refactor(streaming): exact coverage is the only pool mode

Drop the with-replacement sampled path: delete run_pool_stream_simulation
and the --coverage flag; the streaming keep-up sim always uses
run_exact_coverage_stream (ExactCoveragePool), so every frame of every
episode is decoded exactly once per epoch. --pool-samples-per-episode is
kept as a deprecated no-op so existing commands still parse (exact mode
evicts an episode only when all its frames are emitted, so a turnover
cadence no longer applies).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

pyproject.toml

@@ -355,6 +355,8 @@ explicit = true
 [tool.uv.sources]
 torch = [{ index = "pytorch-cu128", marker = "sys_platform == 'linux'" }]
 torchvision = [{ index = "pytorch-cu128", marker = "sys_platform == 'linux'" }]
+huggingface-hub = { git = "https://github.com/huggingface/huggingface_hub.git", branch = "feat/hffs-cache-cdn-range-reads" }
+datasets = { git = "https://github.com/huggingface/datasets.git", branch = "main" }
 
 [tool.setuptools.package-data]
 lerobot = ["envs/*.json", "annotations/steerable_pipeline/prompts/*.txt"]
@@ -421,6 +423,7 @@ exclude_dirs = [
 skips = ["B101", "B311", "B404", "B603", "B615"]
 
 [tool.typos]
+default.extend-words = { trak = "trak" }
 default.extend-ignore-re = [
     "(?Rm)^.*(#|//)\\s*spellchecker:disable-line$",                      # spellchecker:disable-line
     "(?s)(#|//)\\s*spellchecker:off.*?\\n\\s*(#|//)\\s*spellchecker:on", # spellchecker:<on|off>

scripts/build_mp4_sidecar.py

@@ -0,0 +1,93 @@
+#!/usr/bin/env python
+
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+
+from __future__ import annotations
+
+import argparse
+import time
+from pathlib import Path
+
+import fsspec
+
+from lerobot.datasets.dataset_metadata import LeRobotDatasetMetadata
+from lerobot.datasets.episode_video_streaming import EpisodeVideoManifest, assert_hf_hub_range_cache_branch
+
+DEFAULT_REPO = "allenai/MolmoAct2-BimanualYAM-Dataset"
+DEFAULT_REVISION = "e9f21ae15074330839f2ac25ed4b49d76dfa1f9c"
+DEFAULT_DATA_ROOT = "hf://buckets/pepijn223/MolmoAct2-BimanualYAM-Dataset-bucket"
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description="Build a reusable MP4 byte-index sidecar for streaming.")
+    parser.add_argument("--repo-id", default=DEFAULT_REPO)
+    parser.add_argument("--revision", default=DEFAULT_REVISION)
+    parser.add_argument("--data-root", default=DEFAULT_DATA_ROOT)
+    parser.add_argument("--output", required=True)
+    parser.add_argument("--episodes", type=int, default=None)
+    parser.add_argument("--workers", type=int, default=8)
+    parser.add_argument("--range-backend", choices=("fsspec", "native-http"), default="native-http")
+    parser.add_argument("--max-probe-mb", type=int, default=64)
+    parser.add_argument(
+        "--no-push", action="store_true", help="Do not upload the sidecar to data_root/meta/mp4-sidecars."
+    )
+    parser.add_argument("--no-hub-branch-assert", action="store_true")
+    return parser.parse_args()
+
+
+def push_sidecar(local_path: str, data_root: str) -> list[str]:
+    if not data_root.startswith("hf://"):
+        return []
+
+    local = Path(local_path)
+    fs = fsspec.filesystem("hf")
+    remote_dir = f"{data_root.rstrip('/')}/meta/mp4-sidecars"
+    remote_paths = [f"{remote_dir}/{local.name}"]
+
+    for remote in remote_paths:
+        fs.put(str(local), remote)
+    return remote_paths
+
+
+def main() -> None:
+    args = parse_args()
+    if args.data_root.startswith("hf://") and not args.no_hub_branch_assert:
+        assert_hf_hub_range_cache_branch()
+
+    meta = LeRobotDatasetMetadata(args.repo_id, revision=args.revision)
+    meta.ensure_readable()
+    total = (
+        int(meta.total_episodes) if args.episodes is None else min(args.episodes, int(meta.total_episodes))
+    )
+    rel_paths = sorted(
+        {str(meta.get_video_file_path(ep_idx, key)) for ep_idx in range(total) for key in meta.video_keys}
+    )
+
+    start = time.perf_counter()
+    EpisodeVideoManifest.write_file_sidecar(
+        args.output,
+        rel_paths,
+        args.data_root,
+        range_backend=args.range_backend,
+        workers=args.workers,
+        max_probe_bytes=args.max_probe_mb * 1024 * 1024,
+    )
+    elapsed = time.perf_counter() - start
+    print(f"wrote {args.output}")
+    print(f"episodes={total} files={len(rel_paths)} elapsed_s={elapsed:.2f}")
+    if args.no_push:
+        print("push_skipped: --no-push")
+    else:
+        pushed = push_sidecar(args.output, args.data_root)
+        for remote in pushed:
+            print(f"pushed {remote}")
+
+
+if __name__ == "__main__":
+    main()

scripts/summarize_episode_pool_bench.py

@@ -0,0 +1,65 @@
+#!/usr/bin/env python
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description="Summarize distributed episode pool benchmark JSON files.")
+    parser.add_argument("summaries", nargs="+", help="Rank summary JSON files.")
+    return parser.parse_args()
+
+
+def _load(path: str) -> dict:
+    return json.loads(Path(path).read_text())
+
+
+def _fmt(value: float) -> str:
+    return f"{value:.1f}"
+
+
+def main() -> None:
+    args = parse_args()
+    rows = [_load(path) for path in args.summaries]
+    rows.sort(key=lambda row: int(row.get("distributed_shard_index", 0)))
+    total_bytes = sum(float(row.get("fetch_bytes", 0.0)) for row in rows)
+    max_fetch_s = max(float(row.get("fetch_s", 0.0)) for row in rows)
+    aggregate_mib_s = total_bytes / max_fetch_s / 1024**2 if max_fetch_s > 0 else float("inf")
+    summed_rank_mib_s = sum(float(row.get("fetch_mib_s", 0.0)) for row in rows)
+    total_decode_samples_s = sum(float(row.get("pool_decode_training_samples_s", 0.0)) for row in rows)
+    total_stream_samples_s = sum(float(row.get("pool_stream_actual_samples_s", 0.0)) for row in rows)
+    kept_up = all(bool(row.get("pool_stream_kept_up", 0.0)) for row in rows)
+
+    print("| Aggregate | value |")
+    print("|---|---:|")
+    print(f"| ranks | {len(rows)} |")
+    print(f"| total fetched GiB | {total_bytes / 1024**3:.2f} |")
+    print(f"| aggregate fetch MiB/s | {_fmt(aggregate_mib_s)} |")
+    print(f"| summed rank fetch MiB/s | {_fmt(summed_rank_mib_s)} |")
+    if total_decode_samples_s:
+        print(f"| aggregate resident decode samples/s | {_fmt(total_decode_samples_s)} |")
+    if total_stream_samples_s:
+        print(f"| aggregate stream samples/s | {_fmt(total_stream_samples_s)} |")
+        print(f"| all ranks kept up | {'yes' if kept_up else 'no'} |")
+
+    print()
+    print("| Rank | host | fetch MiB/s | fetch s | GiB | decode samples/s | stream samples/s | kept up |")
+    print("|---:|---|---:|---:|---:|---:|---:|---|")
+    for row in rows:
+        rank = int(row.get("distributed_shard_index", 0))
+        print(
+            f"| {rank} | {row.get('hostname', '')} | "
+            f"{_fmt(float(row.get('fetch_mib_s', 0.0)))} | "
+            f"{_fmt(float(row.get('fetch_s', 0.0)))} | "
+            f"{float(row.get('fetch_gib', 0.0)):.2f} | "
+            f"{_fmt(float(row.get('pool_decode_training_samples_s', 0.0)))} | "
+            f"{_fmt(float(row.get('pool_stream_actual_samples_s', 0.0)))} | "
+            f"{'yes' if row.get('pool_stream_kept_up', 0.0) else 'no'} |"
+        )
+
+
+if __name__ == "__main__":
+    main()

src/lerobot/datasets/mp4.py

@@ -0,0 +1,666 @@
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+
+from __future__ import annotations
+
+import struct
+from collections.abc import Callable, Iterable
+from dataclasses import dataclass
+
+import numpy as np
+
+
+@dataclass(frozen=True)
+class Box:
+    type: bytes
+    start: int
+    header_size: int
+    end: int
+
+    @property
+    def payload_start(self) -> int:
+        return self.start + self.header_size
+
+    @property
+    def size(self) -> int:
+        return self.end - self.start
+
+
+@dataclass(frozen=True)
+class Mp4SampleSlice:
+    sample_lo: int
+    sample_hi: int
+    byte_offset: int
+    byte_length: int
+    source_start_pts: float
+
+
+@dataclass(frozen=True)
+class Mp4Index:
+    file_path: str
+    file_size: int
+    ftyp: bytes
+    moov_offset: int
+    mdat_offset: int
+    mdat_payload_offset: int
+    mdat_payload_size: int
+    faststart: bool
+    codec: str
+    timescale: int
+    duration: int
+    track_id: int
+    width: int
+    height: int
+    stsd_body: bytes
+    sample_pts: np.ndarray
+    sample_durations: np.ndarray
+    sample_sizes: np.ndarray
+    sample_offsets: np.ndarray
+    sync_samples: np.ndarray
+
+    def sample_slice(
+        self,
+        from_ts: float,
+        to_ts: float,
+        *,
+        keyframe_pad_s: float = 0.1,
+        keyframe_pad_fraction: float = 0.05,
+        file_size: int | None = None,
+    ) -> Mp4SampleSlice:
+        if to_ts < from_ts:
+            raise ValueError(f"Invalid timestamp span: {from_ts=} {to_ts=}")
+        if len(self.sample_pts) == 0:
+            raise ValueError(f"{self.file_path} contains no indexed samples")
+
+        pad = max(keyframe_pad_s, (to_ts - from_ts) * keyframe_pad_fraction)
+        lo_ts = max(0.0, from_ts - pad)
+        hi_ts = to_ts + pad
+        lo = int(np.searchsorted(self.sample_pts, lo_ts, side="left"))
+        hi = int(np.searchsorted(self.sample_pts, hi_ts, side="right")) - 1
+        lo = min(max(lo, 0), len(self.sample_pts) - 1)
+        hi = min(max(hi, lo), len(self.sample_pts) - 1)
+
+        if len(self.sync_samples):
+            prev_sync = self.sync_samples[self.sync_samples <= lo]
+            if len(prev_sync):
+                lo = int(prev_sync[-1])
+            else:
+                lo = int(self.sync_samples[0])
+                if lo > hi:
+                    hi = lo
+
+        offsets = self.sample_offsets[lo : hi + 1]
+        sizes = self.sample_sizes[lo : hi + 1]
+        slice_lo = int(offsets.min())
+        slice_hi = int((offsets + sizes).max())
+        if file_size is not None:
+            slice_hi = min(slice_hi, int(file_size))
+        return Mp4SampleSlice(
+            sample_lo=lo,
+            sample_hi=hi,
+            byte_offset=slice_lo,
+            byte_length=slice_hi - slice_lo,
+            source_start_pts=float(self.sample_pts[lo]),
+        )
+
+    def to_dict(self) -> dict:
+        return {
+            "file_path": self.file_path,
+            "file_size": self.file_size,
+            "ftyp": self.ftyp.hex(),
+            "moov_offset": self.moov_offset,
+            "mdat_offset": self.mdat_offset,
+            "mdat_payload_offset": self.mdat_payload_offset,
+            "mdat_payload_size": self.mdat_payload_size,
+            "faststart": self.faststart,
+            "codec": self.codec,
+            "timescale": self.timescale,
+            "duration": self.duration,
+            "track_id": self.track_id,
+            "width": self.width,
+            "height": self.height,
+            "stsd_body": self.stsd_body.hex(),
+        }
+
+    @classmethod
+    def from_dict(cls, data: dict, arrays: dict[str, np.ndarray]) -> Mp4Index:
+        return cls(
+            file_path=data["file_path"],
+            file_size=int(data["file_size"]),
+            ftyp=bytes.fromhex(data["ftyp"]),
+            moov_offset=int(data["moov_offset"]),
+            mdat_offset=int(data["mdat_offset"]),
+            mdat_payload_offset=int(data["mdat_payload_offset"]),
+            mdat_payload_size=int(data["mdat_payload_size"]),
+            faststart=bool(data["faststart"]),
+            codec=data["codec"],
+            timescale=int(data["timescale"]),
+            duration=int(data["duration"]),
+            track_id=int(data["track_id"]),
+            width=int(data["width"]),
+            height=int(data["height"]),
+            stsd_body=bytes.fromhex(data["stsd_body"]),
+            sample_pts=arrays["sample_pts"],
+            sample_durations=arrays["sample_durations"],
+            sample_sizes=arrays["sample_sizes"],
+            sample_offsets=arrays["sample_offsets"],
+            sync_samples=arrays["sync_samples"],
+        )
+
+
+def fetch_mp4_index(
+    path: str,
+    read_range: Callable[[str, int, int], bytes],
+    *,
+    file_size: int,
+    header_probe_bytes: int = 4 * 1024 * 1024,
+    max_probe_bytes: int = 64 * 1024 * 1024,
+) -> Mp4Index:
+    probe_size = min(header_probe_bytes, file_size)
+    while True:
+        data = read_range(path, 0, probe_size)
+        top = list(iter_boxes(data, 0, len(data), absolute_base=0, allow_truncated=True))
+        has_mdat = any(box.type == b"mdat" for box in top)
+        has_moov = any(box.type == b"moov" and box.end <= len(data) for box in top)
+        if has_mdat and has_moov:
+            return parse_mp4_index(path, data, file_size=file_size)
+        if probe_size >= min(max_probe_bytes, file_size):
+            if has_mdat and not has_moov:
+                tail_index = _fetch_tail_moov_index(path, read_range, data, top, file_size, max_probe_bytes)
+                if tail_index is not None:
+                    return tail_index
+            missing = []
+            if not has_mdat:
+                missing.append("mdat")
+            if not has_moov:
+                missing.append("moov")
+            raise ValueError(
+                f"Could not find complete {'/'.join(missing)} in first {probe_size} bytes of {path}"
+            )
+        probe_size = min(probe_size * 2, max_probe_bytes, file_size)
+
+
+def _fetch_tail_moov_index(
+    path: str,
+    read_range: Callable[[str, int, int], bytes],
+    prefix: bytes,
+    top_boxes: list[Box],
+    file_size: int,
+    max_probe_bytes: int,
+) -> Mp4Index | None:
+    mdat_box = _one(top_boxes, b"mdat")
+    if mdat_box is None or mdat_box.end >= file_size:
+        return None
+    tail_offset = mdat_box.end
+    tail_length = min(max_probe_bytes, file_size - tail_offset)
+    tail = read_range(path, tail_offset, tail_length)
+    tail_boxes = list(iter_boxes(tail, 0, len(tail), absolute_base=tail_offset, allow_truncated=True))
+    moov_box = next(
+        (box for box in tail_boxes if box.type == b"moov" and box.end <= tail_offset + len(tail)), None
+    )
+    if moov_box is None:
+        return None
+    ftyp_box = _one(top_boxes, b"ftyp", required=False)
+    ftyp = (
+        prefix[ftyp_box.start : ftyp_box.end]
+        if ftyp_box is not None
+        else _box(b"ftyp", b"isom\0\0\2\0isomiso2mp41")
+    )
+    moov_start = moov_box.payload_start - tail_offset
+    moov_end = moov_box.end - tail_offset
+    return _parse_mp4_index_from_layout(
+        path,
+        file_size=file_size,
+        ftyp=ftyp,
+        moov_offset=moov_box.start,
+        moov=tail[moov_start:moov_end],
+        mdat_box=mdat_box,
+    )
+
+
+def parse_mp4_index(path: str, data: bytes, *, file_size: int | None = None) -> Mp4Index:
+    if file_size is None:
+        file_size = len(data)
+    top = list(iter_boxes(data, 0, len(data), absolute_base=0, allow_truncated=True))
+    ftyp_box = _one(top, b"ftyp", required=False)
+    moov_box = _one(top, b"moov")
+    mdat_box = _one(top, b"mdat")
+    if moov_box.end > len(data):
+        raise ValueError(f"{path}: moov box is truncated")
+
+    moov = data[moov_box.payload_start : moov_box.end]
+    ftyp = (
+        data[ftyp_box.start : ftyp_box.end]
+        if ftyp_box is not None
+        else _box(b"ftyp", b"isom\0\0\2\0isomiso2mp41")
+    )
+    return _parse_mp4_index_from_layout(
+        path,
+        file_size=file_size,
+        ftyp=ftyp,
+        moov_offset=moov_box.start,
+        moov=moov,
+        mdat_box=mdat_box,
+    )
+
+
+def _parse_mp4_index_from_layout(
+    path: str,
+    *,
+    file_size: int,
+    ftyp: bytes,
+    moov_offset: int,
+    moov: bytes,
+    mdat_box: Box,
+) -> Mp4Index:
+    mvhd_timescale, mvhd_duration = _parse_mvhd(_find_descendant(moov, [b"mvhd"]))
+    trak_box, trak_payload = _find_video_trak(moov)
+    _ = trak_box
+    tkhd = _parse_tkhd(_find_descendant(trak_payload, [b"tkhd"]))
+    mdhd_timescale, mdhd_duration = _parse_mdhd(_find_descendant(trak_payload, [b"mdia", b"mdhd"]))
+    stbl = _find_descendant(trak_payload, [b"mdia", b"minf", b"stbl"])
+
+    stsd = _find_child(stbl, b"stsd")
+    stsd_body = stbl[stsd.payload_start : stsd.end]
+    codec = _parse_stsd_codec(stsd_body)
+    stts = _parse_stts(_payload(stbl, b"stts"))
+    sample_sizes = _parse_stsz(_payload(stbl, b"stsz"))
+    stsc = _parse_stsc(_payload(stbl, b"stsc"))
+    chunk_offsets = _parse_chunk_offsets(stbl)
+    sync_samples = _parse_stss(stbl, len(sample_sizes))
+
+    sample_durations = _expand_stts(stts, len(sample_sizes))
+    sample_pts_units = np.empty(len(sample_durations), dtype=np.int64)
+    if len(sample_durations):
+        sample_pts_units[0] = 0
+        if len(sample_durations) > 1:
+            sample_pts_units[1:] = np.cumsum(sample_durations[:-1], dtype=np.int64)
+    sample_pts = sample_pts_units.astype(np.float64) / float(mdhd_timescale)
+    sample_offsets = _sample_offsets(stsc, chunk_offsets, sample_sizes)
+
+    return Mp4Index(
+        file_path=path,
+        file_size=file_size,
+        ftyp=ftyp,
+        moov_offset=moov_offset,
+        mdat_offset=mdat_box.start,
+        mdat_payload_offset=mdat_box.payload_start,
+        mdat_payload_size=mdat_box.end - mdat_box.payload_start
+        if mdat_box.end <= file_size
+        else file_size - mdat_box.payload_start,
+        faststart=moov_offset < mdat_box.start,
+        codec=codec,
+        timescale=mdhd_timescale,
+        duration=mdhd_duration or mvhd_duration,
+        track_id=tkhd["track_id"],
+        width=tkhd["width"],
+        height=tkhd["height"],
+        stsd_body=stsd_body,
+        sample_pts=sample_pts,
+        sample_durations=sample_durations,
+        sample_sizes=sample_sizes,
+        sample_offsets=sample_offsets,
+        sync_samples=sync_samples,
+    )
+
+
+def synthesize_mp4(index: Mp4Index, sample_slice: Mp4SampleSlice, mdat_payload: bytes) -> bytes:
+    lo = sample_slice.sample_lo
+    hi = sample_slice.sample_hi + 1
+    if lo < 0 or hi > len(index.sample_sizes) or lo >= hi:
+        raise ValueError(f"Invalid sample range [{lo}, {hi}) for {index.file_path}")
+
+    offsets = index.sample_offsets[lo:hi]
+    sizes = index.sample_sizes[lo:hi]
+    rel_offsets = offsets - sample_slice.byte_offset
+    if int(rel_offsets.min()) != 0:
+        raise ValueError("Sample slice must start at the minimum referenced sample offset")
+    if int((rel_offsets + sizes).max()) > len(mdat_payload):
+        raise ValueError("Sample slice does not cover all referenced samples")
+
+    durations = index.sample_durations[lo:hi]
+    sync = index.sync_samples[(index.sync_samples >= lo) & (index.sync_samples < hi)] - lo + 1
+    moov = _make_moov(index, durations, sizes, rel_offsets, sync, mdat_data_offset=0)
+    header_size = len(index.ftyp) + len(moov)
+    moov = _make_moov(index, durations, sizes, rel_offsets, sync, mdat_data_offset=header_size + 8)
+    return index.ftyp + moov + _box(b"mdat", mdat_payload)
+
+
+def iter_boxes(
+    data: bytes,
+    start: int,
+    end: int,
+    *,
+    absolute_base: int = 0,
+    allow_truncated: bool = False,
+) -> Iterable[Box]:
+    pos = start
+    while pos + 8 <= end:
+        size = struct.unpack_from(">I", data, pos)[0]
+        typ = data[pos + 4 : pos + 8]
+        header_size = 8
+        if size == 1:
+            if pos + 16 > end:
+                break
+            size = struct.unpack_from(">Q", data, pos + 8)[0]
+            header_size = 16
+        elif size == 0:
+            size = end - pos
+        if size < header_size:
+            break
+        box_end = pos + size
+        if box_end > end and not allow_truncated:
+            break
+        yield Box(typ, absolute_base + pos, header_size, absolute_base + box_end)
+        pos = box_end
+
+
+def _find_video_trak(moov: bytes) -> tuple[Box, bytes]:
+    for trak in _children(moov, 0, len(moov)):
+        if trak.type != b"trak":
+            continue
+        payload = moov[trak.payload_start : trak.end]
+        hdlr = _find_descendant(payload, [b"mdia", b"hdlr"])
+        if hdlr[8:12] == b"vide":
+            return trak, payload
+    raise ValueError("No video track found")
+
+
+def _find_descendant(data: bytes, path: list[bytes]) -> bytes:
+    current = data
+    for typ in path:
+        box = _find_child(current, typ)
+        current = current[box.payload_start : box.end]
+    return current
+
+
+def _find_child(data: bytes, typ: bytes) -> Box:
+    for box in _children(data, 0, len(data)):
+        if box.type == typ:
+            return box
+    raise ValueError(f"Missing MP4 box {typ.decode('latin1')}")
+
+
+def _children(data: bytes, start: int, end: int) -> Iterable[Box]:
+    return iter_boxes(data, start, end, absolute_base=0)
+
+
+def _one(boxes: list[Box], typ: bytes, *, required: bool = True) -> Box | None:
+    matches = [box for box in boxes if box.type == typ]
+    if not matches and required:
+        raise ValueError(f"Missing MP4 box {typ.decode('latin1')}")
+    return matches[0] if matches else None
+
+
+def _payload(parent: bytes, typ: bytes) -> bytes:
+    box = _find_child(parent, typ)
+    return parent[box.payload_start : box.end]
+
+
+def _parse_mvhd(payload: bytes) -> tuple[int, int]:
+    version = payload[0]
+    if version == 1:
+        return struct.unpack_from(">IQ", payload, 20)
+    return struct.unpack_from(">II", payload, 12)
+
+
+def _parse_mdhd(payload: bytes) -> tuple[int, int]:
+    version = payload[0]
+    if version == 1:
+        return struct.unpack_from(">IQ", payload, 20)
+    return struct.unpack_from(">II", payload, 12)
+
+
+def _parse_tkhd(payload: bytes) -> dict[str, int]:
+    version = payload[0]
+    if version == 1:
+        track_id = struct.unpack_from(">I", payload, 20)[0]
+        duration = struct.unpack_from(">Q", payload, 28)[0]
+        width, height = struct.unpack_from(">II", payload, 88)
+    else:
+        track_id = struct.unpack_from(">I", payload, 12)[0]
+        duration = struct.unpack_from(">I", payload, 20)[0]
+        width, height = struct.unpack_from(">II", payload, 76)
+    return {"track_id": track_id, "duration": duration, "width": width >> 16, "height": height >> 16}
+
+
+def _parse_stsd_codec(stsd_body: bytes) -> str:
+    if len(stsd_body) < 16:
+        return "unknown"
+    return stsd_body[12:16].decode("latin1")
+
+
+def _parse_stts(payload: bytes) -> list[tuple[int, int]]:
+    count = struct.unpack_from(">I", payload, 4)[0]
+    out = []
+    offset = 8
+    for _ in range(count):
+        out.append(struct.unpack_from(">II", payload, offset))
+        offset += 8
+    return out
+
+
+def _expand_stts(entries: list[tuple[int, int]], sample_count: int) -> np.ndarray:
+    values = np.empty(sample_count, dtype=np.int64)
+    pos = 0
+    for count, delta in entries:
+        values[pos : pos + count] = delta
+        pos += count
+    if pos != sample_count:
+        raise ValueError(f"stts describes {pos} samples, stsz describes {sample_count}")
+    return values
+
+
+def _parse_stsz(payload: bytes) -> np.ndarray:
+    sample_size, sample_count = struct.unpack_from(">II", payload, 4)
+    if sample_size:
+        return np.full(sample_count, sample_size, dtype=np.int64)
+    offset = 12
+    values = np.empty(sample_count, dtype=np.int64)
+    for idx in range(sample_count):
+        values[idx] = struct.unpack_from(">I", payload, offset)[0]
+        offset += 4
+    return values
+
+
+def _parse_stsc(payload: bytes) -> list[tuple[int, int, int]]:
+    count = struct.unpack_from(">I", payload, 4)[0]
+    out = []
+    offset = 8
+    for _ in range(count):
+        out.append(struct.unpack_from(">III", payload, offset))
+        offset += 12
+    return out
+
+
+def _parse_chunk_offsets(stbl: bytes) -> np.ndarray:
+    with_stco = None
+    with_co64 = None
+    for box in _children(stbl, 0, len(stbl)):
+        if box.type == b"stco":
+            with_stco = stbl[box.payload_start : box.end]
+        elif box.type == b"co64":
+            with_co64 = stbl[box.payload_start : box.end]
+    if with_co64 is not None:
+        count = struct.unpack_from(">I", with_co64, 4)[0]
+        return np.array(
+            [struct.unpack_from(">Q", with_co64, 8 + idx * 8)[0] for idx in range(count)], dtype=np.int64
+        )
+    if with_stco is None:
+        raise ValueError("Missing stco/co64 chunk offsets")
+    count = struct.unpack_from(">I", with_stco, 4)[0]
+    return np.array(
+        [struct.unpack_from(">I", with_stco, 8 + idx * 4)[0] for idx in range(count)], dtype=np.int64
+    )
+
+
+def _parse_stss(stbl: bytes, sample_count: int) -> np.ndarray:
+    for box in _children(stbl, 0, len(stbl)):
+        if box.type == b"stss":
+            payload = stbl[box.payload_start : box.end]
+            count = struct.unpack_from(">I", payload, 4)[0]
+            return np.array(
+                [struct.unpack_from(">I", payload, 8 + idx * 4)[0] - 1 for idx in range(count)],
+                dtype=np.int64,
+            )
+    return np.arange(sample_count, dtype=np.int64)
+
+
+def _sample_offsets(
+    stsc: list[tuple[int, int, int]], chunk_offsets: np.ndarray, sample_sizes: np.ndarray
+) -> np.ndarray:
+    if not stsc:
+        raise ValueError("stsc is empty")
+    offsets = np.empty(len(sample_sizes), dtype=np.int64)
+    sample_idx = 0
+    for entry_idx, (first_chunk, samples_per_chunk, _desc_idx) in enumerate(stsc):
+        next_first = stsc[entry_idx + 1][0] if entry_idx + 1 < len(stsc) else len(chunk_offsets) + 1
+        for chunk_number in range(first_chunk, next_first):
+            if chunk_number < 1 or chunk_number > len(chunk_offsets):
+                raise ValueError("stsc references a chunk outside stco/co64")
+            chunk_pos = int(chunk_offsets[chunk_number - 1])
+            for _ in range(samples_per_chunk):
+                if sample_idx >= len(sample_sizes):
+                    return offsets
+                offsets[sample_idx] = chunk_pos
+                chunk_pos += int(sample_sizes[sample_idx])
+                sample_idx += 1
+    if sample_idx != len(sample_sizes):
+        raise ValueError(f"stsc describes {sample_idx} samples, stsz describes {len(sample_sizes)}")
+    return offsets
+
+
+def _make_moov(
+    index: Mp4Index,
+    durations: np.ndarray,
+    sizes: np.ndarray,
+    rel_offsets: np.ndarray,
+    sync_samples: np.ndarray,
+    *,
+    mdat_data_offset: int,
+) -> bytes:
+    duration = int(durations.sum())
+    stco_values = [int(mdat_data_offset + value) for value in rel_offsets]
+    if any(value > 0xFFFFFFFF for value in stco_values):
+        offset_box = _co64(stco_values)
+    else:
+        offset_box = _stco(stco_values)
+    stbl = _box(
+        b"stbl",
+        _box(b"stsd", index.stsd_body)
+        + _stts(durations)
+        + _stsc_one_sample_per_chunk(len(sizes))
+        + _stsz(sizes)
+        + offset_box
+        + (_stss(sync_samples) if len(sync_samples) else b""),
+    )
+    minf = _box(b"minf", _vmhd() + _dinf() + stbl)
+    mdia = _box(b"mdia", _mdhd(index.timescale, duration) + _hdlr() + minf)
+    trak = _box(b"trak", _tkhd(index.track_id, duration, index.width, index.height) + mdia)
+    return _box(b"moov", _mvhd(index.timescale, duration, index.track_id + 1) + trak)
+
+
+def _full_box(typ: bytes, version: int, flags: int, payload: bytes = b"") -> bytes:
+    return _box(typ, bytes([version]) + flags.to_bytes(3, "big") + payload)
+
+
+def _box(typ: bytes, payload: bytes) -> bytes:
+    size = len(payload) + 8
+    if size <= 0xFFFFFFFF:
+        return struct.pack(">I4s", size, typ) + payload
+    return struct.pack(">I4sQ", 1, typ, size + 8) + payload
+
+
+def _mvhd(timescale: int, duration: int, next_track_id: int) -> bytes:
+    matrix = struct.pack(">9I", 0x00010000, 0, 0, 0, 0x00010000, 0, 0, 0, 0x40000000)
+    payload = (
+        struct.pack(">IIII", 0, 0, timescale, duration)
+        + struct.pack(">IHH", 0x00010000, 0x0100, 0)
+        + b"\0" * 8
+        + matrix
+        + b"\0" * 24
+        + struct.pack(">I", next_track_id)
+    )
+    return _full_box(b"mvhd", 0, 0, payload)
+
+
+def _tkhd(track_id: int, duration: int, width: int, height: int) -> bytes:
+    matrix = struct.pack(">9I", 0x00010000, 0, 0, 0, 0x00010000, 0, 0, 0, 0x40000000)
+    payload = (
+        struct.pack(">IIIII", 0, 0, track_id, 0, duration)
+        + b"\0" * 8
+        + struct.pack(">hhhh", 0, 0, 0, 0)
+        + matrix
+        + struct.pack(">II", width << 16, height << 16)
+    )
+    return _full_box(b"tkhd", 0, 7, payload)
+
+
+def _mdhd(timescale: int, duration: int) -> bytes:
+    return _full_box(b"mdhd", 0, 0, struct.pack(">IIIIH", 0, 0, timescale, duration, 0x55C4) + b"\0\0")
+
+
+def _hdlr() -> bytes:
+    return _full_box(b"hdlr", 0, 0, b"\0" * 4 + b"vide" + b"\0" * 12 + b"VideoHandler\0")
+
+
+def _vmhd() -> bytes:
+    return _full_box(b"vmhd", 0, 1, struct.pack(">HHHH", 0, 0, 0, 0))
+
+
+def _dinf() -> bytes:
+    url = _full_box(b"url ", 0, 1)
+    dref = _full_box(b"dref", 0, 0, struct.pack(">I", 1) + url)
+    return _box(b"dinf", dref)
+
+
+def _stts(durations: np.ndarray) -> bytes:
+    runs = []
+    for duration in durations.tolist():
+        if runs and runs[-1][1] == int(duration):
+            runs[-1][0] += 1
+        else:
+            runs.append([1, int(duration)])
+    payload = struct.pack(">I", len(runs)) + b"".join(
+        struct.pack(">II", count, delta) for count, delta in runs
+    )
+    return _full_box(b"stts", 0, 0, payload)
+
+
+def _stsc_one_sample_per_chunk(sample_count: int) -> bytes:
+    return _full_box(b"stsc", 0, 0, struct.pack(">IIII", 1, 1, 1, 1))
+
+
+def _stsz(sizes: np.ndarray) -> bytes:
+    return _full_box(
+        b"stsz",
+        0,
+        0,
+        struct.pack(">II", 0, len(sizes)) + b"".join(struct.pack(">I", int(size)) for size in sizes.tolist()),
+    )
+
+
+def _stco(values: list[int]) -> bytes:
+    return _full_box(
+        b"stco", 0, 0, struct.pack(">I", len(values)) + b"".join(struct.pack(">I", v) for v in values)
+    )
+
+
+def _co64(values: list[int]) -> bytes:
+    return _full_box(
+        b"co64", 0, 0, struct.pack(">I", len(values)) + b"".join(struct.pack(">Q", v) for v in values)
+    )
+
+
+def _stss(values: np.ndarray) -> bytes:
+    return _full_box(
+        b"stss",
+        0,
+        0,
+        struct.pack(">I", len(values)) + b"".join(struct.pack(">I", int(value)) for value in values.tolist()),
+    )

tests/datasets/test_episode_video_streaming.py

@@ -0,0 +1,121 @@
+#!/usr/bin/env python
+
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+
+import json
+import struct
+
+import numpy as np
+import pytest
+
+from lerobot.datasets.episode_video_streaming import assert_hf_hub_range_cache_branch
+from lerobot.datasets.mp4 import (
+    _box,
+    _co64,
+    _dinf,
+    _hdlr,
+    _mdhd,
+    _mvhd,
+    _stco,
+    _stsc_one_sample_per_chunk,
+    _stss,
+    _stsz,
+    _stts,
+    _tkhd,
+    _vmhd,
+    parse_mp4_index,
+    synthesize_mp4,
+)
+
+
+def _minimal_mp4(sample_offsets: list[int], *, use_co64: bool = False) -> bytes:
+    ftyp = _box(b"ftyp", b"isom\0\0\2\0isomiso2mp41")
+    sizes = np.array([10, 10, 10], dtype=np.int64)
+    durations = np.array([1000, 1000, 1000], dtype=np.int64)
+    stsd_body = struct.pack(">II", 0, 1) + struct.pack(">I4s", 16, b"avc1") + b"\0" * 8
+    offsets = _co64(sample_offsets) if use_co64 else _stco(sample_offsets)
+    stbl = _box(
+        b"stbl",
+        _box(b"stsd", stsd_body)
+        + _stts(durations)
+        + _stsc_one_sample_per_chunk(len(sizes))
+        + _stsz(sizes)
+        + offsets
+        + _stss(np.array([1], dtype=np.int64)),
+    )
+    minf = _box(b"minf", _vmhd() + _dinf() + stbl)
+    mdia = _box(b"mdia", _mdhd(1000, 3000) + _hdlr() + minf)
+    trak = _box(b"trak", _tkhd(1, 3000, 64, 48) + mdia)
+    moov = _box(b"moov", _mvhd(1000, 3000, 2) + trak)
+    mdat_payload_start = 10_000
+    free_size = mdat_payload_start - 8 - len(ftyp) - len(moov)
+    assert free_size >= 8
+    free = _box(b"free", b"\0" * (free_size - 8))
+    return ftyp + moov + free + _box(b"mdat", b"x" * 128)
+
+
+def test_episode_slice_uses_min_max_sample_offsets_for_reordered_chunks():
+    mp4 = parse_mp4_index("test.mp4", _minimal_mp4([10_000, 10_050, 10_025]))
+
+    sample_slice = mp4.sample_slice(0.0, 2.0, keyframe_pad_s=0, keyframe_pad_fraction=0)
+
+    assert sample_slice.byte_offset == 10_000
+    assert sample_slice.byte_length == 60
+    assert sample_slice.sample_lo == 0
+    assert sample_slice.sample_hi == 2
+
+
+def test_synthesized_mp4_rebases_one_chunk_per_sample_offsets():
+    mp4 = parse_mp4_index("test.mp4", _minimal_mp4([10_000, 10_050, 10_025]))
+    sample_slice = mp4.sample_slice(0.0, 2.0, keyframe_pad_s=0, keyframe_pad_fraction=0)
+
+    mini = synthesize_mp4(mp4, sample_slice, b"x" * sample_slice.byte_length)
+    mini_index = parse_mp4_index("mini.mp4", mini)
+
+    expected = np.array([0, 50, 25], dtype=np.int64) + mini_index.mdat_payload_offset
+    np.testing.assert_array_equal(mini_index.sample_offsets, expected)
+    np.testing.assert_array_equal(mini_index.sample_sizes, np.array([10, 10, 10]))
+
+
+def test_parser_accepts_co64_chunk_offsets():
+    mp4 = parse_mp4_index("test.mp4", _minimal_mp4([10_000, 10_050, 10_025], use_co64=True))
+
+    np.testing.assert_array_equal(mp4.sample_offsets, np.array([10_000, 10_050, 10_025]))
+
+
+def test_hf_hub_branch_assertion_accepts_requested_revision(monkeypatch):
+    class FakeDist:
+        def read_text(self, name):
+            assert name == "direct_url.json"
+            return json.dumps(
+                {
+                    "url": "https://github.com/huggingface/huggingface_hub.git",
+                    "vcs_info": {"requested_revision": "feat/hffs-cache-cdn-range-reads"},
+                }
+            )
+
+    monkeypatch.setattr(
+        "lerobot.datasets.episode_video_streaming.metadata.distribution", lambda _: FakeDist()
+    )
+
+    assert_hf_hub_range_cache_branch()
+
+
+def test_hf_hub_branch_assertion_rejects_plain_install(monkeypatch):
+    class FakeDist:
+        def read_text(self, name):
+            assert name == "direct_url.json"
+            return json.dumps({"url": "https://github.com/huggingface/huggingface_hub.git"})
+
+    monkeypatch.setattr(
+        "lerobot.datasets.episode_video_streaming.metadata.distribution", lambda _: FakeDist()
+    )
+
+    with pytest.raises(AssertionError):
+        assert_hf_hub_range_cache_branch()

tests/datasets/test_exact_coverage_pool.py

@@ -0,0 +1,97 @@
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""ExactCoveragePool: exactly-once frame coverage over a bounded episode pool."""
+
+from collections import Counter
+
+from lerobot.datasets.episode_video_streaming import ExactCoveragePool
+
+EPISODES = [(0, 5), (1, 3), (2, 8), (3, 1), (4, 6), (5, 4), (6, 7), (7, 2)]
+TOTAL = sum(n for _, n in EPISODES)
+EXPECTED = Counter((ep, i) for ep, n in EPISODES for i in range(n))
+
+
+def _drain(pool):
+    out, max_resident = [], 0
+    while True:
+        try:
+            out.append(next(pool))
+        except StopIteration:
+            break
+        max_resident = max(max_resident, len(pool.resident))
+    return out, max_resident
+
+
+def test_exact_once_coverage():
+    out, _ = _drain(ExactCoveragePool(EPISODES, pool_size=3, seed=42))
+    assert len(out) == TOTAL
+    assert Counter(out) == EXPECTED  # every (episode, frame) exactly once, no dups/misses
+
+
+def test_pool_never_exceeds_size():
+    _, max_resident = _drain(ExactCoveragePool(EPISODES, pool_size=3, seed=42))
+    assert max_resident <= 3
+
+
+def test_deterministic_per_seed_and_epoch():
+    a, _ = _drain(ExactCoveragePool(EPISODES, pool_size=3, seed=7))
+    b, _ = _drain(ExactCoveragePool(EPISODES, pool_size=3, seed=7))
+    c, _ = _drain(ExactCoveragePool(EPISODES, pool_size=3, seed=8))
+    d, _ = _drain(ExactCoveragePool(EPISODES, pool_size=3, seed=7, epoch=1))
+    assert a == b
+    assert a != c and a != d  # seed and epoch both change the order
+    assert Counter(c) == EXPECTED and Counter(d) == EXPECTED  # ... but coverage is preserved
+
+
+def test_admission_and_eviction_events():
+    pool = ExactCoveragePool(EPISODES, pool_size=3, seed=0)
+    admitted_ever, evicted_ever = set(), set()
+    # first three episodes admitted at construction
+    admitted_ever.update(pool.newly_admitted)
+    assert len(admitted_ever) == 3
+    while True:
+        pool.newly_admitted.clear()
+        pool.evicted.clear()
+        try:
+            next(pool)
+        except StopIteration:
+            break
+        admitted_ever.update(pool.newly_admitted)
+        evicted_ever.update(pool.evicted)
+    assert admitted_ever == {ep for ep, _ in EPISODES}  # every episode admitted exactly once
+    # every episode except the pool_size still resident at the end is evicted on exhaustion
+    assert len(evicted_ever) >= len(EPISODES) - 3
+
+
+def test_uniform_mixing_matches_coupon_collector():
+    # 64 equal episodes, pool 64, first 64 draws -> ~64*(1-(1-1/64)^64) ~= 41 distinct
+    big = [(e, 100) for e in range(64)]
+    pool = ExactCoveragePool(big, pool_size=64, seed=0)
+    head = [next(pool)[0] for _ in range(64)]
+    assert len(set(head)) >= 30  # far above sequential (=1); ~41 expected
+
+
+def test_large_epoch_bounded_and_complete():
+    big = [(e, 90) for e in range(500)]
+    out, max_resident = _drain(ExactCoveragePool(big, pool_size=64, seed=3))
+    assert len(out) == 500 * 90
+    assert len(set(out)) == 500 * 90  # exactly once
+    assert max_resident <= 64
+
+
+def test_zero_length_episodes_skipped():
+    pool = ExactCoveragePool([(0, 3), (1, 0), (2, 2)], pool_size=8, seed=0)
+    out, _ = _drain(pool)
+    assert Counter(out) == Counter({(0, 0): 1, (0, 1): 1, (0, 2): 1, (2, 0): 1, (2, 1): 1})

uv.lock

@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.12"
 resolution-markers = [
     "(python_full_version >= '3.15' and platform_machine == 'AMD64' and sys_platform == 'linux') or (python_full_version >= '3.15' and platform_machine == 'x86_64' and sys_platform == 'linux')",
@@ -1089,8 +1089,8 @@ wheels = [
 
 [[package]]
 name = "datasets"
-version = "4.8.5"
-source = { registry = "https://pypi.org/simple" }
+version = "5.0.1.dev0"
+source = { git = "https://github.com/huggingface/datasets.git?branch=main#06fcc085fcdd22fc5cc741954f6187dd879543b6" }
 dependencies = [
     { name = "dill" },
     { name = "filelock" },
@@ -1107,10 +1107,6 @@ dependencies = [
     { name = "tqdm" },
     { name = "xxhash" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/66/34/14cd8e76f907f7d4dca2334cfeec9f81d30fd15c25a015f99aaea694eaed/datasets-4.8.5.tar.gz", hash = "sha256:0f0c1c3d56ffff2c93b2f4c63c95bac94f3d7e8621aea2a2a576275233bba772", size = 605649, upload-time = "2026-04-27T15:43:57.384Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/65/99/00f3196036501b53032c4b1ab8337a0b978dee832ed276dae3815df4e8b5/datasets-4.8.5-py3-none-any.whl", hash = "sha256:5079900781719c0e063a8efdd2cd95a31ad0c63209178669cd23cf1b926149ff", size = 528973, upload-time = "2026-04-27T15:43:53.702Z" },
-]
 
 [[package]]
 name = "debugpy"
@@ -1147,7 +1143,7 @@ name = "decord"
 version = "0.6.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "numpy", marker = "(platform_machine != 'arm64' and sys_platform == 'darwin') or (platform_machine == 'AMD64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "numpy", marker = "(platform_machine != 'arm64' and platform_machine != 's390x' and sys_platform == 'darwin') or (platform_machine == 'AMD64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux') or (platform_machine != 's390x' and sys_platform != 'darwin' and sys_platform != 'linux')" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/11/79/936af42edf90a7bd4e41a6cac89c913d4b47fa48a26b042d5129a9242ee3/decord-0.6.0-py3-none-manylinux2010_x86_64.whl", hash = "sha256:51997f20be8958e23b7c4061ba45d0efcd86bffd5fe81c695d0befee0d442976", size = 13602299, upload-time = "2021-06-14T21:30:55.486Z" },
@@ -2050,8 +2046,8 @@ wheels = [
 
 [[package]]
 name = "huggingface-hub"
-version = "1.19.0"
-source = { registry = "https://pypi.org/simple" }
+version = "1.20.0.dev0"
+source = { git = "https://github.com/huggingface/huggingface_hub.git?branch=feat%2Fhffs-cache-cdn-range-reads#5319b287faa73239bb40df16d69c39e5d6daf0f7" }
 dependencies = [
     { name = "click" },
     { name = "filelock" },
@@ -2064,10 +2060,6 @@ dependencies = [
     { name = "typer" },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/88/27/629cfe58c582f92ded066c4a07d1a057ff617118ab7973200f770bd853cb/huggingface_hub-1.19.0.tar.gz", hash = "sha256:fd771622182d40977272a923953ee3b1b13538f9f8a7f5d78398f10af0f1c0bd", size = 824721, upload-time = "2026-06-11T12:33:18.665Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/b2/a5/558da89f66464d8d0229ff497e8b8666977de2d8cf48c28a2862ecf1250f/huggingface_hub-1.19.0-py3-none-any.whl", hash = "sha256:1dc72e1f6b4d6df6b30eb72e57d00514ef453d660f04af2b87f0e67267f31ee0", size = 693398, upload-time = "2026-06-11T12:33:16.695Z" },
-]
 
 [[package]]
 name = "hydra-core"
@@ -3187,7 +3179,7 @@ requires-dist = [
     { name = "av", marker = "extra == 'av-dep'", specifier = ">=15.0.0,<16.0.0" },
     { name = "cmake", specifier = ">=3.29.0.1,<4.2.0" },
     { name = "contourpy", marker = "extra == 'matplotlib-dep'", specifier = ">=1.3.0,<2.0.0" },
-    { name = "datasets", marker = "extra == 'dataset'", specifier = ">=4.7.0,<5.0.0" },
+    { name = "datasets", marker = "extra == 'dataset'", git = "https://github.com/huggingface/datasets.git?branch=main" },
     { name = "debugpy", marker = "extra == 'dev'", specifier = ">=1.8.1,<1.9.0" },
     { name = "decord", marker = "(platform_machine == 'AMD64' and extra == 'groot') or (platform_machine == 'x86_64' and extra == 'groot')", specifier = ">=0.6.0,<1.0.0" },
     { name = "deepdiff", marker = "extra == 'deepdiff-dep'", specifier = ">=7.0.1,<9.0.0" },
@@ -3210,7 +3202,7 @@ requires-dist = [
     { name = "hebi-py", marker = "extra == 'phone'", specifier = ">=2.8.0,<2.12.0" },
     { name = "hf-libero", marker = "sys_platform == 'linux' and extra == 'libero'", specifier = ">=0.1.4,<0.2.0" },
     { name = "hidapi", marker = "extra == 'gamepad'", specifier = ">=0.14.0,<0.15.0" },
-    { name = "huggingface-hub", specifier = ">=1.0.0,<2.0.0" },
+    { name = "huggingface-hub", git = "https://github.com/huggingface/huggingface_hub.git?branch=feat%2Fhffs-cache-cdn-range-reads" },
     { name = "ipykernel", marker = "extra == 'notebook'", specifier = ">=6.0.0,<7.0.0" },
     { name = "jsonlines", marker = "extra == 'dataset'", specifier = ">=4.0.0,<5.0.0" },
     { name = "jupyter", marker = "extra == 'notebook'", specifier = ">=1.0.0,<2.0.0" },