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fix norm not training in train_control_lora_flux.py #11832

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merged 1 commit into from
Jul 2, 2025
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fix norm not training in train_control_lora_flux.py #11832

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10 changes: 5 additions & 5 deletions examples/flux-control/train_control_lora_flux.py
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Original file line number Diff line number Diff line change
Expand Up @@ -837,11 +837,6 @@ def main(args):
assert torch.all(flux_transformer.x_embedder.weight[:, initial_input_channels:].data == 0)
flux_transformer.register_to_config(in_channels=initial_input_channels * 2, out_channels=initial_input_channels)

if args.train_norm_layers:
for name, param in flux_transformer.named_parameters():
if any(k in name for k in NORM_LAYER_PREFIXES):
param.requires_grad = True

if args.lora_layers is not None:
if args.lora_layers != "all-linear":
target_modules = [layer.strip() for layer in args.lora_layers.split(",")]
Expand Down Expand Up @@ -879,6 +874,11 @@ def main(args):
)
flux_transformer.add_adapter(transformer_lora_config)

if args.train_norm_layers:
for name, param in flux_transformer.named_parameters():
if any(k in name for k in NORM_LAYER_PREFIXES):
param.requires_grad = True

def unwrap_model(model):
model = accelerator.unwrap_model(model)
model = model._orig_mod if is_compiled_module(model) else model
Expand Down