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https://github.com/vladmandic/automatic
synced 2026-09-19 17:24:32 +02:00
update installer usage
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@@ -2,7 +2,7 @@ import os
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import time
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import numpy as np
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import torch
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from modules import shared, devices, sd_models, sd_vae, errors
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from modules import shared, devices, errors, sd_models, sd_models_utils, sd_vae
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from modules.logger import log
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from modules.vae import sd_vae_taesd
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@@ -71,7 +71,7 @@ def full_vqgan_decode(latents, model):
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if 'VAE' in shared.opts.cuda_compile and shared.opts.cuda_compile_backend == "openvino_fx" and shared.compiled_model_state.first_pass_vae:
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shared.compiled_model_state.first_pass_vae = False
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if not shared.opts.openvino_disable_memory_cleanup and hasattr(shared.sd_model, "vqgan"):
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model.vqgan.apply(sd_models.convert_to_faketensors)
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model.vqgan.apply(sd_models_utils.convert_to_faketensors)
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devices.torch_gc(force=True)
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if shared.opts.diffusers_offload_mode == "balanced":
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@@ -166,7 +166,7 @@ def full_vae_decode(latents, model):
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if 'VAE' in shared.opts.cuda_compile and shared.opts.cuda_compile_backend == "openvino_fx" and shared.compiled_model_state.first_pass_vae:
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shared.compiled_model_state.first_pass_vae = False
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if not shared.opts.openvino_disable_memory_cleanup and hasattr(shared.sd_model, "vae"):
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model.vae.apply(sd_models.convert_to_faketensors)
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model.vae.apply(sd_models_utils.convert_to_faketensors)
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devices.torch_gc(force=True)
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elif shared.opts.diffusers_move_unet and not getattr(model, 'has_accelerate', False) and base_device is not None:
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