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Make loras work with --async-offload (#7824)

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comfyanonymous 2025-04-26 16:56:22 -07:00 committed by GitHub
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commit ac10a0d69e
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1 changed files with 13 additions and 4 deletions
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comfy/ops.py
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@ -22,6 +22,7 @@ import comfy.model_management
from comfy.cli_args import args, PerformanceFeature from comfy.cli_args import args, PerformanceFeature
import comfy.float import comfy.float
import comfy.rmsnorm import comfy.rmsnorm
import contextlib
cast_to = comfy.model_management.cast_to #TODO: remove once no more references cast_to = comfy.model_management.cast_to #TODO: remove once no more references
@ -38,20 +39,28 @@ def cast_bias_weight(s, input=None, dtype=None, device=None, bias_dtype=None):
device = input.device device = input.device
offload_stream = comfy.model_management.get_offload_stream(device) offload_stream = comfy.model_management.get_offload_stream(device)
if offload_stream is not None:
wf_context = offload_stream
else:
wf_context = contextlib.nullcontext()
bias = None bias = None
non_blocking = comfy.model_management.device_supports_non_blocking(device) non_blocking = comfy.model_management.device_supports_non_blocking(device)
if s.bias is not None: if s.bias is not None:
has_function = len(s.bias_function) > 0 has_function = len(s.bias_function) > 0
bias = comfy.model_management.cast_to(s.bias, bias_dtype, device, non_blocking=non_blocking, copy=has_function, stream=offload_stream) bias = comfy.model_management.cast_to(s.bias, bias_dtype, device, non_blocking=non_blocking, copy=has_function, stream=offload_stream)
if has_function: if has_function:
for f in s.bias_function: with wf_context:
bias = f(bias) for f in s.bias_function:
bias = f(bias)
has_function = len(s.weight_function) > 0 has_function = len(s.weight_function) > 0
weight = comfy.model_management.cast_to(s.weight, dtype, device, non_blocking=non_blocking, copy=has_function, stream=offload_stream) weight = comfy.model_management.cast_to(s.weight, dtype, device, non_blocking=non_blocking, copy=has_function, stream=offload_stream)
if has_function: if has_function:
for f in s.weight_function: with wf_context:
weight = f(weight) for f in s.weight_function:
weight = f(weight)
comfy.model_management.sync_stream(device, offload_stream) comfy.model_management.sync_stream(device, offload_stream)
return weight, bias return weight, bias