diff --git a/CHANGELOG.md b/CHANGELOG.md index 6c6ab5e3..c3c57fe0 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,3 +1,17 @@ +## 1.3.1 + +### Features: + * revert default cross attention optimization to Doggettx + +### Bug Fixes: + * fix bug: LoRA don't apply on dropdown list sd_lora + * fix png info always added even if setting is not enabled + * fix some fields not applying in xyz plot + * fix "hires. fix" prompt sharing same labels with txt2img_prompt + * fix lora hashes not being added properly to infotex if there is only one lora + * fix --use-cpu failing to work properly at startup + * make --disable-opt-split-attention command line option work again + ## 1.3.0 ### Features: diff --git a/modules/cmd_args.py b/modules/cmd_args.py index 3eeb84d5..71a21b1a 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -62,7 +62,7 @@ parser.add_argument("--opt-split-attention-invokeai", action='store_true', help= parser.add_argument("--opt-split-attention-v1", action='store_true', help="prefer older version of split attention optimization for automatic choice of optimization") parser.add_argument("--opt-sdp-attention", action='store_true', help="prefer scaled dot product cross-attention layer optimization for automatic choice of optimization; requires PyTorch 2.*") parser.add_argument("--opt-sdp-no-mem-attention", action='store_true', help="prefer scaled dot product cross-attention layer optimization without memory efficient attention for automatic choice of optimization, makes image generation deterministic; requires PyTorch 2.*") -parser.add_argument("--disable-opt-split-attention", action='store_true', help="does not do anything") +parser.add_argument("--disable-opt-split-attention", action='store_true', help="prefer no cross-attention layer optimization for automatic choice of optimization") parser.add_argument("--disable-nan-check", action='store_true', help="do not check if produced images/latent spaces have nans; useful for running without a checkpoint in CI") parser.add_argument("--use-cpu", nargs='+', 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") diff --git a/modules/extra_networks.py b/modules/extra_networks.py index 34a3ba63..f4743928 100644 --- a/modules/extra_networks.py +++ b/modules/extra_networks.py @@ -26,7 +26,7 @@ class ExtraNetworkParams: self.named = {} for item in self.items: - parts = item.split('=', 2) + parts = item.split('=', 2) if isinstance(item, str) else [item] if len(parts) == 2: self.named[parts[0]] = parts[1] else: diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index d5f0a49b..cfc04114 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -35,7 +35,7 @@ def reset(): def quote(text): - if ',' not in str(text) and '\n' not in str(text): + if ',' not in str(text) and '\n' not in str(text) and ':' not in str(text): return text return json.dumps(text, ensure_ascii=False) diff --git a/modules/images.py b/modules/images.py index 4e8cd993..3f60e944 100644 --- a/modules/images.py +++ b/modules/images.py @@ -493,9 +493,12 @@ def save_image_with_geninfo(image, geninfo, filename, extension=None, existing_p existing_pnginfo['parameters'] = geninfo if extension.lower() == '.png': - pnginfo_data = PngImagePlugin.PngInfo() - for k, v in (existing_pnginfo or {}).items(): - pnginfo_data.add_text(k, str(v)) + if opts.enable_pnginfo: + pnginfo_data = PngImagePlugin.PngInfo() + for k, v in (existing_pnginfo or {}).items(): + pnginfo_data.add_text(k, str(v)) + else: + pnginfo_data = None image.save(filename, format=image_format, quality=opts.jpeg_quality, pnginfo=pnginfo_data) diff --git a/modules/processing.py b/modules/processing.py index 29a3743f..d22b353f 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -321,14 +321,13 @@ class StableDiffusionProcessing: have been used before. The second element is where the previously computed result is stored. """ - - if cache[0] is not None and (required_prompts, steps) == cache[0]: + if cache[0] is not None and (required_prompts, steps, opts.CLIP_stop_at_last_layers, shared.sd_model.sd_checkpoint_info) == cache[0]: return cache[1] with devices.autocast(): cache[1] = function(shared.sd_model, required_prompts, steps) - cache[0] = (required_prompts, steps) + cache[0] = (required_prompts, steps, opts.CLIP_stop_at_last_layers, shared.sd_model.sd_checkpoint_info) return cache[1] def setup_conds(self): diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index f93df0a6..221771da 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -68,6 +68,8 @@ def apply_optimizations(): if selection == "None": matching_optimizer = None + elif selection == "Automatic" and shared.cmd_opts.disable_opt_split_attention: + matching_optimizer = None elif matching_optimizer is None: matching_optimizer = optimizers[0] diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index 2ec0b049..80e48a42 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -59,7 +59,7 @@ class SdOptimizationSdpNoMem(SdOptimization): name = "sdp-no-mem" label = "scaled dot product without memory efficient attention" cmd_opt = "opt_sdp_no_mem_attention" - priority = 90 + priority = 80 def is_available(self): return hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(torch.nn.functional.scaled_dot_product_attention) @@ -73,7 +73,7 @@ class SdOptimizationSdp(SdOptimizationSdpNoMem): name = "sdp" label = "scaled dot product" cmd_opt = "opt_sdp_attention" - priority = 80 + priority = 70 def apply(self): ldm.modules.attention.CrossAttention.forward = scaled_dot_product_attention_forward @@ -116,7 +116,7 @@ class SdOptimizationInvokeAI(SdOptimization): class SdOptimizationDoggettx(SdOptimization): name = "Doggettx" cmd_opt = "opt_split_attention" - priority = 20 + priority = 90 def apply(self): ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward diff --git a/modules/sd_models.py b/modules/sd_models.py index b1afbaa7..7742998a 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -313,8 +313,6 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer timer.record("apply half()") - devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16 - devices.dtype_vae = torch.float32 if shared.cmd_opts.no_half or shared.cmd_opts.no_half_vae else torch.float16 devices.dtype_unet = model.model.diffusion_model.dtype devices.unet_needs_upcast = shared.cmd_opts.upcast_sampling and devices.dtype == torch.float16 and devices.dtype_unet == torch.float16 diff --git a/modules/shared.py b/modules/shared.py index 3099d1d2..271a062d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -6,6 +6,7 @@ import threading import time import gradio as gr +import torch import tqdm import modules.interrogate @@ -76,6 +77,9 @@ cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_op devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, 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', 'esrgan', 'codeformer']) +devices.dtype = torch.float32 if cmd_opts.no_half else torch.float16 +devices.dtype_vae = torch.float32 if cmd_opts.no_half or cmd_opts.no_half_vae else torch.float16 + device = devices.device weight_load_location = None if cmd_opts.lowram else "cpu" diff --git a/modules/ui.py b/modules/ui.py index e62182da..361f596e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -505,10 +505,10 @@ def create_ui(): with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container: with gr.Column(scale=80): with gr.Row(): - hr_prompt = gr.Textbox(label="Prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.", elem_classes=["prompt"]) + hr_prompt = gr.Textbox(label="Hires prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.", elem_classes=["prompt"]) with gr.Column(scale=80): with gr.Row(): - hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.", elem_classes=["prompt"]) + hr_negative_prompt = gr.Textbox(label="Hires negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.", elem_classes=["prompt"]) elif category == "batch": if not opts.dimensions_and_batch_together: