WAN Context Windows (Manual) node is specifically designed for WAN models. It automatically adjusts parameters to allow WAN models to better handle long content.
How it works:
Like using multiple segmented samples to generate different segments of a video, and finally synthesizing a complete video**
- Each window looks at a part (window processing)
- Windows overlap to ensure coherence (overlap areas)
- Finally, all parts are spliced into a complete image (result fusion)
Input Parameters
| Parameter Name | Function | Simple Explanation |
|---|---|---|
model | WAN Model Input | The WAN model you want to process |
context_length | Window Size | Length of each small window, WAN will automatically adjust to multiples of 4. The larger the range the more memory it occupies |
context_overlap | Overlap Size | Overlapping part between windows, more overlap means smoother effect but slower processing |
context_schedule | Processing Method | Choose how windows move, four modes available |
context_stride | Movement Step | How much the window moves each time, only useful in uniform mode |
closed_loop | Loop Mode | Whether to connect the last window back to the first, only useful in loop mode |
fuse_method | Merge Method | Choose how overlapping parts merge, affects final effect |
dim | Processing Dimension | Fixed at 2, specifically optimized for WAN models |
Scheduling Strategy Selection
| Scheduling Strategy | Working Method |
|---|---|
| STATIC_STANDARD | Window positions are fixed |
| UNIFORM_STANDARD | Windows move uniformly |
| UNIFORM_LOOPED | Windows move in a loop |
| BATCHED | Multiple windows processed simultaneously |
Merge Methods
| Merge Method | Weight Distribution Method | Characteristics |
|---|---|---|
| PYRAMID | Middle part most important, decreasing toward edges | Most natural effect, recommended |
| RELATIVE | Intelligent weight adjustment | Automatically adjusts based on position, natural effect |
| FLAT | Average weight distribution | Simple and direct, suitable for uniform content |
| OVERLAP_LINEAR | Linear gradient | Smoother transition |
Output Results
| Parameter Name | Data Type | Description |
|---|---|---|
model | MODEL | Processed WAN model, can be directly connected to sampler for use |
WAN Parameter Automatic Adjustment
Typical Usage
Usage Steps:- Load WAN model
- Connect to WAN Context Windows Manual node
- Connect to sampler to generate results