re-integrated tiling option as a UI element
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AUTOMATIC
parent
f91d0c3d19
commit
a8a58dbac7
@ -9,7 +9,7 @@ from modules.ui import plaintext_to_html
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import modules.images as images
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import modules.scripts
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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):
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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):
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is_inpaint = mode == 1
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is_loopback = mode == 2
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is_upscale = mode == 3
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@ -37,6 +37,7 @@ def img2img(prompt: str, init_img, init_img_with_mask, steps: int, sampler_index
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width=width,
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height=height,
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use_GFPGAN=use_GFPGAN,
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tiling=tiling,
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init_images=[image],
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mask=mask,
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mask_blur=mask_blur,
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@ -9,6 +9,7 @@ import numpy as np
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from PIL import Image, ImageFilter, ImageOps
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import random
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import modules.sd_hijack
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from modules.sd_hijack import model_hijack
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from modules.sd_samplers import samplers, samplers_for_img2img
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from modules.shared import opts, cmd_opts, state
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@ -28,7 +29,7 @@ def torch_gc():
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class StableDiffusionProcessing:
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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):
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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):
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self.sd_model = sd_model
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self.outpath_samples: str = outpath_samples
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self.outpath_grids: str = outpath_grids
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@ -44,6 +45,7 @@ class StableDiffusionProcessing:
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self.width: int = width
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self.height: int = height
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self.use_GFPGAN: bool = use_GFPGAN
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self.tiling: bool = tiling
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self.do_not_save_samples: bool = do_not_save_samples
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self.do_not_save_grid: bool = do_not_save_grid
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self.extra_generation_params: dict = extra_generation_params
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@ -110,6 +112,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
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os.makedirs(p.outpath_samples, exist_ok=True)
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os.makedirs(p.outpath_grids, exist_ok=True)
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modules.sd_hijack.model_hijack.apply_circular(p.tiling)
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comments = []
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if type(prompt) == list:
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@ -49,6 +49,8 @@ class StableDiffusionModelHijack:
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fixes = None
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comments = []
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dir_mtime = None
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layers = None
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circular_enabled = False
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def load_textual_inversion_embeddings(self, dirname, model):
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mt = os.path.getmtime(dirname)
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@ -105,6 +107,24 @@ class StableDiffusionModelHijack:
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if cmd_opts.opt_split_attention:
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ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward
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def flatten(el):
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flattened = [flatten(children) for children in el.children()]
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res = [el]
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for c in flattened:
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res += c
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return res
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self.layers = flatten(m)
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def apply_circular(self, enable):
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if self.circular_enabled == enable:
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return
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self.circular_enabled = enable
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for layer in [layer for layer in self.layers if type(layer) == torch.nn.Conv2d]:
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layer.padding_mode = 'circular' if enable else 'zeros'
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class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
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def __init__(self, wrapped, hijack):
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@ -30,8 +30,6 @@ parser.add_argument("--precision", type=str, help="evaluate at this precision",
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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)")
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parser.add_argument("--esrgan-models-path", type=str, help="path to directory with ESRGAN models", default=os.path.join(script_path, 'ESRGAN'))
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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")
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parser.add_argument("--tiling", action='store_true', help="causes the model to generate images that can be tiled")
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cmd_opts = parser.parse_args()
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cpu = torch.device("cpu")
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@ -6,7 +6,7 @@ import modules.processing as processing
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from modules.ui import plaintext_to_html
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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):
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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):
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p = StableDiffusionProcessingTxt2Img(
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sd_model=shared.sd_model,
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outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
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@ -21,7 +21,8 @@ def txt2img(prompt: str, negative_prompt: str, steps: int, sampler_index: int, u
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cfg_scale=cfg_scale,
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width=width,
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height=height,
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use_GFPGAN=use_GFPGAN
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use_GFPGAN=use_GFPGAN,
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tiling=tiling,
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)
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processed = modules.scripts.scripts_txt2img.run(p, *args)
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@ -155,6 +155,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
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with gr.Row():
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use_gfpgan = gr.Checkbox(label='GFPGAN', value=False, visible=gfpgan.have_gfpgan)
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tiling = gr.Checkbox(label='Tiling', value=False)
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with gr.Row():
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batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
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@ -195,6 +196,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
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steps,
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sampler_index,
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use_gfpgan,
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tiling,
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batch_count,
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batch_size,
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cfg_scale,
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@ -256,6 +258,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
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with gr.Row():
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use_gfpgan = gr.Checkbox(label='GFPGAN', value=False, visible=gfpgan.have_gfpgan)
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tiling = gr.Checkbox(label='Tiling', value=False)
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sd_upscale_overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, visible=False)
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with gr.Row():
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@ -339,6 +342,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
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mask_blur,
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inpainting_fill,
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use_gfpgan,
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tiling,
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switch_mode,
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batch_count,
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batch_size,
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5
webui.py
5
webui.py
@ -140,11 +140,6 @@ try:
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except Exception:
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pass
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if cmd_opts.tiling:
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# this has to be done before the model is loaded
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modules.sd_hijack.add_circular_option_to_conv_2d()
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sd_config = OmegaConf.load(cmd_opts.config)
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shared.sd_model = load_model_from_config(sd_config, cmd_opts.ckpt)
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shared.sd_model = (shared.sd_model if cmd_opts.no_half else shared.sd_model.half())
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