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# Copyright (c) 2025, 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.
from megatron.core.datasets.megatron_tokenizer import MegatronLegacyTokenizer as MegatronTokenizer
class NullTokenizer(MegatronTokenizer):
"""
Synthetic tokenizer for performance benchmarking and debugging
Args:
vocab_size: vocabulary size for embedding
"""
def __init__(self, vocab_size):
super().__init__(None, vocab_size=vocab_size)
self._vocab_size_without_eod = int(vocab_size)
self._eod_id = self._vocab_size_without_eod
def tokenize(self, text):
return [int(x) for x in text.split(' ')]
def detokenize(self, ids):
text = [str(x) for x in ids]
return ' '.join(text)
def offsets(self, ids: list[int], text: str) -> list[int]:
offsets, start_idx = [], 0
for id_ in ids:
offsets.append(start_idx)
start_idx += 1 + len(str(id_))
return offsets
@property
def vocab_size(self):
return self._vocab_size_without_eod + 1
@property
def vocab(self):
raise NotImplementedError
@property
def inv_vocab(self):
raise NotImplementedError
@property
def cls(self):
return -1
@property
def sep(self):
return -1
@property
def mask(self):
return -1
@property
def eod(self):
return self._eod_id
@property
def additional_special_tokens_ids(self):
return None
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