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

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Add --use-cpu command line option
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AUTOMATIC1111 2022-10-04 15:20:10 +03:00 committed by GitHub
commit bc4d457de8
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6 changed files with 22 additions and 19 deletions
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6
modules/bsrgan_model.py
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@ -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()

5
modules/devices.py
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@ -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):

9
modules/esrgan_model.py
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@ -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()

4
modules/gfpgan_model.py
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@ -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)

8
modules/scunet_model.py
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@ -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)

9
modules/shared.py
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@ -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