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remove type annotations in new code because presumably they don't work in 3.7

AUTOMATIC 2 年之前
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20f8ec877a
共有 1 個文件被更改,包括 3 次插入3 次删除
  1. 3 3
      modules/prompt_parser.py

+ 3 - 3
modules/prompt_parser.py

@@ -175,14 +175,14 @@ def get_multicond_prompt_list(prompts):
 
 class ComposableScheduledPromptConditioning:
     def __init__(self, schedules, weight=1.0):
-        self.schedules: list[ScheduledPromptConditioning] = schedules
+        self.schedules = schedules  # : list[ScheduledPromptConditioning]
         self.weight: float = weight
 
 
 class MulticondLearnedConditioning:
     def __init__(self, shape, batch):
         self.shape: tuple = shape  # the shape field is needed to send this object to DDIM/PLMS
-        self.batch: list[list[ComposableScheduledPromptConditioning]] = batch
+        self.batch = batch  # : list[list[ComposableScheduledPromptConditioning]]
 
 
 def get_multicond_learned_conditioning(model, prompts, steps) -> MulticondLearnedConditioning:
@@ -203,7 +203,7 @@ def get_multicond_learned_conditioning(model, prompts, steps) -> MulticondLearne
     return MulticondLearnedConditioning(shape=(len(prompts),), batch=res)
 
 
-def reconstruct_cond_batch(c: list[list[ScheduledPromptConditioning]], current_step):
+def reconstruct_cond_batch(c, current_step):  # c: list[list[ScheduledPromptConditioning]]
     param = c[0][0].cond
     res = torch.zeros((len(c),) + param.shape, device=param.device, dtype=param.dtype)
     for i, cond_schedule in enumerate(c):