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https://api.github.com/repos/huggingface/datasets/issues/2051 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2051/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2051/comments | https://api.github.com/repos/huggingface/datasets/issues/2051/events | https://github.com/huggingface/datasets/pull/2051 | 831,027,021 | MDExOlB1bGxSZXF1ZXN0NTkyNDQ2MDU1 | 2,051 | Add MDD Dataset | {
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"Hi @lhoestq,\r\n\r\nI have added changes from review.",
"Thanks for approving :)"
] | 1,615,680,065,000 | 1,616,152,544,000 | 1,616,149,919,000 | CONTRIBUTOR | null | - **Name:** *MDD Dataset*
- **Description:** The Movie Dialog dataset (MDD) is designed to measure how well models can perform at goal and non-goal orientated dialog centered around the topic of movies (question answering, recommendation and discussion), from various movie reviews sources such as MovieLens and OMDb.
... | {
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"@lhoestq - We could simply use the \"general\" json dataset for this no? ",
"Sure you can use the json loader\r\n```python\r\ndata_files = {\"train\": \"path/to/your/train_data.json\", \"test\": \"path/to/your/test_data.json\"}\r\ntrain_dataset = load_dataset(\"json\", data_files=data_files, split=\"train\")\r\n... | 1,615,672,870,000 | 1,615,800,448,000 | 1,615,800,448,000 | NONE | null | Thank you for your recent tutorial on how to finetune Wav2Vec2 on a custom dataset. The example you gave here (https://huggingface.co/blog/fine-tune-xlsr-wav2vec2) was on the CommonVoice dataset. However, what if I want to load my own dataset? I have a manifest (transcript and their audio files) in a JSON file.
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https://api.github.com/repos/huggingface/datasets/issues/2049 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2049/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2049/comments | https://api.github.com/repos/huggingface/datasets/issues/2049/events | https://github.com/huggingface/datasets/pull/2049 | 830,978,687 | MDExOlB1bGxSZXF1ZXN0NTkyNDE2MzQ0 | 2,049 | Fix text-classification tags | {
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"LGTM, thanks for fixing."
] | 1,615,665,102,000 | 1,615,909,666,000 | 1,615,909,666,000 | CONTRIBUTOR | null | There are different tags for text classification right now: `text-classification` and `text_classification`:
.
This PR fixes it.
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```
:/tmp$ wget https://raw.githubusercontent.com/huggingface/datasets/1.4.1/metrics/sacrebleu/sacrebleu.py--2021-03-12 18:35:59-- https://raw.githubusercontent.com/huggingface/datasets/1.4.1/metrics/sacrebleu/sacrebleu.py
Resolving raw.githubusercontent.com (raw.githubuser... | {
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https://api.github.com/repos/huggingface/datasets/issues/2047 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2047/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2047/comments | https://api.github.com/repos/huggingface/datasets/issues/2047/events | https://github.com/huggingface/datasets/pull/2047 | 830,626,430 | MDExOlB1bGxSZXF1ZXN0NTkyMTI2NzQ3 | 2,047 | Multilingual dIalogAct benchMark (miam) | {
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"Hello. All aforementioned changes have been made. I've also re-run black on miam.py. :-)",
"I will run isort again. Hopefully it resolves the current check_code_quality test failure.",
"Once the review period is over, feel free to open a PR to add all the missing information ;)",
"Hi! I will follow up right ... | 1,615,590,175,000 | 1,616,495,794,000 | 1,616,150,833,000 | CONTRIBUTOR | null | My collaborators (@EmileChapuis, @PierreColombo) and I within the Affective Computing team at Telecom Paris would like to anonymously publish the miam dataset. It is assocated with a publication currently under review. We will update the dataset with full citations once the review period is over. | {
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"I think faiss automatically sets the number of threads to use to build the index.\r\nCan you check how many CPU cores are being used when you build the index in `use_own_knowleldge_dataset` as compared to this script ? Are there other programs running (maybe for rank>0) ?",
"Hi,\r\n I am running the add_faiss_in... | 1,615,580,838,000 | 1,616,624,951,000 | 1,616,624,951,000 | NONE | null | As the below code suggests, I want to run add_faisis_index in every nth interaction from the training loop. I have 7.2 million documents. Usually, it takes 2.5 hours (if I run an as a separate process similar to the script given in rag/use_own_knowleldge_dataset.py). Now, this takes usually 5hrs. Is this normal? Any ... | {
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https://api.github.com/repos/huggingface/datasets/issues/2045 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2045/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2045/comments | https://api.github.com/repos/huggingface/datasets/issues/2045/events | https://github.com/huggingface/datasets/pull/2045 | 830,351,527 | MDExOlB1bGxSZXF1ZXN0NTkxODc2Mjcz | 2,045 | Preserve column ordering in Dataset.rename_column | {
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"Not sure why CI isn't triggered.\r\n\r\n@lhoestq Can you please help me with this? ",
"I don't know how to trigger it manually, but an empty commit should do the job"
] | 1,615,573,607,000 | 1,615,906,085,000 | 1,615,905,305,000 | CONTRIBUTOR | null | Currently `Dataset.rename_column` doesn't necessarily preserve the order of the columns:
```python
>>> from datasets import Dataset
>>> d = Dataset.from_dict({'sentences': ["s1", "s2"], 'label': [0, 1]})
>>> d
Dataset({
features: ['sentences', 'label'],
num_rows: 2
})
>>> d.rename_column('sentences', '... | {
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"Hi @lhoestq,\r\n\r\nI have added changes from the review.",
"Thanks for approving @lhoestq "
] | 1,615,572,259,000 | 1,616,152,213,000 | 1,616,149,755,000 | CONTRIBUTOR | null | This PR adds the [CBT Dataset](https://arxiv.org/abs/1511.02301).
Note that I have also added the `raw` dataset as a separate configuration. I couldn't find a suitable "task" for it in YAML tags.
The dummy files have one example each, as the examples are slightly big. For `raw` dataset, I just used top few lines,... | {
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"@lhoestq But we don't perform conversion to a `NamedSplit` if `_split` is not a string which means it **will** be a `ReadInstruction` after reloading.",
"Yes right ! I read it wrong.\r\nPerfect then"
] | 1,615,566,911,000 | 1,615,904,738,000 | 1,615,903,505,000 | CONTRIBUTOR | null | Fixes #2022 (+ some style fixes) | {
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https://api.github.com/repos/huggingface/datasets/issues/2042 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2042/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2042/comments | https://api.github.com/repos/huggingface/datasets/issues/2042/events | https://github.com/huggingface/datasets/pull/2042 | 830,190,276 | MDExOlB1bGxSZXF1ZXN0NTkxNzQwNzQ3 | 2,042 | Fix arrow memory checks issue in tests | {
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"following_url"... | [] | 1,615,560,592,000 | 1,615,561,463,000 | 1,615,561,462,000 | MEMBER | null | The tests currently fail on `master` because the arrow memory verification doesn't return the expected memory evolution when loading an arrow table in memory.
From my experiments, the tests fail only when the full test suite is ran.
This made me think that maybe some arrow objects from other tests were not freeing th... | {
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https://api.github.com/repos/huggingface/datasets/issues/2041 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2041/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2041/comments | https://api.github.com/repos/huggingface/datasets/issues/2041/events | https://github.com/huggingface/datasets/pull/2041 | 830,180,803 | MDExOlB1bGxSZXF1ZXN0NTkxNzMyNzMw | 2,041 | Doc2dial update data_infos and data_loaders | {
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https://api.github.com/repos/huggingface/datasets/issues/2040 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2040/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2040/comments | https://api.github.com/repos/huggingface/datasets/issues/2040/events | https://github.com/huggingface/datasets/issues/2040 | 830,169,387 | MDU6SXNzdWU4MzAxNjkzODc= | 2,040 | ValueError: datasets' indices [1] come from memory and datasets' indices [0] come from disk | {
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"Hi ! To help me understand the situation, can you print the values of `load_from_disk(PATH_DATA_CLS_A)['train']._indices_data_files` and `load_from_disk(PATH_DATA_CLS_B)['train']._indices_data_files` ?\r\nThey should both have a path to an arrow file\r\n\r\nAlso note that from #2025 concatenating datasets will no... | 1,615,559,220,000 | 1,628,100,043,000 | 1,628,100,043,000 | NONE | null | Hi there,
I am trying to concat two datasets that I've previously saved to disk via `save_to_disk()` like so (note that both are saved as `DataDict`, `PATH_DATA_CLS_*` are `Path`-objects):
```python
concatenate_datasets([load_from_disk(PATH_DATA_CLS_A)['train'], load_from_disk(PATH_DATA_CLS_B)['train']])
```
Yie... | {
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https://api.github.com/repos/huggingface/datasets/issues/2039 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2039/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2039/comments | https://api.github.com/repos/huggingface/datasets/issues/2039/events | https://github.com/huggingface/datasets/pull/2039 | 830,047,652 | MDExOlB1bGxSZXF1ZXN0NTkxNjE3ODY3 | 2,039 | Doc2dial rc | {
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"following_url"... | [] | 1,615,550,188,000 | 1,615,563,156,000 | 1,615,563,156,000 | CONTRIBUTOR | null | Added fix to handle the last turn that is a user turn. | {
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https://api.github.com/repos/huggingface/datasets/issues/2038 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2038/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2038/comments | https://api.github.com/repos/huggingface/datasets/issues/2038/events | https://github.com/huggingface/datasets/issues/2038 | 830,036,875 | MDU6SXNzdWU4MzAwMzY4NzU= | 2,038 | outdated dataset_infos.json might fail verifications | {
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"Hi ! Thanks for reporting.\r\n\r\nTo update the dataset_infos.json you can run:\r\n```\r\ndatasets-cli test ./datasets/doc2dial --all_configs --save_infos --ignore_verifications\r\n```",
"Fixed by #2041, thanks again @songfeng !"
] | 1,615,549,314,000 | 1,615,912,060,000 | 1,615,912,060,000 | CONTRIBUTOR | null | The [doc2dial/dataset_infos.json](https://github.com/huggingface/datasets/blob/master/datasets/doc2dial/dataset_infos.json) is outdated. It would fail data_loader when verifying download checksum etc..
Could you please update this file or point me how to update this file?
Thank you. | {
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https://api.github.com/repos/huggingface/datasets/issues/2037 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2037/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2037/comments | https://api.github.com/repos/huggingface/datasets/issues/2037/events | https://github.com/huggingface/datasets/pull/2037 | 829,919,685 | MDExOlB1bGxSZXF1ZXN0NTkxNTA4MTQz | 2,037 | Fix: Wikipedia - save memory by replacing root.clear with elem.clear | {
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"The error you got is minor and appeared in the last version of pyarrow, we'll fix the CI to take this into account. You can ignore it"
] | 1,615,540,920,000 | 1,616,479,696,000 | 1,615,892,482,000 | CONTRIBUTOR | null | see: https://github.com/huggingface/datasets/issues/2031
What I did:
- replace root.clear with elem.clear
- remove lines to get root element
- $ make style
- $ make test
- some tests required some pip packages, I installed them.
test results on origin/master and my branch are same. I think it's not related... | {
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https://api.github.com/repos/huggingface/datasets/issues/2036 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2036/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2036/comments | https://api.github.com/repos/huggingface/datasets/issues/2036/events | https://github.com/huggingface/datasets/issues/2036 | 829,909,258 | MDU6SXNzdWU4Mjk5MDkyNTg= | 2,036 | Cannot load wikitext | {
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"Solved!"
] | 1,615,540,179,000 | 1,615,797,902,000 | 1,615,797,884,000 | NONE | null | when I execute these codes
```
>>> from datasets import load_dataset
>>> test_dataset = load_dataset("wikitext")
```
I got an error,any help?
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/xxx/anaconda3/envs/transformer/lib/python3.7/site-packages/datasets/load.p... | {
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"Dear @lhoestq for wikipedia dataset I also get the same error, I greatly appreciate if you could have a look into this dataset as well. Below please find the command to reproduce the error:\r\n\r\n```\r\ndataset = load_dataset(\"wikipedia\", \"20200501.bg\")\r\nprint(dataset)\r\n```\r\n\r\nYour library is my only ... | 1,615,492,494,000 | 1,615,906,417,000 | null | NONE | null | Hi
I am trying to download the data as below:
```
from datasets import load_dataset
dataset = load_dataset("wiki40b", "cs")
print(dataset)
```
I am getting this error. @lhoestq I will be grateful if you could assist me with this error. For almost all languages except english I am getting this error.
I rea... | {
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"following_url"... | [] | 1,615,478,880,000 | 1,615,485,492,000 | 1,615,485,492,000 | MEMBER | null | The `sacrebleu` metric seem to only work for sacrecleu>=1.4.12
For example using sacrebleu==1.2.10, an error is raised (from metric/sacrebleu/sacrebleu.py):
```python
def _compute(
self,
predictions,
references,
smooth_method="exp",
smooth_value=None,
force... | {
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https://api.github.com/repos/huggingface/datasets/issues/2032 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2032/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2032/comments | https://api.github.com/repos/huggingface/datasets/issues/2032/events | https://github.com/huggingface/datasets/issues/2032 | 829,250,912 | MDU6SXNzdWU4MjkyNTA5MTI= | 2,032 | Use Arrow filtering instead of writing a new arrow file for Dataset.filter | {
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"following_url"... | [] | 1,615,475,930,000 | 1,615,483,257,000 | null | MEMBER | null | Currently the filter method reads the dataset batch by batch to write a new, filtered, arrow file on disk. Therefore all the reading + writing can take some time.
Using a mask directly on the arrow table doesn't do any read or write operation therefore it's significantly quicker.
I think there are two cases:
- i... | {
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"Hi @miyamonz \r\nThanks for investigating this issue, good job !\r\nIt would be awesome to integrate your fix in the library, could you open a pull request ?",
"OK! I'll send it later."
] | 1,615,467,084,000 | 1,616,402,032,000 | 1,616,402,032,000 | CONTRIBUTOR | null | I tried downloading Japanese wikipedia, but it always failed because of out of memory maybe.
I found that the generator function that extracts XML data in wikipedia.py doesn't release memory in the loop.
https://github.com/huggingface/datasets/blob/13a5b7db992ad5cf77895e4c0f76595314390418/datasets/wikipedia/wikip... | {
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https://api.github.com/repos/huggingface/datasets/issues/2030 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2030/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2030/comments | https://api.github.com/repos/huggingface/datasets/issues/2030/events | https://github.com/huggingface/datasets/pull/2030 | 829,110,803 | MDExOlB1bGxSZXF1ZXN0NTkwODI4NzQ4 | 2,030 | Implement Dataset from text | {
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"I am wondering why only one test of \"keep_in_memory=True\" fails, when there are many other tests that test the same and it happens only in pyarrow_1..."
] | 1,615,466,090,000 | 1,616,074,169,000 | 1,616,074,169,000 | MEMBER | null | Implement `Dataset.from_text`.
Analogue to #1943, #1946. | {
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"In your code `dataset2` doesn't contain the \"embeddings\" column, since it is created from the pandas DataFrame with columns \"text\" and \"label\".\r\n\r\nTherefore when you call `dataset2[embeddings_name]`, you get a `KeyError`.\r\n\r\nIf you want the \"embeddings\" column back, you can create `dataset2` with\r... | 1,615,464,973,000 | 1,615,508,469,000 | 1,615,508,469,000 | NONE | null | I've recently been testing out RAG and DPR embeddings, and I've run into an issue that is not apparent in the documentation.
The basic steps are:
1. Create a dataset (dataset1)
2. Create an embeddings column using DPR
3. Add a faiss index to the dataset
4. Save faiss index to a file
5. Create a new dataset (d... | {
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https://api.github.com/repos/huggingface/datasets/issues/2028 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2028/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2028/comments | https://api.github.com/repos/huggingface/datasets/issues/2028/events | https://github.com/huggingface/datasets/pull/2028 | 828,721,393 | MDExOlB1bGxSZXF1ZXN0NTkwNDk1NzEx | 2,028 | Adding PersiNLU reading-comprehension | {
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"@lhoestq I think I have addressed all your comments. ",
"Thanks! @lhoestq Let me know if you want me to address anything to get this merged. ",
"It's all good thanks ;)\r\nmerging"
] | 1,615,437,673,000 | 1,615,801,197,000 | 1,615,801,197,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2027 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2027/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2027/comments | https://api.github.com/repos/huggingface/datasets/issues/2027/events | https://github.com/huggingface/datasets/pull/2027 | 828,490,444 | MDExOlB1bGxSZXF1ZXN0NTkwMjkzNDA1 | 2,027 | Update format columns in Dataset.rename_columns | {
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https://api.github.com/repos/huggingface/datasets/issues/2026 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2026/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2026/comments | https://api.github.com/repos/huggingface/datasets/issues/2026/events | https://github.com/huggingface/datasets/issues/2026 | 828,194,467 | MDU6SXNzdWU4MjgxOTQ0Njc= | 2,026 | KeyError on using map after renaming a column | {
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"Hi,\r\n\r\nActually, the error occurs due to these two lines:\r\n```python\r\nraw_dataset.set_format('torch',columns=['img','label'])\r\nraw_dataset = raw_dataset.rename_column('img','image')\r\n```\r\n`Dataset.rename_column` doesn't update the `_format_columns` attribute, previously defined by `Dataset.set_format... | 1,615,402,457,000 | 1,615,473,574,000 | 1,615,473,520,000 | CONTRIBUTOR | null | Hi,
I'm trying to use `cifar10` dataset. I want to rename the `img` feature to `image` in order to make it consistent with `mnist`, which I'm also planning to use. By doing this, I was trying to avoid modifying `prepare_train_features` function.
Here is what I try:
```python
transform = Compose([ToPILImage(),... | {
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https://api.github.com/repos/huggingface/datasets/issues/2025 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2025/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2025/comments | https://api.github.com/repos/huggingface/datasets/issues/2025/events | https://github.com/huggingface/datasets/pull/2025 | 828,047,476 | MDExOlB1bGxSZXF1ZXN0NTg5ODk2NjMz | 2,025 | [Refactor] Use in-memory/memory-mapped/concatenation tables in Dataset | {
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"There is one more thing I would love to see. Let's say we iteratively keep updating a data source that loaded from **load_dataset** or **load_from_disk**. Now we need to save it to the same location by overriding the previous file inorder to save the disk space. At the moment **save_to_disk** can not assign a name... | 1,615,395,647,000 | 1,617,115,613,000 | 1,616,777,519,000 | MEMBER | null | ## Intro
Currently there is one assumption that we need to change: a dataset is either fully in memory (dataset._data_files is empty), or the dataset can be reloaded from disk with memory mapping (using the dataset._data_files).
This assumption is used for pickling for example:
- in-memory dataset can just be pick... | {
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https://api.github.com/repos/huggingface/datasets/issues/2024 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2024/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2024/comments | https://api.github.com/repos/huggingface/datasets/issues/2024/events | https://github.com/huggingface/datasets/pull/2024 | 827,842,962 | MDExOlB1bGxSZXF1ZXN0NTg5NzEzNDAy | 2,024 | Remove print statement from mnist.py | {
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"Thanks for noticing !\r\n#2020 fixed this earlier today though ^^'\r\n\r\nClosing this one"
] | 1,615,387,198,000 | 1,615,485,832,000 | 1,615,485,831,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2023 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2023/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2023/comments | https://api.github.com/repos/huggingface/datasets/issues/2023/events | https://github.com/huggingface/datasets/pull/2023 | 827,819,608 | MDExOlB1bGxSZXF1ZXN0NTg5NjkyNDU2 | 2,023 | Add Romanian to XQuAD | {
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"Hi ! Thanks for updating XQUAD :)\r\n\r\nThe slow test is failing though since there's no dummy data nor metadata in dataset_infos.json for the romanian configuration.\r\n\r\nCould you please generate the dummy data with\r\n```\r\ndatasets-cli dummy_data ./datasets/xquad --auto_generate --json_field data\r\n```\r\... | 1,615,386,272,000 | 1,615,802,897,000 | 1,615,802,897,000 | CONTRIBUTOR | null | On Jan 18, XQuAD was updated with a new Romanian validation file ([xquad commit link](https://github.com/deepmind/xquad/commit/60cac411649156efb6aab9dd4c9cde787a2c0345))
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https://api.github.com/repos/huggingface/datasets/issues/2022 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2022/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2022/comments | https://api.github.com/repos/huggingface/datasets/issues/2022/events | https://github.com/huggingface/datasets/issues/2022 | 827,435,033 | MDU6SXNzdWU4Mjc0MzUwMzM= | 2,022 | ValueError when rename_column on splitted dataset | {
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"Hi,\r\n\r\nThis is a bug so thanks for reporting it. `Dataset.__setstate__` is the problem, which is called when `Dataset.rename_column` tries to copy the dataset with `copy.deepcopy(self)`. This only happens if the `split` arg in `load_dataset` was defined as `ReadInstruction`.\r\n\r\nTo overcome this issue, use... | 1,615,369,238,000 | 1,615,903,568,000 | 1,615,903,505,000 | NONE | null | Hi there,
I am loading `.tsv` file via `load_dataset` and subsequently split the rows into training and test set via the `ReadInstruction` API like so:
```python
split = {
'train': ReadInstruction('train', to=90, unit='%'),
'test': ReadInstruction('train', from_=-10, unit='%')
}
dataset = load_datase... | {
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"Hi,\r\n\r\nCan you give us a minimal reproducible example? This [part](https://huggingface.co/docs/datasets/master/processing.html#controling-the-cache-behavior) of the docs explains how to control caching."
] | 1,615,344,514,000 | 1,615,630,061,000 | 1,615,630,061,000 | NONE | null | dataset_info.json file saved after using save_to_disk gets corrupted as follows.
Is there a way to disable the cache that will save to /tmp/huggiface/datastes ?
I have a feeling there is a seri... | {
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https://api.github.com/repos/huggingface/datasets/issues/2020 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2020/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2020/comments | https://api.github.com/repos/huggingface/datasets/issues/2020/events | https://github.com/huggingface/datasets/pull/2020 | 826,961,126 | MDExOlB1bGxSZXF1ZXN0NTg4OTE3MjYx | 2,020 | Remove unnecessary docstart check in conll-like datasets | {
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"following_url"... | [] | 1,615,342,816,000 | 1,615,469,617,000 | 1,615,469,617,000 | CONTRIBUTOR | null | Related to this PR: #1998
Additionally, this PR adds the docstart note to the conll2002 dataset card ([link](https://raw.githubusercontent.com/teropa/nlp/master/resources/corpora/conll2002/ned.train) to the raw data with `DOCSTART` lines).
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"@lhoestq Maybe a script or even a test in `test_dataset_common.py` that verifies that a dataset script meets some set of quality standards (print calls and todos from the dataset script template are not present, etc.) could be added?",
"Yes definitely !"
] | 1,615,323,574,000 | 1,615,543,741,000 | 1,615,479,259,000 | CONTRIBUTOR | null | Replaces `print(...)` in the dataset scripts with the library logger. | {
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"Link to the card: https://github.com/mcmillanmajora/datasets/blob/md-gender-card/datasets/md_gender_bias/README.md",
"dataset card* @sgugger :p ",
"Ahah that's what I wanted to say @lhoestq, thanks for fixing. Not used to review the Datasets side ;-)"
] | 1,615,316,240,000 | 1,615,570,260,000 | 1,615,570,260,000 | CONTRIBUTOR | null | I updated the descriptions of the datasets as they appear in the HF repo and the descriptions of the source datasets according to what I could find from the paper and the references. I'm still a little unclear about some of the fields of the different configs, and there was little info on the word list and name list. I... | {
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I am creating this draft PR to work on add features similar to [TF datasets](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/core/features). I'll be starting with `Tensor` and `FeatureConnector` classes, and build upon them to add other features as well. This is a work in progress. | {
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Fix #2010 | {
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not super convinced this is better, and while I usually fight against kwargs here it seems to me that it better conveys the relationship to the `_split_generator` method. | {
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"What's the issue exactly ?\r\n\r\nGiven an `upstream` remote repository with url `https://github.com/huggingface/datasets.git`, you can totally rebase from `upstream/master`.\r\n\r\nIt's mentioned at the beginning how to add the `upstream` remote repository\r\n\r\nhttps://github.com/huggingface/datasets/blob/987df... | 1,615,283,335,000 | 1,615,289,611,000 | 1,615,289,611,000 | CONTRIBUTOR | null | Feels like the documentation on adding a new dataset is outdated?
https://github.com/huggingface/datasets/blob/987df6b4e9e20fc0c92bc9df48137d170756fd7b/ADD_NEW_DATASET.md#L49-L54
There is no upstream branch on remote. | {
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"following_url"... | [] | 1,615,282,808,000 | 1,615,485,652,000 | 1,615,485,652,000 | CONTRIBUTOR | null | This PR adds a Romanian sentiment analysis dataset. This PR also closes pending PR #1529.
I had to add an `original_id` feature because the dataset files have repeated IDs. I can remove them if needed. I have also added `id` which is unique.
Let me know in case of any issues. | {
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"I'm not able to reproduce on my side.\r\nCan you provide the full stacktrace please ?\r\nWhat version of `python` and `dill` do you have ? Which OS are you using ?",
"```\r\nco_filename = '<ipython-input-2-e0383a102aae>', returned_obj = [0]\r\n ... | 1,615,280,498,000 | 1,615,298,763,000 | 1,615,298,763,000 | CONTRIBUTOR | null | I'm following the CI setup as described in
https://github.com/huggingface/datasets/blob/8eee4fa9e133fe873a7993ba746d32ca2b687551/.circleci/config.yml#L16-L19
in a new conda environment, at commit https://github.com/huggingface/datasets/commit/4de6dbf84e93dad97e1000120d6628c88954e5d4
and getting
```
FAILED... | {
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"Hi @theo-m !\r\n\r\nA few lines above this line, you'll find that the `_split_generators` method returns a list of `SplitGenerator`s objects:\r\n\r\n```python\r\ndatasets.SplitGenerator(\r\n name=datasets.Split.VALIDATION,\r\n # These kwargs will be passed to _generate_examples\r\n gen_kwargs={\r\n ... | 1,615,279,331,000 | 1,615,561,294,000 | 1,615,561,294,000 | CONTRIBUTOR | null | https://github.com/huggingface/datasets/blob/2ac9a0d24a091989f869af55f9f6411b37ff5188/templates/new_dataset_script.py#L156-L158
Looking at the template, I find this documentation line to be confusing, the method parameters don't include the `gen_kwargs` so I'm unclear where they're coming from.
Happy to push a PR... | {
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"What do yo think of the documentation btw ?\r\nWhat parts would you like to see improved ?",
"I like how concise and straightforward the docs are.\r\n\r\nFew things that would further improve the docs IMO:\r\n* the usage example of `Dataset.formatted_as` in https://huggingface.co/docs/datasets/master/processing.... | 1,615,253,968,000 | 1,615,833,769,000 | 1,615,285,292,000 | CONTRIBUTOR | null | This PR:
* fixes various typos/grammer I came across while reading the docs
* adds the "Install with conda" installation instructions
Closes #1959 | {
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"So maybe a summary here: \r\nIf I could fit a large model with batch_size = X into memory, is there a way I could train this model for huge datasets with keeping setting the same? thanks ",
"The `datastets` library doesn't load datasets into memory. Therefore you can load a dataset that is terabytes big without ... | 1,615,206,926,000 | 1,628,100,145,000 | 1,628,100,145,000 | NONE | null | Hi
I am running this example from transformers library version 4.3.3:
(Here is the full documentation https://github.com/huggingface/transformers/issues/8771 but the running command should work out of the box)
USE_TF=0 deepspeed run_seq2seq.py --model_name_or_path google/mt5-base --dataset_name wmt16 --dataset_... | {
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"following_url"... | [] | 1,615,201,988,000 | 1,615,202,915,000 | 1,615,202,914,000 | MEMBER | null | The benchmarks runs are [failing](https://github.com/huggingface/datasets/runs/2055534629?check_suite_focus=true) because of
```
ERROR: 'dvc.lock' is git-ignored.
```
I removed the dvc.lock file from the gitignore to fix that | {
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"Adding to the previous information, I think `torch.utils.data.DataLoader` is doing some conversion. \r\nWhat I tried:\r\n```python\r\ntrain_dataset = load_dataset('mnist')\r\n```\r\nI don't use any `map` or `set_format` or any `transform`. I use this directly, and try to load batches using the `DataLoader` with ba... | 1,615,189,091,000 | 1,615,312,693,000 | 1,615,312,693,000 | CONTRIBUTOR | null | Hi
I am trying to use `torchvision.transforms` to handle the transformation of the image data in the `mnist` dataset. Assume I have a `transform` variable which contains the `torchvision.transforms` object.
A snippet of what I am trying to do:
```python
def prepare_features(examples):
images = []
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"@lhoestq all the changes requested are implemented. Thank you for your time and feedback :)"
] | 1,615,165,592,000 | 1,615,977,800,000 | 1,615,977,800,000 | CONTRIBUTOR | null | Add LaRoSeDa to huggingface datasets. | {
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"This is expected to show this message to the user via stdout.\r\nThis way the users see it directly and can cancel the downloading if they want to.\r\nCould you elaborate why it would be better to have it in stderr instead of stdout ?",
"@lhoestq, sorry for the late reply\r\n\r\nI completely understand why you d... | 1,615,154,974,000 | 1,615,830,467,000 | null | NONE | null | In this code segment, we can see some messages are being printed to the `stdout`.
https://github.com/huggingface/datasets/blob/7e60bb509b595e8edc60a87f32b2bacfc065d607/src/datasets/builder.py#L545-L554
According to the comment, it is done intentionally, but I don't really understand why don't we log it with a higher ... | {
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"@lhoestq Thank you for all the feedback. I've added the suggested changes in my last commit."
] | 1,615,134,137,000 | 1,616,147,526,000 | 1,616,147,526,000 | CONTRIBUTOR | null | Add MOROCO to huggingface datasets. | {
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all samples has its evidence document (i.e. wikipedia page id) for prediction.
For example, a sample in ELI5 dataset has the format including provenance (=evidence document) like this
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"Hi @itsLuisa !\r\n\r\nCould you give us more information about the error you're getting, please?\r\nA copy-paste of the Traceback would be nice to get a better understanding of what is wrong :) ",
"Hello @SBrandeis , this is it:\r\n```\r\nTraceback (most recent call last):\r\n File \"C:\\Users\\Luisa\\AppData\\... | 1,615,118,128,000 | 1,615,293,777,000 | 1,615,293,777,000 | NONE | null | Hi everyone,
Can anyone help me with why the dataset loading script below raises a Windows Permission Error? I stuck quite closely to https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py , only I want to load the data from three local three-column tsv-files (id\ttokens\tpos_tags\n). I am... | {
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"Hi @lhoestq,\r\n\r\nI have added the changes from the review."
] | 1,615,066,617,000 | 1,615,283,531,000 | 1,615,283,531,000 | CONTRIBUTOR | null | This PR adds [FashionMNIST](https://github.com/zalandoresearch/fashion-mnist) dataset. | {
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"Nice catch! Yes I didn't check the actual data, instead I was just looking for the `if line.startswith(\"-DOCSTART-\")` pattern."
] | 1,615,057,709,000 | 1,615,429,207,000 | 1,615,429,207,000 | CONTRIBUTOR | null | Closes #1983 | {
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"Thanks for reporting! We'll fix that as soon as possible",
"Actually soundfile is not a dependency of this dataset.\r\nThe error comes from a bug that was fixed in this commit: https://github.com/huggingface/datasets/pull/1767/commits/c304e63629f4453367de2fd42883a78768055532\r\nBasically the library used to cons... | 1,615,010,120,000 | 1,615,288,345,000 | null | NONE | null | Navigate to https://huggingface.co/datasets/viewer/?dataset=arabic_speech_corpus
Error:
```
ImportError: To be able to use this dataset, you need to install the following dependencies['soundfile'] using 'pip install soundfile' for instance'
Traceback:
File "/home/sasha/.local/share/virtualenvs/lib-ogGKnCK_/lib/p... | {
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"cc @lhoestq @vrindaprabhu",
"Failing `run (push)` is unrelated -> merging",
"Thanks for fixing this, it was affecting my runs for https://github.com/huggingface/transformers/pull/10581/",
"I am seeing this very late! Sorry for the blunder everyone! :("
] | 1,614,933,771,000 | 1,625,034,353,000 | 1,614,934,739,000 | MEMBER | null | When playing around with timit I noticed that only the first sample is used for all indices. I corrected this typo so that the dataset is correctly loaded. | {
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"@lhoestq I really appreciate if you could help me providiing processed datasets, I do not really have access to enough resources to run the apache-beam and need to run the codes on these datasets. Only en/de/fr currently works, but I need all the languages more or less. thanks ",
"Hi @dorost1234, I think I can ... | 1,614,933,108,000 | 1,615,495,581,000 | null | NONE | null | Hi
I am trying to run a code with wikipedia of config 20200501.es, getting:
Traceback (most recent call last):
File "run_mlm_t5.py", line 608, in <module>
main()
File "run_mlm_t5.py", line 359, in main
datasets = load_dataset(data_args.dataset_name, data_args.dataset_config_name)
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"Hi ! That looks like a bug, can you provide some code so that we can reproduce ?\r\nIt's not supposed to update the original dataset",
"Hi, I experimented with RAG. \r\n\r\nActually, you can run the [use_own_knowldge_dataset.py](https://github.com/shamanez/transformers/blob/rag-end-to-end-retrieval/examples/rese... | 1,614,921,950,000 | 1,616,385,950,000 | 1,616,385,950,000 | NONE | null | I am using the latest datasets library. In my work, I first use **load_from_disk** to load a data set that contains 3.8Gb information. Then during my training process, I update that dataset object and add new elements and save it in a different place.
When I save the dataset with **save_to_disk**, the original da... | {
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"Hi @hwijeen, you might want to look at issues #1796 and #1949. I think it could be something related to the I/O operations being performed.",
"I see that many people are experiencing the same issue. Is this problem considered an \"official\" bug that is worth a closer look? @lhoestq",
"Yes this is an official ... | 1,614,910,202,000 | 1,626,689,109,000 | null | NONE | null | Hi, thank you for the great library.
I've been using datasets to pretrain language models, and it often involves datasets as large as ~70G.
My data preparation step is roughly two steps: `load_dataset` which splits corpora into a table of sentences, and `map` converts a sentence into a list of integers, using a tok... | {
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"Thanks for the reviews! A note that I have addressed the comments, and waiting for a further review."
] | 1,614,896,383,000 | 1,615,977,459,000 | 1,615,977,459,000 | CONTRIBUTOR | null | Adding the conllpp dataset, is a revision from https://github.com/huggingface/datasets/pull/1910. | {
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"Do you think this is trying to bring the dataset into memory and if I can avoid it to save on memory so it only brings a batch into memory? @lhoestq thank you",
"It's not trying to bring the dataset into memory.\r\n\r\nActually, it's trying to memory map the dataset file, which is different. It allows to load l... | 1,614,882,118,000 | 1,628,100,265,000 | 1,628,100,265,000 | NONE | null | Hi,
I am trying to run a code with a wikipedia dataset, here is the command to reproduce the error. You can find the codes for run_mlm.py in huggingface repo here: https://github.com/huggingface/transformers/blob/v4.3.2/examples/language-modeling/run_mlm.py
```
python run_mlm.py --model_name_or_path bert-base-multi... | {
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"It seems that I get parsing errors for various fields in my data. For example now I get this:\r\n```\r\n File \"../../../models/tr-4.3.2/run_puppets.py\", line 523, in <module>\r\n main()\r\n File \"../../../models/tr-4.3.2/run_puppets.py\", line 249, in main\r\n datasets = load_dataset(\"csv\", data_files... | 1,614,877,613,000 | 1,615,455,855,000 | null | NONE | null | Hi, I'm using a dataset with two labels "nurse" and "not nurse". For whatever reason (that I don't understand), I get an error that I think comes from the datasets package (using csv). Everything works fine if the labels are "nurse" and "surgeon".
This is the trace I get:
```
File "../../../models/tr-4.3.2/run_... | {
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"Hi ! Yes it's possible to use image data. There are already a few of them available (MNIST, CIFAR..)"
] | 1,614,877,460,000 | 1,628,100,323,000 | 1,628,100,323,000 | NONE | null | Hi!
At the README.MD, you say: "efficient data pre-processing: simple, fast and reproducible data pre-processing for the above public datasets as well as your own local datasets in CSV/JSON/text. "
But here:
https://github.com/huggingface/datasets/blob/master/templates/new_dataset_script.py#L82-L117
You menti... | {
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"following_url"... | [] | 1,614,876,385,000 | 1,614,876,385,000 | null | MEMBER | null | While testing the hotfix, I tried a random other wmt release and found wmt15 to be broken:
```
python -c 'from datasets import load_dataset; load_dataset("wmt15", "de-en")'
Downloading: 2.91kB [00:00, 818kB/s]
Downloading: 3.02kB [00:00, 897kB/s]
Downloading: 41.1kB [00:00, 19.1MB/s]
Downloading and preparing da... | {
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"caching issue, seems to work again.."
] | 1,614,867,535,000 | 1,614,868,267,000 | 1,614,868,267,000 | NONE | null | ~\.cache\huggingface\modules\datasets_modules\datasets\wmt14\43e717d978d2261502b0194999583acb874ba73b0f4aed0ada2889d1bb00f36e\wmt_utils.py in _split_generators(self, dl_manager)
758 # Extract manually downloaded files.
759 manual_files = dl_manager.extract(manual_paths_dict)
--> 760 e... | {
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"@lhoestq, are the tests OK? Some other cases I missed? Do you agree with this approach?",
"I just tested this and it works like a charm :) \r\n\r\nHowever tokenizing and then setting the format to \"torch\" to feed the tokens into a model doesn't seem to work anymore, since the pytorch tensors have the int32/int... | 1,614,867,143,000 | 1,616,414,680,000 | 1,615,887,840,000 | MEMBER | null | Optimize int precision to reduce dataset file size.
Close #1973, close #1825, close #861. | {
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"following_url"... | [] | 1,614,840,402,000 | 1,614,840,402,000 | null | MEMBER | null | As requested in #1981, we need tests for WMT datasets, using dummy data. | {
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"Hi,\r\n\r\nif you inspect the raw data, you can find there are 946 occurrences of `-DOCSTART- -X- -X- O` in the train split and `14041 + 946 = 14987`, which is exactly the number of sentences the authors report. `-DOCSTART-` is a special line that acts as a boundary between two different documents and is filtered ... | 1,614,832,894,000 | 1,615,220,665,000 | null | NONE | null | Thanks for the dataset sharing! But when I use conll-2003, I meet some questions.
The statistics of conll-2003 in this repo is :
\#train 14041 \#dev 3250 \#test 3453
While the official statistics is:
\#train 14987 \#dev 3466 \#test 3684
Wish for your reply~ | {
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"I validated that this fixed the problem, thank you, @albertvillanova!\r\n",
"still facing the same issue or similar:\r\nfrom datasets import load_dataset\r\nwtm14_test = load_dataset('wmt14',\"de-en\",cache_dir='./datasets')\r\n\r\n~\\.cache\\huggingface\\modules\\datasets_modules\\datasets\\wmt14\\43e717d978d22... | 1,614,802,611,000 | 1,614,876,364,000 | 1,614,811,716,000 | MEMBER | null | Fix #1981 | {
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"@stas00 Mea culpa... May I fix this tomorrow morning?",
"yes, of course, I reverted to the version before that and it works ;)\r\n\r\nbut since a new release was just made you will probably need to make a hotfix.\r\n\r\nand add the wmt to the tests?",
"Sure, I will implement a regression test!",
"@stas00 it ... | 1,614,799,299,000 | 1,614,867,407,000 | 1,614,811,716,000 | MEMBER | null | on master:
```
python -c 'from datasets import load_dataset; load_dataset("wmt14", "de-en")'
Downloading and preparing dataset wmt14/de-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /home/stas/.cache/huggingface/datasets/wmt14/de-en/1.0.0/43e717d978d226150... | {
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"Nice thanks for the change !\r\nThis looks all good to me\r\n\r\nBefore we merge can you just update the dataset_infos.json file of drop ? You can do it by running\r\n```\r\ndatasets-cli test ./datasets/drop --all_configs --save_infos --ignore_verifications\r\n```",
"Done!"
] | 1,614,791,587,000 | 1,615,807,646,000 | 1,615,807,646,000 | CONTRIBUTOR | null | Hello all,
I propose this change to the DROP loading script so that all answers are loaded no matter their type. Currently, only "span" answers are loaded, which excludes a significant amount of answers from drop (i.e. "number" and "date").
I updated the script with the version I use for my work. However, I could... | {
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"Thanks !\r\nNow to fix the CI the only thing left is to add a dummy `test-task-tc-template.out` file inside the `dummy_data.zip` at `./datasets/sem_eval_2020_task_11/dummy/1.1.0`\r\nIt must contain the labels template for each dummy article of the test set included in `dummy_data.zip`\r\n\r\nAfter that we should b... | 1,614,767,672,000 | 1,615,633,180,000 | 1,615,554,650,000 | CONTRIBUTOR | null | … dataset
- `article_id` is needed to create the submission file for the task at https://propaganda.qcri.org/semeval2020-task11/
- The `technique classification` task provides the span indices in a template for the test set that is necessary to complete the task. This PR implements processing of that template for t... | {
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"@lhoestq thank you very much for the quick review and useful comments! \r\n\r\nI have tried to address them all, and a few comments that you left for ro_sts I have applied to the ro_sts_parallel as well (in read-me: fixed source_datasets, links to homepage, repository, leaderboard, thanks to me message, in ro_sts_... | 1,614,766,133,000 | 1,614,938,414,000 | 1,614,936,835,000 | CONTRIBUTOR | null | Adding [RO-STS](https://github.com/dumitrescustefan/RO-STS) dataset | {
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"I sometimes also get this error with other languages of the same dataset:\r\n\r\n File \"/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/arrow_reader.py\", line 322, in read_table\r\n stream = stream_from(filename)\r\n File \"pyarrow/io.pxi\", line 782, in pyarrow.... | 1,614,712,888,000 | 1,614,766,660,000 | null | NONE | null | Hi
I am trying to run run_mlm.py code [1] of huggingface with following "wikipedia"/ "20200501.aa" dataset:
`python run_mlm.py --model_name_or_path bert-base-multilingual-cased --dataset_name wikipedia --dataset_config_name 20200501.aa --do_train --do_eval --output_dir /tmp/test-mlm --max_seq_l... | {
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"following_url"... | [] | 1,614,706,019,000 | 1,614,786,331,000 | 1,614,786,330,000 | MEMBER | null | Add the HF_DATASETS_OFFLINE environment variable for users who want to use `datasets` offline without having to wait for the network timeouts/retries to happen. This was requested in https://github.com/huggingface/datasets/issues/1939
cc @stas00 | {
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"following_url"... | [] | 1,614,698,690,000 | 1,614,854,652,000 | 1,614,854,568,000 | CONTRIBUTOR | null | Enables docs navigation with left/right arrow keys. It can be useful for the ones who navigate with keyboard a lot.
More info : https://github.com/sphinx-doc/sphinx/pull/2064
You can try here : https://29353-250213286-gh.circle-artifacts.com/0/docs/_build/html/index.html | {
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"Echo'ing this observation: I have a few datasets in the neighborhood of 2GB CSVs uncompressed, and when I use something like `Dataset.save_to_disk()` it's ~18GB on disk.\r\n\r\nIf this is unexpected behavior, would be happy to help run debugging as needed.",
"Thanks @ioana-blue for pointing out this problem (and... | 1,614,695,753,000 | 1,617,113,039,000 | 1,615,887,840,000 | NONE | null | I'm running several training jobs (around 10) with a relatively large dataset (3M samples). The datasets cache reached 178G and it seems really large. What is it stored in there and why is it so large? I don't think I noticed this problem before and seems to be related to the new version of the datasets library. Any in... | {
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"Hi ! `rename_column` has been added recently and will be available in the next release"
] | 1,614,672,109,000 | 1,614,690,483,000 | null | NONE | null | 'Dataset' object has no attribute 'rename_column' | {
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"Oh nice thanks for adding the context manager ! All the streams and RecordBatchWriter will be properly closed now. Hopefully this gives a better experience on windows on which it's super important to close stuff.\r\n\r\nNot sure about the error, it looks like a process crashed silently.\r\nLet me take a look",
"... | 1,614,669,154,000 | 1,615,394,217,000 | 1,615,394,217,000 | MEMBER | null | Current implementation of ArrowWriter does not properly release the `stream` resource (by closing it) if its `finalize()` method is not called and/or an Exception is raised before/during the call to its `finalize()` method.
Therefore, ArrowWriter should be used as a context manager that properly closes its `stream` ... | {
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"following_url"... | [] | 1,614,648,178,000 | 1,614,655,146,000 | 1,614,650,493,000 | MEMBER | null | This updates the code and metadata to use the updated `gem_mlsum_bad_ids_fixed.json` file provided by @juand-r
cc @sebastianGehrmann | {
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"Thanks for the change, merging now !"
] | 1,614,622,919,000 | 1,614,705,900,000 | 1,614,705,900,000 | CONTRIBUTOR | null | This PR adds the Turkish News Categories Dataset (270K - Lite Version) dataset which is a text classification dataset by me, @basakbuluz and @serdarakyol.
This dataset contains the same news from the current [interpress_news_category_tr dataset](https://huggingface.co/datasets/interpress_news_category_tr) but contains... | {
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"Since the failure was originally intermittent, there is no 100% telling that the problem is gone. \r\nBut if my artificial race condition setup https://github.com/huggingface/datasets/issues/1942#issuecomment-787124529 is to be the litmus test then the problem has been fixed, as with this PR branch that particular... | 1,614,620,718,000 | 1,614,690,345,000 | 1,614,690,344,000 | MEMBER | null | As noticed in #1942 , there's a issue with locks if you run multiple separate evaluation experiments in a multiprocessed setup.
Indeed there is a time span in Metric._finalize() where the process 0 loses its lock before re-acquiring it. This is bad since the lock of the process 0 tells the other process that the cor... | {
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"Hi !\r\nAs far as I know not all faiss indexes can be computed in parallel and then merged. \r\nFor example [here](https://github.com/facebookresearch/faiss/wiki/Special-operations-on-indexes#splitting-and-merging-indexes) is is mentioned that only IndexIVF indexes can be merged.\r\nMoreover faiss already works us... | 1,614,602,854,000 | 1,614,886,856,000 | 1,614,886,842,000 | NONE | null | I am thinking of making the **add_faiss_index** process faster. What if we run the add_faiss_index process on separate dataset shards and then combine them before (dataset.concatenate) saving the faiss.index file ?
I feel theoretically this will reduce the accuracy of retrieval since it affects the indexing process... | {
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"Hi !\r\n\r\nTo fix 1, an you try to run this code ?\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nload_dataset(\"squad\", download_mode=\"force_redownload\")\r\n```\r\nMaybe the file your downloaded was corrupted, in this case redownloading this way should fix your issue 1.\r\n\r\nRegarding your 2nd poi... | 1,614,588,091,000 | 1,614,870,566,000 | null | NONE | null | ### 1 When I try to train lxmert,and follow the code in README that --dataset name:
```shell
python examples/question-answering/run_qa.py --model_name_or_path unc-nlp/lxmert-base-uncased --dataset_name squad --do_train --do_eval --per_device_train_batch_size 12 --learning_rate 3e-5 --num_train_epochs 2 --max_seq_len... | {
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"Hi ! The labels -1 correspond to the examples without gold labels in the original snli dataset.\r\nFeel free to remove these examples if you don't need them by using\r\n```python\r\ndata = data.filter(lambda x: x[\"label\"] != -1)\r\n```"
] | 1,614,540,980,000 | 1,614,600,089,000 | null | NONE | null | Hi
There is label of -1 in train set of SNLI dataset, please find the code below:
```
import numpy as np
import datasets
data = datasets.load_dataset("snli")["train"]
labels = []
for d in data:
labels.append(d["label"])
print(np.unique(labels))
```
and results:
`[-1 0 1 2]`
version of datas... | {
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"@lhoestq Re-added the arg. The ConnectionError in CI seems unrelated to this PR (the same test fails on master as well).",
"Thanks !\r\nI'm re-running the CI, maybe this was an issue with circleCI",
"Looks all good now, merged :)"
] | 1,614,480,427,000 | 1,615,429,097,000 | 1,614,789,470,000 | CONTRIBUTOR | null | Noticed some args in the codebase are not used, so managed to find all such occurrences with Pylance and fix them. | {
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"following_url"... | [] | 1,614,478,109,000 | 1,614,854,333,000 | 1,614,854,333,000 | CONTRIBUTOR | null | Related to #1934—Add the Stanford Sentiment Treebank dataset. | {
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"@lhoestq Added a test. If you can come up with a better stateful callable, I'm all ears 😄. ",
"Sorry I said earlier that it was good to have it inside the loop, my mistake !",
"@lhoestq Okay, did some refactoring and now the \"cache\" part comes before the for loop. Thanks for the guidance.\r\n\r\nThink this... | 1,614,475,745,000 | 1,616,513,209,000 | 1,616,513,209,000 | CONTRIBUTOR | null | Removes the "test type" section in Dataset.map which would modify the state of the stateful function. Now, the return type of the map function is inferred after processing the first example.
Fixes #1940
@lhoestq Not very happy with the usage of `nonlocal`. Would like to hear your opinion on this. | {
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"Hi,\r\n\r\ntry `skiprows` instead. This part is not properly documented in the docs it seems.\r\n\r\n@lhoestq I'll fix this as part of a bigger PR that fixes typos in the docs."
] | 1,614,468,774,000 | 1,615,285,292,000 | 1,615,285,292,000 | NONE | null | Hello everyone,
I'm quite new to Git so sorry in advance if I'm breaking some ground rules of issues posting... :/
I tried to use the load_dataset function, from Huggingface datasets library, on a csv file using the skip_rows argument described on Huggingface page to skip the first row containing column names
`t... | {
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"Never mind, I ran it again and it worked this time. Strange."
] | 1,614,462,476,000 | 1,614,462,616,000 | 1,614,462,616,000 | NONE | null | I did
```
from datasets import load_dataset
dataset = load_dataset("xsum")
```
This returns
`ConnectionError: Couldn't reach http://bollin.inf.ed.ac.uk/public/direct/XSUM-EMNLP18-Summary-Data-Original.tar.gz` | {
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"following_url"... | [] | 1,614,458,634,000 | 1,614,464,470,000 | null | MEMBER | null | ```
metric = load_metric('glue', 'mrpc', num_process=num_process, process_id=rank)
```
May I suggest that `num_process` is confusing as it's singular yet expects a plural value and either
* be deprecated in favor of `num_processes` which is more intuitive since it's plural as its expected value
* or even better... | {
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"You can pass the same `experiment_id` for all the metrics of the same group, and use another `experiment_id` for the other groups.\r\nMaybe we can add an environment variable that sets the default value for `experiment_id` ? What do you think ?",
"Ah, you're absolutely correct, @lhoestq - it's exactly the equiva... | 1,614,458,325,000 | 1,614,619,482,000 | 1,614,619,482,000 | MEMBER | null | ```
metric = load_metric('glue', 'mrpc', num_process=num_process, process_id=rank)
```
presumes that there is only one set of parallel processes running - and will intermittently fail if you have multiple sets running as they will surely overwrite each other. Similar to https://github.com/huggingface/datasets/issu... | {
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"following_url"... | [] | 1,614,457,303,000 | 1,614,619,238,000 | 1,614,609,799,000 | MEMBER | null | This PR proposes a few typo + grammar fixes, and rewrites some sentences in an attempt to improve readability.
N.B. When referring to the library `datasets` in the docs it is typically used as a singular, and it definitely is a singular when written as "`datasets` library", that is "`datasets` library is ..." and no... | {
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"Hi\r\nnot sure how change the lable after creation, but this is an issue not dataset request. thanks ",
"Hi ! Currently you have to use `map` . You can see an example of how to do it in this comment: https://github.com/huggingface/datasets/issues/853#issuecomment-727872188\r\n\r\nIn the future we'll add support ... | 1,614,363,447,000 | 1,619,707,843,000 | 1,619,707,843,000 | NONE | null | Hi
I'd need to add a new column to the dataset, I was wondering how this can be done? thanks
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"following_url"... | [] | 1,614,357,349,000 | 1,614,607,428,000 | 1,614,607,427,000 | MEMBER | null | I added these methods to the documentation with a small paragraph.
I also fixed some formatting issues in the docstrings | {
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"I never said the calls were hanging indefinitely, what we need is quite different - in the firewalled env with a network, there should be no network calls or they should fail instantly.\r\n\r\nTo make this work I suppose on top of this PR we need:\r\n1. `DATASETS_OFFLINE` env var to force set timeout to 0 globally... | 1,614,351,727,000 | 1,614,608,964,000 | 1,614,608,964,000 | MEMBER | null | As noticed in https://github.com/huggingface/datasets/issues/1939, timeouts were not properly handled when loading a dataset.
This caused the connection to hang indefinitely when working in a firewalled environment cc @stas00
I added a default timeout, and included an option to our offline environment for tests to... | {
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"@mariosasko This is kinda cool! "
] | 1,614,351,385,000 | 1,615,429,106,000 | 1,614,353,426,000 | CONTRIBUTOR | null | One thing I've noticed while going through the codebase is the usage of `scripts` in `setup.py`. This [answer](https://stackoverflow.com/a/28119736/14095927) on SO explains it nicely why it's better to use `entry_points` instead of `scripts`. To add cross-platform support to the CLI, this PR replaces `scripts` with `en... | {
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"following_url"... | [] | 1,614,340,476,000 | 1,614,596,910,000 | 1,614,596,909,000 | CONTRIBUTOR | null | 1) updated fields which were missing earlier
2) added tags to README
3) updated a few fields of README
4) new dataset_infos.json and dummy files | {
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