/usr/local/lib/python3.6/site-packages/datasets/__pycache__
NameSizeModeActions
arrow_dataset.cpython-36.pyc1898500644editdlrm
arrow_reader.cpython-36.pyc224830644editdlrm
arrow_writer.cpython-36.pyc221100644editdlrm
builder.cpython-36.pyc527790644editdlrm
combine.cpython-36.pyc55080644editdlrm
config.cpython-36.pyc51810644editdlrm
dataset_dict.cpython-36.pyc833190644editdlrm
data_files.cpython-36.pyc301530644editdlrm
fingerprint.cpython-36.pyc189790644editdlrm
info.cpython-36.pyc173590644editdlrm
inspect.cpython-36.pyc185830644editdlrm
iterable_dataset.cpython-36.pyc629320644editdlrm
keyhash.cpython-36.pyc33410644editdlrm
load.cpython-36.pyc629220644editdlrm
metric.cpython-36.pyc232170644editdlrm
naming.cpython-36.pyc25710644editdlrm
search.cpython-36.pyc313390644editdlrm
splits.cpython-36.pyc225220644editdlrm
streaming.cpython-36.pyc41190644editdlrm
table.cpython-36.pyc796120644editdlrm
__init__.cpython-36.pyc22820644editdlrm
Edit: /usr/local/lib/python3.6/site-packages/datasets/__pycache__/combine.cpython-36.pyc (5508B)
3 <%Eg@sddlmZmZmZddlmZmZmZddlm Z ddl m Z m Z m Z ddlmZddlmZejeZedd d Zdeeeeeeeee eeed d dZdeeee eeedddZd S))ListOptionalTypeVar)Dataset_concatenate_map_style_datasets_interleave_map_style_datasets) DatasetInfo)IterableDataset_concatenate_iterable_datasets_interleave_iterable_datasets) NamedSplit)logging DatasetTyperr N)datasets probabilitiesseedinfosplitreturnc Csddlm}ddlm}|s$tdt|d|}t|d|}||As^tdt|dxV|ddD]F} |rt| | s|rlt| | rltdt|dd t| d qlW|rt|||||d St|||||d SdS) u Interleave several datasets (sources) into a single dataset. The new dataset is constructed by alternating between the sources to get the examples. You can use this function on a list of :class:`Dataset` objects, or on a list of :class:`IterableDataset` objects. If ``probabilities`` is ``None`` (default) the new dataset is constructed by cycling between each source to get the examples. If ``probabilities`` is not ``None``, the new dataset is constructed by getting examples from a random source at a time according to the provided probabilities. The resulting dataset ends when one of the source datasets runs out of examples. Args: datasets (:obj:`List[Dataset]` or :obj:`List[IterableDataset]`): list of datasets to interleave probabilities (:obj:`List[float]`, optional, default None): If specified, the new dataset is constructued by sampling examples from one source at a time according to these probabilities. seed (:obj:`int`, optional, default None): The random seed used to choose a source for each example. Returns: :class:`Dataset` or :class:`IterableDataset`: Return type depends on the input `datasets` parameter. `Dataset` if the input is a list of `Dataset`, `IterableDataset` if the input is a list of `IterableDataset`. Example:: For regular datasets (map-style): >>> from datasets import Dataset, interleave_datasets >>> d1 = Dataset.from_dict({"a": [0, 1, 2]}) >>> d2 = Dataset.from_dict({"a": [10, 11, 12]}) >>> d3 = Dataset.from_dict({"a": [20, 21, 22]}) >>> dataset = interleave_datasets([d1, d2, d3]) >>> dataset["a"] [0, 10, 20, 1, 11, 21, 2, 12, 22] >>> dataset = interleave_datasets([d1, d2, d3], probabilities=[0.7, 0.2, 0.1], seed=42) >>> dataset["a"] [10, 0, 11, 1, 2, 20, 12] For datasets in streaming mode (iterable): >>> from datasets import load_dataset, interleave_datasets >>> d1 = load_dataset("oscar", "unshuffled_deduplicated_en", split="train", streaming=True) >>> d2 = load_dataset("oscar", "unshuffled_deduplicated_fr", split="train", streaming=True) >>> dataset = interleave_datasets([d1, d2]) >>> iterator = iter(dataset) >>> next(iterator) {'text': 'Mtendere Village was inspired by the vision... >>> next(iterator) {'text': "Média de débat d'idées, de culture... r)r)r z/Unable to interleave an empty list of datasets.rz`Expected a list of Dataset objects or a list of IterableDataset objects, but first element is a NzUnable to interleave a z with a zJ. Expected a list of Dataset objects or a list of IterableDataset objects.)rr) arrow_datasetriterable_datasetr ValueError isinstancetyperr ) rrrrrrr iterable map_styledatasetr:/usr/local/lib/python3.6/site-packages/datasets/combine.pyinterleave_datasetss 8   $r )dsetsrraxiscCs|s tdt|dt}t|dt}||AsFtdt|dxV|ddD]F}|rht|t sx|rTt|t rTtdt|ddt|dqTW|rt||||d St||||d SdS) a Converts a list of :class:`Dataset` with the same schema into a single :class:`Dataset`. Args: dsets (:obj:`List[datasets.Dataset]`): List of Datasets to concatenate. info (:class:`DatasetInfo`, optional): Dataset information, like description, citation, etc. split (:class:`NamedSplit`, optional): Name of the dataset split. axis (``{0, 1}``, default ``0``, meaning over rows): Axis to concatenate over, where ``0`` means over rows (vertically) and ``1`` means over columns (horizontally). *New in version 1.6.0* Example: ```py >>> ds3 = concatenate_datasets([ds1, ds2]) ``` z0Unable to concatenate an empty list of datasets.rz`Expected a list of Dataset objects or a list of IterableDataset objects, but first element is a rNzUnable to concatenate a z with a zJ. Expected a list of Dataset objects or a list of IterableDataset objects.)rrr")rrr rrrr )r!rrr"rrrrrrconcatenate_datasets^s $r#)NNNN)NNr)typingrrrrrrrrr rr r r splitsr utilsr get_logger__name__loggerrfloatintr r#rrrrs     $J