# SOME DESCRIPTIVE TITLE. # Copyright (C) 2021, PaddleNLP # This file is distributed under the same license as the PaddleNLP package. # FIRST AUTHOR , 2022. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: PaddleNLP \n" "Report-Msgid-Bugs-To: \n" "POT-Creation-Date: 2022-03-18 21:31+0800\n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Last-Translator: FULL NAME \n" "Language-Team: LANGUAGE \n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.9.0\n" #: ../source/paddlenlp.data.collate.rst:2 msgid "collate" msgstr "" #: of paddlenlp.data.collate.Dict:1 paddlenlp.data.collate.Pad:1 #: paddlenlp.data.collate.Stack:1 paddlenlp.data.collate.Tuple:1 msgid "基类：:class:`object`" msgstr "" #: of paddlenlp.data.collate.Stack:1 msgid "" "Stacks the input data samples to construct the batch. The N input samples" " must have the same shape/length and will be stacked to construct a " "batch." msgstr "" #: of paddlenlp.data.collate.Dict paddlenlp.data.collate.Dict.__call__ #: paddlenlp.data.collate.Pad paddlenlp.data.collate.Pad.__call__ #: paddlenlp.data.collate.Stack paddlenlp.data.collate.Stack.__call__ #: paddlenlp.data.collate.Tuple paddlenlp.data.collate.Tuple.__call__ msgid "参数" msgstr "" #: of paddlenlp.data.collate.Stack:4 msgid "" "The axis in the result data along which the input data are stacked. " "Default: 0." msgstr "" #: of paddlenlp.data.collate.Stack:7 msgid "" "The value type of the output. If it is set to None, the type of input " "data is used. Default: None." msgstr "" #: of paddlenlp.data.collate.Stack.__call__:1 msgid "Batchifies the input data by stacking." msgstr "" #: of paddlenlp.data.collate.Pad.__call__:6 #: paddlenlp.data.collate.Stack.__call__:3 msgid "" "The input data samples. It is a list. Each element is a numpy.ndarray or " "list." msgstr "" #: of paddlenlp.data.collate.Dict.__call__ paddlenlp.data.collate.Pad.__call__ #: paddlenlp.data.collate.Stack.__call__ paddlenlp.data.collate.Tuple.__call__ msgid "返回" msgstr "" #: of paddlenlp.data.collate.Stack.__call__:7 msgid "Stacked batch data." msgstr "" #: of paddlenlp.data.collate.Dict.__call__ paddlenlp.data.collate.Pad.__call__ #: paddlenlp.data.collate.Stack.__call__ paddlenlp.data.collate.Tuple.__call__ msgid "返回类型" msgstr "" #: of paddlenlp.data.collate.Dict.__call__:14 #: paddlenlp.data.collate.Pad.__call__:18 #: paddlenlp.data.collate.Stack.__call__:11 #: paddlenlp.data.collate.Tuple.__call__:14 msgid "示例" msgstr "" #: of paddlenlp.data.collate.Pad:1 msgid "Pads the input data samples to the largest length at `axis`." msgstr "" #: of paddlenlp.data.collate.Pad:3 msgid "The padding value. Default: 0." msgstr "" #: of paddlenlp.data.collate.Pad:5 msgid "" "The axis to pad the arrays. The arrays will be padded to the largest " "length at `axis`. For example, assume the input arrays have shape (10, 8," " 5), (6, 8, 5), (3, 8, 5) and the axis is 0. Each input will be padded " "into (10, 8, 5) and then stacked to form the final output, which has " "shape (3, 10, 8, 5). Default: 0." msgstr "" #: of paddlenlp.data.collate.Pad:12 msgid "" "If it is bool, indicate whether to return the valid length in the output," " and the data type of returned length is int32 if True. If it is " "numpy.dtype, indicate the data type of returned length. Default: None." msgstr "" #: of paddlenlp.data.collate.Pad:17 msgid "" "The value type of the output. If it is set to None, the input data type " "is used. Default: None." msgstr "" #: of paddlenlp.data.collate.Pad:20 msgid "" "Whether the padding direction is right-side. If True, it indicates we pad" " to the right side, while False indicates we pad to the left side. " "Default: True." msgstr "" #: of paddlenlp.data.collate.Pad.__call__:1 msgid "" "Batchifies the input data by padding. The input will be padded to the " "largest dimension at `axis` and then stacked to form the final output. In" " addition, the function will output the original dimensions at the `axis`" " if `ret_length` is not None or False." msgstr "" #: of paddlenlp.data.collate.Pad.__call__:10 msgid "" "If `ret_length` is False, it is a numpy.ndarray representing the padded " "batch data and the shape is (N, …). Otherwise, it is a tuple, besides the" " padded batch data, the tuple also includes a numpy.ndarray representing " "original length at `axis` of all input samples, which shaped `(N,)`." msgstr "" #: of paddlenlp.data.collate.Dict:1 paddlenlp.data.collate.Tuple:1 msgid "" "Wraps multiple batchify functions together. The input functions will be " "applied to the corresponding input fields." msgstr "" #: of paddlenlp.data.collate.Tuple:4 msgid "" "Each sample should be a list or tuple containing multiple fields. The " "i'th batchify function stored in Tuple will be applied on the i'th field." msgstr "" #: of paddlenlp.data.collate.Tuple:7 msgid "" "For example, when data sample is (nd_data, label), you can wrap two " "batchify functions using `Tuple(DataBatchify, LabelBatchify)` to batchify" " nd_data and label correspondingly." msgstr "" #: of paddlenlp.data.collate.Tuple:11 msgid "" "The batchify functions to wrap. It is a callable function or a list/tuple" " of callable functions." msgstr "" #: of paddlenlp.data.collate.Tuple:14 msgid "The additional batchify functions to wrap." msgstr "" #: of paddlenlp.data.collate.Tuple.__call__:1 msgid "" "Batchifies data samples by applying each function on the corresponding " "data field, and each data field is produced by stacking the field data of" " samples." msgstr "" #: of paddlenlp.data.collate.Tuple.__call__:5 msgid "" "The samples to batchfy. Each sample in list/tuple should contain `N` " "fields." msgstr "" #: of paddlenlp.data.collate.Dict.__call__:9 #: paddlenlp.data.collate.Tuple.__call__:9 msgid "A tuple composed of results from all including batchifying functions." msgstr "" #: of paddlenlp.data.collate.Dict:4 msgid "" "Each sample should be a dict containing multiple fields. Each batchify " "function with key stored in `Dict` will be applied on the field which has" " the same key." msgstr "" #: of paddlenlp.data.collate.Dict:8 msgid "" "For example, when data sample is {'tokens': tokens, 'labels': labels}, " "you can wrap two batchify functions using `Dict({'tokens': DataBatchify, " "'labels': LabelBatchify})` to batchify tokens and labels correspondingly." msgstr "" #: of paddlenlp.data.collate.Dict:13 msgid "" "The batchify functions to wrap. It is a dict, which values is callable " "functions." msgstr "" #: of paddlenlp.data.collate.Dict.__call__:1 msgid "" "Batchifies data samples by applying each function on the corresponding " "data field, and each data field is produced by stacking the field data " "with the same key as batchify functions of all samples." msgstr "" #: of paddlenlp.data.collate.Dict.__call__:5 msgid "" "The samples to batchfy. Each sample in list/tuple is a dict with `N` key-" "values." msgstr ""