diff options
Diffstat (limited to 'text_recognizer/data/mappings')
-rw-r--r-- | text_recognizer/data/mappings/word_piece.py | 72 |
1 files changed, 0 insertions, 72 deletions
diff --git a/text_recognizer/data/mappings/word_piece.py b/text_recognizer/data/mappings/word_piece.py deleted file mode 100644 index 861c3bd..0000000 --- a/text_recognizer/data/mappings/word_piece.py +++ /dev/null @@ -1,72 +0,0 @@ -"""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) |