and generate a dummy audio with an unsual sample rate... | ### Feature request
Return the audio filename when the audio decoding fails. Although currently there are some checks for mp3 and opus formats with the library version there are still cases when the audio decoding could fail, eg. Corrupt file.
### Motivation
When you try to load an object file dataset and the... | 81 | Return the audio filename when decoding fails due to corrupt files
### Feature request
Return the audio filename when the audio decoding fails. Although currently there are some checks for mp3 and opus formats with the library version there are still cases when the audio decoding could fail, eg. Corrupt file.
... | [
-0.23499369621276855,
0.25069087743759155,
-0.08755706995725632,
0.02398011088371277,
0.05561872571706772,
-0.26540830731391907,
-0.087335005402565,
0.45494359731674194,
-0.26085108518600464,
0.6982676386833191,
-0.07927187532186508,
0.5527425408363342,
-0.3463275730609894,
-0.060290887951... |
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 ... | 22 | IndexError Not Solving -> IndexError: Invalid key: ?? is out of bounds for size 0 or ??
### Describe the bug
in <cell line: 1>:1 │
│ │
│ /usr... | [
-0.18714353442192078,
-0.2914623022079468,
-0.20474490523338318,
0.2455594390630722,
0.14909157156944275,
-0.09316441416740417,
0.3255345821380615,
0.5325322151184082,
-0.18145301938056946,
0.2625061869621277,
-0.038032419979572296,
0.262340247631073,
-0.2751730978488922,
0.084632173180580... |
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 ... | 27 | IndexError Not Solving -> IndexError: Invalid key: ?? is out of bounds for size 0 or ??
### Describe the bug
in <cell line: 1>:1 │
│ │
│ /usr... | [
-0.18714353442192078,
-0.2914623022079468,
-0.20474490523338318,
0.2455594390630722,
0.14909157156944275,
-0.09316441416740417,
0.3255345821380615,
0.5325322151184082,
-0.18145301938056946,
0.2625061869621277,
-0.038032419979572296,
0.262340247631073,
-0.2751730978488922,
0.084632173180580... |
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 ... | 22 | IndexError Not Solving -> IndexError: Invalid key: ?? is out of bounds for size 0 or ??
### Describe the bug
in <cell line: 1>:1 │
│ │
│ /usr... | [
-0.18714353442192078,
-0.2914623022079468,
-0.20474490523338318,
0.2455594390630722,
0.14909157156944275,
-0.09316441416740417,
0.3255345821380615,
0.5325322151184082,
-0.18145301938056946,
0.2625061869621277,
-0.038032419979572296,
0.262340247631073,
-0.2751730978488922,
0.084632173180580... |
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... | 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... | [
-0.3492950201034546,
-0.4361373484134674,
0.011495620012283325,
0.13727539777755737,
0.14236459136009216,
-0.13144251704216003,
0.16318371891975403,
0.2404133826494217,
-0.09034916758537292,
0.07815946638584137,
0.15260660648345947,
0.2544565200805664,
-0.19957603514194489,
0.1263260394334... |
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... | 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... | [
-0.3584897816181183,
-0.4968304932117462,
0.041109565645456314,
0.1569756418466568,
0.1653336137533188,
-0.17984622716903687,
0.18572792410850525,
0.24879460036754608,
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0.1392478197813034,
0.08525040745735168,
0.33221131563186646,
-0.21793584525585175,
0.122851945459842... |
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... | 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:[ ... | [
-0.43044018745422363,
-0.21508733928203583,
-0.003619099035859108,
0.4080132246017456,
0.20815591514110565,
0.01632867008447647,
0.27846309542655945,
0.5538163781166077,
0.13296939432621002,
-0.0480373352766037,
-0.33031442761421204,
0.2580046057701111,
-0.25866419076919556,
0.172478318214... |
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... | 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:[ ... | [
-0.43044018745422363,
-0.21508733928203583,
-0.003619099035859108,
0.4080132246017456,
0.20815591514110565,
0.01632867008447647,
0.27846309542655945,
0.5538163781166077,
0.13296939432621002,
-0.0480373352766037,
-0.33031442761421204,
0.2580046057701111,
-0.25866419076919556,
0.172478318214... |
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... | 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:[ ... | [
-0.43044018745422363,
-0.21508733928203583,
-0.003619099035859108,
0.4080132246017456,
0.20815591514110565,
0.01632867008447647,
0.27846309542655945,
0.5538163781166077,
0.13296939432621002,
-0.0480373352766037,
-0.33031442761421204,
0.2580046057701111,
-0.25866419076919556,
0.172478318214... |
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... | 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:[ ... | [
-0.43044018745422363,
-0.21508733928203583,
-0.003619099035859108,
0.4080132246017456,
0.20815591514110565,
0.01632867008447647,
0.27846309542655945,
0.5538163781166077,
0.13296939432621002,
-0.0480373352766037,
-0.33031442761421204,
0.2580046057701111,
-0.25866419076919556,
0.172478318214... |
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... | 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:[ ... | [
-0.43044018745422363,
-0.21508733928203583,
-0.003619099035859108,
0.4080132246017456,
0.20815591514110565,
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0.27846309542655945,
0.5538163781166077,
0.13296939432621002,
-0.0480373352766037,
-0.33031442761421204,
0.2580046057701111,
-0.25866419076919556,
0.172478318214... |
https://github.com/huggingface/datasets/issues/5941 | Load Data Sets Too Slow In Train Seq2seq Model | I have already solved this problem, referring to #5990 : read audio frist, then use data_generator to change format . | ### 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... | 20 | 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:[ ... | [
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-0.21508733928203583,
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0.13296939432621002,
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0.2580046057701111,
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0.172478318214... |
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... | 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... | [
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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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
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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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
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0.19706682860851288,
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0.3061685562133789,
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0.10903318226337433,
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0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
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0.19706682860851288,
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0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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... | 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... | [
-0.32510867714881897,
-0.4293314516544342,
-0.06096174567937851,
0.08869542926549911,
0.2131727784872055,
-0.06696058809757233,
0.19706682860851288,
0.5384528636932373,
0.05225832387804985,
0.3061685562133789,
0.08448539674282074,
0.10903318226337433,
0.03724022954702377,
0.220244050025939... |
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
... | 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
... | [
0.04710442200303078,
-0.41798636317253113,
-0.21846047043800354,
0.25921615958213806,
0.27266204357147217,
0.06292108446359634,
0.3563428819179535,
0.2676527798175812,
0.21745391190052032,
0.05035842955112457,
0.19395604729652405,
0.30664584040641785,
-0.2323111742734909,
0.203426659107208... |
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