feat: Support FastVideo for Video Generation Models

.gitignore

@@ -83,3 +83,4 @@ CLAUDE.md
 .worktrees/
 Bagel/
 MMaDA/
+.codex

lmms_eval/api/task.py

@@ -1036,8 +1036,11 @@ def _download_from_youtube(path):
                     force_unzip = dataset_kwargs.get("force_unzip", False)
                     revision = dataset_kwargs.get("revision", "main")
                     create_link = dataset_kwargs.get("create_link", False)
-                    # If the user already has a cache dir, we skip download the zip files
-                    if not os.path.exists(cache_dir):
+                    cache_path = None
+                    # If the user already has a cache dir, we skip downloading archives.
+                    # Tasks that set create_link need the snapshot path even when the
+                    # cache dir already exists as a symlink from a previous run.
+                    if not os.path.exists(cache_dir) or (create_link and os.path.islink(cache_dir)):
                         cache_path = snapshot_download(repo_id=self.DATASET_PATH, revision=revision, repo_type="dataset", force_download=force_download, etag_timeout=60)
                         zip_files = glob(os.path.join(cache_path, "**/*.zip"), recursive=True)
                         tar_files = glob(os.path.join(cache_path, "**/*.tar*"), recursive=True)
@@ -1106,7 +1109,7 @@ def concat_tar_parts(tar_parts, output_tar):
                                 untar_video_data(output_tar)
 
                     # Link cache_path to cache_dir if needed.
-                    if create_link:
+                    if create_link and cache_path is not None:
                         if not os.path.exists(cache_dir) or os.path.islink(cache_dir):
                             if os.path.islink(cache_dir):
                                 os.remove(cache_dir)

lmms_eval/models/__init__.py

@@ -114,6 +114,7 @@
 
 AVAILABLE_CHAT_TEMPLATE_MODELS = {
     "bagel_lmms_engine": "BagelLmmsEngine",
+    "fastvideo": "FastVideo",
     "internvl_hf": "InternVLHf",
     "llava_hf": "LlavaHf",
     "nanovlm": "NanoVLM",