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"@lhoestq is there a problem in the master branch? I got a segmentation fault...\r\n```\r\ntests/test_table.py::test_concatenation_table_cast[in_memory] Fatal Python error: Segmentation fault\r\n```",
"Oh wow. Let me re-run the CI just to make sure",
"Hmm interesting, the segfault is still there. I'm investigat... | 1,619,178,347,000 | 1,622,106,765,000 | 1,619,535,779,000 | MEMBER | null | Perform minor refactoring related to `config`. | {
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"Hi ! Sorry to hear that. This may come from another issue then.\r\n\r\nFirst can we check if this latency comes from the dataset itself ?\r\nYou can try to load your dataset and benchmark the speed of querying random examples inside it ?\r\n```python\r\nimport time\r\nimport numpy as np\r\n\r\nfrom datasets import... | 1,619,165,900,000 | 1,637,776,195,000 | null | NONE | null | Hi,
I reported too slow data fetching when data is large(#2210) a couple of weeks ago, and @lhoestq referred me to the fix (#2122).
However, the problem seems to persist. Here is the profiled results:
1) Running with 60GB
```
Action | Mean duration (s) |Num calls | Total ... | {
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python3 run_qa.py --model_name_or_path hyunwoongko/kobart --dataset_name squad_kor_v2 --do_train --do_eval --per_device_train_batch_size 8 --learning_rate 3e-5 --num_train_epochs 3 --max_seq_length 512 --doc_stride 128 --output_dir /tmp/debug_squad/
error:
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"Hi,\r\n\r\n1. try\r\n ```python\r\n dataset = load_dataset(\"text\", data_files={\"train\": [\"a1.txt\", \"b1.txt\"], \"test\": [\"c1.txt\"]})\r\n ```\r\n instead.\r\n\r\n Sadly, I can't reproduce the error on my machine. If the above code doesn't resolve the issue, try to update the library to the ... | 1,619,120,353,000 | 1,629,258,552,000 | null | NONE | null | 
first of all, I tried to load 3 .txt files as a dataset (sure that the directory and permission is OK.), I face with the below error.
> FileNotFoundError: [Errno 2] No such file or directory: 'c'
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"> If you pass a dictionary like this:\r\n> \r\n> ```\r\n> {\"main_metadata\": url_to_main_data,\r\n> \"secondary_metadata\": url_to_sec_data,\r\n> \"train\": url_train_data,\r\n> \"test\": url_test_data}\r\n> ```\r\n> \r\n> then only the train or test keys will be kept, which I feel not intuitive.\r\n> \r\n> For e... | 1,619,113,904,000 | 1,630,560,811,000 | null | MEMBER | null | Allow downloading/processing/caching only specific splits without downloading/processing/caching the other splits.
This PR implements two steps to handle only specific splits:
- it allows processing/caching only specific splits into Arrow files
- for some simple cases, it allows downloading only specific splits (w... | {
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"@lhoestq Just fixed the code style issues— I think it should be good to merge now :)"
] | 1,619,034,547,000 | 1,619,453,639,000 | 1,619,453,639,000 | CONTRIBUTOR | null | @lhoestq Fixes #2193
- `map` now uses `with_format` to only load needed columns in memory when `input_columns` is set
- Slicing datasets with Iterables of indices now uses a new `Table.fast_gather` method, implemented with `np.searchsorted`, to find the appropriate batch indices all at once. `pa.concat_tables` is ... | {
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"@lhoestq The tests for key type and duplicate keys have been added and verified successfully.\r\nAfter generating with an intentionally faulty `mnist` script, when there is an incompatible key type, it shows:\r\n\r\n```\r\nDownloading and preparing dataset mnist/mnist (download: 11.06 MiB, generated: 60.62 MiB, po... | 1,618,948,999,000 | 1,620,669,877,000 | 1,620,667,882,000 | CONTRIBUTOR | null | Closes #2230
There is currently no verification for the data type and the uniqueness of the keys yielded by the `dataset_builder`.
This PR is currently a work in progress with the following goals:
- [x] Adding `hash_salt` to `ArrowWriter` so that the keys belonging to different splits have different hash
- [x]... | {
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"@lhoestq, I think this reaches some memory limit on Linux instances... (?)",
"It looks like the `comet` metric test fails because it tries to load a model in memory.\r\nIn the tests I think we have `patch_comet` that mocks the model download + inference. Not sure why it didn't work though.\r\nI can take a look t... | 1,618,938,382,000 | 1,630,560,811,000 | null | MEMBER | null | Implement specific cache directories (datasets, metrics and modules) per test function call.
Currently, the cache directories are set within the temporary test directory, but they are shared across all test function calls.
This PR implements specific cache directories for each test function call, so that tests ar... | {
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"Hi @villmow, thanks for reporting.\r\n\r\nCould you please try with the Datasets version 1.6? We released it yesterday and it fixes some issues about the processing speed. You can see the fix implemented by @lhoestq here: #2122.\r\n\r\nOnce you update Datasets, please confirm if the problem persists.",
"Hi @albe... | 1,618,930,700,000 | 1,620,064,473,000 | 1,620,064,472,000 | NONE | null | ## Describe the bug
I have a somewhat unclear bug to me, where I can't figure out what the problem is. The code works as expected on a small subset of my dataset (2000 samples) on my local machine, but when I execute the same code with a larger dataset (1.4 million samples) this problem occurs. Thats why I can't giv... | {
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"This should be fixed now!\r\n\r\ncc @srush "
] | 1,618,928,391,000 | 1,618,930,965,000 | 1,618,930,965,000 | NONE | null | Link to datasets viwer (https://huggingface.co/datasets/viewer/) on Quick Tour page (https://huggingface.co/docs/datasets/quicktour.html) returns "502 Bad Gateway"
The same error with https://huggingface.co/datasets/viewer/?dataset=glue&config=mrpc | {
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"> And yet another one ! Thanks a lot :)\r\n\r\nI just hope you don’t get fed up with openslr PR 😊 there are still few other datasets created by google in openslr that is not in hf dataset yet\r\n"
] | 1,618,916,565,000 | 1,619,194,884,000 | 1,619,192,175,000 | CONTRIBUTOR | null | I would like to add SLR32 to OpenSLR. It contains four South African languages: Afrikaans, Sesotho, Setswana and isiXhosa | {
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https://api.github.com/repos/huggingface/datasets/issues/2240 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2240/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2240/comments | https://api.github.com/repos/huggingface/datasets/issues/2240/events | https://github.com/huggingface/datasets/pull/2240 | 862,537,856 | MDExOlB1bGxSZXF1ZXN0NjE5MDkyODc5 | 2,240 | Clarify how to load wikihow | {
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En relation with #2239. | {
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"Hi @odellus, thanks for reporting.\r\n\r\nThe `wikihow` dataset has 2 versions:\r\n- `all`: Consisting of the concatenation of all paragraphs as the articles and the bold lines as the reference summaries.\r\n- `sep`: Consisting of each paragraph and its summary.\r\n\r\nTherefore, in order to load it, you have to s... | 1,618,866,151,000 | 1,618,936,391,000 | 1,618,936,391,000 | CONTRIBUTOR | null | ## Describe the bug
When attempting to load wikihow into a dataset with
```python
from datasets import load_dataset
dataset = load_dataset('wikihow', data_dir='./wikihow')
```
I get the message:
```
AttributeError: 'BuilderConfig' object has no attribute 'filename'
```
at the end of a [full stack trace](htt... | {
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"@albertvillanova I would like to take this up. It would be great if you could point me as to how the dataset size is calculated in HF. Thanks!"
] | 1,618,845,578,000 | 1,618,928,525,000 | null | MEMBER | null | After loading a dataset, if we transform it by using `.map` its `dataset_size` attirbute is not updated. | {
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"following_url"... | [] | 1,618,843,586,000 | 1,618,843,586,000 | null | NONE | null | ## Request to add StrategyQA dataset
- **Name:** StrategyQA
- **Description:** open-domain QA [(project page)](https://allenai.org/data/strategyqa)
- **Paper:** [url](https://arxiv.org/pdf/2101.02235.pdf)
- **Data:** [here](https://allenai.org/data/strategyqa)
- **Motivation:** uniquely-formulated dataset that als... | {
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"following_url"... | [] | 1,618,600,362,000 | 1,618,822,602,000 | 1,618,822,602,000 | CONTRIBUTOR | null | Closes #2229
The `xnli` dataset yields a tuple key in case of `ar` which is inconsistant with the acceptable key types (str/int).
The key was thus ported to `str` keeping the original information intact. | {
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"I replaced all the \"we\" and applied your suggestion",
"Merging this for now, we can continue improving this card in other PRs :)"
] | 1,618,598,257,000 | 1,618,997,589,000 | 1,618,997,588,000 | MEMBER | null | The dataset card was pretty much empty.
I added the descriptions (mainly from TFDS since the script is the same), and I also added the tasks tags as well as examples for a subset of the tasks.
cc @sgugger | {
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The `remove_columns` argument was ignored on formatted datasets | {
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"Hi ! Indeed there's no verification on the uniqueness nor the types of the keys.\r\nDo you already have some ideas of what you would like to implement and how ?",
"Hey @lhoestq, thank you so much for the opportunity.\r\nAlthough I haven't had much experience with the HF Datasets code, after a careful look at how... | 1,618,579,787,000 | 1,620,667,881,000 | 1,620,667,881,000 | CONTRIBUTOR | null | The keys used in the dataset generation script to ensure the same order is generated on every user's end should be checked for their types (i.e either `str` or `int`) as well as whether they are unique or not.
Currently, the keys are not being checked for any of these, as evident from `xnli' dataset generation:
https... | {
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"Hi ! Sure sounds good. Also if you find other datasets that use tuples instead of str/int, you can also fix them !\r\nthanks :)",
"@lhoestq I have sent a PR for fixing the issue. Would be great if you could have a look! Thanks!"
] | 1,618,579,313,000 | 1,618,822,602,000 | 1,618,822,602,000 | CONTRIBUTOR | null | When using `ds = datasets.load_dataset('xnli', 'ar')`, the dataset generation script uses the following section of code in the egging, which yields a tuple key instead of the specified `str` or `int` key:
https://github.com/huggingface/datasets/blob/56346791aed417306d054d89bd693d6b7eab17f7/datasets/xnli/xnli.py#L196
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https://api.github.com/repos/huggingface/datasets/issues/2228 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2228/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2228/comments | https://api.github.com/repos/huggingface/datasets/issues/2228/events | https://github.com/huggingface/datasets/pull/2228 | 859,795,563 | MDExOlB1bGxSZXF1ZXN0NjE2ODE2MTQz | 2,228 | [WIP] Add ArrayXD support for fixed size list. | {
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"Awesome thanks ! To fix the CI you just need to merge master into your branch.\r\nThe error is unrelated to your PR"
] | 1,618,578,248,000 | 1,618,837,338,000 | null | NONE | null | Add support for fixed size list for ArrayXD when shape is known . See https://github.com/huggingface/datasets/issues/2146
Since offset are not stored anymore, the file size is now roughly equal to the actual data size. | {
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https://api.github.com/repos/huggingface/datasets/issues/2227 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2227/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2227/comments | https://api.github.com/repos/huggingface/datasets/issues/2227/events | https://github.com/huggingface/datasets/pull/2227 | 859,771,526 | MDExOlB1bGxSZXF1ZXN0NjE2Nzk1NjMx | 2,227 | Use update_metadata_with_features decorator in class_encode_column method | {
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https://api.github.com/repos/huggingface/datasets/issues/2226 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2226/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2226/comments | https://api.github.com/repos/huggingface/datasets/issues/2226/events | https://github.com/huggingface/datasets/issues/2226 | 859,720,302 | MDU6SXNzdWU4NTk3MjAzMDI= | 2,226 | Batched map fails when removing all columns | {
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"I found the problem. I called `set_format` on some columns before. This makes it crash. Here is a complete example to reproduce:\r\n\r\n```python\r\nfrom datasets import load_dataset\r\nsst = load_dataset(\"sst\")\r\nsst.set_format(\"torch\", columns=[\"label\"], output_all_columns=True)\r\nds = sst[\"train\"]\r\n... | 1,618,571,821,000 | 1,618,585,841,000 | null | NONE | null | Hi @lhoestq ,
I'm hijacking this issue, because I'm currently trying to do the approach you recommend:
> Currently the optimal setup for single-column computations is probably to do something like
>
> ```python
> result = dataset.map(f, input_columns="my_col", remove_columns=dataset.column_names)
> ```
He... | {
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https://api.github.com/repos/huggingface/datasets/issues/2225 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2225/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2225/comments | https://api.github.com/repos/huggingface/datasets/issues/2225/events | https://github.com/huggingface/datasets/pull/2225 | 858,469,561 | MDExOlB1bGxSZXF1ZXN0NjE1NzAzMTY4 | 2,225 | fixed one instance of 'train' to 'test' | {
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"Thanks ! good catch\r\n\r\nCould you also update the metadata of this dataset ?\r\nYou can do so by running\r\n```\r\ndatasets-cli test ./datasets/newsgroup --all_configs --save_infos --ignore_verifications\r\n```\r\nThis should update the dataset_infos.json file that contains the size of all the splits for exampl... | 1,618,460,800,000 | 1,618,524,590,000 | 1,618,521,549,000 | CONTRIBUTOR | null | I believe this should be 'test' instead of 'train' | {
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Linked to discussion in #2220. | {
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"> why a cache dir per test function does not work?\r\n\r\nProbably because we end up with multiple `datasets_module` in the python path. This breaks the import of all the datasets/metrics modules.\r\nIf you want to use one modules cache per test, you may need remove the `datasets_module` that was added to the pyt... | 1,618,404,924,000 | 1,618,513,885,000 | 1,618,513,885,000 | MEMBER | null | Currently, running the tests populates the default cache directory `"~/.cache"`.
This PR monkey-patches the config to set the cache directory within the temporary test directory, avoiding side effects. | {
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"Windows users should disable the max path length limit. It's a nightmare to handle it.\r\nAlso the lock path must not be changed in a random way. Otherwise from another process the lock path might not be the same and the locking mechanism won't work.",
"Do you agree with handling the case where MAX_PATH is not d... | 1,618,403,212,000 | 1,618,412,425,000 | 1,618,411,579,000 | MEMBER | null | Fix WindowsFileLock name longer than allowed MAX_PATH by shortening the basename. | {
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"following_url"... | [] | 1,618,402,158,000 | 1,618,408,219,000 | 1,618,408,219,000 | CONTRIBUTOR | null | I would like to add SLR70, SLR71, SLR72, SLR73, SLR74, SLR75, SLR76, SLR77, SLR78, SLR79, SLR80 and SLR86 to OpenSLR dataset. The languages are:
Nigerian English, Chilean Spanish, Columbian Spanish, Peruvian Spanish, Puerto Rico Spanish, Venezuelan Spanish, Basque, Galician, Gujarati and Kannada. | {
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"How is it possible to get an infinite loop ? Can you add more details ?",
"Yes, in Windows, if the filename is too long, a `FileNotFoundError` is raised. The exception should be raised in this case. Otherwise, we get into an infinite loop.\r\n\r\nIf other process has the file locked, then `PermissionError` is ra... | 1,618,397,398,000 | 1,618,412,390,000 | 1,618,412,374,000 | MEMBER | null | Raise exception to avoid infinite loop. | {
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"1) Changed the language in a few places apart from those you mentioned in README\r\n2) Reduced the size of dummy data folder by removing all other entries except the first\r\n3) Updated YAML tags by using to the past version of `datasets-tagging` app. Will update the quick fix on that repository too in a while",
... | 1,618,347,903,000 | 1,619,274,351,000 | 1,618,563,044,000 | CONTRIBUTOR | null | Dataset link : https://github.com/TheAtticusProject/cuad/
Working on README.md currently.
Closes #2084 and [#1](https://github.com/TheAtticusProject/cuad/issues/1). | {
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"Hi,\r\n\r\ncurrently the datasets API doesn't have a dedicated function to remove duplicate rows, but since the LAMA dataset is not too big (it fits in RAM), we can leverage pandas to help us remove duplicates:\r\n```python\r\n>>> from datasets import load_dataset, Dataset\r\n>>> dataset = load_dataset('lama', spl... | 1,618,340,389,000 | 1,618,436,547,000 | null | NONE | null | I observed duplicates in the LAMA probing dataset, see a minimal code below.
```
>>> import datasets
>>> dataset = datasets.load_dataset('lama')
No config specified, defaulting to: lama/trex
Reusing dataset lama (/home/anam/.cache/huggingface/datasets/lama/trex/1.1.0/97deffae13eca0a18e77dfb3960bb31741e973586f5c... | {
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"following_url"... | [] | 1,618,323,604,000 | 1,618,410,264,000 | 1,618,410,263,000 | MEMBER | null | #2025 changed the format of `Dataset.cache_files`.
Before it was formatted like
```python
[{"filename": "path/to/file.arrow", "start": 0, "end": 1337}]
```
and it was changed to
```python
["path/to/file.arrow"]
```
since there's no start/end offsets available anymore.
To make this less breaking, I'm setting... | {
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"Hi @lhoestq,\r\nCould you please help me, I got this error message in all \"ci/circleci: run_dataset_script_tests_pyarrow*\" tests:\r\n```\r\n...\r\n \"\"\"Wrapper classes for various types of tokenization.\"\"\"\r\n \r\n from bleurt.lib import bert_tokenization\r\n import tensorflow.compat.v1 as tf\r\... | 1,618,302,247,000 | 1,618,322,714,000 | 1,618,322,714,000 | CONTRIBUTOR | null | I would like to add [SLR35](https://openslr.org/35/) (18GB) and [SLR36](https://openslr.org/36/) (22GB) which are Large Javanese and Sundanese ASR training data set collected by Google in collaboration with Reykjavik University and Universitas Gadjah Mada in Indonesia. | {
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"Hi @nsaphra, thanks for reporting.\r\n\r\nThis issue was fixed in `datasets` version 1.3.0. Could you please update `datasets` and tell me if the problem persists?\r\n```shell\r\npip install -U datasets\r\n```",
"There might be a bug in the conda version of `datasets` 1.2.1 where the datasets/metric scripts are ... | 1,618,259,161,000 | 1,619,191,202,000 | 1,619,191,202,000 | NONE | null | I'm having the same problem as [Notebooks issue 10](https://github.com/huggingface/notebooks/issues/10) on datasets 1.2.1, and it seems to be an issue with the datasets package.
```python
>>> from datasets import load_metric
>>> metric = load_metric("glue", "sst2")
Traceback (most recent call last):
File "<std... | {
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"following_url"... | [] | 1,618,237,019,000 | 1,618,437,894,000 | 1,618,407,745,000 | CONTRIBUTOR | null | Fixes #2211 | {
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https://api.github.com/repos/huggingface/datasets/issues/2212 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2212/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2212/comments | https://api.github.com/repos/huggingface/datasets/issues/2212/events | https://github.com/huggingface/datasets/issues/2212 | 855,999,133 | MDU6SXNzdWU4NTU5OTkxMzM= | 2,212 | Can't reach "https://storage.googleapis.com/illuin/fquad/train.json.zip" when trying to load fquad dataset | {
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"Hi ! Apparently the data are not available from this url anymore. We'll replace it with the new url when it's available",
"I saw this on their website when we request to download the dataset:\r\n\r\n\r\... | 1,618,235,396,000 | 1,621,289,826,000 | null | NONE | null | I'm trying to load the [fquad dataset](https://huggingface.co/datasets/fquad) by running:
```Python
fquad = load_dataset("fquad")
```
which produces the following error:
```
Using custom data configuration default
Downloading and preparing dataset fquad/default (download: 3.14 MiB, generated: 6.62 MiB, ... | {
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"Hi,\r\n\r\nI've already opened a PR with the fix. If you are in a hurry, just build the project from source and run:\r\n```bash\r\ndatasets-cli test datasets/lc_quad --save_infos --all_configs --ignore_verifications\r\n```\r\n\r\n",
"Ah sorry, I tried searching but couldn't find any related PR. \r\n\r\nThank you... | 1,618,234,738,000 | 1,618,407,745,000 | 1,618,407,745,000 | NONE | null | I'm having issues loading the [lc_quad](https://huggingface.co/datasets/fquad) dataset by running:
```Python
lc_quad = load_dataset("lc_quad")
```
which is giving me the following error:
```
Using custom data configuration default
Downloading and preparing dataset lc_quad/default (download: 3.69 MiB, ge... | {
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https://api.github.com/repos/huggingface/datasets/issues/2210 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2210/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2210/comments | https://api.github.com/repos/huggingface/datasets/issues/2210/events | https://github.com/huggingface/datasets/issues/2210 | 855,709,400 | MDU6SXNzdWU4NTU3MDk0MDA= | 2,210 | dataloading slow when using HUGE dataset | {
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"Hi ! Yes this is an issue with `datasets<=1.5.0`\r\nThis issue has been fixed by #2122 , we'll do a new release soon :)\r\nFor now you can test it on the `master` branch.",
"Hi, thank you for your answer. I did not realize that my issue stems from the same problem. "
] | 1,618,216,382,000 | 1,618,279,385,000 | 1,618,279,385,000 | NONE | null | Hi,
When I use datasets with 600GB data, the dataloading speed increases significantly.
I am experimenting with two datasets, and one is about 60GB and the other 600GB.
Simply speaking, my code uses `datasets.set_format("torch")` function and let pytorch-lightning handle ddp training.
When looking at the pytorch... | {
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https://api.github.com/repos/huggingface/datasets/issues/2209 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2209/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2209/comments | https://api.github.com/repos/huggingface/datasets/issues/2209/events | https://github.com/huggingface/datasets/pull/2209 | 855,638,232 | MDExOlB1bGxSZXF1ZXN0NjEzMzQwMTI2 | 2,209 | Add code of conduct to the project | {
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"following_url"... | [] | 1,618,211,774,000 | 1,618,250,152,000 | 1,618,250,152,000 | MEMBER | null | Add code of conduct to the project and link it from README and CONTRIBUTING.
This was already done in `transformers`. | {
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https://api.github.com/repos/huggingface/datasets/issues/2208 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2208/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2208/comments | https://api.github.com/repos/huggingface/datasets/issues/2208/events | https://github.com/huggingface/datasets/pull/2208 | 855,343,835 | MDExOlB1bGxSZXF1ZXN0NjEzMTAxMzMw | 2,208 | Remove Python2 leftovers | {
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"merging since the CI is fixed on master"
] | 1,618,157,283,000 | 1,618,437,936,000 | 1,618,407,651,000 | CONTRIBUTOR | null | This PR removes Python2 leftovers since this project aims for Python3.6+ (and as of 2020 Python2 is no longer officially supported) | {
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"Hi ! The ClassLabel feature type encodes the labels as integers.\r\nThe integer corresponds to the index of the label name in the `names` list of the ClassLabel.\r\nHere that means that the labels are 'entailment' (0), 'neutral' (1), 'contradiction' (2).\r\n\r\nYou can get the label names back by using `a.features... | 1,618,135,436,000 | 1,618,408,920,000 | null | NONE | null | Hi
For accessing the labels one can type
```
>>> a.features['label']
ClassLabel(num_classes=3, names=['entailment', 'neutral', 'contradiction'], names_file=None, id=None)
```
The labels however are not consistent with the actual labels sometimes, for instance in case of XNLI, the actual labels are 0,1,2, but if ... | {
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https://api.github.com/repos/huggingface/datasets/issues/2206 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2206/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2206/comments | https://api.github.com/repos/huggingface/datasets/issues/2206/events | https://github.com/huggingface/datasets/issues/2206 | 855,252,415 | MDU6SXNzdWU4NTUyNTI0MTU= | 2,206 | Got pyarrow error when loading a dataset while adding special tokens into the tokenizer | {
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"Hi,\r\n\r\nthe output of the tokenizers is treated specially in the lib to optimize the dataset size (see the code [here](https://github.com/huggingface/datasets/blob/master/src/datasets/arrow_writer.py#L138-L141)). It looks like that one of the values in a dictionary returned by the tokenizer is out of the assume... | 1,618,130,409,000 | 1,636,546,710,000 | 1,636,545,868,000 | NONE | null | I added five more special tokens into the GPT2 tokenizer. But after that, when I try to pre-process the data using my previous code, I got an error shown below:
Traceback (most recent call last):
File "/home/xuyan/anaconda3/envs/convqa/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1687, in _map_sin... | {
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https://api.github.com/repos/huggingface/datasets/issues/2205 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2205/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2205/comments | https://api.github.com/repos/huggingface/datasets/issues/2205/events | https://github.com/huggingface/datasets/pull/2205 | 855,207,605 | MDExOlB1bGxSZXF1ZXN0NjEzMDAwMzYw | 2,205 | Updating citation information on LinCE readme | {
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"following_url"... | [] | 1,618,111,085,000 | 1,618,250,014,000 | 1,618,250,014,000 | CONTRIBUTOR | null | Hi!
I just updated the citation information in this PR. It had an additional bibtex from one of the datasets used in LinCE and then the LinCE bibtex. I removed the former and added a link that shows the full list of citations for each dataset.
Thanks! | {
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https://api.github.com/repos/huggingface/datasets/issues/2204 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2204/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2204/comments | https://api.github.com/repos/huggingface/datasets/issues/2204/events | https://github.com/huggingface/datasets/pull/2204 | 855,144,431 | MDExOlB1bGxSZXF1ZXN0NjEyOTU1MzM2 | 2,204 | Add configurable options to `seqeval` metric | {
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"following_url"... | [] | 1,618,084,699,000 | 1,618,494,586,000 | 1,618,494,586,000 | CONTRIBUTOR | null | Fixes #2148
Adds options to use strict mode, different schemes of evaluation, sample weight and adjust zero_division behavior, if encountered.
`seqeval` provides schemes as objects, hence dynamic import from string, to avoid making the user do the import (thanks to @albertvillanova for the `importlib` idea). | {
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"Hi ! Can you add a description regarding this PR ? Why do you think we need to update the dummy data used to test the `banking77` dataset loading script ?",
"Closing for inactivity. Feel free to re-open if you want to push this change"
] | 1,618,056,610,000 | 1,619,188,419,000 | 1,619,188,419,000 | NONE | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2202 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2202/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2202/comments | https://api.github.com/repos/huggingface/datasets/issues/2202/events | https://github.com/huggingface/datasets/pull/2202 | 854,501,109 | MDExOlB1bGxSZXF1ZXN0NjEyNDM2ODMx | 2,202 | Add classes GenerateMode, DownloadConfig and Version to the documentation | {
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"following_url"... | [] | 1,617,973,099,000 | 1,618,250,280,000 | 1,618,250,279,000 | MEMBER | null | Add documentation for classes `GenerateMode`, `DownloadConfig` and `Version`.
Update the docstring of `load_dataset` to create cross-reference links to the classes.
Related to #2187. | {
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https://api.github.com/repos/huggingface/datasets/issues/2201 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2201/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2201/comments | https://api.github.com/repos/huggingface/datasets/issues/2201/events | https://github.com/huggingface/datasets/pull/2201 | 854,499,563 | MDExOlB1bGxSZXF1ZXN0NjEyNDM1NTE3 | 2,201 | Fix ArrowWriter overwriting features in ArrowBasedBuilder | {
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"following_url"... | [] | 1,617,972,979,000 | 1,618,234,337,000 | 1,618,234,336,000 | MEMBER | null | This should fix the issues with CSV loading experienced in #2153 and #2200.
The CSV builder is an ArrowBasedBuilder that had an issue with its ArrowWriter used to write the arrow file from the csv data.
The writer wasn't initialized with the features passed by the user. Therefore the writer was inferring the featur... | {
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https://api.github.com/repos/huggingface/datasets/issues/2200 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2200/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2200/comments | https://api.github.com/repos/huggingface/datasets/issues/2200/events | https://github.com/huggingface/datasets/issues/2200 | 854,449,656 | MDU6SXNzdWU4NTQ0NDk2NTY= | 2,200 | _prepare_split will overwrite DatasetBuilder.info.features | {
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"Hi ! This might be related to #2153 \r\n\r\nYou're right the ArrowWriter should be initialized with `features=self.info.features` ! Good catch\r\nI'm opening a PR to fix this and also to figure out how it was not caught in the tests\r\n\r\nEDIT: opened #2201",
"> Hi ! This might be related to #2153\r\n> \r\n> Yo... | 1,617,968,833,000 | 1,622,803,055,000 | 1,622,803,055,000 | NONE | null | Hi, here is my issue:
I initialized a Csv datasetbuilder with specific features:
```
def get_dataset_features(data_args):
features = {}
if data_args.text_features:
features.update({text_feature: hf_features.Value("string") for text_feature in data_args.text_features.strip().split(",")})
if da... | {
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https://api.github.com/repos/huggingface/datasets/issues/2199 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2199/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2199/comments | https://api.github.com/repos/huggingface/datasets/issues/2199/events | https://github.com/huggingface/datasets/pull/2199 | 854,417,318 | MDExOlB1bGxSZXF1ZXN0NjEyMzY0ODU3 | 2,199 | Fix backward compatibility in Dataset.load_from_disk | {
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"Hi @lhoestq, could you please check if this makes sense? Thanks.",
"What about using `_indices_data_files` field in save_to_disk instead of `_indices_files` ?\r\nThis way future datasets can also be reloaded from older versions of the lib\r\n\r\n`_indices_files` was introduced in a recent PR and was not released... | 1,617,966,070,000 | 1,617,983,825,000 | 1,617,983,825,000 | MEMBER | null | Fix backward compatibility when loading from disk an old dataset saved to disk with indices using key "_indices_data_files".
Related to #2195. | {
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"From offline discussions: we want to make the permissions handling consistent with `transformers`. However from discussion in https://github.com/huggingface/transformers/pull/11119 it looks like it might not be a good solution to provide this argument. Users should use umask for now, and we'll see how things evol... | 1,617,961,146,000 | 1,618,582,306,000 | 1,618,582,306,000 | CONTRIBUTOR | null | As discussed in #2065 I've added `file_permission` argument in `load_dataset`.
Added mainly 2 things here:
1) Permission of downloaded datasets when converted to .arrow files can be changed with argument `file_permission` argument in `load_dataset` (default is 0o644 only)
2) Incase the user uses `map` later on t... | {
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https://api.github.com/repos/huggingface/datasets/issues/2197 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2197/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2197/comments | https://api.github.com/repos/huggingface/datasets/issues/2197/events | https://github.com/huggingface/datasets/pull/2197 | 854,356,559 | MDExOlB1bGxSZXF1ZXN0NjEyMzEzMzQw | 2,197 | fix missing indices_files in load_form_disk | {
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`load_from_disk` was failing if there was no "_indices_files" field in state.json. This can happen if the dataset has no indices mapping | {
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"Hi ! Files that starts with `cache-*` are cached computation files, i.e. they are the cached results of map/filter/cast/etc. operations. For example if you used `map` on your dataset to transform it, then the resulting dataset is going to be stored and cached in a `cache-*` file. These files are used to avoid havi... | 1,617,940,159,000 | 1,618,205,129,000 | 1,618,205,129,000 | NONE | null | Hi,
I am using datasets to load large json file of 587G.
I checked the cached folder and found that there are two arrow files created:
* `cache-ed205e500a7dc44c.arrow` - 355G
* `json-train.arrow` - 582G
Why is the first file created?
If I delete it, would I still be able to `load_from_disk`? | {
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"Thanks for reporting @samsontmr.\r\n\r\nIt seems a backward compatibility issue...",
"Thanks @samsontmr this should be fixed on master now\r\n\r\nFeel free to reopen if you're still having issues"
] | 1,617,932,232,000 | 1,617,962,109,000 | 1,617,962,079,000 | NONE | null | After pulling the latest master, I'm getting a crash when `load_from_disk` tries to load my local dataset.
Trace:
```
Traceback (most recent call last):
File "load_data.py", line 11, in <module>
dataset = load_from_disk(SRC)
File "/opt/conda/envs/py38/lib/python3.8/site-packages/datasets/load.py", line ... | {
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"\r\nThis wasn't a `datasets` problem, but `transformers`' and it was solved here https://github.com/huggingface/transformers/pull/11168\r\n"
] | 1,617,915,768,000 | 1,617,987,410,000 | 1,617,933,177,000 | MEMBER | null | While this works fine with py3.8, under py3.7, with a totally new conda env and transformers install:
```
git clone https://github.com/huggingface/transformers
cd transformers
pip install -e .[testing]
export BS=1; rm -rf /tmp/test-clm; PYTHONPATH=src USE_TF=0 CUDA_VISIBLE_DEVICES=0 python \
examples/language... | {
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"Hi ! Yes we are working on making `filter` significantly faster. You can look at related PRs here: #2060 #2178 \r\n\r\nI think you can expect to have the fast version of `filter` available next week.\r\n\r\nWe'll make it only select one column, and we'll also make the overall filtering operation way faster by avoi... | 1,617,905,774,000 | 1,619,453,639,000 | 1,619,453,639,000 | CONTRIBUTOR | null | I'm currently using the `wikipedia` dataset— I'm tokenizing the articles with the `tokenizers` library using `map()` and also adding a new `num_tokens` column to the dataset as part of that map operation.
I want to be able to _filter_ the dataset based on this `num_tokens` column, but even when I specify `input_colu... | {
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The `packaging` dependency is also required for the build to complete. | {
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"I find very interesting that idea of using a fixture instead!\r\n\r\nLet me rework a little bit this PR, @lhoestq.",
"@lhoestq, as this is a big refactoring, I had many problems to solve the conflicts with the master branch...\r\n\r\nTherefore, I think it is better to merge this as it is, and then to make other ... | 1,617,880,864,000 | 1,618,818,791,000 | 1,618,818,790,000 | MEMBER | null | Refactorize Dataset tests to use Dataset as context manager. | {
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"Hi @anassalamah,\r\n\r\nCould you please try with this:\r\n```python\r\ntrain_ds = load_dataset(\"news_commentary\", lang1=\"ar\", lang2=\"en\", split='train[:98%]')\r\nval_ds = load_dataset(\"news_commentary\", lang1=\"ar\", lang2=\"en\", split='train[98%:]')\r\n```",
"Hello @albertvillanova, \r\n\r\nThanks for... | 1,617,868,423,000 | 1,621,850,635,000 | 1,621,850,635,000 | NONE | null | I used load_dataset to load the news_commentary dataset for "ar-en" translation pairs but found translations from Arabic to Hindi.
```
train_ds = load_dataset("news_commentary", "ar-en", split='train[:98%]')
val_ds = load_dataset("news_commentary", "ar-en", split='train[98%:]')
# filtering out examples that a... | {
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"Hi ! We refactored save_to_disk in #2025 so this doesn't happen.\r\nFeel free to try it on master for now\r\nWe'll do a new release soon"
] | 1,617,856,973,000 | 1,618,408,625,000 | null | NONE | null | As you can see, it saves the entire dataset.
@lhoestq
You can check by going through the following example,
```
from datasets import load_from_disk,concatenate_datasets
loaded_data=load_from_disk('/home/gsir059/HNSW-ori/my_knowledge_dataset')
n=20
kb_list=[loaded_data.shard(n, i, contiguous=True) for i... | {
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"Hi ! Thanks for reporting\r\nIf I recall correctly this has been recently fixed #1995\r\nCan you try to upgrade your local version of `datasets` ?\r\n```\r\npip install --upgrade datasets\r\n```",
"Hi Ihoestq,\r\n\r\nThank you. It works after upgrading the datasets\r\n"
] | 1,617,855,714,000 | 1,617,883,999,000 | 1,617,883,999,000 | NONE | null | I ran a simple code to list all texts in Timit dataset and the texts were all the same.
Is this dataset corrupted?
**Code:**
timit = load_dataset("timit_asr")
print(*timit['train']['text'], sep='\n')
**Result:**
Would such an act of refusal be useful?
Would such an act of refusal be useful?
Would such an act of... | {
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"An educated guess: does this refer to the fact that depending on the custom column names in the dataset files (csv in this case), there is a dataset loader being created? and this dataset loader - using the \"custom data configuration\" is used among all jobs running using this particular csv files? (thinking out ... | 1,617,840,988,000 | 1,618,412,158,000 | null | NONE | null | I thought I had disabled datasets caching in my code, as follows:
```
from datasets import set_caching_enabled
...
def main():
# disable caching in datasets
set_caching_enabled(False)
```
However, in my log files I see messages like the following:
```
04/07/2021 18:34:42 - WARNING - datasets.build... | {
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"cc @sebastiangehrmann"
] | 1,617,831,547,000 | 1,617,832,595,000 | 1,617,832,595,000 | MEMBER | null | This PR updates the GEM dataset to:
- remove extraneous fields in WikiAuto after https://github.com/huggingface/datasets/pull/2171 fixed the source
- add context and services to Schema Guided Dialog
- Add new or update challenge sets for MLSUM ES and DE, XSUM, and SGD | {
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"Hi, one workaround would be to save the mapped(tokenized in your case) file using `save_to_disk`, and having each process load this file using `load_from_disk`. This is what I am doing, and in this case, I turn off the ability to automatically load from the cache.\r\n\r\nAlso, multiprocessing the map function seem... | 1,617,819,734,000 | 1,634,973,075,000 | 1,617,982,711,000 | MEMBER | null | Hi,
I have a question regarding distributed training and the `.map` call on a dataset.
I have a local dataset "my_custom_dataset" that I am loading with `datasets = load_from_disk(dataset_path=my_path)`.
`dataset` is then tokenized:
```python
datasets = load_from_disk(dataset_path=my_path)
[...]
def tokeni... | {
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"Made the required changes @lhoestq , sorry it took so much time!"
] | 1,617,814,063,000 | 1,618,573,477,000 | 1,618,572,419,000 | CONTRIBUTOR | null | Addresses #2176
I'm happy to discuss the API and internals! | {
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"following_url"... | [] | 1,617,808,631,000 | 1,617,872,085,000 | 1,617,872,084,000 | MEMBER | null | Recently several changes happened:
1. latest versions of `fsspec` require python>3.7 for async features
2. `s3fs` added a dependency on `aiobotocore`, which is not compatible with the `moto` s3 mock context manager
This PR fixes both issues, by pinning `fsspec` and `s3fs` for python 3.6, and by using `moto` in ser... | {
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"I ping @krandiash to keep him up to date.",
"TODO:\r\n- [x] Add a section in the docs about this.\r\n- ~Add a warning if someone tries to specify `cache_file_name=` in `map`, `filter` etc. on a dataset that is in memory, since the computation is not going to be cached in this case.~",
"@lhoestq I have a questi... | 1,617,800,418,000 | 1,618,928,412,000 | 1,618,913,044,000 | MEMBER | null | Set a default value for `in_memory` depending on the size of the dataset to be loaded.
Close #2179.
TODO:
- [x] Add a section in the docs about this.
- ~Add a warning if someone tries to specify `cache_file_name=` in `map`, `filter` etc. on a dataset that is in memory, since the computation is not going to be c... | {
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https://api.github.com/repos/huggingface/datasets/issues/2181 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2181/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2181/comments | https://api.github.com/repos/huggingface/datasets/issues/2181/events | https://github.com/huggingface/datasets/issues/2181 | 852,261,607 | MDU6SXNzdWU4NTIyNjE2MDc= | 2,181 | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries) | {
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"Hi ! Can you try to increase the block size ? For example\r\n```python\r\nblock_size_10MB = 10<<20\r\nload_dataset(\"json\", ..., block_size=block_size_10MB)\r\n```\r\nThe block size corresponds to how much bytes to process at a time from the input stream.\r\nThis will determine multi-threading granularity as well... | 1,617,791,206,000 | 1,618,211,755,000 | 1,618,211,755,000 | NONE | null | Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as follows:
```
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.7.9/lib/python3.7/site-pack... | {
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"following_url"... | [] | 1,617,789,496,000 | 1,618,913,044,000 | 1,618,913,043,000 | MEMBER | null | Currently all datasets are loaded using memory mapping by default in `load_dataset`.
However this might not be necessary for small datasets. If a dataset is small enough, then it can be loaded in-memory and:
- its memory footprint would be small so it's ok
- in-memory computations/queries would be faster
- the cach... | {
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"I addressed your comments about the docstrings and the output validation :)",
"I updated the bleurt mocking method and bleurt test is passing now.\r\nI also ran the slow tests and they are passing for bleurt.",
"Thanks @lhoestq and @albertvillanova !"
] | 1,617,787,850,000 | 1,618,928,444,000 | 1,618,306,096,000 | MEMBER | null | The `cast` operation on a pyarrow Table may create new arrays in memory.
This is an issue since users expect memory mapped datasets to not fill up the RAM.
To fix that I used `map` to write a new arrow file on disk when cast is used.
To make things more convenient I introduced the `arrow` formatting of a dataset, ... | {
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https://api.github.com/repos/huggingface/datasets/issues/2177 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2177/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2177/comments | https://api.github.com/repos/huggingface/datasets/issues/2177/events | https://github.com/huggingface/datasets/pull/2177 | 852,065,307 | MDExOlB1bGxSZXF1ZXN0NjEwMzc5MDYx | 2,177 | add social thumbnial | {
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"following_url"... | [] | 1,617,777,606,000 | 1,617,783,361,000 | 1,617,783,361,000 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/datasets/issues/2176 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2176/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2176/comments | https://api.github.com/repos/huggingface/datasets/issues/2176/events | https://github.com/huggingface/datasets/issues/2176 | 851,865,795 | MDU6SXNzdWU4NTE4NjU3OTU= | 2,176 | Converting a Value to a ClassLabel | {
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"Hi @nelson-liu!\r\nHere is what I do to convert a string to class label:\r\n\r\n```python\r\nfrom datasets import load_dataset, features\r\n\r\n\r\ndset = load_dataset(...)\r\ncol_name = \"the string column name\"\r\n\r\nclass_names = dset.unique(col_name)\r\nclass_feature = features.ClassLabel(names=sorted(class... | 1,617,749,656,000 | 1,618,827,034,000 | null | NONE | null | Hi!
In the docs for `cast`, it's noted that `For non-trivial conversion, e.g. string <-> ClassLabel you should use map() to update the Dataset.`
Would it be possible to have an example that demonstrates such a string <-> ClassLabel conversion using `map`? Thanks! | {
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https://api.github.com/repos/huggingface/datasets/issues/2175 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2175/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2175/comments | https://api.github.com/repos/huggingface/datasets/issues/2175/events | https://github.com/huggingface/datasets/issues/2175 | 851,836,096 | MDU6SXNzdWU4NTE4MzYwOTY= | 2,175 | dataset.search_batch() function outputs all -1 indices sometime. | {
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"Actually, I found the answer [here](https://github.com/facebookresearch/faiss/wiki/FAQ#what-does-it-mean-when-a-search-returns--1-ids). \r\n\r\nSo we have to do some modifications to the code for instances where the index doesn't retrieve any IDs.",
"@lhoestq @patrickvonplaten \r\n\r\nI also found another short... | 1,617,745,849,000 | 1,618,575,676,000 | 1,618,575,675,000 | NONE | null | I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/rag/retrieval_... | {
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https://api.github.com/repos/huggingface/datasets/issues/2174 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2174/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2174/comments | https://api.github.com/repos/huggingface/datasets/issues/2174/events | https://github.com/huggingface/datasets/pull/2174 | 851,383,675 | MDExOlB1bGxSZXF1ZXN0NjA5ODE2OTQ2 | 2,174 | Pin docutils for better doc | {
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"following_url"... | [] | 1,617,712,820,000 | 1,617,713,753,000 | 1,617,713,753,000 | MEMBER | null | The latest release of docutils make the navbar in the documentation weird and the Markdown wrongly interpreted:
We had the same problem in Transformers and solved it by pinning docutils (a dep of sphinx... | {
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https://api.github.com/repos/huggingface/datasets/issues/2173 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2173/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2173/comments | https://api.github.com/repos/huggingface/datasets/issues/2173/events | https://github.com/huggingface/datasets/pull/2173 | 851,359,284 | MDExOlB1bGxSZXF1ZXN0NjA5Nzk2NzI2 | 2,173 | Add OpenSLR dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/2172 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2172/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2172/comments | https://api.github.com/repos/huggingface/datasets/issues/2172/events | https://github.com/huggingface/datasets/pull/2172 | 851,229,399 | MDExOlB1bGxSZXF1ZXN0NjA5Njg4ODgx | 2,172 | Pin fsspec lower than 0.9.0 | {
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"following_url"... | [] | 1,617,700,749,000 | 1,617,702,567,000 | 1,617,702,566,000 | MEMBER | null | Today's release of `fsspec` 0.9.0 implied a new release of `s3fs` 0.6.0 but this version breaks the CI (see [here](https://app.circleci.com/pipelines/github/huggingface/datasets/5312/workflows/490f3240-cd1c-4dd1-bb60-b416771c5584/jobs/32734) for example)
I'm pinning `fsspec` until this has been resolved | {
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https://api.github.com/repos/huggingface/datasets/issues/2171 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2171/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2171/comments | https://api.github.com/repos/huggingface/datasets/issues/2171/events | https://github.com/huggingface/datasets/pull/2171 | 851,090,662 | MDExOlB1bGxSZXF1ZXN0NjA5NTY4MDcw | 2,171 | Fixed the link to wikiauto training data. | {
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"Also you can ignore the CI failing on `docs`, this has been fixed on master :)",
"@lhoestq I need to update other stuff on GEM later today too, so will merge this one and remove columns in the next PR!",
"Ok !"
] | 1,617,693,191,000 | 1,617,725,142,000 | 1,617,725,109,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2170 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2170/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2170/comments | https://api.github.com/repos/huggingface/datasets/issues/2170/events | https://github.com/huggingface/datasets/issues/2170 | 850,913,228 | MDU6SXNzdWU4NTA5MTMyMjg= | 2,170 | Wikipedia historic dumps are deleted but hf/datasets hardcodes dump date | {
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"It seems that this can be fixed from user's end by including a `date` argument, like this:\r\n\r\n`dataset = datasets.load_dataset('wikipedia', '20200501.en', date='20210420')`\r\n\r\nYou can get available dates from [here](https://dumps.wikimedia.org/enwiki/).\r\n\r\nThis is not a proper fix however as all the fi... | 1,617,678,798,000 | 1,623,805,850,000 | null | NONE | null | Wikimedia does not keep all historical dumps. For example, as of today https://dumps.wikimedia.org/kowiki/ only provides
```
20201220/ 02-Feb-2021 01:36 -
20210101/ 21-Feb-2021 01:26 -
20210120/ ... | {
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https://api.github.com/repos/huggingface/datasets/issues/2169 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2169/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2169/comments | https://api.github.com/repos/huggingface/datasets/issues/2169/events | https://github.com/huggingface/datasets/pull/2169 | 850,456,180 | MDExOlB1bGxSZXF1ZXN0NjA5MDI2ODUz | 2,169 | Updated WER metric implementation to avoid memory issues | {
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"Hi ! Thanks for suggesting this fix \r\nUnfortunately it looks like it's already been fixed by #2111 \r\n\r\nFeel free to share your thoughts about this PR !\r\n\r\nI'm closing this one if you don't mind."
] | 1,617,637,400,000 | 1,617,721,378,000 | 1,617,721,378,000 | NONE | null | This is in order to fix this issue:
https://github.com/huggingface/datasets/issues/2078
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https://api.github.com/repos/huggingface/datasets/issues/2168 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2168/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2168/comments | https://api.github.com/repos/huggingface/datasets/issues/2168/events | https://github.com/huggingface/datasets/pull/2168 | 849,957,941 | MDExOlB1bGxSZXF1ZXN0NjA4NjA4Nzg5 | 2,168 | Preserve split type when realoding dataset | {
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"Thanks for diving into this !\r\n\r\nBefore going further, I just want to make sure if using `eval` is the right solution\r\nPersonally I'm not a big fan of `eval` since it has many security concerns. Also storing string representations of python objects in the json files is not ideal either IMO, so maybe it's pos... | 1,617,569,181,000 | 1,618,829,825,000 | 1,618,823,335,000 | CONTRIBUTOR | null | Fixes #2167
Using `eval` is not ideal for security reasons (in web apps I assume), but without it the code would be much more complex IMO.
In terms of style, instead of explicitly importing a private member (`_RelativeInstruction`), we can add these imports at the top of the module:
```python
from . import arr... | {
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"following_url"... | [] | 1,617,564,594,000 | 1,618,823,335,000 | 1,618,823,335,000 | CONTRIBUTOR | null | A minimal reproducible example:
```python
>>> from datasets import load_dataset, Dataset
>>> dset = load_dataset("sst", split="train")
>>> dset.save_to_disk("sst")
>>> type(dset.split)
<class 'datasets.splits.NamedSplit'>
>>> dset = Dataset.load_from_disk("sst")
>>> type(dset.split) # NamedSplit expected
<cla... | {
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"Hi @vyraun ! The test references for CommonGen are not publicly available: you can reach out to the original dataset authors if you would like to ask for them, but we will not be releasing them as part of GEM (March 31st was the release date for the test set inputs, references are incidentally released for some of... | 1,617,501,765,000 | 1,617,696,792,000 | 1,617,696,792,000 | NONE | null | @yjernite Hi, are the test sets for the GEM datasets scheduled to be [added soon](https://gem-benchmark.com/shared_task)?
e.g.
```
from datasets import load_dataset
DATASET_NAME="common_gen"
data = load_dataset("gem", DATASET_NAME)
```
The test set doesn't have the target or references.
```
data['test... | {
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"Hi,\r\n\r\na HF dataset can be converted to a Torch Dataset with a simple wrapper as follows:\r\n```python\r\nfrom torch.utils.data import Dataset\r\n \r\nclass HFDataset(Dataset):\r\n def __init__(self, dset):\r\n self.dset = dset\r\n\r\n def __getitem__(self, idx):\r\n return self.dset[idx]\r... | 1,617,498,108,000 | 1,629,820,535,000 | 1,617,807,964,000 | NONE | null | Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_attention_mask", "labels"],
)
engine, _, _, _ = deepspeed.initialize(
... | {
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"following_url"... | [] | 1,617,484,022,000 | 1,617,720,069,000 | 1,617,720,068,000 | CONTRIBUTOR | null | Replaces all the occurrences of the `assertTrue(isinstance(` pattern with `assertIsInstance`. | {
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"Hi @mariosasko,\r\nJust came across this PR and I was wondering if we can use\r\n`description = \"\\n\\n\".join(OrderedDict.fromkeys([info.description for info in dataset_infos]))`\r\n\r\nThis will obviate the need for `unique` and is almost as fast as `set`. We could have used `dict` inplace of `OrderedDict` but ... | 1,617,460,290,000 | 1,617,720,000,000 | 1,617,719,999,000 | CONTRIBUTOR | null | I thought someone from the community with less experience would be interested in fixing this issue, but that wasn't the case.
Fixes #2103 | {
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"This looks like an issue with the cc100 dataset itself but not sure\r\nDid you try loading cc100 on your machine ?",
"Hi\nloading works fine, but the viewer only is broken\nthanks\n\nOn Wed, Apr 7, 2021 at 12:17 PM Quentin Lhoest ***@***.***>\nwrote:\n\n> This looks like an issue with the cc100 dataset itself bu... | 1,617,358,273,000 | 1,617,800,467,000 | null | NONE | null | Hi
visualization through dataset viewer for cc100 is broken
https://huggingface.co/datasets/viewer/
thanks a lot
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"Not yet but it’s on the short/mid-term roadmap (requested by many indeed).",
"oh, great, really awesome feature to have, thank you very much for the great, fabulous work",
"We'll work on dataset streaming soon. This should allow you to only load the examples you need ;)",
"thanks a lot Quentin, this would be... | 1,617,358,006,000 | 1,625,239,169,000 | null | NONE | null | Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks | {
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"Hi.\r\nI cannot always reproduce this issue, and on later runs I did not see it so far. Sometimes also I set 8 processes but I see less being showed, is this normal, here only 5 are shown for 8 being set, thanks\r\n\r\n```\r\n#3: 11%|███████████████▊ ... | 1,617,350,173,000 | 1,617,358,472,000 | 1,617,358,471,000 | NONE | null | Hi @lhoestq
I am running this code from huggingface transformers https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py
to speed up tokenization, since I am running on multiple datasets, I am using data_args.preprocessing_num_workers = 4 with opus100 corpus but this moves ... | {
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"closing since I think this is cc100, just the name has been changed. thanks "
] | 1,617,319,716,000 | 1,617,357,919,000 | 1,617,357,919,000 | NONE | null | ## Adding a Dataset
- **Name:** ccnet
- **Description:**
Common Crawl
- **Paper:**
https://arxiv.org/abs/1911.00359
- **Data:**
https://github.com/facebookresearch/cc_net
- **Motivation:**
this is one of the most comprehensive clean monolingual datasets across a variety of languages. Quite importan... | {
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"Thanks for reporting !\r\nThe viewer doesn't have all the dependencies of the datasets. We may add openpyxl to be able to show this dataset properly"
] | 1,617,286,400,000 | 1,617,791,169,000 | null | NONE | null | When I visit the [Huggingface - viewer](https://huggingface.co/datasets/viewer/) web site, under the dataset "fake_news_english" I've got this error:
> ImportError: To be able to use this dataset, you need to install the following dependencies['openpyxl'] using 'pip install # noqa: requires this pandas optional depe... | {
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"following_url"... | [] | 1,617,219,509,000 | 1,617,693,559,000 | 1,617,693,559,000 | CONTRIBUTOR | null | Updated user permissions based on running user's umask (#2065). Let me know if `0o666` is looking good or should I change it to `~umask` only (to give execute permissions as well) | {
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"Just note that docstrings injected from PyArrow do not follow the same convention for formatting types in `Args` or `Returns` as we do... Not a big problem, anyway! 😄 "
] | 1,617,201,370,000 | 1,617,295,590,000 | 1,617,205,328,000 | MEMBER | null | Following #2025 , I added the table classes to the documentation
cc @albertvillanova | {
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"Awesome!"
] | 1,617,200,570,000 | 1,617,269,220,000 | 1,617,268,568,000 | CONTRIBUTOR | null | NorNE is a manually annotated corpus of named entities which extends the annotation of the existing Norwegian Dependency Treebank. Comprising both of the official standards of written Norwegian (Bokmål and Nynorsk), the corpus contains around 600,000 tokens and annotates a rich set of entity types including persons, or... | {
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