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https://github.com/huggingface/datasets/issues/5608 | audiofolder only creates dataset of 13 rows (files) when the data folder it's reading from has 20,000 mp3 files. | Hi!
> naming convention of mp3 files
Yes, this could be the problem. MP3 files should end with `.mp3`/`.MP3` to be recognized as audio files.
If the file names are not the culprit, can you paste the audio folder's directory structure to help us reproduce the error (e.g., by running the `tree "x"` command)? | ### Describe the bug
x = load_dataset("audiofolder", data_dir="x")
When running this, x is a dataset of 13 rows (files) when it should be 20,000 rows (files) as the data_dir "x" has 20,000 mp3 files. Does anyone know what could possibly cause this (naming convention of mp3 files, etc.)
### Steps to reproduce the b... | 54 | audiofolder only creates dataset of 13 rows (files) when the data folder it's reading from has 20,000 mp3 files.
### Describe the bug
x = load_dataset("audiofolder", data_dir="x")
When running this, x is a dataset of 13 rows (files) when it should be 20,000 rows (files) as the data_dir "x" has 20,000 mp3 files. Do... | [
-0.2228221297264099,
0.2703635096549988,
-0.01823902502655983,
0.670859694480896,
0.31988680362701416,
-0.08301005512475967,
0.4203839898109436,
0.0990840494632721,
-0.06525041908025742,
0.3750690817832947,
0.04306965321302414,
0.20323854684829712,
-0.21926312148571014,
-0.1251742690801620... |
https://github.com/huggingface/datasets/issues/5608 | audiofolder only creates dataset of 13 rows (files) when the data folder it's reading from has 20,000 mp3 files. | Hi! I'm sorry, I don't want to reveal my entire dataset, but here's a snippet (all of the mp3 files below are some of the ones not being recognized by audiofolder. Also, for another dataset, audiofolder loaded zero mp3 files because "train" was in the name of one of the mp3 files.
my_dataset
├── data
│ ├── VHA_In... | ### Describe the bug
x = load_dataset("audiofolder", data_dir="x")
When running this, x is a dataset of 13 rows (files) when it should be 20,000 rows (files) as the data_dir "x" has 20,000 mp3 files. Does anyone know what could possibly cause this (naming convention of mp3 files, etc.)
### Steps to reproduce the b... | 94 | audiofolder only creates dataset of 13 rows (files) when the data folder it's reading from has 20,000 mp3 files.
### Describe the bug
x = load_dataset("audiofolder", data_dir="x")
When running this, x is a dataset of 13 rows (files) when it should be 20,000 rows (files) as the data_dir "x" has 20,000 mp3 files. Do... | [
-0.1735651195049286,
0.2785465717315674,
-0.029778899624943733,
0.7486942410469055,
0.27932077646255493,
-0.07498657703399658,
0.4905414879322052,
0.10613946616649628,
-0.0346919521689415,
0.36654210090637207,
0.07218091189861298,
0.21181759238243103,
-0.2388114482164383,
-0.11272311210632... |
https://github.com/huggingface/datasets/issues/5606 | Add `Dataset.to_list` to the API | Hello, I have an interest in this issue.
Is the `Dataset.to_dict` you are describing correct in the code here?
https://github.com/huggingface/datasets/blob/35b789e8f6826b6b5a6b48fcc2416c890a1f326a/src/datasets/arrow_dataset.py#L4633-L4667 | Since there is `Dataset.from_list` in the API, we should also add `Dataset.to_list` to be consistent.
Regarding the implementation, we can re-use `Dataset.to_dict`'s code and replace the `to_pydict` calls with `to_pylist`. | 20 | Add `Dataset.to_list` to the API
Since there is `Dataset.from_list` in the API, we should also add `Dataset.to_list` to be consistent.
Regarding the implementation, we can re-use `Dataset.to_dict`'s code and replace the `to_pydict` calls with `to_pylist`.
Hello, I have an interest in this issue.
Is the `Datase... | [
-0.20222844183444977,
-0.033509351313114166,
-0.12614156305789948,
0.05524766445159912,
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0.17522980272769928,
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0.06443379819393158,
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0.6672616600990295,
-0.01613599807024002,
0.3745966255... |
https://github.com/huggingface/datasets/issues/5600 | Dataloader getitem not working for DreamboothDatasets | Hi!
> (see example of DreamboothDatasets)
Could you please provide a link to it? If you are referring to the example in the `diffusers` repo, your issue is unrelated to `datasets` as that example uses `Dataset` from PyTorch to load data. | ### Describe the bug
Dataloader getitem is not working as before (see example of [DreamboothDatasets](https://github.com/huggingface/peft/blob/main/examples/lora_dreambooth/train_dreambooth.py#L451C14-L529))
moving Datasets to 2.8.0 solved the issue.
### Steps to reproduce the bug
1- using DreamBoothDataset ... | 41 | Dataloader getitem not working for DreamboothDatasets
### Describe the bug
Dataloader getitem is not working as before (see example of [DreamboothDatasets](https://github.com/huggingface/peft/blob/main/examples/lora_dreambooth/train_dreambooth.py#L451C14-L529))
moving Datasets to 2.8.0 solved the issue.
### S... | [
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0.053990840911865234,
0.03020792081952095,
0.5625457763671875,
0.3081146478652954,
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0.5493577718734741,
0.25166958570480347,
0.11080946028232574,
0.18487271666526794,
-0.23793628811836243,
0.11405925452709198,
-0.05533238500356674,
-0.2742110192775... |
https://github.com/huggingface/datasets/issues/5597 | in-place dataset update | We won't support in-place modifications since `datasets` is based on the Apache Arrow format which doesn't support in-place modifications.
In your case the old dataset is garbage collected pretty quickly so you won't have memory issues.
Note that datasets loaded from disk (memory mapped) are not loaded in memory,... | ### Motivation
For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this.
```python
from datasets import Dataset
ds = Datas... | 63 | in-place dataset update
### Motivation
For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this.
```python
from datasets im... | [
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0.3782786726951599,
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0.2564661... |
https://github.com/huggingface/datasets/issues/5597 | in-place dataset update | Thank you for your detailed reply.
> In your case the old dataset is garbage collected pretty quickly so you won't have memory issues.
I understand this, but it still copies the old dataset to create the new one, is this correct? So maybe it is not memory-consuming, but time-consuming? | ### Motivation
For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this.
```python
from datasets import Dataset
ds = Datas... | 50 | in-place dataset update
### Motivation
For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this.
```python
from datasets im... | [
-0.23113484680652618,
-0.03319161385297775,
-0.07787811011075974,
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0.05626409500837326,
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0.002092592418193817,
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0.01160384714603424,
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0.384450763463974,
-0.1661481112241745,
0.27561950683... |
https://github.com/huggingface/datasets/issues/5597 | in-place dataset update | Indeed, and because of that it is more efficient to add multiple rows at once instead of one by one, using `concatenate_datasets` for example. | ### Motivation
For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this.
```python
from datasets import Dataset
ds = Datas... | 24 | in-place dataset update
### Motivation
For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this.
```python
from datasets im... | [
-0.21308301389217377,
-0.023431286215782166,
-0.07231560349464417,
-0.1571054756641388,
0.07469707727432251,
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0.025151867419481277,
0.24270620942115784,
0.08568133413791656,
0.04726583510637283,
-0.0036469679325819016,
0.3562849164009094,
-0.16501128673553467,
0.264403... |
https://github.com/huggingface/datasets/issues/5596 | [TypeError: Couldn't cast array of type] Can only load a subset of the dataset | Apparently some JSON objects have a `"labels"` field. Since this field is not present in every object, you must specify all the fields types in the README.md
EDIT: actually specifying the feature types doesn’t solve the issue, it raises an error because “labels” is missing in the data | ### Describe the bug
I'm trying to load this [dataset](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues) which consists of jsonl files and I get the following error:
```
casted_values = _c(array.values, feature[0])
File "/opt/conda/lib/python3.7/site-packages/datasets/table.py", line 1839, in wr... | 48 | [TypeError: Couldn't cast array of type] Can only load a subset of the dataset
### Describe the bug
I'm trying to load this [dataset](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues) which consists of jsonl files and I get the following error:
```
casted_values = _c(array.values, feature[0])
... | [
-0.17818354070186615,
-0.10365822166204453,
-0.07276815176010132,
0.42764705419540405,
0.4102258086204529,
0.15316423773765564,
0.2850620448589325,
0.5654889345169067,
0.1791166067123413,
-0.0494285523891449,
-0.07908792793750763,
0.3755905330181122,
-0.15938618779182434,
0.340528070926666... |
https://github.com/huggingface/datasets/issues/5596 | [TypeError: Couldn't cast array of type] Can only load a subset of the dataset | We've updated the dataset to remove the extra `labels` field from some files, closing this issue. Thanks! | ### Describe the bug
I'm trying to load this [dataset](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues) which consists of jsonl files and I get the following error:
```
casted_values = _c(array.values, feature[0])
File "/opt/conda/lib/python3.7/site-packages/datasets/table.py", line 1839, in wr... | 17 | [TypeError: Couldn't cast array of type] Can only load a subset of the dataset
### Describe the bug
I'm trying to load this [dataset](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues) which consists of jsonl files and I get the following error:
```
casted_values = _c(array.values, feature[0])
... | [
-0.17818354070186615,
-0.10365822166204453,
-0.07276815176010132,
0.42764705419540405,
0.4102258086204529,
0.15316423773765564,
0.2850620448589325,
0.5654889345169067,
0.1791166067123413,
-0.0494285523891449,
-0.07908792793750763,
0.3755905330181122,
-0.15938618779182434,
0.340528070926666... |
https://github.com/huggingface/datasets/issues/5594 | Error while downloading the xtreme udpos dataset | "Hi! I cannot reproduce this error on my machine.\r\n\r\nThe raised error could mean that one of the(...TRUNCATED) | "### Describe the bug\r\n\r\nHi,\r\n\r\nI am facing an error while downloading the xtreme udpos data(...TRUNCATED) | 45 | "Error while downloading the xtreme udpos dataset \n ### Describe the bug\r\n\r\nHi,\r\n\r\nI am fac(...TRUNCATED) | [-0.3754369914531708,-0.09867477416992188,0.012532349675893784,0.3179013729095459,0.5317246913909912(...TRUNCATED) |
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