Merge pull request #1616 from brkirch/cpu-cmdline-opt

Add --use-cpu command line option

6 files changed, 22 insertions, 19 deletions

diff --git a/modules/bsrgan_model.py b/modules/bsrgan_model.py
index e62c6657..3bd80791 100644
--- a/modules/bsrgan_model.py
+++ b/modules/bsrgan_model.py
@@ -8,7 +8,7 @@ import torch
 from basicsr.utils.download_util import load_file_from_url
 
 import modules.upscaler
-from modules import shared, modelloader
+from modules import devices, modelloader
 from modules.bsrgan_model_arch import RRDBNet
 from modules.paths import models_path
 
@@ -44,13 +44,13 @@ class UpscalerBSRGAN(modules.upscaler.Upscaler):
         model = self.load_model(selected_file)
         if model is None:
             return img
-        model.to(shared.device)
+        model.to(devices.device_bsrgan)
         torch.cuda.empty_cache()
         img = np.array(img)
         img = img[:, :, ::-1]
         img = np.moveaxis(img, 2, 0) / 255
         img = torch.from_numpy(img).float()
-        img = img.unsqueeze(0).to(shared.device)
+        img = img.unsqueeze(0).to(devices.device_bsrgan)
         with torch.no_grad():
             output = model(img)
         output = output.squeeze().float().cpu().clamp_(0, 1).numpy()
diff --git a/modules/devices.py b/modules/devices.py
index 12aab665..0158b11f 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -2,9 +2,9 @@ import contextlib
 
 import torch
 
-# has_mps is only available in nightly pytorch (for now), `getattr` for compatibility
 from modules import errors
 
+# has_mps is only available in nightly pytorch (for now), `getattr` for compatibility
 has_mps = getattr(torch, 'has_mps', False)
 
 cpu = torch.device("cpu")
@@ -34,8 +34,7 @@ def enable_tf32():
 
 errors.run(enable_tf32, "Enabling TF32")
 
-device = get_optimal_device()
-device_codeformer = cpu if has_mps else device
+device = device_gfpgan = device_bsrgan = device_esrgan = device_scunet = device_codeformer = get_optimal_device()
 dtype = torch.float16
 
 def randn(seed, shape):
diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index 4aed9283..d17e730f 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -6,8 +6,7 @@ from PIL import Image
 from basicsr.utils.download_util import load_file_from_url

 

 import modules.esrgam_model_arch as arch

-from modules import shared, modelloader, images

-from modules.devices import has_mps

+from modules import shared, modelloader, images, devices

 from modules.paths import models_path

 from modules.upscaler import Upscaler, UpscalerData

 from modules.shared import opts

@@ -97,7 +96,7 @@ class UpscalerESRGAN(Upscaler):
         model = self.load_model(selected_model)

         if model is None:

             return img

-        model.to(shared.device)

+        model.to(devices.device_esrgan)

         img = esrgan_upscale(model, img)

         return img

 

@@ -112,7 +111,7 @@ class UpscalerESRGAN(Upscaler):
             print("Unable to load %s from %s" % (self.model_path, filename))

             return None

 

-        pretrained_net = torch.load(filename, map_location='cpu' if has_mps else None)

+        pretrained_net = torch.load(filename, map_location='cpu' if shared.device.type == 'mps' else None)

         crt_model = arch.RRDBNet(3, 3, 64, 23, gc=32)

 

         pretrained_net = fix_model_layers(crt_model, pretrained_net)

@@ -127,7 +126,7 @@ def upscale_without_tiling(model, img):
     img = img[:, :, ::-1]

     img = np.moveaxis(img, 2, 0) / 255

     img = torch.from_numpy(img).float()

-    img = img.unsqueeze(0).to(shared.device)

+    img = img.unsqueeze(0).to(devices.device_esrgan)

     with torch.no_grad():

         output = model(img)

     output = output.squeeze().float().cpu().clamp_(0, 1).numpy()

diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py
index 5586b554..a9452dce 100644
--- a/modules/gfpgan_model.py
+++ b/modules/gfpgan_model.py
@@ -21,7 +21,7 @@ def gfpgann():
     global loaded_gfpgan_model

     global model_path

     if loaded_gfpgan_model is not None:

-        loaded_gfpgan_model.gfpgan.to(shared.device)

+        loaded_gfpgan_model.gfpgan.to(devices.device_gfpgan)

         return loaded_gfpgan_model

 

     if gfpgan_constructor is None:

@@ -53,7 +53,7 @@ def gfpgan_fix_faces(np_image):
     if model is None:

         return np_image

 

-    send_model_to(model, devices.device)

+    send_model_to(model, devices.device_gfpgan)

 

     np_image_bgr = np_image[:, :, ::-1]

     cropped_faces, restored_faces, gfpgan_output_bgr = model.enhance(np_image_bgr, has_aligned=False, only_center_face=False, paste_back=True)

diff --git a/modules/scunet_model.py b/modules/scunet_model.py
index 7987ac14..fb64b740 100644
--- a/modules/scunet_model.py
+++ b/modules/scunet_model.py
@@ -8,7 +8,7 @@ import torch
 from basicsr.utils.download_util import load_file_from_url
 
 import modules.upscaler
-from modules import shared, modelloader
+from modules import devices, modelloader
 from modules.paths import models_path
 from modules.scunet_model_arch import SCUNet as net
 
@@ -51,12 +51,12 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
         if model is None:
             return img
 
-        device = shared.device
+        device = devices.device_scunet
         img = np.array(img)
         img = img[:, :, ::-1]
         img = np.moveaxis(img, 2, 0) / 255
         img = torch.from_numpy(img).float()
-        img = img.unsqueeze(0).to(shared.device)
+        img = img.unsqueeze(0).to(device)
 
         img = img.to(device)
         with torch.no_grad():
@@ -69,7 +69,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
         return PIL.Image.fromarray(output, 'RGB')
 
     def load_model(self, path: str):
-        device = shared.device
+        device = devices.device_scunet
         if "http" in path:
             filename = load_file_from_url(url=self.model_url, model_dir=self.model_path, file_name="%s.pth" % self.name,
                                           progress=True)
diff --git a/modules/shared.py b/modules/shared.py
index 2a599e9c..25aff5b0 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -12,7 +12,7 @@ import modules.interrogate
 import modules.memmon

 import modules.sd_models

 import modules.styles

-from modules.devices import get_optimal_device

+import modules.devices as devices

 from modules.paths import script_path, sd_path

 

 sd_model_file = os.path.join(script_path, 'model.ckpt')

@@ -46,6 +46,7 @@ parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with
 parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")

 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")

 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")

+parser.add_argument("--use-cpu", nargs='+',choices=['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'], help="use CPU as torch device for specified modules", default=[])

 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")

 parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)

 parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False)

@@ -63,7 +64,11 @@ parser.add_argument("--enable-console-prompts", action='store_true', help="print
 

 

 cmd_opts = parser.parse_args()

-device = get_optimal_device()

+

+devices.device, devices.device_gfpgan, devices.device_bsrgan, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \

+(devices.cpu if x in cmd_opts.use_cpu else devices.get_optimal_device() for x in ['SD', 'GFPGAN', 'BSRGAN', 'ESRGAN', 'SCUNet', 'CodeFormer'])

+

+device = devices.device

 

 batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram)

 parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram