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assign devices.dtype early because it's needed before the model is loaded

This commit is contained in:
AUTOMATIC 2023-06-01 07:28:13 +03:00
parent 884435796a
commit 915d1da1cd
2 changed files with 4 additions and 2 deletions
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2
modules/sd_models.py
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@ -313,8 +313,6 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
timer.record("apply half()")
devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16
devices.dtype_vae = torch.float32 if shared.cmd_opts.no_half or shared.cmd_opts.no_half_vae else torch.float16
devices.dtype_unet = model.model.diffusion_model.dtype
devices.unet_needs_upcast = shared.cmd_opts.upcast_sampling and devices.dtype == torch.float16 and devices.dtype_unet == torch.float16

4
modules/shared.py
View File

@ -6,6 +6,7 @@ import threading
import time
import gradio as gr
import torch
import tqdm
import modules.interrogate
@ -76,6 +77,9 @@ cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_op
devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \
(devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'esrgan', 'codeformer'])
devices.dtype = torch.float32 if cmd_opts.no_half else torch.float16
devices.dtype_vae = torch.float32 if cmd_opts.no_half or cmd_opts.no_half_vae else torch.float16
device = devices.device
weight_load_location = None if cmd_opts.lowram else "cpu"