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https://github.com/huggingface/datasets/pull/8598
[httpx migration] Import httpx from huggingface_hub
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_8598). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
Direct httpx imports will break when huggingface_hub migrates to httpx2. This updates them to use the compatibility re-export introduced in https://github.com/huggingface/huggingface_hub/pull/4803, following the migration plan in https://github.com/huggingface/huggingface_hub/issues/4802. Goal is to make datasets compa...
[httpx migration] Import httpx from huggingface_hub Direct httpx imports will break when huggingface_hub migrates to httpx2. This updates them to use the compatibility re-export introduced in https://github.com/huggingface/huggingface_hub/pull/4803, following the migration plan in https://github.com/huggingface/hugging...
[ 0.09664132446050644, -0.3601100444793701, -0.06200414523482323, -0.07477857917547226, 0.1955280900001526, 0.09222032874822617, 0.13134528696537018, 0.31443706154823303, 0.20349138975143433, -0.009685147553682327, -0.3508707582950592, -0.30892273783683777, -0.03389598801732063, 0.2073323875...
https://github.com/huggingface/datasets/pull/8598
[httpx migration] Import httpx from huggingface_hub
Failing CI seems unrelated ``` FAILED tests/test_hub.py::test_delete_from_hub - huggingface_hub.errors.HfHubHTTPError: Server error '502 Bad Gateway' for url 'https://hub-ci.huggingface.co/api/datasets/__DUMMY_DATASETS_USER__/test-dataset-14a7d7-17890532107233/commit/main' For more information check: https://deve...
Direct httpx imports will break when huggingface_hub migrates to httpx2. This updates them to use the compatibility re-export introduced in https://github.com/huggingface/huggingface_hub/pull/4803, following the migration plan in https://github.com/huggingface/huggingface_hub/issues/4802. Goal is to make datasets compa...
[httpx migration] Import httpx from huggingface_hub Direct httpx imports will break when huggingface_hub migrates to httpx2. This updates them to use the compatibility re-export introduced in https://github.com/huggingface/huggingface_hub/pull/4803, following the migration plan in https://github.com/huggingface/hugging...
[ -0.06642121821641922, -0.18476155400276184, -0.04284598305821419, 0.018656481057405472, 0.22505217790603638, 0.0760914608836174, 0.10948563367128372, 0.31411659717559814, -0.03423465043306351, -0.1486196368932724, -0.31741487979888916, -0.1046658456325531, 0.1123252809047699, 0.44926166534...
https://github.com/huggingface/datasets/pull/8598
[httpx migration] Import httpx from huggingface_hub
cool ! I guess we need to bump the minimal version from 0.25.0 to 1.30.0 (both in setup.py and in the "minimum version" CI)
Direct httpx imports will break when huggingface_hub migrates to httpx2. This updates them to use the compatibility re-export introduced in https://github.com/huggingface/huggingface_hub/pull/4803, following the migration plan in https://github.com/huggingface/huggingface_hub/issues/4802. Goal is to make datasets compa...
[httpx migration] Import httpx from huggingface_hub Direct httpx imports will break when huggingface_hub migrates to httpx2. This updates them to use the compatibility re-export introduced in https://github.com/huggingface/huggingface_hub/pull/4803, following the migration plan in https://github.com/huggingface/hugging...
[ -0.16685202717781067, -0.32649412751197815, -0.11599967628717422, 0.006541070993989706, 0.2499535083770752, 0.04923224449157715, 0.05442256107926369, 0.524398148059845, 0.1537390798330307, -0.0491214320063591, -0.2734866142272949, -0.17101657390594482, -0.05267921835184097, 0.2569395303726...
https://github.com/huggingface/datasets/pull/8594
Forward max_buffer_input_shards from IterableDatasetDict.shuffle
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_8594). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
## What breaks `load_dataset(..., streaming=True)` without a split returns an `IterableDatasetDict`, and shuffling it cannot reach the shard-interleaving control: ```python ds = load_dataset("HuggingFaceFW/fineweb", streaming=True) ds = ds.shuffle(seed=42, buffer_size=10_000, max_buffer_input_shards=4) # TypeError: I...
Forward max_buffer_input_shards from IterableDatasetDict.shuffle ## What breaks `load_dataset(..., streaming=True)` without a split returns an `IterableDatasetDict`, and shuffling it cannot reach the shard-interleaving control: ```python ds = load_dataset("HuggingFaceFW/fineweb", streaming=True) ds = ds.shuffle(seed=...
[ -0.1987999975681305, -0.5981290936470032, -0.02844133973121643, 0.08585389703512192, -0.028091641142964363, -0.16591666638851166, 0.2601541578769684, 0.13958348333835602, -0.015885010361671448, 0.31751111149787903, -0.1113712340593338, 0.08701872080564499, -0.19547326862812042, 0.191598072...
https://github.com/huggingface/datasets/pull/8591
Better error when a column written as null gets values in a later batch
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_8591). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
On #2831 the map still fails at HEAD, as `TypeError: Couldn't cast array of type double to null` now rather than `ArrowInvalid`. Your 2021 comment on that issue has the mechanism and both workarounds; the error itself says none of it. So this does not change what the writer accepts. Before the cast, `ArrowWriter` now ...
Better error when a column written as null gets values in a later batch On #2831 the map still fails at HEAD, as `TypeError: Couldn't cast array of type double to null` now rather than `ArrowInvalid`. Your 2021 comment on that issue has the mechanism and both workarounds; the error itself says none of it. So this does...
[ 0.034668587148189545, -0.5024073719978333, 0.0644623190164566, -0.047000691294670105, 0.21944843232631683, -0.1634937822818756, 0.22597160935401917, 0.13186460733413696, 0.4030679762363434, 0.18253980576992035, 0.21798600256443024, 0.013955647125840187, -0.12735795974731445, 0.090035483241...
https://github.com/huggingface/datasets/pull/8589
Advance the user-supplied generator in Dataset.shuffle even on cache hits
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_8589). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
Fixes #7127. When a `np.random.Generator` is passed to `Dataset.shuffle`, the indices cache lookup returns before `generator.permutation(...)` is called, so the caller's generator never advances on a cache hit. Because the fingerprint is derived from the generator's state, the next call recomputes the same fingerpri...
Advance the user-supplied generator in Dataset.shuffle even on cache hits Fixes #7127. When a `np.random.Generator` is passed to `Dataset.shuffle`, the indices cache lookup returns before `generator.permutation(...)` is called, so the caller's generator never advances on a cache hit. Because the fingerprint is deriv...
[ 0.022823724895715714, -0.06085316091775894, 0.04495702311396599, 0.01178084034472704, 0.28447529673576355, -0.1268148571252823, 0.43660488724708557, 0.22514212131500244, -0.020861955359578133, 0.4828891158103943, -0.0699952021241188, 0.40311765670776367, -0.1867009699344635, 0.004238705616...
https://github.com/huggingface/datasets/pull/8585
Reject a non-callable generator in GeneratorConfig
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_8585). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
### The bug `GeneratorConfig` checks that `generator` is not `None`, but not that it is callable. A wrong type is only discovered during generation: ```python Dataset.from_generator([{"a": 1}]) ``` ``` DatasetGenerationError: An error occurred while generating the dataset caused by TypeError: 'list' object is not ...
Reject a non-callable generator in GeneratorConfig ### The bug `GeneratorConfig` checks that `generator` is not `None`, but not that it is callable. A wrong type is only discovered during generation: ```python Dataset.from_generator([{"a": 1}]) ``` ``` DatasetGenerationError: An error occurred while generating the d...
[ -0.07609846442937851, -0.2211441993713379, 0.014412201009690762, 0.01814841851592064, 0.34675800800323486, -0.09240495413541794, 0.10916101187467575, 0.20534390211105347, 0.1476440280675888, 0.36890295147895813, 0.07669489830732346, 0.2192411571741104, -0.3427641689777374, 0.15258485078811...
https://github.com/huggingface/datasets/pull/8577
Fix infinite repetition of empty iterable datasets
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_8577). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
Infinite repetition currently restarts an empty input indefinitely. For example, a streaming dataset filtered down to zero rows hangs in `dataset.repeat(None).take(1)` instead of finishing. The same problem affects an empty distributed shard and an Arrow input containing only zero-row tables. Stop infinite repetition ...
Fix infinite repetition of empty iterable datasets Infinite repetition currently restarts an empty input indefinitely. For example, a streaming dataset filtered down to zero rows hangs in `dataset.repeat(None).take(1)` instead of finishing. The same problem affects an empty distributed shard and an Arrow input containi...
[ -0.14178752899169922, -0.23508508503437042, -0.04093222692608833, -0.19054226577281952, 0.05191263183951378, -0.28301629424095154, 0.2730185389518738, 0.2044234722852707, 0.16221871972084045, 0.2867491841316223, 0.13459615409374237, 0.10861001163721085, -0.17637395858764648, 0.184957802295...
https://github.com/huggingface/datasets/pull/8575
Fix async map checkpoint accounting across repeated resumes
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_8575). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
Resuming an iterable dataset with an asynchronous map function works once, but a checkpoint captured during the resumed iteration can skip additional examples on the next resume. A deterministic identity coroutine over IDs 0–9, checkpointed after two outputs and again after one more output, produces `[0, 1, 2, 5, 6, 7,...
Fix async map checkpoint accounting across repeated resumes Resuming an iterable dataset with an asynchronous map function works once, but a checkpoint captured during the resumed iteration can skip additional examples on the next resume. A deterministic identity coroutine over IDs 0–9, checkpointed after two outputs a...
[ -0.31582894921302795, 0.008758404292166233, -0.08455117791891098, -0.35339200496673584, -0.1498624086380005, -0.3290441930294037, 0.44311338663101196, 0.2504814565181732, -0.1256839632987976, -0.11365680396556854, 0.1310632973909378, 0.45841413736343384, -0.0701218843460083, -0.10305752605...
https://github.com/huggingface/datasets/pull/8569
Shard the sources when skipping a distributed IterableDataset
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_8569). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.
`SkipExamplesIterable.shard_data_sources` returned `self` when `split_when_sharding` is False, so a `.skip()` applied after `split_dataset_by_node` threw the sharding away and every rank iterated the whole dataset. `TakeExamplesIterable` already handles that branch by sharding the sources and leaving `n` alone, so this...
Shard the sources when skipping a distributed IterableDataset `SkipExamplesIterable.shard_data_sources` returned `self` when `split_when_sharding` is False, so a `.skip()` applied after `split_dataset_by_node` threw the sharding away and every rank iterated the whole dataset. `TakeExamplesIterable` already handles that...
[ -0.1972104161977768, -0.2527852952480316, -0.004973702132701874, -0.004438798408955336, 0.05931602790951729, -0.17621886730194092, 0.32067251205444336, 0.20271195471286774, -0.06326252222061157, 0.33627304434776306, -0.18997468054294586, 0.16454914212226868, 0.004600999876856804, 0.1173225...
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