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value:## Summary `NumpyFormatter._consolidate` only stacks a column when every element is an `np.ndarray`. Numpy scalars are `np.generic`, not `np.ndarray`, so any path that hands the formatter a list of scalars falls into the `dtype=object` branch: - `IterableDataset.batch()` regroups with a python transpose (`{k: [...
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value:### Describe the bug `NumpyFormatter._consolidate` builds a typed array only when every element is an `np.ndarray`. numpy **scalars** are `np.number`, not `np.ndarray`. ### Face 1 — `IterableDataset.batch()` on an arrow-backed dataset `.batch()` regroups via a Python transpose (`_batch_fn = lambda unbatched: {...
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value:Fixes the remaining indexed-export slowdown described in #3419. Non-contiguous selections and shuffles still leave an indices mapping. Querying a JSON export batch then produces one Arrow chunk per selected row, making conversion to pandas expensive. Combine the queried batch before conversion, while keeping the...
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value:## Summary Eight checks in the library validate a split name with `re.match(_split_re, name)` and, when it fails, raise `Split name should match '^\w+(\.\w+)*$' but got '<name>'`. The message promises a full match, but `"$"` also matches right before a newline at the end of the string, so a name such as `"train\...
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value:Fixes #8659. With declared languages, `TranslationVariableLanguages` raises a `ValueError` for `{}`, `{"en": []}`, and other inputs containing no translations. Return `{"language": [], "translation": []}` when normalization produces no translation pairs, after validating the language names. Regression tests cov...
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value:## Describe the bug With an explicit language list, `TranslationVariableLanguages.encode_example()` raises `ValueError: not enough values to unpack (expected 2, got 0)` for `{}`, `{"en": []}`, or `{"en": [], "fr": []}`. The same inputs also prevent `Dataset.from_dict()` from constructing a dataset. The equivale...
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value:An IterableDataset can have unknown features (features=None), e.g. when built with IterableDataset.from_generator() without `features=`, or when streaming CSV files (or JSON files that require a full read) without declared features. IterableDataset._push_parquet_shards_to_hub() then crashed at the decodable-co...
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value:The docs and a few docstrings still use commands that are no longer the recommended `huggingface_hub` usage in 1.x: `hf` replaced `huggingface-cli`, `hf repos` replaced `hf repo`, and `--organization` was replaced by a namespaced repo id. - `docs/source/share.mdx`: `huggingface-cli login` → `hf auth login`, `hug...
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value:Serializing an in-memory PIL image through `Image` drops its EXIF orientation before decoding can apply the transpose added in #6739. The same JPEG with orientation 6 is decoded as `(4, 8)` when supplied as bytes, but `(8, 4)` when supplied as `PIL.Image.open(BytesIO(...))`. This also reproduces on the 5.0.1 rele...
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value:`size_str()` documents that it returns `"Unknown size"` when `size_in_bytes` is `None`: ```python def size_str(size_in_bytes): """Returns a human readable size string. If size_in_bytes is None, then returns "Unknown size". ... """ if not size_in_bytes: return "Unknown size" ``` The ...
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value:Fixes #8653. Long lock filenames are shortened with Python's process-randomized string hash. Independent processes can therefore acquire different lock files for the same original path, bypassing mutual exclusion. This can affect the cache-directory lock in `DatasetBuilder`, where the directory path is flattened...
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value:### Describe the bug `FileLock.hash_filename_if_too_long()` uses Python's `hash(filename)` to shorten long lock filenames. String hashes vary between independently started Python processes, so two processes given the same long lock path can lock different files and both enter the protected section. This affects...
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value:`pandas_read_json()` in `packaged_modules/json/json.py` calls `pd.read_json()` with pandas' default float parser, which is fast but not round-trip exact: ```python >>> import io, pandas as pd >>> pd.read_json(io.StringIO('{"v": 0.7}\n'), lines=True)["v"][0] np.float64(0.7000000000000001) >>> pd.read_json(io.Stri...
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value:Closes #8373. ## Summary - passes the new Python 3.14 `_batch_setitems` object argument when the custom datasets pickler is called through the old two-argument path - keeps the existing key sorting behavior for stable fingerprints - adds a regression test that simulates the Python 3.14 parent pickler sign...
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value:## Summary When datasets are stored in nested remote directories, loading a child directory first can make loading its parent fail with `FileNotFoundError` for `state.json`. Reloading a remote dataset after its contents change can also return the previous rows. Each load now gets a fresh directory inside the ma...
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value:`convert_file_size_to_int` already distinguishes bits from bytes: a unit ending in a lowercase `b` is read as bits and divided by 8. That check is only applied to the decimal branches, though, so the binary ones return a bit size as if it were bytes, eight times larger than asked for: ```python >>> from datasets...
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value:Apply the bit-to-byte conversion to binary units too
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value:## Problem The `eval` packaged module reads sample log JSON files with the locale's preferred encoding: ```python for sample_file in sample_files: with open(sample_file) as f: sample = json.load(f) ``` On Windows with a non-UTF-8 locale (e.g. cp936/GBK), any sample containing non-ASCII text — CJK p...
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value:Pin UTF-8 encoding when reading eval sample logs
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value:`list(dataset.filter())` raises `TypeError` because the iterator tries to call `None`. The documented default is to keep all rows. Return a new dataset wrapper when no function is supplied. Returning a new object, rather than `self`, keeps changes to its epoch from affecting the input dataset. Tests cover t...
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value:Fixes #8386. When `drop_last_batch=True` and a shard is smaller than `batch_size`, `_map_single` iterates zero batches, so the map function never runs and `update_data` stays `None`. The final branch then yielded the original shard back unchanged (3 rows instead of 0), disagreeing with `IterableDataset.batch` an...
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value:Fixes #6267 class_encode_column currently rejects list-valued columns even when the feature is List(Value(...)). That makes multi-label datasets fall back to manually collecting labels and calling cast_column. This change accepts List(Value(...)) columns, collects class names from the list elements, and maps ea...
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value:## Description When `set_pytorch=True` is passed to `temp_seed`, the context manager saves and restores the PyTorch CPU and CUDA RNG states. On non-CUDA accelerators (e.g. Ascend NPU), the device RNG state is silently left unseeded during the context, breaking reproducibility across seeded dataset transforms. T...
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value:## What `DatasetDict.cast` now accepts the same processing arguments as `Dataset.cast` (`batch_size`, `keep_in_memory`, `load_from_cache_file`, `writer_batch_size`, `num_proc`) plus `cache_file_names` as a per-split dict, and forwards them to each split. ## Why `Dataset.cast` runs through `map` and exposes the...
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value:Follows the discussion on #8558. Separate PR because that one fixes call sites in the builders and this fixes the writer itself, so they can be reviewed or reverted independently. @lhoestq happy to fold them together if you would rather have one change. Line numbers below are against `main`. ## The problem `fi...
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value:Towards #4964. This reduces the construction overhead rather than removing it, and the numbers below say by how much. ### What is slow Building a `Dataset` from a whole ndarray converts it row by row and then concatenates. On this machine, 3200 rows of 64x64 float32, a 50 MB payload: | | peak RSS over baseline...
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value:Closes #4352. ### The problem When a `map()` function returns values that do not match the declared features, the error never says which column is at fault. On a wide dataset that leaves you bisecting your own function to find it. Measured on `main`, all four mismatch shapes: | case | before | |---|---| | dec...
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value:Closes #5517. ### What users hit A column stored as `float64` comes back as `float32`: ```python >>> ds = Dataset.from_dict({"v": [[3.141592653589793, 1e300]]}, ... features=Features({"v": List(Value("float64"))})) >>> ds.with_format("numpy")[0]["v"] array([3.1415927e+00, inf],...
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value:Closes #6744. ### The problem `load_dataset` takes cache locks through `filelock`, which uses `flock`/`fcntl`. Some network filesystems do not implement those calls, so the lock fails and the dataset never loads. The reporter hit this on an NFS-mounted Weka mount. Moving `cache_dir` to local disk is not a way o...
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value:### Describe the bug `datasets.utils._filelock.FileLock` silently discards every keyword argument except `lock_file`. Passing `timeout=` has no effect, and `is_singleton=True` raises instead of returning the cached lock. The wrapper declares a variadic signature: ```python # src/datasets/utils/_filelock.py def...
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value:Automated hardening of the workflow files flagged on #8635. > [!WARNING] > **This narrows what the workflow can reach.** Job permissions were declared in `.github/workflows/ci.yml`, `.github/workflows/release-conda.yml`. Each job now gets only the scopes its steps were read to need — if one of them does somethin...
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value:Fixes #6829. ### Problem Calls passing `pathlib.Path` objects (e.g. `ds.save_to_disk(Path(...))`, `Dataset.load_from_disk(Path(...))`, `DatasetDict.load_from_disk(Path(...))`, `DatasetInfo.from_directory(Path(...))`) fail with `TypeError: argument of type 'PosixPath' is not iterable` from `fsspec` because `url_t...
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value:url_to_fs expects a str and raises an error when given a pathlib.Path. This was a regression introduced in #6704, which changed load_from_disk and save_to_disk to use url_to_fs directly without converting Path to str. Fix: wrap dataset_path with str() before passing to url_to_fs in both load_from_disk and save...
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value:Fixes #8381. Picks up #8382 after [the original author handed it over](https://github.com/huggingface/datasets/issues/8381#issuecomment-5675668289). The original fix is by @ebarkhordar. `to_dict()` and `to_polars()` return generators even with `batched=False`, because both methods contain a `yield` in their batc...
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value:Fixes #8596. Validate `ClassLabel` values during table casts while keeping the metadata-only path for other features.
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value:Two tests evaluate a comparison and throw the result away, so those checks can never fail. **`tests/test_builder.py::test_builder_as_dataset`**: `dataset.column_names == ["text"]` is missing its `assert`. **`tests/commands/test_test.py::test_test_command`**: the loop over `DatasetInfo._INCLUDED_INFO_IN_YAML` en...
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value:`Dataset.map()` creates an event loop for an async callback but never closes it. When a callback fails, gathering the cancelled tasks can also propagate the first failure before sibling callbacks finish their asynchronous cleanup. Move task cleanup into `finally`, wait for all tracked tasks with `return_except...
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value:## What `tests/test_extract.py::test_tar_extract_insecure_files` errors in setup on an unprivileged Windows machine: ``` OSError: [WinError 1314] A required privilege is not held by the client ``` The `tar_file_with_sym_link` fixture calls `os.symlink(...)` unconditionally, and the test requests all three tar ...
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value:Fixes #8626. When probabilistic `interleave_datasets` uses `all_exhausted_without_replacement`, an empty source starts as not exhausted. Its first draw appends an invalid source offset, producing a duplicate row from the next dataset or an `IndexError` when the empty source is last. Mark empty sources exhausted...
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value:### Describe the bug With probabilities and `stopping_strategy="all_exhausted_without_replacement"`, an empty map-style input can add a duplicate row from another source or cause an out-of-range index. This can happen when filtering one of the datasets before mixing them. ### Steps to reproduce ```python from ...
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value:Five public docstrings document parameters under names the functions don't accept, so code written from the docs fails with `TypeError: got an unexpected keyword argument`: | Function | Docstring says | Signature has | |---|---|---| | `Dataset.train_test_split` | `train_cache_file_name`, `test_cache_file_name` |...
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value:## Summary Fixes #8618. `DataFilesList.filter()` returns a filtered list of data files but reuses the original, unfiltered `origin_metadata`. `origin_metadata` is parallel to the file list (one entry per file describing where the file was resolved from), so after filtering it no longer lines up with the files i...
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value:## Summary Fixes #8617. `SplitDict.copy()` crashes with `AttributeError: 'SplitInfo' object has no attribute 'get'` whenever the `SplitDict` holds `SplitInfo` objects (the normal case after construction) and `dataset_name` is not passed explicitly. In `SplitDict.from_split_dict`, the `dataset_name` fallback un...
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value:## Description `DataFilesList` keeps `origin_metadata`, a list parallel to the file list where each entry describes the origin of the file at the same index (e.g. the data files pattern it was resolved from). After `filter()` removes some files, the returned `DataFilesList` keeps the *unfiltered* `origin_metadat...
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value:## Description `SplitDict.copy()` (and `SplitDict.from_split_dict`) crashes with `AttributeError: 'SplitInfo' object has no attribute 'get'` whenever the split dict contains `SplitInfo` objects and `dataset_name` is `None`. ## Reproduction ```python from datasets import SplitDict, SplitInfo split_dict = Split...
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value:### Summary Adds focused unit tests in `tests/test_dataset_name_invariants.py` verifying repository path identifier parsing: - Confirms organization namespace and dataset name separation. - Validates clean fallback handling for unnamespaced identifiers. - Non-invasive, test-only addition.
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value:Resolves #4661 ## Root cause `ExtractManager.extract` decided "already extracted" (output file exists, or output directory non-empty) **before** `Extractor.extract` took the per-output `FileLock`, and the extractor wrote straight into the final path. With two jobs sharing a cache directory, job B saw job A's ha...
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value:`load_dataset` on a dataset name with no namespace fails at HEAD and on 5.0.1: ```python >>> from datasets import load_dataset >>> load_dataset("imdb", split="train[:5]") ... File "src/datasets/load.py", line 609, in get_module standalone_yaml_path = cached_path( File "src/datasets/utils/file_utils.py", ...
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value:Resolves #1992 ## Root cause `Dataset.map(num_proc>1)` shards the table with Arrow slices (`table.slice`), and Arrow slices share their parent buffers. When a shard is pickled for a worker, `InMemoryTable.__getstate__` serializes the sliced arrays' full buffers, so every worker receives the whole table. A 2-pro...
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value:Send map workers only their shard's rows instead of the whole table
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value:Resolves #2643 ## Root cause `dill` serializes a class it cannot import by its module path through `_create_type`, which rebuilds the class from `type(name, bases, dict)`. That path cannot rebuild an `Enum`: the members, `_value2member_map_`, aliases, Flag boundary and slot descriptors are produced by `EnumMeta...
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value:Fixes #8608. `_get_updated_dataset_card` updates the splits and sizes of the existing `dataset_info` when a config is re-pushed, but never assigns the pushed `features` to it. Re-pushing a dataset's only split with different columns therefore leaves the card declaring the previous schema while the shards ho...
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value:### Describe the bug Re-pushing a dataset's only split with different columns updates the shards and the split sizes in the README, but silently keeps the **old** `dataset_info.features`. The card then declares a schema the parquet files no longer have, and the dataset viewer fails on the first batch with `CastE...
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value:`push_to_hub()` keeps stale `dataset_info.features` when re-pushing a single split with different columns
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value:Tiny docs fix: remove duplicate `to` in the Dataset push_to_hub save instructions.
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value:## Summary Implement `construct_from_string` on `PandasArrayExtensionDtype`: parse `array[<dtype>]` into a `PandasArrayExtensionDtype`, and raise `TypeError` for anything else (how pandas spells "not my dtype" in `__eq__`). Provenance: pandas extension-dtype docs, and the reproduction on `main` in #8467 (pandas ...
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value:## Summary Restore the early return in `Pickler._batch_setitems` that honours `_legacy_no_dict_keys_sorting`, keeping the `*args` / `**kwargs` passthrough from `#7817`. `#7817` updated `Pickler._batch_setitems` for Python 3.14's extra argument and, in the same hunk, dropped that return. `_check_legacy_cache2` st...
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value:Resolves #5531 ## Root cause The invalid Arrow data comes from pyarrow's JSON reader, not from `datasets`: when a list column's first non-empty value in a block starts with `null` (e.g. `{"a": [null, 1]}`), type inference can drop the leading null while the offsets still count it, so the table's list offsets sp...
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value:Resolves #7738. Closes #887 (dynamic leading dimensions, e.g. `Tensor(shape=(None, 137, 2))`, with `to_pandas` and `map` covered by the tests). This adds a `Tensor(shape, dtype)` feature for multi-dimensional arrays whose dimensions can vary from row to row, following the direction discussed in the issue: fixed ...
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value:## What does this PR do? `build_pr_documentation.yml` keys its concurrency group on `github.head_ref`, which is the head branch name without the fork owner. Two open PRs from different forks whose branches share a name therefore land in the same group, and a push on one cancels the in-flight doc build on the oth...
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value:Resolves #6290. `push_to_hub` replaced every shard of a split on each call, so growing a dataset meant re-uploading all of it. This adds `append=True` to `Dataset.push_to_hub` and `DatasetDict.push_to_hub`, following the approach discussed in the issue: download the last Parquet shard of the target split, copy i...
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value:`BioSequence.decode_example` and `BioStructure.decode_example` wrap the stored bytes in `StringIO` with its default newline handling, which only splits on `\n`. A record with bare-CR line endings therefore reaches Biopython as one line: FASTQ fails with "Unexpected end of file", FASTA decodes to an empty sequence...
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value: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...
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value:[httpx migration] Import httpx from huggingface_hub, require huggingface_hub>=1.31.0
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value:Fixes #8595. `_apply_async` polled `future.ready()` in an `await asyncio.sleep(0)` loop. With the in-flight cap at `2 * num_threads`, that many hot loops keep the event loop thread holding the GIL, starving the ThreadPool threads it is waiting on — in stack dumps a pool worker took 45+ seconds to get through `ss...
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value:### Describe the bug Loading a file whose parsed Arrow dtype already matches a declared `ClassLabel`'s storage type (`int64`) skips the range check entirely. Out-of-range indices load with no error and no warning, and only surface later at `int2str` time or as silently wrong labels during training. ```python fr...
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value: ### Describe the bug `decode(num_threads=N)` (added in #7450, "speeds up streaming up to 20 times") schedules the sync `decode_example` calls onto a `multiprocessing.pool.ThreadPool` and bridges them into the async map machinery with a busy-poll (`iterable_dataset.py`): ```python async def _apply_async(pool, f...
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value:IterableDataset.decode(num_threads) busy-polls its ThreadPool futures, starving the decode threads — 0 rows on remote audio; callback-based bridging restores the intended 20x
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value:## 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) # TypeEr...
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value:Fixes #5967. When `Dataset.map()` recombines multiple shards, it drops the source split. It also loses metadata such as `config_name` when the shards infer different compatible features (for example, a new column is null throughout the first shard and integer-valued in the second). Pass a copy of the source inf...
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value:This fixes mypy errors when passing list of paths to `Dataset.from_parquet()`, `from_csv()`, `from_json()`, `from_text()`, and `IterableDataset` equivalents. **Problem**: `List` is invariant while `Sequence` is covariant, so passing a `List[str]` to a function expecting `Union[PathLike, List[PathLike]]` fails ty...
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value: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...
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value:### What changed Between 4.8.4 and 4.8.5, checksum recording flipped from on to off by default in two places. From the sdists: ``` 4.8.4 src/datasets/download/download_manager.py:80 record_checksums=True 4.8.5 src/datasets/download/download_manager.py:80 record_checksums=False 4.8.4 src/datasets/utils/i...
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value:record_checksums default changed True -> False in 4.8.5, not in the release notes
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value: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 fin...
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value:### What is wrong `TranslationVariableLanguages` declares `languages` as optional, but building one without it makes every example fail to encode. ```python >>> from datasets import Dataset, Features >>> from datasets.features.translation import TranslationVariableLanguages >>> TranslationVariableLanguages().en...
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value:## What this changes I've fixed `flatten()` losing a selected struct's formatted columns. Its old name stays in the selection after flattening, so indexing can return an empty batch instead of the selected values. The fix flattens the selected features alongside the schema. It keeps unselected descendants exclu...
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value:### The bug `metadata_filenames` is only ever used as a membership test: ```python metadata_filenames = self.config.metadata_filenames or self.METADATA_FILENAMES ... elif os.path.basename(original_file) in metadata_filenames: ``` If it is a bare string rather than a list, `in` becomes a **substring** test: ``...
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value:### 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 i...
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value:### The bug `load_dataset("xml", ...)` fails for **every** input: ```python open("a.xml", "w").write("<root><a>1</a></root>") load_dataset("xml", data_files="a.xml", split="train") ``` ``` DatasetGenerationError: An error occurred while generating the dataset caused by FileNotFoundError: [Errno 2] No such fi...
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value:Fix the xml loader, which cannot load any file
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value:`to_csv()` hands the Arrow batch to pandas, and pandas renders a list cell with numpy's repr. So it comes out space separated, and past numpy's summarization threshold of 1000 the middle is elided: a 1500-element list is written as `[ 0 1 2 ... 1497 1498 1499]` and 1494 values are gone. Struct columns and...
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value:`benchmarks/benchmark_array_xd.py` defines `read_unformated` / `read_batch_unformated` / `read_col_unformated` (all call sites internal to the file). Renamed to `read_unformatted` / `read_batch_unformatted` / `read_col_unformatted`.
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value:`src/datasets/load.py`: "dataset loaded from data files of **a a** Storage Bucket" → "of a Storage Bucket". Docs-only.
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value:`docs/source/about_map_batch.mdx` and `docs/source/stream.mdx` both link an in-page `#map` anchor, but neither file has a Map heading — the "Map" section lives in `docs/source/process.mdx` (`## Map`). Both links now target `/process#map` (doc-builder cross-file style).
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value:`GeneratorBasedBuilder.as_dataset(self, split=None, in_memory=False)`'s docstring documents a `verification_mode` parameter (with an `<Added version="2.9.1"/>` tag). The parameter belongs to `download_and_prepare`, not `as_dataset`. The stale block is removed (the `download_and_prepare` docstring's own entry is u...
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value:`Dataset.train_test_split`'s docstring documents `train_cache_file_name` and `test_cache_file_name`; the actual parameters are `train_indices_cache_file_name` and `test_indices_cache_file_name`. The two docstring entries renamed to match. Docs-only.
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value: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 repet...
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value:`Dataset.to_parquet(..., compression="gzip")` raises `TypeError: ParquetWriter() got multiple values for keyword argument 'compression'` on current main. Explicit `use_dictionary` and `column_encoding` options fail for the same reason: the writer supplies defaults as named arguments while leaving the caller's val...
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value: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,...
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value:### What Adds a small worked example to the "nested field" JSON section of the loading guide (`docs/source/loading.mdx`), right after the existing `field="data"` example, showing the same mechanism applied to an eval/benchmark run's results file: ```py {"version": "1.1.0", "suite_id": "image-description-suite"...
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value: Fixes #8572 A source with no rows still contributes its columns, so horizontal concatenation has to check its row count like any other source. The empty-source filter in `_concatenate_map_style_datasets` ran before the axis dispatch, so on `axis=1` a 0-row source was removed before the "Number of rows must matc...
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value: `concatenate_datasets([ds1, ds2], axis=1)` returns a dataset without `ds2`'s columns when `ds2` has 0 rows, and raises nothing. The row-count check that rejects every other length mismatch never runs. ### Steps to reproduce ```python from datasets import Dataset, Features, Value, concatenate_datasets ds1 = Da...
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value:# What does this PR do? Fixes #8570 This PR adds a comprehensive and high-quality Simplified Chinese translation of the project's README (`README.zh.md`) and establishes a seamless bidirectional language switcher in both English and Chinese documentation. ## Summary of Changes - **New File `README.zh.md`**: F...
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value:### Motivation 🤗 Datasets is a fundamental library widely used by researchers, data scientists, and developers worldwide, with a large and active Chinese-speaking developer and research community. Providing an accurate, idiomatic Simplified Chinese translation (`README.zh.md`) along with a language switcher wi...
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value:`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, s...
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value:### Describe the bug Calling `.skip()` on an iterable dataset that already went through `split_dataset_by_node` cancels the node split. Each rank then iterates every shard, so a distributed run sees each example `world_size` times. `SkipExamplesIterable.shard_data_sources` returns `self` when `split_when_shardi...
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value:Fixes `repace` → `replace` in `templates/README_guide.md` (the template used to generate dataset guides, so the typo propagates). Docs-only change.
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value:`Pdf.decode_example` on a remote path outside the Hub raised before any download: ``` >>> Pdf().decode_example({"path": "https://example.com/a.pdf", "bytes": None}) TypeError: 'NoneType' object is not subscriptable # src/datasets/features/pdf.py:158 ``` `string_to_dict` returns `None` when the URL does not ma...
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value:Closes #8253 by adding the explicit splitting-strategy argument that @lhoestq asked for in that thread. ```python split_dataset_by_node(ds, rank, world_size, strategy="auto" | "shards" | "examples") ``` - `"auto"`: unchanged. Shards are assigned when `num_shards % world_size == 0`, otherwise each node keeps one...
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value:### What breaks Four feature classes show a repr in their `Examples` block that they cannot print. ``` >>> ds.features["image"] Image(decode=True, id=None) ``` `Image`, `Pdf`, `Nifti` and `Video` all declare `id: Optional[str] = field(default=None, repr=False)`, so `id=None` never appears. On top of that `Imag...
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value:Print the repr these feature examples actually produce
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