Datasets:

taeseokyi

/

github-issues

like 0

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"2022-11-17T04:00:50"

"2022-11-17T04:00:50"

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"2022-11-17T03:54:26"

"2022-11-17T03:54:26"

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[]

[ "Also cc @mariosasko and @lhoestq " ]

"2022-11-17T03:22:22"

"2022-11-17T05:56:34"

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"2022-11-17T02:39:57"

"2022-11-17T02:39:57"

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"2022-11-17T02:22:58"

"2022-11-17T02:22:58"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5252). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5252). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-16T15:02:13"

"2022-11-16T18:06:50"

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[]

[ "After a discussion with @mishig25:\r\n- He said that this action should be triggered if we call our release branch according to the regex `v*-release`, as transformers does\r\n- I said that our procedure is different: our release branch is *temporary* and it is deleted just after the release PR is merged to main\r\n - Indeed the release tag is not yet created when we make the release PR (not event when this is merged to main), but when we make the Release itself.\r\n\r\nI was thinking that maybe we could change the triggering event: use `release` instead of `push`.\r\n\r\nWhat do you think, @huggingface/datasets?", "Why is it an issue if our branch is temporary ?", "He says not; but the branch has no tag yet; does the doc building require the tag? Or just the version number in `__init__.py` or setup.py?", "It uses `module.__version__` (i.e. the one defined in `__init__.py`) - no need to have a tag\r\n\r\nhttps://github.com/huggingface/doc-builder/blob/81575cf081964c30ea5fd39450f4820db963f18e/src/doc_builder/commands/build.py#L69", "Thanks, @lhoestq.\r\n\r\n@mishig25 has manually forced the generation of the docs, that are live for 2.7.0 version: https://huggingface.co/docs/datasets/v2.7.0/en/index " ]

"2022-11-16T14:59:31"

"2022-11-16T16:08:35"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5250). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5250). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5250). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5250). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-16T14:35:32"

"2022-11-16T18:25:20"

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"2022-11-16T14:19:03"

"2022-11-16T14:36:14"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5248). All of your documentation changes will be reflected on that endpoint.", "Thanks for the fix @mishig25.\r\n\r\nI guess this is the reason why the docs are not generated for the latest release version 2.7.0? https://huggingface.co/docs/datasets/index " ]

"2022-11-16T10:41:04"

"2022-11-16T15:06:50"

"2022-11-16T10:41:10"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5247). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-16T10:17:31"

"2022-11-16T10:22:20"

"2022-11-16T10:17:50"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-16T09:32:44"

"2022-11-16T09:39:42"

"2022-11-16T09:37:03"

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[ "Hi @peregilk this bug is directly related to https://github.com/huggingface/datasets/issues/3888, and still not fixed... But I'll try to have a look!", "Thanks @alvarobartt. It is great if you are able to fix it, but when reading the explanation it seems like it is possible to work around it.\r\n\r\nWe also tried keeping the 'info.features' and then adding a modified version back after the remove/rename. Unforutunately that leads to a dataset that is not possible to iterate over.", "So if you iterate over the `IterableDataset` as `next(iter(ds))` and then run `rename_columns` when checking that data it will work, but in the end, it's just renaming the column one example/batch at a time, not renaming the column name for all the entries in the dataset, which is the ideal.", "@alvarobartt Thanks. My use case was that I wanted to do multiple things, ie removing all unnecessary columns, renaming some valid columns, and then using cast (in my case checking if the audio is not 16K and casting it). It is just convenient to look into the info.features between each of these operations. Alternatively, I will just plan ahead...;) To me it seems like all the operations are working.\r\n\r\nThanks for the advice. It was very useful.", "If we know the features before renaming, then we know the features after renaming, so we can pass the new features to the returned dataset in `rename_column` indeed ! If anyone is interested in contributing, feel free to open a PR and I'd be happy to help / give some pointers :)", "Sure @lhoestq thanks! I’ll try to work on that" ]

"2022-11-15T21:04:41"

"2022-11-16T17:20:20"

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"2022-11-15T16:02:10"

"2022-11-15T16:03:09"

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[ "Hi @capsabogdan! Unfortunately, it's hard to implement because quite often datasets data is being hosted in a single archive for all splits :( So we have to download the whole archive to split it into splits. This is the case for CommonVoice too. \r\n\r\nHowever, for cases when data is distributed in separate archives ащк different splits I suppose it can (and will) be implemented someday. \r\n\r\n\r\nBtw for quick check of the dataset you can use [streaming](https://huggingface.co/docs/datasets/stream):\r\n```python\r\ncv = load_dataset(\"mozilla-foundation/common_voice_11_0\", \"en\", split=\"test\", streaming=True)\r\ncv = iter(cv)\r\nprint(next(cv))\r\n\r\n>> {'client_id': 'a07b17f8234ded5e847443ea6f423cef745cbbc7537fb637d58326000aa751e829a21c4fd0a35fc17fb833aa7e95ebafce5efd19beeb8d843887b85e4eb35f5b',\r\n>> 'path': None,\r\n>> 'audio': {'path': 'cv-corpus-11.0-2022-09-21/en/clips/common_voice_en_100363.mp3',\r\n>> 'array': array([ 0.0000000e+00, 1.1748125e-14, 1.5450088e-14, ...,\r\n>> 1.3011958e-06, -6.3548953e-08, -9.9098514e-08], dtype=float32),\r\n>> ...}\r\n\r\n```", "thank you for the answer but am not sure if this will not be helpful, as we\nneed maybe just 10% of the datasets for some experiment\n\ncan we get just a portion of the dataset with stream?\n\n\nis there really no solution? :(\n\nAm Di., 15. Nov. 2022 um 16:55 Uhr schrieb Polina Kazakova <\n***@***.***>:\n\n> Hi @capsabogdan <https://github.com/capsabogdan>! Unfortunately, it's\n> hard to implement because quite often datasets data is being hosted in a\n> single archive for all splits :( So we have to download the whole archive\n> to split it into splits. This is the case for CommonVoice too.\n>\n> However, for cases when data is distributed in separate archives in\n> different splits I suppose it can be implemented someday.\n>\n> Btw for quick check of the dataset you can use streaming\n> <https://huggingface.co/docs/datasets/stream>:\n>\n> cv = load_dataset(\"mozilla-foundation/common_voice_11_0\", \"en\", split=\"test\", streaming=True)cv = iter(cv)print(next(cv))\n> >> {'client_id': 'a07b17f8234ded5e847443ea6f423cef745cbbc7537fb637d58326000aa751e829a21c4fd0a35fc17fb833aa7e95ebafce5efd19beeb8d843887b85e4eb35f5b',>> 'path': None,>> 'audio': {'path': 'cv-corpus-11.0-2022-09-21/en/clips/common_voice_en_100363.mp3',>> 'array': array([ 0.0000000e+00, 1.1748125e-14, 1.5450088e-14, ...,>> 1.3011958e-06, -6.3548953e-08, -9.9098514e-08], dtype=float32),>> ...}\n>\n> —\n> Reply to this email directly, view it on GitHub\n> <https://github.com/huggingface/datasets/issues/5243#issuecomment-1315512887>,\n> or unsubscribe\n> <https://github.com/notifications/unsubscribe-auth/ALSIFOC3JYRCTH54OBRUJULWIOW6PANCNFSM6AAAAAASAYO2LY>\n> .\n> You are receiving this because you were mentioned.Message ID:\n> ***@***.***>\n>\n", "maybe it would be nice if you guys ould do some sort of shard before\nloading the dataset, so users can download just chunks of data :)\n\nI think this would be very helpful\n\nAm Di., 15. Nov. 2022 um 19:24 Uhr schrieb Bogdan Capsa <\n***@***.***>:\n\n> thank you for the answer but am not sure if this will not be helpful, as\n> we need maybe just 10% of the datasets for some experiment\n>\n> can we get just a portion of the dataset with stream?\n>\n>\n> is there really no solution? :(\n>\n> Am Di., 15. Nov. 2022 um 16:55 Uhr schrieb Polina Kazakova <\n> ***@***.***>:\n>\n>> Hi @capsabogdan <https://github.com/capsabogdan>! Unfortunately, it's\n>> hard to implement because quite often datasets data is being hosted in a\n>> single archive for all splits :( So we have to download the whole archive\n>> to split it into splits. This is the case for CommonVoice too.\n>>\n>> However, for cases when data is distributed in separate archives in\n>> different splits I suppose it can be implemented someday.\n>>\n>> Btw for quick check of the dataset you can use streaming\n>> <https://huggingface.co/docs/datasets/stream>:\n>>\n>> cv = load_dataset(\"mozilla-foundation/common_voice_11_0\", \"en\", split=\"test\", streaming=True)cv = iter(cv)print(next(cv))\n>> >> {'client_id': 'a07b17f8234ded5e847443ea6f423cef745cbbc7537fb637d58326000aa751e829a21c4fd0a35fc17fb833aa7e95ebafce5efd19beeb8d843887b85e4eb35f5b',>> 'path': None,>> 'audio': {'path': 'cv-corpus-11.0-2022-09-21/en/clips/common_voice_en_100363.mp3',>> 'array': array([ 0.0000000e+00, 1.1748125e-14, 1.5450088e-14, ...,>> 1.3011958e-06, -6.3548953e-08, -9.9098514e-08], dtype=float32),>> ...}\n>>\n>> —\n>> Reply to this email directly, view it on GitHub\n>> <https://github.com/huggingface/datasets/issues/5243#issuecomment-1315512887>,\n>> or unsubscribe\n>> <https://github.com/notifications/unsubscribe-auth/ALSIFOC3JYRCTH54OBRUJULWIOW6PANCNFSM6AAAAAASAYO2LY>\n>> .\n>> You are receiving this because you were mentioned.Message ID:\n>> ***@***.***>\n>>\n>\n" ]

"2022-11-15T10:15:54"

"2022-11-15T20:12:24"

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[ "cc @abhishekkrthakur @SBrandeis " ]

"2022-11-15T02:47:52"

"2022-11-15T17:59:23"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-14T18:05:47"

"2022-11-15T16:11:30"

"2022-11-15T16:09:31"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "@lhoestq Good catch! This currently leads to an AttributeError (due to `writer` being None) on this line:\r\nhttps://github.com/huggingface/datasets/blob/fed1628d49a91f9ae259ddf6edbb252c7972d9a3/src/datasets/builder.py#L1552\r\n" ]

"2022-11-14T17:42:02"

"2022-11-15T18:26:48"

"2022-11-15T18:24:38"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5239). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-14T14:53:00"

"2022-11-14T15:27:10"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-14T14:52:55"

"2022-11-14T15:30:02"

"2022-11-14T15:27:35"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-14T14:46:57"

"2022-11-14T17:38:18"

"2022-11-14T17:35:59"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "> Not sure how we can have a test that is relevant for this though - feel free to add one if you have ideas\r\n\r\nYes, this was my reasoning for not adding a test. This change is pretty simple, so I think it's OK not to have a test for it." ]

"2022-11-14T14:38:59"

"2022-11-14T16:04:29"

"2022-11-14T16:01:48"

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"2022-11-14T13:17:02"

"2022-11-14T15:43:01"

"2022-11-14T13:41:12"

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"2022-11-14T12:47:40"

"2022-11-14T12:47:40"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-14T11:42:09"

"2022-11-14T14:16:03"

"2022-11-14T14:13:22"

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[ "Thanks for reporting, @vinaykakade.\r\n\r\nWe are discussing about making a release early this week.\r\n\r\nPlease note that in the meantime, in your specific case (as we also pointed out here: https://github.com/huggingface/datasets/issues/5162#issuecomment-1291720293), you can circumvent the issue by pinning `multiprocess` to 0.70.13 version (instead of using latest 0.70.14).\r\n\r\nDuplicate of:\r\n- https://github.com/huggingface/datasets/issues/5162", "You can also make `pip-compile` work by using the backtracking resolver (instead of the legacy one): https://pip-tools.readthedocs.io/en/latest/#a-note-on-resolvers\r\n```\r\npip-compile --resolver=backtracking requirements.in\r\n```\r\nThis resolver will automatically use `multiprocess` 0.70.13 version.\r\n" ]

"2022-11-12T06:46:23"

"2022-11-14T08:24:43"

"2022-11-14T08:07:59"

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[ "In case others find this, the problem was not with set_format, but my usages of `to_pandas()` and `from_pandas()` which I was using during dataset splitting; somewhere in the chain of converting to and from pandas the `Array2D/Array3D` types get converted to series of `Sequence()` types" ]

"2022-11-11T18:54:36"

"2022-11-11T20:42:29"

"2022-11-11T18:59:50"

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[ "I opened [this issue](https://github.com/python/cpython/issues/99401).\r\nPython's maintainers say that the issue is caused by [this change](https://docs.python.org/3.11/whatsnew/3.11.html#dataclasses).\r\nI believe adding a `__hash__` method to `datasets.utils.version.Version` should solve (at least partially) this issue.", "Has this been fixed? I am running into this issue now. \r\n\r\nIf this has been fixed, could have a new release with this?\r\n" ]

"2022-11-11T13:53:49"

"2022-11-14T20:51:44"

"2022-11-14T15:27:37"

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"2022-11-11T08:27:28"

"2022-11-11T10:28:16"

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[ "`load_dataset` first checks for a local directory before checking for the Hub.\r\n\r\nTo make it explicit that it has to fetch the Hub, we could support the `hffs` syntax:\r\n```python\r\nload_dataset(\"hf://datasets/glue\")\r\n```\r\n\r\nwould that work for you ? Also cc @mariosasko who's leading the `hffs` project", "yeah, that would be a fine solution." ]

"2022-11-11T00:51:54"

"2022-11-14T18:17:34"

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[ "Fixed. Please close." ]

"2022-11-10T21:57:06"

"2022-11-10T22:05:43"

"2022-11-10T22:05:43"

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[ "Hi ! Datasets are memory mapped from your disk, i.e. they're not loaded in RAM. This is possible thanks to the Arrow data format.\r\n\r\nTherefore the column you remove is not in RAM, so removing it doesn't cause the RAM to decrease.", "Thanks for the explanation! @lhoestq \r\nI wonder since it is memory mapped, can we reduce or remove this memory map?", "Yes you can `del common_voice` for example or wait for it to be garbage collected" ]

"2022-11-10T18:35:27"

"2022-11-16T13:20:39"

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"2022-11-10T17:36:11"

"2022-11-10T17:36:53"

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[ "I just tried to do the same but changing the `.wav` files to `.mp3` files and that doesn't fix it." ]

"2022-11-10T10:29:31"

"2022-11-10T10:45:29"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5223). All of your documentation changes will be reflected on that endpoint.", "I think we may want more content on this page that's not SQL related. Some of that content probably already lives in the main `load` docs page, but might be bad to remove major things like csv/pandas from there...WDYT we should do @lhoestq ?", "Maybe the main load page can only show one example and redirect to this page for more details ?\r\n\r\nWe can do the same for pandas stuff: have one example in load, and redirect to this page for more details", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5223). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-09T19:10:27"

"2022-11-15T17:40:25"

"2022-11-15T17:40:21"

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[ "cc @McPatate maybe you know what's happening ?", "Yes I think I know what is happening. We check in zips for pickles, and the UI must display the pickle jar when a scan has an associated list of imports, even when empty.\r\n~I'll fix ASAP !~", "> I'll fix ASAP !\r\n\r\nActually I'd rather leave it like that for now, as it indicates that we checked for pickles and nothing dangerous appeared :)", "Closing the issue with the typical \"feature not a bug\" " ]

"2022-11-09T16:41:16"

"2022-11-09T18:10:46"

"2022-11-09T18:06:57"

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[ "Did you run `huggingface-cli lfs-enable-largefiles` before committing or before adding ? Maybe you can try before adding\r\n\r\nAnyway I'd encourage you to split your data into several TAR archives if possible, this way the dataset can loaded faster using multiprocessing (by giving each process a subset of shards to process)", "@lhoestq \r\nThanks for the help!\r\n> Maybe you can try before adding\r\n\r\nIt did not help\r\n\r\nBut I totally got your point about split into multiple TAR archives. It really helped!" ]

"2022-11-09T15:32:05"

"2022-11-10T18:11:21"

"2022-11-10T18:11:11"

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[ "I think this behavior comes from PyArrow:\r\n```python\r\nimport pyarrow as pa\r\nt = pa.table({\"a\": [[0]]})\r\nt.to_pandas().a.values[0]\r\n# array([0])\r\n```\r\n\r\nI believe this has to do with zero-copy: you can get a pandas DataFrame without copying the buffers from arrow, and therefore end up with numpy arrays.", "That's interesting, I guess not much to do here then." ]

"2022-11-09T08:40:18"

"2022-11-10T16:12:26"

"2022-11-10T16:12:26"

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[ "Hi ! Interesting :) Can you provide concrete examples of cases where it can be useful ?" ]

"2022-11-09T02:43:56"

"2022-11-09T13:34:51"

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"2022-11-09T02:42:18"

"2022-11-09T02:42:36"

"2022-11-09T02:42:36"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-09T02:40:01"

"2022-11-10T01:38:09"

"2022-11-10T01:36:09"

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[ "Hi ! I think there exist tools to dump and reload an index in your elastic search but I'm not super familiar with it.\r\n\r\nAnyway after reloading an index in elastic search you can call `ds.load_elasticsearch_index` which will connect the index to the dataset without re-indexing" ]

"2022-11-08T23:06:52"

"2022-11-09T13:16:45"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5214). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-08T14:43:37"

"2022-11-08T15:39:58"

"2022-11-08T15:39:57"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5213). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5213). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5213). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-08T11:45:47"

"2022-11-15T10:19:51"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5212). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-08T07:30:01"

"2022-11-15T06:32:27"

"2022-11-15T06:32:26"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5211). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-07T15:23:52"

"2022-11-07T15:30:01"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5210). All of your documentation changes will be reflected on that endpoint.", "Nit: We should also update the `Disclaimers` section to let the dataset owners know they should use Hub discussions rather than GH issues for removal requests/updates" ]

"2022-11-07T14:51:23"

"2022-11-09T15:17:04"

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[]

[ "@merveenoyan Do you want different files to be splits or configurations?\r\n\r\nFrom [what you specified in `Readme.md`](https://huggingface.co/datasets/inria-soda/tabular-benchmark/commit/fb4575853772c62a20203bdd6cc0202f5db4ce4e) I hypothesize that you want to have 4 **configs** corresponding to directories: `\"clf_cat\", \"clf_num\", \"reg_cat\", \"reg_num\"`. And inside each config you require to have as many splits as there are `csv` files\r\nso if you run \r\n```python\r\nload_dataset(\"inria-soda/tabular-benchmark\", \"clf_cat\", split=\"compass\")\r\n```\r\nyou will generate the data only from `compass.csv` file.\r\nIn this case, running `load_dataset(\"inria-soda/tabular-benchmark\", \"clf_cat\"`) without split parameter will return `DatasetDict` object with `\"KDDCup09_upselling\", \"cat_compass\", \"cat_covertype\", ... \"road_safety\"` keys (which values are splits - `Dataset` objects)\r\n\r\n**or**\r\ndo you want each file to be a separate config? Like:\r\n```python\r\nload_dataset(\"inria-soda/tabular-benchmark\", \"clf_cat_compass\") # returns DatasetDict with a single \"train\" split\r\n```\r\n**or**\r\nmaybe smth completely different? :smile: \r\n\r\nAnyway, now I have an impression that this is probably rather a matter of automatically inferring configs from repository structure rather than providing parameters in metadata yaml.\r\n", "@polinaeterna I want the latter where you can think of every CSV file as a config, like MNLI from GLUE.", "@merveenoyan @lhoestq I see two solutions to this case. \r\n1. Parse configurations automatically from directories names. That is, if you have data structure like:\r\n```\r\ntabular-benchmark\r\n └─clf_cat_compass\r\n └─compass.csv\r\n └─clf_cat_cat_covertype\r\n └─covertype.csv\r\n ...\r\n └─reg_cat_house_sales\r\n └─house_sales.csv\r\n```\r\nyou'll get \"clf_cat_compass\", \"clf_cat_cat_covertype\", ... \"reg_cat_house_sales\" configurations that would contain **only files from corresponding directories**. \r\n**\\+** this is a requested change and needed in general and would solve other problems, see https://github.com/huggingface/datasets/issues/4578, would also help with https://github.com/huggingface/datasets/pull/5213 which I'm working on currently\r\n**\\+** would allow users to do just `load_dataset(“inria-soda/tabular-benchmark”, “clf_cat_compass”)`, no `data_files` param required\r\n**\\-** in this specific case it would require restructuring of the data - putting each file in a directory named as a config name (to me personally it doesn't seem to be a big deal) \r\n\r\n2. More or less what we discussed before - add support for manually specifying parameters in the metadata. We can add new metadata yaml field (say, `\"custom_configs_info\"`), so that we can provide smth like:\r\n```yaml\r\n---\r\n...\r\ndataset_info:\r\n ... \r\ncustom_configs_info:\r\n- config_name: reg_cat_house_sales\r\n data_files:\r\n - reg_cat/house_sales.csv\r\n- config_name: clf_cat_compass\r\n data_files:\r\n - clf_cat/compass.csv\r\n...\r\n---\r\n```\r\n**\\+** Would be useful not only for tabular data and not only for `data_files` parameter - any packaged dataset’s viewer can be customized to use specific, non-default parameters. @merveenoyan do you maybe have any other examples/use cases in mind where you want to provide any specific parameters to the viewer? \r\n**\\-** I'm not sure here but assume that it might require changes in interaction with the viewer on the hub side - to parse these configurations, as they not default configurations (not in `BUILDER_CONFIGS` list). cc @severo But probably this can be solved on the `datasets` side too.\r\n\r\nOverall, I would start from implementing the first solution since it's related to what I'm doing now and is super useful for `datasets` in general. And then if we agree that having more flexibility in providing parameters to the viewer is required, I can implement the second one. Let me know what you think :) ", "> We can add new metadata yaml field (say, \"custom_configs_info\"), so that we can provide smth like:\r\n\r\nLove it ! Some other ideas to name the \"custom_configs_info\" field: \"configs\", \"parameters\", \"config_args\", \"configurations\"\r\n\r\n> it might require changes in interaction with the viewer on the hub side - to parse these configurations, as they not default configurations (not in BUILDER_CONFIGS list)\r\n\r\nIf we update the `get_dataset_config_names()` function in `datasets` in inspect.py we should be fine - that's what the viewer is using\r\n\r\n> Overall, I would start from implementing the first solution since it's related to what I'm doing now and is super useful for datasets in general. And then if we agree that having more flexibility in providing parameters to the viewer is required, I can implement the second one. Let me know what you think :)\r\n\r\nActually I feel like the second solution includes the first use case you mentioned. If you implement the second solution, then users would just have to add a few lines of YAML and their directories would be considered configurations no ? Maybe there's no need to implement two different logics to do the same thing" ]

"2022-11-07T13:27:16"

"2022-11-09T17:19:48"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-07T09:25:05"

"2022-11-08T06:51:20"

"2022-11-08T06:49:17"

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[ "Hi ! It looks like an issue with your python environment, can you make sure you're able to run GET requests to https://huggingface.co using `requests` in python ?", "\r\nThanks for your reply. Does this mean that I have to use the `do_dataset `function and the `requests `function to download the dataset from the company's proxy environment?\r\n\r\n\r\n* Reference: \r\n```\r\n### How to load this dataset directly with the [datasets](https://github.com/huggingface/datasets) library\r\n\r\n\r\n* https://huggingface.co/datasets/moyix/debian_csrc\r\n\r\n\r\n* \r\nfrom datasets import load_dataset\r\ndataset = load_dataset(\"moyix/debian_csrc\")\r\n\r\n\r\n\r\n### Or just clone the dataset repo\r\n\r\n\r\ngit lfs install\r\ngit clone https://huggingface.co/datasets/moyix/debian_csrc\r\n# if you want to clone without large files – just their pointers\r\n# prepend your git clone with the following env var:\r\nGIT_LFS_SKIP_SMUDGE=1\r\n```", "You can use `requests` to see if downloading a file from the Hugging Face Hub works. If so, then `datasets` should work as well. If not, then you have to find another way using an internet connection that works" ]

"2022-11-07T06:56:23"

"2022-11-12T15:31:58"

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[ "Actually upon closer inspection, it is documented in the code that this behavior is intentional, so I'll close this." ]

"2022-11-05T23:48:02"

"2022-11-06T00:06:00"

"2022-11-06T00:05:59"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-05T23:36:36"

"2022-11-08T08:13:00"

"2022-11-07T16:20:24"

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[ "#self-assign", "@lhoestq can you close this issue as part of the recent #5205 merge? Thanks 🤗 ", "Thank you :)" ]

"2022-11-05T23:32:20"

"2022-11-08T10:12:09"

"2022-11-08T10:12:08"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-04T22:50:50"

"2022-11-07T18:43:05"

"2022-11-07T18:40:19"

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[ "Fix: https://huggingface.co/datasets/paws/discussions/1" ]

"2022-11-04T10:51:20"

"2022-11-04T10:51:37"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "It would be coherent with https://github.com/huggingface/datasets-server/issues/614#issuecomment-1290534153", "I think we started working on this issue nearly at the same time... :sweat_smile: \r\n- CI was fixed with this: https://huggingface.co/datasets/paws/discussions/1\r\n\r\nRelated issue:\r\n- #5202", "@albertvillanova yeah I noticed it right after the PR :smile: thank you! the fix of the dataset info yaml fixes tests on CI, but in general order of splits in yaml influences the order in which they are displayed in the viewer, if I understand it correctly. So I suggest not to sort splits in yaml initially to avoid this for other datasets in the future. I think [this change](https://github.com/huggingface/datasets/pull/5201/files#diff-198ba4fdf2f94cb3e1aba8a0170a43b08d4ab5636d682374321c5a383a8be24dR571) should work for it. \r\n\r\nChanges to tests here maybe can be reverted considering that order in yaml now corresponds to the one in tests, thanks to your change in the dataset info.", "Hehe, @polinaeterna, we make comments nearly at the same time as well... :laughing: " ]

"2022-11-04T10:47:21"

"2022-11-04T14:47:37"

"2022-11-04T14:45:09"

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[ "Thanks for catching this, I can go through the docs and replace the links to their corresponding datasets on the Hub!" ]

"2022-11-04T10:06:21"

"2022-11-07T18:40:20"

"2022-11-07T18:40:20"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-03T15:05:54"

"2022-11-04T14:01:50"

"2022-11-04T13:59:47"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-03T13:51:32"

"2022-11-04T12:47:59"

"2022-11-04T12:46:01"

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[ "@albertvillanova Please take a review.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5197). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-03T13:35:58"

"2022-11-03T13:45:19"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5196). All of your documentation changes will be reflected on that endpoint.", "@lhoestq I think we should first agree if `datasets` can introduce the breaking change of ignoring `config.HUB_DATASETS_URL`: some users may have override this.\r\n\r\nIf so, I then would suggest to initiate a deprecation cycle.", "After a discussion with the rest of the datasets team, we agreed we can introduce the breaking change of ignoring `config.HUB_DATASETS_URL`: this will have minimal impact, only for **private Hubs**. We will address eventual possible impacts in the future.\r\n\r\nAdditionally, we also ignore `config.HUB_DEFAULT_VERSION`.\r\n\r\nSee explanation in this PR description: https://github.com/huggingface/datasets/pull/5196#issue-1434401646" ]

"2022-11-03T10:08:09"

"2022-11-09T08:15:38"

"2022-11-09T07:15:12"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5195). All of your documentation changes will be reflected on that endpoint." ]

"2022-11-03T08:37:34"

"2022-11-03T08:42:53"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-03T07:10:23"

"2022-11-03T13:31:27"

"2022-11-03T13:29:21"

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[ "Also unrelated but still: https://huggingface.co/docs/datasets/image_dataset#generate-the-dataset\r\n```If your loading script passed the test, you should now have a dataset_infos.json file in your dataset folder.```\r\nIt's not the case anymore as it's now in the readme.md, it was confusing to me", "And here is my data loader script: https://huggingface.co/datasets/corentinm7/MyoQuant-SDH-Data/blob/main/SDH_16k.py\r\nI have one file archive to download that contains the images for all splits and one `metadata.jsonl` to download that contains the informations about what image goes into what split.", "Hi @lambda-science! It seems that your repo is recognized as a packaged module [ImageFolder](https://huggingface.co/docs/datasets/main/en/image_dataset#imagefolder), not as a dataset with the custom loading script, because loader looks for a script that has the same name as the dataset repo. So please try to rename your script to `MyoQuant-SDH-Data.py`, this should help.", "> Hi @lambda-science! It seems that your repo is recognized as a packaged module [ImageFolder](https://huggingface.co/docs/datasets/main/en/image_dataset#imagefolder), not as a dataset with the custom loading script, because loader looks for a script that has the same name as the dataset repo. So please try to rename your script to `MyoQuant-SDH-Data.py`, this should help.\r\n\r\nHi !\r\n\r\nThank you for your answer. That was... embarrassingly easy, sorry for this issue, everything is fixed now ! \r\n\r\nHave a nice day ! :)", "@lambda-science that's not embarrassing at all! it's actually not clear from the documentation that the script should have the same name, so thank you for the issue, we'll add this information to the docs :) " ]

"2022-11-02T22:46:25"

"2022-11-03T13:39:16"

"2022-11-03T13:35:44"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on that endpoint.", "> Nit: maybe we can use the count_path_segments function from this file for counting (updated with your logic to make it faster).\r\n\r\n@mariosasko just to make sure I understood you correctly - are you okay with this change? (actually `os.path.normpath` is redundant here as paths from `data_files` should be already normalized but just in case)\r\nhttps://github.com/huggingface/datasets/pull/5192/files#diff-1f09f7a178211f7539b1499b64b69793bd53b30c8b7b34cfcc5835e25d31929fR33\r\nIf you are, we can merge.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on that endpoint.", "awesome ! :D" ]

"2022-11-02T14:01:41"

"2022-11-15T16:32:53"

"2022-11-15T16:31:07"

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

"2022-11-02T13:56:18"

"2022-11-02T17:20:48"

"2022-11-02T17:18:42"

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[ "Hi! Yes, this is expected behavior - we do this as a security measure to not leak local paths (this info would be useless on other users' machines anyways) and only push audio bytes. \r\n" ]

"2022-11-02T11:51:25"

"2022-11-02T12:55:02"

"2022-11-02T12:55:02"

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[ "I have to admit I'm not a fan of this idea, as this would result in a non-consistent behavior between tabular and non-tabular datasets, which is confusing if done without the context you provided. Instead, we could consider returning a `Dataset` object rather than `DatasetDict` if there is only one split in the generated dataset. But then again, I think this lib is a bit too old to make such changes. @lhoestq @albertvillanova WDYT?\r\n\r\n", "We can brainstorm here to see how we could make it happen ? And then depending on the options we see if it's a change we can do.\r\n\r\nI'm starting with a first reasoning\r\n\r\nCurrently not passing `split=` in `load_dataset` means \"return a dict with each split\".\r\n\r\nNow what would happen if a dataset has no split ? Ideally it should return one Dataset. And passing `split=` would have no sense. So depending on the dataset content, not passing `split=` should return a dict or a Dataset. In particular, those two cases should work:\r\n```python\r\n# case 1: dataset without split\r\nds = load_dataset(\"dataset_without_split\")\r\nds[0], ds[\"column_name\"], list(ds) # we want this\r\n\r\n# case 2: dataset with splits\r\nds = load_dataset(\"dataset_with_splits\")\r\nds[\"train\"] # this works and can't be changed\r\nds = load_dataset(\"dataset_with_splits\", split=\"train\")\r\nds[0], ds[\"column_name\"], list(ds) # this works and can't be changed\r\n```\r\n\r\nI can see several ideas:\r\n1. allowing `load_dataset` to return a different object based on the dataset content - either a Dataset or a DatasetDict\r\n - we can update `get_dataset_split_names` to return None or a list if users want to know in advance what object will be returned. They can also use `isinstance` _a posteriori_\r\n - but in this case we expect users to be careful when loading datasets and always to extra steps to check if they got a Dataset or DatasetDict\r\n2. merge Dataset and DatasetDict objects\r\n - they already share many functions: map, filter, push_to_hub etc.\r\n - we can define `ds[0]` to be the first item of the first split, and consider that the uses accesses rows from the full table of all the splits concatenated\r\n - however there is a collision when doing `ds[\"column_name\"]` or `ds[\"train\"]` that we need to address: the first returns a list, while the other returns a Dataset.\r\n\r\nWhat are your opinions on those two ideas ? Do you have other ideas in mind ?", "I like the first idea more (concatenating splits doesn't seem useful, no?). This is a significant breaking change, so I think we should do a poll (or something similar) to gather more info on the actual \"expected behavior\" and wait for Datasets 3.0 if we decide to implement it.\r\n\r\nPS: @thomwolf also suggested the same thing a while ago (https://github.com/huggingface/datasets/issues/743#issuecomment-746074641).", "I think it's an interesting improvement to the user experience for a case that comes often (no split) so I would definitively support it.\r\n\r\nI would be more in favor of option 2 rather than returning various types of objects from load_dataset and handling carefully the possible collisions indeed", "Related: if a dataset only has one split, we don't show the splits select control in the dataset viewer on the Hub, eg. compare https://huggingface.co/datasets/hf-internal-testing/fixtures_image_utils/viewer/image/test with https://huggingface.co/datasets/glue/viewer/mnli/test.\r\n\r\nSee https://github.com/huggingface/moon-landing/pull/3858 for more details (internal)", "I feel like the second idea is a bit more overkill. \r\n@severo I would say it's a bit irrelevant to the problem we have but is a separate problem @polinaeterna is solving at the moment. 😅 (also discussed on slack)", "OK, sorry for polluting the thread. The relation I saw with the dataset viewer is that from a UX point of view, we hide the concepts of split and configuration whenever possible -> this issue feels like doing the same in the datasets library.", "I would agree that returning different types based on the content of the dataset might be confusing.\r\n\r\nWe can do something similar to what `fetch_*` or `load_*` from `sklearn.datasets` do, which is to have an arg which changes the type of the returned type. For instance, `load_iris` would return a dict, but `load_iris(..., return_X_y=True)` would return a tuple.\r\n\r\nHere we can have a similar arg such as `return_X` which would then only return a single `DataSet` or an array.", "> I feel like the second idea is a bit more overkill.\r\n\r\nOverkill in what sense ?\r\n\r\n> Here we can have a similar arg such as return_X which would then only return a single DataSet or an array.\r\n\r\nRight now one can already pass `split=\"all\"` to get one `Dataset` object with all the data in it (unsplit). We could also have something like `return_all=True` so make the API clearer.\r\n\r\n> I would be more in favor of option 2 rather than returning various types of objects from load_dataset and handling carefully the possible collisions indeed\r\n\r\nI think it would be ok to handle the collision by allowing both `ds[\"train\"]` and `ds[\"column_name\"]` (and maybe adding something like `ds.splits` for those who want to iterate over the splits or add new ones)", "Would it make sense to remove the notion of \"split\" in `load_dataset`? I feel a lof of it comes from the want to have some sort of group of more or less similar dataset. \"train\"/\"test\"/\"validation\" are the traditional ones, but there are some datasets that have much more splits.\r\n\r\nWould it make sense to force `load_dataset` to only load a single `Dataset` object, and fail if it doesn't point to one. And have another method that's like `load_dataset_group_info` that can return a very arbitrary info class (Dict, List whatever), but you need to pass individual infos to `load_dataset` to run anything? Typically I don't think `DatasetDict.map` is really that helpful, but that's my personal opinion. This would help make things more readable (typically knowing if an object is a `Dataset` or a `DatasetDict`)", "> Would it make sense to remove the notion of \"split\" in load_dataset?\r\n\r\nI think we need to keep it - though in practice people can name the splits whatever they want anyway.\r\n\r\n> Would it make sense to force load_dataset to only load a single Dataset object, and fail if it doesn't point to one.\r\n\r\nWe need to keep backward compatibility ideally - in particular the load_dataset + ds[\"train\"] one", "> I think we need to keep it - though in practice people can name the splits whatever they want anyway.\r\n\r\nIt was my understanding that the whole issue was that `load_dataset` returned multiple types of objects.\r\n\r\n> We need to keep backward compatibility ideally - in particular the load_dataset + ds[\"train\"] one\r\n\r\nYeah sorry I meant ideally. One can always start developing `load_dataset_v2` can deprecate the first one and remove it in the longer term.", "> It was my understanding that the whole issue was that load_dataset returned multiple types of objects.\r\n\r\nYes indeed, but we still want to keep a way to load the train/val/test/whatever splits alone ;)", "@thomasw21's solution is good but it will break backwards compatibility. 😅" ]

"2022-11-02T09:15:02"

"2022-11-08T18:52:29"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "Thanks @osanseviero. Am I good to merge? ", "I would wait for a second approval just in case :) ", "Sure :) ", "Merging since the images have been pushed as LFS files ([PR](https://huggingface.co/datasets/huggingface/documentation-images/discussions/8)). " ]

"2022-11-02T04:34:36"

"2022-11-04T18:25:57"

"2022-11-04T18:23:34"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "@nateraw I guess the failing test is unrelated. ", "@sayakpaul Yea failures are unrelated. ", "Alright. Will wait for @osanseviero's take and then merge. ", "FYI @stevhliu ", "@osanseviero @stevhliu @nateraw thank you for your comments. Acted on them.", "Thanks! Can I merge? Or should we wait for approvals from the others?", "Since @stevhliu approved as well, I think you're good to go", "Alright!\r\n\r\nMerging as a Member for the first time 🫀" ]

"2022-11-02T02:30:09"

"2022-11-03T01:52:24"

"2022-11-03T01:49:56"

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[ "Hi! The first `Dataset.from_sql` call also outputs the \"ImportError: Using URI string without sqlalchemy installed.\" message, but you also get \"During handling of the above exception another exception occurred: ...\" after which the ValueError is printed. I agree that this behavior makes it easy to miss the original error. \r\n\r\nI think we can improve this by not throwing the writer's ValueError if the error from a dataset script is already being handled to make debugging easier. @lhoestq @albertvillanova wdyt?", "Yup ! Alternatively the error can be raised in sql.py before generating the examples ? In `_info` for example", "yea @lhoestq that would probably be good. The 2nd error is useless if the 1st error is the real reason it failed. " ]

"2022-11-01T20:25:51"

"2022-11-15T18:24:39"

"2022-11-15T18:24:39"

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"2022-11-01T20:07:20"

"2022-11-01T20:07:34"

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"2022-11-01T13:18:29"

"2022-11-02T11:57:50"

"2022-11-02T11:57:50"

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