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from fastai.basics import *
from .numpy_encode import *
from .music_transformer import transform
BOS = 'xxbos'
PAD = 'xxpad'
EOS = 'xxeos'
MASK = 'xxmask' # Used for BERT masked language modeling.
CSEQ = 'xxcseq' # Used for Seq2Seq translation - denotes start of chord sequence
MSEQ = 'xxmseq' # Used for Seq2Seq translation - denotes start of melody sequence
# Deprecated tokens. Kept for compatibility
S2SCLS = 'xxs2scls' # deprecated
NSCLS = 'xxnscls' # deprecated
SEP = 'xxsep' # Used to denote end of timestep (required for polyphony). separator idx = -1 (part of notes)
SPECIAL_TOKS = [BOS, PAD, EOS, S2SCLS, MASK, CSEQ, MSEQ, NSCLS, SEP] # Important: SEP token must be last
NOTE_TOKS = [f'n{i}' for i in range(NOTE_SIZE)]
DUR_TOKS = [f'd{i}' for i in range(DUR_SIZE)]
NOTE_START, NOTE_END = NOTE_TOKS[0], NOTE_TOKS[-1]
DUR_START, DUR_END = DUR_TOKS[0], DUR_TOKS[-1]
MTEMPO_SIZE = 10
MTEMPO_OFF = 'mt0'
MTEMPO_TOKS = [f'mt{i}' for i in range(MTEMPO_SIZE)]
# Vocab - token to index mapping
class MusicVocab():
"Contain the correspondence between numbers and tokens and numericalize."
def __init__(self, itos:Collection[str]):
self.itos = itos
self.stoi = {v:k for k,v in enumerate(self.itos)}
def numericalize(self, t:Collection[str]) -> List[int]:
"Convert a list of tokens `t` to their ids."
return [self.stoi[w] for w in t]
def textify(self, nums:Collection[int], sep=' ') -> List[str]:
"Convert a list of `nums` to their tokens."
items = [self.itos[i] for i in nums]
return sep.join(items) if sep is not None else items
def to_music_item(self, idxenc):
return transform.MusicItem(idxenc, self)
@property
def mask_idx(self): return self.stoi[MASK]
@property
def pad_idx(self): return self.stoi[PAD]
@property
def bos_idx(self): return self.stoi[BOS]
@property
def sep_idx(self): return self.stoi[SEP]
@property
def npenc_range(self): return (self.stoi[SEP], self.stoi[DUR_END]+1)
@property
def note_range(self): return self.stoi[NOTE_START], self.stoi[NOTE_END]+1
@property
def dur_range(self): return self.stoi[DUR_START], self.stoi[DUR_END]+1
def is_duration(self, idx):
return idx >= self.dur_range[0] and idx < self.dur_range[1]
def is_duration_or_pad(self, idx):
return idx == self.pad_idx or self.is_duration(idx)
def __getstate__(self):
return {'itos':self.itos}
def __setstate__(self, state:dict):
self.itos = state['itos']
self.stoi = {v:k for k,v in enumerate(self.itos)}
def __len__(self): return len(self.itos)
def save(self, path):
"Save `self.itos` in `path`"
pickle.dump(self.itos, open(path, 'wb'))
@classmethod
def create(cls) -> 'Vocab':
"Create a vocabulary from a set of `tokens`."
itos = SPECIAL_TOKS + NOTE_TOKS + DUR_TOKS + MTEMPO_TOKS
if len(itos)%8 != 0:
itos = itos + [f'dummy{i}' for i in range(len(itos)%8)]
return cls(itos)
@classmethod
def load(cls, path):
"Load the `Vocab` contained in `path`"
itos = pickle.load(open(path, 'rb'))
return cls(itos)
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