Inital commit for refactoring to lightning

1 files changed, 114 insertions, 0 deletions

diff --git a/tasks/make_wordpieces.py b/tasks/make_wordpieces.py
new file mode 100644
index 0000000..2ac0e2c
--- /dev/null
+++ b/tasks/make_wordpieces.py
@@ -0,0 +1,114 @@
+"""Creates word pieces from a text file.
+
+Most code stolen from:
+
+    https://github.com/facebookresearch/gtn_applications/blob/master/scripts/make_wordpieces.py
+
+"""
+import io
+from pathlib import Path
+from typing import List, Optional, Union
+
+import click
+from loguru import logger
+import sentencepiece as spm
+
+from text_recognizer.datasets.iam_preprocessor import load_metadata
+
+
+def iamdb_pieces(
+    data_dir: Path, text_file: str, num_pieces: int, output_prefix: str
+) -> None:
+    """Creates word pieces from the iamdb train text."""
+    # Load training text.
+    with open(data_dir / text_file, "r") as f:
+        text = [line.strip() for line in f]
+
+    sp = train_spm_model(
+        iter(text),
+        num_pieces + 1,  # To account for <unk>
+        user_symbols=["/"],  # added so token is in the output set
+    )
+
+    vocab = sorted(set(w for t in text for w in t.split("▁") if w))
+    if "move" not in vocab:
+        raise RuntimeError("`MOVE` not in vocab")
+
+    save_pieces(sp, num_pieces, data_dir, output_prefix, vocab)
+
+
+def train_spm_model(
+    sentences: iter, vocab_size: int, user_symbols: Union[str, List[str]] = ""
+) -> spm.SentencePieceProcessor:
+    """Trains the sentence piece model."""
+    model = io.BytesIO()
+    spm.SentencePieceTrainer.train(
+        sentence_iterator=sentences,
+        model_writer=model,
+        vocab_size=vocab_size,
+        bos_id=-1,
+        eos_id=-1,
+        character_coverage=1.0,
+        user_defined_symbols=user_symbols,
+    )
+    sp = spm.SentencePieceProcessor(model_proto=model.getvalue())
+    return sp
+
+
+def save_pieces(
+    sp: spm.SentencePieceProcessor,
+    num_pieces: int,
+    data_dir: Path,
+    output_prefix: str,
+    vocab: set,
+) -> None:
+    """Saves word pieces to disk."""
+    logger.info(f"Generating word piece list of size {num_pieces}.")
+    pieces = [sp.id_to_piece(i) for i in range(1, num_pieces + 1)]
+    logger.info(f"Encoding vocabulary of size {len(vocab)}.")
+    encoded_vocab = [sp.encode_as_pieces(v) for v in vocab]
+
+    # Save pieces to file.
+    with open(data_dir / f"{output_prefix}_tokens_{num_pieces}.txt", "w") as f:
+        f.write("\n".join(pieces))
+
+    # Save lexicon to a file.
+    with open(data_dir / f"{output_prefix}_lex_{num_pieces}.txt", "w") as f:
+        for v, p in zip(vocab, encoded_vocab):
+            f.write(f"{v} {' '.join(p)}\n")
+
+
+@click.command()
+@click.option("--data_dir", type=str, default=None, help="Path to processed iam dir.")
+@click.option(
+    "--text_file", type=str, default=None, help="Name of sentence piece training text."
+)
+@click.option(
+    "--output_prefix",
+    type=str,
+    default="word_pieces",
+    help="Prefix name to store tokens and lexicon.",
+)
+@click.option("--num_pieces", type=int, default=1000, help="Number of word pieces.")
+def cli(
+    data_dir: Optional[str],
+    text_file: Optional[str],
+    output_prefix: Optional[str],
+    num_pieces: Optional[int],
+) -> None:
+    """CLI for training the sentence piece model."""
+    if data_dir is None:
+        data_dir = (
+            Path(__file__).resolve().parents[2] / "data" / "processed" / "iam_lines"
+        )
+        logger.debug(f"Using data dir: {data_dir}")
+        if not data_dir.exists():
+            raise RuntimeError(f"Could not locate iamdb directory at {data_dir}")
+    else:
+        data_dir = Path(data_dir)
+
+    iamdb_pieces(data_dir, text_file, num_pieces, output_prefix)
+
+
+if __name__ == "__main__":
+    cli()