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Memory estimation code can now take into account conds. (#8307)

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comfyanonymous
2025-05-27 12:09:05 -07:00
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parent c9e1821a7b
commit 06c661004e
4 changed files with 47 additions and 7 deletions
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8
comfy/samplers.py
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@@ -256,7 +256,13 @@ def _calc_cond_batch(model: 'BaseModel', conds: list[list[dict]], x_in: torch.Te
for i in range(1, len(to_batch_temp) + 1):
batch_amount = to_batch_temp[:len(to_batch_temp)//i]
input_shape = [len(batch_amount) * first_shape[0]] + list(first_shape)[1:]
if model.memory_required(input_shape) * 1.5 < free_memory:
cond_shapes = collections.defaultdict(list)
for tt in batch_amount:
cond = {k: v.size() for k, v in to_run[tt][0].conditioning.items()}
for k, v in to_run[tt][0].conditioning.items():
cond_shapes[k].append(v.size())
if model.memory_required(input_shape, cond_shapes=cond_shapes) * 1.5 < free_memory:
to_batch = batch_amount
break