re-integrated tiling option as a UI element

modules/img2img.py

@@ -9,7 +9,7 @@ from modules.ui import plaintext_to_html
 import modules.images as images
 import modules.scripts
 
-def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, use_GFPGAN: bool, mode: int, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, height: int, width: int, resize_mode: int, upscaler_index: str, upscale_overlap: int, inpaint_full_res: bool, inpainting_mask_invert: int, *args):
+def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, use_GFPGAN: bool, tiling: bool, mode: int, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, height: int, width: int, resize_mode: int, upscaler_index: str, upscale_overlap: int, inpaint_full_res: bool, inpainting_mask_invert: int, *args):
     is_inpaint = mode == 1
     is_loopback = mode == 2
     is_upscale = mode == 3
@@ -37,6 +37,7 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
         width=width,
         height=height,
         use_GFPGAN=use_GFPGAN,
+        tiling=tiling,
         init_images=[image],
         mask=mask,
         mask_blur=mask_blur,

modules/processing.py

@@ -9,6 +9,7 @@ import numpy as np
 from PIL import Image, ImageFilter, ImageOps
 import random
 
+import modules.sd_hijack
 from modules.sd_hijack import model_hijack
 from modules.sd_samplers import samplers, samplers_for_img2img
 from modules.shared import opts, cmd_opts, state
@@ -28,7 +29,7 @@ def torch_gc():
 
 
 class StableDiffusionProcessing:
-    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt="", seed=-1, sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, use_GFPGAN=False, do_not_save_samples=False, do_not_save_grid=False, extra_generation_params=None, overlay_images=None, negative_prompt=None):
+    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt="", seed=-1, sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, use_GFPGAN=False, tiling=False, do_not_save_samples=False, do_not_save_grid=False, extra_generation_params=None, overlay_images=None, negative_prompt=None):
         self.sd_model = sd_model
         self.outpath_samples: str = outpath_samples
         self.outpath_grids: str = outpath_grids
@@ -44,6 +45,7 @@ class StableDiffusionProcessing:
         self.width: int = width
         self.height: int = height
         self.use_GFPGAN: bool = use_GFPGAN
+        self.tiling: bool = tiling
         self.do_not_save_samples: bool = do_not_save_samples
         self.do_not_save_grid: bool = do_not_save_grid
         self.extra_generation_params: dict = extra_generation_params
@@ -110,6 +112,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
     os.makedirs(p.outpath_samples, exist_ok=True)
     os.makedirs(p.outpath_grids, exist_ok=True)
 
+    modules.sd_hijack.model_hijack.apply_circular(p.tiling)
+
     comments = []
 
     if type(prompt) == list:

modules/sd_hijack.py

@@ -49,6 +49,8 @@ class StableDiffusionModelHijack:
     fixes = None
     comments = []
     dir_mtime = None
+    layers = None
+    circular_enabled = False
 
     def load_textual_inversion_embeddings(self, dirname, model):
         mt = os.path.getmtime(dirname)
@@ -105,6 +107,24 @@ class StableDiffusionModelHijack:
         if cmd_opts.opt_split_attention:
             ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward
 
+        def flatten(el):
+            flattened = [flatten(children) for children in el.children()]
+            res = [el]
+            for c in flattened:
+                res += c
+            return res
+
+        self.layers = flatten(m)
+
+    def apply_circular(self, enable):
+        if self.circular_enabled == enable:
+            return
+
+        self.circular_enabled = enable
+
+        for layer in [layer for layer in self.layers if type(layer) == torch.nn.Conv2d]:
+            layer.padding_mode = 'circular' if enable else 'zeros'
+
 
 class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
     def __init__(self, wrapped, hijack):

modules/shared.py

@@ -30,8 +30,6 @@ parser.add_argument("--precision", type=str, help="evaluate at this precision",
 parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)")
 parser.add_argument("--esrgan-models-path", type=str, help="path to directory with ESRGAN models", default=os.path.join(script_path, 'ESRGAN'))
 parser.add_argument("--opt-split-attention", action='store_true', help="enable optimization that reduced vram usage by a lot for about 10% decrease in performance")
-parser.add_argument("--tiling", action='store_true', help="causes the model to generate images that can be tiled")
-
 cmd_opts = parser.parse_args()
 
 cpu = torch.device("cpu")

modules/txt2img.py

@@ -6,7 +6,7 @@ import modules.processing as processing
 from modules.ui import plaintext_to_html
 
 
-def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, use_GFPGAN: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, height: int, width: int, *args):
+def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, use_GFPGAN: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, height: int, width: int, *args):
     p = StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
@@ -21,7 +21,8 @@ def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, u
         cfg_scale=cfg_scale,
         width=width,
         height=height,
-        use_GFPGAN=use_GFPGAN
+        use_GFPGAN=use_GFPGAN,
+        tiling=tiling,
     )
 
     processed = modules.scripts.scripts_txt2img.run(p, *args)

modules/ui.py

@@ -155,6 +155,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
 
                 with gr.Row():
                     use_gfpgan = gr.Checkbox(label='GFPGAN', value=False, visible=gfpgan.have_gfpgan)
+                    tiling = gr.Checkbox(label='Tiling', value=False)
 
                 with gr.Row():
                     batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
@@ -195,6 +196,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                     steps,
                     sampler_index,
                     use_gfpgan,
+                    tiling,
                     batch_count,
                     batch_size,
                     cfg_scale,
@@ -256,6 +258,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
 
                 with gr.Row():
                     use_gfpgan = gr.Checkbox(label='GFPGAN', value=False, visible=gfpgan.have_gfpgan)
+                    tiling = gr.Checkbox(label='Tiling', value=False)
                     sd_upscale_overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, visible=False)
 
                 with gr.Row():
@@ -339,6 +342,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                     mask_blur,
                     inpainting_fill,
                     use_gfpgan,
+                    tiling,
                     switch_mode,
                     batch_count,
                     batch_size,

webui.py

@@ -140,11 +140,6 @@ try:
 except Exception:
     pass
 
-
-if cmd_opts.tiling:
-    # this has to be done before the model is loaded
-    modules.sd_hijack.add_circular_option_to_conv_2d()
-
 sd_config = OmegaConf.load(cmd_opts.config)
 shared.sd_model = load_model_from_config(sd_config, cmd_opts.ckpt)
 shared.sd_model = (shared.sd_model if cmd_opts.no_half else shared.sd_model.half())