fix: chroma LoRA training without Text Encode caching

This commit is contained in:
Kohya S
2025-08-30 09:30:24 +09:00
parent 8cadec68bb
commit e836b7f66d

View File

@@ -220,8 +220,12 @@ class DummyTextModel(torch.nn.Module):
class DummyCLIPL(torch.nn.Module):
def __init__(self):
super().__init__()
self.output_shape = (77, 1) # Note: The original code had (77, 768), but we use (77, 1) for the dummy output
self.dummy_param = torch.nn.Parameter(torch.zeros(1)) # get dtype and device from this parameter
self.output_shape = (77, 1) # Note: The original code had (77, 768), but we use (77, 1) for the dummy output
# dtype and device from these parameters. train_network.py accesses them
self.dummy_param = torch.nn.Parameter(torch.zeros(1))
self.dummy_param_2 = torch.nn.Parameter(torch.zeros(1))
self.dummy_param_3 = torch.nn.Parameter(torch.zeros(1))
self.text_model = DummyTextModel()
@property