upgrade diffusers

CHANGELOG.md

@@ -18,6 +18,8 @@ Mostly a service release, but with some changes in behavior, especially in HiRes
   - all combinations of: decode full/quick + upscale none/latent/non-latent + hires on/off + refiner on/off  
     should be supported, but given the number of combinations, issues are possible  
   - all operations are captured in image medata
+- diffusers:
+  - allow loading of sd/sdxl models from safetensors without online connectivity
 - minor re-layout of the main ui  
 - update **ui hints**  
 - updated **models -> civitai**  

javascript/extraNetworks.js

@@ -153,13 +153,18 @@ function setupExtraNetworksForTab(tabname) {
   tabs.appendChild(div);
   div.appendChild(search);
   div.appendChild(description);
+  let searchTimer = null;
   search.addEventListener('input', (evt) => {
-    const searchTerm = search.value.toLowerCase();
-    gradioApp().querySelectorAll(`#${tabname}_extra_tabs div.card`).forEach((elem) => {
-      let text = `${elem.querySelector('.name').textContent.toLowerCase()} ${elem.querySelector('.search_term').textContent.toLowerCase()}`;
-      text = text.replace('models--', 'Diffusers');
-      elem.style.display = text.indexOf(searchTerm) === -1 ? 'none' : '';
-    });
+    if (searchTimer) clearTimeout(searchTimer);
+    searchTimer = setTimeout(() => {
+      const searchTerm = search.value.toLowerCase();
+      gradioApp().querySelectorAll(`#${tabname}_extra_tabs div.card`).forEach((elem) => {
+        let text = `${elem.querySelector('.name').textContent.toLowerCase()} ${elem.querySelector('.search_term').textContent.toLowerCase()}`;
+        text = text.replace('models--', 'Diffusers');
+        elem.style.display = text.indexOf(searchTerm) === -1 ? 'none' : '';
+      });
+      searchTimer = null;
+    }, 100);
   });
 
   let hoverTimer = null;

javascript/style.css

@@ -230,7 +230,7 @@ table.settings-value-table td { padding: 0.4em; border: 1px solid #ccc; max-widt
 .extra-networks .description { flex: 3; }
 .extra-networks .tab-nav > button { margin-right: 0; height: 24px; padding: 2px 4px 2px 4px; }
 .extra-networks-tab { padding: 0 !important; }
-.extra-network-subdirs { background: var(--input-background-fill); overflow-x: hidden; overflow-y: auto; min-width: 20%; padding-top: 0.5em; }
+.extra-network-subdirs { background: var(--input-background-fill); overflow-x: hidden; overflow-y: auto; min-width: max(20%, 120px); padding-top: 0.5em; }
 .extra-networks-page { display: flex }
 .extra-networks .custom-button { width: 120px; width: 100%; background: none; justify-content: left; text-align: left; padding: 2px 8px 2px 16px; text-indent: -8px; box-shadow: none; line-break: auto; }
 .extra-networks .custom-button:hover { background: var(--button-primary-background-fill) }

modules/devices.py

@@ -160,7 +160,7 @@ def test_bf16():
 
 
 def set_cuda_params():
-    shared.log.debug('Verifying Torch settings')
+    # shared.log.debug('Verifying Torch settings')
     if cuda_ok:
         try:
             torch.backends.cuda.matmul.allow_tf32 = True
@@ -212,8 +212,7 @@ def set_cuda_params():
     else:
         inference_context = torch.no_grad
     shared.log.debug(f'Desired Torch parameters: dtype={shared.opts.cuda_dtype} no-half={shared.opts.no_half} no-half-vae={shared.opts.no_half_vae} upscast={shared.opts.upcast_sampling}')
-    shared.log.info(f'Setting Torch parameters: dtype={dtype} vae={dtype_vae} unet={dtype_unet} context={inference_context.__name__} fp16={fp16_ok} bf16={bf16_ok}')
-    shared.log.debug(f'Torch default device: {torch.device(get_optimal_device_name())}')
+    shared.log.info(f'Setting Torch parameters: device={torch.device(get_optimal_device_name())} dtype={dtype} vae={dtype_vae} unet={dtype_unet} context={inference_context.__name__} fp16={fp16_ok} bf16={bf16_ok}')
 
 
 args = cmd_args.parser.parse_args()

modules/processing_diffusers.py

@@ -68,7 +68,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
                 time.sleep(0.1)
 
     def full_vae_decode(latents, model):
-        shared.log.debug(f'VAE decode: name={sd_vae.loaded_vae_file if sd_vae.loaded_vae_file is not None else "baked"} dtype={model.vae.dtype} upcast={model.vae.config.get("force_upcast", None)} images={latents.shape[0]} latents={latents.shape}')
+        t0 = time.time()
         if shared.opts.diffusers_move_unet and not model.has_accelerate:
             shared.log.debug('Moving to CPU: model=UNet')
             unet_device = model.unet.device
@@ -80,6 +80,8 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
         decoded = model.vae.decode(latents / model.vae.config.scaling_factor, return_dict=False)[0]
         if shared.opts.diffusers_move_unet and not model.has_accelerate:
             model.unet.to(unet_device)
+        t1 = time.time()
+        shared.log.debug(f'VAE decode: name={sd_vae.loaded_vae_file if sd_vae.loaded_vae_file is not None else "baked"} dtype={model.vae.dtype} upcast={model.vae.config.get("force_upcast", None)} images={latents.shape[0]} latents={latents.shape} time={round(t1-t0, 3)}s')
         return decoded
 
     def full_vae_encode(image, model):
@@ -168,7 +170,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
         except Exception:
             is_refiner = False
         if hasattr(model, "set_progress_bar_config"):
-            model.set_progress_bar_config(bar_format='Progress {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} '+desc, ncols=80, colour='#327fba')
+            model.set_progress_bar_config(bar_format='Progress {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} ' + '\x1b[38;5;71m' + desc, ncols=80, colour='#327fba')
         args = {}
         signature = inspect.signature(type(model).__call__)
         possible = signature.parameters.keys()

modules/sd_models.py

@@ -719,7 +719,7 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
             if vae is not None:
                 diffusers_load_config["vae"] = vae
 
-        shared.log.info(f'Loading diffuser {op}: {checkpoint_info.filename}')
+        # shared.log.info(f'Loading diffuser {op}: {checkpoint_info.filename}')
         if not os.path.isfile(checkpoint_info.path):
             try:
                 # shared.log.debug(f'Diffusers load {op} config: {diffusers_load_config}')

requirements.txt

@@ -47,7 +47,7 @@ requests==2.31.0
 tqdm==4.65.0
 accelerate==0.20.3
 opencv-python-headless==4.7.0.72
-diffusers==0.20.2
+diffusers==0.21.1
 einops==0.4.1
 gradio==3.43.2
 huggingface_hub==0.16.4