mindspore.dataset.text.utils.SentencePieceVocab

class mindspore.dataset.text.utils.SentencePieceVocab[source]

SentencePiece obiect that is used to segmentate words

classmethod from_dataset(dataset, col_names, vocab_size, character_coverage, model_type, params)[source]

Build a sentencepiece from a dataset

Parameters

dataset (Dataset) – Dataset to build sentencepiece.
col_names (list) – The list of the col name.
vocab_size (int) – Vocabulary size.
character_coverage (float) – Amount of characters covered by the model, good defaults are: 0.9995 for languages. with rich character set like Japanese or Chinese and 1.0 for other languages with small character set.
model_type (SentencePieceModel) – Choose from UNIGRAM (default), BPE, CHAR, or WORD. The input sentence must be pretokenized when using word type.
params (dict) – A dictionary with no incoming parameters.

Returns

SentencePieceVocab, vocab built from the dataset.

classmethod from_file(file_path, vocab_size, character_coverage, model_type, params)[source]

Build a SentencePiece object from a list of word.

Parameters

file_path (list) – Path to the file which contains the sentencepiece list.
vocab_size (int) – Vocabulary size, the type of uint32_t.
character_coverage (float) – Amount of characters covered by the model, good defaults are: 0.9995 for languages. with rich character set like Japanse or Chinese and 1.0 for other languages with small character set.
model_type (SentencePieceModel) – Choose from unigram (default), bpe, char, or word. The input sentence must be pretokenized when using word type.
params (dict) –
A dictionary with no incoming parameters(The parameters are derived from SentencePiece library).
```
input_sentence_size 0
max_sentencepiece_length 16
```

Returns

SentencePieceVocab, vocab built from the file.

classmethod save_model(vocab, path, filename)[source]

Save model to filepath

Parameters