Files
deepmind-research/perceiver/bytes_tokenizer.py
Sebastian Borgeaud 0e552473e5 Add BytesTokenizer and EmbeddingDecoder
Both are required for the language colab (coming next)

PiperOrigin-RevId: 387574746
2021-07-30 17:38:05 +01:00

66 lines
1.8 KiB
Python

# Copyright 2021 DeepMind Technologies Limited
#
# 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
#
# https://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.
"""Tokenizer implementation mapping strings to their UTF-8 bytes."""
from typing import Union
import numpy as np
class BytesTokenizer:
"""Tokenizes string to utf-8 bytes."""
def __init__(self):
self._num_reserved_tokens = 6 # PAD, BOS, EOS, MASK, CLS, SEP
def to_string(self, inputs: np.ndarray) -> str:
inputs_no_special = (
inputs[inputs >= self._num_reserved_tokens] - self._num_reserved_tokens)
decoded_bytes = inputs_no_special.astype(np.uint8).tobytes()
return decoded_bytes.decode('utf-8', errors='replace')
def to_int(self, inputs: Union[str, bytes]) -> np.ndarray:
if isinstance(inputs, str):
inputs = inputs.encode('utf-8')
encoded = np.frombuffer(inputs, np.uint8).astype(np.int32)
encoded = encoded + self._num_reserved_tokens
return encoded.astype(np.int32)
@property
def vocab_size(self) -> int:
return 256 + self._num_reserved_tokens
@property
def pad_token(self) -> int:
return 0
@property
def bos_token(self) -> int:
return 1
@property
def eos_token(self) -> int:
return 2
@property
def mask_token(self) -> int:
return 3
@property
def cls_token(self) -> int:
return 4
@property
def sep_token(self) -> int:
return 5