1 files changed, 48 insertions, 0 deletions
diff --git a/text_recognizer/data/transforms/word_piece.py b/text_recognizer/data/transforms/word_piece.py
new file mode 100644
index 0000000..6bf5472
--- /dev/null
+++ b/text_recognizer/data/transforms/word_piece.py
@@ -0,0 +1,48 @@
+"""Target transform for word pieces."""
+from pathlib import Path
+from typing import Optional, Union, Set
+
+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",
+        data_dir: Optional[Union[str, Path]] = None,
+        use_words: bool = False,
+        prepend_wordsep: bool = False,
+        special_tokens: Set[str] = {"<s>", "<e>", "<p>"},
+        extra_symbols: Optional[Set[str]] = {"\n",},
+        max_len: int = 451,
+    ) -> None:
+        self.mapping = WordPieceMapping(
+            data_dir=data_dir,
+            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