Datasets:
jblitzar
/
github-python-corpus

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"partial_prompt": (PartialPrompt.ID,),
"fixed_partial_prompt": (PartialPrompt.ID,),
"total_frames": ("INT", {"default": 100, "min": 1, "max": 0xffffffffffffffff}),
"prompt_interval": ("INT", {"default": 10, "min": 1, "max": 0xffffffffffffffff}),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
"num_positive": ("INT", {"default": 3, "min": 1, "max": 100}),
"num_negative": ("INT", {"default": 0, "min": 0, "max": 100}),
"adjustment": (["raw", "by_abs_max", "by_abs_sum"],),
"clamp": ("FLOAT", {"default": 2.0, "min": 0.1, "step": 0.1}),
"adjustment_reference": ("FLOAT", {"default": 1.0, "min": 0.1}),
},
}
CATEGORY = NodeCategories.CONDITIONING
RETURN_TYPES = ("STRING", "STRING", "STRING")
RETURN_NAMES = ("prompt_schedule", "positive_prompt_schedule", "negative_prompt_schedule")
FUNCTION = "result"
def result(self, partial_prompt: PartialPrompt, fixed_partial_prompt, total_frames, prompt_interval, seed,
num_positive, num_negative, adjustment, adjustment_reference, clamp):
text = list()
text_pos = list()
text_neg = list()
prompt_interval = max(1, prompt_interval)
i = 0
while i < total_frames:
step_prompt = partial_prompt.random_subset(num_positive, num_negative, seed + i)
step_prompt = step_prompt.merge(fixed_partial_prompt)
f = 1.0
if adjustment == "by_abs_sum":
f = adjustment_reference / step_prompt.abs_sum()
elif adjustment == "by_abs_max":
f = adjustment_reference / step_prompt.abs_max()
step_prompt = step_prompt.scaled_by(f)
pos, neg = step_prompt.finalize(clamp)
signed_prompt = step_prompt.finalize_signed(clamp)
text.append('"{}": "{}"'.format(i, signed_prompt))
text_pos.append('"{}": "{}"'.format(i, pos))
text_neg.append('"{}": "{}"'.format(i, neg))
i += prompt_interval
return (",\n".join(text) + "\n", ",\n".join(text_pos) + "\n", ",\n".join(text_neg) + "\n")
class DreamWeightedPromptBuilder:
NODE_NAME = "Build Prompt"
ICON = "⚖"
@classmethod
def INPUT_TYPES(cls):
return {
"optional": {
"partial_prompt": (PartialPrompt.ID,)
},
"required": {
"added_prompt": ("STRING", {"default": "", "multiline": True}),
"weight": ("FLOAT", {"default": 1.0}),
},
}
CATEGORY = NodeCategories.CONDITIONING
RETURN_TYPES = (PartialPrompt.ID,)
RETURN_NAMES = ("partial_prompt",)
FUNCTION = "result"
def result(self, added_prompt, weight, **args):
input = args.get("partial_prompt", PartialPrompt())
p = input.add(added_prompt, weight)
return (p,)
class DreamPromptFinalizer:
NODE_NAME = "Finalize Prompt"
ICON = "🗫"
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"partial_prompt": (PartialPrompt.ID,),
"adjustment": (["raw", "by_abs_max", "by_abs_sum"],),
"clamp": ("FLOAT", {"default": 2.0, "min": 0.1, "step": 0.1}),
"adjustment_reference": ("FLOAT", {"default": 1.0, "min": 0.1}),
},
}
CATEGORY = NodeCategories.CONDITIONING
RETURN_TYPES = ("STRING", "STRING")
RETURN_NAMES = ("positive", "negative")
FUNCTION = "result"
def result(self, partial_prompt: PartialPrompt, adjustment, adjustment_reference, clamp):
if adjustment == "raw" or partial_prompt.is_empty():
return partial_prompt.finalize(clamp)
elif adjustment == "by_abs_sum":
f = adjustment_reference / partial_prompt.abs_sum()