Merge branch 'main' into flux2

toolkit/memory_management/manager_modules.py

@@ -99,7 +99,10 @@ def _ensure_cpu_pinned(t: Optional[torch.Tensor]) -> Optional[torch.Tensor]:
     if t is None:
         return None
     if t.device.type != "cpu":
-        t = t.to("cpu", copy=True)
+        try:
+            t = t.to("cpu", copy=True)
+        except Exception:
+            t = t.to("cpu")
     # Don't attempt to pin quantized tensors; many backends don't support it
     if _is_quantized_tensor(t):
         return t

toolkit/unloader.py

@@ -47,6 +47,7 @@ def unload_text_encoder(model: "BaseModel"):
             if hasattr(pipe, "text_encoder"):
                 te = FakeTextEncoder(device=model.device_torch, dtype=model.torch_dtype)
                 text_encoder_list.append(te)
+                pipe.text_encoder.to('cpu')
                 pipe.text_encoder = te
 
             i = 2

ui/src/components/JobsTable.tsx

@@ -102,7 +102,7 @@ export default function JobsTable({ onlyActive = false }: JobsTableProps) {
     jd['Idle'] = { name: 'Idle', jobs: [] };
     jobs.forEach(job => {
       const gpu = gpuList.find(gpu => job.gpu_ids?.split(',').includes(gpu.index.toString())) as GpuInfo;
-      const key = `${gpu.index}`;
+      const key = `${gpu?.index || '0'}`;
       if (['queued', 'running', 'stopping'].includes(job.status) && key in jd) {
         jd[key].jobs.push(job);
       } else {

ui/src/components/SampleImageViewer.tsx

@@ -46,10 +46,21 @@ export default function SampleImageViewer({
   const onCancel = useCallback(() => setIsOpen(false), []);
 
   const imgInfo = useMemo(() => {
+    // handle windows C:\\Apps\\AI-Toolkit\\AI-Toolkit\\output\\LoRA-Name\\samples\\1763563000704__000004000_0.jpg
     const ii = { filename: '', step: 0, promptIdx: 0 };
     if (imgPath) {
-      const filename = imgPath.split('/').pop();
+      // handle windows
-      if (!filename) return ii;
+      let filename: string | null = null;
+      if (imgPath.includes('\\')) {
+        const parts = imgPath.split('\\');
+        filename = parts[parts.length - 1];
+      } else {
+        filename = imgPath.split('/').pop() || null;
+      }
+      if (!filename) {
+        console.error('Filename could not be determined from imgPath:', imgPath);
+        return ii;
+      }
       ii.filename = filename;
       const parts = filename
         .split('.')[0]
@@ -58,6 +69,8 @@ export default function SampleImageViewer({
       if (parts.length === 3) {
         ii.step = parseInt(parts[1]);
         ii.promptIdx = parseInt(parts[2]);
+      } else {
+        console.error('Unexpected filename format for sample image:', filename);
       }
     }
     return ii;