update_flux_default_setting

README.md

@@ -32,7 +32,7 @@ To use MagCache node, simply add `MagCache` node to your workflow after `Load Di
 
 | Models                       |   magcache_thresh |   retention_ratio |    magcache_K     |  
 |:----------------------------:|:-----------------:|:-----------------:|:-----------------:|
-| FLUX                         |        0.24       |         0.1       |         5         |
+| FLUX                         |        0.24       |         0.1       |         3         |
 | HunyuanVideo-T2V             |        0.24       |         0.2       |         6         |
 | Wan2.1-T2V-1.3B              |        0.12       |         0.2       |         4         |
 | Wan2.1-T2V-14B               |        0.24       |         0.2       |         6         |
@@ -41,7 +41,7 @@ To use MagCache node, simply add `MagCache` node to your workflow after `Load Di
 
 </div>
 
-If the image/video after applying MagCache is of low quality, please reduce magcache_thresh and magcache_K.
+If the image/video after applying MagCache is of low quality, please reduce **magcache_thresh** and **magcache_K**.
 
 The demo workflows ([flux](./examples/flux.json), [hunyuanvideo](./examples/hunyuanvideo.json), [wan2.1_t2v](./examples/wan2.1_t2v.json) and [wan2.1_i2v](./examples/wan2.1_i2v.json)) are placed in examples folder. **In our experiments, the videos generated by Wan2.1 are not as high-quality as those produced by the [original unquantized version](https://github.com/Wan-Video/Wan2.1).**
 

examples/flux.json

@@ -771,7 +771,7 @@
         "flux",
         0.24,
         0.1,
-        5
+        3
       ]
     }
   ],

nodes.py

@@ -74,7 +74,7 @@ def magcache_flux_forward(
             self.accumulated_ratio = 1
             self.accumulated_steps = 0
         skip_forward = False
-        if enable_magcache and cur_step!=11:
+        if enable_magcache and cur_step not in [11]:
             cur_mag_ratio = mag_ratios[cur_step]
             self.accumulated_ratio = self.accumulated_ratio*cur_mag_ratio # magnitude ratio between current step and the cached step
             self.accumulated_steps += 1 # skip steps plus 1