migration: scope subfolder download, keep normalized joints as-is

- download_subfolder: fetch only the target sub-dataset subtree instead of
  enumerating the whole community_dataset_v3 monorepo tree (fixes apparent hang)
- normalized SO gripper (RANGE_0_100) left in native 0..100 frame, matching
  degrees_new datasets, instead of remapping to +/-45deg
- uncalibrated normalized datasets: skip identity value rewrite, keep normalized
  units and flag them APPROXIMATE on the dataset card
- remove --allow-uncalibrated flag and its CANON_IS_CALIBRATED side effect

community_v3_migration/fix_dataset.py

@@ -7,8 +7,8 @@ from pathlib import Path
 import numpy as np
 import pandas as pd
 
+import so_arm_frame
 from classify import classify
-from so_arm_frame import to_degrees
 
 VALUE_COLS = ("observation.state", "action")
 
@@ -23,7 +23,7 @@ def _rewrite_parquet(root: Path, encoding: str) -> None:
         changed = False
         for col in VALUE_COLS:
             if col in df.columns:
-                conv = to_degrees(_stack(df[col].values), encoding, n_joints_per_arm=6)
+                conv = so_arm_frame.to_degrees(_stack(df[col].values), encoding, n_joints_per_arm=6)
                 df[col] = list(conv.astype(np.float32))
                 changed = True
         if changed:
@@ -71,6 +71,13 @@ def fix_dataset_in_place(root) -> dict:
         }.get(enc, "no joint conversion applicable")
         return {**cls, "converted": False,
                 "action": f"structural v2.1->v3.0 only ({reason}); joint values left unchanged"}
+    if enc == "normalized" and not so_arm_frame.CANON_IS_CALIBRATED:
+        # Without per-robot calibration the un-normalization is an identity (placeholder
+        # spans == 100), so rewriting is pointless. Keep the normalized values as-is and let
+        # the dataset card flag them APPROXIMATE instead.
+        return {**cls, "converted": False,
+                "action": "structural v2.1->v3.0 only; joint values kept in normalized units "
+                          "(-100..100 / 0..100), NOT converted to degrees (uncalibrated -> APPROXIMATE)"}
     # drop stray files that would otherwise be uploaded
     for junk in (root / "meta").glob("info.json.bak"):
         junk.unlink()

community_v3_migration/run_migration.py

@@ -7,12 +7,13 @@ result under the same path into a NEW repo, then delete the local copy. Resumabl
   uv run python run_migration.py --dst-repo HuggingFaceVLA/community_dataset_v3_degrees \
       --work-dir /big/disk/cdv3_work --manifest manifest.csv
 Flags: --only-classify (just write manifest), --no-push (fix+convert locally, keep output,
-       no upload), --folder-name A [B ...] (target specific dataset folders), --limit N,
+       no upload), --folder-name A [B ...] (target specific dataset folders), --limit N.
-       --allow-uncalibrated (accept placeholder CANON ranges).
+Uncalibrated `normalized` datasets keep their normalized joint units (flagged APPROXIMATE on
+the card); paste fitted CANON ranges in so_arm_frame.py to convert them to degrees instead.
 """
 import argparse, csv, json, shutil, sys, traceback
 from pathlib import Path
-from huggingface_hub import HfApi, snapshot_download
+from huggingface_hub import HfApi
 
 import so_arm_frame
 from classify import classify, load_info
@@ -21,6 +22,28 @@ from fix_dataset import fix_dataset_in_place
 SRC_REPO = "HuggingFaceVLA/community_dataset_v3"
 
 
+def download_subfolder(sub: str, work_dir: str, patterns: list[str] | None = None) -> None:
+    """Download only ``SRC_REPO/{sub}/...`` into ``work_dir``.
+
+    ``snapshot_download`` walks the entire repo tree (``list_repo_tree(recursive=True)``
+    with no path scope) before applying ``allow_patterns``. On this 791-dataset monorepo
+    that whole-repo enumeration is pathologically slow and looks like a hang. Listing the
+    scoped ``path_in_repo=sub`` subtree and fetching its files directly avoids it.
+    """
+    from fnmatch import fnmatch
+
+    from huggingface_hub import hf_hub_download
+    from huggingface_hub.hf_api import RepoFile
+
+    api = HfApi()
+    for entry in api.list_repo_tree(SRC_REPO, path_in_repo=sub, repo_type="dataset", recursive=True):
+        if not isinstance(entry, RepoFile):
+            continue
+        if patterns and not any(fnmatch(entry.path, pat) for pat in patterns):
+            continue
+        hf_hub_download(SRC_REPO, filename=entry.path, repo_type="dataset", local_dir=work_dir)
+
+
 def list_datasets(api: HfApi, repo: str) -> list[str]:
     files = api.list_repo_files(repo, repo_type="dataset")
     roots = {p[: -len("/meta/info.json")] for p in files if p.endswith("/meta/info.json")}
@@ -69,7 +92,9 @@ def _write_dataset_card(local: Path, sub: str, result: dict) -> None:
     joint_actions = {
         "degrees_old": "per-joint offsets and axis directions corrected to the post-#777 frame (values stay in degrees)",
         "degrees_new": "already in the post-#777 degrees frame; values unchanged",
-        "normalized": "un-normalized to physical degrees using canonical joint ranges",
+        "normalized": ("un-normalized to physical degrees using calibrated joint ranges"
+                       if converted_degrees else
+                       "left in normalized units (-100..100 joints, 0..100 gripper); NOT converted to degrees"),
         "radians": "left unchanged (already in radians)",
         "unknown": "left unchanged (encoding could not be determined)",
     }
@@ -94,8 +119,9 @@ def _write_dataset_card(local: Path, sub: str, result: dict) -> None:
     else:
         lines += ["- Joint values: not applicable (not an SO-100/101 dataset)"]
     if approx:
-        lines += ["", "> **Note:** normalized (-100..100 / 0..100) joint values were un-normalized "
+        lines += ["", "> **Note:** per-robot calibration was unavailable, so joint state/action were "
-                  "using *placeholder* canonical joint ranges (uncalibrated). These values are APPROXIMATE."]
+                  "left in their original *normalized* units (-100..100 joints, 0..100 gripper) rather "
+                  "than converted to physical degrees. Treat these joint values as APPROXIMATE."]
     if result.get("ambiguous"):
         lines += ["", "> **Note:** joint-encoding detection was flagged ambiguous; conversion used the "
                   "best-guess encoding above and may warrant manual review."]
@@ -134,8 +160,7 @@ def migrate_one(api, dst_repo, sub, work_dir, no_upload) -> dict:
     local = Path(work_dir) / sub
     if local.parent.exists():
         shutil.rmtree(local.parent, ignore_errors=True)  # clean any partial
-    snapshot_download(SRC_REPO, repo_type="dataset", revision="main",
+    download_subfolder(sub, work_dir)
-                      allow_patterns=[f"{sub}/*"], local_dir=work_dir)
 
     info = load_info(local)
     if info.get("codebase_version") != "v2.1":
@@ -191,17 +216,11 @@ def main():
     ap.add_argument("--no-push", action="store_true",
                     help="Fix + convert locally but do NOT upload; the converted v3.0 output is "
                          "kept under --work-dir for inspection instead of being deleted.")
-    ap.add_argument("--allow-uncalibrated", action="store_true",
-                    help="Permit converting 'normalized' (-100..100) datasets using the PLACEHOLDER "
-                         "canonical joint ranges in so_arm_frame.py. Omit this to force running "
-                         "calibrate_canonical_ranges.py first (recommended for a real run).")
     args = ap.parse_args()
     no_upload = args.no_push
     if not no_upload and not args.only_classify and not args.dst_repo:
         ap.error("--dst-repo is required unless --no-push or --only-classify is set.")
 
-    if args.allow_uncalibrated:
-        so_arm_frame.CANON_IS_CALIBRATED = True
     api = HfApi()
     if args.folder_name:
         subs = resolve_folders(api, SRC_REPO, args.folder_name)
@@ -224,8 +243,7 @@ def main():
             try:
                 if args.only_classify:
                     # classify without full download: fetch just the meta/ of this sub
-                    snapshot_download(SRC_REPO, repo_type="dataset",
+                    download_subfolder(sub, args.work_dir, patterns=[f"{sub}/meta/*"])
-                                      allow_patterns=[f"{sub}/meta/*"], local_dir=args.work_dir)
                     row = {"root": sub, **classify(Path(args.work_dir) / sub)}
                     shutil.rmtree(Path(args.work_dir) / sub.split("/")[0], ignore_errors=True)
                 elif not no_upload and already_done(api, args.dst_repo, sub, dst_files):

community_v3_migration/slurm_migrate.py

@@ -14,7 +14,7 @@ Example (numeric smoke test on one namespace, no SLURM):
     python slurm_migrate.py --slurm 0 --workers 1 \
         --dst-repo HuggingFaceVLA/community_dataset_v3_degrees \
         --work-dir ./cdv3_work --manifest-dir ./cdv3_manifests \
-        --folder-name Beegbrain --allow-uncalibrated
+        --folder-name Beegbrain
 
 Full run on the cluster:
     python slurm_migrate.py \
@@ -24,7 +24,6 @@ Full run on the cluster:
         --logs-dir /fsx/$USER/logs/cdv3_migrate \
         --workers 64 --partition hopper-cpu --qos normal \
         --cpus-per-task 4 --mem-per-cpu 4G \
-        --allow-uncalibrated \
         --env-command "source /fsx/$USER/venvs/lerobot/bin/activate; export HF_TOKEN=<token>"
 
 IMPORTANT: workers must reach the internet (HF download + upload) and have a write-scoped
@@ -54,7 +53,6 @@ class MigrateShard(PipelineStep):
         migration_dir,
         no_push=False,
         only_classify=False,
-        allow_uncalibrated=False,
     ):
         super().__init__()
         self.subs = subs
@@ -64,7 +62,6 @@ class MigrateShard(PipelineStep):
         self.migration_dir = migration_dir
         self.no_push = no_push
         self.only_classify = only_classify
-        self.allow_uncalibrated = allow_uncalibrated
 
     def run(self, data=None, rank: int = 0, world_size: int = 1):
         # Pickled onto the worker: keep self-contained. The migration package dir must be on
@@ -80,16 +77,13 @@ class MigrateShard(PipelineStep):
         if self.migration_dir not in sys.path:
             sys.path.insert(0, self.migration_dir)
 
-        import so_arm_frame
         from classify import classify
         from huggingface_hub import HfApi
-        from run_migration import SRC_REPO, already_done, migrate_one
+        from run_migration import already_done, download_subfolder, migrate_one
 
         from lerobot.utils.utils import init_logging
 
         init_logging()
-        if self.allow_uncalibrated:
-            so_arm_frame.CANON_IS_CALIBRATED = True
 
         my_subs = self.subs[rank::world_size]
         if not my_subs:
@@ -122,14 +116,7 @@ class MigrateShard(PipelineStep):
             for i, sub in enumerate(my_subs):
                 try:
                     if self.only_classify:
-                        from huggingface_hub import snapshot_download
+                        download_subfolder(sub, work_dir, patterns=[f"{sub}/meta/*"])
-
-                        snapshot_download(
-                            SRC_REPO,
-                            repo_type="dataset",
-                            allow_patterns=[f"{sub}/meta/*"],
-                            local_dir=work_dir,
-                        )
                         row = {"root": sub, **classify(Path(work_dir) / sub)}
                         shutil.rmtree(Path(work_dir) / sub.split("/")[0], ignore_errors=True)
                     elif not self.no_push and already_done(api, self.dst_repo, sub, dst_files):
@@ -205,7 +192,6 @@ def main():
     p.add_argument("--limit", type=int, default=None, help="Only the first N sub-datasets (ignored with --folder-name).")
     p.add_argument("--only-classify", action="store_true", help="Only classify + write manifest; no convert/upload.")
     p.add_argument("--no-push", action="store_true", help="Fix + convert locally, keep output, do not upload.")
-    p.add_argument("--allow-uncalibrated", action="store_true", help="Accept placeholder CANON ranges.")
     args = p.parse_args()
 
     if not args.no_push and not args.only_classify and not args.dst_repo:
@@ -236,7 +222,6 @@ def main():
                 MIGRATION_DIR,
                 no_push=args.no_push,
                 only_classify=args.only_classify,
-                allow_uncalibrated=args.allow_uncalibrated,
             )
         ],
         logs_dir=args.logs_dir,

community_v3_migration/so_arm_frame.py

@@ -8,8 +8,9 @@ Two calibration-free branches + one that needs an assumed canonical range:
   * degrees_new  (`*_follower` recorded with use_degrees=True, not saturated): already
                  degrees. EXACT.
   * normalized   (`*_follower`, -100..100 joints / 0..100 gripper, saturates at bounds):
-                 already mid-range-zero; only the SCALE is missing (per-robot range_min/max
+                 5 arm joints are mid-range-zero, only the SCALE is missing (per-robot
-                 is not stored) -> use assumed canonical per-joint spans below. APPROXIMATE.
+                 range_min/max not stored) -> use assumed canonical spans below. APPROXIMATE.
+                 The gripper (0..100) is kept in its native frame, matching degrees_new.
   * radians      -> untouched.
 
 Joint order per arm: shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper.
@@ -23,13 +24,12 @@ JOINT_ORDER = ["shoulder_pan", "shoulder_lift", "elbow_flex", "wrist_flex", "wri
 SIGNS = np.array([1.0, -1.0, 1.0, 1.0, 1.0, 1.0], dtype=np.float64)
 OFFSETS_DEG = np.array([0.0, 90.0, 90.0, 0.0, 0.0, 0.0], dtype=np.float64)
 
-# --- Canonical per-joint spans (DEGREES) used ONLY to invert the -100..100 / 0..100
+# --- Canonical per-joint spans (DEGREES) used ONLY to invert the -100..100 normalization of
-#     normalization when per-robot calibration is unavailable. joints 0..4 (RANGE_M100_100):
+#     the 5 arm joints (RANGE_M100_100) when per-robot calibration is unavailable: normalized
-#     normalized +/-100 -> +/-HALF_RANGE. gripper (RANGE_0_100): 0..100 -> centered at 50,
+#     +/-100 -> +/-HALF_RANGE. The gripper (RANGE_0_100) is left in its native 0..100 frame in
-#     span FULL_RANGE. THESE ARE PLACEHOLDERS — run calibrate_canonical_ranges.py and paste
+#     every SO dataset, so it needs no canonical span. THESE ARE PLACEHOLDERS — run
-#     the fitted values here before a production run. ---
+#     calibrate_canonical_ranges.py and paste the fitted values here before a production run. ---
 CANON_HALF_RANGE_DEG = np.array([100.0, 100.0, 100.0, 100.0, 100.0], dtype=np.float64)  # 5 arm joints
-CANON_GRIPPER_FULL_RANGE_DEG = 90.0
 CANON_IS_CALIBRATED = False  # flipped to True once you paste fitted values
 
 
@@ -43,9 +43,10 @@ def _convert_arm(x: np.ndarray, encoding: str) -> np.ndarray:
     if encoding == "degrees_new":
         return x
     if encoding == "normalized":
-        new_deg = np.empty_like(x)
+        new_deg = np.array(x, dtype=np.float64)
         new_deg[..., :5] = (x[..., :5] / 100.0) * CANON_HALF_RANGE_DEG
-        new_deg[..., 5] = (x[..., 5] / 100.0 - 0.5) * CANON_GRIPPER_FULL_RANGE_DEG
+        # gripper is RANGE_0_100 in every SO dataset (including use_degrees=True / degrees_new),
+        # so it is already frame-consistent and must be left untouched, not remapped to +/-deg.
         return new_deg
     raise ValueError(f"unknown encoding: {encoding!r}")
 
@@ -59,7 +60,7 @@ def to_degrees(arr, encoding: str, n_joints_per_arm: int = 6) -> np.ndarray:
     if encoding == "normalized" and not CANON_IS_CALIBRATED:
         raise RuntimeError(
             "CANON ranges are placeholders. Run calibrate_canonical_ranges.py and set "
-            "CANON_* + CANON_IS_CALIBRATED=True, or pass --allow-uncalibrated to accept them."
+            "CANON_* + CANON_IS_CALIBRATED=True before converting 'normalized' datasets to degrees."
         )
     out = np.empty_like(arr)
     for a in range(d // n_joints_per_arm):