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Merge upstream/master, keep local README.md

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GitHub Actions 2025-12-30 00:38:04 +00:00
commit 3708bc9baf
2 changed files with 18 additions and 1 deletions
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3
comfy/ldm/lumina/model.py
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@ -491,7 +491,8 @@ class NextDiT(nn.Module):
for layer_id in range(n_layers) for layer_id in range(n_layers)
] ]
) )
self.norm_final = operation_settings.get("operations").RMSNorm(dim, eps=norm_eps, elementwise_affine=True, device=operation_settings.get("device"), dtype=operation_settings.get("dtype")) # This norm final is in the lumina 2.0 code but isn't actually used for anything.
# self.norm_final = operation_settings.get("operations").RMSNorm(dim, eps=norm_eps, elementwise_affine=True, device=operation_settings.get("device"), dtype=operation_settings.get("dtype"))
self.final_layer = FinalLayer(dim, patch_size, self.out_channels, z_image_modulation=z_image_modulation, operation_settings=operation_settings) self.final_layer = FinalLayer(dim, patch_size, self.out_channels, z_image_modulation=z_image_modulation, operation_settings=operation_settings)
if self.pad_tokens_multiple is not None: if self.pad_tokens_multiple is not None:

16
comfy/model_management.py
View File

@ -1126,6 +1126,16 @@ if not args.disable_pinned_memory:
PINNING_ALLOWED_TYPES = set(["Parameter", "QuantizedTensor"]) PINNING_ALLOWED_TYPES = set(["Parameter", "QuantizedTensor"])
def discard_cuda_async_error():
try:
a = torch.tensor([1], dtype=torch.uint8, device=get_torch_device())
b = torch.tensor([1], dtype=torch.uint8, device=get_torch_device())
_ = a + b
torch.cuda.synchronize()
except torch.AcceleratorError:
#Dump it! We already know about it from the synchronous return
pass
def pin_memory(tensor): def pin_memory(tensor):
global TOTAL_PINNED_MEMORY global TOTAL_PINNED_MEMORY
if MAX_PINNED_MEMORY <= 0: if MAX_PINNED_MEMORY <= 0:
@ -1158,6 +1168,9 @@ def pin_memory(tensor):
PINNED_MEMORY[ptr] = size PINNED_MEMORY[ptr] = size
TOTAL_PINNED_MEMORY += size TOTAL_PINNED_MEMORY += size
return True return True
else:
logging.warning("Pin error.")
discard_cuda_async_error()
return False return False
@ -1186,6 +1199,9 @@ def unpin_memory(tensor):
if len(PINNED_MEMORY) == 0: if len(PINNED_MEMORY) == 0:
TOTAL_PINNED_MEMORY = 0 TOTAL_PINNED_MEMORY = 0
return True return True
else:
logging.warning("Unpin error.")
discard_cuda_async_error()
return False return False