diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index c2c2a43c..ae0d0e6a 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/extensions-builtin/SwinIR/scripts/swinir_model.py @@ -1,4 +1,5 @@ import sys +import platform import numpy as np import torch @@ -18,6 +19,8 @@ device_swinir = devices.get_device_for('swinir') class UpscalerSwinIR(Upscaler): def __init__(self, dirname): + self._cached_model = None # keep the model when SWIN_torch_compile is on to prevent re-compile every runs + self._cached_model_config = None # to clear '_cached_model' when changing model (v1/v2) or settings self.name = "SwinIR" self.model_url = SWINIR_MODEL_URL self.model_name = "SwinIR 4x" @@ -35,12 +38,24 @@ class UpscalerSwinIR(Upscaler): self.scalers = scalers def do_upscale(self, img, model_file): - try: - model = self.load_model(model_file) - except Exception as e: - print(f"Failed loading SwinIR model {model_file}: {e}", file=sys.stderr) - return img - model = model.to(device_swinir, dtype=devices.dtype) + use_compile = hasattr(opts, 'SWIN_torch_compile') and opts.SWIN_torch_compile \ + and int(torch.__version__.split('.')[0]) >= 2 and platform.system() != "Windows" + current_config = (model_file, opts.SWIN_tile) + + if use_compile and self._cached_model_config == current_config: + model = self._cached_model + else: + self._cached_model = None + try: + model = self.load_model(model_file) + except Exception as e: + print(f"Failed loading SwinIR model {model_file}: {e}", file=sys.stderr) + return img + model = model.to(device_swinir, dtype=devices.dtype) + if use_compile: + model = torch.compile(model) + self._cached_model = model + self._cached_model_config = current_config img = upscale(img, model) devices.torch_gc() return img @@ -170,6 +185,8 @@ def on_ui_settings(): shared.opts.add_option("SWIN_tile", shared.OptionInfo(192, "Tile size for all SwinIR.", gr.Slider, {"minimum": 16, "maximum": 512, "step": 16}, section=('upscaling', "Upscaling"))) shared.opts.add_option("SWIN_tile_overlap", shared.OptionInfo(8, "Tile overlap, in pixels for SwinIR. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}, section=('upscaling', "Upscaling"))) + if int(torch.__version__.split('.')[0]) >= 2 and platform.system() != "Windows": # torch.compile() require pytorch 2.0 or above, and not on Windows + shared.opts.add_option("SWIN_torch_compile", shared.OptionInfo(False, "Use torch.compile to accelerate SwinIR.", gr.Checkbox, {"interactive": True}, section=('upscaling', "Upscaling")).info("Takes longer on first run")) script_callbacks.on_ui_settings(on_ui_settings)