Fix DynaDiff VD weights, xformers, and brain thumbnail path resolution

- Pre-bake Versatile Diffusion weights into the image via snapshot_download
to avoid ~3 GB runtime download from HF Hub
- Add xformers to pip deps (models.py calls enable_xformers unconditionally)
- Resolve brain image_paths against --brain-thumbnails even when stored as
absolute paths that don't exist on the current machine (scratch paths)
- Bump CACHEBUST to 9 to force a clean rebuild

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Dockerfile

@@ -1,7 +1,7 @@
 FROM pytorch/pytorch:2.3.0-cuda12.1-cudnn8-runtime
 
 # Cache-bust: increment to force a full rebuild
-ARG CACHEBUST=8
+ARG CACHEBUST=9
 RUN echo "Build $CACHEBUST"
 
 # System deps
@@ -36,6 +36,7 @@ RUN pip install --no-cache-dir \
     scikit-image==0.24.0 \
     dreamsim==0.2.0 \
     wandb \
+    xformers \
     "git+https://github.com/openai/CLIP.git"
 
 # ── Runtime ENV: CUDA path for deepspeed inference + disable op compilation ──
@@ -56,6 +57,21 @@ COPY dynadiff/diffusers /app/dynadiff/diffusers
 RUN pip install --no-cache-dir -e /app/dynadiff/diffusers
 RUN pip install --no-cache-dir transformers==4.41.2
 
+# ── Pre-download Versatile Diffusion weights ─────────────────────────────────
+# Baked into the image so cold-starts don't download ~3 GB from HF Hub.
+# Placed after patched-diffusers install and before COPY statements
+# (which change often) to maximise Docker layer cache reuse.
+RUN python -c "
+from huggingface_hub import snapshot_download
+print('Pre-downloading shi-labs/versatile-diffusion ...')
+snapshot_download(
+    'shi-labs/versatile-diffusion',
+    local_dir='/app/dynadiff/versatile_diffusion',
+    local_dir_use_symlinks=False,
+)
+print('Versatile Diffusion saved to /app/dynadiff/versatile_diffusion')
+"
+
 # ── DynaDiff model code ──────────────────────────────────────────────────────
 COPY dynadiff/model  /app/dynadiff/model
 COPY dynadiff/config /app/dynadiff/config

scripts/explorer_app.py

@@ -391,10 +391,13 @@ def _load_brain_dataset_dict(path, label, thumb_dir):
         print(f"[Brain] WARNING: Failed to load NSD dataset: {err}")
         return None
 
-    # Resolve image_paths: prepend thumb_dir when paths are stored as basenames.
+    # Resolve image_paths: prepend thumb_dir when paths are stored as basenames,
+    # or when stored as absolute paths that don't exist on this machine.
     raw_paths = bd.get('image_paths', [])
-    if raw_paths and thumb_dir and not os.path.isabs(raw_paths[0]):
-        bd_paths = [os.path.join(thumb_dir, p) for p in raw_paths]
+    if raw_paths and thumb_dir and (
+        not os.path.isabs(raw_paths[0]) or not os.path.exists(raw_paths[0])
+    ):
+        bd_paths = [os.path.join(thumb_dir, os.path.basename(p)) for p in raw_paths]
     else:
         bd_paths = raw_paths