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mrfakename
2025-05-06 18:59:32 -07:00
parent 54da683d36
commit a5746eaab6
36 changed files with 2928 additions and 1251 deletions
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acestep/music_dcae/music_vocoder.py
+22 -11
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@@ -1,3 +1,11 @@
"""
ACE-Step: A Step Towards Music Generation Foundation Model
https://github.com/ace-step/ACE-Step
Apache 2.0 License
"""
import librosa
import torch
from torch import nn
@@ -132,13 +140,11 @@ class ConvNeXtBlock(nn.Module):
self.act = nn.GELU()
self.pwconv2 = nn.Linear(int(mlp_ratio * dim), dim)
self.gamma = (
nn.Parameter(layer_scale_init_value *
torch.ones((dim)), requires_grad=True)
nn.Parameter(layer_scale_init_value * torch.ones((dim)), requires_grad=True)
if layer_scale_init_value > 0
else None
)
self.drop_path = DropPath(
drop_path) if drop_path > 0.0 else nn.Identity()
self.drop_path = DropPath(drop_path) if drop_path > 0.0 else nn.Identity()
def forward(self, x, apply_residual: bool = True):
input = x
@@ -367,8 +373,7 @@ class HiFiGANGenerator(nn.Module):
upsample_rates: Tuple[int] = (8, 8, 2, 2, 2),
upsample_kernel_sizes: Tuple[int] = (16, 16, 8, 2, 2),
resblock_kernel_sizes: Tuple[int] = (3, 7, 11),
resblock_dilation_sizes: Tuple[Tuple[int]] = (
(1, 3, 5), (1, 3, 5), (1, 3, 5)),
resblock_dilation_sizes: Tuple[Tuple[int]] = ((1, 3, 5), (1, 3, 5), (1, 3, 5)),
num_mels: int = 128,
upsample_initial_channel: int = 512,
use_template: bool = True,
@@ -417,7 +422,7 @@ class HiFiGANGenerator(nn.Module):
continue
if i + 1 < len(upsample_rates):
stride_f0 = np.prod(upsample_rates[i + 1:])
stride_f0 = np.prod(upsample_rates[i + 1 :])
self.noise_convs.append(
Conv1d(
1,
@@ -485,7 +490,7 @@ class HiFiGANGenerator(nn.Module):
class ADaMoSHiFiGANV1(ModelMixin, ConfigMixin, FromOriginalModelMixin):
@register_to_config
def __init__(
self,
@@ -498,7 +503,11 @@ class ADaMoSHiFiGANV1(ModelMixin, ConfigMixin, FromOriginalModelMixin):
upsample_kernel_sizes: Tuple[int] = (8, 8, 4, 4, 4, 4, 4),
resblock_kernel_sizes: Tuple[int] = (3, 7, 11, 13),
resblock_dilation_sizes: Tuple[Tuple[int]] = (
(1, 3, 5), (1, 3, 5), (1, 3, 5), (1, 3, 5)),
(1, 3, 5),
(1, 3, 5),
(1, 3, 5),
(1, 3, 5),
),
num_mels: int = 512,
upsample_initial_channel: int = 1024,
use_template: bool = False,
@@ -555,7 +564,7 @@ class ADaMoSHiFiGANV1(ModelMixin, ConfigMixin, FromOriginalModelMixin):
@torch.no_grad()
def encode(self, x):
return self.mel_transform(x)
def forward(self, mel):
y = self.backbone(mel)
y = self.head(y)
@@ -566,7 +575,9 @@ if __name__ == "__main__":
import soundfile as sf
x = "test_audio.flac"
model = ADaMoSHiFiGANV1.from_pretrained("./checkpoints/music_vocoder", local_files_only=True)
model = ADaMoSHiFiGANV1.from_pretrained(
"./checkpoints/music_vocoder", local_files_only=True
)
wav, sr = librosa.load(x, sr=44100, mono=True)
wav = torch.from_numpy(wav).float()[None]