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# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import logging
import sys
from argparse import ArgumentParser
import sentencepiece as spm
try:
import sentencepiece_model_pb2 as spt
except (ImportError, ModuleNotFoundError):
raise Exception("Ensure that sentencepiece_model_pb2.py has been generated from the protoc compiler")
"""Utility to add special tokens to existing sentencepiece models.
Generate sentencepiece_model_pb2.py in the directory of this script before running
To generate run `protoc --python_out=<path_to_NeMo>/scripts/tokenizers/ sentencepiece_model.proto`
inside the src folder in sentencepiece repo
Refer: https://github.com/google/sentencepiece/issues/121
Usage:
python edit_spt_model.py \
--input_file <input_model_dir> \
--output_file <output_model_dir> \
--tokens <space separated special tokens>
Example:
python edit_spt_model.py \
--input_file test.model \
--output_file test.model \
--tokens [CLS] [SEP]
"""
def edit_spt_model():
parser = ArgumentParser()
parser.add_argument(
"--input_file", type=str, required=True, help="Path to sentencepiece model file",
)
parser.add_argument(
"--output_file", type=str, required=True, help="Path to sentencepiece model file",
)
parser.add_argument(
"--tokens", type=str, nargs='+', required=True, help="Special tokens to add to tokenizer",
)
parser.add_argument(
"--is_userdefined", action="store_true", help="When set, the new tokens are set as user_defined tokens",
)
args = parser.parse_args()
token_type = 3
if args.is_userdefined:
token_type = 4
model = spt.ModelProto()
model.ParseFromString(open(args.input_file, 'rb').read())
for token in args.tokens:
piece = model.SentencePiece(piece=token, score=0.0, type=token_type)
if piece in model.pieces:
logging.error(f"Special Token '{token}' already exists in the input model!")
sys.exit(1)
model.pieces.append(piece)
sp = spm.SentencePieceProcessor()
try:
sp.LoadFromSerializedProto(model.SerializeToString())
for token in args.tokens:
id = sp.piece_to_id(token)
logging.info(f"Created token '{token}' at ID {id}")
logging.info(f"New tokenizer vocab size: {sp.get_piece_size()}")
except:
logging.error("Could not appropriately configure new tokenizer. Verify if the special tokens already exist.")
sys.exit(1)
with open(args.output_file, 'wb') as outf:
outf.write(model.SerializeToString())
logging.info(f"Created new tokenizer at: {args.output_file}")
if __name__ == "__main__":
logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")
edit_spt_model()
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