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authorAUTOMATIC1111 <16777216c@gmail.com>2023-09-09 07:31:56 +0000
committerGitHub <noreply@github.com>2023-09-09 07:31:56 +0000
commit924642331b13b73adbada3270a52cc5c7ae85ace (patch)
treedd15c7eccf1ef65d9da772c14c16f943766ac69d /modules/prompt_parser.py
parentc9c457eda8dec414dc38e874691d1e2736d6dcbb (diff)
parentb6c1a1bbbf29a3041025aa336f6f843ffd7c7d46 (diff)
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Merge pull request #12846 from a666/deprecated-types
Fix some deprecated types
Diffstat (limited to 'modules/prompt_parser.py')
-rw-r--r--modules/prompt_parser.py7
1 files changed, 3 insertions, 4 deletions
diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 334efeef..ddf4d2dd 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -2,7 +2,6 @@ from __future__ import annotations
import re
from collections import namedtuple
-from typing import List
import lark
# a prompt like this: "fantasy landscape with a [mountain:lake:0.25] and [an oak:a christmas tree:0.75][ in foreground::0.6][ in background:0.25] [shoddy:masterful:0.5]"
@@ -240,14 +239,14 @@ def get_multicond_prompt_list(prompts: SdConditioning | list[str]):
class ComposableScheduledPromptConditioning:
def __init__(self, schedules, weight=1.0):
- self.schedules: List[ScheduledPromptConditioning] = schedules
+ self.schedules: list[ScheduledPromptConditioning] = schedules
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: list[list[ComposableScheduledPromptConditioning]] = batch
def get_multicond_learned_conditioning(model, prompts, steps, hires_steps=None, use_old_scheduling=False) -> MulticondLearnedConditioning:
@@ -278,7 +277,7 @@ class DictWithShape(dict):
return self["crossattn"].shape
-def reconstruct_cond_batch(c: List[List[ScheduledPromptConditioning]], current_step):
+def reconstruct_cond_batch(c: list[list[ScheduledPromptConditioning]], current_step):
param = c[0][0].cond
is_dict = isinstance(param, dict)