in point_e/diffusion/sampler.py [0:0]
def combine(cls, *samplers: "PointCloudSampler") -> "PointCloudSampler":
assert all(x.device == samplers[0].device for x in samplers[1:])
assert all(x.aux_channels == samplers[0].aux_channels for x in samplers[1:])
assert all(x.clip_denoised == samplers[0].clip_denoised for x in samplers[1:])
return cls(
device=samplers[0].device,
models=[x for y in samplers for x in y.models],
diffusions=[x for y in samplers for x in y.diffusions],
num_points=[x for y in samplers for x in y.num_points],
aux_channels=samplers[0].aux_channels,
model_kwargs_key_filter=[x for y in samplers for x in y.model_kwargs_key_filter],
guidance_scale=[x for y in samplers for x in y.guidance_scale],
clip_denoised=samplers[0].clip_denoised,
use_karras=[x for y in samplers for x in y.use_karras],
karras_steps=[x for y in samplers for x in y.karras_steps],
sigma_min=[x for y in samplers for x in y.sigma_min],
sigma_max=[x for y in samplers for x in y.sigma_max],
s_churn=[x for y in samplers for x in y.s_churn],
)