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[Auto] Freeze shared ZImage ControlNet transformer modules (cluster-13077-4): merged 1 of 3 PRs #8

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17 changes: 17 additions & 0 deletions src/diffusers/models/controlnets/controlnet_z_image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -517,7 +517,12 @@ def __init__(

@classmethod
def from_transformer(cls, controlnet, transformer):
# Scalar value — immutable, direct assignment is safe
controlnet.t_scale = transformer.t_scale

# Shared modules from transformer — these are intentionally shared references.
# They should remain frozen during controlnet training; only control_* modules
# are meant to be trained.
controlnet.t_embedder = transformer.t_embedder
controlnet.all_x_embedder = transformer.all_x_embedder
controlnet.cap_embedder = transformer.cap_embedder
Expand All @@ -526,6 +531,18 @@ def from_transformer(cls, controlnet, transformer):
controlnet.context_refiner = transformer.context_refiner
controlnet.x_pad_token = transformer.x_pad_token
controlnet.cap_pad_token = transformer.cap_pad_token

# Freeze all shared modules/parameters to prevent accidental training.
# Only control_* modules (control_layers, control_all_x_embedder,
# control_noise_refiner) should be trained.
controlnet.t_embedder.requires_grad_(False)
controlnet.all_x_embedder.requires_grad_(False)
controlnet.cap_embedder.requires_grad_(False)
controlnet.noise_refiner.requires_grad_(False)
controlnet.context_refiner.requires_grad_(False)
controlnet.x_pad_token.requires_grad_(False)
controlnet.cap_pad_token.requires_grad_(False)

return controlnet

@staticmethod
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