Public/automatic
1
0
Fork 0
mirror of https://github.com/vladmandic/automatic synced 2026-09-18 16:54:33 +02:00
Code Issues Packages Projects Releases Wiki Activity

Move embedder object, cleanup stepwise lora

Browse Source
This commit is contained in:
AI-Casanova
2024-10-30 23:24:50 -05:00
parent 38303f0c61
commit 3932d5fd1b
4 changed files with 27 additions and 26 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/processing_callbacks.py
+5 -6
View File
@@ -3,8 +3,7 @@ import os
import time
import torch
import numpy as np
from modules import shared, processing_correction, extra_networks, timer
from modules import shared, processing_correction, extra_networks, timer, prompt_parser_diffusers
p = None
debug_callback = shared.log.trace if os.environ.get('SD_CALLBACK_DEBUG', None) is not None else lambda *args, **kwargs: None
@@ -49,7 +48,7 @@ def diffusers_callback(pipe, step: int, timestep: int, kwargs: dict):
if shared.state.interrupted or shared.state.skipped:
raise AssertionError('Interrupted...')
time.sleep(0.1)
if hasattr(p, "extra_network_data"):
if hasattr(p, "stepwise_lora"):
extra_networks.activate(p, p.extra_network_data, step=step)
if latents is None:
return kwargs
@@ -67,12 +66,12 @@ def diffusers_callback(pipe, step: int, timestep: int, kwargs: dict):
pipe.set_ip_adapter_scale(ip_adapter_scales)
if step != getattr(pipe, 'num_timesteps', 0):
kwargs = processing_correction.correction_callback(p, timestep, kwargs)
if p.embedder is not None:
if prompt_parser_diffusers.embedder is not None:
try:
if 'prompt_embeds' in kwargs:
kwargs["prompt_embeds"] = p.embedder("prompt_embeds", step + 1)
kwargs["prompt_embeds"] = prompt_parser_diffusers.embedder("prompt_embeds", step + 1)
if 'negative_prompt_embeds' in kwargs:
kwargs["negative_prompt_embeds"] = p.embedder("negative_prompt_embeds", step + 1)
kwargs["negative_prompt_embeds"] = prompt_parser_diffusers.embedder("negative_prompt_embeds", step + 1)
except Exception as e:
shared.log.debug(f"Callback: {e}")
if step == int(getattr(pipe, 'num_timesteps', 100) * p.cfg_end) and 'prompt_embeds' in kwargs and 'negative_prompt_embeds' in kwargs: