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[ "Well actually it looks like it was already added in #1428 \r\n\r\nMaybe we can close this one ? Or you wanted to make changes to this dataset ?", "Thank you, it's just a modification of Readme. I added the missing citation.", "Indeed thanks" ]

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[ "Hi @eric-mitchell,\r\nI think the issue might be that this dataset was added during the community sprint and has not been released yet. It will be available with the v2 of `datasets`.\r\nFor now, you should be able to load the datasets after installing the latest (master) version of `datasets` using pip:\r\n`pip install git+https://github.com/huggingface/datasets.git@master`", "@bhavitvyamalik Great, thanks for this! Confirmed that the problem is resolved on master at [cbbda53](https://github.com/huggingface/datasets/commit/cbbda53ac1520b01f0f67ed6017003936c41ec59).", "Update: HuggingFace did an intermediate release yesterday just before the v2.0.\r\n\r\nTo load it you can just update `datasets`\r\n\r\n`pip install --upgrade datasets`" ]

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[ "Hover was added recently, that's why it wasn't available yet.\r\n\r\nTo load it you can just update `datasets`\r\n```\r\npip install --upgrade datasets\r\n```\r\n\r\nand then you can load `hover` with\r\n\r\n```python\r\nfrom datasets import load_dataset\r\n\r\ndataset = load_dataset(\"hover\")\r\n```" ]

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[ "I see, master is already fixed in https://github.com/huggingface/datasets/commit/9e058f098a0919efd03a136b9b9c3dec5076f626" ]

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[ "I have encountered the same error with `v1.0.1` and `v1.0.2` on both Windows and Linux environments. However, cloning the repo and using the path to the dataset's root directory worked for me. Even after having the dataset cached - passing the path is the only way (for now) to load the dataset.\r\n\r\n```python\r\nfrom datasets import load_dataset\r\n\r\ndataset = load_dataset(\"squad\") # Works\r\ndataset = load_dataset(\"code_search_net\", \"python\") # Error\r\ndataset = load_dataset(\"covid_qa_deepset\") # Error\r\n\r\npath = \"/huggingface/datasets/datasets/{}/\"\r\ndataset = load_dataset(path.format(\"code_search_net\"), \"python\") # Works\r\ndataset = load_dataset(path.format(\"covid_qa_deepset\")) # Works\r\n```\r\n\r\n", "Hi @mrm8488 and @amoux!\r\n The datasets you are trying to load have been added to the library during the community sprint for v2 last month. They will be available with the v2 release!\r\nFor now, there are still a couple of solutions to load the datasets:\r\n1. As suggested by @amoux, you can clone the git repo and pass the local path to the script\r\n2. You can also install the latest (master) version of `datasets` using pip: `pip install git+https://github.com/huggingface/datasets.git@master`", "If you don't want to clone entire `datasets` repo, just download the `muchocine` directory and pass the local path to the directory. Cheers!", "Muchocine was added recently, that's why it wasn't available yet.\r\n\r\nTo load it you can just update `datasets`\r\n```\r\npip install --upgrade datasets\r\n```\r\n\r\nand then you can load `muchocine` with\r\n\r\n```python\r\nfrom datasets import load_dataset\r\n\r\ndataset = load_dataset(\"muchocine\", split=\"train\")\r\n```", "Thanks @lhoestq " ]

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[ "Maybe you can use nltk's treebank detokenizer ?\r\n```python\r\nfrom nltk.tokenize.treebank import TreebankWordDetokenizer\r\n\r\nTreebankWordDetokenizer().detokenize(\"it 's a charming and often affecting journey . \".split())\r\n# \"it's a charming and often affecting journey.\"\r\n```", "I am looking for alternative file URL here instead of adding extra processing code: https://github.com/huggingface/datasets/blob/171f2bba9dd8b92006b13cf076a5bf31d67d3e69/datasets/glue/glue.py#L174", "I don't know if there exists a detokenized version somewhere. Even the version on kaggle is tokenized" ]

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[ "As always, I got stuck in the correct order of imports 😅\r\n@lhoestq, It's finished!", "@lhoestq, It's done! Is there anything else that needs changes?" ]

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[ "I have same issue for other datasets (`myanmar_news` in my case).\r\n\r\nA version of `datasets` runs correctly on my local machine (**without GPU**) which looking for the dataset at \r\n```\r\nhttps://raw.githubusercontent.com/huggingface/datasets/master/datasets/myanmar_news/myanmar_news.py\r\n```\r\n\r\nMeanwhile, other version runs on Colab (**with GPU**) failed to download the dataset. It try to find the dataset at `1.1.3` instead of `master` . If I disable GPU on my Colab, the code can load the dataset without any problem.\r\n\r\nMaybe there is some version missmatch with the GPU and CPU version of code for these datasets?", "It looks like they're two different issues\r\n\r\n----------\r\n\r\nFirst for `myanmar_news`: \r\n\r\nIt must come from the way you installed `datasets`.\r\nIf you install `datasets` from source, then the `myanmar_news` script will be loaded from `master`.\r\nHowever if you install from `pip` it will get it using the version of the lib (here `1.1.3`) and `myanmar_news` is not available in `1.1.3`.\r\n\r\nThe difference between your GPU and CPU executions must be the environment, one seems to have installed `datasets` from source and not the other.\r\n\r\n----------\r\n\r\nThen for `winogrande`:\r\n\r\nThe errors says that the url https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/winogrande/winogrande.py is not reachable.\r\nHowever it works fine on my side.\r\n\r\nDoes your machine have an internet connection ? Are connections to github blocked by some sort of proxy ?\r\nCan you also try again in case github had issues when you tried the first time ?\r\n" ]

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[ "That's interesting, can you tell me what you think would be useful to access to inspect a dataset?\r\n\r\nYou can filter them in the hub with the search by the way: https://huggingface.co/datasets have you seen it?", "Hi @thomwolf \r\nthank you, I was not aware of this, I was looking into the data viewer linked into readme page. \r\n\r\nThis is exactly what I was looking for, but this does not work currently, please see the attached \r\nI am selecting to see all nli datasets in english and it retrieves none. thanks\r\n\r\n\r\n\r\n\r\n\r\n", "I see 4 results for NLI in English but indeed some are not tagged yet and missing (GLUE), we will focus on that in January (cc @yjernite): https://huggingface.co/datasets?filter=task_ids:natural-language-inference,languages:en" ]

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[ "@lhoestq, should I raise a PR for this? Just a minor change while reading labels text file", "Sure feel free to open a PR thanks !" ]

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[ "Adding a link to the guide on adding a dataset if someone want to give it a try: https://github.com/huggingface/datasets#add-a-new-dataset-to-the-hub\r\n\r\nwe should add this guide to the issue template @lhoestq ", "thanks @thomwolf , this is added now. The template is correct, sorry my mistake not to include it. " ]

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[ "Progress bar can be disabled like this:\r\n```python\r\nfrom datasets.utils.logging import set_verbosity_error\r\nset_verbosity_error()\r\n```\r\n\r\nThere is this line in `Dataset.map`:\r\n```python\r\nnot_verbose = bool(logger.getEffectiveLevel() > WARNING)\r\n```\r\n\r\nSo any logging level higher than `WARNING` turns off the progress bar." ]

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[ "Hi @him1411, the dataset you are trying to load has been added during the community sprint and has not been released yet. It will be available with the v2 of `datasets`.\r\nFor now, you should be able to load the datasets after installing the latest (master) version of `datasets` using pip:\r\n`pip install git+https://github.com/huggingface/datasets.git@master`", "`ade_corpus_v2` was added recently, that's why it wasn't available yet.\r\n\r\nTo load it you can just update `datasets`\r\n```\r\npip install --upgrade datasets\r\n```\r\n\r\nand then you can load `ade_corpus_v2` with\r\n\r\n```python\r\nfrom datasets import load_dataset\r\n\r\ndataset = load_dataset(\"ade_corpus_v2\", \"Ade_corpos_v2_drug_ade_relation\")\r\n```\r\n\r\n(looks like there is a typo in the configuration name, we'll fix it for the v2.0 release of `datasets` soon)" ]

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[ "Thank you @lhoestq for your comments! 😄 I added your suggested changes, ran the tests and regenerated `dataset_infos.json` and `dummy_data`." ]

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[ "Indeed that's a typo, do you want to open a PR to fix it?", "Yes, created a PR" ]

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[ "I've updated the code and Readme to reflect your comments.\r\nThank you very much,", "looks like this PR includes changes about many other files than the ones for myPOS2017\r\n\r\nCould you open another branch and another PR please ?\r\n(or fix this branch)", "Hi @hungluumfc ! Have you had a chance to fix this PR so that it only includes the changes for `mypos` ? \r\n\r\nFeel free to ping me if you have questions or if I can help :) " ]

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[ "Thank you for all the feedback! I have updated the dummy data with a zip under 30KB, which needs to include at least one data instance from both document domain and dialog domain. Please let me know if it is still too big. Thanks!", "Thank you again for the feedback! I am not too sure what the preferable style for data instance in readme, but still added my edits. Thanks!" ]

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[ "cc'ing @mapmeld ", "Full language list is now deployed to https://huggingface.co/datasets ! Recommend close", "Cool @mapmeld ! My 2 cents (for a next iteration), it would be cool to have a small search widget in the filter dropdown as you have a ton of languages now here! Closing this in the meantime." ]

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[ "Yee a Computer Vision dataset!", "Yep, the first one ! Thank @czabo " ]

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[ "> I just generated the dataset_infos.json file\r\n> \r\n> Thanks for adding this one !\r\n\r\nThank you very much for your support." ]

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[ "Hi @SapirWeissbuch,\r\nWhen you are saying it freezes, at that time it is unzipping the file from the zip file it downloaded. Since it's a very heavy file it'll take some time. It was taking ~11GB after unzipping when it started reading examples for me. Hope that helps!\r\n\r\n", "Hi @bhavitvyamalik \r\nThanks for the reply!\r\nActually I let it run for 30 minutes before I killed the process. In this time, 30GB were extracted (much more than 11GB), I checked the size of the destination directory.\r\n\r\nWhat version of Datasets are you using?\r\n", "I'm using datasets version: 1.1.3. I think you should drop `cache_dir` and use only\r\n`dataset = datasets.load_dataset(\"trivia_qa\", \"rc\")`\r\n\r\nTried that on colab and it's working there too\r\n\r\n", "Train, Validation, and Test splits contain 138384, 18669, and 17210 samples respectively. It takes some time to read the samples. Even in your colab notebook it was reading the samples before you killed the process. Let me know if it works now!", "Hi, it works on colab but it still doesn't work on my computer, same problem as before - overly large and long extraction process.\r\nI have to use a custom 'cache_dir' because I don't have any space left in my home directory where it is defaulted, maybe this could be the issue?", "I tried running this again - More details of the problem:\r\nCode:\r\n```\r\ndatasets.load_dataset(\"trivia_qa\", \"rc\", cache_dir=\"/path/to/cache\")\r\n```\r\n\r\nThe output:\r\n```\r\nDownloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to path/to/cache/trivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d... \r\nDownloading: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2.67G/2.67G [03:38<00:00, 12.2MB/s]\r\n\r\n```\r\nThe process continues (no progress bar is visible).\r\nI tried `du -sh .` in `path/to/cache`, and the size keeps increasing, reached 35G before I killed the process.\r\n\r\nGoogle Colab with custom `cache_dir` has same issue.\r\nhttps://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing#scrollTo=2G2O0AeNIXan", "1) You can clear the huggingface folder in your `.cache` directory to use default directory for datasets. Speed of extraction and loading of samples depends a lot on your machine's configurations too.\r\n\r\n2) I tried on colab `dataset = datasets.load_dataset(\"trivia_qa\", \"rc\", cache_dir = \"./datasets\")`. After memory usage reached around 42GB (starting from 32GB used already), the dataset was loaded in the memory. Even Your colab notebook shows \r\n\r\nwhich means it's loaded now.", "Facing the same issue.\r\nI am able to download datasets without `cache_dir`, however, when I specify the `cache_dir`, the process hangs indefinitely after partial download. \r\nTried for `data = load_dataset(\"cnn_dailymail\", \"3.0.0\")`", "Hi @ashutoshml,\r\nI tried this and it worked for me:\r\n`data = load_dataset(\"cnn_dailymail\", \"3.0.0\", cache_dir=\"./dummy\")`\r\n\r\nI'm using datasets==1.8.0. It took around 3-4 mins for dataset to unpack and start loading examples.", "Ok. I waited for 20-30 mins, and it still is stuck.\r\nI am using datasets==1.8.0.\r\n\r\nIs there anyway to check what is happening? like a` --verbose` flag?\r\n\r\n\r\n" ]

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[ "Is there a way one can convert the two generator? not sure overall what alternatives I could have to shuffle the datasets with a torch generator, thanks ", "@lhoestq let me please expalin in more details, maybe you could help me suggesting an alternative to solve the issue for now, I have multiple large datasets using huggingface library, then I need to define a distributed sampler on top of it, for this I need to shard the datasets and give each shard to each core, but before sharding I need to shuffle the dataset, if you are familiar with distributed sampler in pytorch, this needs to be done based on seed+epoch generator to make it consistent across the cores they do it through defining a torch generator, I was wondering if you could tell me how I can shuffle the data for now, I am unfortunately blocked by this and have a limited time left, and I greatly appreciate your help on this. thanks ", "@lhoestq Is there a way I could shuffle the datasets from this library with a custom defined shuffle function? thanks for your help on this. ", "Right now the shuffle method only accepts the `seed` (optional int) or `generator` (optional `np.random.Generator`) parameters.\r\n\r\nHere is a suggestion to shuffle the data using your own shuffle method using `select`.\r\n`select` can be used to re-order the dataset samples or simply pick a few ones if you want.\r\nIt's what is used under the hood when you call `dataset.shuffle`.\r\n\r\nTo use `select` you must have the list of re-ordered indices of your samples.\r\n\r\nLet's say you have a `shuffle` methods that you want to use. Then you can first build your shuffled list of indices:\r\n```python\r\nshuffled_indices = shuffle(range(len(dataset)))\r\n```\r\n\r\nThen you can shuffle your dataset using the shuffled indices with \r\n```python\r\nshuffled_dataset = dataset.select(shuffled_indices)\r\n```\r\n\r\nHope that helps", "thank you @lhoestq thank you very much for responding to my question, this greatly helped me and remove the blocking for continuing my work, thanks. ", "@lhoestq could you confirm the method proposed does not bring the whole data into memory? thanks ", "Yes the dataset is not loaded into memory", "great. thanks a lot." ]

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[ "Hi, did you check the doc on `shuffle`?\r\nhttps://huggingface.co/docs/datasets/package_reference/main_classes.html?datasets.Dataset.shuffle#datasets.Dataset.shuffle", "Hi Thomas\r\nthanks for reponse, yes, I did checked it, but this does not work for me please see \r\n\r\n```\r\n(internship) rkarimi@italix17:/idiap/user/rkarimi/dev$ python \r\nPython 3.7.9 (default, Aug 31 2020, 12:42:55) \r\n[GCC 7.3.0] :: Anaconda, Inc. on linux\r\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\r\n>>> import datasets \r\n2020-12-20 01:48:50.766004: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\r\n2020-12-20 01:48:50.766029: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\r\n>>> data = datasets.load_dataset(\"scitail\", \"snli_format\")\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\nReusing dataset scitail (/idiap/temp/rkarimi/cache_home_1/datasets/scitail/snli_format/1.1.0/fd8ccdfc3134ce86eb4ef10ba7f21ee2a125c946e26bb1dd3625fe74f48d3b90)\r\n>>> data.shuffle(seed=2)\r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\nTypeError: shuffle() got an unexpected keyword argument 'seed'\r\n\r\n```\r\n\r\ndatasets version\r\n`datasets 1.1.2 <pip>\r\n`\r\n", "Thanks for reporting ! \r\n\r\nIndeed it looks like an issue with `suffle` on `DatasetDict`. We're going to fix that.\r\nIn the meantime you can shuffle each split (train, validation, test) separately:\r\n```python\r\nshuffled_train_dataset = data[\"train\"].shuffle(seed=42)\r\n```\r\n" ]

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[ "Hi @jassimran,\r\nThe `jigsaw_toxicity_pred` dataset has not been released yet, it will be available with version 2 of `datasets`, coming soon.\r\nYou can still access it by installing the master (unreleased) version of datasets directly :\r\n`pip install git+https://github.com/huggingface/datasets.git@master`\r\nPlease let me know if this helps", "Thanks.That works for now." ]

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[ "Closing this with reference to the new approach #1676 " ]

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[ "I think we’ll need complete dataset_infos.json to create YAML tags. I ran the script again with 100 files after going through your comments and it was occupying ~16 GB space. So in total it should take ~960GB and I don’t have this much memory available with me. Also, I'll have to download the whole dataset for generating dummy data, right?" ]

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[ "merging this one then :) " ]

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[ "I close this PR, since it based on 1 week old repo. And I will create a new one" ]

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[ "Hi @david-waterworth!\r\n\r\nAs indicated in the error message, `load_dataset(\"csv\")` returns a `DatasetDict` object, which is mapping of `str` to `Dataset` objects. I believe in this case the behavior is to return a `train` split with all the data.\r\n`train_test_split` is a method of the `Dataset` object, so you will need to do something like this:\r\n```python\r\ndataset_dict = load_dataset(`'csv', data_files='data.txt')\r\ndataset = dataset_dict['split name, eg train']\r\ndataset.train_test_split(test_size=0.1)\r\n```\r\n\r\nPlease let me know if this helps. 🙂 ", "Thanks, that's working - the same issue also tripped me up with training. \r\n\r\nI also agree https://github.com/huggingface/datasets/issues/767 would be a useful addition. ", "Closing this now", "> ```python\r\n> dataset_dict = load_dataset(`'csv', data_files='data.txt')\r\n> dataset = dataset_dict['split name, eg train']\r\n> dataset.train_test_split(test_size=0.1)\r\n> ```\r\n\r\nI am getting error like\r\nKeyError: 'split name, eg train'\r\nCould you please tell me how to solve this?", "dataset = load_dataset('csv', data_files=['files/datasets/dataset.csv'])\r\ndataset = dataset['train']\r\ndataset = dataset.train_test_split(test_size=0.1)" ]

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[ "made suggested changes and opened PR https://github.com/huggingface/datasets/pull/1628" ]

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[ "I'm getting an error when I try to create the dummy data:\r\n```python\r\naclifton@pop-os:~/data/hf_datasets_sprint/datasets$ python datasets-cli dummy_data ./datasets/logiqa_en/ --auto_generate \r\n2021-01-07 10:50:12.024791: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory\r\n2021-01-07 10:50:12.024814: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\r\nUsing custom data configuration default\r\nCouldn't generate dummy file 'datasets/dummy/1.1.0/dummy_data/master.zip/LogiQA-dataset-master/README.md'. Ignore that if this file is not useful for dummy data.\r\nDummy data generation done but dummy data test failed since splits ['train', 'test', 'validation'] have 0 examples for config 'default''.\r\nAutomatic dummy data generation failed for some configs of './datasets/logiqa_en/'\r\n```", "Hi ! Sorry for the delay\r\n\r\nTo fix your issue for the dummy data you must increase the number of lines that will be kept to generate the dummy files. By default it's 5, and as you need at least 8 lines here to yield one example you must increase this.\r\n\r\nYou can increase the number of lines to 32 for example by doing\r\n```\r\ndatasets-cli dummy_data ./datasets/logica_en --auto_generate --n_lines 32\r\n```\r\n\r\nAlso it looks like there are changes about other datasets in this PR (imppres). Can you fix that ? You may need to create another branch and another PR.", "To fix the branch issue, I went ahead and made a backup of the dataset then deleted my local copy of my fork of `datasets`. I then followed the [detailed guide](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md) from the beginning to reclone the fork and start a new branch. \r\n\r\nHowever, when it came time to create the dummy data I got the following error:\r\n```python\r\naclifton@pop-os:~/data/hf_datasets_sprint/datasets$ datasets-cli dummy_data ./datasets/logiqa_en --auto_generate --n_lines 32\r\n2021-02-03 11:23:23.145885: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory\r\n2021-02-03 11:23:23.145914: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\r\nUsing custom data configuration default\r\nCouldn't generate dummy file 'datasets/logiqa_en/dummy/1.1.0/dummy_data/master.zip/LogiQA-dataset-master/README.md'. Ignore that if this file is not useful for dummy data.\r\nTraceback (most recent call last):\r\n File \"/home/aclifton/anaconda3/bin/datasets-cli\", line 36, in <module>\r\n service.run()\r\n File \"/home/aclifton/anaconda3/lib/python3.7/site-packages/datasets/commands/dummy_data.py\", line 317, in run\r\n keep_uncompressed=self._keep_uncompressed,\r\n File \"/home/aclifton/anaconda3/lib/python3.7/site-packages/datasets/commands/dummy_data.py\", line 355, in _autogenerate_dummy_data\r\n dataset_builder._prepare_split(split_generator)\r\n File \"/home/aclifton/anaconda3/lib/python3.7/site-packages/datasets/builder.py\", line 905, in _prepare_split\r\n example = self.info.features.encode_example(record)\r\n File \"/home/aclifton/anaconda3/lib/python3.7/site-packages/datasets/features.py\", line 799, in encode_example\r\n return encode_nested_example(self, example)\r\n File \"/home/aclifton/anaconda3/lib/python3.7/site-packages/datasets/features.py\", line 710, in encode_nested_example\r\n (k, encode_nested_example(sub_schema, sub_obj)) for k, (sub_schema, sub_obj) in utils.zip_dict(schema, obj)\r\n File \"/home/aclifton/anaconda3/lib/python3.7/site-packages/datasets/features.py\", line 710, in <genexpr>\r\n (k, encode_nested_example(sub_schema, sub_obj)) for k, (sub_schema, sub_obj) in utils.zip_dict(schema, obj)\r\n File \"/home/aclifton/anaconda3/lib/python3.7/site-packages/datasets/features.py\", line 737, in encode_nested_example\r\n return schema.encode_example(obj)\r\n File \"/home/aclifton/anaconda3/lib/python3.7/site-packages/datasets/features.py\", line 522, in encode_example\r\n example_data = self.str2int(example_data)\r\n File \"/home/aclifton/anaconda3/lib/python3.7/site-packages/datasets/features.py\", line 481, in str2int\r\n output.append(self._str2int[str(value)])\r\nKeyError: \"Some Cantonese don't like chili, so some southerners don't like chili.\"\r\n```", "Hi ! The error happens when the script is verifying that the generated dummy data work fine with the dataset script.\r\nApparently it fails because the text `\"Some Cantonese don't like chili, so some southerners don't like chili.\"` was given in a field that is a ClassLabel feature (probably the `answer` field), while it actually expects \"a\", \"b\", \"c\" or \"d\". Can you fix the script so that it returns the expected labels for this field instead of the text ?\r\n\r\nAlso it would be awesome to rename this field `answerKey` instead of `answer` to have the same column names as the other multiple-choice-QA datasets in the library :) ", "Ok getting closer! I got the dummy data to work. However I am now getting the following error:\r\n```python\r\naclifton@pop-os:~/data/hf_datasets_sprint/datasets$ RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_logiqa_en\r\n===================================================================== test session starts ======================================================================\r\nplatform linux -- Python 3.7.6, pytest-5.3.5, py-1.8.1, pluggy-0.13.1\r\nrootdir: /home/aclifton/data/hf_datasets_sprint/datasets\r\nplugins: astropy-header-0.1.2, xdist-2.1.0, doctestplus-0.5.0, forked-1.3.0, hypothesis-5.5.4, arraydiff-0.3, remotedata-0.3.2, openfiles-0.4.0\r\ncollected 0 items / 1 error \r\n\r\n============================================================================ ERRORS ============================================================================\r\n________________________________________________________ ERROR collecting tests/test_dataset_common.py _________________________________________________________\r\nImportError while importing test module '/home/aclifton/data/hf_datasets_sprint/datasets/tests/test_dataset_common.py'.\r\nHint: make sure your test modules/packages have valid Python names.\r\nTraceback:\r\ntests/test_dataset_common.py:42: in <module>\r\n from datasets.packaged_modules import _PACKAGED_DATASETS_MODULES\r\nE ModuleNotFoundError: No module named 'datasets.packaged_modules'\r\n----------------------------------------------------------------------- Captured stderr ------------------------------------------------------------------------\r\n2021-02-10 11:06:14.345510: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory\r\n2021-02-10 11:06:14.345551: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\r\n======================================================================= warnings summary =======================================================================\r\n/home/aclifton/anaconda3/lib/python3.7/site-packages/tensorflow/python/autograph/utils/testing.py:21\r\n /home/aclifton/anaconda3/lib/python3.7/site-packages/tensorflow/python/autograph/utils/testing.py:21: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses\r\n import imp\r\n\r\n/home/aclifton/anaconda3/lib/python3.7/site-packages/apache_beam/typehints/typehints.py:693\r\n /home/aclifton/anaconda3/lib/python3.7/site-packages/apache_beam/typehints/typehints.py:693: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\r\n if not isinstance(type_params, collections.Iterable):\r\n\r\n/home/aclifton/anaconda3/lib/python3.7/site-packages/apache_beam/typehints/typehints.py:532\r\n /home/aclifton/anaconda3/lib/python3.7/site-packages/apache_beam/typehints/typehints.py:532: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\r\n if not isinstance(type_params, (collections.Sequence, set)):\r\n\r\n/home/aclifton/anaconda3/lib/python3.7/site-packages/elasticsearch/compat.py:38\r\n /home/aclifton/anaconda3/lib/python3.7/site-packages/elasticsearch/compat.py:38: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\r\n from collections import Mapping\r\n\r\n-- Docs: https://docs.pytest.org/en/latest/warnings.html\r\n================================================================= 4 warnings, 1 error in 2.74s =================================================================\r\nERROR: not found: /home/aclifton/data/hf_datasets_sprint/datasets/tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_logiqa_en\r\n(no name '/home/aclifton/data/hf_datasets_sprint/datasets/tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_logiqa_en' in any of [<Module test_dataset_common.py>])\r\n\r\n```", "Hi ! It looks like the version of `datasets` that is installed in your environment doesn't match the version of `datasets` you're using for the tests. Can you try uninstalling datasets and reinstall it again ?\r\n```\r\npip uninstall datasets -y\r\npip install -e .\r\n```", "Closer still!\r\n```python\r\naclifton@pop-os:~/data/hf_datasets_sprint/datasets$ git commit\r\n[logiqa_en 2664fe7f] fixed several issues with logiqa_en.\r\n 4 files changed, 324 insertions(+)\r\n create mode 100644 datasets/logiqa_en/README.md\r\n create mode 100644 datasets/logiqa_en/dataset_infos.json\r\n create mode 100644 datasets/logiqa_en/dummy/1.1.0/dummy_data.zip\r\n create mode 100644 datasets/logiqa_en/logiqa_en.py\r\naclifton@pop-os:~/data/hf_datasets_sprint/datasets$ git fetch upstream\r\nremote: Enumerating objects: 1, done.\r\nremote: Counting objects: 100% (1/1), done.\r\nremote: Total 1 (delta 0), reused 0 (delta 0), pack-reused 0\r\nUnpacking objects: 100% (1/1), 590 bytes | 590.00 KiB/s, done.\r\nFrom https://github.com/huggingface/datasets\r\n 6e114a0c..318b09eb master -> upstream/master\r\naclifton@pop-os:~/data/hf_datasets_sprint/datasets$ git rebase upstream/master \r\nerror: cannot rebase: You have unstaged changes.\r\nerror: Please commit or stash them.\r\naclifton@pop-os:~/data/hf_datasets_sprint/datasets$ git push -u origin logiqa_en\r\nUsername for 'https://github.com': aclifton314\r\nPassword for 'https://aclifton314@github.com': \r\nTo https://github.com/aclifton314/datasets\r\n ! [rejected] logiqa_en -> logiqa_en (non-fast-forward)\r\nerror: failed to push some refs to 'https://github.com/aclifton314/datasets'\r\nhint: Updates were rejected because the tip of your current branch is behind\r\nhint: its remote counterpart. Integrate the remote changes (e.g.\r\nhint: 'git pull ...') before pushing again.\r\nhint: See the 'Note about fast-forwards' in 'git push --help' for details.\r\n```" ]

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[ "This happen quite often when they are too many concurrent requests to github.\r\n\r\ni can understand it’s a bit cumbersome to handle on the user side. Maybe we should try a few times in the lib (eg with timeout) before failing, what do you think @lhoestq ?", "Yes currently there's no retry afaik. We should add retries", "Retries were added in #1603 :) \r\nIt will be available in the next release", "Hi @lhoestq thank you for the modification, I will use`script_version=\"master\"` for now :), to my experience, also setting timeout to a larger number like 3*60 which I normally use helps a lot on this.\r\n" ]

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[ "Indeed that would be cool\r\n\r\nAlso FYI right now the easiest way to do this is\r\n```python\r\ndataset_dict[\"train\"] = dataset_dict[\"train\"].map(my_transform_for_the_train_set)\r\ndataset_dict[\"test\"] = dataset_dict[\"test\"].map(my_transform_for_the_test_set)\r\n```" ]

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[ "We are indeed working on the integration with `Trainer` :)" ]

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[ "Sorry, this is a duplicate of #1287. Not sure why it didn't come up when I searched `iwslt` in the issues list.", "Closing this since its a duplicate" ]

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[ "Do you have an example?", "I was thinking about using something like [importlib](https://docs.python.org/3/library/importlib.html#importing-a-source-file-directly) to over-ride the collision. \r\n\r\n**Reason requested**: I use the [following template](https://github.com/jramapuram/ml_base/) repo where I house all my datasets as a submodule.", "Alternatively huggingface could consider some submodule type structure like:\r\n\r\n`import huggingface.datasets`\r\n`import huggingface.transformers`\r\n\r\n`datasets` is a very common module in ML and should be an end-user decision and not scope all of python ¯\\_(ツ)_/¯ \r\n", "That's a interesting option indeed. We'll think about it.", "It also wasn't initially obvious to me that the samples which contain `import datasets` were in fact importing a huggingface library (in fact all the huggingface imports are very generic - transformers, tokenizers, datasets...)" ]

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[ "Thanks for adding the `doc2dial_rc` config :) \r\n\r\nIt looks like you're missing the dummy data for this config though. Could you add them please ?\r\nAlso to fix the CI you'll need to format the code with `make style`" ]

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[ "welcome, awesome " ]

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[ "@SBrandeis all checks passing" ]

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