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Author SHA1 Message Date
vanDuven
ed722b5ae9
Merge 5905513e32 into 9125613b53 2026-01-16 20:50:23 +00:00
Alexander Piskun
9125613b53
feat(api-nodes): extend ByteDance nodes with seedance-1-5-pro model (#11871)
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2026-01-15 22:09:07 -08:00
Jedrzej Kosinski
732b707397
Added try-except around seed_assets call in get_object_info with a logging statement (#11901) 2026-01-15 23:15:15 -05:00
comfyanonymous
4c816d5c69
Adjust memory usage factor calculation for flux2 klein. (#11900)
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2026-01-15 20:06:40 -05:00
ComfyUI Wiki
6125b3a5e7
Update workflow templates to v0.8.10 (#11899)
* chore: update workflow templates to v0.8.9

* Update requirements.txt
2026-01-15 13:12:13 -08:00
ComfyUI Wiki
12918a5f78
chore: update workflow templates to v0.8.7 (#11896) 2026-01-15 11:08:21 -08:00
vanDuven
5905513e32 revert fp16 support for Lumina2 2025-12-11 01:06:26 -05:00
vanDuven
a8ea6953ec Fix Z Image FP16 overflow via downscaling 2025-12-08 05:43:02 -05:00
6 changed files with 117 additions and 15 deletions

View File

@ -119,6 +119,9 @@ class JointAttention(nn.Module):
xv = xv.unsqueeze(3).repeat(1, 1, 1, n_rep, 1).flatten(2, 3)
output = optimized_attention_masked(xq.movedim(1, 2), xk.movedim(1, 2), xv.movedim(1, 2), self.n_local_heads, x_mask, skip_reshape=True, transformer_options=transformer_options)
if output.dtype == torch.float16:
output.div_(4)
return self.out(output)
@ -175,8 +178,12 @@ class FeedForward(nn.Module):
def _forward_silu_gating(self, x1, x3):
return clamp_fp16(F.silu(x1) * x3)
def forward(self, x):
return self.w2(self._forward_silu_gating(self.w1(x), self.w3(x)))
def forward(self, x, apply_fp16_downscale=False):
x3 = self.w3(x)
if x.dtype == torch.float16 and apply_fp16_downscale:
x3.div_(32)
return self.w2(self._forward_silu_gating(self.w1(x), x3))
class JointTransformerBlock(nn.Module):
@ -287,6 +294,7 @@ class JointTransformerBlock(nn.Module):
x = x + gate_mlp.unsqueeze(1).tanh() * self.ffn_norm2(
clamp_fp16(self.feed_forward(
modulate(self.ffn_norm1(x), scale_mlp),
apply_fp16_downscale=True,
))
)
else:

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@ -763,7 +763,7 @@ class Flux2(Flux):
def __init__(self, unet_config):
super().__init__(unet_config)
self.memory_usage_factor = self.memory_usage_factor * (2.0 * 2.0) * 2.36
self.memory_usage_factor = self.memory_usage_factor * (2.0 * 2.0) * (unet_config['hidden_size'] / 2604)
def get_model(self, state_dict, prefix="", device=None):
out = model_base.Flux2(self, device=device)

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@ -65,11 +65,13 @@ class TaskImageContent(BaseModel):
class Text2VideoTaskCreationRequest(BaseModel):
model: str = Field(...)
content: list[TaskTextContent] = Field(..., min_length=1)
generate_audio: bool | None = Field(...)
class Image2VideoTaskCreationRequest(BaseModel):
model: str = Field(...)
content: list[TaskTextContent | TaskImageContent] = Field(..., min_length=2)
generate_audio: bool | None = Field(...)
class TaskCreationResponse(BaseModel):
@ -141,4 +143,9 @@ VIDEO_TASKS_EXECUTION_TIME = {
"720p": 65,
"1080p": 100,
},
"seedance-1-5-pro-251215": {
"480p": 80,
"720p": 100,
"1080p": 150,
},
}

View File

@ -477,7 +477,12 @@ class ByteDanceTextToVideoNode(IO.ComfyNode):
inputs=[
IO.Combo.Input(
"model",
options=["seedance-1-0-pro-250528", "seedance-1-0-lite-t2v-250428", "seedance-1-0-pro-fast-251015"],
options=[
"seedance-1-5-pro-251215",
"seedance-1-0-pro-250528",
"seedance-1-0-lite-t2v-250428",
"seedance-1-0-pro-fast-251015",
],
default="seedance-1-0-pro-fast-251015",
),
IO.String.Input(
@ -528,6 +533,12 @@ class ByteDanceTextToVideoNode(IO.ComfyNode):
tooltip='Whether to add an "AI generated" watermark to the video.',
optional=True,
),
IO.Boolean.Input(
"generate_audio",
default=False,
tooltip="This parameter is ignored for any model except seedance-1-5-pro.",
optional=True,
),
],
outputs=[
IO.Video.Output(),
@ -552,7 +563,10 @@ class ByteDanceTextToVideoNode(IO.ComfyNode):
seed: int,
camera_fixed: bool,
watermark: bool,
generate_audio: bool = False,
) -> IO.NodeOutput:
if model == "seedance-1-5-pro-251215" and duration < 4:
raise ValueError("Minimum supported duration for Seedance 1.5 Pro is 4 seconds.")
validate_string(prompt, strip_whitespace=True, min_length=1)
raise_if_text_params(prompt, ["resolution", "ratio", "duration", "seed", "camerafixed", "watermark"])
@ -567,7 +581,11 @@ class ByteDanceTextToVideoNode(IO.ComfyNode):
)
return await process_video_task(
cls,
payload=Text2VideoTaskCreationRequest(model=model, content=[TaskTextContent(text=prompt)]),
payload=Text2VideoTaskCreationRequest(
model=model,
content=[TaskTextContent(text=prompt)],
generate_audio=generate_audio if model == "seedance-1-5-pro-251215" else None,
),
estimated_duration=max(1, math.ceil(VIDEO_TASKS_EXECUTION_TIME[model][resolution] * (duration / 10.0))),
)
@ -584,7 +602,12 @@ class ByteDanceImageToVideoNode(IO.ComfyNode):
inputs=[
IO.Combo.Input(
"model",
options=["seedance-1-0-pro-250528", "seedance-1-0-lite-t2v-250428", "seedance-1-0-pro-fast-251015"],
options=[
"seedance-1-5-pro-251215",
"seedance-1-0-pro-250528",
"seedance-1-0-lite-i2v-250428",
"seedance-1-0-pro-fast-251015",
],
default="seedance-1-0-pro-fast-251015",
),
IO.String.Input(
@ -639,6 +662,12 @@ class ByteDanceImageToVideoNode(IO.ComfyNode):
tooltip='Whether to add an "AI generated" watermark to the video.',
optional=True,
),
IO.Boolean.Input(
"generate_audio",
default=False,
tooltip="This parameter is ignored for any model except seedance-1-5-pro.",
optional=True,
),
],
outputs=[
IO.Video.Output(),
@ -664,7 +693,10 @@ class ByteDanceImageToVideoNode(IO.ComfyNode):
seed: int,
camera_fixed: bool,
watermark: bool,
generate_audio: bool = False,
) -> IO.NodeOutput:
if model == "seedance-1-5-pro-251215" and duration < 4:
raise ValueError("Minimum supported duration for Seedance 1.5 Pro is 4 seconds.")
validate_string(prompt, strip_whitespace=True, min_length=1)
raise_if_text_params(prompt, ["resolution", "ratio", "duration", "seed", "camerafixed", "watermark"])
validate_image_dimensions(image, min_width=300, min_height=300, max_width=6000, max_height=6000)
@ -686,6 +718,7 @@ class ByteDanceImageToVideoNode(IO.ComfyNode):
payload=Image2VideoTaskCreationRequest(
model=model,
content=[TaskTextContent(text=prompt), TaskImageContent(image_url=TaskImageContentUrl(url=image_url))],
generate_audio=generate_audio if model == "seedance-1-5-pro-251215" else None,
),
estimated_duration=max(1, math.ceil(VIDEO_TASKS_EXECUTION_TIME[model][resolution] * (duration / 10.0))),
)
@ -703,7 +736,7 @@ class ByteDanceFirstLastFrameNode(IO.ComfyNode):
inputs=[
IO.Combo.Input(
"model",
options=["seedance-1-0-pro-250528", "seedance-1-0-lite-i2v-250428"],
options=["seedance-1-5-pro-251215", "seedance-1-0-pro-250528", "seedance-1-0-lite-i2v-250428"],
default="seedance-1-0-lite-i2v-250428",
),
IO.String.Input(
@ -762,6 +795,12 @@ class ByteDanceFirstLastFrameNode(IO.ComfyNode):
tooltip='Whether to add an "AI generated" watermark to the video.',
optional=True,
),
IO.Boolean.Input(
"generate_audio",
default=False,
tooltip="This parameter is ignored for any model except seedance-1-5-pro.",
optional=True,
),
],
outputs=[
IO.Video.Output(),
@ -788,7 +827,10 @@ class ByteDanceFirstLastFrameNode(IO.ComfyNode):
seed: int,
camera_fixed: bool,
watermark: bool,
generate_audio: bool = False,
) -> IO.NodeOutput:
if model == "seedance-1-5-pro-251215" and duration < 4:
raise ValueError("Minimum supported duration for Seedance 1.5 Pro is 4 seconds.")
validate_string(prompt, strip_whitespace=True, min_length=1)
raise_if_text_params(prompt, ["resolution", "ratio", "duration", "seed", "camerafixed", "watermark"])
for i in (first_frame, last_frame):
@ -821,6 +863,7 @@ class ByteDanceFirstLastFrameNode(IO.ComfyNode):
TaskImageContent(image_url=TaskImageContentUrl(url=str(download_urls[0])), role="first_frame"),
TaskImageContent(image_url=TaskImageContentUrl(url=str(download_urls[1])), role="last_frame"),
],
generate_audio=generate_audio if model == "seedance-1-5-pro-251215" else None,
),
estimated_duration=max(1, math.ceil(VIDEO_TASKS_EXECUTION_TIME[model][resolution] * (duration / 10.0))),
)
@ -896,7 +939,41 @@ class ByteDanceImageReferenceNode(IO.ComfyNode):
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=PRICE_BADGE_VIDEO,
price_badge=IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["model", "duration", "resolution"]),
expr="""
(
$priceByModel := {
"seedance-1-0-pro": {
"480p":[0.23,0.24],
"720p":[0.51,0.56]
},
"seedance-1-0-lite": {
"480p":[0.17,0.18],
"720p":[0.37,0.41]
}
};
$model := widgets.model;
$modelKey :=
$contains($model, "seedance-1-0-pro") ? "seedance-1-0-pro" :
"seedance-1-0-lite";
$resolution := widgets.resolution;
$resKey :=
$contains($resolution, "720") ? "720p" :
"480p";
$modelPrices := $lookup($priceByModel, $modelKey);
$baseRange := $lookup($modelPrices, $resKey);
$min10s := $baseRange[0];
$max10s := $baseRange[1];
$scale := widgets.duration / 10;
$minCost := $min10s * $scale;
$maxCost := $max10s * $scale;
($minCost = $maxCost)
? {"type":"usd","usd": $minCost}
: {"type":"range_usd","min_usd": $minCost, "max_usd": $maxCost}
)
""",
),
)
@classmethod
@ -967,10 +1044,15 @@ def raise_if_text_params(prompt: str, text_params: list[str]) -> None:
PRICE_BADGE_VIDEO = IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["model", "duration", "resolution"]),
depends_on=IO.PriceBadgeDepends(widgets=["model", "duration", "resolution", "generate_audio"]),
expr="""
(
$priceByModel := {
"seedance-1-5-pro": {
"480p":[0.12,0.12],
"720p":[0.26,0.26],
"1080p":[0.58,0.59]
},
"seedance-1-0-pro": {
"480p":[0.23,0.24],
"720p":[0.51,0.56],
@ -989,6 +1071,7 @@ PRICE_BADGE_VIDEO = IO.PriceBadge(
};
$model := widgets.model;
$modelKey :=
$contains($model, "seedance-1-5-pro") ? "seedance-1-5-pro" :
$contains($model, "seedance-1-0-pro-fast") ? "seedance-1-0-pro-fast" :
$contains($model, "seedance-1-0-pro") ? "seedance-1-0-pro" :
"seedance-1-0-lite";
@ -1002,11 +1085,12 @@ PRICE_BADGE_VIDEO = IO.PriceBadge(
$min10s := $baseRange[0];
$max10s := $baseRange[1];
$scale := widgets.duration / 10;
$minCost := $min10s * $scale;
$maxCost := $max10s * $scale;
$audioMultiplier := ($modelKey = "seedance-1-5-pro" and widgets.generate_audio) ? 2 : 1;
$minCost := $min10s * $scale * $audioMultiplier;
$maxCost := $max10s * $scale * $audioMultiplier;
($minCost = $maxCost)
? {"type":"usd","usd": $minCost}
: {"type":"range_usd","min_usd": $minCost, "max_usd": $maxCost}
? {"type":"usd","usd": $minCost, "format": { "approximate": true }}
: {"type":"range_usd","min_usd": $minCost, "max_usd": $maxCost, "format": { "approximate": true }}
)
""",
)

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@ -1,5 +1,5 @@
comfyui-frontend-package==1.36.14
comfyui-workflow-templates==0.8.4
comfyui-workflow-templates==0.8.10
comfyui-embedded-docs==0.4.0
torch
torchsde

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@ -686,7 +686,10 @@ class PromptServer():
@routes.get("/object_info")
async def get_object_info(request):
seed_assets(["models"])
try:
seed_assets(["models"])
except Exception as e:
logging.error(f"Failed to seed assets: {e}")
with folder_paths.cache_helper:
out = {}
for x in nodes.NODE_CLASS_MAPPINGS: