Files
Runware-ComfyUI-Runware/modules/acceleratorOptions.py
T
Sirshendu Ganguly 056ade0661 Refactor: Use librosa instead of torchaudio, Add dedicated handlers for all use parameters and fix widget ordering
- Use librosa instead of torchaudio for mediaStorage
- Created dedicated toggle handlers for Image Inference, Video Inference, Upscaler, Audio Inference, Accelerator Options, Bytedance Provider Settings, and OpenAI Provider Settings
- Fixed Audio Inference widget ordering (use parameters now appear before their corresponding parameters)
- All handlers use the same proven pattern from videoInferenceDimensionsHandler
- Improved widget disabling/enabling functionality across all nodes
2025-11-05 22:31:15 -05:00

173 lines
8.9 KiB
Python

class acceleratorOptions:
"""Accelerator Options node for configuring caching options for faster generation"""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {},
"optional": {
"fbcache": ("BOOLEAN", {
"tooltip": "Enable Frame Buffer Cache for faster generation",
"default": None,
}),
"useCacheDistance": ("BOOLEAN", {
"tooltip": "Enable to include cacheDistance parameter in API request.",
"default": False,
}),
"cacheDistance": ("FLOAT", {
"tooltip": "Cache distance parameter for FBCache",
"default": 0.0,
"min": 0.0,
"max": 1.0,
"step": 0.01,
}),
"teaCache": ("BOOLEAN", {
"tooltip": "Enable TeaCache for transformer-based models (Flux, SD3). Does not work with UNet models like SDXL or SD1.5. Particularly effective for iterative editing workflows.",
"default": None,
}),
"useTeaCacheDistance": ("BOOLEAN", {
"tooltip": "Enable to include teaCacheDistance parameter in API request.",
"default": False,
}),
"teaCacheDistance": ("FLOAT", {
"tooltip": "Controls TeaCache aggressiveness: 0.0 (conservative/quality) to 1.0 (aggressive/speed). Lower values maintain quality, higher values prioritize speed.",
"default": 0.0,
"min": 0.0,
"max": 1.0,
"step": 0.01,
}),
"deepCache": ("BOOLEAN", {
"tooltip": "Enable DeepCache for UNet-based models (SDXL, SD1.5). Not applicable to transformer models. Provides performance improvements for high-throughput scenarios.",
"default": None,
}),
"useDeepCacheOptions": ("BOOLEAN", {
"tooltip": "Enable to include DeepCache options (deepCacheInterval and deepCacheBranchId) in API request.",
"default": False,
}),
"deepCacheInterval": ("INT", {
"tooltip": "Frequency of feature caching - steps between cache operations. Larger values = faster but may impact quality. Smaller values = better quality but slower.",
"default": 1,
"min": 1,
"max": 20,
}),
"deepCacheBranchId": ("INT", {
"tooltip": "Network branch for caching (0=shallowest, deeper=more conservative). Lower IDs = aggressive caching/faster, higher IDs = conservative caching/better quality.",
"default": 0,
"min": 0,
"max": 10,
}),
"useCacheSteps": ("BOOLEAN", {
"tooltip": "Enable to include cache step control parameters (step numbers) in API request.",
"default": False,
}),
"cacheStartStep": ("INT", {
"tooltip": "Inference step number where caching begins (0 to total steps). Only included when useCacheSteps is enabled and value > 0.",
"default": 0,
"min": 0,
"max": 200,
}),
"cacheEndStep": ("INT", {
"tooltip": "Inference step number where caching stops (must be > cacheStartStep). Only included when useCacheSteps is enabled.",
"default": 1,
"min": 1,
"max": 200,
}),
"useCachePercentageSteps": ("BOOLEAN", {
"tooltip": "Enable to include cache step control parameters (percentages) in API request.",
"default": False,
}),
"cacheStartStepPercentage": ("INT", {
"tooltip": "Percentage of total steps where caching begins (0-99). Only included when useCachePercentageSteps is enabled and value > 0.",
"default": 0,
"min": 0,
"max": 99,
}),
"cacheEndStepPercentage": ("INT", {
"tooltip": "Percentage of total steps where caching stops (must be > cacheStartStepPercentage). Only included when useCachePercentageSteps is enabled.",
"default": 1,
"min": 1,
"max": 100,
}),
"useCacheMaxConsecutiveSteps": ("BOOLEAN", {
"tooltip": "Enable to include cacheMaxConsecutiveSteps parameter in API request.",
"default": False,
}),
"cacheMaxConsecutiveSteps": ("INT", {
"tooltip": "Max consecutive steps using cached computations before forcing fresh computation. Prevents quality degradation from extended cache reuse.",
"default": 1,
"min": 1,
"max": 5,
}),
},
}
DESCRIPTION = "Configure Runware accelerator options for faster image generation. Supports TeaCache (transformer models like Flux/SD3) and DeepCache (UNet models like SDXL/SD1.5) with fine-grained control over caching parameters and step ranges. Note: These caching methods work best with deterministic schedulers (Euler, DDIM) rather than stochastic schedulers."
FUNCTION = "acceleratorOptions"
RETURN_TYPES = ("RUNWAREACCELERATOR",)
RETURN_NAMES = ("Runware Accelerator",)
CATEGORY = "Runware"
def acceleratorOptions(self, **kwargs):
"""Build accelerator options dictionary"""
params = self._extractParameters(kwargs)
acceleratorOptions = self._buildAcceleratorOptions(params)
return (acceleratorOptions,)
def _extractParameters(self, kwargs):
"""Extract all parameters from kwargs"""
return {
"fbcache": kwargs.get("fbcache"),
"useCacheDistance": kwargs.get("useCacheDistance", False),
"cacheDistance": kwargs.get("cacheDistance", 0.0),
"teaCache": kwargs.get("teaCache"),
"useTeaCacheDistance": kwargs.get("useTeaCacheDistance", False),
"teaCacheDistance": kwargs.get("teaCacheDistance", 0.0),
"deepCache": kwargs.get("deepCache"),
"useDeepCacheOptions": kwargs.get("useDeepCacheOptions", False),
"deepCacheInterval": kwargs.get("deepCacheInterval", 1),
"deepCacheBranchId": kwargs.get("deepCacheBranchId", 0),
"useCacheSteps": kwargs.get("useCacheSteps", False),
"cacheStartStep": kwargs.get("cacheStartStep", 0),
"cacheEndStep": kwargs.get("cacheEndStep", 1),
"useCachePercentageSteps": kwargs.get("useCachePercentageSteps", False),
"cacheStartStepPercentage": kwargs.get("cacheStartStepPercentage", 0),
"cacheEndStepPercentage": kwargs.get("cacheEndStepPercentage", 1),
"useCacheMaxConsecutiveSteps": kwargs.get("useCacheMaxConsecutiveSteps", False),
"cacheMaxConsecutiveSteps": kwargs.get("cacheMaxConsecutiveSteps", 1),
}
def _buildAcceleratorOptions(self, params):
"""Build accelerator options dictionary from parameters"""
acceleratorOptions = {}
if params["fbcache"] is True:
acceleratorOptions["fbcache"] = params["fbcache"]
if params["useCacheDistance"]:
acceleratorOptions["cacheDistance"] = params["cacheDistance"]
if params["teaCache"] is True:
acceleratorOptions["teaCache"] = params["teaCache"]
if params["useTeaCacheDistance"]:
acceleratorOptions["teaCacheDistance"] = params["teaCacheDistance"]
if params["deepCache"] is True:
acceleratorOptions["deepCache"] = params["deepCache"]
if params["useDeepCacheOptions"]:
acceleratorOptions["deepCacheInterval"] = params["deepCacheInterval"]
acceleratorOptions["deepCacheBranchId"] = params["deepCacheBranchId"]
if params["useCacheSteps"]:
if params["cacheStartStep"] > 0:
acceleratorOptions["cacheStartStep"] = params["cacheStartStep"]
acceleratorOptions["cacheEndStep"] = params["cacheEndStep"]
if params["useCachePercentageSteps"]:
if params["cacheStartStepPercentage"] > 0:
acceleratorOptions["cacheStartStepPercentage"] = params["cacheStartStepPercentage"]
acceleratorOptions["cacheEndStepPercentage"] = params["cacheEndStepPercentage"]
if params["useCacheMaxConsecutiveSteps"]:
acceleratorOptions["cacheMaxConsecutiveSteps"] = params["cacheMaxConsecutiveSteps"]
return acceleratorOptions