chore: remove word pieces

1 files changed, 0 insertions, 45 deletions

diff --git a/text_recognizer/data/transforms/word_piece.py b/text_recognizer/data/transforms/word_piece.py
deleted file mode 100644
index d805c7e..0000000
--- a/text_recognizer/data/transforms/word_piece.py
+++ /dev/null
@@ -1,45 +0,0 @@
-"""Target transform for word pieces."""
-from typing import Optional, Sequence
-
-import torch
-from torch import Tensor
-
-from text_recognizer.data.mappings.word_piece_mapping import WordPieceMapping
-
-
-class WordPiece:
-    """Converts EMNIST indices to Word Piece indices."""
-
-    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: Sequence[str] = ("<s>", "<e>", "<p>"),
-        extra_symbols: Optional[Sequence[str]] = ("\n",),
-        max_len: int = 451,
-    ) -> None:
-        self.mapping = WordPieceMapping(
-            num_features=num_features,
-            tokens=tokens,
-            lexicon=lexicon,
-            use_words=use_words,
-            prepend_wordsep=prepend_wordsep,
-            special_tokens=special_tokens,
-            extra_symbols=extra_symbols,
-        )
-        self.max_len = max_len
-
-    def __call__(self, x: Tensor) -> Tensor:
-        """Converts Emnist target tensor to Word piece target tensor."""
-        y = self.mapping.emnist_to_wordpiece_indices(x)
-        if len(y) < self.max_len:
-            pad_len = self.max_len - len(y)
-            y = torch.cat(
-                (y, torch.LongTensor([self.mapping.get_index("<p>")] * pad_len))
-            )
-        else:
-            y = y[: self.max_len]
-        return y