From c515bdf3710e77233e5b4baa24e038de8e86f56e Mon Sep 17 00:00:00 2001
From: "Dr.Lt.Data" <128333288+ltdrdata@users.noreply.github.com>
Date: Wed, 8 Jan 2025 06:03:56 +0900
Subject: [PATCH 1/2] fixed: robust loading `comfy.settings.json` (#6383)

https://github.com/comfyanonymous/ComfyUI/issues/6371
---
 app/app_settings.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/app/app_settings.py b/app/app_settings.py
index efe87adbd..a545df92e 100644
--- a/app/app_settings.py
+++ b/app/app_settings.py
@@ -1,6 +1,7 @@
 import os
 import json
 from aiohttp import web
+import logging
 
 
 class AppSettings():
@@ -11,8 +12,12 @@ class AppSettings():
         file = self.user_manager.get_request_user_filepath(
             request, "comfy.settings.json")
         if os.path.isfile(file):
-            with open(file) as f:
-                return json.load(f)
+            try:
+                with open(file) as f:
+                    return json.load(f)
+            except:
+                logging.error(f"The user settings file is corrupted: {file}")
+                return {}
         else:
             return {}
 

From d0f3752e332ad9b2d8ee6f9c4317868aa685a62e Mon Sep 17 00:00:00 2001
From: comfyanonymous <comfyanonymous@protonmail.com>
Date: Tue, 7 Jan 2025 17:32:29 -0500
Subject: [PATCH 2/2] Properly calculate inner dim for t5 model.

This is required to support some different types of t5 models.
---
 comfy/text_encoders/t5.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/comfy/text_encoders/t5.py b/comfy/text_encoders/t5.py
index 38d8d5234..7405528e2 100644
--- a/comfy/text_encoders/t5.py
+++ b/comfy/text_encoders/t5.py
@@ -227,8 +227,9 @@ 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, 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.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.dtype = dtype
         self.shared = operations.Embedding(config_dict["vocab_size"], model_dim, device=device, dtype=dtype)