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value:`PandasArrayExtensionArray._concat_same_type` can turn whole input batches into individual rows. For example, concatenating dense batches with 2 and 1 rows returns 2 rows instead of 3, with an extra batch dimension inside each row. A single input chunk is also wrapped as one row. Equally sized object-backed chunk...
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value:## Summary Related to #6046. Forward the configured DownloadConfig.user_agent to fsspec HTTP/HTTPS requests. - Reuse the existing get_datasets_user_agent() helper. - Preserve explicitly configured User-Agent headers. - Keep existing HTTP proxy handling unchanged. - Add regression tests for default and custom h...
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value: ## What does this PR do? Fixes #8859 Concatenating the same datasets using different axes can produce the same fingerprint. As a result, `map()` can reuse cached results from the wrong concatenation without warning. This change adds `axis` to the existing fingerprint calculation and adds two regression tests ...
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value:Since #8791, `load_dataset(..., streaming=True)` decodes media datasets from the Hub in worker threads, and `IterableDataset.decode()` replaces that threaded step when it finds it as the last step of the dataset (`MappedExamplesIterable.decoding_pool`). `MappedExamplesIterable.shard_data_sources`, `shuffle_data_...
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value:### Describe the bug Since #8791, `load_dataset(..., streaming=True)` decodes media datasets from the Hub in worker threads by default. `decode()` replaces that threaded decoding step when it is the last step of the dataset, but `shard()` loses track of it. After `ds.shard(...)`, `ds.decode(False)` keeps yieldin...
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value:When an async-mapped `IterableDataset` creates an event loop for iteration, it retains that loop without closing it. Repeated epochs therefore leak file descriptors. Early iterator closure also leaves pending callbacks without completing their asynchronous cleanup. Track loop ownership per iterator, settle that ...
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value:`Dataset.push_to_hub()` can upload path-only records for images or audio nested inside a struct, `List`, or `LargeList` when `decode=False`, even with `embed_external_files=True`. The resulting Parquet shards refer to files on the uploader's machine instead of containing their bytes. Use the existing recursive `...
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value:HDF5 compound records can contain numeric array fields, such as `np.dtype([("id", "int32"), ("values", "float32", (3,))])`. Loading this valid file currently raises `TypeError: 'NoneType' object is not iterable` during schema inference: the subarray dtype is mistaken for another compound record. Keep the field d...
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value:### Describe the bug Concatenating the same disk-backed datasets using different axes gives the same fingerprint, even though the resulting datasets are different. As a result, calling `map()` on one can reuse the cached results of the other without warning. In the example below, a dataset with two rows of pair...
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value:concatenate_datasets reuses preprocessing caches across different axes
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value:A split slice whose end falls one row before its start returns the rest of the split instead of nothing: ```python import pathlib, tempfile from datasets import load_dataset path = pathlib.Path(tempfile.mkdtemp()) / "data.csv" path.write_text("x\n" + "\n".join(map(str, range(10))) + "\n") print(list(load_datase...
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value:Creating a new decoding view from a threaded `IterableDataset` currently shuts down the original dataset's decoding pool. If an existing iterator has prefetched examples queued behind active decoders, calling `ds.decode(False)` or changing its thread count cancels those examples. Continuing the original iterator ...
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value:A one-word comment typo in `src/datasets/utils/_filelock.py`: the comment reads "In previous **previous** it was already using the current umask", duplicating a word and dropping the noun. ```diff # The "mode" argument is required if we want to use the current umask in filelock >= 3.10 - # In pre...
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value:### What was wrong `load_dataset("conll", ...)` keeps a leading UTF-8 BOM. Because the BOM sits at the very start of the first line, it also defeats the two line-level checks (`skip_docstart` and `comment_prefix`), which compare the beginning of a line, so the first marker/comment line is turned into a data row:...
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value:### What was wrong `load_dataset("text", ...)` keeps a leading UTF-8 BOM as part of the data: ```python import codecs import os import tempfile from datasets import load_dataset path = os.path.join(tempfile.mkdtemp(), "corpus.txt") with open(path, "wb") as f: f.write(codecs.BOM_UTF8 + b"hello\nworld\n") ...
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value:Since #8791, streaming a media dataset from the Hub decodes it in worker threads by default, through the `map` step added by `IterableDataset.decode(num_threads=...)`. `cast` and `cast_column` only replaced `info.features` on top of that step, so they had no effect on decoding: * `cast_column("audio", Audio(samp...
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value:### Describe the bug Since #8791, `load_dataset(..., streaming=True)` decodes media in worker threads by default when the dataset is on the Hub. The threaded decoding is a `map` step created by `IterableDataset.decode(num_threads=...)`, so the examples coming out of the dataset are already decoded. `IterableDat...
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value:cast_column / cast are ignored on streaming datasets decoded in threads (audio sampling_rate, decode=False)
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value:`string_to_dict` turns every `{field}` in the pattern into a named group `(?P<_field>.+)` and then reads the match with `result.groups()`, which is positional. Any other capture group in the pattern shifts the values, so `string_to_dict("train/alice", "(train|test)/{name}")` returns `{'name': 'train'}` instead of...
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value:`to_tf_dataset(num_workers=...)` can import a user's collator and initialize TensorFlow before `worker_loop` hides its GPUs. Hide GPUs in the spawn environment so initialization already uses the CPU, then restore the parent environment. Fixes #6948. Six new cases cover imported collators with eager TensorFlow ...
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value:Restores packaged inline type information. The `py.typed` marker is included in the wheel and source archive and explicit aliases mark the existing public re exports. Annotating the `Features` constructor's variadic arguments as `Any` also lets ordinary dictionary inputs type check. Fixes #7390. Checked an ins...
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value:Streaming `with_format("torch").map(...)` warns for every row when a transform returns tensors. Copy existing tensors directly while keeping dtype/device overrides, independent storage and leaf gradient settings. Fixes #7088. Added 18 regression cases, including batched maps. Formatting checks: 59 passed, 12 s...
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value:Repeated checkpoint restores can print the same shuffle-buffer warning thousands of times. This shows it once per process, including when several datasets are restored. Fixes #7444. Added four cases covering repeated restores and initial checkpoints, with checks on the returned rows. The iterable suite has 655 p...
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value:The Torchvision example now resizes masks with nearest neighbor interpolation so it doesn't create new class labels. I also removed the old output image, which shows the incorrect mask boundaries. Fixes #6865. Checked the updated example with upscaling and downscaling, for single examples and batches. Class la...
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value:When the first config in a README has no matching data files, the error now includes its name and the dataset path. This makes it easier to find the broken entry. Added tests for README and standalone YAML configs, Hub and bucket loaders and explicit file overrides. Fixes #6819. Tests: 302 local tests passe...
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value:Follow up to #8243. Strip the UTF-8 BOM at the start of each JSON input file. Multifile loads with inferred or explicit `List(Json())` columns otherwise fail when a later file has a BOM. Adds eight regression cases covering inferred/explicit features and regular/streaming loads, including multiple batches and ...
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value:`Dataset.from_buffer` reads the data buffer twice when `indices_buffer` is provided. this raises a type error for string columns and can silently return the wrong rows for uint64 data. Read the supplied indices buffer instead, with 8 regression cases covering empty, reordered and repeated indices, plus the no ind...
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value:`to_sql` with `num_proc > 1` hands every batch to the pool at once. The batch at offset 0 runs `DataFrame.to_sql` with `if_exists` as given (`"fail"` by default) and is meant to create the table; the later batches run with `if_exists="append"`, which also creates the table when it is missing. Whenever a later bat...
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value:### Describe the bug `Dataset.to_sql(name, con, num_proc=N)` with more than one batch fails with `table already exists` (sqlite: `(sqlite3.OperationalError) table t already exists`, or pandas' `ValueError: Table 't' already exists.`), and whether it fails depends on which worker reaches the database first. `Sql...
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value:`Dataset.__getitem__` reads a list, tuple, numpy array or pandas Series of booleans as row indices: `_query_table` turns the key into integers with `np.fromiter(key, np.int64)`, so a mask becomes the rows 0 and 1, and the result is silently wrong. ```python >>> ds = Dataset.from_dict({"a": [10, 20, 30, 40, 50]})...
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value:### Describe the bug `Dataset.__getitem__` accepts a list, tuple, numpy array or pandas Series of booleans and reads it as integer row indices: every `True` becomes row 1 and every `False` row 0. No error is raised, and the result has the length of the mask, so it looks like a valid selection. The docstring says...
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value:`Dataset.to_csv(path, encoding="utf-16")` wrote UTF-8. `CsvDatasetWriter._batch_csv` hands the batch to pandas with `path_or_buf=None`, so pandas returns a `str` and never applies `encoding`; the writer then encoded that `str` with a hard-coded `"utf-8"`. The docstring points at `pandas.DataFrame.to_csv` for the ...
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value:`to_csv(index=True)` and `to_sql(index=True)` wrote an index column that restarts at 0 in every batch: `CsvDatasetWriter._batch_csv` and `SqlDatasetWriter._batch_sql` convert each batch with `batch.to_pandas()`, which gives the batch a fresh `RangeIndex` from 0, and pandas writes that. With the default `batch_siz...
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value:`ClassLabel.cast_storage` handles `pa.StringArray` and `pa.IntegerArray` and hands anything else to `array_cast(storage, int64)`. A pandas `Categorical` column arrives as a `pa.DictionaryArray` (`dictionary<values=large_string, indices=int8>`), so Arrow tries to parse the category names as integers: ``` ArrowInv...
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value:### Describe the bug `Dataset.to_csv(path, encoding="utf-16")` writes UTF-8. The docstring says the extra keyword arguments go to `pandas.DataFrame.to_csv`, which documents `encoding` (and `errors`), and both are accepted without complaint, but the file is always UTF-8. The cause is in `datasets/io/csv.py`: `Cs...
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value:### Describe the bug `Dataset.to_csv(..., index=True)` and `Dataset.to_sql(..., index=True)` write an index column whose values restart at 0 at every batch boundary. The docstrings of both methods say "If you would like to write the index, pass `index=True` and also set a name for the index column by passing `in...
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value:### Describe the bug `Dataset.from_pandas(df, features=...)` fails when the label column of the DataFrame is a pandas `Categorical` and the feature is a `ClassLabel`. pandas hands the column to Arrow as a `DictionaryArray` (`dictionary<values=large_string, indices=int8>`), and `ClassLabel.cast_storage` only know...
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value:Fixes #8590 Clarifies that checksum recording has been disabled by default since Datasets 4.8.5, and that `verification_mode="all_checks"` does not enable it. The integrity guide now explains when checksum comparison runs, shows how to pin a Hub dataset commit for reproducibility, and distinguishes that from ver...
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value:Fixes #5717 Supersedes [#8141](https://github.com/huggingface/datasets/pull/8141), which @kasperg3 [agreed to hand over](https://github.com/huggingface/datasets/pull/8141#issuecomment-6208799638). The first commit is kasperg3's, minus a `to_dict` line that [a later commit](https://github.com/huggingface/datasets...
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value:Related to #8793. `IterableDataset.iter(...).close()` can leave nested generators alive while the caller keeps the closed iterator. On Python 3.12 this leaves shuffled streaming sources and their files open until that iterator is deleted. Return an iterator that closes and releases its owned batch generator, so ...
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value:`for row in ds` slices a one-row table and runs `format_table` on it for every row. With the default Python format that means `to_pydict()` on a 1-row table, `_unnest`, and `decode_example`, so most of the time goes to per-row overhead rather than conversion. Datasets with an indices mapping (after `shuffle` or `...
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value:## What Fixed the duplicated article 'a a Storage Bucket' in a docstring in load.py. ## Why A small, objectively-verifiable improvement (typo) found during a daily open-source maintenance pass (2026-10-16). ## How verified Found with a grep for repeated words. Checked the diff: 1 line changed in 1 file. Committ...
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value:`Dataset.save_to_disk`, `Dataset.load_from_disk`, `DatasetDict.save_to_disk`, `DatasetDict.load_from_disk` and `datasets.load_from_disk` all document their path argument as `path-like`, but they pass it straight to `fsspec.core.url_to_fs`, which only started stringifying `os.PathLike` inputs in fsspec 2024.6. On ...
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value:Fixes #7440 When the Hub is briefly unavailable (429, 5xx or a timeout), streaming can raise `FileNotFoundError` for a file that exists, and a long training run stops. ```python from unittest.mock import patch from huggingface_hub import HfFileSystem from huggingface_hub.errors import HfHubHTTPError f...
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value:Fully exhausting `dataset.take(n)` currently asks the upstream iterable for one extra example (or Arrow table) before stopping. If that next read raises, a sample containing all requested rows still fails. The extra read can also run unnecessary mapping or I/O. Stop both iteration paths immediately after yieldin...
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value:Pickling a dataset concatenated along columns can undo `select_columns()` ordering and replace the full feature metadata with metadata from its first source. For example, two memory-mapped datasets concatenated as `a, b` and selected as `b, a` come back from a pickle roundtrip as `a, b`. Restore the saved schema...
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value:`Features |= other` inherits `dict.__ior__`, so it changes the schema without updating the cached decoding flags. Adding a column then raises `KeyError` during decoding. Replacing a `Value("string")` or `Json(decode=False)` column with `Json()` silently leaves JSON payloads encoded as strings. Apply the existing...
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value:Using `defaults | example` inside `Dataset.map()` should keep existing example values. For an unread overlapping column, the reverse union currently removes its deferred-formatting marker while retaining its `None` placeholder. Row mapping silently writes null values; batched mapping raises `TypeError`. Keep the...
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value:Mapping an empty Arrow or pandas stream with `batched=True` and `batch_size=None` (also `0` or a negative value) crashes with `ArrowInvalid: Must pass at least one table` after `take(0)`. If a filter instead emits empty tables, the same path invokes the callback with an empty batch. Positive-size batches already ...
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value:After a typed Arrow or pandas map, `select_columns()` removes columns from rows but retains the parent iterable's full feature schema. A subsequent `filter()` reintroduces those removed columns during formatting, then raises `CastError` because they no longer match the dataset's selected schema. Project `SelectC...
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value:Indexing a nested column with a NumPy integer, such as `dataset["metadata"]["score"][np.int64(0)]`, treats the returned row as an iterable and raises `TypeError`. Ordinary dataset columns already accept NumPy integer indices. Recognize NumPy integers in the nested-column scalar path as well. Regression tests cov...
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value:`Dataset.cast_column(..., new_fingerprint="cast-result")` ignores the supplied fingerprint for features without a decoder, including `Value`, `ClassLabel`, and `List`. The returned dataset and its saved `state.json` instead contain the fingerprint produced by the nested `cast()` call. Decoder-backed features alre...
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value:Arrow-formatted batched maps advance `with_indices=True` by the number of output rows when read through the Python row iterator. If a batch is duplicated, filtered, or dropped, later callbacks receive the wrong source indices. For example, concatenating a mapped Arrow stream with a generator-backed stream makes s...
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value:`Dataset.to_iterable_dataset()` keeps the rows and features but currently drops the split name and all other `DatasetInfo` fields. For example, a dataset with `split="train"`, a description and a license becomes a stream with `split=None` and empty description/license values. This loses attribution and provenance...
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value:Fixes #8410 ### Problem `DatasetBuilder._check_legacy_cache2` patches `Pickler._legacy_no_dict_keys_sorting = True` to recompute the `config_id` that datasets 2.15 wrote, since 2.15 hashed dicts without sorting their keys. Since 4.4.0 the flag does nothing, so the lookup computes the current (sorted) hash and m...
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value:Fixes #7077. When loading a CSV dataset directory, `column_names` can be ignored and the first data row used as the header. It is also ignored when overriding column names from README configuration. Loading with the explicit `"csv"` builder already works. Normalize incoming `column_names` to `names` before the ...
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value:Fixes #8793 The workaround for apache/arrow#45214 in the Parquet builder (`del parquet_fragment` + `gc.collect()` when a stream stops before the fragment is fully read) was gated on `datasets.config.PYARROW_VERSION <= 24.0.0`. The issue reports that the fatal `PyGILState_Release` at interpreter exit still happen...
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value:Fixes #8617. Bug explanation: `SplitDict.copy()` crashes with `AttributeError` because `from_split_dict` calls `.get()` on the `SplitInfo` dataclass instances passed from `to_split_dict()`, which have no `.get()` method. What changed: one line in `src/datasets/splits.py` inside `from_split_dict`. Dict inputs be...
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value:## Summary The cache guide currently recommends `force_redownload` to get data without previous `map` transforms. Reloading with `load_dataset` already returns the original prepared dataset. ```diff - Re-download files to get the original data without transforms. + Use download_mode for source downloads and dat...
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value:`Dataset.repeat(n)` returns `split=None` for any `n >= 1`, while `repeat(0)`, `select`, `shuffle` and `filter` keep the split: ```python ds = Dataset.from_dict({"x": [1, 2]}, split="train") ds.repeat(3).split # None ds.repeat(0).split # train ``` `repeat` concatenates `[self] * num_times` without passing the ...
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value:Fingerprint hashing uses the custom dill pickler in `datasets.utils._dill`, but its failure warnings and caching documentation say objects can be serializable with "pickle or dill". This incorrectly suggests that successful pickle serialization is sufficient when dill serialization fails. This change makes the t...
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value:Fixes #5967. With `num_proc > 1`, `map` concatenates the processed shards via `_concatenate_map_style_datasets(all_transformed_shards)` without passing an info or split. The split is therefore always `None`, and `DatasetInfo.from_merge` drops `config_name`/`dataset_name` as soon as the shard infos differ, e.g. w...
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value:Fixes #8799 If you split iterable datasets with `split_dataset_by_node` and then concatenate them, every rank gets all the data instead of its own part. The cause: `_concatenate_iterable_datasets` doesn't pass the split (`distributed=`) to the dataset it returns. This PR fixes it the same way `interleave_da...
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value:### Describe the bug If you call `split_dataset_by_node` on iterable datasets and then concatenate them with `concatenate_datasets`, the result is no longer split: every rank iterates over the full data of all inputs. There is no error. In distributed training, each rank silently trains on the same data, so...
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value:Fixes #5088 ## What does this PR do? The single-file extractors (`GzipExtractor`, `XzExtractor`, `ZstdExtractor`, `Bzip2Extractor`) streamed decompression **directly to the final cache path**, while `ExtractManager._do_extract` only checks for the file's existence to skip re-extraction. A process killed mid-ext...
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value:#8303 fixed #8296 (a symlink planted at the extraction directory made `Extractor.extract` write the archive into the directory it points to), but it shipped without a test. This adds one. The test plants a symlink to another directory at the output path, extracts a tar archive, and checks that the output path is...
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value:`Dataset.sort` fails when a sort key is a `float16` column, or a struct with a `float16` field: ```python ds = Dataset.from_dict({"x": [0.5, -1.0, 2.0]}, features=Features({"x": Value("float16")})) ds.sort("x") # ArrowNotImplementedError: halffloat ``` Arrow has no sort kernel for half floats, on pyarrow 24 an...
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value:`Dataset.push_to_hub` silently uploads only part of the dataset when `num_shards` is smaller than `num_proc`: ```python ds = Dataset.from_dict({"i": list(range(2000))}) ds.push_to_hub("user/repo", num_shards=2, num_proc=4) # uploads 1000 of the 2000 rows, no error ``` With `num_shards=3, num_proc=4` it uploads...
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value:Fixes #8713. **Bug:** When `load_dataset("json")` infers a `Json` column (a column mixing objects and strings, with no explicit `features` passed), any plain string in that column that happens to be valid JSON (e.g. `"123"`, `"null"`, `"true"`) was decoded to another type on load: `123`, `None`, `True`. Only str...
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value:### Describe the bug When streaming Parquet datasets from the Hub and stopping iteration early (normal for streaming), the process aborts during interpreter shutdown: ``` Fatal Python error: PyGILState_Release: thread state 0x7fca9c0036d0 must be current when releasing Python runtime state: finalizing (tstate=0...
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value:Fatal `PyGILState_Release` at interpreter exit when streaming Parquet with pyarrow 25 (arrow#45214 workaround is gated to pyarrow <= 24)
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value:Streaming `skip(n)` currently decodes every preceding Parquet source. This change uses `_generate_num_examples` to advance past complete sources using footer row counts, then keeps the existing scan/slice logic for the remainder. Addresses #5380, following [the maintainer’s suggested approach](https://github.c...
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value:enable multithreading by default only mesh datasets have a lower multithreading since they load the full files in memory, to avoid OOMs
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value:## Summary Fix Arrow fingerprinting/serialization failing with `PicklingError: Can't pickle <class 'MonthDayNano'>` on the declared Python 3.11 / dill 0.4.1 / PyArrow 26.0.0 dependency combination. A two-row `Dataset.from_dict` fails during fingerprint creation, and the existing chunk-independent Arrow-table has...
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value:### Describe the bug If I push a dataset to the Hub, rename a column, and push it again to the same repo, `load_dataset` fails with a `CastError`. The parquet file has the new column name, but the README metadata still lists the old one. It only happens when the dataset has a single split. With multiple splits,...
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value:re-pushing all dataset partitions corrupts it
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value:Fixes the bug reported in #8789 . `_get_updated_dataset_card()` updates the splits and sizes in the existing `dataset_info`, but never the features. So re-pushing every split of a dataset with different columns (e.g. after renaming a column) left the card declaring the old schema. `load_dataset` then fails wit...
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value:`IterableDataset.map()` documents that a callback returning `None` runs for side effects and leaves the input data unchanged. It currently raises `TypeError`: the Python path unpacks `None` as a mapping, and the table-formatted path rejects it as an invalid return type. ```python from datasets import IterableDat...
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value:`xpandas_read_csv` hands `xopen(path, "rb")` to `pd.read_csv`, and pandas never closes a buffer it did not open. The handle now closes after a full read, and when `iterator=True` or `chunksize` is set it closes with the reader, which pandas calls on exhaustion and on `close()`, and which #8779 adds for a generato...
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value:On main, `interleave_datasets([d, d], probabilities=[1.0])` with map-style datasets raises `IndexError: boolean index did not match indexed array along axis 0; size of axis is 2 but size of corresponding boolean axis is 1`. datasets 4.0.0 raised `ValueError: a and p must have same size` for the same call. Iterabl...
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value:### Describe the bug The packaged `csv` builder leaves the file object of every CSV it reads open, even after a complete read. Only the garbage collector closes it. `xpandas_read_csv` (`src/datasets/utils/file_utils.py:1273`) passes `xopen(path, "rb")` to `pd.read_csv`. pandas wraps that buffer, and `IOHandles.c...
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value:The `DatasetDict` examples in the NumPy and JAX guides call `DatasetDict.from_dict(data)`, but `DatasetDict` has no `from_dict` (only `Dataset` does), so the snippet fails: ``` AttributeError: type object 'DatasetDict' has no attribute 'from_dict' ``` This builds the `DatasetDict` from `Dataset.from_dict(...)` ...
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value:### What It Is Speed up dense indexed batch reads by gathering selected rows per Arrow record batch, then restoring the requested order. Normalize unsigned indices before offset arithmetic. No dependency or public API change. --- ### Why Shuffled and noncontiguous reads currently create one Arrow batch per ro...
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value:`Dataset.map()` raises `ArrowInvalid` when a transform returns a decoded mesh, even when the column already has a `Mesh` feature: ```python import trimesh from datasets import Dataset, Features, Mesh ds = Dataset.from_dict( {"mesh": [trimesh.creation.box()]}, features=Features({"mesh": Mesh()}), ) def ...
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value:`Dataset.add_faiss_index()` rejects one-dimensional embedding columns stored as `LargeList`, including columns inferred from Arrow or loaded from Parquet. The feature check accepts `List` but raises `ValueError: Wrong feature type for column ... Expected 1d array` for equivalent `LargeList` values. Accept `Large...
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value:CSV table generation leaves its pandas reader open when the generator is closed early or table casting raises. Close the reader in a `finally` block so both paths release the file handle while preserving the existing error propagation. Added regression coverage using real pandas readers for exhaustion, generator...
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value:`Dataset.to_csv(index=True)` currently restarts the exported index at zero for each batch. For example, exporting 12 rows with `batch_size=5` writes indices `0..4, 0..4, 0..1`, while a single batch writes `0..11`. Set each batch's DataFrame index from its logical row offset before CSV serialization. This makes i...
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value:Fixes #8776. `keep_features_dicts_synced` rebuilds the whole `_column_requires_decoding` dict after every `__setitem__` / `__delitem__`, and `Features.__init__` sets every column once, so building a `Features` with N columns makes N × N `require_decoding` calls. This change makes `__setitem__` and `__delitem__` ...
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value:### Describe the bug Every `Features` object is built in O(columns²) time, so datasets with thousands of columns become very slow to load and process. `Features.__init__` re-assigns every column (the datasets<4 list compatibility loop), and each `__setitem__` goes through `keep_features_dicts_synced`, which reb...
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value:Loading a dataset with many columns is quadratic in the number of columns (20k-column CSV: 15-25 min to load, ~30 s with a small fix)
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value:## What does this PR do? Fixes [#8743](https://github.com/huggingface/datasets/issues/8743): `ParquetDatasetWriter._write` only closes the `pyarrow.parquet.ParquetWriter` on the successful completion path. If a batch query/write or metadata persistence raises, the writer is left unclosed while the outer file han...
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value:Pandas equality on an ArrayXD column reduces the whole column to one boolean. If two Series differ in only one row, `(left == right)` marks every row as unequal, and `!=` marks every row as different. Ragged rows can also raise an ambiguous-truth-value error. Compare each row's array with `np.array_equal` and re...
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value:Adds an optional `return_file_name` parameter to the JSON dataset loader. When set to `True`, the returned dataset includes a `file_name` column containing the source file name for each row. Changes: - Added `return_file_name: bool = False` to `JsonConfig` - Updated `_info()` to include `file_name` feature when ...
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value:Add return_file_name parameter to load_dataset for JSON (issue #5806)
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value:Fixes mypy errors by replacing invariant `List` with covariant `Sequence` in type annotations and docstrings. Changes: - `path_or_paths: Union[PathLike, list[PathLike]]` → `Union[PathLike, Sequence[PathLike]]` in `from_csv`, `from_json`, `from_parquet`, `from_text` methods - Docstring `List[str]` → `Sequence[str...
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value:Use Sequence instead of List in type hints (issue #5354)
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value:NumPy passes dtype and copy to extension arrays. The Arrow ArrayXD adapter currently rejects both arguments; the Pandas adapter rejects copy and can allocate for a same-dtype conversion. This also breaks NumPy 2 copy=False dispatch. Accept both protocol arguments in the Arrow and Pandas adapters. Keep a view whe...
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value:Since 4.5.0, `save_to_disk` writes no data file at all for a dataset with zero rows, so `load_from_disk` can't read the directory back: ```python import tempfile from datasets import Dataset, DatasetDict, load_from_disk path = tempfile.mkdtemp() full = Dataset.from_dict({"x": [1, 2, 3]}) DatasetDict({"train": f...
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value:`Video` accepts a `torch.device`, but passing one makes `Dataset.from_dict` fail with `TypeError: Object of type device is not JSON serializable` while building feature metadata. Normalize non-`None` devices to their string descriptors when constructing the feature. This preserves indexed devices such as `cuda:1...
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value:## Summary - Keep columns returned by an Arrow-format `IterableDataset.map` function even when their names appear in `remove_columns`. - Align streaming behavior with `Dataset.map` and the documented rule that `remove_columns` applies before the function output. - Update the Arrow iterable tests and add a regress...
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