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[pull] master from comfyanonymous:master #54

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Merged
merged 7 commits into from
May 12, 2025
Merged

[pull] master from comfyanonymous:master #54

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31e9e36
remove aspect ratio from kling request (#8062)
christian-byrne May 12, 2025
640c47e
Fix torch warning about deprecated function. (#8075)
comfyanonymous May 12, 2025
158419f
ComfyUI version 0.3.34
comfyanonymous May 12, 2025
b4abca8
add opus and mp3 to audio output node (#8019)
thot-experiment May 12, 2025
b7ed5f5
string node (#7952)
jtydhr88 May 12, 2025
f5cacae
Update frontend to v1.19 (#8076)
May 12, 2025
9ad287f
add support to record video as output for 3d node (#7927)
jtydhr88 May 12, 2025
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22 changes: 9 additions & 13 deletions comfy/ldm/ace/vae/music_vocoder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,11 +8,7 @@

import numpy as np
import torch.nn.functional as F
from torch.nn.utils import weight_norm
from torch.nn.utils.parametrize import remove_parametrizations as remove_weight_norm
# from diffusers.models.modeling_utils import ModelMixin
# from diffusers.loaders import FromOriginalModelMixin
# from diffusers.configuration_utils import ConfigMixin, register_to_config

from .music_log_mel import LogMelSpectrogram

Expand Down Expand Up @@ -259,7 +255,7 @@ def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):

self.convs1 = nn.ModuleList(
[
weight_norm(
torch.nn.utils.parametrizations.weight_norm(
ops.Conv1d(
channels,
channels,
Expand All @@ -269,7 +265,7 @@ def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
padding=get_padding(kernel_size, dilation[0]),
)
),
weight_norm(
torch.nn.utils.parametrizations.weight_norm(
ops.Conv1d(
channels,
channels,
Expand All @@ -279,7 +275,7 @@ def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
padding=get_padding(kernel_size, dilation[1]),
)
),
weight_norm(
torch.nn.utils.parametrizations.weight_norm(
ops.Conv1d(
channels,
channels,
Expand All @@ -294,7 +290,7 @@ def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):

self.convs2 = nn.ModuleList(
[
weight_norm(
torch.nn.utils.parametrizations.weight_norm(
ops.Conv1d(
channels,
channels,
Expand All @@ -304,7 +300,7 @@ def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
padding=get_padding(kernel_size, 1),
)
),
weight_norm(
torch.nn.utils.parametrizations.weight_norm(
ops.Conv1d(
channels,
channels,
Expand All @@ -314,7 +310,7 @@ def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
padding=get_padding(kernel_size, 1),
)
),
weight_norm(
torch.nn.utils.parametrizations.weight_norm(
ops.Conv1d(
channels,
channels,
Expand Down Expand Up @@ -366,7 +362,7 @@ def __init__(
prod(upsample_rates) == hop_length
), f"hop_length must be {prod(upsample_rates)}"

self.conv_pre = weight_norm(
self.conv_pre = torch.nn.utils.parametrizations.weight_norm(
ops.Conv1d(
num_mels,
upsample_initial_channel,
Expand All @@ -386,7 +382,7 @@ def __init__(
for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
c_cur = upsample_initial_channel // (2 ** (i + 1))
self.ups.append(
weight_norm(
torch.nn.utils.parametrizations.weight_norm(
ops.ConvTranspose1d(
upsample_initial_channel // (2**i),
upsample_initial_channel // (2 ** (i + 1)),
Expand Down Expand Up @@ -421,7 +417,7 @@ def __init__(
self.resblocks.append(ResBlock1(ch, k, d))

self.activation_post = post_activation()
self.conv_post = weight_norm(
self.conv_post = torch.nn.utils.parametrizations.weight_norm(
ops.Conv1d(
ch,
1,
Expand Down
10 changes: 2 additions & 8 deletions comfy/ldm/audio/autoencoder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -75,16 +75,10 @@ def forward(self, x):
return x

def WNConv1d(*args, **kwargs):
try:
return torch.nn.utils.parametrizations.weight_norm(ops.Conv1d(*args, **kwargs))
except:
return torch.nn.utils.weight_norm(ops.Conv1d(*args, **kwargs)) #support pytorch 2.1 and older
return torch.nn.utils.parametrizations.weight_norm(ops.Conv1d(*args, **kwargs))

def WNConvTranspose1d(*args, **kwargs):
try:
return torch.nn.utils.parametrizations.weight_norm(ops.ConvTranspose1d(*args, **kwargs))
except:
return torch.nn.utils.weight_norm(ops.ConvTranspose1d(*args, **kwargs)) #support pytorch 2.1 and older
return torch.nn.utils.parametrizations.weight_norm(ops.ConvTranspose1d(*args, **kwargs))

def get_activation(activation: Literal["elu", "snake", "none"], antialias=False, channels=None) -> nn.Module:
if activation == "elu":
Expand Down
1 change: 0 additions & 1 deletion comfy_api_nodes/nodes_kling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -671,7 +671,6 @@ def api_call(
negative_prompt=negative_prompt if negative_prompt else None,
cfg_scale=cfg_scale,
mode=KlingVideoGenMode(mode),
aspect_ratio=KlingVideoGenAspectRatio(aspect_ratio),
duration=KlingVideoGenDuration(duration),
camera_control=camera_control,
),
Expand Down
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