refactoring training spc setup and benchmarking

engine/telemetry/wandb.py

@@ -0,0 +1,98 @@
+from __future__ import annotations
+
+from typing import Any, Callable, Iterable, Mapping
+
+
+def get_wandb_module():
+    try:
+        import wandb
+
+        return wandb
+    except ImportError:
+        return None
+
+
+def _require_wandb():
+    wandb = get_wandb_module()
+    if wandb is None:
+        raise ImportError("wandb is required for this workflow")
+    return wandb
+
+
+def init_run(
+    *,
+    mode: str,
+    project: str | None = None,
+    config: Mapping[str, Any] | None = None,
+    name: str | None = None,
+    tags: Iterable[str] | None = None,
+    group: str | None = None,
+    sweep_mode: bool = False,
+):
+    wandb = _require_wandb()
+    kwargs: dict[str, Any] = {"mode": mode}
+    if group:
+        kwargs["group"] = group
+    if sweep_mode:
+        run = wandb.init(**kwargs)
+        if name and run is not None:
+            run.name = name
+        return run
+
+    init_kwargs = dict(kwargs)
+    init_kwargs["project"] = project
+    if config is not None:
+        init_kwargs["config"] = dict(config)
+    if name:
+        init_kwargs["name"] = name
+    if tags:
+        init_kwargs["tags"] = list(tags)
+    return wandb.init(**init_kwargs)
+
+
+def finish_run() -> None:
+    wandb = get_wandb_module()
+    if wandb is not None and wandb.run is not None:
+        wandb.finish()
+
+
+def current_config() -> dict[str, Any]:
+    wandb = get_wandb_module()
+    if wandb is None or wandb.run is None:
+        return {}
+    return {key: wandb.config[key] for key in wandb.config.keys()}
+
+
+def update_run_config(config: Mapping[str, Any]) -> None:
+    wandb = get_wandb_module()
+    if wandb is None or wandb.run is None:
+        return
+    try:
+        wandb.config.update(dict(config), allow_val_change=True)
+    except TypeError:
+        wandb.config.update(dict(config))
+
+
+def log_metrics(metrics: Mapping[str, Any], *, step: int) -> None:
+    wandb = get_wandb_module()
+    if wandb is None or wandb.run is None:
+        return
+    wandb.log(dict(metrics), step=step)
+
+
+def update_summary(metrics: Mapping[str, Any]) -> None:
+    wandb = get_wandb_module()
+    if wandb is None or wandb.run is None:
+        return
+    for key, value in metrics.items():
+        wandb.run.summary[key] = value
+
+
+def run_agent(
+    sweep_id: str,
+    fn: Callable[[], None],
+    *,
+    count: int | None = None,
+) -> None:
+    wandb = _require_wandb()
+    wandb.agent(sweep_id, function=fn, count=count)