Token Classification
Transformers
ONNX
Safetensors
English
Japanese
Chinese
bert
anime
filename-parsing
Eval Results (legacy)
Instructions to use ModerRAS/AniFileBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModerRAS/AniFileBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ModerRAS/AniFileBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ModerRAS/AniFileBERT") model = AutoModelForTokenClassification.from_pretrained("ModerRAS/AniFileBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 11,759 Bytes
7509455 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 | """Expand DAG annotation patches over the full DMHY source list.
The DAG annotation runner samples terminal.value_examples. This tool keeps the
LLM patch layer intact, but applies it to every dmhy_list.jsonl value by
deterministic terminal prefix matching.
"""
from __future__ import annotations
import argparse
import json
from collections import Counter
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Iterable
from anifilebert.tokenizer import AnimeTokenizer
from tools.annotate_dmhy_prefix_graph import (
build_prefix_trie,
matching_terminal_ordinal,
normalize_generated_tokens,
prefix_boundary_ok as prefix_boundary_ok,
)
from tools.dmhy_dataset import weak_label_filename
DEFAULT_DAG = Path("datasets/AnimeName/dmhy_prefix_dag.json")
DEFAULT_SOURCE_LIST = Path("datasets/AnimeName/dmhy_list.jsonl")
DEFAULT_PATCHES = Path("datasets/AnimeName/dmhy_prefix_dag.annotations.dag_full.jsonl")
DEFAULT_OUTPUT = Path("datasets/AnimeName/dmhy_weak.dag_full_expanded.jsonl")
@dataclass(frozen=True)
class Args:
dag: Path
source_list: Path
patches: Path
output: Path
manifest_output: Path
limit: int | None
preserve_i_labels: bool
strict_boundary: bool
def parse_args() -> Args:
parser = argparse.ArgumentParser(
description="Expand DMHY DAG terminal annotations across the full source-list"
)
parser.add_argument("--dag", type=Path, default=DEFAULT_DAG)
parser.add_argument("--source-list", type=Path, default=DEFAULT_SOURCE_LIST)
parser.add_argument("--patches", type=Path, default=DEFAULT_PATCHES)
parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT)
parser.add_argument(
"--manifest-output",
type=Path,
default=None,
help="Output manifest JSON; defaults to <output stem>.manifest.json",
)
parser.add_argument("--limit", type=int, default=None, help="Maximum source-list rows to scan")
parser.add_argument("--preserve-i-labels", action="store_true")
parser.add_argument(
"--strict-boundary",
action="store_true",
help="Require a separator boundary after the matched terminal prefix",
)
ns = parser.parse_args()
manifest_output = ns.manifest_output or ns.output.with_suffix(".manifest.json")
return Args(
dag=ns.dag,
source_list=ns.source_list,
patches=ns.patches,
output=ns.output,
manifest_output=manifest_output,
limit=None if ns.limit is None else max(0, ns.limit),
preserve_i_labels=ns.preserve_i_labels,
strict_boundary=ns.strict_boundary,
)
def load_json(path: Path) -> dict[str, Any]:
if not path.exists():
raise SystemExit(f"file not found: {path}")
try:
value = json.loads(path.read_text(encoding="utf-8"))
except json.JSONDecodeError as exc:
raise SystemExit(f"invalid JSON in {path}: {exc}") from exc
if not isinstance(value, dict):
raise SystemExit(f"invalid JSON schema in {path}: root must be object")
return value
def iter_jsonl(path: Path) -> Iterable[tuple[int, dict[str, Any]]]:
if not path.exists():
raise SystemExit(f"file not found: {path}")
with path.open("r", encoding="utf-8") as handle:
for line_number, line in enumerate(handle, start=1):
if not line.strip():
continue
try:
row = json.loads(line)
except json.JSONDecodeError as exc:
raise SystemExit(f"invalid JSON in {path}:{line_number}: {exc}") from exc
if isinstance(row, dict):
yield line_number, row
def terminal_id(terminal: dict[str, Any], fallback: int) -> str:
for key in ("terminal_id", "id", "node_id"):
value = terminal.get(key)
if value is not None:
return str(value)
return str(fallback)
def load_terminals(dag_path: Path) -> list[tuple[int, dict[str, Any], dict[str, Any]]]:
dag = load_json(dag_path)
terminals = dag.get("terminals")
if not isinstance(terminals, list):
raise SystemExit(f"invalid DAG schema in {dag_path}: missing terminals list")
selected: list[tuple[int, dict[str, Any], dict[str, Any]]] = []
for index, terminal in enumerate(terminals):
if not isinstance(terminal, dict):
continue
row = dict(terminal)
row["_terminal_id"] = terminal_id(row, index)
row["_terminal_index"] = index
if not str(row.get("prefix") or ""):
continue
selected.append((index, row, {}))
if not selected:
raise SystemExit(f"DAG has no prefix-bearing terminals: {dag_path}")
return selected
def load_patches(path: Path) -> tuple[dict[str, dict[str, Any]], Counter[str]]:
patches_by_terminal: dict[str, dict[str, Any]] = {}
patch_statuses: Counter[str] = Counter()
for _line_number, patch in iter_jsonl(path):
terminal_ids = patch.get("terminal_ids")
if not isinstance(terminal_ids, list):
terminal_ids = [patch.get("terminal_id")] if patch.get("terminal_id") is not None else []
clean_ids = [str(item) for item in terminal_ids if str(item).strip()]
status = str(patch.get("status") or ("fallback" if patch.get("fallback") else "ok"))
patch_statuses[status] += 1
for tid in clean_ids:
patches_by_terminal[tid] = patch
if not patches_by_terminal:
raise SystemExit(f"no terminal patches found in {path}")
return patches_by_terminal, patch_statuses
def matching_terminal_ordinal_relaxed(
value: str,
trie: Any,
selected: list[tuple[int, dict[str, Any], dict[str, Any]]],
*,
strict_boundary: bool,
) -> int | None:
node = trie
best: int | None = None
for char in value:
node = node.children.get(char)
if node is None:
break
for ordinal in node.terminal_ordinals:
if not strict_boundary:
best = ordinal
continue
prefix = str(selected[ordinal][1].get("prefix") or "")
if prefix_boundary_ok(value, prefix):
best = ordinal
return best
def row_from_match(
*,
filename: str,
source_line: int,
terminal: dict[str, Any],
patch: dict[str, Any],
tokenizer: AnimeTokenizer,
preserve_i_labels: bool,
) -> dict[str, Any] | None:
sample = weak_label_filename(filename, tokenizer)
if sample is None:
return None
tokens, labels = normalize_generated_tokens(
sample["tokens"],
sample["labels"],
preserve_i_labels=preserve_i_labels,
)
terminal_id_value = str(terminal["_terminal_id"])
unit_id = str(patch.get("unit_id") or terminal_id_value)
terminal_index = terminal["_terminal_index"]
source = str(patch.get("source") or "unknown")
fallback = bool(patch.get("fallback", False))
status = str(patch.get("status") or ("fallback" if fallback else "ok"))
episode_title_suffixes = patch.get("episode_title_suffixes") or []
media_suffixes = patch.get("media_suffixes") or []
title_candidates = patch.get("title_candidates") or []
return {
"file_id": f"prefix-dag-expanded:{unit_id}:{terminal_id_value}:{source_line}",
"filename": filename,
"tokens": tokens,
"labels": labels,
"terminal_id": terminal_id_value,
"terminal_index": terminal_index,
"unit_id": unit_id,
"source": source,
"needs_llm_review": fallback,
"episode_title_suffixes": episode_title_suffixes,
"media_suffixes": media_suffixes,
"title_candidates": title_candidates,
"annotations": {
"unit_id": unit_id,
"terminal_id": terminal_id_value,
"terminal_ids": [str(item) for item in patch.get("terminal_ids") or [terminal_id_value]],
"terminal_index": terminal_index,
"source": source,
"fallback": fallback,
"status": status,
"episode_title_suffixes": episode_title_suffixes,
"media_suffixes": media_suffixes,
"title_candidates": title_candidates,
"llm_label": patch.get("llm_label"),
"notes": patch.get("notes"),
},
}
def expand(args: Args) -> dict[str, Any]:
selected = load_terminals(args.dag)
patches_by_terminal, patch_statuses = load_patches(args.patches)
trie = build_prefix_trie(selected)
tokenizer = AnimeTokenizer()
input_rows = 0
matched_source_rows = 0
emitted_rows = 0
unmatched_rows = 0
weak_label_failed_rows = 0
patch_covered_rows = 0
unique_terminals_matched: set[str] = set()
status_counts: Counter[str] = Counter()
args.output.parent.mkdir(parents=True, exist_ok=True)
with args.output.open("w", encoding="utf-8", newline="\n") as output_handle:
for source_line, source_row in iter_jsonl(args.source_list):
if args.limit is not None and input_rows >= args.limit:
break
input_rows += 1
value = source_row.get("value")
if not isinstance(value, str) or not value.strip():
unmatched_rows += 1
status_counts["unmatched"] += 1
continue
ordinal = matching_terminal_ordinal_relaxed(
value,
trie,
selected,
strict_boundary=args.strict_boundary,
)
if ordinal is None:
unmatched_rows += 1
status_counts["unmatched"] += 1
continue
matched_source_rows += 1
terminal = selected[ordinal][1]
terminal_id_value = str(terminal["_terminal_id"])
unique_terminals_matched.add(terminal_id_value)
patch = patches_by_terminal.get(terminal_id_value)
if patch is None:
status_counts["missing_patch"] += 1
continue
row = row_from_match(
filename=value,
source_line=source_line,
terminal=terminal,
patch=patch,
tokenizer=tokenizer,
preserve_i_labels=args.preserve_i_labels,
)
if row is None:
weak_label_failed_rows += 1
status_counts["weak_label_failed"] += 1
continue
output_handle.write(json.dumps(row, ensure_ascii=False, separators=(",", ":")) + "\n")
emitted_rows += 1
patch_covered_rows += 1
status_counts[str(row["annotations"]["status"])] += 1
manifest = {
"dag": str(args.dag),
"source_list": str(args.source_list),
"patches": str(args.patches),
"output": str(args.output),
"input_rows": input_rows,
"matched_rows": matched_source_rows,
"output_rows": emitted_rows,
"unmatched_rows": unmatched_rows,
"weak_label_failed_rows": weak_label_failed_rows,
"patch_covered_rows": patch_covered_rows,
"unique_terminals_matched": len(unique_terminals_matched),
"status_counts": dict(sorted(status_counts.items())),
"patch_status_counts": dict(sorted(patch_statuses.items())),
}
args.manifest_output.parent.mkdir(parents=True, exist_ok=True)
args.manifest_output.write_text(
json.dumps(manifest, ensure_ascii=False, indent=2, sort_keys=True) + "\n",
encoding="utf-8",
)
return manifest
def main() -> None:
manifest = expand(parse_args())
print(json.dumps(manifest, ensure_ascii=False, indent=2, sort_keys=True))
if __name__ == "__main__":
main()
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