Merge branch 'master' into blueprint-gradient-slider

This commit is contained in:
Jedrzej Kosinski
2026-02-20 22:53:06 -08:00
committed by GitHub
4 changed files with 10 additions and 4 deletions

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@@ -229,9 +229,9 @@ AMD users can install rocm and pytorch with pip if you don't have it already ins
```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.1```
This is the command to install the nightly with ROCm 7.1 which might have some performance improvements:
This is the command to install the nightly with ROCm 7.2 which might have some performance improvements:
```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.1```
```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.2```
### AMD GPUs (Experimental: Windows and Linux), RDNA 3, 3.5 and 4 only.

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@@ -176,6 +176,8 @@ class InputTypeOptions(TypedDict):
"""COMBO type only. Specifies the configuration for a multi-select widget.
Available after ComfyUI frontend v1.13.4
https://github.com/Comfy-Org/ComfyUI_frontend/pull/2987"""
gradient_stops: NotRequired[list[list[float]]]
"""Gradient color stops for gradientslider display mode. Each stop is [offset, r, g, b] (``FLOAT``)."""
class HiddenInputTypeDict(TypedDict):

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@@ -444,7 +444,7 @@ class VideoFromComponents(VideoInput):
output.mux(packet)
if audio_stream and self.__components.audio:
frame = av.AudioFrame.from_ndarray(waveform.float().cpu().numpy(), format='fltp', layout=layout)
frame = av.AudioFrame.from_ndarray(waveform.float().cpu().contiguous().numpy(), format='fltp', layout=layout)
frame.sample_rate = audio_sample_rate
frame.pts = 0
output.mux(audio_stream.encode(frame))

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@@ -73,6 +73,7 @@ class RemoteOptions:
class NumberDisplay(str, Enum):
number = "number"
slider = "slider"
gradient_slider = "gradientslider"
class ControlAfterGenerate(str, Enum):
@@ -296,13 +297,15 @@ class Float(ComfyTypeIO):
'''Float input.'''
def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None, lazy: bool=None,
default: float=None, min: float=None, max: float=None, step: float=None, round: float=None,
display_mode: NumberDisplay=None, socketless: bool=None, force_input: bool=None, extra_dict=None, raw_link: bool=None, advanced: bool=None):
display_mode: NumberDisplay=None, gradient_stops: list[list[float]]=None,
socketless: bool=None, force_input: bool=None, extra_dict=None, raw_link: bool=None, advanced: bool=None):
super().__init__(id, display_name, optional, tooltip, lazy, default, socketless, None, force_input, extra_dict, raw_link, advanced)
self.min = min
self.max = max
self.step = step
self.round = round
self.display_mode = display_mode
self.gradient_stops = gradient_stops
self.default: float
def as_dict(self):
@@ -312,6 +315,7 @@ class Float(ComfyTypeIO):
"step": self.step,
"round": self.round,
"display": self.display_mode,
"gradient_stops": self.gradient_stops,
})
@comfytype(io_type="STRING")