Removing parts no longer needed to fix vram

modules/devices.py

 import contextlib
 
 import torch
-import gc
 
 from modules import errors
 
@@ -20,8 +19,8 @@ def get_optimal_device():
 
     return cpu
 
+
 def torch_gc():
-    gc.collect()
     if torch.cuda.is_available():
         torch.cuda.empty_cache()
         torch.cuda.ipc_collect()

modules/processing.py

@@ -346,7 +346,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             state.job_count = p.n_iter
 
         for n in range(p.n_iter):
-        with torch.no_grad(), precision_scope("cuda"), ema_scope():
             if state.interrupted:
                 break
 
@@ -396,21 +395,18 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
                 x_samples_ddim = modules.safety.censor_batch(x_samples_ddim)
 
             for i, x_sample in enumerate(x_samples_ddim):
-            with torch.no_grad(), precision_scope("cuda"), ema_scope():
                 x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
                 x_sample = x_sample.astype(np.uint8)
 
                 if p.restore_faces:
-                with torch.no_grad(), precision_scope("cuda"), ema_scope():
                     if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:
                         images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
 
-                    x_sample = modules.face_restoration.restore_faces(x_sample)
                     devices.torch_gc()
 
+                    x_sample = modules.face_restoration.restore_faces(x_sample)
                     devices.torch_gc()
 
-            with torch.no_grad(), precision_scope("cuda"), ema_scope():
                 image = Image.fromarray(x_sample)
 
                 if p.color_corrections is not None and i < len(p.color_corrections):
@@ -444,7 +440,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
             state.nextjob()
 
-    with torch.no_grad(), precision_scope("cuda"), ema_scope():
         p.color_corrections = None
 
         index_of_first_image = 0