From 4c24347e45776d505937856ab280548d9298f0a8 Mon Sep 17 00:00:00 2001 From: brkirch Date: Mon, 24 Oct 2022 23:04:50 -0400 Subject: [PATCH] Remove BSRGAN from --use-cpu, add SwinIR --- modules/devices.py | 2 +- modules/shared.py | 6 +++--- modules/swinir_model.py | 12 ++++++------ 3 files changed, 10 insertions(+), 10 deletions(-) diff --git a/modules/devices.py b/modules/devices.py index dc1f3cdd..033a42d5 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -45,7 +45,7 @@ def enable_tf32(): errors.run(enable_tf32, "Enabling TF32") -device = device_interrogate = device_gfpgan = device_bsrgan = device_esrgan = device_scunet = device_codeformer = None +device = device_interrogate = device_gfpgan = device_swinir = device_esrgan = device_scunet = device_codeformer = None dtype = torch.float16 dtype_vae = torch.float16 diff --git a/modules/shared.py b/modules/shared.py index 76cbb1bd..308fccce 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -58,7 +58,7 @@ parser.add_argument("--opt-split-attention", action='store_true', help="force-en parser.add_argument("--opt-split-attention-invokeai", action='store_true', help="force-enables InvokeAI's cross-attention layer optimization. By default, it's on when cuda is unavailable.") 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("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization") -parser.add_argument("--use-cpu", nargs='+',choices=['all', 'sd', 'interrogate', 'gfpgan', 'bsrgan', 'esrgan', 'scunet', 'codeformer'], help="use CPU as torch device for specified modules", default=[], type=str.lower) +parser.add_argument("--use-cpu", nargs='+',choices=['all', 'sd', 'interrogate', 'gfpgan', 'swinir', 'esrgan', 'scunet', 'codeformer'], help="use CPU as torch device for specified modules", default=[], type=str.lower) 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) @@ -96,8 +96,8 @@ restricted_opts = [ "outdir_save", ] -devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_bsrgan, devices.device_esrgan, devices.device_scunet, 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', 'bsrgan', 'esrgan', 'scunet', 'codeformer']) +devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_swinir, devices.device_esrgan, devices.device_scunet, 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', 'swinir', 'esrgan', 'scunet', 'codeformer']) device = devices.device weight_load_location = None if cmd_opts.lowram else "cpu" diff --git a/modules/swinir_model.py b/modules/swinir_model.py index baa02e3d..facd262d 100644 --- a/modules/swinir_model.py +++ b/modules/swinir_model.py @@ -7,8 +7,8 @@ from PIL import Image from basicsr.utils.download_util import load_file_from_url from tqdm import tqdm -from modules import modelloader -from modules.shared import cmd_opts, opts, device +from modules import modelloader, devices +from modules.shared import cmd_opts, opts from modules.swinir_model_arch import SwinIR as net from modules.swinir_model_arch_v2 import Swin2SR as net2 from modules.upscaler import Upscaler, UpscalerData @@ -42,7 +42,7 @@ class UpscalerSwinIR(Upscaler): model = self.load_model(model_file) if model is None: return img - model = model.to(device) + model = model.to(devices.device_swinir) img = upscale(img, model) try: torch.cuda.empty_cache() @@ -111,7 +111,7 @@ def upscale( img = img[:, :, ::-1] img = np.moveaxis(img, 2, 0) / 255 img = torch.from_numpy(img).float() - img = img.unsqueeze(0).to(device) + img = img.unsqueeze(0).to(devices.device_swinir) with torch.no_grad(), precision_scope("cuda"): _, _, h_old, w_old = img.size() h_pad = (h_old // window_size + 1) * window_size - h_old @@ -139,8 +139,8 @@ def inference(img, model, tile, tile_overlap, window_size, scale): stride = tile - tile_overlap h_idx_list = list(range(0, h - tile, stride)) + [h - tile] w_idx_list = list(range(0, w - tile, stride)) + [w - tile] - E = torch.zeros(b, c, h * sf, w * sf, dtype=torch.half, device=device).type_as(img) - W = torch.zeros_like(E, dtype=torch.half, device=device) + E = torch.zeros(b, c, h * sf, w * sf, dtype=torch.half, device=devices.device_swinir).type_as(img) + W = torch.zeros_like(E, dtype=torch.half, device=devices.device_swinir) with tqdm(total=len(h_idx_list) * len(w_idx_list), desc="SwinIR tiles") as pbar: for h_idx in h_idx_list: