ahmedfarazsyk/datasets-github-issues huggingface dataset:
Trying to load FEVER dataset results in NonMatchingChecksumError
Author: santhnm2
State: closed
Labels: name: bug

## Describe the bug
Trying to load the `fever` dataset fails with `datasets.utils.info_utils.NonMatchingChecksumError`.

I tried with `download_mode="force_redownload"` but that did not fix the error. I also tried with `ignore_verification=True` but then that raised a `json.decoder.JSONDecodeError`.

## Steps to reproduce the bug
```python
from datasets import load_dataset

dataset = load_dataset('fever', 'v1.0') # Fails with NonMatchingChecksumError
dataset = load_dataset('fever', 'v1.0', download_mode="force_redownload") # Fails with NonMatchingChecksumError
dataset = load_dataset('fever', 'v1.0', ignore_verification=True)` # Fails with JSONDecodeError
```

## Expected results
I expect this call to return with no error raised.

## Actual results
With `ignore_verification=False`:
```
*** datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://s3-eu-west-1.amazonaws.com/fever.public/train.jsonl', 'https://s3-eu-west-1.amazonaws.com/fever.public/shared_task_dev.jsonl', 'https://s3-eu-west-1.amazonaws.com/fever.public/shared_task_dev_public.jsonl', 'https://s3-eu-west-1.amazonaws.com/fever.public/shared_task_test.jsonl', 'https://s3-eu-west-1.amazonaws.com/fever.public/paper_dev.jsonl', 'https://s3-eu-west-1.amazonaws.com/fever.public/paper_test.jsonl']
```
With `ignore_verification=True`:
```
*** json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
```

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.2.3.dev0
- Platform: Linux-4.15.0-50-generic-x86_64-with-glibc2.10
- Python version: 3.8.13
- PyArrow version: 8.0.0
- Pandas version: 1.4.2


Comments: Thanks for reporting @santhnm2. We are fixing it.

Data owners updated their URLs recently. We have to align with them, otherwise you do not download anything (that is why ignore_verifications does not work).

Hello! Is there any update on this? I am having the same issue 6 months later.
New Preprocessing Feature  - Deduplication [Request]
Author: yuvalkirstain
State: open
Labels: name: duplicate

name: enhancement

**Is your feature request related to a problem? Please describe.**
Many large datasets are full of duplications and it has been shown that deduplicating datasets can lead to better performance while training, and more truthful evaluation at test-time.

A feature that allows one to easily deduplicate a dataset can be cool!

**Describe the solution you'd like**
We can define a function and keep only the first/last data-point that yields the value according to this function.

**Describe alternatives you've considered**
The clear alternative is to repeat a clear boilerplate every time someone want to deduplicate a dataset.


Comments: Hi! The [datasets_sql](https://github.com/mariosasko/datasets_sql) package lets you easily find distinct rows in a dataset (an example with `SELECT DISTINCT` is in the readme). Deduplication is (still) not part of the official API because it's hard to implement for datasets bigger than RAM while only using the native PyArrow ops.

(Btw, this is a duplicate of https://github.com/huggingface/datasets/issues/2514)

Here is an example using the [datasets_sql](https://github.com/mariosasko/datasets_sql) mentioned 

```python 
from datasets_sql import query

dataset = load_dataset("imdb", split="train")

# If you dont have an id column just add one by enumerating
dataset=dataset.add_column("id", range(len(dataset)))

id_column='id'
unique_column='text'

# always selects min id
unique_dataset = query(f"SELECT dataset.* FROM dataset JOIN (SELECT MIN({id_column}) as unique_id FROM dataset group by {unique_column}) ON unique_id=dataset.{id_column}")
```
Not ideal for large datasets but good enough for basic cases.
Sure would be nice to have in the library 🤗
Dataset Viewer issue for openclimatefix/nimrod-uk-1km
Author: ZYMXIXI
State: open

### Link

_No response_

### Description

_No response_

### Owner

_No response_

Comments: If I understand correctly, this is due to the key `split` missing in the line https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km/blob/main/nimrod-uk-1km.py#L41 of the script.
Maybe @albertvillanova could confirm.

I'm having a look.

Indeed there are several issues in this dataset loading script.

The one pointed out by @severo: for the default configuration "crops": https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km/blob/main/nimrod-uk-1km.py#L244
- The download manager downloads `_URL`
- But `_URL` is not defined:  https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km/blob/main/nimrod-uk-1km.py#L41
  ```python
  _URL = {'train': []}
  ```
- Afterwards, for each split, a different key in `_ULR` is used, but it only contains one key: "train"
  - "valid" key: https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km/blob/main/nimrod-uk-1km.py#L260
  - "test key: https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km/blob/main/nimrod-uk-1km.py#L269
  
These keys do not exist inside `_URL`, thus the error message reported in the viewer: 
```
Exception:     KeyError
Message:       'valid'
```

Would anyone want to submit a Hub PR (or open a Discussion for the authors to be aware) to this dataset? https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km

Hi, I'm the main author for that dataset, so I'll work on updating it! I was working on debugging some stuff awhile ago, which is what broke it. 

I've opened a Discussion page, so that we can ask/answer and propose fixes until the script works properly: https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km/discussions/1

CC: @julien-c @jacobbieker 

can we close this issue and followup in the discussion?
Dataset Viewer issue for amazon_polarity
Author: lewtun
State: closed
Labels: name: dataset-viewer

### Link

https://huggingface.co/datasets/amazon_polarity/viewer/amazon_polarity/test

### Description

For some reason the train split is OK but the test split is not for this dataset:

```
Server error
Status code:   400
Exception:     FileNotFoundError
Message:       [Errno 2] No such file or directory: '/cache/modules/datasets_modules/datasets/amazon_polarity/__init__.py'
```

### Owner

No

Comments: Thanks, looking at it

Not sure what happened 😬, but it's fixed
Dataset Viewer issue for aeslc
Author: lewtun
State: closed
Labels: name: dataset-viewer

### Link

https://huggingface.co/datasets/aeslc

### Description

The dataset viewer can't find `dataset_infos.json` in it's cache:

```
Server error
Status code:   400
Exception:     FileNotFoundError
Message:       [Errno 2] No such file or directory: '/cache/modules/datasets_modules/datasets/aeslc/eb8e30234cf984a58ebe9f205674597ac1db2ec91e7321cd7f36864f7e3671b8/dataset_infos.json'
```

### Owner

No

Comments: Not sure what happened 😬, but it's fixed
TIMIT won't load after manual download: Errors about files that don't exist
Author: drscotthawley
State: closed
Labels: name: bug

## Describe the bug

I get the message from HuggingFace that it must be downloaded manually. From the URL provided in the message, I got to UPenn page for manual download. (UPenn apparently want $250? for the dataset??)   ...So, ok, I obtained a copy from a friend and also a smaller version from Kaggle. But in both cases the HF dataloader fails; it is looking for files that don't exist anywhere in the dataset: it is looking for files with lower-case letters like "**test*" (all the filenames in both my copies are uppercase) and certain file extensions that exclude the .DOC which is provided in TIMIT:


## Steps to reproduce the bug
```python
data = load_dataset('timit_asr', 'clean')['train']
```

## Expected results
The dataset should load with no errors. 

## Actual results
This error message:
```
  File "/home/ubuntu/envs/data2vec/lib/python3.9/site-packages/datasets/data_files.py", line 201, in resolve_patterns_locally_or_by_urls
    raise FileNotFoundError(error_msg)
FileNotFoundError: Unable to resolve any data file that matches '['**test*', '**eval*']' at /home/ubuntu/datasets/timit with any supported extension ['csv', 'tsv', 'json', 'jsonl', 'parquet', 'txt', 'blp', 'bmp', 'dib', 'bufr', 'cur', 'pcx', 'dcx', 'dds', 'ps', 'eps', 'fit', 'fits', 'fli', 'flc', 'ftc', 'ftu', 'gbr', 'gif', 'grib', 'h5', 'hdf', 'png', 'apng', 'jp2', 'j2k', 'jpc', 'jpf', 'jpx', 'j2c', 'icns', 'ico', 'im', 'iim', 'tif', 'tiff', 'jfif', 'jpe', 'jpg', 'jpeg', 'mpg', 'mpeg', 'msp', 'pcd', 'pxr', 'pbm', 'pgm', 'ppm', 'pnm', 'psd', 'bw', 'rgb', 'rgba', 'sgi', 'ras', 'tga', 'icb', 'vda', 'vst', 'webp', 'wmf', 'emf', 'xbm', 'xpm', 'zip']
```

But this is a strange sort of error: why is it looking for lower-case file names when all the TIMIT dataset filenames are uppercase?  Why does it exclude .DOC files when the only parts of the TIMIT data set with "TEST" in them have ".DOC" extensions?   ...I wonder, how was anyone able to get this to work in the first place?

The files in the dataset look like the following: 
```
³       PHONCODE.DOC
³       PROMPTS.TXT
³       SPKRINFO.TXT
³       SPKRSENT.TXT
³       TESTSET.DOC
```
...so why are these being excluded by the dataset loader? 


## Environment info
- `datasets` version: 2.2.2
- Platform: Linux-5.4.0-1060-aws-x86_64-with-glibc2.27
- Python version: 3.9.9
- PyArrow version: 8.0.0
- Pandas version: 1.4.2


Comments: To have some context, please see:
- #4145

Please, also note that we have recently made some fixes to the script, which are in our GitHub master branch but not yet released:
- #4422
- #4425 
- #4436

Thanks Albert! I'll try pulling `datasets` from the git repo instead of PyPI, and/or just wait for the next release.


I'm closing this issue then. Please, feel free to reopen it again if the problem persists.
Load a local cached dataset that has been modified
Author: mihail911
State: closed
Labels: name: bug

## Describe the bug
I have loaded a dataset as follows:
```
d = load_dataset("emotion", split="validation")
```
Afterwards I make some modifications to the dataset via a `map` call:
```
d.map(some_update_func, cache_file_name=modified_dataset)
```
This generates a cached version of the dataset on my local system in the same directory as the original download of the data (/path/to/cache). Running an `ls` returns:
```
modified_dataset
dataset_info.json  
emotion-test.arrow  
emotion-train.arrow  
emotion-validation.arrow
```
as expected. However, when I try to load up the modified cached dataset via a call to 
```
modified = load_dataset("emotion", split="validation", data_files="/path/to/cache/modified_dataset") 
```
it simply redownloads a new version of the dataset and dumps to a new cache rather than loading up the original modified dataset:
```
Using custom data configuration validation-cdbf51685638421b
Downloading and preparing dataset emotion/validation to ...
```

How am I supposed to load the original modified local cache copy of the dataset?

## Environment info
- `datasets` version: 2.2.2
- Platform: Linux-5.4.0-113-generic-x86_64-with-glibc2.17
- Python version: 3.8.13
- PyArrow version: 8.0.0
- Pandas version: 1.4.2



Comments: Hi! `datasets` caches every modification/loading, so you can either rerun the pipeline up to the `map` call or use `Dataset.from_file(modified_dataset)` to load the dataset directly from the cache file.

Awesome, hvala Mario! This works.
Add loading variable number of columns for different splits
Author: DrMatters
State: closed
Labels: name: enhancement

**Is your feature request related to a problem? Please describe.**
The original dataset `blended_skill_talk` consists of different sets of columns for the different splits: (test/valid) splits have additional data column `label_candidates` that the (train) doesn't have.
When loading such data, an exception occurs at table.py:cast_table_to_schema, because of mismatched columns.

Comments: Hi! Indeed the column is missing, but you shouldn't get an error? Have you made some modifications (locally) to the loading script? I've opened a PR to add the missing columns to the script.
Cannot load timit_asr data set
Author: bhaddow
State: closed
Labels: name: bug

## Describe the bug
I am trying to load the timit_asr data set. I have tried with a copy from the LDC, and a copy from deepai. In both cases they fail with a "duplicate key" error. With the LDC version I have to convert the file extensions all to upper-case before I can load it at all.

## Steps to reproduce the bug
```python
timit = datasets.load_dataset("timit_asr", data_dir = "/path/to/dataset")
# Sample code to reproduce the bug
```

## Expected results

The data set should load without error. It worked for me before the LDC url change.

## Actual results
```
datasets.keyhash.DuplicatedKeysError: FAILURE TO GENERATE DATASET !
Found duplicate Key: SA1
Keys should be unique and deterministic in nature
```

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- `datasets` version: 2.2.2
- Platform: Linux-5.4.0-90-generic-x86_64-with-glibc2.17
- Python version: 3.8.12
- PyArrow version: 8.0.0
- Pandas version: 1.4.2



Comments: Thanks for reporting, @bhaddow.

I'm fixing it.

Thanks for the quick fix!

@bhaddow we have also made a fix so that you don't have to convert to uppercase the file extensions of the LDC data.

Would you mind checking if it works OK now for you and reporting if there are any issues? Thanks. 

Hi @albertvillanova  -It loads fine on a copy of the data from deepai - although I have to remove the copies of the .WAV files (with extension .WAV,wav). On a copy of the data that was obtained from the LDC, the glob still fails to find the files. The LDC copy looks like it was copied from CD, in 2004, so the structure may be different to a current download.

Ah, if I change the train/ and test/ directories to TRAIN/ and TEST/  then it works!

Thanks for your investigation and report, @bhaddow. I'm adding another fix for the TRAIN/train and TEST/test directory names.
Update `unittest` assertions over tuples from `assertEqual` to `assertTupleEqual`
Author: alvarobartt
State: closed
Labels: name: enhancement

**Is your feature request related to a problem? Please describe.**

So this is more a readability improvement rather than a proposal, wouldn't it be better to use `assertTupleEqual` over the tuples rather than `assertEqual`? As `unittest` added that function in `v3.1`, as detailed at https://docs.python.org/3/library/unittest.html#unittest.TestCase.assertTupleEqual, so maybe it's worth updating.

Find an example of an `assertEqual` over a tuple in 🤗 `datasets` unit tests over an `ArrowDataset` at https://github.com/huggingface/datasets/blob/0bb47271910c8a0b628dba157988372307fca1d2/tests/test_arrow_dataset.py#L570

**Describe the solution you'd like**

Start slowly replacing all the `assertEqual` statements with `assertTupleEqual` if the assertion is done over a Python tuple, as we're doing with the Python lists using `assertListEqual` rather than `assertEqual`.

**Additional context**

If so, please let me know and I'll try to go over the tests and create a PR if applicable, otherwise, if you consider this should stay as `assertEqual` rather than `assertSequenceEqual` feel free to close this issue! Thanks 🤗 


Comments: Hi! If the only goal is to improve readability, it's better to use `assertTupleEqual` than `assertSequenceEqual` for Python tuples. Also, note that this function is called internally by `assertEqual`, but I guess we can accept a PR to be more verbose.

Hi @mariosasko, right! I'll update the issue title/desc with `assertTupleEqual` even though as you said it seems to be internally using `assertEqual` so I'm not sure whether it's worth it or not...

https://docs.python.org/3/library/unittest.html#unittest.TestCase.assertTupleEqual

I thought we were supposed to move gradually from `unittest` to `pytest`...
Dataset Viewer issue for ett
Author: dgcnz
State: closed
Labels: name: dataset-viewer

### Link

https://huggingface.co/datasets/ett

### Description

Timestamp is not JSON serializable. 

```
Status code:   500
Exception:     Status500Error
Message:       Type is not JSON serializable: Timestamp
```

### Owner

No

Comments: Thanks for reporting @dgcnz.

I have checked that the dataset works fine in streaming mode.

Additionally, other datasets containing timestamps are properly rendered by the viewer: https://huggingface.co/datasets/blbooks

I have tried to force the refresh of the preview, but the endpoint is not responsive: Connection timed out

CC: @severo 

I've just resent the refresh of the preview to the new endpoint, without success.

CC: @severo 

Fixed!

https://huggingface.co/datasets/ett/viewer/h1/test

<img width="982" alt="Capture d’écran 2022-06-15 à 09 30 22" src="https://user-images.githubusercontent.com/1676121/173769035-a075d753-ecfc-4a43-b54b-973105d464d3.png">
Dataset Viewer issue for conll2012_ontonotesv5
Author: jiangwangyi
State: closed
Labels: name: dataset-viewer

### Link

https://huggingface.co/datasets/conll2012_ontonotesv5

### Description

Dataset viewer outage.

### Owner

No

Comments: Thanks for reporting, @jiangwy99.

I guess this could be addressed only once we fix our issue with irresponsive backend endpoint.

CC: @severo 

I've just sent the forcing of the refresh of the preview to the new endpoint.

Fixed, thanks for the patience. The issue was the amount of RAM allowed to extract the first rows of the dataset was not sufficient.
Dataset should have a `.name` field
Author: f4hy
State: closed
Labels: name: enhancement

**Is your feature request related to a problem? Please describe.**
If building pipelines that can evaluate on more than one dataset, it would be nice to be able to log results of things like `Evaluating on {dataset.name}` or `results for {dataset.name} are: {results}`

Without some way of concisely identifying a dataset from the dataset object, tools which might run on more than one dataset must be passed the dataset object _and_ the name/id of the dataset being used. 

**Describe the solution you'd like**
The DatasetInfo class should have a `name` field which is the name of a dataset. then for a given dataset if it evolves in time the `version` can be updated but its different versions of the same dataset with a unique `name`. The name could then all be accessed by `dataset.name`

**Describe alternatives you've considered**
For my own purposes I am considering making `NamedDataset[Dataset]` where the subclass just has a .name field. 

**Additional context**
My guess is that most usecases are not working with more than one dataset in a given pipeline so a name is not really needed. This has surprised me though as one of the advantages of a standard dataset interface is to be able to build pipelines which can be passed in a dataset and separate responsibilities of the dataset loading from the train or eval pipeline.


Comments: Hi! You can already use `dset.builder_name` and `dset.config_name` for that purpose. And when it comes to versioning, it's better to use `dset._fingerprint` than the `version` attribute as the former represents a deterministic hash that encodes all the mutable ops executed on a dataset, and the latter stays the same unless it's manually updated after each op.

@mariosasko  Can we make ._fingerprint not private? seems a critical component for tracking how a model was generated to ensure reproducibility.
"NonMatchingChecksumError" when importing 'spider' dataset
Author: OmarAlaaeldein
State: closed
Labels: name: hosted-on-google-drive

## Describe the bug
When importing 'spider' dataset [https://huggingface.co/datasets/spider] an error occurs

## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('spider')
```

## Expected results
Dataset object

## Actual results
NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0']

## Environment info
- `datasets` version: 2.2.2
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.7.11
- PyArrow version: 6.0.1
- Pandas version: 1.3.5


Comments: Thanks for reporting, @OmarAlaaeldein.

Datasets hosted at Google Drive give problems quite often due to a change in their service:
- #3786 

Related to:
- #3906

I'm having a look.

We have made a Pull Request to replace the Google Drive URL. This fix will be accessible in our next `datasets` library release.

In the meantime, once the PR merged into master, you can get this fix by installing our library from the GitHub master branch:
```shell
pip install git+https://github.com/huggingface/datasets#egg=datasets
```
Then, if you had previously tried to load the data and got the checksum error, you should force the redownload of the data (before the fix, you just downloaded and cached the virus scan warning page, instead of the data file):
```shell
load_dataset("...", download_mode="force_redownload")
```
load dataset wikitext-2-raw-v1 failed. Could not reach wikitext-2-raw-v1.py.
Author: cailun01
State: closed
Labels: name: bug

## Describe the bug
Could not reach wikitext-2-raw-v1.py

## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset("wikitext-2-raw-v1")
```

## Expected results
Download `wikitext-2-raw-v1` dataset successfully.

## Actual results
```
  File "load_datasets.py", line 13, in <module>
    load_dataset("wikitext-2-raw-v1")
  File "/root/miniconda3/lib/python3.6/site-packages/datasets/load.py", line 1715, in load_dataset
    **config_kwargs,
  File "/root/miniconda3/lib/python3.6/site-packages/datasets/load.py", line 1536, in load_dataset_builder
    data_files=data_files,
  File "/root/miniconda3/lib/python3.6/site-packages/datasets/load.py", line 1282, in dataset_module_factory
    raise e1 from None
  File "/root/miniconda3/lib/python3.6/site-packages/datasets/load.py", line 1224, in dataset_module_factory
    dynamic_modules_path=dynamic_modules_path,
  File "/root/miniconda3/lib/python3.6/site-packages/datasets/load.py", line 559, in get_module
    local_path = self.download_loading_script(revision)
  File "/root/miniconda3/lib/python3.6/site-packages/datasets/load.py", line 539, in download_loading_script
    return cached_path(file_path, download_config=download_config)
  File "/root/miniconda3/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 246, in cached_path
    download_desc=download_config.download_desc,
  File "/root/miniconda3/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 582, in get_from_cache
    raise ConnectionError(f"Couldn't reach {url} ({repr(head_error)})")
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/2.2.2/datasets/wikitext-2-raw-v1/wikitext-2-raw-v1.py (ReadTimeout(ReadTimeoutError("HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Read timed out. (read timeout=100)",),))
```
I tried to download wikitext-2-raw-v1.py by chrome and got:
![image](https://user-images.githubusercontent.com/20658907/170171595-0ca9f1da-c05a-4b57-861e-9530bfa3bdb9.png)

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.2.2
- Platform: CentOS 7
- Python version: 3.6
- PyArrow version: 3.0.0


Comments: I tried in this way.

```python
from datasets import load_dataset
dataset = load_dataset(path="wikitext", name="wikitext-103-v1", split="train")
```
device/google/accessory/adk2012 - Git at Google
Author: Aeckard45
State: closed

"git clone https://android.googlesource.com/device/google/accessory/adk2012"
 https://android.googlesource.com/device/google/accessory/adk2012/#:~:text=git%20clone%20https%3A//android.googlesource.com/device/google/accessory/adk2012