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Running
on
A10G
File size: 2,641 Bytes
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from transformers import CLIPTokenizer
from transformers.utils import logging
logger = logging.get_logger(__name__)
VOCAB_FILES_NAMES = {
"vocab_file": "vocab.json",
"merges_file": "merges.txt",
}
PRETRAINED_VOCAB_FILES_MAP = {
"vocab_file": {
"lb203/LanguageBind-Audio": "https://huggingface.co/lb203/LanguageBind-Audio/resolve/main/vocab.json",
},
"merges_file": {
"lb203/LanguageBind-Audio": "https://huggingface.co/lb203/LanguageBind-Audio/resolve/main/merges.txt",
},
}
PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
"lb203/LanguageBind-Audio": 77,
}
PRETRAINED_INIT_CONFIGURATION = {
"lb203/LanguageBind-Audio": {},
}
class LanguageBindAudioTokenizer(CLIPTokenizer):
"""
Construct a CLIP tokenizer. Based on byte-level Byte-Pair-Encoding.
This tokenizer inherits from [`PreTrainedTokenizer`] which contains most of the main methods. Users should refer to
this superclass for more information regarding those methods.
Args:
vocab_file (`str`):
Path to the vocabulary file.
merges_file (`str`):
Path to the merges file.
errors (`str`, *optional*, defaults to `"replace"`):
Paradigm to follow when decoding bytes to UTF-8. See
[bytes.decode](https://docs.python.org/3/library/stdtypes.html#bytes.decode) for more information.
unk_token (`str`, *optional*, defaults to `<|endoftext|>`):
The unknown token. A token that is not in the vocabulary cannot be converted to an ID and is set to be this
token instead.
bos_token (`str`, *optional*, defaults to `<|startoftext|>`):
The beginning of sequence token.
eos_token (`str`, *optional*, defaults to `<|endoftext|>`):
The end of sequence token.
"""
vocab_files_names = VOCAB_FILES_NAMES
pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
model_input_names = ["input_ids", "attention_mask"]
def __init__(
self,
vocab_file,
merges_file,
errors="replace",
unk_token="<|endoftext|>",
bos_token="<|startoftext|>",
eos_token="<|endoftext|>",
pad_token="<|endoftext|>", # hack to enable padding
**kwargs,
):
super(LanguageBindAudioTokenizer, self).__init__(
vocab_file,
merges_file,
errors,
unk_token,
bos_token,
eos_token,
pad_token, # hack to enable padding
**kwargs,) |