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author | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2021-10-27 22:10:14 +0200 |
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committer | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2021-10-27 22:10:14 +0200 |
commit | 07a5b84b001756b06c6dc0c54f396ea42b11067b (patch) | |
tree | d878d498d7bd4aebab1194e6d9851dc16e0b6b8e /text_recognizer/data/mappings/word_piece.py | |
parent | eb672fa209d4a34124cce06bd8737164647a2b1b (diff) |
Rename mappings
Diffstat (limited to 'text_recognizer/data/mappings/word_piece.py')
-rw-r--r-- | text_recognizer/data/mappings/word_piece.py | 72 |
1 files changed, 72 insertions, 0 deletions
diff --git a/text_recognizer/data/mappings/word_piece.py b/text_recognizer/data/mappings/word_piece.py new file mode 100644 index 0000000..861c3bd --- /dev/null +++ b/text_recognizer/data/mappings/word_piece.py @@ -0,0 +1,72 @@ +"""Word piece mapping.""" +from typing import List, Set, Union + +import torch +from torch import Tensor + +from text_recognizer.data.mappings.emnist import EmnistMapping +from text_recognizer.data.utils.iam_preprocessor import Preprocessor + + +class WordPieceMapping(EmnistMapping): + """Word piece mapping.""" + + def __init__( + self, + num_features: int = 1000, + tokens: str = "iamdb_1kwp_tokens_1000.txt", + lexicon: str = "iamdb_1kwp_lex_1000.txt", + use_words: bool = False, + prepend_wordsep: bool = False, + special_tokens: Set[str] = {"<s>", "<e>", "<p>"}, + extra_symbols: Set[str] = {"\n"}, + ) -> None: + super().__init__(extra_symbols=extra_symbols) + special_tokens = set(special_tokens) + if self.extra_symbols is not None: + special_tokens = special_tokens | set(extra_symbols) + + self.wordpiece_processor = Preprocessor( + num_features=num_features, + tokens=tokens, + lexicon=lexicon, + use_words=use_words, + prepend_wordsep=prepend_wordsep, + special_tokens=special_tokens, + ) + + def __len__(self) -> int: + """Return number of word pieces.""" + return len(self.wordpiece_processor.tokens) + + def get_token(self, index: Union[int, Tensor]) -> str: + """Returns token for index.""" + if (index := int(index)) <= self.wordpiece_processor.num_tokens: + return self.wordpiece_processor.tokens[index] + raise KeyError(f"Index ({index}) not in mapping.") + + def get_index(self, token: str) -> Tensor: + """Returns index of token.""" + if token in self.wordpiece_processor.tokens: + return torch.LongTensor([self.wordpiece_processor.tokens_to_index[token]]) + raise KeyError(f"Token ({token}) not found in inverse mapping.") + + def get_text(self, indices: Union[List[int], Tensor]) -> str: + """Returns text from indices.""" + if isinstance(indices, Tensor): + indices = indices.tolist() + return self.wordpiece_processor.to_text(indices) + + def get_indices(self, text: str) -> Tensor: + """Returns indices of text.""" + return self.wordpiece_processor.to_index(text) + + def emnist_to_wordpiece_indices(self, x: Tensor) -> Tensor: + """Returns word pieces indices from emnist indices.""" + text = "".join([self.mapping[i] for i in x]) + text = text.lower().replace(" ", "▁") + return torch.LongTensor(self.wordpiece_processor.to_index(text)) + + def __getitem__(self, x: Union[int, Tensor]) -> str: + """Returns token for word piece index.""" + return self.get_token(x) |