Merge remote-tracking branch 'origin/main' into klin/5090-test-scripts

Author: kevin314

.agents/skills/add-model-01-prep/scripts/clone_reference_repo.py

@@ -10,9 +10,7 @@
 
 
 def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(
-        description="Clone a reference repo for FastVideo parity tests."
-    )
+    parser = argparse.ArgumentParser(description="Clone a reference repo for FastVideo parity tests.")
     parser.add_argument("repo_url", help="Official reference repository URL")
     parser.add_argument("target_dir", help="Directory to clone into")
     parser.add_argument("--branch", help="Branch or tag to clone")
@@ -62,9 +60,7 @@ def gitignore_entry_for(target: Path) -> str:
     try:
         relative = resolved.relative_to(root)
     except ValueError as exc:
-        raise ValueError(
-            "--update-gitignore requires target_dir to be under the current directory"
-        ) from exc
+        raise ValueError("--update-gitignore requires target_dir to be under the current directory") from exc
 
     text = relative.as_posix().rstrip("/")
     return "/" + text + "/"

.agents/skills/add-model-01-prep/scripts/download_hf_weights.py

@@ -8,14 +8,12 @@
 import sys
 from pathlib import Path
 
-
 HF_TOKEN_ENV_KEYS = ("HF_TOKEN", "HUGGINGFACE_HUB_TOKEN", "HF_API_KEY")
 
 
 def parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(
-        description="Download a HF model snapshot or selected files into a local directory."
-    )
+        description="Download a HF model snapshot or selected files into a local directory.")
     parser.add_argument("repo_id", help="HF repo id, for example Org/Model")
     parser.add_argument("local_dir", help="Destination directory")
     parser.add_argument("--repo-type", default="model", help="HF repo type (default: model)")

.agents/skills/add-model-01-prep/scripts/inspect_hf_layout.py

@@ -10,7 +10,6 @@
 from pathlib import Path
 from typing import Any
 
-
 HF_TOKEN_ENV_KEYS = ("HF_TOKEN", "HUGGINGFACE_HUB_TOKEN", "HF_API_KEY")
 RAW_WEIGHT_SUFFIXES = (".safetensors", ".pt", ".pth", ".ckpt", ".bin")
 KNOWN_COMPONENTS = {
@@ -34,8 +33,7 @@
 
 def parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(
-        description="Classify a HF repo or local directory as Diffusers, raw, custom, or unknown."
-    )
+        description="Classify a HF repo or local directory as Diffusers, raw, custom, or unknown.")
     parser.add_argument("source", help="HF repo id or local weights directory")
     parser.add_argument("--repo-type", default="model", help="HF repo type (default: model)")
     parser.add_argument("--revision", help="HF revision to inspect")
@@ -94,14 +92,12 @@ def load_remote_files(
 ) -> list[str]:
     from huggingface_hub import list_repo_files
 
-    return sorted(
-        list_repo_files(
-            repo_id,
-            repo_type=repo_type,
-            revision=revision,
-            token=token,
-        )
-    )
+    return sorted(list_repo_files(
+        repo_id,
+        repo_type=repo_type,
+        revision=revision,
+        token=token,
+    ))
 
 
 def load_remote_model_index(
@@ -215,24 +211,24 @@ def build_result(args: argparse.Namespace) -> dict[str, Any]:
         "components_seen": components,
         "file_count": len(files),
         "file_scan_truncated": truncated,
-        "files_sample": files[: args.sample_limit],
+        "files_sample": files[:args.sample_limit],
     }
 
 
 def print_human(result: dict[str, Any]) -> None:
     for key in (
-        "source",
-        "source_kind",
-        "repo_type",
-        "revision",
-        "token_env",
-        "source_layout",
-        "needs_conversion",
-        "model_index_class",
-        "model_index_diffusers_version",
-        "model_index_error",
-        "file_count",
-        "file_scan_truncated",
+            "source",
+            "source_kind",
+            "repo_type",
+            "revision",
+            "token_env",
+            "source_layout",
+            "needs_conversion",
+            "model_index_class",
+            "model_index_diffusers_version",
+            "model_index_error",
+            "file_count",
+            "file_scan_truncated",
     ):
         value = result.get(key)
         if value is not None:

.agents/skills/add-model-02-parity/templates/component_parity_test.py

@@ -18,7 +18,6 @@
 import torch
 from torch.testing import assert_close
 
-
 os.environ.setdefault("MASTER_ADDR", "localhost")
 os.environ.setdefault("MASTER_PORT", "29519")
 os.environ.setdefault("DISABLE_SP", "1")
@@ -35,15 +34,10 @@
 FASTVIDEO_MODEL_MODULE = "fastvideo.models.<bucket>.<module>"  # TODO.
 FASTVIDEO_MODEL_CLASS = "<FastVideoModel>"  # TODO.
 
-OFFICIAL_REF_DIR = Path(
-    os.getenv("<FAMILY_UPPER>_OFFICIAL_REF_DIR", REPO_ROOT / "<ReferenceDir>")
-)
-LOCAL_WEIGHTS_DIR = Path(
-    os.getenv("<FAMILY_UPPER>_LOCAL_WEIGHTS_DIR", REPO_ROOT / "official_weights" / FAMILY)
-)
-CONVERTED_WEIGHTS_DIR = Path(
-    os.getenv("<FAMILY_UPPER>_CONVERTED_WEIGHTS_DIR", REPO_ROOT / "converted_weights" / FAMILY)
-)
+OFFICIAL_REF_DIR = Path(os.getenv("<FAMILY_UPPER>_OFFICIAL_REF_DIR", REPO_ROOT / "<ReferenceDir>"))
+LOCAL_WEIGHTS_DIR = Path(os.getenv("<FAMILY_UPPER>_LOCAL_WEIGHTS_DIR", REPO_ROOT / "official_weights" / FAMILY))
+CONVERTED_WEIGHTS_DIR = Path(os.getenv("<FAMILY_UPPER>_CONVERTED_WEIGHTS_DIR",
+                                       REPO_ROOT / "converted_weights" / FAMILY))
 
 
 def _resolve_hf_token() -> str | None:
@@ -99,18 +93,14 @@ def _load_official_model(device: torch.device, dtype: torch.dtype) -> torch.nn.M
     model = OfficialClass()  # TODO: pass official config kwargs.
     state_dict = {}  # TODO: load official state dict from LOCAL_WEIGHTS_DIR.
     missing, unexpected = model.load_state_dict(state_dict, strict=True)
-    assert not missing and not unexpected, (
-        f"official load mismatch missing={missing[:5]} unexpected={unexpected[:5]}"
-    )
+    assert not missing and not unexpected, (f"official load mismatch missing={missing[:5]} unexpected={unexpected[:5]}")
     return model.to(device=device, dtype=dtype).eval()
 
 
 def _load_fastvideo_model(device: torch.device, dtype: torch.dtype) -> torch.nn.Module:
     """Load the FastVideo component with the same tensor content."""
     if not CONVERTED_WEIGHTS_DIR.exists() and not LOCAL_WEIGHTS_DIR.exists():
-        pytest.skip(
-            f"No FastVideo loadable weights: {CONVERTED_WEIGHTS_DIR} or {LOCAL_WEIGHTS_DIR}"
-        )
+        pytest.skip(f"No FastVideo loadable weights: {CONVERTED_WEIGHTS_DIR} or {LOCAL_WEIGHTS_DIR}")
 
     # TODO: replace with the bucket-specific FastVideo config/class/loader.
     # DiT examples:
@@ -127,8 +117,7 @@ def _load_fastvideo_model(device: torch.device, dtype: torch.dtype) -> torch.nn.
     state_dict = {}  # TODO: load converted or directly mapped state dict.
     missing, unexpected = model.load_state_dict(state_dict, strict=True)
     assert not missing and not unexpected, (
-        f"FastVideo load mismatch missing={missing[:5]} unexpected={unexpected[:5]}"
-    )
+        f"FastVideo load mismatch missing={missing[:5]} unexpected={unexpected[:5]}")
     return model.to(device=device, dtype=dtype).eval()
 
 
@@ -187,11 +176,9 @@ def test_component_parity():
 
     assert official_out.shape == fastvideo_out.shape
     diff = (official_out - fastvideo_out).abs()
-    print(
-        f"official abs_mean={official_out.abs().mean().item():.6f} "
-        f"fastvideo abs_mean={fastvideo_out.abs().mean().item():.6f} "
-        f"diff_max={diff.max().item():.6f} diff_mean={diff.mean().item():.6f}"
-    )
+    print(f"official abs_mean={official_out.abs().mean().item():.6f} "
+          f"fastvideo abs_mean={fastvideo_out.abs().mean().item():.6f} "
+          f"diff_max={diff.max().item():.6f} diff_mean={diff.mean().item():.6f}")
 
     # TODO: pick tolerance by scope:
     # - single block / same kernel: 1e-4

.agents/skills/add-model-07-conversion/templates/family_to_diffusers.py

@@ -27,7 +27,6 @@
 except ImportError:  # pragma: no cover - optional local conversion dependency
     snapshot_download = None
 
-
 # TODO: fill with authoritative component prefixes for monolithic checkpoints.
 # Example: {"model.model.": "transformer", "pretransform.model.": "vae"}
 COMPONENT_PREFIXES: dict[str, str] = {}
@@ -47,10 +46,7 @@
 
 
 def _hf_token() -> str | None:
-    return (
-        os.environ.get("HF_TOKEN") or os.environ.get("HUGGINGFACE_HUB_TOKEN")
-        or os.environ.get("HF_API_KEY")
-    )
+    return (os.environ.get("HF_TOKEN") or os.environ.get("HUGGINGFACE_HUB_TOKEN") or os.environ.get("HF_API_KEY"))
 
 
 def resolve_src(src: str, revision: str | None) -> Path:
@@ -95,11 +91,10 @@ def apply_mapping(key: str) -> str | None:
     return key
 
 
-def split_monolithic(
-    state: dict[str, torch.Tensor],
-) -> dict[str, OrderedDict[str, torch.Tensor]]:
+def split_monolithic(state: dict[str, torch.Tensor], ) -> dict[str, OrderedDict[str, torch.Tensor]]:
     components: dict[str, OrderedDict[str, torch.Tensor]] = {
-        name: OrderedDict() for name in set(COMPONENT_PREFIXES.values())
+        name: OrderedDict()
+        for name in set(COMPONENT_PREFIXES.values())
     }
     intentionally_skipped: list[str] = []
     unowned: list[str] = []
@@ -117,10 +112,8 @@ def split_monolithic(
             unowned.append(key)
     if unowned:
         sample = ", ".join(unowned[:10])
-        raise ValueError(
-            f"Unowned monolithic keys: {len(unowned)}. "
-            f"Add COMPONENT_PREFIXES or SKIP_PATTERNS entries. Sample: {sample}"
-        )
+        raise ValueError(f"Unowned monolithic keys: {len(unowned)}. "
+                         f"Add COMPONENT_PREFIXES or SKIP_PATTERNS entries. Sample: {sample}")
     if intentionally_skipped:
         print(f"Intentionally skipped {len(intentionally_skipped)} keys")
     return {name: weights for name, weights in components.items() if weights}
@@ -143,8 +136,12 @@ def build_component_configs(_src_dir: Path) -> dict[str, dict[str, Any]]:
     # TODO: emit config content accepted by FastVideo loaders. Most components use
     # config.json; schedulers use scheduler_config.json.
     return {
-        "transformer": {"_class_name": "<FastVideoTransformerClass>"},
-        "vae": {"_class_name": "<FastVideoVAEClass>"},
+        "transformer": {
+            "_class_name": "<FastVideoTransformerClass>"
+        },
+        "vae": {
+            "_class_name": "<FastVideoVAEClass>"
+        },
     }
 
 
@@ -177,19 +174,13 @@ def build_model_index(
     }
     if revision:
         index["_fastvideo_converted_revision"] = revision
-    return {
-        key: value
-        for key, value in index.items()
-        if key.startswith("_") or key in available_components
-    }
+    return {key: value for key, value in index.items() if key.startswith("_") or key in available_components}
 
 
 def validate_component_configs(configs: dict[str, dict[str, Any]]) -> None:
     # TODO: instantiate each FastVideo config and call update_model_arch(...) or
     # update_model_config(...) with this JSON so unknown emitted keys fail here.
-    placeholder_configs = [
-        name for name, config in configs.items() if "<" in json.dumps(config)
-    ]
+    placeholder_configs = [name for name, config in configs.items() if "<" in json.dumps(config)]
     if placeholder_configs:
         raise ValueError(f"Replace config placeholders for: {placeholder_configs}")
 
@@ -201,9 +192,7 @@ def verify_conversion(
     del dst_dir, components
     # TODO: load each emitted stateful component through its production loader and
     # assert strict load, or document exact allowed missing/unexpected keys.
-    raise NotImplementedError(
-        "Implement production config validation and strict-load checks"
-    )
+    raise NotImplementedError("Implement production config validation and strict-load checks")
 
 
 def write_component(
@@ -216,9 +205,7 @@ def write_component(
     if component_dir.exists() and any(component_dir.iterdir()):
         shutil.rmtree(component_dir)
     component_dir.mkdir(parents=True, exist_ok=True)
-    save_file(
-        dict(state), str(component_dir / "diffusion_pytorch_model.safetensors")
-    )
+    save_file(dict(state), str(component_dir / "diffusion_pytorch_model.safetensors"))
     if config is not None:
         config_path = component_dir / config_filename(name)
         with config_path.open("w", encoding="utf-8") as f:
@@ -261,19 +248,15 @@ def convert(
 
     if layout in {"monolithic", "raw_official"}:
         # TODO: replace model.safetensors with the official monolithic file name.
-        components = split_monolithic(
-            load_checkpoint(default_monolithic_checkpoint(src_path))
-        )
+        components = split_monolithic(load_checkpoint(default_monolithic_checkpoint(src_path)))
     elif layout in {"separate_components", "mixed"}:
         if not src_path.is_dir():
             raise ValueError(f"{layout} layout requires a source directory: {src_path}")
         components = load_separate_components(src_path)
     else:
         raise ValueError(f"Unsupported template layout: {layout}")
 
-    copied = (
-        copy_passthrough(src_path, dst_dir) if src_path.is_dir() else []
-    )
+    copied = (copy_passthrough(src_path, dst_dir) if src_path.is_dir() else [])
     configs = build_component_configs(src_path if src_path.is_dir() else src_path.parent)
     validate_component_configs(configs)
     for name, state in components.items():
@@ -289,9 +272,7 @@ def convert(
 
 def main() -> None:
     parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument(
-        "--src", required=True, help="HF repo id, local dir, or checkpoint path"
-    )
+    parser.add_argument("--src", required=True, help="HF repo id, local dir, or checkpoint path")
     parser.add_argument("--revision", help="HF branch, tag, or commit for repo sources")
     parser.add_argument(
         "--dst",