| |
| """Generate the staged ImageNet-v2 launch matrix without submitting jobs.""" |
|
|
| from __future__ import annotations |
|
|
| import argparse |
| import copy |
| import re |
| import sys |
| from collections import Counter |
| from dataclasses import asdict, dataclass |
| from pathlib import Path |
| from typing import Any |
|
|
| import yaml |
|
|
| SCRIPT_PATH = Path(__file__).resolve() |
| JOURNAL_ROOT = SCRIPT_PATH.parents[1] |
| GMNET_ROOT = JOURNAL_ROOT.parent |
| DEPLOY_ROOT = GMNET_ROOT / "depoly" |
| PROTOCOL_PATH = JOURNAL_ROOT / "configs/imagenet_v2_protocol.yaml" |
| BASE_TEMPLATE = Path("/nfs/ywang29/LongLive/deploy/jul11_vgp/j11_vgp01_base.yaml") |
| EXPECTED_RUN_ROOT = GMNET_ROOT / "runs/imagenet_v2" |
| CODE_MANIFEST_RELATIVE_PATH = "configs/imagenet_v2_code_manifest.json" |
|
|
| RESOURCE_KEYS = ( |
| "gpu_type", |
| "gpu_num", |
| "gpu_memory", |
| "cpu_num", |
| "memory", |
| "efa", |
| "priority", |
| "pytorchjob", |
| "custom_node_labels", |
| "volcano_queue", |
| ) |
| PROJECT_KEYS = ( |
| "project_name", |
| "project_support_alias", |
| "team", |
| "cost_team", |
| "cost_feature", |
| "cost_sub_feature", |
| "docker_image", |
| "mount", |
| ) |
| GENERATED_HEADER = ( |
| "# Generated by journal_exp/scripts/generate_deploy.py; do not edit.\n" |
| ) |
| VALID_STATUSES = {"ready", "held", "conditional"} |
| TASK_ID_PATTERN = re.compile(r"[a-z0-9_]+") |
|
|
|
|
| @dataclass(frozen=True) |
| class LaunchTask: |
| task_id: str |
| experiment: str |
| model: str |
| gate: str |
| seed: int |
| config_path: str |
| deploy_group: str |
| phase: str |
| role: str |
| depends_on: tuple[str, ...] |
| external_prerequisites: tuple[str, ...] |
| status: str |
| submission_allowed: bool |
| condition: str | None = None |
|
|
| @property |
| def deploy_path(self) -> str: |
| return f"{self.deploy_group}/{self.task_id}.yaml" |
|
|
| @property |
| def job_name(self) -> str: |
| return "gmnet-" + self.task_id.replace("_", "-") |
|
|
| @property |
| def output_dir(self) -> str: |
| return str(EXPECTED_RUN_ROOT / self.task_id) |
|
|
|
|
| def load_protocol() -> dict[str, Any]: |
| if not PROTOCOL_PATH.is_file(): |
| raise FileNotFoundError(f"protocol does not exist: {PROTOCOL_PATH}") |
| with PROTOCOL_PATH.open("r", encoding="utf-8") as handle: |
| protocol = yaml.safe_load(handle) |
| if not isinstance(protocol, dict): |
| raise ValueError("ImageNet-v2 protocol must be a mapping") |
| return protocol |
|
|
|
|
| def build_launch_tasks(protocol: dict[str, Any] | None = None) -> list[LaunchTask]: |
| protocol = load_protocol() if protocol is None else protocol |
| raw_tasks = protocol.get("tasks") |
| if not isinstance(raw_tasks, list): |
| raise ValueError("protocol tasks must be a list") |
|
|
| tasks: list[LaunchTask] = [] |
| for record in raw_tasks: |
| if not isinstance(record, dict): |
| raise ValueError("each protocol task must be a mapping") |
| tasks.append( |
| LaunchTask( |
| task_id=str(record["task_id"]), |
| experiment=str(record["experiment"]), |
| model=str(record["model"]), |
| gate=str(record["gate"]), |
| seed=int(record["seed"]), |
| config_path=str(record["config_path"]), |
| deploy_group=str(record["deploy_group"]), |
| phase=str(record["phase"]), |
| role=str(record["role"]), |
| depends_on=tuple(record.get("depends_on", [])), |
| external_prerequisites=tuple(record.get("external_prerequisites", [])), |
| status=str(record["status"]), |
| submission_allowed=bool(record["submission_allowed"]), |
| condition=record.get("condition"), |
| ) |
| ) |
| validate_protocol(protocol, tasks) |
| return tasks |
|
|
|
|
| def load_resolved_config(path: Path) -> dict[str, Any]: |
| """Load a task config through the same inheritance code used by training.""" |
|
|
| if str(JOURNAL_ROOT) not in sys.path: |
| sys.path.insert(0, str(JOURNAL_ROOT)) |
| from gmnet.config import load_config |
|
|
| return load_config(path) |
|
|
|
|
| def _require_config_value( |
| task: LaunchTask, |
| config: dict[str, Any], |
| dotted_key: str, |
| expected: object, |
| ) -> None: |
| value: object = config |
| for part in dotted_key.split("."): |
| if not isinstance(value, dict) or part not in value: |
| raise ValueError( |
| f"resolved config for {task.task_id} is missing {dotted_key}" |
| ) |
| value = value[part] |
| if value != expected: |
| raise ValueError( |
| f"resolved config mismatch for {task.task_id}: " |
| f"{dotted_key}={value!r}, expected {expected!r}" |
| ) |
|
|
|
|
| def validate_resolved_config(task: LaunchTask, config: dict[str, Any]) -> None: |
| """Ensure protocol labels describe the resolved training semantics.""" |
|
|
| expected_gate = ( |
| "smooth_clipped_self" |
| if task.gate == "smooth_clipped_self_fixed_c6" |
| else task.gate |
| ) |
| is_release_audit = task.role == "conditional_recipe_audit" |
| expected_recipe = ( |
| "release-readme-legacy-audit-only" |
| if is_release_audit |
| else "paper-supplementary-table8-v1" |
| ) |
| expected_epochs = 310 if is_release_audit else 300 |
| expected_drop_path = 0.0 if is_release_audit or task.model in {"s1", "s2"} else 0.02 |
|
|
| invariants = { |
| "recipe_id": expected_recipe, |
| "model.variant": task.model, |
| "model.gate_type": expected_gate, |
| "model.num_classes": 1000, |
| "model.drop_path_rate": expected_drop_path, |
| "data.dataset": "imagenet", |
| "data.num_classes": 1000, |
| "data.expected_train_samples": 1_281_167, |
| "data.expected_val_samples": 50_000, |
| "data.expected_manifest_sha256": str( |
| load_protocol()["canonical_data_manifest"]["manifest_sha256"] |
| ), |
| "train.epochs": expected_epochs, |
| "train.eval_interval": expected_epochs, |
| "train.official_validation_policy": "final_epoch_only", |
| "train.save_best_checkpoint": False, |
| "train.fail_on_nonfinite": True, |
| "train.strict_resume": True, |
| } |
| for dotted_key, expected in invariants.items(): |
| _require_config_value(task, config, dotted_key, expected) |
|
|
| patterns = config.get("optimizer", {}).get("no_weight_decay_patterns", []) |
| if not isinstance(patterns, list) or "raw_clip" not in patterns: |
| raise ValueError( |
| f"resolved config for {task.task_id} must exclude raw_clip from weight decay" |
| ) |
|
|
| is_smooth = task.gate in { |
| "smooth_clipped_self", |
| "smooth_clipped_self_fixed_c6", |
| } |
| if is_smooth: |
| _require_config_value(task, config, "model.smooth_clip_per_channel", False) |
| _require_config_value(task, config, "model.smooth_clip_init", 6.0) |
| _require_config_value(task, config, "model.smooth_clip_beta", 10.0) |
| _require_config_value( |
| task, |
| config, |
| "model.smooth_clip_trainable", |
| task.gate == "smooth_clipped_self", |
| ) |
|
|
| if task.task_id == "imv2_e0_s3_release_fullbn_seed0": |
| expected_bn = (True, True) |
| else: |
| expected_bn = (False, False) |
| _require_config_value(task, config, "model.f12_bn", expected_bn[0]) |
| _require_config_value(task, config, "model.second_dw_bn", expected_bn[1]) |
| _require_config_value(task, config, "model.projection_bn", True) |
|
|
|
|
| def resolved_config_summary(task: LaunchTask) -> dict[str, object]: |
| config = load_resolved_config(JOURNAL_ROOT / task.config_path) |
| model = config["model"] |
| return { |
| "recipe_id": config["recipe_id"], |
| "variant": model["variant"], |
| "gate_type": model["gate_type"], |
| "smooth_clip_trainable": model.get("smooth_clip_trainable"), |
| "epochs": config["train"]["epochs"], |
| "final_epoch_only": ( |
| config["train"]["official_validation_policy"] == "final_epoch_only" |
| ), |
| "raw_clip_zero_weight_decay": ( |
| "raw_clip" in config["optimizer"].get("no_weight_decay_patterns", []) |
| ), |
| } |
|
|
|
|
| def validate_protocol(protocol: dict[str, Any], tasks: list[LaunchTask]) -> None: |
| if protocol.get("schema_version") != 2: |
| raise ValueError("ImageNet-v2 protocol schema_version must be 2") |
| if Path(str(protocol.get("run_root"))) != EXPECTED_RUN_ROOT: |
| raise ValueError(f"protocol run_root must be {EXPECTED_RUN_ROOT}") |
| if len(tasks) != 21: |
| raise ValueError( |
| f"ImageNet-v2 protocol must contain 21 tasks, got {len(tasks)}" |
| ) |
|
|
| task_ids = [task.task_id for task in tasks] |
| if len(task_ids) != len(set(task_ids)): |
| raise ValueError("duplicate task IDs in ImageNet-v2 protocol") |
| task_id_set = set(task_ids) |
| if any(TASK_ID_PATTERN.fullmatch(task_id) is None for task_id in task_ids): |
| raise ValueError( |
| "ImageNet-v2 task IDs may contain only lowercase letters, digits, and underscores" |
| ) |
| job_names = [task.job_name for task in tasks] |
| if len(job_names) != len(set(job_names)): |
| raise ValueError("duplicate launchjob names in ImageNet-v2 protocol") |
|
|
| phases = protocol.get("phases", {}) |
| external = protocol.get("external_prerequisites", {}) |
| if not isinstance(external, dict): |
| raise ValueError("protocol external_prerequisites must be a mapping") |
| external_ids = set(external) |
| decision_rule_ids = { |
| str(rule.get("id")) |
| for rule in protocol.get("decision_rules", []) |
| if isinstance(rule, dict) |
| } |
| for prerequisite_id, prerequisite in external.items(): |
| if not isinstance(prerequisite, dict): |
| raise ValueError( |
| f"external prerequisite {prerequisite_id} must be a mapping" |
| ) |
| if prerequisite.get("decision_rule") not in decision_rule_ids: |
| raise ValueError( |
| f"external prerequisite {prerequisite_id} references an unknown decision rule" |
| ) |
| if prerequisite.get("required_state") != "passed": |
| raise ValueError( |
| f"external prerequisite {prerequisite_id} must require passed state" |
| ) |
| state = prerequisite.get("state") |
| if state not in {"pending", "passed", "failed"}: |
| raise ValueError( |
| f"external prerequisite {prerequisite_id} has invalid state {state!r}" |
| ) |
| if state == "passed": |
| evidence = prerequisite.get("evidence") |
| if not isinstance(evidence, str) or not Path(evidence).is_file(): |
| raise ValueError( |
| f"passed external prerequisite {prerequisite_id} lacks evidence" |
| ) |
| for task in tasks: |
| if not task.task_id.startswith("imv2_"): |
| raise ValueError(f"task ID lacks imv2 namespace: {task.task_id}") |
| if task.status not in VALID_STATUSES: |
| raise ValueError(f"invalid status for {task.task_id}: {task.status}") |
| if task.submission_allowed and task.status != "ready": |
| raise ValueError(f"only ready tasks may be submitted: {task.task_id}") |
| if task.phase not in phases: |
| raise ValueError(f"undefined phase for {task.task_id}: {task.phase}") |
| missing_dependencies = set(task.depends_on) - task_id_set |
| if missing_dependencies: |
| raise ValueError( |
| f"unknown dependencies for {task.task_id}: " |
| + ", ".join(sorted(missing_dependencies)) |
| ) |
| if task.task_id in task.depends_on: |
| raise ValueError(f"task depends on itself: {task.task_id}") |
| missing_external = set(task.external_prerequisites) - external_ids |
| if missing_external: |
| raise ValueError( |
| f"unknown external prerequisites for {task.task_id}: " |
| + ", ".join(sorted(missing_external)) |
| ) |
| if task.submission_allowed != (task.status == "ready"): |
| raise ValueError(f"ready/submission state mismatch for {task.task_id}") |
| if task.status == "conditional" and not task.condition: |
| raise ValueError(f"conditional task lacks condition: {task.task_id}") |
| config = JOURNAL_ROOT / task.config_path |
| if not config.is_file(): |
| raise FileNotFoundError(f"missing config for {task.task_id}: {config}") |
| validate_resolved_config(task, load_resolved_config(config)) |
|
|
| allowed = [task.task_id for task in tasks if task.submission_allowed] |
| expected_allowed = ["imv2_e0_s3_relu6_seed0"] |
| if allowed != expected_allowed: |
| raise ValueError( |
| "initial submission policy must allow only " + expected_allowed[0] |
| ) |
|
|
| confirmatory = [task for task in tasks if task.role.startswith("confirmatory_")] |
| gate_counts = Counter(task.gate for task in confirmatory) |
| expected_gate_counts = { |
| "relu6_self": 3, |
| "relu_self": 3, |
| "smooth_clipped_self": 3, |
| "relu6_only": 3, |
| "no_gate": 3, |
| } |
| if dict(gate_counts) != expected_gate_counts: |
| raise ValueError(f"confirmatory gate matrix mismatch: {dict(gate_counts)}") |
| smooth_seed0 = next( |
| task for task in tasks if task.task_id == "imv2_e3_s3_smooth_corrected_seed0" |
| ) |
| if smooth_seed0.external_prerequisites != ("smooth_local_pregate",): |
| raise ValueError( |
| "learned-smooth seed0 must require external smooth_local_pregate" |
| ) |
|
|
| primary = protocol.get("primary_analysis", {}) |
| if not isinstance(primary, dict): |
| raise ValueError("primary_analysis must be a mapping") |
| expected_control = "fixed_entry_gate_then_parallel_holm" |
| if ( |
| primary.get("alpha") != 0.05 |
| or primary.get("familywise_error_control") != expected_control |
| ): |
| raise ValueError( |
| "primary analysis must use a fixed entry gate followed by Holm " |
| "control at alpha 0.05" |
| ) |
| entry = primary.get("fixed_entry_gate", {}) |
| if ( |
| entry.get("id") != "h1_no_gate_material_loss" |
| or entry.get("candidate_gate") != "no_gate" |
| ): |
| raise ValueError("primary entry gate does not match the frozen protocol") |
| downstream = primary.get("downstream_holm_family", {}) |
| expected_hypotheses = [ |
| ("h2_relu6_only_noninferiority", "relu6_only"), |
| ("h3_relu_equivalence", "relu_self"), |
| ("h4_smooth_noninferiority", "smooth_clipped_self"), |
| ] |
| observed_hypotheses = [ |
| (hypothesis.get("id"), hypothesis.get("candidate_gate")) |
| for hypothesis in downstream.get("hypotheses", []) |
| ] |
| if observed_hypotheses != expected_hypotheses: |
| raise ValueError( |
| "primary downstream Holm hypotheses do not match the frozen protocol" |
| ) |
|
|
|
|
| def load_base_invariants() -> dict[str, object]: |
| if not BASE_TEMPLATE.is_file(): |
| raise FileNotFoundError(f"launch template does not exist: {BASE_TEMPLATE}") |
| with BASE_TEMPLATE.open("r", encoding="utf-8") as handle: |
| source = yaml.safe_load(handle) |
| required = (*RESOURCE_KEYS, *PROJECT_KEYS) |
| missing = [key for key in required if key not in source] |
| if missing: |
| raise ValueError(f"launch template is missing fields: {', '.join(missing)}") |
| return {key: copy.deepcopy(source[key]) for key in required} |
|
|
|
|
| def unlock_guard(task: LaunchTask) -> str | None: |
| if task.submission_allowed: |
| return None |
| variable = "GMNET_PROTOCOL_UNLOCK_TASK" |
| return ( |
| f'if [ "${{{variable}:-}}" != "{task.task_id}" ]; then ' |
| f'echo "Protocol guard denied {task.task_id}; set {variable}={task.task_id} ' |
| 'only after documented prerequisite review" >&2; exit 64; fi' |
| ) |
|
|
|
|
| def _guarded_command(task: LaunchTask, command: str) -> str: |
| guard = unlock_guard(task) |
| return command if guard is None else f"{guard}; {command}" |
|
|
|
|
| def build_command(task: LaunchTask, data_root: str) -> str: |
| assignments = ( |
| f"RUN_NAME={task.task_id}", |
| f"CONFIG_PATH={task.config_path}", |
| f"DATA_ROOT={data_root}", |
| f"OUTPUT_DIR={task.output_dir}", |
| f"SEED={task.seed}", |
| "NPROC_PER_NODE=8", |
| f"CODE_MANIFEST_PATH={CODE_MANIFEST_RELATIVE_PATH}", |
| ) |
| command = ( |
| f"cd {JOURNAL_ROOT} && " + " ".join(assignments) + " bash scripts/init_run.sh" |
| ) |
| return _guarded_command(task, command) |
|
|
|
|
| def build_launch_document( |
| task: LaunchTask, |
| invariants: dict[str, object], |
| data_root: str, |
| ) -> dict[str, object]: |
| document: dict[str, object] = {} |
| for key in RESOURCE_KEYS: |
| document[key] = copy.deepcopy(invariants[key]) |
| pre_run_event = ( |
| f"cd {JOURNAL_ROOT} && chmod +x ./scripts/*.sh && " |
| "INSTALL_DEV=0 bash ./scripts/setup_env.sh && " |
| "KEEP_ARCHIVE=0 bash ./scripts/stage_imagenet.sh full" |
| ) |
| document["script"] = { |
| "pre_run_event": _guarded_command(task, pre_run_event), |
| "command": build_command(task, data_root), |
| "jobs": [{"name": task.job_name}], |
| } |
| for key in PROJECT_KEYS: |
| document[key] = copy.deepcopy(invariants[key]) |
| return document |
|
|
|
|
| def dump_yaml(document: object) -> str: |
| body = yaml.safe_dump( |
| document, |
| sort_keys=False, |
| default_flow_style=False, |
| width=1_000_000, |
| ) |
| return GENERATED_HEADER + body |
|
|
|
|
| def _counts(tasks: list[LaunchTask], field: str) -> dict[str, int]: |
| counts = Counter(str(getattr(task, field)) for task in tasks) |
| return dict(sorted(counts.items())) |
|
|
|
|
| def build_task_matrix( |
| protocol: dict[str, Any], tasks: list[LaunchTask] |
| ) -> dict[str, object]: |
| records = [] |
| for task in tasks: |
| record = asdict(task) |
| record["depends_on"] = list(task.depends_on) |
| record["external_prerequisites"] = list(task.external_prerequisites) |
| record.update( |
| { |
| "deploy_path": task.deploy_path, |
| "job_name": task.job_name, |
| "eta_class": ">12h", |
| "runner": "imagenet_classification", |
| "data_root": str(protocol["data_root"]), |
| "output_dir": task.output_dir, |
| "resolved_config": resolved_config_summary(task), |
| } |
| ) |
| if record["condition"] is None: |
| del record["condition"] |
| records.append(record) |
|
|
| return { |
| "schema_version": 2, |
| "protocol_id": protocol["protocol_id"], |
| "protocol_source": str(PROTOCOL_PATH), |
| "generated_by": str(SCRIPT_PATH), |
| "source_template": str(BASE_TEMPLATE), |
| "policy": copy.deepcopy(protocol["policy"]), |
| "technical_validity": copy.deepcopy(protocol["technical_validity"]), |
| "external_prerequisites": copy.deepcopy(protocol["external_prerequisites"]), |
| "data_root": str(protocol["data_root"]), |
| "data_staging": copy.deepcopy(protocol["data_staging"]), |
| "canonical_data_uri": str(protocol["canonical_data_uri"]), |
| "canonical_data_manifest": copy.deepcopy(protocol["canonical_data_manifest"]), |
| "run_root": str(EXPECTED_RUN_ROOT), |
| "code_manifest": str(JOURNAL_ROOT / CODE_MANIFEST_RELATIVE_PATH), |
| "summary": { |
| "launch_yaml_count": len(tasks), |
| "submission_allowed_count": sum(task.submission_allowed for task in tasks), |
| "by_status": _counts(tasks, "status"), |
| "by_phase": _counts(tasks, "phase"), |
| "by_role": _counts(tasks, "role"), |
| "by_experiment": _counts(tasks, "experiment"), |
| }, |
| "decision_rules": copy.deepcopy(protocol.get("decision_rules", [])), |
| "primary_analysis": copy.deepcopy(protocol["primary_analysis"]), |
| "secondary_analysis": copy.deepcopy(protocol["secondary_analysis"]), |
| "tasks": records, |
| } |
|
|
|
|
| def expected_files() -> dict[Path, str]: |
| protocol = load_protocol() |
| tasks = build_launch_tasks(protocol) |
| invariants = load_base_invariants() |
| data_root = str(protocol["data_root"]) |
|
|
| files: dict[Path, str] = {} |
| for task in tasks: |
| document = build_launch_document(task, invariants, data_root) |
| for key in (*RESOURCE_KEYS, *PROJECT_KEYS): |
| if document[key] != invariants[key]: |
| raise AssertionError(f"{task.task_id} changed invariant field {key}") |
| files[DEPLOY_ROOT / task.deploy_path] = dump_yaml(document) |
| files[DEPLOY_ROOT / "task_matrix.yaml"] = dump_yaml( |
| build_task_matrix(protocol, tasks) |
| ) |
| return files |
|
|
|
|
| def find_stale_generated_files(expected_paths: set[Path]) -> list[Path]: |
| stale = [] |
| if not DEPLOY_ROOT.is_dir(): |
| return stale |
| for path in DEPLOY_ROOT.rglob("*.yaml"): |
| if path in expected_paths or not path.is_file(): |
| continue |
| try: |
| generated = path.read_text(encoding="utf-8").startswith(GENERATED_HEADER) |
| except UnicodeDecodeError: |
| generated = False |
| if generated: |
| stale.append(path) |
| return sorted(stale) |
|
|
|
|
| def write_files(files: dict[Path, str]) -> list[Path]: |
| for path, content in files.items(): |
| path.parent.mkdir(parents=True, exist_ok=True) |
| if path.exists() and path.read_text(encoding="utf-8") == content: |
| continue |
| path.write_text(content, encoding="utf-8") |
|
|
| stale = find_stale_generated_files(set(files)) |
| for path in stale: |
| path.unlink() |
| for directory in sorted(DEPLOY_ROOT.rglob("*"), reverse=True): |
| if directory.is_dir() and not any(directory.iterdir()): |
| directory.rmdir() |
| return stale |
|
|
|
|
| def check_files(files: dict[Path, str]) -> list[str]: |
| errors = [] |
| for path, expected in files.items(): |
| if not path.is_file(): |
| errors.append(f"missing: {path}") |
| continue |
| actual = path.read_text(encoding="utf-8") |
| if actual != expected: |
| errors.append(f"stale: {path}") |
| continue |
| parsed = yaml.safe_load(actual) |
| if path.name != "task_matrix.yaml": |
| jobs = parsed.get("script", {}).get("jobs", []) |
| if len(jobs) != 1: |
| errors.append(f"expected one job: {path}") |
| errors.extend( |
| f"stale generated file: {path}" |
| for path in find_stale_generated_files(set(files)) |
| ) |
| return errors |
|
|
|
|
| def parse_args() -> argparse.Namespace: |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument( |
| "--check", |
| action="store_true", |
| help="verify generated files without modifying them", |
| ) |
| return parser.parse_args() |
|
|
|
|
| def main() -> int: |
| args = parse_args() |
| files = expected_files() |
| launch_count = len(files) - 1 |
| if args.check: |
| errors = check_files(files) |
| if errors: |
| print("\n".join(errors), file=sys.stderr) |
| return 1 |
| print( |
| f"Validated {launch_count} ImageNet-v2 launch YAML files " |
| "and task_matrix.yaml" |
| ) |
| return 0 |
| removed = write_files(files) |
| print( |
| f"Generated {launch_count} ImageNet-v2 launch YAML files under " |
| f"{DEPLOY_ROOT}; removed {len(removed)} stale generated YAML files" |
| ) |
| return 0 |
|
|
|
|
| if __name__ == "__main__": |
| raise SystemExit(main()) |
|
|