mindspore.dataset.text.Ngram

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class mindspore.dataset.text.Ngram(n, left_pad=('', 0), right_pad=('', 0), separator=' ')[source]

Generate n-gram from a 1-D string Tensor.

Refer to N-gram for an overview of what n-gram is and how it works.

Parameters

  • n (list[int]) – n in n-gram, which is a list of positive integers. For example, if n=[4, 3], then the result would be a 4-gram followed by a 3-gram in the same tensor. If the number of words is not enough to make up for a n-gram, an empty string will be returned. For example, 3 grams on [“mindspore”, “best”] will result in an empty string produced.

  • left_pad (tuple, optional) – Padding performed on left side of the sequence shaped like (“pad_token”, pad_width). pad_width will be capped at n-1. For example, specifying left_pad=(“_”, 2) would pad left side of the sequence with “__”. Default: ('', 0).

  • right_pad (tuple, optional) – Padding performed on right side of the sequence shaped like (“pad_token”, pad_width). pad_width will be capped at n-1. For example, specifying right_pad=(“_”, 2) would pad right side of the sequence with “__”. Default: ('', 0).

  • separator (str, optional) – Symbol used to join strings together. For example, if 2-gram is [“mindspore”, “amazing”] with separator is "-", the result would be [“mindspore-amazing”]. Default: ' ', which will use whitespace as separator.

Raises

  • TypeError – If values of n not positive is not of type int.

  • ValueError – If values of n not positive.

  • ValueError – If left_pad is not a tuple of length 2.

  • ValueError – If right_pad is not a tuple of length 2.

  • TypeError – If separator is not of type string.

Supported Platforms:

CPU

Examples

>>> import mindspore.dataset as ds
>>> import mindspore.dataset.text as text
>>> ngram_op = text.Ngram(3, separator="-")
>>> output = ngram_op(["WildRose Country", "Canada's Ocean Playground", "Land of Living Skies"])
>>> # output
>>> # ["WildRose Country-Canada's Ocean Playground-Land of Living Skies"]
>>>
>>> # same ngram_op called through map
>>> text_file_list = ["/path/to/text_file_dataset_file"]
>>> text_file_dataset = ds.TextFileDataset(dataset_files=text_file_list)
>>> text_file_dataset = text_file_dataset.map(operations=ngram_op)
Tutorial Examples: