Datasets:

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SurAyush

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[ "Okay nevermind looks like to works both ways for models. but my doubt still remains, isnt this changing the device of the model every batch?" ]

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[ "cc: @lhoestq ", "I am going to rebase #7434 onto this branch. Then we can merge this one first if you approve, and then #7434.", "@lhoestq any thoughts here?", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7435). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "@lhoestq please let me know what you think about this.", "It looks like I can't change the merge target to #7435, so it will look like there is a bunch of extra stuff until #7435 is in main." ]

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[ "This feels related: https://github.com/huggingface/datasets/issues/3044", "@lhoestq This comment specifically, I agree:\n\n* https://github.com/huggingface/datasets/issues/3044#issuecomment-1239877570\n\n> Almost a year later and I'm in a similar boat. Using custom fingerprints and when using multiprocessing the cached datasets are saved with a template at the end of the filename (something like \"000001_of_000008\" for every process of num_proc). So if in the next time you run the script you set num_proc to a different number, the cache cannot be used.\n> \n> Is there any way to get around this? I am processing a huge dataset so I do the processing on one machine and then transfer the processed data to another in its cache dir but currently that's not possible due to num_proc mismatch.\n\n" ]

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[ "Thanks ! There is https://github.com/huggingface/datasets/pull/7426 already that fixes the issue, I'm closing your PR if you don't mind" ]

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[ "what's the error message ?", "This was the final error message that it was giving pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0", "Here is the list of errors:\n\nTraceback (most recent call last):\n File \".venv/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py\", line 160, in _generate_tables\n df = pandas_read_json(f)\n ^^^^^^^^^^^^^^^^^^^\n File \".venv/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py\", line 38, in pandas_read_json\n return pd.read_json(path_or_buf, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \".venv/lib/python3.12/site-packages/pandas/io/json/_json.py\", line 815, in read_json\n return json_reader.read()\n ^^^^^^^^^^^^^^^^^^\n File \".venv/lib/python3.12/site-packages/pandas/io/json/_json.py\", line 1025, in read\n obj = self._get_object_parser(self.data)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \".venv/lib/python3.12/site-packages/pandas/io/json/_json.py\", line 1051, in _get_object_parser\n obj = FrameParser(json, **kwargs).parse()\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \".venv/lib/python3.12/site-packages/pandas/io/json/_json.py\", line 1187, in parse\n self._parse()\n File \".venv/lib/python3.12/site-packages/pandas/io/json/_json.py\", line 1402, in _parse\n self.obj = DataFrame(\n ^^^^^^^^^^\n File \".venv/lib/python3.12/site-packages/pandas/core/frame.py\", line 778, in __init__\n mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \".venv/lib/python3.12/site-packages/pandas/core/internals/construction.py\", line 503, in dict_to_mgr\n return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \".venv/lib/python3.12/site-packages/pandas/core/internals/construction.py\", line 114, in arrays_to_mgr\n index = _extract_index(arrays)\n ^^^^^^^^^^^^^^^^^^^^^^\n File \".venv/lib/python3.12/site-packages/pandas/core/internals/construction.py\", line 677, in _extract_index\n raise ValueError(\"All arrays must be of the same length\")\nValueError: All arrays must be of the same length\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \".venv/lib/python3.12/site-packages/datasets/builder.py\", line 1854, in _prepare_split_single\n for _, table in generator:\n File \".venv/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py\", line 163, in _generate_tables\n raise e\n File \".venv/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py\", line 137, in _generate_tables\n pa_table = paj.read_json(\n ^^^^^^^^^^^^^^\n File \"pyarrow/_json.pyx\", line 308, in pyarrow._json.read_json\n File \"pyarrow/error.pxi\", line 155, in pyarrow.lib.pyarrow_internal_check_status\n File \"pyarrow/error.pxi\", line 92, in pyarrow.lib.check_status\npyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to number in row 0\n\nThe above exception was the direct cause of the following exception:\n\nTraceback (most recent call last):\n File \"run_object_detection.py\", line 582, in <module>\n main()\n File \"run_object_detection.py\", line 407, in main\n dataset = load_dataset(\n ^^^^^^^^^^^^^\n File \"venv/lib/python3.12/site-packages/datasets/load.py\", line 2151, in load_dataset\n builder_instance.download_and_prepare(\n File \".venv/lib/python3.12/site-packages/datasets/builder.py\", line 924, in download_and_prepare\n self._download_and_prepare(\n File \".venv/lib/python3.12/site-packages/datasets/builder.py\", line 1000, in _download_and_prepare\n self._prepare_split(split_generator, **prepare_split_kwargs)\n File \".venv/lib/python3.12/site-packages/datasets/builder.py\", line 1741, in _prepare_split\n for job_id, done, content in self._prepare_split_single(\n File \".venv/lib/python3.12/site-packages/datasets/builder.py\", line 1897, in _prepare_split_single\n raise DatasetGenerationError(\"An error occurred while generating the dataset\") from e\ndatasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset", "`datasets` is based on Arrow which expects all the lists inside the data to be of fixed type. Arrow can't load lists that contain a mix of integers and strings for example. In your case it looks like one of the lists contains numbers and JSON objects.\n\nI'd suggest you to reformat the data to end up with list of fixed types, otherwise you won't be able to load the data in `datasets`" ]

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[ "You should open an issue in the NLP course website / github page. I'm closing this issue if you don't mind", "ok, i don't mind, i'll mark the error there" ]

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[ "Hi ! can you run `make style` to fix code formatting ?", "@lhoestq Fixed", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7428). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "First time I see this error :/ maybe it's an issue with your version of `multiprocess` and `dill` ? Make sure they are compatible with `datasets`", "> First time I see this error :/ maybe it's an issue with your version of `multiprocess` and `dill` ? Make sure they are compatible with `datasets`\n\nany recommendation for `multiprocess` and `dill`" ]

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[ "> datasets\n\nHi, have you solved this bug? Today I also met the same problem about `livecodebench/code_generation_lite` when evaluating the `Open-R1` repo. I am looking forward to your reply!\n\n", "Hey guys,\nI tried to reproduce the issue and it works fine. I used google colab as enviroment.\n\n", "> Hey guys, I tried to reproduce the issue and it works fine. I used google colab as enviroment.\n> \n> \n\nThanks for your kind reply! I wonder which Python version do you use? My Python version is 3.11.11 and datasets version is 3.3.2 but I still met this bug.\n\n<img width=\"1121\" alt=\"Image\" src=\"https://github.com/user-attachments/assets/7c2c5007-ee55-4030-94b9-01fcdea0bf4a\" />", "@zwxandy It's Python 3.11.11" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7424). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "Would be cool to be consistent when it comes to indexing with numpy objects, if we do accept numpy arrays we should indeed accept numpy integers. Your idea sounds reasonable, I'd also be in favor of adding a simple test as well" ]

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[ "Unfortunately `url` is a reserved argument in `fsspec.url_to_fs`, so ideally file system implementations like DVC should use another argument name to avoid this kind of errors" ]

[ { "color": "a2eeef", "default": true, "description": "New feature or request", "id": 1935892871, "name": "enhancement", "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement" } ]

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[ "@lhoestq ", "Can you try passing text: None for the image object ? Pyarrow expects all the objects to have the exact same type, in particular the dicttionaries in \"content\" should all have the keys \"type\" and \"text\"", "The following modification on system prompt works, but it is different from the usual way to use it.\n```\ndef make_conversation(example):\n prompt = []\n\n prompt.append({\"role\": \"system\", \"content\": [{\"type\": \"text\", \"text\": system_prompt}]})\n prompt.append(\n {\n \"role\": \"user\", \n \"content\": [\n {\"type\": \"image\"},\n {\"type\": \"text\", \"text\": example[\"problem\"]},\n ]\n }\n )\n return {\"prompt\": prompt}\n```", "Good to know ! But yes Arrow / Parquet have this typing limitation (which is great to ensure data integrity, but constraining at the same time). It's is really blocking you, feel free to ping the arrow team / community if they plan to have a Union type or a JSON type" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7417). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7416). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "Hi ! if it's an option I'd suggest to have one sequence per row instead.\n\nOtherwise you'd have to make your own save/load mechanism", "Saving one sequence per row is very difficult and heavy and makes all the optimizations pointless. How would a custom save/load mechanism look like?", "You can use `pyarrow` for example to save/load individual arrow or parquet files and control what they contain" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7414). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "Yes this is correct and it works with huggingface datasets as well ! Feel free to include an example here: https://github.com/huggingface/datasets/blob/main/docs/source/video_dataset.mdx" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7411). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Thanks for the fix! We have been affected by this a lot when we try to use LLM Foundry with larger multimodal ICL datasets. ", "@lorabit110 are you able to test it out for your case as well? Would be great to get a second validation that it actually fixes the issue. Thanks!" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7410). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7409). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7408). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ { "color": "a2eeef", "default": true, "description": "New feature or request", "id": 1935892871, "name": "enhancement", "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement" } ]

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[ "@lhoestq", "there is no per-module maintainer and the list is me alone nowadays ^^'", "@lhoestq \nOh... I feel for you. \nWhat are your criteria for choosing a core maintainer? \nIt seems like it's too much work for you to manage all this code by yourself.\n\nAlso, if you don't mind, can you check this PR for me?\n#7368 I'd like this to be added as soon as possible because I need it." ]

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[ "Many python packages out there, including `huggingface_hub`, do load the environment variables on import.\nYou should `load_dotenv()` before importing the libraries.\n\nFor example you can move all you imports inside your `main()` function" ]

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[ "Thanks for reporting, I'll fix the regression today", "I just released `datasets` 3.3.1 with a fix, let me know if it's good now :)", "@lhoestq it fixed the issue.\n\nThis was (very) fast, thank you very much!" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7401). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "Hi ! the `desc` parameter is only available for Dataset / DatasetDict for the progress bar of `map()``\n\nSince IterableDataset only runs the map functions when you iterate over the dataset, there is no progress bar and `desc` is useless. We could still add the argument for parity but it wouldn't be used for anything", "I think you should add it. It doesn't hurt. The reason I ran into it was because I re-wrote a pipeline to use either a stream or a fully loaded dataset. Of course I can simply remove it but it is nice to have on the memory loaded dataset. " ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7398). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "Hi ! feel free to uplad the CSV on https://huggingface.co/datasets :)\r\n\r\nwe don't store the datasets' data in this github repository" ]

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[ "I transferred to the `datasets` repository. Is there any retry mechanism in `datasets` @lhoestq ?\n\nAnother solution @hotchpotch if you want to get your dataset pushed to the Hub in a robust way is to save it to a local folder first and then use `huggingface-cli upload-large-folder` (see https://huggingface.co/docs/huggingface_hub/guides/upload#upload-a-large-folder). It has better retry mechanism in case of failure.", "There is no retry mechanism for `api.preupload_lfs_files` in `push_to_hub()` but we can definitely add one here\n\nhttps://github.com/huggingface/datasets/blob/de062f0552a810c52077543c1169c38c1f0c53fc/src/datasets/arrow_dataset.py#L5372", "@Wauplin \n\nThank you! I believe that to use load_dataset() to read data from Hugging Face, we need to first save the markdown metadata and parquet files in our local filesystem, then upload them using upload-large-folder. If you know how to do this, could you please let me know?\n\n", "@lhoestq \n\nI see, so adding a retry mechanism there would solve it. If I continue to have issues, I'll consider implementing that kind of solution." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7396). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]