Merge branch 'master' into hooks_part2

api_server/services/file_service.py

@@ -10,4 +10,4 @@ class FileService:
         if directory_key not in self.allowed_directories:
             raise ValueError("Invalid directory key")
         directory_path: str = self.allowed_directories[directory_key]
-        return self.file_system_ops.walk_directory(directory_path)
+        return self.file_system_ops.walk_directory(directory_path)

api_server/utils/file_operations.py

@@ -39,4 +39,4 @@ class FileSystemOperations:
                     "path": relative_path,
                     "type": "directory"
                 })
-        return file_list
+        return file_list

app/app_settings.py

@@ -51,4 +51,4 @@ class AppSettings():
             settings = self.get_settings(request)
             settings[setting_id] = await request.json()
             self.save_settings(request, settings)
-            return web.Response(status=200)
+            return web.Response(status=200)

comfy/ldm/util.py

@@ -194,4 +194,4 @@ class AdamWwithEMAandWings(optim.Optimizer):
             for param, ema_param in zip(params_with_grad, ema_params_with_grad):
                 ema_param.mul_(cur_ema_decay).add_(param.float(), alpha=1 - cur_ema_decay)
 
-        return loss
+        return loss

comfy/samplers.py

@@ -467,6 +467,13 @@ def linear_quadratic_schedule(model_sampling, steps, threshold_noise=0.025, line
         sigma_schedule = [1.0 - x for x in sigma_schedule]
     return torch.FloatTensor(sigma_schedule) * model_sampling.sigma_max.cpu()
 
+# Referenced from https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/15608
+def kl_optimal_scheduler(n: int, sigma_min: float, sigma_max: float) -> torch.Tensor:
+    adj_idxs = torch.arange(n, dtype=torch.float).div_(n - 1)
+    sigmas = adj_idxs.new_zeros(n + 1)
+    sigmas[:-1] = (adj_idxs * math.atan(sigma_min) + (1 - adj_idxs) * math.atan(sigma_max)).tan_()
+    return sigmas
+
 def get_mask_aabb(masks):
     if masks.numel() == 0:
         return torch.zeros((0, 4), device=masks.device, dtype=torch.int)
@@ -913,7 +920,7 @@ def sample(model, noise, positive, negative, cfg, device, sampler, sigmas, model
     return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
 
 
-SCHEDULER_NAMES = ["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "linear_quadratic"]
+SCHEDULER_NAMES = ["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "linear_quadratic", "kl_optimal"]
 SAMPLER_NAMES = KSAMPLER_NAMES + ["ddim", "uni_pc", "uni_pc_bh2"]
 
 def calculate_sigmas(model_sampling, scheduler_name, steps):
@@ -933,6 +940,8 @@ def calculate_sigmas(model_sampling, scheduler_name, steps):
         sigmas = beta_scheduler(model_sampling, steps)
     elif scheduler_name == "linear_quadratic":
         sigmas = linear_quadratic_schedule(model_sampling, steps)
+    elif scheduler_name == "kl_optimal":
+        sigmas = kl_optimal_scheduler(n=steps, sigma_min=float(model_sampling.sigma_min), sigma_max=float(model_sampling.sigma_max))
     else:
         logging.error("error invalid scheduler {}".format(scheduler_name))
     return sigmas

comfy_execution/graph.py

@@ -54,8 +54,8 @@ class DynamicPrompt:
     def get_original_prompt(self):
         return self.original_prompt
 
-def get_input_info(class_def, input_name):
+def get_input_info(class_def, input_name, valid_inputs=None):
-    valid_inputs = class_def.INPUT_TYPES()
+    valid_inputs = valid_inputs or class_def.INPUT_TYPES()
     input_info = None
     input_category = None
     if "required" in valid_inputs and input_name in valid_inputs["required"]:

comfy_extras/nodes_load_3d.py

@@ -121,4 +121,4 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "Load3D": "Load 3D",
     "Load3DAnimation": "Load 3D - Animation",
     "Preview3D": "Preview 3D"
-}
+}

comfy_extras/nodes_morphology.py

@@ -46,4 +46,4 @@ NODE_CLASS_MAPPINGS = {
 
 NODE_DISPLAY_NAME_MAPPINGS = {
     "Morphology": "ImageMorphology",
-}
+}

comfy_extras/nodes_webcam.py

@@ -30,4 +30,4 @@ NODE_CLASS_MAPPINGS = {
 
 NODE_DISPLAY_NAME_MAPPINGS = {
     "WebcamCapture": "Webcam Capture",
-}
+}

execution.py

@@ -93,7 +93,7 @@ def get_input_data(inputs, class_def, unique_id, outputs=None, dynprompt=None, e
     missing_keys = {}
     for x in inputs:
         input_data = inputs[x]
-        input_type, input_category, input_info = get_input_info(class_def, x)
+        input_type, input_category, input_info = get_input_info(class_def, x, valid_inputs)
         def mark_missing():
             missing_keys[x] = True
             input_data_all[x] = (None,)
@@ -555,7 +555,7 @@ def validate_inputs(prompt, item, validated):
     received_types = {}
 
     for x in valid_inputs:
-        type_input, input_category, extra_info = get_input_info(obj_class, x)
+        type_input, input_category, extra_info = get_input_info(obj_class, x, class_inputs)
         assert extra_info is not None
         if x not in inputs:
             if input_category == "required":

ruff.toml

@@ -5,6 +5,7 @@ lint.ignore = ["ALL"]
 lint.select = [
     "S307",  # suspicious-eval-usage
     "T201",  # print-usage
+    "W292",
     "W293",
     # The "F" series in Ruff stands for "Pyflakes" rules, which catch various Python syntax errors and undefined names.
     # See all rules here: https://docs.astral.sh/ruff/rules/#pyflakes-f

tests-unit/comfy_test/folder_path_test.py

@@ -95,4 +95,4 @@ def test_get_save_image_path(temp_dir):
         assert filename == "test"
         assert counter == 1
         assert subfolder == ""
-        assert filename_prefix == "test"
+        assert filename_prefix == "test"

tests-unit/folder_paths_test/filter_by_content_types_test.py

@@ -49,4 +49,4 @@ def test_handles_no_extension():
 
 def test_handles_no_files():
     files = []
-    assert filter_files_content_types(files, ["image", "audio", "video"]) == []
+    assert filter_files_content_types(files, ["image", "audio", "video"]) == []