Merge branch 'master' into focal-point-cropping

1 files changed, 4 insertions, 5 deletions

diff --git a/modules/lowvram.py b/modules/lowvram.py
index 7eba1349..f327c3df 100644
--- a/modules/lowvram.py
+++ b/modules/lowvram.py
@@ -1,9 +1,8 @@
 import torch

-from modules.devices import get_optimal_device

+from modules import devices

 

 module_in_gpu = None

 cpu = torch.device("cpu")

-device = gpu = get_optimal_device()

 

 

 def send_everything_to_cpu():

@@ -33,7 +32,7 @@ def setup_for_low_vram(sd_model, use_medvram):
         if module_in_gpu is not None:

             module_in_gpu.to(cpu)

 

-        module.to(gpu)

+        module.to(devices.device)

         module_in_gpu = module

 

     # see below for register_forward_pre_hook;

@@ -51,7 +50,7 @@ def setup_for_low_vram(sd_model, use_medvram):
     # send the model to GPU. Then put modules back. the modules will be in CPU.

     stored = sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.model

     sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.model = None, None, None

-    sd_model.to(device)

+    sd_model.to(devices.device)

     sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.model = stored

 

     # register hooks for those the first two models

@@ -70,7 +69,7 @@ def setup_for_low_vram(sd_model, use_medvram):
         # so that only one of them is in GPU at a time

         stored = diff_model.input_blocks, diff_model.middle_block, diff_model.output_blocks, diff_model.time_embed

         diff_model.input_blocks, diff_model.middle_block, diff_model.output_blocks, diff_model.time_embed = None, None, None, None

-        sd_model.model.to(device)

+        sd_model.model.to(devices.device)

         diff_model.input_blocks, diff_model.middle_block, diff_model.output_blocks, diff_model.time_embed = stored

 

         # install hooks for bits of third model