[training] fix: registration of out_channels in the control flux scripts. (#10367)

* fix: registration of out_channels in the control flux scripts.

* free memory.

examples/flux-control/train_control_flux.py

@@ -795,7 +795,7 @@ def main(args):
         flux_transformer.x_embedder = new_linear
 
     assert torch.all(flux_transformer.x_embedder.weight[:, initial_input_channels:].data == 0)
-    flux_transformer.register_to_config(in_channels=initial_input_channels * 2)
+    flux_transformer.register_to_config(in_channels=initial_input_channels * 2, out_channels=initial_input_channels)
 
     def unwrap_model(model):
         model = accelerator.unwrap_model(model)
@@ -1166,6 +1166,11 @@ def main(args):
             flux_transformer.to(torch.float32)
         flux_transformer.save_pretrained(args.output_dir)
 
+        del flux_transformer
+        del text_encoding_pipeline
+        del vae
+        free_memory()
+
         # Run a final round of validation.
         image_logs = None
         if args.validation_prompt is not None:

examples/flux-control/train_control_lora_flux.py

@@ -830,7 +830,7 @@ def main(args):
         flux_transformer.x_embedder = new_linear
 
     assert torch.all(flux_transformer.x_embedder.weight[:, initial_input_channels:].data == 0)
-    flux_transformer.register_to_config(in_channels=initial_input_channels * 2)
+    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():
@@ -1319,6 +1319,11 @@ def main(args):
             transformer_lora_layers=transformer_lora_layers,
         )
 
+        del flux_transformer
+        del text_encoding_pipeline
+        del vae
+        free_memory()
+
         # Run a final round of validation.
         image_logs = None
         if args.validation_prompt is not None: