chore: Fix typos

README.md

@@ -34,7 +34,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
 - Sampling method selection
 - Interrupt processing at any time
 - 4GB video card support (also reports of 2GB working)
-- Correct seeds for batches 
+- Correct seeds for batches
 - Prompt length validation
      - get length of prompt in tokens as you type
      - get a warning after generation if some text was truncated

javascript/imageviewer.js

@@ -95,7 +95,7 @@ function showGalleryImage(){
 
                     e.addEventListener('click', function (evt) {
                         if(!opts.js_modal_lightbox) return;
-                        modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initialy_zoomed)
+                        modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed)
                         showModal(evt)
                     },true);
                 }

modules/interrogate.py

@@ -140,11 +140,11 @@ class InterrogateModels:
 
             res = caption
 
-            cilp_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(shared.device)
+            clip_image = self.clip_preprocess(pil_image).unsqueeze(0).type(self.dtype).to(shared.device)
 
             precision_scope = torch.autocast if shared.cmd_opts.precision == "autocast" else contextlib.nullcontext
             with torch.no_grad(), precision_scope("cuda"):
-                image_features = self.clip_model.encode_image(cilp_image).type(self.dtype)
+                image_features = self.clip_model.encode_image(clip_image).type(self.dtype)
 
                 image_features /= image_features.norm(dim=-1, keepdim=True)
 

modules/processing.py

@@ -386,7 +386,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
             if state.interrupted or state.skipped:
 
-                # if we are interruped, sample returns just noise
+                # if we are interrupted, sample returns just noise
                 # use the image collected previously in sampler loop
                 samples_ddim = shared.state.current_latent
 

modules/scunet_model_arch.py

@@ -40,7 +40,7 @@ class WMSA(nn.Module):
         Returns:
             attn_mask: should be (1 1 w p p),
         """
-        # supporting sqaure.
+        # supporting square.
         attn_mask = torch.zeros(h, w, p, p, p, p, dtype=torch.bool, device=self.relative_position_params.device)
         if self.type == 'W':
             return attn_mask
@@ -65,7 +65,7 @@ class WMSA(nn.Module):
         x = rearrange(x, 'b (w1 p1) (w2 p2) c -> b w1 w2 p1 p2 c', p1=self.window_size, p2=self.window_size)
         h_windows = x.size(1)
         w_windows = x.size(2)
-        # sqaure validation
+        # square validation
         # assert h_windows == w_windows
 
         x = rearrange(x, 'b w1 w2 p1 p2 c -> b (w1 w2) (p1 p2) c', p1=self.window_size, p2=self.window_size)

modules/sd_models.py

@@ -147,7 +147,7 @@ def load_model_weights(model, checkpoint_file, sd_model_hash):
         model.first_stage_model.load_state_dict(vae_dict)
 
     model.sd_model_hash = sd_model_hash
-    model.sd_model_checkpint = checkpoint_file
+    model.sd_model_checkpoint = checkpoint_file
 
 
 def load_model():
@@ -175,7 +175,7 @@ def reload_model_weights(sd_model, info=None):
     from modules import lowvram, devices, sd_hijack
     checkpoint_info = info or select_checkpoint()
 
-    if sd_model.sd_model_checkpint == checkpoint_info.filename:
+    if sd_model.sd_model_checkpoint == checkpoint_info.filename:
         return
 
     if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:

modules/sd_samplers.py

@@ -181,7 +181,7 @@ class VanillaStableDiffusionSampler:
 
         self.initialize(p)
 
-        # existing code fails with cetain step counts, like 9
+        # existing code fails with certain step counts, like 9
         try:
             self.sampler.make_schedule(ddim_num_steps=steps,  ddim_eta=self.eta, ddim_discretize=p.ddim_discretize, verbose=False)
         except Exception:
@@ -204,7 +204,7 @@ class VanillaStableDiffusionSampler:
 
         steps = steps or p.steps
 
-        # existing code fails with cetin step counts, like 9
+        # existing code fails with certain step counts, like 9
         try:
             samples_ddim, _ = self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=self.eta)
         except Exception:

modules/shared.py

@@ -141,9 +141,9 @@ class OptionInfo:
         self.section = None
 
 
-def options_section(section_identifer, options_dict):
+def options_section(section_identifier, options_dict):
     for k, v in options_dict.items():
-        v.section = section_identifer
+        v.section = section_identifier
 
     return options_dict
 
@@ -246,7 +246,7 @@ options_templates.update(options_section(('ui', "User interface"), {
     "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
     "font": OptionInfo("", "Font for image grids that have text"),
     "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
-    "js_modal_lightbox_initialy_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
+    "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
     "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
 }))
 

modules/swinir_model_arch.py

@@ -166,7 +166,7 @@ class SwinTransformerBlock(nn.Module):
 
     Args:
         dim (int): Number of input channels.
-        input_resolution (tuple[int]): Input resulotion.
+        input_resolution (tuple[int]): Input resolution.
         num_heads (int): Number of attention heads.
         window_size (int): Window size.
         shift_size (int): Shift size for SW-MSA.

modules/ui.py

@@ -38,7 +38,7 @@ from modules import prompt_parser
 from modules.images import save_image
 import modules.textual_inversion.ui
 
-# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
+# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
 mimetypes.init()
 mimetypes.add_type('application/javascript', '.js')
 
@@ -102,7 +102,7 @@ def save_files(js_data, images, index):
     import csv    
     filenames = []
 
-    #quick dictionary to class object conversion. Its neccesary due apply_filename_pattern requiring it
+    #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
     class MyObject:
         def __init__(self, d=None):
             if d is not None: