File size: 4,392 Bytes
2577656 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 | # Adapted for diffusers from multimodal-art-projection/YuE at commit ef1936f2ee39fe8de486a0f47a481c95f8d4da87.
# Licensed under Apache-2.0; see LICENSE.
from __future__ import annotations
import math
from dataclasses import asdict, dataclass
EOD = 151643
ABC_START, ABC_END = (151847, 151848)
MUSIC_START, MUSIC_END = (151851, 151852)
CODEC_OFFSET, CODEC_SIZE = (151853, 32768)
CONTEXT = 24576
INSTRUCTIONS = {
"off": "Generate music with codec tokens from the given conditions.",
"melody": "Generate a melody-only ABC transcription without chord symbols, then generate music with codec tokens from the given conditions.",
"full": "Generate a chord-annotated ABC transcription, then generate music with codec tokens from the given conditions.",
}
@dataclass(frozen=True)
class Sampling:
temperature: float = 1.0
top_p: float = 0.95
top_k: int = 100
repetition_penalty: float = 1.2
penalty_window: int = 50
min_tokens: int = 200
max_tokens: int = 9000
def __post_init__(self):
if any(type(x) is not int for x in (self.top_k, self.penalty_window, self.min_tokens, self.max_tokens)):
raise ValueError("Sampling counts must be integers")
if not all(math.isfinite(x) for x in (self.temperature, self.top_p, self.repetition_penalty)):
raise ValueError("Sampling numbers must be finite")
if not 0 <= self.temperature <= 5 or not 0 < self.top_p <= 1 or self.top_k < 1:
raise ValueError("Invalid sampling temperature/top_p/top_k")
if self.repetition_penalty <= 0 or not 1 <= self.penalty_window <= 100:
raise ValueError("Invalid repetition penalty/window")
if not 0 <= self.min_tokens <= self.max_tokens or self.max_tokens < 1:
raise ValueError("Require 0 <= min_tokens <= max_tokens")
ABC_SAMPLING = Sampling(0.7, 0.9, 30, 1.005, 100, 32, 4096)
SEMANTIC_SAMPLING = Sampling()
def resolve_sampling(overrides, default):
if overrides is None:
return default
if not isinstance(overrides, dict):
raise TypeError("Sampling overrides must be a dictionary")
return Sampling(**{**asdict(default), **overrides})
@dataclass(frozen=True)
class SongRequest:
style: str
lyrics: str
cot: str = "full"
seed: int = 831001
abc: str | None = None
def __post_init__(self):
if self.cot not in INSTRUCTIONS:
raise ValueError("cot must be off, melody or full")
if not isinstance(self.style, str) or not isinstance(self.lyrics, str):
raise TypeError("style and lyrics must be strings")
if type(self.seed) is not int or not 0 <= self.seed < 2**63:
raise ValueError("seed must be an integer in [0, 2**63)")
if self.abc is not None and (self.cot == "off" or not isinstance(self.abc, str) or not self.abc.strip()):
raise ValueError("External ABC requires nonempty text and cot=melody/full")
def text(self):
return f"{INSTRUCTIONS[self.cot]}\n[Tags]\n{self.style}\n[Lyrics]\n{self.lyrics}\n"
def _check_abc_ids(abc_ids):
abc_ids = list(abc_ids)
if any(type(token) is not int or not 0 <= token < EOD for token in abc_ids):
raise ValueError("ABC IDs must remain inside the ordinary text vocabulary")
return abc_ids
def token_prefixes(request, tokenizer, abc_ids=None):
base = [EOD] + tokenizer.encode(request.text())
if request.cot == "off":
return base + [ABC_START, ABC_END, MUSIC_START]
if abc_ids is None:
if request.abc is None:
return base + [ABC_START]
abc_ids = tokenizer.encode(request.abc)
return base + [ABC_START] + _check_abc_ids(abc_ids) + [ABC_END, MUSIC_START]
def negative_prefix(request, tokenizer, abc_ids=None):
base = [EOD] + tokenizer.encode(INSTRUCTIONS[request.cot])
if request.cot == "off":
return base + [MUSIC_START]
if abc_ids is None:
raise ValueError("Symbolic CFG must retain the exact positive-branch ABC IDs")
return base + [ABC_START] + _check_abc_ids(abc_ids) + [ABC_END, MUSIC_START]
def chunk_ranges(frames, prefix_tokens, context=CONTEXT):
size = min((context - prefix_tokens - 3) // 2, CONTEXT)
if frames < 1 or size < 1:
raise ValueError("Empty codec or prefix leaves no acoustic context")
return [(a, min(a + size, frames)) for a in range(0, frames, size)]
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