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fix the problem with infinite prompts where empty cond would be calculated incorrectly

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AUTOMATIC1111
2024-06-28 11:15:34 +03:00
parent 0b64633584
commit 179ae47d64
3 changed files with 10 additions and 11 deletions
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9
modules/models/sd3/sd3_cond.py
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@@ -177,12 +177,13 @@ class SD3Cond(torch.nn.Module):
self.weights_loaded = False
def forward(self, prompts: list[str]):
lg_out, vector_out = self.model_lg(prompts)
with devices.without_autocast():
lg_out, vector_out = self.model_lg(prompts)
token_count = lg_out.shape[1]
token_count = lg_out.shape[1]
t5_out = self.model_t5(prompts, token_count=token_count)
lgt_out = torch.cat([lg_out, t5_out], dim=-2)
t5_out = self.model_t5(prompts, token_count=token_count)
lgt_out = torch.cat([lg_out, t5_out], dim=-2)
return {
'crossattn': lgt_out,

3
modules/models/sd3/sd3_model.py
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@@ -47,8 +47,7 @@ class SD3Inferencer(torch.nn.Module):
return contextlib.nullcontext()
def get_learned_conditioning(self, batch: list[str]):
with devices.without_autocast():
return self.cond_stage_model(batch)
return self.cond_stage_model(batch)
def apply_model(self, x, t, cond):
return self.model(x, t, c_crossattn=cond['crossattn'], y=cond['vector'])