File size: 9,765 Bytes
05d6af6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
"""Generate manifest.jsonl and metadata.json for the sf_release dataset.

Walks `<root>/dataset/<source_dataset>/<method>/<object_id>/` and records one row
per instance with the artifacts present in that directory. Designed to be
idempotent and to ship inside the released Hugging Face repository so users can
rebuild the manifest at any revision.

Usage:
    python scripts/build_manifest.py            # writes manifest.jsonl + metadata.json
    python scripts/build_manifest.py --checksums # also compute sha256 (slow)
    python scripts/build_manifest.py --root /path/to/sf_release --out-dir /path/to/out
"""

from __future__ import annotations

import argparse
import hashlib
import json
import re
from collections import Counter, defaultdict
from pathlib import Path
from typing import Any

# Artifacts we look for in each instance directory.
# Order matters only for documentation; lookup is by exact filename.
OPTIONAL_FILES: dict[str, str] = {
    "config": "config.json",
    "primitive_assembly": "primitive_assembly.pkl",
    "primitive_assembly_textured": "primitive_assembly.pkl_textured.pkl",
    "primitive_assembly_eval": "primitive_assembly_eval.pkl",
    "primitive_assembly_error": "primitive_assembly_error.pkl",
}

# Subdirectory under the release root that holds subset/method/instance trees.
DATASET_DIR = "dataset"

# Aggregate / method-level files we expect to find at <subset>/<method>/
METHOD_LEVEL_FILES: dict[str, str] = {
    "eval_summary_md": "eval_summary",  # prefix; suffix encodes range
    "eval_summary_pkl": "eval_summary",
}

# toys4k uses "<category>_<numeric_id>" object ids; PartObjaverse uses 32-char hex.
TOYS4K_OBJECT_RE = re.compile(r"^(?P<category>[A-Za-z][A-Za-z0-9_]*?)_(?P<num>\d{3,})$")
HEX_OBJECT_RE = re.compile(r"^[0-9a-f]{32}$")


def sha256_file(path: Path, chunk_size: int = 1 << 20) -> str:
    h = hashlib.sha256()
    with path.open("rb") as fh:
        while True:
            buf = fh.read(chunk_size)
            if not buf:
                break
            h.update(buf)
    return h.hexdigest()


def parse_object_id(source_dataset: str, name: str) -> tuple[str | None, str]:
    """Return (category, object_id). category is None when not derivable."""
    if source_dataset == "toys4k":
        m = TOYS4K_OBJECT_RE.match(name)
        if m:
            return m.group("category"), name
        return None, name
    if source_dataset == "partobjaverse":
        if HEX_OBJECT_RE.match(name):
            return None, name
        return None, name
    return None, name


def scan_instance(instance_dir: Path) -> dict[str, Any]:
    files_present: dict[str, bool] = {}
    file_sizes: dict[str, int] = {}
    for key, filename in OPTIONAL_FILES.items():
        candidate = instance_dir / filename
        present = candidate.is_file()
        files_present[f"has_{key}"] = present
        if present:
            file_sizes[f"{key}_bytes"] = candidate.stat().st_size
    return {"files_present": files_present, "file_sizes": file_sizes}


def build_manifest(
    root: Path,
    compute_checksums: bool,
    dataset_dir: str = DATASET_DIR,
) -> tuple[list[dict[str, Any]], dict[str, Any]]:
    rows: list[dict[str, Any]] = []
    subset_counts: Counter[tuple[str, str]] = Counter()
    method_aggregates: dict[tuple[str, str], dict[str, Any]] = {}
    category_counts: dict[tuple[str, str], Counter[str]] = defaultdict(Counter)

    if not root.is_dir():
        raise SystemExit(f"Release root does not exist: {root}")

    data_root = root / dataset_dir
    if not data_root.is_dir():
        raise SystemExit(f"Dataset directory does not exist: {data_root}")

    subsets = sorted(
        p.name for p in data_root.iterdir() if p.is_dir() and not p.name.startswith(".")
    )
    for subset in subsets:
        subset_dir = data_root / subset
        methods = sorted(p.name for p in subset_dir.iterdir() if p.is_dir())
        for method in methods:
            method_dir = subset_dir / method

            method_files: dict[str, list[str]] = {"eval_summary_md": [], "eval_summary_pkl": []}
            for entry in method_dir.iterdir():
                if entry.is_file() and entry.name.startswith("eval_summary"):
                    if entry.suffix == ".md":
                        method_files["eval_summary_md"].append(entry.name)
                    elif entry.suffix == ".pkl":
                        method_files["eval_summary_pkl"].append(entry.name)
            for k in method_files:
                method_files[k].sort()
            method_aggregates[(subset, method)] = method_files

            instance_dirs = sorted(p for p in method_dir.iterdir() if p.is_dir())
            for instance_dir in instance_dirs:
                name = instance_dir.name
                category, object_id = parse_object_id(subset, name)
                scan = scan_instance(instance_dir)

                paths: dict[str, str | None] = {}
                for key, filename in OPTIONAL_FILES.items():
                    rel = f"{dataset_dir}/{subset}/{method}/{name}/{filename}"
                    paths[f"{key}_path"] = rel if scan["files_present"][f"has_{key}"] else None

                row: dict[str, Any] = {
                    "source_dataset": subset,
                    "method": method,
                    "object_id": object_id,
                    "category": category,
                    "instance_dir": f"{dataset_dir}/{subset}/{method}/{name}",
                    **paths,
                    **scan["files_present"],
                    **scan["file_sizes"],
                }
                if compute_checksums:
                    for key, filename in OPTIONAL_FILES.items():
                        candidate = instance_dir / filename
                        if candidate.is_file():
                            row[f"{key}_sha256"] = sha256_file(candidate)

                rows.append(row)
                subset_counts[(subset, method)] += 1
                if category is not None:
                    category_counts[(subset, method)][category] += 1

    metadata: dict[str, Any] = {
        "release_root_name": root.resolve().name,
        "data_dir": dataset_dir,
        "subsets": sorted({s for s, _ in subset_counts}),
        "methods_by_subset": {
            subset: sorted({m for s, m in subset_counts if s == subset})
            for subset in sorted({s for s, _ in subset_counts})
        },
        "instance_counts": {
            f"{subset}/{method}": count
            for (subset, method), count in sorted(subset_counts.items())
        },
        "total_instances": sum(subset_counts.values()),
        "method_level_files": {
            f"{subset}/{method}": files
            for (subset, method), files in sorted(method_aggregates.items())
        },
        "category_counts_toys4k": {
            f"{subset}/{method}": dict(sorted(counts.items()))
            for (subset, method), counts in sorted(category_counts.items())
            if subset == "toys4k"
        },
        "schema": {
            "artifact_filenames": OPTIONAL_FILES,
            "manifest_columns": [
                "source_dataset",
                "method",
                "object_id",
                "category",
                "instance_dir",
                "config_path",
                "primitive_assembly_path",
                "primitive_assembly_textured_path",
                "primitive_assembly_eval_path",
                "primitive_assembly_error_path",
                "has_config",
                "has_primitive_assembly",
                "has_primitive_assembly_textured",
                "has_primitive_assembly_eval",
                "has_primitive_assembly_error",
                "config_bytes",
                "primitive_assembly_bytes",
                "primitive_assembly_textured_bytes",
                "primitive_assembly_eval_bytes",
                "primitive_assembly_error_bytes",
            ],
            "checksums_included": compute_checksums,
        },
    }
    return rows, metadata


def write_outputs(rows: list[dict[str, Any]], metadata: dict[str, Any], out_dir: Path) -> None:
    out_dir.mkdir(parents=True, exist_ok=True)
    manifest_path = out_dir / "manifest.jsonl"
    with manifest_path.open("w") as fh:
        for row in rows:
            fh.write(json.dumps(row, sort_keys=True))
            fh.write("\n")
    metadata_path = out_dir / "metadata.json"
    with metadata_path.open("w") as fh:
        json.dump(metadata, fh, indent=2, sort_keys=True)
        fh.write("\n")
    print(f"Wrote {len(rows)} rows to {manifest_path}")
    print(f"Wrote summary to {metadata_path}")


def main() -> None:
    parser = argparse.ArgumentParser(description=__doc__)
    default_root = Path(__file__).resolve().parent.parent
    parser.add_argument("--root", type=Path, default=default_root,
                        help="Release root (expects dataset/<subset>/<method>/<instance>/).")
    parser.add_argument("--dataset-dir", type=str, default=DATASET_DIR,
                        help=f"Name of the data subdirectory under --root (default: {DATASET_DIR}).")
    parser.add_argument("--out-dir", type=Path, default=None,
                        help="Where to write manifest.jsonl and metadata.json. Defaults to --root.")
    parser.add_argument("--checksums", action="store_true",
                        help="Compute sha256 for every artifact file. Slow on the full release.")
    args = parser.parse_args()

    out_dir = args.out_dir if args.out_dir is not None else args.root
    rows, metadata = build_manifest(
        args.root,
        compute_checksums=args.checksums,
        dataset_dir=args.dataset_dir,
    )
    write_outputs(rows, metadata, out_dir)


if __name__ == "__main__":
    main()