mindspore.dataset.text.Ngram
- 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=”-”, 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
>>> 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_dataset = text_file_dataset.map(operations=ngram_op)