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"I second this request. The bottom line is that **scores produced with different reference tokenizations are not comparable**. To discourage (even inadvertent) cheating, the user should never touch the reference. The `v13a` tokenization standard is not ideal, but at least it has been consistently used at matrix.sta... | 1,589,573,314,000 | 1,610,016,088,000 | null | NONE | null | https://github.com/huggingface/nlp/blob/7d1526dfeeb29248d832f1073192dbf03ad642da/metrics/bleu/bleu.py#L76 assumes the inputs are tokenized by the user. This is bad practice because the user's tokenizer is usually not the same as the one used by `mteval-v13a.pl`, the closest thing we have to a standard. Moreover, toke... | {
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"Thanks, this was fixed with #135 :)"
] | 1,589,572,867,000 | 1,589,717,848,000 | 1,589,717,848,000 | NONE | null | small typo | {
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"Indeed, thanks!"
] | 1,589,572,343,000 | 1,589,717,646,000 | 1,589,717,645,000 | CONTRIBUTOR | null | print statement was throwing generator object instead of printing names of available datasets/metrics | {
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"the readme got removed, closing this one"
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"Hi @zphang,\r\n\r\nSo you can just give the local path to a dataset script file and it should work.\r\n\r\nHere is an example:\r\n- you can download one of the scripts in the `datasets` folder of the present repo (or clone the repo)\r\n- then you can load it with `load_dataset('PATH/TO/YOUR/LOCAL/SCRIPT.py')`\r\n\... | 1,589,559,966,000 | 1,595,522,649,000 | 1,595,522,649,000 | NONE | null | Users may want to either create/modify a local copy of a dataset, or use a custom-built dataset with the same `Dataset` API as externally downloaded datasets.
It appears to be possible to point to a local dataset path rather than downloading the external ones, but I'm not exactly sure how to go about doing this.
... | {
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"We're experimenting with hosting the OpenWebText corpus on Zenodo for easier downloading. https://zenodo.org/record/3834942#.Xs1w8i-z2J8",
"Closing since it's been added in #660 "
] | 1,589,558,249,000 | 1,602,080,568,000 | 1,602,080,568,000 | MEMBER | null | The OpenWebText dataset is an open clone of OpenAI's WebText dataset. It can be used to train ELECTRA as is specified in the [README](https://www.github.com/google-research/electra).
More information and the download link are available [here](https://skylion007.github.io/OpenWebTextCorpus/). | {
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"As far as I understand, `wikitext` is refer to `WikiText-103` and `WikiText-2` that created by researchers in Salesforce, and mostly used in traditional language modeling.\r\n\r\nYou might want to say `wikipedia`, a dump from wikimedia foundation.\r\n\r\nAlso I would like to have Toronto BookCorpus too ! Though it... | 1,589,557,844,000 | 1,593,379,651,000 | 1,593,379,651,000 | CONTRIBUTOR | null | I know the copyright/distribution of this one is complex, but it would be great to have! That, combined with the existing `wikitext`, would provide a complete dataset for pretraining models like BERT. | {
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"As a follow-up to this: It looks like the actual GLUE task name is supplied as the `name` argument. Is there a way to check what `name`s/sub-datasets are available under a grouping like GLUE? That information doesn't seem to be readily available in info from `nlp.list_datasets()`.\r\n\r\nEdit: I found the info und... | 1,589,554,550,000 | 1,590,617,295,000 | 1,590,617,295,000 | NONE | null | If I run:
```python
dataset = nlp.load_dataset('glue')
```
The resultant dataset seems to be CoLA be default, without throwing any error. This is in contrast to calling:
```python
metric = nlp.load_metric("glue")
```
which throws an error telling the user that they need to specify a task in GLUE. Should the... | {
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"Indeed, I think this one is almost ready cc @lhoestq ",
"I'm doing the latest adjustments to make the processing of the dataset run on Dataflow",
"Is there an update to this? It will be very beneficial for the QA community!",
"Still work in progress :)\r\nThe idea is to have the dataset already processed som... | 1,589,552,060,000 | 1,595,510,489,000 | 1,595,510,489,000 | NONE | null | Would be great to have https://github.com/google-research-datasets/natural-questions as an alternative to SQuAD. | {
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"Google colab has an old version of Apache Arrow built-in.\r\nBe sure you execute the \"pip install\" cell and restart the notebook environment if the colab asks for it.",
"Thanks for reply, worked fine!\r\n"
] | 1,589,547,689,000 | 1,589,548,240,000 | 1,589,548,240,000 | NONE | null | First of all, nice work!
I am going through [this overview notebook](https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb)
In simple step `dataset = nlp.load_dataset('squad', split='validation[:10%]')`
I get an error, which is connected with some inner code, I think:
`... | {
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Our first dataset script that only lives on AWS :-) https://s3.console.aws.amazon.com/s3/buckets/datasets.huggingface.co/nlp/datasets/webis/tl_dr/?region=us-east-1 @julien-c @jplu | {
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"For each dataset, If there exist a `dataset_info.json`, then the command `nlp-cli test path/to/my/dataset --al_configs` is successful only if the `dataset_infos.json` is correct. The infos are correct if the size and checksums of the downloaded file are correct, and if the number of examples in each split are corr... | 1,589,533,945,000 | 1,589,537,172,000 | 1,589,537,006,000 | MEMBER | null | ## Change default Test from local => aws
As a default we set` aws=True`, `Local=False`, `slow=False`
### 1. RUN_AWS=1 (default)
This runs 4 tests per dataset script.
a) Does the dataset script have a valid etag / Can it be reached on AWS?
b) Can we load its `builder_class`?
c) Can we load **all** dataset c... | {
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"I didn't assign the output 🤦♂️\r\n\r\n```python\r\ndataset.map(test)\r\n```\r\n\r\nshould be :\r\n\r\n```python\r\ndataset = dataset.map(test)\r\n```"
] | 1,589,524,988,000 | 1,589,526,158,000 | 1,589,526,158,000 | NONE | null | I'm trying to run a basic example (mapping function to add a prefix).
[Here is the colab notebook I'm using.](https://colab.research.google.com/drive/1YH4JCAy0R1MMSc-k_Vlik_s1LEzP_t1h?usp=sharing)
```python
import nlp
dataset = nlp.load_dataset('squad', split='validation[:10%]')
def test(sample):
samp... | {
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"It's strange, after installing `nlp` on Colab, the `pyarrow` version seems fine from `pip` but not from python :\r\n\r\n```python\r\nimport pyarrow\r\n\r\n!pip show pyarrow\r\nprint(\"version = {}\".format(pyarrow.__version__))\r\n```\r\n\r\n> Name: pyarrow\r\nVersion: 0.17.0\r\nSummary: Python library for Apache ... | 1,589,509,646,000 | 1,589,519,482,000 | 1,589,510,728,000 | NONE | null | I'm trying to load CNN/DM dataset on Colab.
[Colab notebook](https://colab.research.google.com/drive/11Mf7iNhIyt6GpgA1dBEtg3cyMHmMhtZS?usp=sharing)
But I meet this error :
> AttributeError: type object 'pyarrow.lib.RecordBatch' has no attribute 'from_struct_array'
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"That's the way!"
] | 1,589,507,932,000 | 1,589,526,349,000 | 1,589,526,265,000 | NONE | null | I'm working with CNN/DM dataset, where I have 3 subsets : `train`, `test`, `validation`.
Should I apply my map function on the subsets one by one ?
```python
import nlp
cnn_dm = nlp.load_dataset('cnn_dailymail')
for corpus in ['train', 'test', 'validation']:
cnn_dm[corpus] = cnn_dm[corpus].map(my_f... | {
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"Hi, you can't do that at the moment."
] | 1,589,505,906,000 | 1,620,964,939,000 | 1,589,526,272,000 | NONE | null | I saw on the [example notebook](https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb#scrollTo=efFhDWhlvSVC) how to remove a specific column :
```python
dataset.drop('id')
```
But I didn't find how to remove a specific row.
**For example, how can I remove all sample w... | {
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"default": false,
"description": "A bug in a metric script"
}
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"Can you share your data files or a minimally reproducible example?",
"Sure, [here is a Colab notebook](https://colab.research.google.com/drive/1uiS89fnHMG7HV_cYxp3r-_LqJQvNNKs9?usp=sharing) reproducing the error.\r\n\r\n> ArrowInvalid: Column 1 named references expected length 36 but got length 56",
"This is b... | 1,589,505,126,000 | 1,590,709,387,000 | 1,590,709,387,000 | NONE | null | I'm trying to use rouge metric.
I have to files : `test.pred.tokenized` and `test.gold.tokenized` with each line containing a sentence.
I tried :
```python
import nlp
rouge = nlp.load_metric('rouge')
with open("test.pred.tokenized") as p, open("test.gold.tokenized") as g:
for lp, lg in zip(p, g):
... | {
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"I could access the info by first accessing the different splits :\r\n\r\n```python\r\nimport nlp\r\n\r\ncnn_dm = nlp.load_dataset('cnn_dailymail')\r\nprint(cnn_dm['train'].info)\r\n```\r\n\r\nInformation seems to be duplicated between the subsets :\r\n\r\n```python\r\nprint(cnn_dm[\"train\"].info == cnn_dm[\"test\... | 1,589,502,587,000 | 1,589,721,060,000 | 1,589,721,060,000 | NONE | null | I'm trying to access the information of CNN/DM dataset :
```python
cnn_dm = nlp.load_dataset('cnn_dailymail')
print(cnn_dm.info)
```
returns :
> AttributeError: 'dict' object has no attribute 'info' | {
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"Installing from source (instead of Pypi package) solved the problem."
] | 1,589,501,777,000 | 1,589,501,992,000 | 1,589,501,991,000 | NONE | null | I can't get CNN / DailyMail dataset.
```python
import nlp
assert "cnn_dailymail" in [dataset.id for dataset in nlp.list_datasets()]
cnn_dm = nlp.load_dataset('cnn_dailymail')
```
[Colab notebook](https://colab.research.google.com/drive/1zQ3bYAVzm1h0mw0yWPqKAg_4EUlSx5Ex?usp=sharing)
gives following error ... | {
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I had to do add some minor hacks to an important function to make it work.
There might be a cleaner way to handle it - can you take a look @thomwolf ? | {
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"Awesome that's great!"
] | 1,589,474,139,000 | 1,589,475,030,000 | 1,589,475,029,000 | MEMBER | null | You can now specify `writer_batch_size` in the builder arguments or directly in `load_dataset` | {
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"Nice - I think we can merge this. I will update the checksums for `wikihow` then as well"
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"> Wikihow is an example that needs to manually download two files as stated in: https://github.com/mahnazkoupaee/WikiHow-Dataset.\r\n> \r\n> The user can then store these files under a hard-coded name: `wikihowAll.csv` and `wikihowSep.csv` in this case in a directory of his choice, e.g. `~/wikihow/manual_dir`.\r\n... | 1,589,463,036,000 | 1,589,466,461,000 | 1,589,466,460,000 | MEMBER | null | Wikihow is an example that needs to manually download two files as stated in: https://github.com/mahnazkoupaee/WikiHow-Dataset.
The user can then store these files under a hard-coded name: `wikihowAll.csv` and `wikihowSep.csv` in this case in a directory of his choice, e.g. `~/wikihow/manual_dir`.
The dataset ca... | {
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"Haha that cornell dialogue dataset - that ran for 3h on my computer as well. The `generate_examples` method in this script is one of the most inefficient code samples I've ever seen :D ",
"Indeed it's been 3 hours already\r\n```73111 examples [3:07:48, 2.40 examples/s]```"
] | 1,589,462,846,000 | 1,589,470,984,000 | 1,589,470,983,000 | MEMBER | null | I replaced the old checksum file with the new `dataset_infos.json` by running the script on almost all the datasets we have. The only one that is still running on my side is the cornell dialog | {
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"LGTM :-) Some small suggestions to shorten the code a bit :-) ",
"Can you put the kwargs as normal kwargs instead of a dict? (And add them to the kwargs description As well)",
"@thom Is-it what you meant?",
"Yes and there is a dynamically generated doc string in the metric script KWARGS DESCRIPTION"
] | 1,589,449,072,000 | 1,589,498,495,000 | 1,589,498,494,000 | CONTRIBUTOR | null | This PR add a bit more detail in the seqeval metric. Now the usage and output are:
```python
import nlp
met = nlp.load_metric('metrics/seqeval')
references = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]
predictions = [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-... | {
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"> Should that rather be in an organization scope, @thomwolf @patrickvonplaten ?\r\n\r\nI'm a bit indifferent - both would be fine for me!",
"@jplu - if creating the dummy_data is too tedious, I can do it as well :-) ",
"There is... | 1,589,437,338,000 | 1,599,127,221,000 | 1,589,489,656,000 | CONTRIBUTOR | null | Add the Webid TL:DR dataset. | {
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"@thomwolf - can you check and merge if ok? "
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"I might have a different version of `isort` than others. It seems like I'm always reordering the imports of others. But isn't really a problem..."
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"Great! LGTM :-) ",
"> Ok, really clean!\r\n> I like the logic (not a huge fan of using `_asdict_inner` but it makes sense).\r\n> I think it's a nice improvement!\r\n> \r\n> How should we update the files in the repo? Run a big job on a server or on somebody's computer who has most of the datasets already downloa... | 1,589,398,576,000 | 1,589,446,723,000 | 1,589,446,722,000 | MEMBER | null | ### Better verifications when loading a dataset
I replaced the `urls_checksums` directory that used to contain `checksums.txt` and `cached_sizes.txt`, by a single file `dataset_infos.json`. It's just a dict `config_name` -> `DatasetInfo`.
It simplifies and improves how verifications of checksums and splits sizes ... | {
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- WMT is the first dataset that uses an abstract class IMO, so I had to modify the `load_dataset_module` a bit. | {
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- Also this PR reformats all dataset scripts and adds `datasets` to `make style` | {
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"awesome - so no manual downloaded needed here? ",
"Yes exactly. It works like a standard download"
] | 1,589,363,762,000 | 1,589,373,988,000 | 1,589,364,331,000 | MEMBER | null | We can now add datasets that download from google drive | {
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```python
nlp.list_datasets()
nlp.list_metrics()
# Copy and prepare the scripts at `local_path` for easy inspection/modification.
nlp.inspect_dataset(path, local_path)
# Copy and prepare the scripts at `local_path` for easy... | {
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"Looks good to me. I have not really looked too much into the Beam Datasets yet though - so I think you can merge whenever you think is good for Beam datasets :-) "
] | 1,589,361,361,000 | 1,589,373,115,000 | 1,589,373,114,000 | MEMBER | null | This one is a beam dataset that downloads files using tensorflow.
I tested it on a small config and it works fine | {
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"Awesome :-) Thanks for adding the function to the Mock DL Manager"
] | 1,589,358,747,000 | 1,589,360,979,000 | 1,589,360,978,000 | MEMBER | null | I just added the dummy data for this dataset.
This one was uses `tf.io.gfile.copy` to download the data but I added the support for custom download in the mock_download_manager. I also had to add a `tensorflow` dependency for tests. | {
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The result looks like this:
![Screenshot from 2020-05-12 18-34-43](https://user-images.githubusercontent.com/23423619/81721933-ee1faf00-9480-11ea-9e95-d6557cbd0c... | {
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I also removed unused utils functions. | {
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"Looks good to me! Should we hard code those numbers in the config classes and make sure that when loading a dataset that the numbers match? "
] | 1,589,300,323,000 | 1,589,356,354,000 | 1,589,356,353,000 | MEMBER | null | ### Save size and number of examples
Now when you do `save_checksums`, it also create `cached_sizes.txt` right next to the checksum file.
This new file stores the bytes sizes and the number of examples of each split that has been prepared and stored in the cache. Example:
```
# Cached sizes: <full_config_name> <n... | {
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"@lhoestq - I moved the wkipedia file to the \"correct\" folder. ",
"Nice thanks !"
] | 1,589,299,258,000 | 1,589,300,184,000 | 1,589,300,182,000 | MEMBER | null | For now we will skip tests for Beam Datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/77 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/77/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/77/comments | https://api.github.com/repos/huggingface/datasets/issues/77/events | https://github.com/huggingface/datasets/pull/77 | 616,674,601 | MDExOlB1bGxSZXF1ZXN0NDE2NzQwMjAz | 77 | New datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/75 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/75/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/75/comments | https://api.github.com/repos/huggingface/datasets/issues/75/events | https://github.com/huggingface/datasets/pull/75 | 616,520,163 | MDExOlB1bGxSZXF1ZXN0NDE2NjE0MzU1 | 75 | WIP adding metrics | {
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"It's all about my metric stuff so I'll probably merge it unless you want to have a look.\r\n\r\nTook the occasion to remove the old doc and requirements.txt"
] | 1,589,277,120,000 | 1,589,355,852,000 | 1,589,355,850,000 | MEMBER | null | Adding the following metrics as identified by @mariamabarham:
1. BLEU: BiLingual Evaluation Understudy: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py, https://github.com/chakki-works/sumeval/blob/master/sumeval/metrics/bleu.py (multilingual)
2. GLEU: Google-BLEU: https://github.com/cnap/gec-... | {
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https://api.github.com/repos/huggingface/datasets/issues/74 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/74/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/74/comments | https://api.github.com/repos/huggingface/datasets/issues/74/events | https://github.com/huggingface/datasets/pull/74 | 616,511,101 | MDExOlB1bGxSZXF1ZXN0NDE2NjA3MDcy | 74 | fix overflow check | {
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```
pa_array.nbytes > MAX_BATCH_BYTES
```
doesn't work. Indeed for a StructArray, `nbytes` can be less 2GB even if there is an overflow (it loops...).
I don't think we can do a proper overflow test for the limit of 2GB...
For now I replaced it with a sanity check on... | {
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https://api.github.com/repos/huggingface/datasets/issues/73 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/73/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/73/comments | https://api.github.com/repos/huggingface/datasets/issues/73/events | https://github.com/huggingface/datasets/pull/73 | 616,417,845 | MDExOlB1bGxSZXF1ZXN0NDE2NTMyMTg1 | 73 | JSON script | {
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"The tests for the Wikipedia dataset do not pass anymore with the error:\r\n```\r\nTo be able to use this dataset, you need to install the following dependencies ['mwparserfromhell'] using 'pip install mwparserfromhell' for instance'\r\n```",
"This was an issue on master. You can just rebase from master.",
"Per... | 1,589,267,482,000 | 1,589,784,637,000 | 1,589,784,636,000 | CONTRIBUTOR | null | Add a JSONS script to read JSON datasets from files. | {
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https://api.github.com/repos/huggingface/datasets/issues/72 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/72/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/72/comments | https://api.github.com/repos/huggingface/datasets/issues/72/events | https://github.com/huggingface/datasets/pull/72 | 616,225,010 | MDExOlB1bGxSZXF1ZXN0NDE2Mzc4Mjg4 | 72 | [README dummy data tests] README to better understand how the dummy data structure works | {
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@... | {
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"After a quick chat with Yacine : the 2Go test may not be sufficient actually, as I'm looking at the size of the array and not the size of the current_rows. If the test doesn't do the job I think I'll remove it and lower the batch size a bit to be sure that it never exceeds 2Go. I'll do more tests later"
] | 1,589,208,336,000 | 1,589,227,787,000 | 1,589,227,238,000 | MEMBER | null | This PR fixes Yacine's bug.
According to [this](https://github.com/apache/arrow/blob/master/docs/source/cpp/arrays.rst#size-limitations-and-recommendations), it is not recommended to have pyarrow arrays bigger than 2Go.
Therefore I set a default batch size of 100 000 examples per batch. In general it shouldn't exce... | {
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"I think rebasing to master will solve the quality test and the datasets that don't have a testing structure yet because of the manual download - maybe you can put them in `datasets under construction`? Then would also make it easier for me to see how to add tests for them :-) "
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"Nice, is that the reason one cannot rerun the tests without deleting the cache? \r\n",
"Yes exactly. It was not using the temporary dir for tests."
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@lhoestq noticed that I accidently deleted it in https://github.com/huggingface/nlp/pull/63#discussion_r422263729. | {
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"Super nice, good job @patrickvonplaten!"
] | 1,588,950,163,000 | 1,588,967,447,000 | 1,588,951,020,000 | MEMBER | null | This PR adds a `aws` and a `local` decorator to the tests so that tests now run on the local datasets.
By default, the `aws` is deactivated and `local` is activated and `slow` is deactivated, so that only 1 test per dataset runs on circle ci.
**When local is activated all folders in `./datasets` are tested.**
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@mariamabarham @lhoestq @thomwolf - what do you think?
If this is ok for you, I can sync up the master with the `add_datase... | {
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See: PR #59. | {
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https://api.github.com/repos/huggingface/datasets/issues/60 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/60/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/60/comments | https://api.github.com/repos/huggingface/datasets/issues/60/events | https://github.com/huggingface/datasets/pull/60 | 614,372,553 | MDExOlB1bGxSZXF1ZXN0NDE0OTQyNjEy | 60 | Update to simplify some datasets conversion | {
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"Awesome! ",
"Also we should convert `tf.io.gfile.exists` into `os.path.exists` , `tf.io.gfile.listdir`into `os.listdir` and `tf.io.gfile.glob` into `glob.glob` (will need to add `import glob`)",
"> Also we should convert `tf.io.gfile.exists` into `os.path.exists` , `tf.io.gfile.listdir`into `os.listdir` and `... | 1,588,888,944,000 | 1,588,934,312,000 | 1,588,933,104,000 | MEMBER | null | This PR updates the encoding of `Values` like `integers`, `boolean` and `float` to use python casting and avoid having to cast in the dataset scripts, as mentioned here: https://github.com/huggingface/nlp/pull/37#discussion_r420176626
We could also change (not included in this PR yet):
- `supervized_keys` to make t... | {
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https://api.github.com/repos/huggingface/datasets/issues/59 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/59/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/59/comments | https://api.github.com/repos/huggingface/datasets/issues/59/events | https://github.com/huggingface/datasets/pull/59 | 614,366,045 | MDExOlB1bGxSZXF1ZXN0NDE0OTM3NTgx | 59 | Fix tests | {
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"I can fix the tests tomorrow :-) ",
"Very weird bug indeed! I think the problem was that when importing `setup_module` we overwrote `pytest's` setup_module function. I think this is the relevant code in pytest: https://github.com/pytest-dev/pytest/blob/9d2eabb397b059b75b746259daeb20ee5588f559/src/_pytest/python.... | 1,588,888,089,000 | 1,588,935,477,000 | 1,588,934,811,000 | MEMBER | null | @patrickvonplaten I've broken a bit the tests with #25 while simplifying and re-organizing the `load.py` and `download_manager.py` scripts.
I'm trying to fix them here but I have a weird error, do you think you can have a look?
```bash
(datasets) MacBook-Pro-de-Thomas:datasets thomwolf$ python -m pytest -sv ./test... | {
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https://api.github.com/repos/huggingface/datasets/issues/58 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/58/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/58/comments | https://api.github.com/repos/huggingface/datasets/issues/58/events | https://github.com/huggingface/datasets/pull/58 | 614,362,308 | MDExOlB1bGxSZXF1ZXN0NDE0OTM0NTY4 | 58 | Aborted PR - Fix tests | {
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"Wait I messed up my branch, let me clean this."
] | 1,588,887,619,000 | 1,588,888,081,000 | 1,588,887,687,000 | MEMBER | null | @patrickvonplaten I've broken a bit the tests with #25 while simplifying and re-organizing the `load.py` and `download_manager.py` scripts.
I'm trying to fix them here but I have a weird error, do you think you can have a look?
```bash
(datasets) MacBook-Pro-de-Thomas:datasets thomwolf$ python -m pytest -sv ./test... | {
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https://api.github.com/repos/huggingface/datasets/issues/57 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/57/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/57/comments | https://api.github.com/repos/huggingface/datasets/issues/57/events | https://github.com/huggingface/datasets/pull/57 | 614,261,638 | MDExOlB1bGxSZXF1ZXN0NDE0ODUzMDM5 | 57 | Better cached path | {
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"I should have read this PR before doing my own: https://github.com/huggingface/nlp/pull/62 :D \r\nwill close mine. Looks great :-) ",
"> Awesome, this is really nice!\r\n> \r\n> By the way, we should improve the `cached_path` method of the `transformers` repo similarly, don't you think (@patrickvonplaten in part... | 1,588,876,560,000 | 1,588,944,030,000 | 1,588,944,028,000 | MEMBER | null | ### Changes:
- The `cached_path` no longer returns None if the file is missing/the url doesn't work. Instead, it can raise `FileNotFoundError` (missing file), `ConnectionError` (no cache and unreachable url) or `ValueError` (parsing error)
- Fix requests to firebase API that doesn't handle HEAD requests...
- Allow c... | {
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https://api.github.com/repos/huggingface/datasets/issues/55 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/55/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/55/comments | https://api.github.com/repos/huggingface/datasets/issues/55/events | https://github.com/huggingface/datasets/pull/55 | 613,968,072 | MDExOlB1bGxSZXF1ZXN0NDE0NjE0MjE1 | 55 | Beam datasets | {
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"Right now the changes are a bit hard to read as the one from #25 are also included. You can wait until #25 is merged before looking at the implementation details",
"Nice!! I tested it a bit and works quite well. I will do a my review once the #25 will be merged because there are several overlaps.\r\n\r\nAt least... | 1,588,849,472,000 | 1,589,181,602,000 | 1,589,181,600,000 | MEMBER | null | # Beam datasets
## Intro
Beam Datasets are using beam pipelines for preprocessing (basically lots of `.map` over objects called PCollections).
The advantage of apache beam is that you can choose which type of runner you want to use to preprocess your data. The main runners are:
- the `DirectRunner` to run the p... | {
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https://api.github.com/repos/huggingface/datasets/issues/54 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/54/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/54/comments | https://api.github.com/repos/huggingface/datasets/issues/54/events | https://github.com/huggingface/datasets/pull/54 | 613,513,348 | MDExOlB1bGxSZXF1ZXN0NDE0MjUyODkw | 54 | [Tests] Improved Error message for dummy folder structure | {
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https://api.github.com/repos/huggingface/datasets/issues/51 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/51/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/51/comments | https://api.github.com/repos/huggingface/datasets/issues/51/events | https://github.com/huggingface/datasets/pull/51 | 613,266,668 | MDExOlB1bGxSZXF1ZXN0NDE0MDUyOTYw | 51 | [Testing] Improved testing structure | {
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"Awesome!\r\nLet's have this in the doc at the end :-)"
] | 1,588,766,587,000 | 1,588,889,239,000 | 1,588,771,218,000 | MEMBER | null | This PR refactors the test design a bit and puts the mock download manager in the `utils` files as it is just a test helper class.
as @mariamabarham pointed out, creating a dummy folder structure can be quite hard to grasp.
This PR tries to change that to some extent.
It follows the following logic for the `dumm... | {
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https://api.github.com/repos/huggingface/datasets/issues/50 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/50/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/50/comments | https://api.github.com/repos/huggingface/datasets/issues/50/events | https://github.com/huggingface/datasets/pull/50 | 612,583,126 | MDExOlB1bGxSZXF1ZXN0NDEzNTAwMjE0 | 50 | [Tests] test only for fast test as a default | {
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"Test failure is not related to change in test file.\r\n"
] | 1,588,683,562,000 | 1,588,683,738,000 | 1,588,683,736,000 | MEMBER | null | Test only for one config on circle ci to speed up testing. Add all config test as a slow test.
@mariamabarham @thomwolf | {
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https://api.github.com/repos/huggingface/datasets/issues/49 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/49/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/49/comments | https://api.github.com/repos/huggingface/datasets/issues/49/events | https://github.com/huggingface/datasets/pull/49 | 612,545,483 | MDExOlB1bGxSZXF1ZXN0NDEzNDY5ODg0 | 49 | fix flatten nested | {
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https://api.github.com/repos/huggingface/datasets/issues/48 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/48/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/48/comments | https://api.github.com/repos/huggingface/datasets/issues/48/events | https://github.com/huggingface/datasets/pull/48 | 612,504,687 | MDExOlB1bGxSZXF1ZXN0NDEzNDM2MTgz | 48 | [Command Convert] remove tensorflow import | {
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https://api.github.com/repos/huggingface/datasets/issues/47 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/47/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/47/comments | https://api.github.com/repos/huggingface/datasets/issues/47/events | https://github.com/huggingface/datasets/pull/47 | 612,446,493 | MDExOlB1bGxSZXF1ZXN0NDEzMzg5MDc1 | 47 | [PyArrow Feature] fix py arrow bool | {
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https://api.github.com/repos/huggingface/datasets/issues/46 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/46/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/46/comments | https://api.github.com/repos/huggingface/datasets/issues/46/events | https://github.com/huggingface/datasets/pull/46 | 612,398,190 | MDExOlB1bGxSZXF1ZXN0NDEzMzUxNTY0 | 46 | [Features] Strip str key before dict look-up | {
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https://api.github.com/repos/huggingface/datasets/issues/45 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/45/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/45/comments | https://api.github.com/repos/huggingface/datasets/issues/45/events | https://github.com/huggingface/datasets/pull/45 | 612,386,583 | MDExOlB1bGxSZXF1ZXN0NDEzMzQzMjAy | 45 | [Load] Separate Module kwargs and builder kwargs. | {
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This is a follow-up PR of: https://github.com/huggingface/nlp/pull/41 | {
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https://api.github.com/repos/huggingface/datasets/issues/44 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/44/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/44/comments | https://api.github.com/repos/huggingface/datasets/issues/44/events | https://github.com/huggingface/datasets/pull/44 | 611,873,486 | MDExOlB1bGxSZXF1ZXN0NDEyOTUwMzU1 | 44 | [Tests] Fix tests for datasets with no config | {
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"Whoops I fixed it directly on master before checking that you have done it in this PR. We may close it",
"Yeah, I saw :-) But I think we should add this as well since some datasets have an empty list of configs and then as the code is now it would fail. \r\n\r\nIn this PR, I just make sure that the code jumps in... | 1,588,588,782,000 | 1,588,598,283,000 | 1,588,598,283,000 | MEMBER | null | `movie_rationales` e.g. has no configs. | {
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In this case the dummy data will be saved as:
- natural_questions
-> dummy
-> -> 1.0.0 (version num)
-> -> -> dummy_data.zip
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https://api.github.com/repos/huggingface/datasets/issues/41 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/41/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/41/comments | https://api.github.com/repos/huggingface/datasets/issues/41/events | https://github.com/huggingface/datasets/pull/41 | 611,739,219 | MDExOlB1bGxSZXF1ZXN0NDEyODQzNDQy | 41 | [Load module] allow kwargs into load module | {
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This simple change allows to pass ``force_reload=True`` as ``builder_kwargs`` in the ``load.py`` function. | {
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https://api.github.com/repos/huggingface/datasets/issues/40 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/40/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/40/comments | https://api.github.com/repos/huggingface/datasets/issues/40/events | https://github.com/huggingface/datasets/pull/40 | 611,721,308 | MDExOlB1bGxSZXF1ZXN0NDEyODI4NzU2 | 40 | Update remote checksums instead of overwrite | {
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If the user uploads the dataset in several steps, then the remote checksums file was previously overwritten. Now it's going to be updated with the new checksums. | {
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https://api.github.com/repos/huggingface/datasets/issues/39 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/39/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/39/comments | https://api.github.com/repos/huggingface/datasets/issues/39/events | https://github.com/huggingface/datasets/pull/39 | 611,712,135 | MDExOlB1bGxSZXF1ZXN0NDEyODIxNTA4 | 39 | [Test] improve slow testing | {
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https://api.github.com/repos/huggingface/datasets/issues/38 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/38/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/38/comments | https://api.github.com/repos/huggingface/datasets/issues/38/events | https://github.com/huggingface/datasets/issues/38 | 611,677,656 | MDU6SXNzdWU2MTE2Nzc2NTY= | 38 | [Checksums] Error for some datasets | {
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"@lhoestq - could you take a look? It's not very urgent though!",
"Fixed with 06882b4\r\n\r\nNow your command works :)\r\nNote that you can also do\r\n```\r\nnlp-cli test datasets/nlp/xnli --save_checksums\r\n```\r\nSo that it will save the checksums directly in the right directory.",
"Awesome!"
] | 1,588,579,216,000 | 1,588,585,700,000 | 1,588,585,700,000 | MEMBER | null | The checksums command works very nicely for `squad`. But for `crime_and_punish` and `xnli`,
the same bug happens:
When running:
```
python nlp-cli nlp-cli test xnli --save_checksums
```
leads to:
```
File "nlp-cli", line 33, in <module>
service.run()
File "/home/patrick/python_bin/nlp/commands... | {
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