Fix open_clip batch_first compatibility via auto-applied patch

Newer open_clip creates nn.MultiheadAttention with batch_first=True,
but STAR's embedder unconditionally permutes to [seq, batch, embed].
This causes a RuntimeError in the text encoder (attn_mask shape
mismatch). The patch detects batch_first at runtime and only permutes
when needed.

Patches in patches/ are auto-applied to the STAR submodule on startup
and skip gracefully if already applied.

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

inference.py

@@ -29,8 +29,26 @@ import types
 from pathlib import Path
 
 SCRIPT_DIR = Path(__file__).resolve().parent
+STAR_REPO = SCRIPT_DIR / "STAR"
 sys.path.insert(0, str(SCRIPT_DIR))
-sys.path.insert(0, str(SCRIPT_DIR / "STAR"))
+sys.path.insert(0, str(STAR_REPO))
+
+# Apply patches from patches/ directory to the STAR submodule.
+import subprocess  # noqa: E402
+
+_PATCHES_DIR = SCRIPT_DIR / "patches"
+if _PATCHES_DIR.is_dir():
+    for _patch in sorted(_PATCHES_DIR.iterdir()):
+        if _patch.suffix != ".patch":
+            continue
+        if subprocess.call(
+            ["git", "apply", "--check", "--reverse", str(_patch)],
+            cwd=str(STAR_REPO), stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL,
+        ) != 0:
+            if subprocess.call(["git", "apply", str(_patch)], cwd=str(STAR_REPO)) == 0:
+                print(f"[STAR] Applied patch: {_patch.name}")
+            else:
+                print(f"[STAR] Warning: failed to apply patch: {_patch.name}")
 
 import torch  # noqa: E402 — needed for stub defaults
 
@@ -138,7 +156,6 @@ print(f"[STAR] Available attention backends: {list(_ATTN_BACKENDS.keys())}")
 import argparse  # noqa: E402
 import json  # noqa: E402
 import shutil  # noqa: E402
-import subprocess  # noqa: E402
 
 import numpy as np  # noqa: E402
 from PIL import Image  # noqa: E402

nodes.py

@@ -29,6 +29,24 @@ if not os.path.isdir(os.path.join(STAR_REPO, "video_to_video")):
 if STAR_REPO not in sys.path:
     sys.path.insert(0, STAR_REPO)
 
+# Apply patches from patches/ directory to the STAR submodule.
+_PATCHES_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "patches")
+if os.path.isdir(_PATCHES_DIR):
+    import subprocess as _sp
+    for _patch in sorted(os.listdir(_PATCHES_DIR)):
+        if not _patch.endswith(".patch"):
+            continue
+        _patch_path = os.path.join(_PATCHES_DIR, _patch)
+        # --check + --reverse: succeeds silently if already applied.
+        if _sp.call(
+            ["git", "apply", "--check", "--reverse", _patch_path],
+            cwd=STAR_REPO, stdout=_sp.DEVNULL, stderr=_sp.DEVNULL,
+        ) != 0:
+            if _sp.call(["git", "apply", _patch_path], cwd=STAR_REPO) == 0:
+                print(f"[STAR] Applied patch: {_patch}")
+            else:
+                print(f"[STAR] Warning: failed to apply patch: {_patch}")
+
 # ── Attention backend dispatcher ──────────────────────────────────────
 # Build a registry of available backends at import time.
 # sdpa (PyTorch native) is always available and is the default.

patches/openclip_batch_first.patch

@@ -0,0 +1,24 @@
+diff --git a/video_to_video/modules/embedder.py b/video_to_video/modules/embedder.py
+index 9b2e760..29cc0fd 100644
+--- a/video_to_video/modules/embedder.py
++++ b/video_to_video/modules/embedder.py
+@@ -54,9 +54,17 @@ class FrozenOpenCLIPEmbedder(nn.Module):
+     def encode_with_transformer(self, text):
+         x = self.model.token_embedding(text)
+         x = x + self.model.positional_embedding
+-        x = x.permute(1, 0, 2)
++        # Newer open_clip sets batch_first=True on MHA, so the resblocks
++        # expect [batch, seq, embed].  Older versions use batch_first=False
++        # and expect [seq, batch, embed].  Only permute for the old layout.
++        needs_permute = not getattr(
++            self.model.transformer.resblocks[0].attn, "batch_first", False
++        )
++        if needs_permute:
++            x = x.permute(1, 0, 2)
+         x = self.text_transformer_forward(x, attn_mask=self.model.attn_mask)
+-        x = x.permute(1, 0, 2)
++        if needs_permute:
++            x = x.permute(1, 0, 2)
+         x = self.model.ln_final(x)
+         return x
+