Merge fa87f263ce into 4209edf48d

app/app_settings.py

@@ -1,7 +1,6 @@
 import os
 import json
 from aiohttp import web
-import logging
 
 
 class AppSettings():
@@ -12,12 +11,8 @@ class AppSettings():
         file = self.user_manager.get_request_user_filepath(
             request, "comfy.settings.json")
         if os.path.isfile(file):
-            try:
-                with open(file) as f:
-                    return json.load(f)
-            except:
-                logging.error(f"The user settings file is corrupted: {file}")
-                return {}
+            with open(file) as f:
+                return json.load(f)
         else:
             return {}
 

comfy/text_encoders/t5.py

@@ -227,9 +227,8 @@ class T5(torch.nn.Module):
         super().__init__()
         self.num_layers = config_dict["num_layers"]
         model_dim = config_dict["d_model"]
-        inner_dim = config_dict["d_kv"] * config_dict["num_heads"]
 
-        self.encoder = T5Stack(self.num_layers, model_dim, inner_dim, config_dict["d_ff"], config_dict["dense_act_fn"], config_dict["is_gated_act"], config_dict["num_heads"], config_dict["model_type"] != "umt5", dtype, device, operations)
+        self.encoder = T5Stack(self.num_layers, model_dim, model_dim, config_dict["d_ff"], config_dict["dense_act_fn"], config_dict["is_gated_act"], config_dict["num_heads"], config_dict["model_type"] != "umt5", dtype, device, operations)
         self.dtype = dtype
         self.shared = operations.Embedding(config_dict["vocab_size"], model_dim, device=device, dtype=dtype)