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Pass per-device model to multigpu control clones in pre_run_control

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QwenFunControlNet.pre_run stashes model.diffusion_model into extra_args,
which the control_model then uses for forward passes (img_in, txt_in,
pe_embedder, time_text_embed). With multigpu, every per-device control
clone was being pre_run with the base model on GPU0, so secondary
devices would invoke those modules with parameters on GPU0 and inputs
on their own device, raising 'Expected all tensors to be on the same
device'. Build a device -> per-device BaseModel lookup from the
patcher's additional multigpu models and pass each clone the model on
its own device. Falls back to the base model when no per-device match
is found (single-GPU path and the case where cnet.multigpu_clones lags
the patcher's clone set).

Amp-Thread-ID: https://ampcode.com/threads/T-019e4a00-fe3d-76bd-a2f2-a8c8c4040082
Co-authored-by: Amp <amp@ampcode.com>
This commit is contained in:
Kosinkadink 2026-05-21 11:40:49 -07:00
parent 963621603c
commit a18dd219d5
1 changed files with 9 additions and 2 deletions
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11
comfy/samplers.py
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@ -870,14 +870,21 @@ def calculate_start_end_timesteps(model, conds):
def pre_run_control(model, conds): def pre_run_control(model, conds):
s = model.model_sampling s = model.model_sampling
# Per-device model lookup so multigpu control clones get the matching
# diffusion_model (e.g. QwenFunControlNet stashes it into extra_args).
device_models: dict = {}
patcher = getattr(model, "current_patcher", None)
if patcher is not None:
for p in patcher.get_additional_models_with_key("multigpu"):
device_models[p.load_device] = p.model
for t in range(len(conds)): for t in range(len(conds)):
x = conds[t] x = conds[t]
percent_to_timestep_function = lambda a: s.percent_to_sigma(a) percent_to_timestep_function = lambda a: s.percent_to_sigma(a)
if 'control' in x: if 'control' in x:
x['control'].pre_run(model, percent_to_timestep_function) x['control'].pre_run(model, percent_to_timestep_function)
for device_cnet in x['control'].multigpu_clones.values(): for device, device_cnet in x['control'].multigpu_clones.items():
device_cnet.pre_run(model, percent_to_timestep_function) device_cnet.pre_run(device_models.get(device, model), percent_to_timestep_function)
def apply_empty_x_to_equal_area(conds, uncond, name, uncond_fill_func): def apply_empty_x_to_equal_area(conds, uncond, name, uncond_fill_func):
cond_cnets = [] cond_cnets = []