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from .fbcache_nodes import ApplyFBCacheOnModel
from .misc_nodes import (
EnhancedLoadDiffusionModel,
EnhancedCompileModel,
)
from .velocator_nodes import (
VelocatorCompileModel,
VelocatorLoadAndQuantizeClip,
VelocatorLoadAndQuantizeDiffusionModel,
VelocatorQuantizeModel,
)
# def patch_cast_to():
# def cast_to(weight, dtype=None, device=None, non_blocking=False, copy=False):
# if device is None or weight.device == device:
# if not copy:
# if dtype is None or weight.dtype == dtype:
# return weight
# return weight.to(dtype=dtype, copy=copy)
#
# # torch.empty_like does not work with tensor subclasses well
# # r = torch.empty_like(weight, dtype=dtype, device=device)
# # r.copy_(weight, non_blocking=non_blocking)
# r = weight.to(device=device, dtype=dtype, non_blocking=non_blocking, copy=copy)
# return r
#
# from comfy import model_management
#
# model_management.cast_to = cast_to
#
#
# patch_cast_to()
NODE_CLASS_MAPPINGS = {
"ApplyFBCacheOnModel": ApplyFBCacheOnModel,
"EnhancedLoadDiffusionModel": EnhancedLoadDiffusionModel,
"EnhancedCompileModel": EnhancedCompileModel,
"VelocatorLoadAndQuantizeDiffusionModel": VelocatorLoadAndQuantizeDiffusionModel,
"VelocatorLoadAndQuantizeClip": VelocatorLoadAndQuantizeClip,
"VelocatorQuantizeModel": VelocatorQuantizeModel,
"VelocatorCompileModel": VelocatorCompileModel,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"ApplyFBCacheOnModel": "Apply First Block Cache",
"EnhancedLoadDiffusionModel": "Load Diffusion Model+",
"EnhancedCompileModel": "Compile Model+",
"VelocatorLoadAndQuantizeDiffusionModel": "🚀Load & Quantize Diffusion Model",
"VelocatorLoadAndQuantizeClip": "🚀Load & Quantize CLIP",
"VelocatorQuantizeModel": "🚀Quantize Model",
"VelocatorCompileModel": "🚀Compile Model",
}