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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
https://api.github.com/repos/huggingface/datasets/issues/657 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/657/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/657/comments | https://api.github.com/repos/huggingface/datasets/issues/657/events | https://github.com/huggingface/datasets/issues/657 | 706,204,383 | MDU6SXNzdWU3MDYyMDQzODM= | 657 | Squad Metric Description & Feature Mismatch | {
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"Thanks for reporting !\r\nThere indeed a mismatch between the features and the kwargs description\r\n\r\nI believe `answer_start` was added to match the squad dataset format for consistency, even though it is not used in the metric computation. I think I'd rather keep it this way, so that you can just give `refere... | 2020-09-22T09:07:00Z | 2020-10-13T02:16:56Z | 2020-09-29T15:57:38Z | NONE | null | null | {
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} | The [description](https://github.com/huggingface/datasets/blob/master/metrics/squad/squad.py#L39) doesn't mention `answer_start` in squad. However the `datasets.features` require [it](https://github.com/huggingface/datasets/blob/master/metrics/squad/squad.py#L68). It's also not used in the evaluation. | {
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https://api.github.com/repos/huggingface/datasets/issues/650 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/650/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/650/comments | https://api.github.com/repos/huggingface/datasets/issues/650/events | https://github.com/huggingface/datasets/issues/650 | 704,861,844 | MDU6SXNzdWU3MDQ4NjE4NDQ= | 650 | dummy data testing can't test datasets using `dl_manager.extract` in `_split_generators` | {
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"Hi :) \r\nIn your dummy data zip file you can just have `subset000.xz` as directories instead of compressed files.\r\nLet me know if it helps",
"Thanks for your comment @lhoestq ,\r\nJust for confirmation, changing dummy data like this won't make dummy test test the functionality to extract `subsetxxx.xz` but ac... | 2020-09-19T11:07:03Z | 2020-09-22T11:54:10Z | 2020-09-22T11:54:09Z | CONTRIBUTOR | null | null | {
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} | Hi, I recently want to add a dataset whose source data is like this
```
openwebtext.tar.xz
|__ openwebtext
|__subset000.xz
| |__ ....txt
| |__ ....txt
| ...
|__ subset001.xz
|
....
```
So I wrote `openwebtext.py` like this
```
d... | {
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https://api.github.com/repos/huggingface/datasets/issues/649 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/649/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/649/comments | https://api.github.com/repos/huggingface/datasets/issues/649/events | https://github.com/huggingface/datasets/issues/649 | 704,838,415 | MDU6SXNzdWU3MDQ4Mzg0MTU= | 649 | Inconsistent behavior in map | {
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"Thanks for reporting !\r\n\r\nThis issue must have appeared when we refactored type inference in `nlp`\r\nBy default the library tries to keep the same feature types when applying `map` but apparently it has troubles with nested structures. I'll try to fix that next week"
] | 2020-09-19T08:41:12Z | 2020-09-21T16:13:05Z | 2020-09-21T16:13:05Z | NONE | null | null | {
"completed": 0,
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} | I'm observing inconsistent behavior when applying .map(). This happens specifically when I'm incrementally adding onto a feature that is a nested dictionary. Here's a simple example that reproduces the problem.
```python
import datasets
# Dataset with a single feature called 'field' consisting of two examples
d... | {
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https://api.github.com/repos/huggingface/datasets/issues/648 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/648/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/648/comments | https://api.github.com/repos/huggingface/datasets/issues/648/events | https://github.com/huggingface/datasets/issues/648 | 704,753,123 | MDU6SXNzdWU3MDQ3NTMxMjM= | 648 | offset overflow when multiprocessing batched map on large datasets. | {
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"This should be fixed with #645 ",
"Feel free to re-open if it still occurs"
] | 2020-09-19T02:15:11Z | 2020-09-19T16:47:07Z | 2020-09-19T16:46:31Z | CONTRIBUTOR | null | null | {
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} | It only happened when "multiprocessing" + "batched" + "large dataset" at the same time.
```
def bprocess(examples):
examples['len'] = []
for text in examples['text']:
examples['len'].append(len(text))
return examples
wiki.map(brpocess, batched=True, num_proc=8)
```
```
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https://api.github.com/repos/huggingface/datasets/issues/647 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/647/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/647/comments | https://api.github.com/repos/huggingface/datasets/issues/647/events | https://github.com/huggingface/datasets/issues/647 | 704,734,764 | MDU6SXNzdWU3MDQ3MzQ3NjQ= | 647 | Cannot download dataset_info.json | {
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"Thanks for reporting !\r\nWe should add support for servers without internet connection indeed\r\nI'll do that early next week",
"Thanks, @lhoestq !\r\nPlease let me know when it is available. ",
"Right now the recommended way is to create the dataset on a server with internet connection and then to save it an... | 2020-09-19T01:35:15Z | 2020-09-21T08:28:42Z | 2020-09-21T08:28:42Z | NONE | null | null | {
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} | I am running my job on a cloud server where does not provide for connections from the standard compute nodes to outside resources. Hence, when I use `dataset.load_dataset()` to load data, I got an error like this:
```
ConnectionError: Couldn't reach https://storage.googleapis.com/huggingface-nlp/cache/datasets/text... | {
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https://api.github.com/repos/huggingface/datasets/issues/643 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/643/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/643/comments | https://api.github.com/repos/huggingface/datasets/issues/643/events | https://github.com/huggingface/datasets/issues/643 | 704,477,164 | MDU6SXNzdWU3MDQ0NzcxNjQ= | 643 | Caching processed dataset at wrong folder | {
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"Thanks for reporting !\r\nIt uses a temporary file to write the data.\r\nHowever it looks like the temporary file is not placed in the right directory during the processing",
"Well actually I just tested and the temporary file is placed in the same directory, so it should work as expected.\r\nWhich version of `d... | 2020-09-18T15:41:26Z | 2022-02-16T14:53:29Z | 2022-02-16T14:53:29Z | CONTRIBUTOR | null | null | {
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} | Hi guys, I run this on my Colab (PRO):
```python
from datasets import load_dataset
dataset = load_dataset('text', data_files='/content/corpus.txt', cache_dir='/content/drive/My Drive', split='train')
def encode(examples):
return tokenizer(examples['text'], truncation=True, padding='max_length')
dataset = ... | {
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https://api.github.com/repos/huggingface/datasets/issues/638 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/638/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/638/comments | https://api.github.com/repos/huggingface/datasets/issues/638/events | https://github.com/huggingface/datasets/issues/638 | 704,146,956 | MDU6SXNzdWU3MDQxNDY5NTY= | 638 | GLUE/QQP dataset: NonMatchingChecksumError | {
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"Hi ! Sure I'll take a look"
] | 2020-09-18T07:09:10Z | 2020-09-18T11:37:07Z | 2020-09-18T11:37:07Z | CONTRIBUTOR | null | null | {
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} | Hi @lhoestq , I know you are busy and there are also other important issues. But if this is easy to be fixed, I am shamelessly wondering if you can give me some help , so I can evaluate my models and restart with my developing cycle asap. 😚
datasets version: editable install of master at 9/17
`datasets.load_data... | {
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https://api.github.com/repos/huggingface/datasets/issues/630 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/630/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/630/comments | https://api.github.com/repos/huggingface/datasets/issues/630/events | https://github.com/huggingface/datasets/issues/630 | 701,636,350 | MDU6SXNzdWU3MDE2MzYzNTA= | 630 | Text dataset not working with large files | {
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"Seems like it works when setting ```block_size=2100000000``` or something arbitrarily large though.",
"Can you give us some stats on the data files you use as inputs?",
"Basically ~600MB txt files(UTF-8) * 59. \r\ncontents like ```안녕하세요, 이것은 예제로 한번 말해보는 텍스트입니다. 그냥 이렇다고요.<|endoftext|>\\n```\r\n\r\nAlso, it gets... | 2020-09-15T06:02:36Z | 2020-09-25T22:21:43Z | 2020-09-25T22:21:43Z | NONE | null | null | {
"completed": 0,
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} | ```
Traceback (most recent call last):
File "examples/language-modeling/run_language_modeling.py", line 333, in <module>
main()
File "examples/language-modeling/run_language_modeling.py", line 262, in main
get_dataset(data_args, tokenizer=tokenizer, cache_dir=model_args.cache_dir) if training_args.do_t... | {
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https://api.github.com/repos/huggingface/datasets/issues/629 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/629/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/629/comments | https://api.github.com/repos/huggingface/datasets/issues/629/events | https://github.com/huggingface/datasets/issues/629 | 701,517,550 | MDU6SXNzdWU3MDE1MTc1NTA= | 629 | straddling object straddles two block boundaries | {
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"sorry it's an apache arrow issue."
] | 2020-09-15T00:30:46Z | 2020-09-15T00:36:17Z | 2020-09-15T00:32:17Z | NONE | null | null | {
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} | I am trying to read json data (it's an array with lots of dictionaries) and getting block boundaries issue as below :
I tried calling read_json with readOptions but no luck .
```
table = json.read_json(fn)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "pyarrow/_json.pyx", li... | {
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https://api.github.com/repos/huggingface/datasets/issues/625 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/625/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/625/comments | https://api.github.com/repos/huggingface/datasets/issues/625/events | https://github.com/huggingface/datasets/issues/625 | 701,057,799 | MDU6SXNzdWU3MDEwNTc3OTk= | 625 | dtype of tensors should be preserved | {
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"Indeed we convert tensors to list to be able to write in arrow format. Because of this conversion we lose the dtype information. We should add the dtype detection when we do type inference. However it would require a bit of refactoring since currently the conversion happens before the type inference..\r\n\r\nAnd t... | 2020-09-14T12:38:05Z | 2021-08-17T08:30:04Z | 2021-08-17T08:30:04Z | CONTRIBUTOR | null | null | {
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} | After switching to `datasets` my model just broke. After a weekend of debugging, the issue was that my model could not handle the double that the Dataset provided, as it expected a float (but didn't give a warning, which seems a [PyTorch issue](https://discuss.pytorch.org/t/is-it-required-that-input-and-hidden-for-gru-... | {
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https://api.github.com/repos/huggingface/datasets/issues/623 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/623/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/623/comments | https://api.github.com/repos/huggingface/datasets/issues/623/events | https://github.com/huggingface/datasets/issues/623 | 700,235,308 | MDU6SXNzdWU3MDAyMzUzMDg= | 623 | Custom feature types in `load_dataset` from CSV | {
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"Currently `csv` doesn't support the `features` attribute (unlike `json`).\r\nWhat you can do for now is cast the features using the in-place transform `cast_`\r\n\r\n```python\r\nfrom datasets import load_dataset\r\n\r\ndataset = load_dataset('csv', data_files=file_dict, delimiter=';', column_names=['text', 'label... | 2020-09-12T13:21:34Z | 2020-09-30T19:51:43Z | 2020-09-30T08:39:54Z | MEMBER | null | null | {
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} | I am trying to load a local file with the `load_dataset` function and I want to predefine the feature types with the `features` argument. However, the types are always the same independent of the value of `features`.
I am working with the local files from the emotion dataset. To get the data you can use the followi... | {
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https://api.github.com/repos/huggingface/datasets/issues/622 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/622/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/622/comments | https://api.github.com/repos/huggingface/datasets/issues/622/events | https://github.com/huggingface/datasets/issues/622 | 700,225,826 | MDU6SXNzdWU3MDAyMjU4MjY= | 622 | load_dataset for text files not working | {
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"Can you give us more information on your os and pip environments (pip list)?",
"@thomwolf Sure. I'll try downgrading to 3.7 now even though Arrow say they support >=3.5.\r\n\r\nLinux (Ubuntu 18.04) - Python 3.8\r\n======================\r\nPackage - Version\r\n---------------------\r\ncertifi 2... | 2020-09-12T12:49:28Z | 2020-10-28T11:07:31Z | 2020-10-28T11:07:30Z | CONTRIBUTOR | null | null | {
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} | Trying the following snippet, I get different problems on Linux and Windows.
```python
dataset = load_dataset("text", data_files="data.txt")
# or
dataset = load_dataset("text", data_files=["data.txt"])
```
(ps [This example](https://huggingface.co/docs/datasets/loading_datasets.html#json-files) shows that ... | {
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https://api.github.com/repos/huggingface/datasets/issues/620 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/620/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/620/comments | https://api.github.com/repos/huggingface/datasets/issues/620/events | https://github.com/huggingface/datasets/issues/620 | 699,815,135 | MDU6SXNzdWU2OTk4MTUxMzU= | 620 | map/filter multiprocessing raises errors and corrupts datasets | {
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"It seems that I ran into the same problem\r\n```\r\ndef tokenize(cols, example):\r\n for in_col, out_col in cols.items():\r\n example[out_col] = hf_tokenizer.convert_tokens_to_ids(hf_tokenizer.tokenize(example[in_col]))\r\n return example\r\ncola = datasets.load_dataset('glue', 'cola')\r\ntokenized_cola = col... | 2020-09-11T22:30:06Z | 2020-10-08T16:31:47Z | 2020-10-08T16:31:46Z | NONE | null | null | {
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} | After upgrading to the 1.0 started seeing errors in my data loading script after enabling multiprocessing.
```python
...
ner_ds_dict = ner_ds.train_test_split(test_size=test_pct, shuffle=True, seed=seed)
ner_ds_dict["validation"] = ner_ds_dict["test"]
rel_ds_dict = rel_ds.train_test_split(test_si... | {
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https://api.github.com/repos/huggingface/datasets/issues/619 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/619/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/619/comments | https://api.github.com/repos/huggingface/datasets/issues/619/events | https://github.com/huggingface/datasets/issues/619 | 699,733,612 | MDU6SXNzdWU2OTk3MzM2MTI= | 619 | Mistakes in MLQA features names | {
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"Indeed you're right ! Thanks for reporting that\r\n\r\nCould you open a PR to fix the features names ?"
] | 2020-09-11T20:46:23Z | 2020-09-16T06:59:19Z | 2020-09-16T06:59:19Z | CONTRIBUTOR | null | null | {
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} | I think the following features in MLQA shouldn't be named the way they are:
1. `questions` (should be `question`)
2. `ids` (should be `id`)
3. `start` (should be `answer_start`)
The reasons I'm suggesting these features be renamed are:
* To make them consistent with other QA datasets like SQuAD, XQuAD, TyDiQA et... | {
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https://api.github.com/repos/huggingface/datasets/issues/617 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/617/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/617/comments | https://api.github.com/repos/huggingface/datasets/issues/617/events | https://github.com/huggingface/datasets/issues/617 | 699,472,596 | MDU6SXNzdWU2OTk0NzI1OTY= | 617 | Compare different Rouge implementations | {
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"Updates - the differences between the following three\r\n(1) https://github.com/bheinzerling/pyrouge (previously popular. The one I trust the most)\r\n(2) https://github.com/google-research/google-research/tree/master/rouge\r\n(3) https://github.com/pltrdy/files2rouge (used in fairseq)\r\ncan be explained by two t... | 2020-09-11T15:49:32Z | 2023-03-22T12:08:44Z | 2020-10-02T09:52:18Z | NONE | null | null | {
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} | I used RougeL implementation provided in `datasets` [here](https://github.com/huggingface/datasets/blob/master/metrics/rouge/rouge.py) and it gives numbers that match those reported in the pegasus paper but very different from those reported in other papers, [this](https://arxiv.org/pdf/1909.03186.pdf) for example.
Ca... | {
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https://api.github.com/repos/huggingface/datasets/issues/615 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/615/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/615/comments | https://api.github.com/repos/huggingface/datasets/issues/615/events | https://github.com/huggingface/datasets/issues/615 | 699,410,773 | MDU6SXNzdWU2OTk0MTA3NzM= | 615 | Offset overflow when slicing a big dataset with an array of indices in Pyarrow >= 1.0.0 | {
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"Related: https://issues.apache.org/jira/browse/ARROW-9773\r\n\r\nIt's definitely a size thing. I took a smaller dataset with 87000 rows and did:\r\n```\r\nfor i in range(10,1000,20):\r\n table = pa.concat_tables([dset._data]*i)\r\n table.take([0])\r\n```\r\nand it broke at around i=300.\r\n\r\nAlso when `_in... | 2020-09-11T14:50:38Z | 2024-05-02T06:53:15Z | 2020-09-19T16:46:31Z | MEMBER | null | null | {
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} | How to reproduce:
```python
from datasets import load_dataset
wiki = load_dataset("wikipedia", "20200501.en", split="train")
wiki[[0]]
---------------------------------------------------------------------------
ArrowInvalid Traceback (most recent call last)
<ipython-input-13-38... | {
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https://api.github.com/repos/huggingface/datasets/issues/611 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/611/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/611/comments | https://api.github.com/repos/huggingface/datasets/issues/611/events | https://github.com/huggingface/datasets/issues/611 | 698,863,988 | MDU6SXNzdWU2OTg4NjM5ODg= | 611 | ArrowCapacityError: List array cannot contain more than 2147483646 child elements, have 2147483648 | {
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"Can you give us stats/information on your pandas DataFrame?",
"```\r\n<class 'pandas.core.frame.DataFrame'>\r\nInt64Index: 17136104 entries, 0 to 17136103\r\nData columns (total 6 columns):\r\n # Column Dtype \r\n--- ------ ----- \r\n 0 item_id int64 \r\n 1 item_titl object \r\n... | 2020-09-11T05:29:12Z | 2022-06-01T15:11:43Z | 2022-06-01T15:11:43Z | NONE | null | null | {
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```bash
---------------------------------------------------------------------------
ArrowCapacityError Traceback (most recent call last)
<ipython-input-7-146b6b495963> in <module>
----> 1 dataset = Dataset.from_pandas(emb)... | {
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https://api.github.com/repos/huggingface/datasets/issues/610 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/610/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/610/comments | https://api.github.com/repos/huggingface/datasets/issues/610/events | https://github.com/huggingface/datasets/issues/610 | 698,349,388 | MDU6SXNzdWU2OTgzNDkzODg= | 610 | Load text file for RoBERTa pre-training. | {
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"Could you try\r\n```python\r\nload_dataset('text', data_files='test.txt',cache_dir=\"./\", split=\"train\")\r\n```\r\n?\r\n\r\n`load_dataset` returns a dictionary by default, like {\"train\": your_dataset}",
"Hi @lhoestq\r\nThanks for your suggestion.\r\n\r\nI tried \r\n```\r\ndataset = load_dataset('text', data... | 2020-09-10T18:41:38Z | 2022-11-22T13:51:24Z | 2022-11-22T13:51:23Z | NONE | null | null | {
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} | I migrate my question from https://github.com/huggingface/transformers/pull/4009#issuecomment-690039444
I tried to train a Roberta from scratch using transformers. But I got OOM issues with loading a large text file.
According to the suggestion from @thomwolf , I tried to implement `datasets` to load my text file.... | {
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https://api.github.com/repos/huggingface/datasets/issues/608 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/608/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/608/comments | https://api.github.com/repos/huggingface/datasets/issues/608/events | https://github.com/huggingface/datasets/issues/608 | 698,291,156 | MDU6SXNzdWU2OTgyOTExNTY= | 608 | Don't use the old NYU GLUE dataset URLs | {
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"Feel free to open the PR ;)\r\nThanks for updating the dataset_info.json file !"
] | 2020-09-10T17:47:02Z | 2020-09-16T06:53:18Z | 2020-09-16T06:53:18Z | CONTRIBUTOR | null | null | {
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} | NYU is switching dataset hosting from Google to FB. Initial changes to `datasets` are in https://github.com/jeswan/nlp/commit/b7d4a071d432592ded971e30ef73330529de25ce. What tests do you suggest I run before opening a PR?
See: https://github.com/jiant-dev/jiant/issues/161 and https://github.com/nyu-mll/jiant/pull/111... | {
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https://api.github.com/repos/huggingface/datasets/issues/600 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/600/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/600/comments | https://api.github.com/repos/huggingface/datasets/issues/600/events | https://github.com/huggingface/datasets/issues/600 | 697,496,913 | MDU6SXNzdWU2OTc0OTY5MTM= | 600 | Pickling error when loading dataset | {
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"When I change from python3.6 to python3.8, it works! ",
"Does it work when you install `nlp` from source on python 3.6?",
"No, still the pickling error.",
"I wasn't able to reproduce on google colab (python 3.6.9 as well) with \r\n\r\npickle==4.0\r\ndill=0.3.2\r\ntransformers==3.1.0\r\ndatasets=1.0.1 (also t... | 2020-09-10T06:28:08Z | 2020-09-25T14:31:54Z | 2020-09-25T14:31:54Z | NONE | null | null | {
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I modified line 136 in the original [run_language_modeling.py](https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_language_modeling.py) as:
```
# line 136: return LineByLineTextDataset(tokenizer=tokenizer, file_path=file_path, block_size=args.block_size)
dataset = load_da... | {
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https://api.github.com/repos/huggingface/datasets/issues/598 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/598/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/598/comments | https://api.github.com/repos/huggingface/datasets/issues/598/events | https://github.com/huggingface/datasets/issues/598 | 697,156,501 | MDU6SXNzdWU2OTcxNTY1MDE= | 598 | The current version of the package on github has an error when loading dataset | {
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"Thanks for reporting !\r\nWhich version of transformers are you using ?\r\nIt looks like it doesn't have the PreTrainedTokenizerBase class",
"I was using transformer 2.9. And I switch to the latest transformer package. Everything works just fine!!\r\n\r\nThanks for helping! I should look more carefully next time... | 2020-09-09T21:03:23Z | 2020-09-10T06:25:21Z | 2020-09-09T22:57:28Z | NONE | null | null | {
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} | Instead of downloading the package from pip, downloading the version from source will result in an error when loading dataset (the pip version is completely fine):
To recreate the error:
First, installing nlp directly from source:
```
git clone https://github.com/huggingface/nlp.git
cd nlp
pip install -e .
``... | {
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https://api.github.com/repos/huggingface/datasets/issues/597 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/597/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/597/comments | https://api.github.com/repos/huggingface/datasets/issues/597/events | https://github.com/huggingface/datasets/issues/597 | 697,112,029 | MDU6SXNzdWU2OTcxMTIwMjk= | 597 | Indices incorrect with multiprocessing | {
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"I fixed a bug that could cause this issue earlier today. Could you pull the latest version and try again ?",
"Still the case on master.\r\nI guess we should have an offset in the multi-procs indeed (hopefully it's enough).\r\n\r\nAlso, side note is that we should add some logging before the \"test\" to say we ar... | 2020-09-09T19:50:56Z | 2020-09-10T11:03:37Z | 2020-09-10T11:03:37Z | CONTRIBUTOR | null | null | {
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} | When `num_proc` > 1, the indices argument passed to the map function is incorrect:
```python
d = load_dataset('imdb', split='test[:1%]')
def fn(x, inds):
print(inds)
return x
d.select(range(10)).map(fn, with_indices=True, batched=True)
# [0, 1]
# [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
d.select(range(10... | {
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https://api.github.com/repos/huggingface/datasets/issues/595 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/595/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/595/comments | https://api.github.com/repos/huggingface/datasets/issues/595/events | https://github.com/huggingface/datasets/issues/595 | 696,892,304 | MDU6SXNzdWU2OTY4OTIzMDQ= | 595 | `Dataset`/`DatasetDict` has no attribute 'save_to_disk' | {
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"`pip install git+https://github.com/huggingface/nlp.git` should have done the job.\r\n\r\nDid you uninstall `nlp` before installing from github ?",
"> Did you uninstall `nlp` before installing from github ?\r\n\r\nI did not. I created a new environment and installed `nlp` directly from `github` and it worked!\r\... | 2020-09-09T15:01:52Z | 2020-09-09T16:20:19Z | 2020-09-09T16:20:18Z | NONE | null | null | {
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As the title indicates, both `Dataset` and `DatasetDict` classes don't seem to have the `save_to_disk` method. While the file [`arrow_dataset.py`](https://github.com/huggingface/nlp/blob/34bf0b03bfe03e7f77b8fec1cd48f5452c4fc7c1/src/nlp/arrow_dataset.py) in the repo here has the method, the file `arrow_dataset.p... | {
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https://api.github.com/repos/huggingface/datasets/issues/590 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/590/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/590/comments | https://api.github.com/repos/huggingface/datasets/issues/590/events | https://github.com/huggingface/datasets/issues/590 | 696,501,827 | MDU6SXNzdWU2OTY1MDE4Mjc= | 590 | The process cannot access the file because it is being used by another process (windows) | {
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"Hi, which version of `nlp` are you using?\r\n\r\nBy the way we'll be releasing today a significant update fixing many issues (but also comprising a few breaking changes).\r\nYou can see more informations here #545 and try it by installing from source from the master branch.",
"I'm using version 0.4.0.\r\n\r\n",
... | 2020-09-09T07:01:36Z | 2020-09-25T14:02:28Z | 2020-09-25T14:02:28Z | NONE | null | null | {
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} | Hi, I consistently get the following error when developing in my PC (windows 10):
```
train_dataset = train_dataset.map(convert_to_features, batched=True)
File "C:\Users\saareliad\AppData\Local\Continuum\miniconda3\envs\py38\lib\site-packages\nlp\arrow_dataset.py", line 970, in map
shutil.move(tmp_file.... | {
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https://api.github.com/repos/huggingface/datasets/issues/589 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/589/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/589/comments | https://api.github.com/repos/huggingface/datasets/issues/589/events | https://github.com/huggingface/datasets/issues/589 | 696,488,447 | MDU6SXNzdWU2OTY0ODg0NDc= | 589 | Cannot use nlp.load_dataset text, AttributeError: module 'nlp.utils' has no attribute 'logging' | {
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```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/root/anaconda3/envs/pytorch/lib/python3.7/site-packages/nlp/load.py", line 533, in load_dataset
builder_cls = import_main_class(module_path, dataset=True)
File "/root/anaconda3/envs/pytorch/lib/python3.7/site-packages/nlp... | {
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https://api.github.com/repos/huggingface/datasets/issues/583 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/583/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/583/comments | https://api.github.com/repos/huggingface/datasets/issues/583/events | https://github.com/huggingface/datasets/issues/583 | 695,166,265 | MDU6SXNzdWU2OTUxNjYyNjU= | 583 | ArrowIndexError on Dataset.select | {
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} | If the indices table consists in several chunks, then `dataset.select` results in an `ArrowIndexError` error for pyarrow < 1.0.0
Example:
```python
from nlp import load_dataset
mnli = load_dataset("glue", "mnli", split="train")
shuffled = mnli.shuffle(seed=42)
mnli.select(list(range(len(mnli))))
```
rai... | {
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https://api.github.com/repos/huggingface/datasets/issues/582 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/582/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/582/comments | https://api.github.com/repos/huggingface/datasets/issues/582/events | https://github.com/huggingface/datasets/issues/582 | 695,126,456 | MDU6SXNzdWU2OTUxMjY0NTY= | 582 | Allow for PathLike objects | {
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} | Using PathLike objects as input for `load_dataset` does not seem to work. The following will throw an error.
```python
files = list(Path(r"D:\corpora\yourcorpus").glob("*.txt"))
dataset = load_dataset("text", data_files=files)
```
Traceback:
```
Traceback (most recent call last):
File "C:/dev/python/dut... | {
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https://api.github.com/repos/huggingface/datasets/issues/581 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/581/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/581/comments | https://api.github.com/repos/huggingface/datasets/issues/581/events | https://github.com/huggingface/datasets/issues/581 | 695,120,517 | MDU6SXNzdWU2OTUxMjA1MTc= | 581 | Better error message when input file does not exist | {
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} | In the following scenario, when `data_files` is an empty list, the stack trace and error message could be improved. This can probably be solved by checking for each file whether it actually exists and/or whether the argument is not false-y.
```python
dataset = load_dataset("text", data_files=[])
```
Example err... | {
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https://api.github.com/repos/huggingface/datasets/issues/580 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/580/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/580/comments | https://api.github.com/repos/huggingface/datasets/issues/580/events | https://github.com/huggingface/datasets/issues/580 | 694,954,551 | MDU6SXNzdWU2OTQ5NTQ1NTE= | 580 | nlp re-creates already-there caches when using a script, but not within a shell | {
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"Couln't reproduce on my side :/ \r\nlet me know if you manage to reproduce on another env (colab for example)",
"Fixed with a clean re-install!"
] | 2020-09-07T10:23:50Z | 2020-09-07T15:19:09Z | 2020-09-07T14:26:41Z | CONTRIBUTOR | null | null | {
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} | `nlp` keeps creating new caches for the same file when launching `filter` from a script, and behaves correctly from within the shell.
Example: try running
```
import nlp
hans_easy_data = nlp.load_dataset('hans', split="validation").filter(lambda x: x['label'] == 0)
hans_hard_data = nlp.load_dataset('hans', s... | {
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https://api.github.com/repos/huggingface/datasets/issues/577 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/577/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/577/comments | https://api.github.com/repos/huggingface/datasets/issues/577/events | https://github.com/huggingface/datasets/issues/577 | 694,607,148 | MDU6SXNzdWU2OTQ2MDcxNDg= | 577 | Some languages in wikipedia dataset are not loading | {
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"Some wikipedia languages have already been processed by us and are hosted on our google storage. This is the case for \"fr\" and \"en\" for example.\r\n\r\nFor other smaller languages (in terms of bytes), they are directly downloaded and parsed from the wikipedia dump site.\r\nParsing can take some time for langua... | 2020-09-07T01:16:29Z | 2023-04-11T22:50:48Z | 2022-10-11T11:16:04Z | CONTRIBUTOR | null | null | {
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} | Hi,
I am working with the `wikipedia` dataset and I have a script that goes over 92 of the available languages in that dataset. So far I have detected that `ar`, `af`, `an` are not loading. Other languages like `fr` and `en` are working fine. Here's how I am loading them:
```
import nlp
langs = ['ar'. 'af', '... | {
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https://api.github.com/repos/huggingface/datasets/issues/575 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/575/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/575/comments | https://api.github.com/repos/huggingface/datasets/issues/575/events | https://github.com/huggingface/datasets/issues/575 | 693,691,611 | MDU6SXNzdWU2OTM2OTE2MTE= | 575 | Couldn't reach certain URLs and for the ones that can be reached, code just blocks after downloading. | {
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"Update:\r\n\r\nThe imdb download completed after a long time (about 45 mins). Ofcourse once download loading was instantaneous. Also, the loaded object was of type `arrow_dataset`. \r\n\r\nThe urls for glue still doesn't work though.",
"Thanks for the report, I'll give a look!",
"I am also seeing a similar err... | 2020-09-04T21:46:25Z | 2020-09-22T10:41:36Z | 2020-09-22T10:41:36Z | NONE | null | null | {
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I'm following the [quick tour](https://huggingface.co/nlp/quicktour.html) and tried to load the glue dataset:
```
>>> from nlp import load_dataset
>>> dataset = load_dataset('glue', 'mrpc', split='train')
```
However, this ran into a `ConnectionError` saying it could not reach the URL (just pasting the la... | {
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https://api.github.com/repos/huggingface/datasets/issues/568 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/568/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/568/comments | https://api.github.com/repos/huggingface/datasets/issues/568/events | https://github.com/huggingface/datasets/issues/568 | 691,638,656 | MDU6SXNzdWU2OTE2Mzg2NTY= | 568 | `metric.compute` throws `ArrowInvalid` error | {
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"Hmm might be related to what we are solving in #564",
"Could you try to update to `datasets>=1.0.0` (we changed the name of the library) and try again ?\r\nIf is was related to the distributed setup settings it must be fixed.\r\nIf it was related to empty metric inputs it's going to be fixed in #654 ",
"Closin... | 2020-09-03T04:56:57Z | 2020-10-05T16:33:53Z | 2020-10-05T16:33:53Z | NONE | null | null | {
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} | I get the following error with `rouge.compute`. It happens only with distributed training, and it occurs randomly I can't easily reproduce it. This is using `nlp==0.4.0`
```
File "/home/beltagy/trainer.py", line 92, in validation_step
rouge_scores = rouge.compute(predictions=generated_str, references=gold_st... | {
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https://api.github.com/repos/huggingface/datasets/issues/565 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/565/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/565/comments | https://api.github.com/repos/huggingface/datasets/issues/565/events | https://github.com/huggingface/datasets/issues/565 | 691,039,121 | MDU6SXNzdWU2OTEwMzkxMjE= | 565 | No module named 'nlp.logging' | {
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"Thanks for reporting.\r\n\r\nApparently this is a versioning issue: the lib downloaded the `bleurt` script from the master branch where we did this change recently. We'll fix that in a new release this week or early next week. Cc @thomwolf \r\n\r\nUntil that, I'd suggest you to download the right bleurt folder fro... | 2020-09-02T13:49:50Z | 2020-09-03T07:29:50Z | 2020-09-03T07:29:50Z | NONE | null | null | {
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} | Hi, I am using nlp version 0.4.0. Trying to use bleurt as an eval metric, however, the bleurt script imports nlp.logging which creates the following error. What am I missing?
```
>>> import nlp
2020-09-02 13:47:09.210310: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic l... | {
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https://api.github.com/repos/huggingface/datasets/issues/560 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/560/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/560/comments | https://api.github.com/repos/huggingface/datasets/issues/560/events | https://github.com/huggingface/datasets/issues/560 | 690,488,764 | MDU6SXNzdWU2OTA0ODg3NjQ= | 560 | Using custom DownloadConfig results in an error | {
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"From my limited understanding, part of the issue seems related to the `prepare_module` and `download_and_prepare` functions each handling the case where no config is passed. For example, `prepare_module` does mutate the object passed and forces the flags `extract_compressed_file` and `force_extract` to `True`.\r\... | 2020-09-01T22:23:02Z | 2022-10-04T17:23:45Z | 2022-10-04T17:23:45Z | NONE | null | null | {
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} | ## Version / Environment
Ubuntu 18.04
Python 3.6.8
nlp 0.4.0
## Description
Loading `imdb` dataset works fine when when I don't specify any `download_config` argument. When I create a custom `DownloadConfig` object and pass it to the `nlp.load_dataset` function, this results in an error.
## How to reprodu... | {
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https://api.github.com/repos/huggingface/datasets/issues/554 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/554/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/554/comments | https://api.github.com/repos/huggingface/datasets/issues/554/events | https://github.com/huggingface/datasets/issues/554 | 690,173,214 | MDU6SXNzdWU2OTAxNzMyMTQ= | 554 | nlp downloads to its module path | {
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"Indeed this is a known issue arising from the fact that we try to be compatible with cloupickle.\r\n\r\nDoes this also happen if you are installing in a virtual environment?",
"> Indeed this is a know issue with the fact that we try to be compatible with cloupickle.\r\n> \r\n> Does this also happen if you are in... | 2020-09-01T14:06:14Z | 2020-09-11T06:19:24Z | 2020-09-11T06:19:24Z | MEMBER | null | null | {
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} | I am trying to package `nlp` for Nix, because it is now an optional dependency for `transformers`. The problem that I encounter is that the `nlp` library downloads to the module path, which is typically not writable in most package management systems:
```>>> import nlp
>>> squad_dataset = nlp.load_dataset('squad')
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https://api.github.com/repos/huggingface/datasets/issues/546 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/546/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/546/comments | https://api.github.com/repos/huggingface/datasets/issues/546/events | https://github.com/huggingface/datasets/issues/546 | 689,186,526 | MDU6SXNzdWU2ODkxODY1MjY= | 546 | Very slow data loading on large dataset | {
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"When you load a text file for the first time with `nlp`, the file is converted into Apache Arrow format. Arrow allows to use memory-mapping, which means that you can load an arbitrary large dataset.\r\n\r\nNote that as soon as the conversion has been done once, the next time you'll load the dataset it will be much... | 2020-08-31T12:57:23Z | 2024-01-02T20:26:24Z | 2020-09-08T10:19:57Z | NONE | null | null | {
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} | I made a simple python script to check the NLP library speed, which loads 1.1 TB of textual data.
It has been 8 hours and still, it is on the loading steps.
It does work when the text dataset size is small about 1 GB, but it doesn't scale.
It also uses a single thread during the data loading step.
```
train_fil... | {
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https://api.github.com/repos/huggingface/datasets/issues/545 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/545/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/545/comments | https://api.github.com/repos/huggingface/datasets/issues/545/events | https://github.com/huggingface/datasets/issues/545 | 689,138,878 | MDU6SXNzdWU2ODkxMzg4Nzg= | 545 | New release coming up for this library | {
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"Update: release is planed mid-next week."
] | 2020-08-31T11:37:38Z | 2021-01-13T10:59:04Z | 2021-01-13T10:59:04Z | MEMBER | null | null | {
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} | Hi all,
A few words on the roadmap for this library.
The next release will be a big one and is planed at the end of this week.
In addition to the support for indexed datasets (useful for non-parametric models like REALM, RAG, DPR, knn-LM and many other fast dataset retrieval technics), it will:
- have support f... | {
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https://api.github.com/repos/huggingface/datasets/issues/543 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/543/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/543/comments | https://api.github.com/repos/huggingface/datasets/issues/543/events | https://github.com/huggingface/datasets/issues/543 | 688,644,407 | MDU6SXNzdWU2ODg2NDQ0MDc= | 543 | nlp.load_dataset is not safe for multi processes when loading from local files | {
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"I'll take a look!"
] | 2020-08-30T03:20:34Z | 2020-08-31T11:15:10Z | 2020-08-31T11:15:10Z | NONE | null | null | {
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} | Loading from local files, e.g., `dataset = nlp.load_dataset('csv', data_files=['file_1.csv', 'file_2.csv'])`
concurrently from multiple processes, will raise `FileExistsError` from builder's line 430, https://github.com/huggingface/nlp/blob/6655008c738cb613c522deb3bd18e35a67b2a7e5/src/nlp/builder.py#L423-L438
Likel... | {
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https://api.github.com/repos/huggingface/datasets/issues/541 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/541/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/541/comments | https://api.github.com/repos/huggingface/datasets/issues/541/events | https://github.com/huggingface/datasets/issues/541 | 688,521,224 | MDU6SXNzdWU2ODg1MjEyMjQ= | 541 | Best practices for training tokenizers with nlp | {
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"Docs that explain how to train a tokenizer with `datasets` are available here: https://huggingface.co/docs/tokenizers/training_from_memory#using-the-datasets-library"
] | 2020-08-29T12:06:49Z | 2022-10-04T17:28:04Z | 2022-10-04T17:28:04Z | NONE | null | null | {
"completed": 0,
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} | Hi, thank you for developing this library.
What do you think are the best practices for training tokenizers using `nlp`? In the document and examples, I could only find pre-trained tokenizers used. | {
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https://api.github.com/repos/huggingface/datasets/issues/539 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/539/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/539/comments | https://api.github.com/repos/huggingface/datasets/issues/539/events | https://github.com/huggingface/datasets/issues/539 | 688,323,602 | MDU6SXNzdWU2ODgzMjM2MDI= | 539 | [Dataset] `NonMatchingChecksumError` due to an update in the LinCE benchmark data | {
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"Hi @gaguilar \r\n\r\nIf you want to take care of this, it very simple, you just need to regenerate the `dataset_infos.json` file as indicated [in the doc](https://huggingface.co/nlp/share_dataset.html#adding-metadata) by [installing from source](https://huggingface.co/nlp/installation.html#installing-from-source) ... | 2020-08-28T19:55:51Z | 2020-09-03T16:34:02Z | 2020-09-03T16:34:01Z | CONTRIBUTOR | null | null | {
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} | Hi,
There is a `NonMatchingChecksumError` error for the `lid_msaea` (language identification for Modern Standard Arabic - Egyptian Arabic) dataset from the LinCE benchmark due to a minor update on that dataset.
How can I update the checksum of the library to solve this issue? The error is below and it also appea... | {
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https://api.github.com/repos/huggingface/datasets/issues/537 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/537/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/537/comments | https://api.github.com/repos/huggingface/datasets/issues/537/events | https://github.com/huggingface/datasets/issues/537 | 687,614,699 | MDU6SXNzdWU2ODc2MTQ2OTk= | 537 | [Dataset] RACE dataset Checksums error | {
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"color": "2edb81",
"default": false,
"description": "A bug in a dataset script provided in the library",
"id": 2067388877,
"name": "dataset bug",
"node_id": "MDU6TGFiZWwyMDY3Mzg4ODc3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/dataset%20bug"
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"`NonMatchingChecksumError` means that the checksum of the downloaded file is not the expected one.\r\nEither the file you downloaded was corrupted along the way, or the host updated the file.\r\nCould you try to clear your cache and run `load_dataset` again ? If the error is still there, it means that there was an... | 2020-08-27T23:58:16Z | 2020-09-18T12:07:04Z | 2020-09-18T12:07:04Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | Hi there, I just would like to use this awesome lib to perform a dataset fine-tuning on RACE dataset. I have performed the following steps:
```
dataset = nlp.load_dataset("race")
len(dataset["train"]), len(dataset["validation"])
```
But then I got the following error:
```
----------------------------------... | {
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https://api.github.com/repos/huggingface/datasets/issues/534 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/534/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/534/comments | https://api.github.com/repos/huggingface/datasets/issues/534/events | https://github.com/huggingface/datasets/issues/534 | 686,115,912 | MDU6SXNzdWU2ODYxMTU5MTI= | 534 | `list_datasets()` is broken. | {
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"Thanks for reporting !\r\nThis has been fixed in #475 and the fix will be available in the next release",
"What you can do instead to get the list of the datasets is call\r\n\r\n```python\r\nprint([dataset.id for dataset in nlp.list_datasets()])\r\n```",
"Thanks @lhoestq . "
] | 2020-08-26T08:19:01Z | 2020-08-27T06:31:11Z | 2020-08-27T06:31:11Z | NONE | null | null | {
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} | version = '0.4.0'
`list_datasets()` is broken. It results in the following error :
```
In [3]: nlp.list_datasets()
Out[3]: ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
~/.virtualenvs/san-lgUCsFg_/lib/py... | {
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https://api.github.com/repos/huggingface/datasets/issues/525 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/525/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/525/comments | https://api.github.com/repos/huggingface/datasets/issues/525/events | https://github.com/huggingface/datasets/issues/525 | 683,875,483 | MDU6SXNzdWU2ODM4NzU0ODM= | 525 | wmt download speed example | {
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"Thanks for creating the issue :)\r\nThe download link for wmt-en-de raw looks like a mirror. We should use that instead of the current url.\r\nIs this mirror official ?\r\n\r\nAlso it looks like for `ro-en` it tried to download other languages. If we manage to only download the one that is asked it'd be cool\r\n\r... | 2020-08-21T23:29:06Z | 2022-10-04T17:45:39Z | 2022-10-04T17:45:39Z | CONTRIBUTOR | null | null | {
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} | Continuing from the slack 1.0 roadmap thread w @lhoestq , I realized the slow downloads is only a thing sometimes. Here are a few examples, I suspect there are multiple issues. All commands were run from the same gcp us-central-1f machine.
```
import nlp
nlp.load_dataset('wmt16', 'de-en')
```
Downloads at 49.1 K... | {
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"Indeed, good catch!"
] | 2020-08-21T16:47:34Z | 2020-08-25T09:04:03Z | 2020-08-25T09:04:03Z | CONTRIBUTOR | null | null | {
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} | See https://huggingface.co/nlp/master/package_reference/main_classes.html#nlp.Dataset.map. I believe this is because the parameter names are enclosed in backticks in the docstrings, maybe it's an old docstring format that doesn't work with the current Sphinx version. | {
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"Thanks!"
] | 2020-08-20T07:11:05Z | 2020-08-20T07:52:14Z | 2020-08-20T07:52:13Z | CONTRIBUTOR | null | null | {
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} | Many places dictionary is spelled dictionnary, not sure if its on purpose or not.
Fixed in this pr:
https://github.com/huggingface/nlp/pull/521 | {
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https://api.github.com/repos/huggingface/datasets/issues/519 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/519/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/519/comments | https://api.github.com/repos/huggingface/datasets/issues/519/events | https://github.com/huggingface/datasets/issues/519 | 682,193,882 | MDU6SXNzdWU2ODIxOTM4ODI= | 519 | [BUG] Metrics throwing new error on master since 0.4.0 | {
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"Update - maybe this is only failing on bleu because I was not tokenizing inputs to the metric",
"Closing - seems to be just forgetting to tokenize. And found the helpful discussion in huggingface/evaluate#105 "
] | 2020-08-19T21:29:15Z | 2022-06-02T16:41:01Z | 2020-08-19T22:04:40Z | CONTRIBUTOR | null | null | {
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} | The following error occurs when passing in references of type `List[List[str]]` to metrics like bleu.
Wasn't happening on 0.4.0 but happening now on master.
```
File "/usr/local/lib/python3.7/site-packages/nlp/metric.py", line 226, in compute
self.add_batch(predictions=predictions, references=references)
... | {
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https://api.github.com/repos/huggingface/datasets/issues/514 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/514/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/514/comments | https://api.github.com/repos/huggingface/datasets/issues/514/events | https://github.com/huggingface/datasets/issues/514 | 681,256,348 | MDU6SXNzdWU2ODEyNTYzNDg= | 514 | dataset.shuffle(keep_in_memory=True) is never allowed | {
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"This seems to be fixed in #513 for the filter function, replacing `cache_file_name` with `indices_cache_file_name` in the assert. Although not for the `map()` function @thomwolf ",
"Maybe I'm a bit tired but I fail to see the issue here.\r\n\r\nSince `cache_file_name` is `None` by default, if you set `keep_in_me... | 2020-08-18T18:47:40Z | 2022-10-10T12:21:58Z | 2022-10-10T12:21:58Z | CONTRIBUTOR | null | null | {
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} | As of commit ef4aac2, the usage of the parameter `keep_in_memory=True` is never possible: `dataset.select(keep_in_memory=True)`
The commit added the lines
```python
# lines 994-996 in src/nlp/arrow_dataset.py
assert (
not keep_in_memory or cache_file_name is None
), "Please use either... | {
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https://api.github.com/repos/huggingface/datasets/issues/511 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/511/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/511/comments | https://api.github.com/repos/huggingface/datasets/issues/511/events | https://github.com/huggingface/datasets/issues/511 | 681,055,553 | MDU6SXNzdWU2ODEwNTU1NTM= | 511 | dataset.shuffle() and select() resets format. Intended? | {
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"Hi @vegarab yes feel free to open a discussion here.\r\n\r\nThis design choice was not very much thought about.\r\n\r\nSince `dataset.select()` (like all the method without a trailing underscore) is non-destructive and returns a new dataset it has most of its properties initialized from scratch (except the table a... | 2020-08-18T13:46:01Z | 2020-09-14T08:45:38Z | 2020-09-14T08:45:38Z | CONTRIBUTOR | null | null | {
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} | Calling `dataset.shuffle()` or `dataset.select()` on a dataset resets its format set by `dataset.set_format()`. Is this intended or an oversight?
When working on quite large datasets that require a lot of preprocessing I find it convenient to save the processed dataset to file using `torch.save("dataset.pt")`. Later... | {
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https://api.github.com/repos/huggingface/datasets/issues/510 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/510/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/510/comments | https://api.github.com/repos/huggingface/datasets/issues/510/events | https://github.com/huggingface/datasets/issues/510 | 680,823,644 | MDU6SXNzdWU2ODA4MjM2NDQ= | 510 | Version of numpy to use the library | {
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"Seems like this method was added in 1.17. I'll add a requirement on this.",
"Thank you so much. After upgrading the numpy library, it worked."
] | 2020-08-18T08:59:13Z | 2020-08-19T18:35:56Z | 2020-08-19T18:35:56Z | NONE | null | null | {
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} | Thank you so much for your excellent work! I would like to use nlp library in my project. While importing nlp, I am receiving the following error `AttributeError: module 'numpy.random' has no attribute 'Generator'` Numpy version in my project is 1.16.0. May I learn which numpy version is used for the nlp library.
Th... | {
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"Do you want to convert a dataset script to the tfds format ?\r\nIf so, we currently have a comversion script nlp/commands/convert.py but it is a conversion script that goes from tfds to nlp.\r\nI think it shouldn't be too hard to do the changes in reverse (at some manual adjustments).\r\nIf you manage to make it w... | 2020-08-16T08:05:20Z | 2021-08-03T06:01:18Z | 2021-08-03T06:01:17Z | NONE | null | null | {
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I want to use TensorFlow datasets with this repo, I noticed you made some conversion script,
can you give a simple example of using it?
Thanks
| {
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https://api.github.com/repos/huggingface/datasets/issues/508 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/508/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/508/comments | https://api.github.com/repos/huggingface/datasets/issues/508/events | https://github.com/huggingface/datasets/issues/508 | 679,705,734 | MDU6SXNzdWU2Nzk3MDU3MzQ= | 508 | TypeError: Receiver() takes no arguments | {
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"Which version of Apache Beam do you have (can you copy your full environment info here)?",
"apache-beam==2.23.0\r\nnlp==0.4.0\r\n\r\nFor me this was resolved by running the same python script on Linux (or really WSL). ",
"Do you manage to run a dummy beam pipeline with python on windows ? \r\nYou can test a du... | 2020-08-16T07:18:16Z | 2020-09-01T14:53:33Z | 2020-09-01T14:49:03Z | NONE | null | null | {
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```
import nlp
from nlp import load_dataset
dataset = load_dataset("wikipedia", "20200501.en", split="train", cache_dir=data_path, beam_runner='DirectRunner')
#dataset = load_dataset('wikipedia', '20200501.sv', cache_dir=data_path, beam_runner='DirectRunner')
```
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https://api.github.com/repos/huggingface/datasets/issues/507 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/507/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/507/comments | https://api.github.com/repos/huggingface/datasets/issues/507/events | https://github.com/huggingface/datasets/issues/507 | 679,400,683 | MDU6SXNzdWU2Nzk0MDA2ODM= | 507 | Errors when I use | {
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"Looks like an issue with 3.0.2 transformers version. Works fine when I use \"master\" version of transformers."
] | 2020-08-14T21:03:57Z | 2020-08-14T21:39:10Z | 2020-08-14T21:39:10Z | NONE | null | null | {
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I am using **transformers 3.0.2** code .
from transformers.pipelines import pipeline
from transformers.modeling_auto import AutoModelForQuestionAnswering
from transformers.tokenization_auto import AutoToke... | {
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"Thanks for reporting !\r\n\r\nTo store the cache file, we compute a hash of the function given in `.map`, using our own hashing function.\r\nThe hash doesn't seem to stay the same over sessions for the tokenizer.\r\nApparently this is because of the regex at `tokenizer.pat` is not well supported by our hashing fun... | 2020-08-12T20:20:07Z | 2022-08-08T11:02:23Z | 2020-08-24T16:34:35Z | NONE | null | null | {
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} | The caching functionality doesn't work reliably when tokenizing a dataset. Here's a small example to reproduce it.
```python
import nlp
import transformers
def main():
ds = nlp.load_dataset("reddit", split="train[:500]")
tokenizer = transformers.AutoTokenizer.from_pretrained("gpt2")
def conv... | {
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https://api.github.com/repos/huggingface/datasets/issues/492 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/492/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/492/comments | https://api.github.com/repos/huggingface/datasets/issues/492/events | https://github.com/huggingface/datasets/issues/492 | 676,495,064 | MDU6SXNzdWU2NzY0OTUwNjQ= | 492 | nlp.Features does not distinguish between nullable and non-nullable types in PyArrow schema | {
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"In 0.4.0, the assertion in `concatenate_datasets ` is on the features, and not the schema.\r\nCould you try to update `nlp` ?\r\n\r\nAlso, since 0.4.0, you can use `dset_wikipedia.cast_(dset_books.features)` to avoid the schema cast hack.",
"Or maybe the assertion comes from elsewhere ?",
"I'm using the master... | 2020-08-11T00:27:46Z | 2020-08-26T16:17:19Z | 2020-08-26T16:17:19Z | CONTRIBUTOR | null | null | {
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```python
dset_wikipedia = nlp.load_dataset("wikipedia", "20200501.en", split="train", cache_dir=args.cache_dir)
dset_wikipedia.drop(columns=["title"])
dset_wikipedia.features.pop("title")
dset_books = nlp.load_dataset("bookcorpus", split="train", cache_dir=args.cache_dir)
dse... | {
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"I did the release on github, and updated the doc :)\r\nSorry for the delay",
"Thanks!"
] | 2020-08-10T23:59:57Z | 2020-08-11T16:50:07Z | 2020-08-11T16:50:07Z | CONTRIBUTOR | null | null | {
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} | 0.4.0 was released on PyPi, but not on GitHub. This means [the documentation](https://huggingface.co/nlp/) is still displaying from 0.3.0, and that there's no tag to easily clone the 0.4.0 version of the repo. | {
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"completed": 0,
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} | Running
`nlp.load_dataset("wikipedia", "20200501.en", split="train", dir="/tmp/wikipedia")`
gives an error if apache_beam is not installed, stemming from
https://github.com/huggingface/nlp/blob/38eb2413de54ee804b0be81781bd65ac4a748ced/src/nlp/builder.py#L981-L988
This succeeded without the dependency in ve... | {
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"whoops",
"please delete this"
] | 2020-08-10T22:33:03Z | 2020-08-10T22:55:14Z | 2020-08-10T22:33:40Z | NONE | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/488 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/488/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/488/comments | https://api.github.com/repos/huggingface/datasets/issues/488/events | https://github.com/huggingface/datasets/issues/488 | 676,299,993 | MDU6SXNzdWU2NzYyOTk5OTM= | 488 | issues with downloading datasets for wmt16 and wmt19 | {
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"I found `UNv1.0.en-ru.tar.gz` here: https://conferences.unite.un.org/uncorpus/en/downloadoverview, so it can be reconstructed with:\r\n```\r\nwget -c https://stuncorpusprod.blob.core.windows.net/corpusfiles/UNv1.0.en-ru.tar.gz.00\r\nwget -c https://stuncorpusprod.blob.core.windows.net/corpusfiles/UNv1.0.en-ru.tar.... | 2020-08-10T17:32:51Z | 2022-10-04T17:46:59Z | 2022-10-04T17:46:58Z | CONTRIBUTOR | null | null | {
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} | I have encountered multiple issues while trying to:
```
import nlp
dataset = nlp.load_dataset('wmt16', 'ru-en')
metric = nlp.load_metric('wmt16')
```
1. I had to do `pip install -e ".[dev]" ` on master, currently released nlp didn't work (sorry, didn't save the error) - I went back to the released version and no... | {
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https://api.github.com/repos/huggingface/datasets/issues/486 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/486/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/486/comments | https://api.github.com/repos/huggingface/datasets/issues/486/events | https://github.com/huggingface/datasets/issues/486 | 675,649,034 | MDU6SXNzdWU2NzU2NDkwMzQ= | 486 | Bookcorpus data contains pretokenized text | {
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"Yes indeed it looks like some `'` and spaces are missing (for example in `dont` or `didnt`).\r\nDo you know if there exist some copies without this issue ?\r\nHow would you fix this issue on the current data exactly ? I can see that the data is raw text (not tokenized) so I'm not sure I understand how you would do... | 2020-08-09T06:53:24Z | 2022-10-04T17:44:33Z | 2022-10-04T17:44:33Z | CONTRIBUTOR | null | null | {
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} | It seem that the bookcoprus data downloaded through the library was pretokenized with NLTK's Treebank tokenizer, which changes the text in incompatible ways to how, for instance, BERT's wordpiece tokenizer works. For example, "didn't" becomes "did" + "n't", and double quotes are changed to `` and '' for start and end q... | {
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https://api.github.com/repos/huggingface/datasets/issues/485 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/485/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/485/comments | https://api.github.com/repos/huggingface/datasets/issues/485/events | https://github.com/huggingface/datasets/issues/485 | 675,595,393 | MDU6SXNzdWU2NzU1OTUzOTM= | 485 | PAWS dataset first item is header | {
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} | ```
import nlp
dataset = nlp.load_dataset('xtreme', 'PAWS-X.en')
dataset['test'][0]
```
prints the following
```
{'label': 'label', 'sentence1': 'sentence1', 'sentence2': 'sentence2'}
```
dataset['test'][0] should probably be the first item in the dataset, not just a dictionary mapping the column names t... | {
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https://api.github.com/repos/huggingface/datasets/issues/483 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/483/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/483/comments | https://api.github.com/repos/huggingface/datasets/issues/483/events | https://github.com/huggingface/datasets/issues/483 | 675,080,694 | MDU6SXNzdWU2NzUwODA2OTQ= | 483 | rotten tomatoes movie review dataset taken down | {
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"found a mirror: https://storage.googleapis.com/seldon-datasets/sentence_polarity_v1/rt-polaritydata.tar.gz",
"fixed in #484 ",
"Closing this one. Thanks again @jxmorris12 for taking care of this :)"
] | 2020-08-07T15:12:01Z | 2020-09-08T09:36:34Z | 2020-09-08T09:36:33Z | CONTRIBUTOR | null | null | {
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} | In an interesting twist of events, the individual who created the movie review seems to have left Cornell, and their webpage has been removed, along with the movie review dataset (http://www.cs.cornell.edu/people/pabo/movie-review-data/rt-polaritydata.tar.gz). It's not downloadable anymore. | {
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"This comes from an overflow in pyarrow's array.\r\nIt is stuck inside the loop that reduces the batch size to avoid the overflow.\r\nI'll take a look",
"I created a PR to fix the issue.\r\nIt was due to an overflow check that handled badly an empty list.\r\n\r\nYou can try the changes by using \r\n```\r\n!pip in... | 2020-08-07T08:23:35Z | 2023-04-06T09:39:59Z | 2020-08-11T23:55:15Z | NONE | null | null | {
"completed": 0,
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} | Hi Huggingface Team!
Thank you guys once again for this amazing repo.
I have tried to prepare ELI5 to train with T5, based on [this wonderful notebook of Suraj Patil](https://github.com/patil-suraj/exploring-T5/blob/master/T5_on_TPU.ipynb)
However, when I run `dataset.map()` on ELI5 to prepare `input_text, ta... | {
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"Nevermind, I restarted my python session and it worked fine...\r\n\r\n---\r\n\r\nI had an authentification error, and I authenticated from another terminal. After that, no more error but it was not working. Restarting the sessions makes it work :)"
] | 2020-08-05T01:08:32Z | 2020-08-05T01:21:37Z | 2020-08-05T01:21:36Z | NONE | null | null | {
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} | Previously, I was writing TFRecords manually to GCP bucket with : `with tf.io.TFRecordWriter('gs://my_bucket/x.tfrecord')`
Since `0.4.0` is out with the `export()` function, I tried it. But it seems TFRecords cannot be directly written to GCP bucket.
`dataset.export('local.tfrecord')` works fine,
but `dataset.... | {
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"Thanks for reporting this issue\r\n\r\nThere was a bug where numpy arrays would get returned instead of tensorflow tensors.\r\nThis is fixed on master.\r\n\r\nI tried to re-run the colab and encountered this error instead:\r\n\r\n```\r\nAttributeError: 'tensorflow.python.framework.ops.EagerTensor' object has no at... | 2020-08-04T23:18:15Z | 2021-08-03T06:02:15Z | 2021-08-03T06:02:15Z | NONE | null | null | {
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} | with nlp 0.4.0, the TensorFlow example in Overview.ipynb throws the following exceptions:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-5-48907f2ad433> in <module>
----> 1 features = {x: trai... | {
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https://api.github.com/repos/huggingface/datasets/issues/474 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/474/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/474/comments | https://api.github.com/repos/huggingface/datasets/issues/474/events | https://github.com/huggingface/datasets/issues/474 | 672,407,330 | MDU6SXNzdWU2NzI0MDczMzA= | 474 | test_load_real_dataset when config has BUILDER_CONFIGS that matter | {
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"The `data_dir` parameter has been removed. Now the error is `ValueError: Config name is missing`\r\n\r\nAs mentioned in #470 I think we can have one test with the first config of BUILDER_CONFIGS, and another test that runs all of the configs in BUILDER_CONFIGS",
"This was fixed in #527 \r\n\r\nClosing this one, ... | 2020-08-03T23:46:36Z | 2020-09-07T14:53:13Z | 2020-09-07T14:53:13Z | NONE | null | null | {
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} | It a dataset has custom `BUILDER_CONFIGS` with non-keyword arguments (or keyword arguments with non default values), the config is not loaded during the test and causes an error.
I think the problem is that `test_load_real_dataset` calls `load_dataset` with `data_dir=temp_data_dir` ([here](https://github.com/huggingfa... | {
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https://api.github.com/repos/huggingface/datasets/issues/469 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/469/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/469/comments | https://api.github.com/repos/huggingface/datasets/issues/469/events | https://github.com/huggingface/datasets/issues/469 | 671,876,963 | MDU6SXNzdWU2NzE4NzY5NjM= | 469 | invalid data type 'str' at _convert_outputs in arrow_dataset.py | {
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"Hi ! Did you try to set the output format to pytorch ? (or tensorflow if you're using tensorflow)\r\nIt can be done with `dataset.set_format(\"torch\", columns=columns)` (or \"tensorflow\").\r\n\r\nNote that for pytorch, string columns can't be converted to `torch.Tensor`, so you have to specify in `columns=` the... | 2020-08-03T07:48:29Z | 2023-07-20T15:54:17Z | 2023-07-20T15:54:17Z | NONE | null | null | {
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} | I trying to build multi label text classifier model using Transformers lib.
I'm using Transformers NLP to load the data set, while calling trainer.train() method. It throws the following error
File "C:\***\arrow_dataset.py", line 343, in _convert_outputs
v = command(v)
TypeError: new(): invalid data type ... | {
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https://api.github.com/repos/huggingface/datasets/issues/468 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/468/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/468/comments | https://api.github.com/repos/huggingface/datasets/issues/468/events | https://github.com/huggingface/datasets/issues/468 | 671,622,441 | MDU6SXNzdWU2NzE2MjI0NDE= | 468 | UnicodeDecodeError while loading PAN-X task of XTREME dataset | {
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"Indeed. Solution 1 is the simplest.\r\n\r\nThis is actually a recurring problem.\r\nI think we should scan all the datasets with regexpr to fix the use of `open()` without encodings.\r\nAnd probably add a test in the CI to forbid using this in the future.",
"I'm happy to tackle the broader problem - will open a ... | 2020-08-02T14:05:10Z | 2020-08-20T08:16:08Z | 2020-08-20T08:16:08Z | MEMBER | null | null | {
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## Description of the problem
I'm running into a `UnicodeDecodeError` while trying to load the PAN-X subset the XTREME dataset:
```
---------------------------------------------------------------------------
UnicodeDecodeError Traceback (most recent call last)
<ipython-inp... | {
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https://api.github.com/repos/huggingface/datasets/issues/445 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/445/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/445/comments | https://api.github.com/repos/huggingface/datasets/issues/445/events | https://github.com/huggingface/datasets/issues/445 | 666,836,658 | MDU6SXNzdWU2NjY4MzY2NTg= | 445 | DEFAULT_TOKENIZER import error in sacrebleu | {
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"This issue was resolved by #447 "
] | 2020-07-28T07:31:30Z | 2020-07-28T12:58:56Z | 2020-07-28T12:58:56Z | CONTRIBUTOR | null | null | {
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When loading the metric "sacrebleu" there is an import error due to the wrong path
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https://api.github.com/repos/huggingface/datasets/issues/444 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/444/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/444/comments | https://api.github.com/repos/huggingface/datasets/issues/444/events | https://github.com/huggingface/datasets/issues/444 | 666,280,842 | MDU6SXNzdWU2NjYyODA4NDI= | 444 | Keep loading old file even I specify a new file in load_dataset | {
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"Same here !",
"This is the only fix I could come up with without touching the repo's code.\r\n```python\r\nfrom nlp.builder import FORCE_REDOWNLOAD\r\ndataset = load_dataset('csv', data_file='./a.csv', download_mode=FORCE_REDOWNLOAD, version='0.0.1')\r\n```\r\nYou'll have to change the version each time you want... | 2020-07-27T13:08:06Z | 2020-07-29T13:57:22Z | 2020-07-29T13:57:22Z | NONE | null | null | {
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} | I used load a file called 'a.csv' by
```
dataset = load_dataset('csv', data_file='./a.csv')
```
And after a while, I tried to load another csv called 'b.csv'
```
dataset = load_dataset('csv', data_file='./b.csv')
```
However, the new dataset seems to remain the old 'a.csv' and not loading new csv file.
Even... | {
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"This seems to be fixed in a non-released version. \r\n\r\nInstalling nlp from source\r\n```\r\ngit clone https://github.com/huggingface/nlp\r\ncd nlp\r\npip install .\r\n```\r\nsolves the issue. "
] | 2020-07-27T12:13:37Z | 2020-07-27T13:05:11Z | 2020-07-27T13:05:11Z | CONTRIBUTOR | null | null | {
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} | Saving a formatted torch dataset to file using `torch.save()`. Loading the same file fails during unpickling:
```python
>>> import torch
>>> import nlp
>>> squad = nlp.load_dataset("squad.py", split="train")
>>> squad
Dataset(features: {'source_text': Value(dtype='string', id=None), 'target_text': Value(dtype... | {
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"`DPRContextEncoder` and `DPRContextEncoderTokenizer` will be available in the next release of `transformers`.\r\n\r\nRight now you can experiment with it by installing `transformers` from the master branch.\r\nYou can also check the docs of DPR [here](https://huggingface.co/transformers/master/model_doc/dpr.html).... | 2020-07-27T04:25:17Z | 2020-10-28T01:46:24Z | 2020-10-28T01:46:24Z | NONE | null | null | {
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} | It seems the DPRContextEncoder, DPRContextEncoderTokenizer cited[ in this documentation](https://huggingface.co/nlp/faiss_and_ea.html) is not implemented ? It didnot work with the standard nlp installation . Also, I couldn't find or use it with the latest nlp install from github in Colab. Is there any dependency on t... | {
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"Indeed, we’ll make a new PyPi release next week to solve this. Cc @lhoestq ",
"+1! this is the reason our tests are failing at [TextAttack](https://github.com/QData/TextAttack) \r\n\r\n(Though it's worth noting if we fixed the version number of pyarrow to 0.16.0 that would fix our problem too. But in this case w... | 2020-07-25T13:05:20Z | 2020-08-20T08:08:18Z | 2020-08-20T08:08:18Z | NONE | null | null | {
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ImportWarning: To use `nlp`, the module `pyarrow>=0.16.0` is required, and the current version of `pyarrow` doesn't match this condition. If you are running this in a Google Colab, you should probably just rest... | {
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"This was fixed in #434 \r\nWe'll do a release later this week to include this fix.\r\nThanks for reporting",
"I dont know if the fix was made but the problem is still present : \r\nInstaled with pip : NLP 0.3.0 // pyarrow 1.0.0 \r\nOS : archlinux with kernel zen 5.8.5",
"Yes it was fixed in `nlp>=0.4.0`\r\nYou... | 2020-07-25T03:44:39Z | 2020-09-08T17:57:15Z | 2020-08-03T16:37:32Z | NONE | null | null | {
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"Hi @ArneBinder, we have a few \"generic\" datasets which are intended to load data files with a predefined format:\r\n- csv: https://github.com/huggingface/nlp/tree/master/datasets/csv\r\n- json: https://github.com/huggingface/nlp/tree/master/datasets/json\r\n- text: https://github.com/huggingface/nlp/tree/master/... | 2020-07-24T17:27:37Z | 2022-10-04T17:59:34Z | 2022-10-04T17:59:33Z | NONE | null | null | {
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} | I have written a generic dataset for corpora created with the Brat annotation tool ([specification](https://brat.nlplab.org/standoff.html), [dataset code](https://github.com/ArneBinder/nlp/blob/brat/datasets/brat/brat.py)). Now I wonder how to use that to create specific dataset instances. What's the recommended way to... | {
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https://api.github.com/repos/huggingface/datasets/issues/426 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/426/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/426/comments | https://api.github.com/repos/huggingface/datasets/issues/426/events | https://github.com/huggingface/datasets/issues/426 | 664,203,897 | MDU6SXNzdWU2NjQyMDM4OTc= | 426 | [FEATURE REQUEST] Multiprocessing with for dataset.map, dataset.filter | {
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"Yes that's definitely something we plan to add ^^",
"Yes, that would be nice. We could take a look at what tensorflow `tf.data` does under the hood for instance.",
"So `tf.data.Dataset.map()` returns a `ParallelMapDataset` if `num_parallel_calls is not None` [link](https://github.com/tensorflow/tensorflow/blob... | 2020-07-23T05:00:41Z | 2021-03-12T09:34:12Z | 2020-09-07T14:48:04Z | NONE | null | null | {
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} | It would be nice to be able to speed up `dataset.map` or `dataset.filter`. Perhaps this is as easy as sharding the dataset sending each shard to a process/thread/dask pool and using the new `nlp.concatenate_dataset()` function to join them all together? | {
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https://api.github.com/repos/huggingface/datasets/issues/425 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/425/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/425/comments | https://api.github.com/repos/huggingface/datasets/issues/425/events | https://github.com/huggingface/datasets/issues/425 | 664,029,848 | MDU6SXNzdWU2NjQwMjk4NDg= | 425 | Correct data structure for PAN-X task in XTREME dataset? | {
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"Thanks for noticing ! This looks more reasonable indeed.\r\nFeel free to open a PR",
"Hi @lhoestq \r\nI made the proposed changes to the `xtreme.py` script. I noticed that I also need to change the schema in the `dataset_infos.json` file. More specifically the `\"features\"` part of the PAN-X.LANG dataset:\r\n\... | 2020-07-22T20:29:20Z | 2020-08-02T13:30:34Z | 2020-08-02T13:30:34Z | MEMBER | null | null | {
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} | Hi 🤗 team!
## Description of the problem
Thanks to the fix from #416 I am now able to load the NER task in the XTREME dataset as follows:
```python
from nlp import load_dataset
# AmazonPhotos.zip is located in data/
dataset = load_dataset("xtreme", "PAN-X.en", data_dir='./data')
dataset_train = dataset['tr... | {
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https://api.github.com/repos/huggingface/datasets/issues/418 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/418/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/418/comments | https://api.github.com/repos/huggingface/datasets/issues/418/events | https://github.com/huggingface/datasets/issues/418 | 661,914,873 | MDU6SXNzdWU2NjE5MTQ4NzM= | 418 | Addition of google drive links to dl_manager | {
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"I think the problem is the way you wrote your urls. Try the following structure to see `https://drive.google.com/uc?export=download&id=your_file_id` . \r\n\r\n@lhoestq ",
"Oh sorry, I think `_get_drive_url` is doing that. \r\n\r\nHave you tried to use `dl_manager.download_and_extract(_get_drive_url(_TRAIN_URL)`... | 2020-07-20T14:52:02Z | 2020-07-20T15:39:32Z | 2020-07-20T15:39:32Z | CONTRIBUTOR | null | null | {
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} | Hello there, I followed the template to create a download script of my own, which works fine for me, although I had to shun the dl_manager because it was downloading nothing from the drive links and instead use gdown.
This is the script for me:
```python
class EmoConfig(nlp.BuilderConfig):
"""BuilderConfig ... | {
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https://api.github.com/repos/huggingface/datasets/issues/414 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/414/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/414/comments | https://api.github.com/repos/huggingface/datasets/issues/414/events | https://github.com/huggingface/datasets/issues/414 | 660,654,013 | MDU6SXNzdWU2NjA2NTQwMTM= | 414 | from_dict delete? | {
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"`from_dict` was added in #350 that was unfortunately not included in the 0.3.0 release. It's going to be included in the next release that will be out pretty soon though.\r\nRight now if you want to use `from_dict` you have to install the package from the master branch\r\n```\r\npip install git+https://github.com/... | 2020-07-19T07:08:36Z | 2020-07-21T02:21:17Z | 2020-07-21T02:21:17Z | NONE | null | null | {
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} | AttributeError: type object 'Dataset' has no attribute 'from_dict' | {
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https://api.github.com/repos/huggingface/datasets/issues/413 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/413/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/413/comments | https://api.github.com/repos/huggingface/datasets/issues/413/events | https://github.com/huggingface/datasets/issues/413 | 660,063,655 | MDU6SXNzdWU2NjAwNjM2NTU= | 413 | Is there a way to download only NQ dev? | {
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"Unfortunately it's not possible to download only the dev set of NQ.\r\n\r\nI think we could add a way to download only the test set by adding a custom configuration to the processing script though.",
"Ok, got it. I think this could be a valuable feature - especially for large datasets like NQ, but potentially al... | 2020-07-18T10:28:23Z | 2022-02-11T09:50:21Z | 2022-02-11T09:50:21Z | NONE | null | null | {
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} | Maybe I missed that in the docs, but is there a way to only download the dev set of natural questions (~1 GB)?
As we want to benchmark QA models on different datasets, I would like to avoid downloading the 41GB of training data.
I tried
```
dataset = nlp.load_dataset('natural_questions', split="validation", bea... | {
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https://api.github.com/repos/huggingface/datasets/issues/412 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/412/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/412/comments | https://api.github.com/repos/huggingface/datasets/issues/412/events | https://github.com/huggingface/datasets/issues/412 | 660,047,139 | MDU6SXNzdWU2NjAwNDcxMzk= | 412 | Unable to load XTREME dataset from disk | {
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"Hi @lewtun, you have to provide the full path to the downloaded file for example `/home/lewtum/..`",
"I was able to repro. Opening a PR to fix that.\r\nThanks for reporting this issue !",
"Thanks for the rapid fix @lhoestq!"
] | 2020-07-18T09:55:00Z | 2020-07-21T08:15:44Z | 2020-07-21T08:15:44Z | MEMBER | null | null | {
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} | Hi 🤗 team!
## Description of the problem
Following the [docs](https://huggingface.co/nlp/loading_datasets.html?highlight=xtreme#manually-downloading-files) I'm trying to load the `PAN-X.fr` dataset from the [XTREME](https://github.com/google-research/xtreme) benchmark.
I have manually downloaded the `AmazonPho... | {
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https://api.github.com/repos/huggingface/datasets/issues/409 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/409/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/409/comments | https://api.github.com/repos/huggingface/datasets/issues/409/events | https://github.com/huggingface/datasets/issues/409 | 659,128,611 | MDU6SXNzdWU2NTkxMjg2MTE= | 409 | train_test_split error: 'dict' object has no attribute 'deepcopy' | {
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"It was fixed in 2ddd18d139d3047c9c3abe96e1e7d05bb360132c.\r\nCould you pull the latest changes from master @morganmcg1 ?",
"Thanks @lhoestq, works fine now!"
] | 2020-07-17T10:36:28Z | 2020-07-21T14:34:52Z | 2020-07-21T14:34:52Z | NONE | null | null | {
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} | `train_test_split` is giving me an error when I try and call it:
`'dict' object has no attribute 'deepcopy'`
## To reproduce
```
dataset = load_dataset('glue', 'mrpc', split='train')
dataset = dataset.train_test_split(test_size=0.2)
```
## Full Stacktrace
```
-------------------------------------------... | {
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https://api.github.com/repos/huggingface/datasets/issues/407 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/407/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/407/comments | https://api.github.com/repos/huggingface/datasets/issues/407/events | https://github.com/huggingface/datasets/issues/407 | 658,672,736 | MDU6SXNzdWU2NTg2NzI3MzY= | 407 | MissingBeamOptions for Wikipedia 20200501.en | {
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"Fixed. Could you try again @mitchellgordon95 ?\r\nIt was due a file not being updated on S3.\r\n\r\nWe need to make sure all the datasets scripts get updated properly @julien-c ",
"Works for me! Thanks.",
"I found the same issue with almost any language other than English. (For English, it works). Will someone... | 2020-07-16T23:48:03Z | 2021-01-12T11:41:16Z | 2020-07-17T14:24:28Z | CONTRIBUTOR | null | null | {
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} | There may or may not be a regression for the pre-processed Wikipedia dataset. This was working fine 10 commits ago (without having Apache Beam available):
```
nlp.load_dataset('wikipedia', "20200501.en", split='train')
```
And now, having pulled master, I get:
```
Downloading and preparing dataset wikipedia... | {
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https://api.github.com/repos/huggingface/datasets/issues/406 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/406/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/406/comments | https://api.github.com/repos/huggingface/datasets/issues/406/events | https://github.com/huggingface/datasets/issues/406 | 658,581,764 | MDU6SXNzdWU2NTg1ODE3NjQ= | 406 | Faster Shuffling? | {
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"I think the slowness here probably come from the fact that we are copying from and to python.\r\n\r\n@lhoestq for all the `select`-based methods I think we should stay in Arrow format and update the writer so that it can accept Arrow tables or batches as well. What do you think?",
"> @lhoestq for all the `select... | 2020-07-16T21:21:53Z | 2023-08-16T09:52:39Z | 2020-09-07T14:45:25Z | CONTRIBUTOR | null | null | {
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```
dataset = nlp.load_dataset('bookcorpus', split='train')
dataset.shuffle()
```
According to tqdm, this will take around 2.5 hours on my machine to complete (even with the faster version of select from #405). I've also tried with `keep_in_memory=True` and `writer_batch_size=1000`... | {
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https://api.github.com/repos/huggingface/datasets/issues/395 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/395/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/395/comments | https://api.github.com/repos/huggingface/datasets/issues/395/events | https://github.com/huggingface/datasets/issues/395 | 657,454,983 | MDU6SXNzdWU2NTc0NTQ5ODM= | 395 | Memory issue when doing select | {
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} | As noticed in #389, the following code loads the entire wikipedia in memory.
```python
import nlp
w = nlp.load_dataset("wikipedia", "20200501.en", split="train")
w.select([0])
```
This is caused by [this line](https://github.com/huggingface/nlp/blob/master/src/nlp/arrow_dataset.py#L626) for some reason, that ... | {
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https://api.github.com/repos/huggingface/datasets/issues/388 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/388/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/388/comments | https://api.github.com/repos/huggingface/datasets/issues/388/events | https://github.com/huggingface/datasets/issues/388 | 656,707,497 | MDU6SXNzdWU2NTY3MDc0OTc= | 388 | 🐛 [Dataset] Cannot download wmt14, wmt15 and wmt17 | {
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"similar slow download speed here for nlp.load_dataset('wmt14', 'fr-en')\r\n`\r\nDownloading: 100%|██████████████████████████████████████████████████████████| 658M/658M [1:00:42<00:00, 181kB/s]\r\nDownloading: 100%|██████████████████████████████████████████████████████████| 918M/918M [1:39:38<00:00, 154kB/s]\r\nDow... | 2020-07-14T15:36:41Z | 2022-10-04T18:01:28Z | 2022-10-04T18:01:28Z | NONE | null | null | {
"completed": 0,
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} | 1. I try downloading `wmt14`, `wmt15`, `wmt17`, `wmt19` with the following code:
```
nlp.load_dataset('wmt14','de-en')
nlp.load_dataset('wmt15','de-en')
nlp.load_dataset('wmt17','de-en')
nlp.load_dataset('wmt19','de-en')
```
The code runs but the download speed is **extremely slow**, the same behaviour is not ob... | {
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https://api.github.com/repos/huggingface/datasets/issues/387 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/387/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/387/comments | https://api.github.com/repos/huggingface/datasets/issues/387/events | https://github.com/huggingface/datasets/issues/387 | 656,361,357 | MDU6SXNzdWU2NTYzNjEzNTc= | 387 | Conversion through to_pandas output numpy arrays for lists instead of python objects | {
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"To convert from arrow type we have three options: to_numpy, to_pandas and to_pydict/to_pylist.\r\n\r\n- to_numpy and to_pandas return numpy arrays instead of lists but are very fast.\r\n- to_pydict/to_pylist can be 100x slower and become the bottleneck for reading data, but at least they return lists.\r\n\r\nMaybe... | 2020-07-14T06:24:01Z | 2020-07-17T11:37:00Z | 2020-07-17T11:37:00Z | MEMBER | null | null | {
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} | In a related question, the conversion through to_pandas output numpy arrays for the lists instead of python objects.
Here is an example:
```python
>>> dataset._data.slice(key, 1).to_pandas().to_dict("list")
{'sentence1': ['Amrozi accused his brother , whom he called " the witness " , of deliberately distorting hi... | {
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https://api.github.com/repos/huggingface/datasets/issues/382 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/382/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/382/comments | https://api.github.com/repos/huggingface/datasets/issues/382/events | https://github.com/huggingface/datasets/issues/382 | 655,290,482 | MDU6SXNzdWU2NTUyOTA0ODI= | 382 | 1080 | {
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https://api.github.com/repos/huggingface/datasets/issues/378 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/378/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/378/comments | https://api.github.com/repos/huggingface/datasets/issues/378/events | https://github.com/huggingface/datasets/issues/378 | 655,226,316 | MDU6SXNzdWU2NTUyMjYzMTY= | 378 | [dataset] Structure of MLQA seems unecessary nested | {
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"Same for the RACE dataset: https://github.com/huggingface/nlp/blob/master/datasets/race/race.py\r\n\r\nShould we scan all the datasets to remove this pattern of un-necessary nesting?",
"You're right, I think we don't need to use the nested dictionary. \r\n"
] | 2020-07-11T15:16:08Z | 2020-07-15T16:17:20Z | 2020-07-15T16:17:20Z | MEMBER | null | null | {
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} | The features of the MLQA dataset comprise several nested dictionaries with a single element inside (for `questions` and `ids`): https://github.com/huggingface/nlp/blob/master/datasets/mlqa/mlqa.py#L90-L97
Should we keep this @mariamabarham @patrickvonplaten? Was this added for compatibility with tfds?
```python
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https://api.github.com/repos/huggingface/datasets/issues/377 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/377/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/377/comments | https://api.github.com/repos/huggingface/datasets/issues/377/events | https://github.com/huggingface/datasets/issues/377 | 655,215,790 | MDU6SXNzdWU2NTUyMTU3OTA= | 377 | Iyy!!! | {
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https://api.github.com/repos/huggingface/datasets/issues/376 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/376/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/376/comments | https://api.github.com/repos/huggingface/datasets/issues/376/events | https://github.com/huggingface/datasets/issues/376 | 655,047,826 | MDU6SXNzdWU2NTUwNDc4MjY= | 376 | to_pandas conversion doesn't always work | {
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"**Edit**: other topic previously in this message moved to a new issue: https://github.com/huggingface/nlp/issues/387",
"Could you try to update pyarrow to >=0.17.0 ? It should fix the `to_pandas` bug\r\n\r\nAlso I'm not sure that structures like list<struct> are fully supported in the lib (none of the datasets u... | 2020-07-10T21:33:31Z | 2022-10-04T18:05:39Z | 2022-10-04T18:05:39Z | MEMBER | null | null | {
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} | For some complex nested types, the conversion from Arrow to python dict through pandas doesn't seem to be possible.
Here is an example using the official SQUAD v2 JSON file.
This example was found while investigating #373.
```python
>>> squad = load_dataset('json', data_files={nlp.Split.TRAIN: ["./train-v2.0.... | {
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https://api.github.com/repos/huggingface/datasets/issues/375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/375/comments | https://api.github.com/repos/huggingface/datasets/issues/375/events | https://github.com/huggingface/datasets/issues/375 | 655,023,307 | MDU6SXNzdWU2NTUwMjMzMDc= | 375 | TypeError when computing bertscore | {
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"I am not able to reproduce this issue on my side.\r\nCould you give us more details about the inputs you used ?\r\n\r\nI do get another error though:\r\n```\r\n~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/bert_score/utils.py in bert_cos_score_idf(model, refs, hyps, tokenizer, idf_dict, verbose, batch_siz... | 2020-07-10T20:37:44Z | 2022-06-01T15:15:59Z | 2022-06-01T15:15:59Z | NONE | null | null | {
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I installed nlp 0.3.0 via pip, and my python version is 3.7.
When I tried to compute bertscore with the code:
```
import nlp
bertscore = nlp.load_metric('bertscore')
# load hyps and refs
...
print (bertscore.compute(hyps, refs, lang='en'))
```
I got the following error.
```
Traceback (most rece... | {
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https://api.github.com/repos/huggingface/datasets/issues/373 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/373/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/373/comments | https://api.github.com/repos/huggingface/datasets/issues/373/events | https://github.com/huggingface/datasets/issues/373 | 654,845,133 | MDU6SXNzdWU2NTQ4NDUxMzM= | 373 | Segmentation fault when loading local JSON dataset as of #372 | {
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"I've seen this sort of thing before -- it might help to delete the directory -- I've also noticed that there is an error with the json Dataloader for any data I've tried to load. I've replaced it with this, which skips over the data feature population step:\r\n\r\n\r\n```python\r\nimport os\r\n\r\nimport pyarrow.j... | 2020-07-10T15:04:25Z | 2022-10-04T18:05:47Z | 2022-10-04T18:05:47Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | The last issue was closed (#369) once the #372 update was merged. However, I'm still not able to load a SQuAD formatted JSON file. Instead of the previously recorded pyarrow error, I now get a segmentation fault.
```
dataset = nlp.load_dataset('json', data_files={nlp.Split.TRAIN: ["./datasets/train-v2.0.json"]}, f... | {
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https://api.github.com/repos/huggingface/datasets/issues/369 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/369/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/369/comments | https://api.github.com/repos/huggingface/datasets/issues/369/events | https://github.com/huggingface/datasets/issues/369 | 654,186,890 | MDU6SXNzdWU2NTQxODY4OTA= | 369 | can't load local dataset: pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries | {
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{
"color": "2edb81",
"default": false,
"description": "A bug in a dataset script provided in the library",
"id": 2067388877,
"name": "dataset bug",
"node_id": "MDU6TGFiZWwyMDY3Mzg4ODc3",
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"I am able to reproduce this with the official SQuAD `train-v2.0.json` file downloaded directly from https://rajpurkar.github.io/SQuAD-explorer/",
"I am facing this issue in transformers library 3.0.2 while reading a csv using datasets.\r\nIs this fixed in latest version? \r\nI updated the latest version 4.0.1 bu... | 2020-07-09T16:16:53Z | 2020-12-15T23:07:22Z | 2020-07-10T14:52:06Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | Trying to load a local SQuAD-formatted dataset (from a JSON file, about 60MB):
```
dataset = nlp.load_dataset(path='json', data_files={nlp.Split.TRAIN: ["./path/to/file.json"]})
```
causes
```
Traceback (most recent call last):
File "dataloader.py", line 9, in <module>
["./path/to/file.json"]})
File "/... | {
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https://api.github.com/repos/huggingface/datasets/issues/368 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/368/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/368/comments | https://api.github.com/repos/huggingface/datasets/issues/368/events | https://github.com/huggingface/datasets/issues/368 | 654,087,251 | MDU6SXNzdWU2NTQwODcyNTE= | 368 | load_metric can't acquire lock anymore | {
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"I found that, in the same process (or the same interactive session), if I do\r\n\r\nimport nlp\r\n\r\nm1 = nlp.load_metric('glue', 'mrpc')\r\nm2 = nlp.load_metric('glue', 'sst2')\r\n\r\nI will get the same error `ValueError: Cannot acquire lock, caching file might be used by another process, you should setup a uni... | 2020-07-09T14:04:09Z | 2020-07-10T13:45:20Z | 2020-07-10T13:45:20Z | NONE | null | null | {
"completed": 0,
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} | I can't load metric (glue) anymore after an error in a previous run. I even removed the whole cache folder `/home/XXX/.cache/huggingface/`, and the issue persisted. What are the steps to fix this?
Traceback (most recent call last):
File "/home/XXX/miniconda3/envs/ML-DL-py-3.7/lib/python3.7/site-packages/n... | {
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https://api.github.com/repos/huggingface/datasets/issues/365 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/365/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/365/comments | https://api.github.com/repos/huggingface/datasets/issues/365/events | https://github.com/huggingface/datasets/issues/365 | 653,845,964 | MDU6SXNzdWU2NTM4NDU5NjQ= | 365 | How to augment data ? | {
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"Using batched map is probably the easiest way at the moment.\r\nWhat kind of augmentation would you like to do ?",
"Some samples in the dataset are too long, I want to divide them in several samples.",
"Using batched map is the way to go then.\r\nWe'll make it clearer in the docs that map could be used for aug... | 2020-07-09T07:52:37Z | 2020-07-10T09:12:07Z | 2020-07-10T08:22:15Z | NONE | null | null | {
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} | Is there any clean way to augment data ?
For now my work-around is to use batched map, like this :
```python
def aug(samples):
# Simply copy the existing data to have x2 amount of data
for k, v in samples.items():
samples[k].extend(v)
return samples
dataset = dataset.map(aug, batched=T... | {
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https://api.github.com/repos/huggingface/datasets/issues/362 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/362/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/362/comments | https://api.github.com/repos/huggingface/datasets/issues/362/events | https://github.com/huggingface/datasets/issues/362 | 653,766,245 | MDU6SXNzdWU2NTM3NjYyNDU= | 362 | [dateset subset missing] xtreme paws-x | {
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"You're right, thanks for pointing it out. We will update it "
] | 2020-07-09T05:04:54Z | 2020-07-09T12:38:42Z | 2020-07-09T12:38:42Z | CONTRIBUTOR | null | null | {
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} | I tried nlp.load_dataset('xtreme', 'PAWS-X.es') but get the value error
It turns out that the subset for Spanish is missing
https://github.com/google-research-datasets/paws/tree/master/pawsx | {
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https://api.github.com/repos/huggingface/datasets/issues/361 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/361/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/361/comments | https://api.github.com/repos/huggingface/datasets/issues/361/events | https://github.com/huggingface/datasets/issues/361 | 653,757,376 | MDU6SXNzdWU2NTM3NTczNzY= | 361 | 🐛 [Metrics] ROUGE is non-deterministic | {
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"Hi, can you give a full self-contained example to reproduce this behavior?",
"> Hi, can you give a full self-contained example to reproduce this behavior?\r\n\r\nThere is a notebook in the post ;)",
"> If I run the ROUGE metric 2 times, with same predictions / references, the scores are slightly different.\r\n... | 2020-07-09T04:39:37Z | 2022-09-09T15:20:55Z | 2020-07-20T23:48:37Z | NONE | null | null | {
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} | If I run the ROUGE metric 2 times, with same predictions / references, the scores are slightly different.
Refer to [this Colab notebook](https://colab.research.google.com/drive/1wRssNXgb9ldcp4ulwj-hMJn0ywhDOiDy?usp=sharing) for reproducing the problem.
Example of F-score for ROUGE-1, ROUGE-2, ROUGE-L in 2 differe... | {
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https://api.github.com/repos/huggingface/datasets/issues/360 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/360/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/360/comments | https://api.github.com/repos/huggingface/datasets/issues/360/events | https://github.com/huggingface/datasets/issues/360 | 653,687,176 | MDU6SXNzdWU2NTM2ODcxNzY= | 360 | [Feature request] Add dataset.ragged_map() function for many-to-many transformations | {
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"Actually `map(batched=True)` can already change the size of the dataset.\r\nIt can accept examples of length `N` and returns a batch of length `M` (can be null or greater than `N`).\r\n\r\nI'll make that explicit in the doc that I'm currently writing.",
"You're two steps ahead of me :) In my testing, it also wor... | 2020-07-09T01:04:43Z | 2020-07-09T19:31:51Z | 2020-07-09T19:31:51Z | CONTRIBUTOR | null | null | {
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} | `dataset.map()` enables one-to-one transformations. Input one example and output one example. This is helpful for tokenizing and cleaning individual lines.
`dataset.filter()` enables one-to-(one-or-none) transformations. Input one example and output either zero/one example. This is helpful for removing portions from t... | {
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https://api.github.com/repos/huggingface/datasets/issues/359 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/359/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/359/comments | https://api.github.com/repos/huggingface/datasets/issues/359/events | https://github.com/huggingface/datasets/issues/359 | 653,656,279 | MDU6SXNzdWU2NTM2NTYyNzk= | 359 | ArrowBasedBuilder _prepare_split parse_schema breaks on nested structures | {
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"Hi, it depends on what it is in your `dataset_builder.py` file. Can you share it?\r\n\r\nIf you are just loading `json` files, you can also directly use the `json` script (which will find the schema/features from your JSON structure):\r\n\r\n```python\r\nfrom nlp import load_dataset\r\nds = load_dataset(\"json\", ... | 2020-07-08T23:24:05Z | 2020-07-10T14:52:06Z | 2020-07-10T14:52:06Z | NONE | null | null | {
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```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-23-9aecfbee53bd> in <mo... | {
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