Export every recorded input, not only the ones that vary
`export runs` dropped a `param.*` column whose value was constant across the exported runs, so a downstream filter broke depending on which runs the selection happened to hold. Every input the selection recorded is a column now; `--params` still narrows it to a sweep's axis. The metrics default is unchanged. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_019Hra4ndWMCLU5F3KjUuVAc
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@@ -422,25 +422,6 @@ def _dig(record: dict[str, Any], path: str) -> Any:
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return value
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def _varying(runs: list[Run]) -> list[str]:
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"""The inputs that differ across these runs — the axis of a sweep.
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What a reader comparing arms wants as columns, compared leaf by leaf: two
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configurations differing in one field give that field as a column rather
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than two blobs that are not the same. Under two runs nothing can differ,
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and a table of one run with none of its inputs in it is not worth reading,
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so all of them are kept.
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"""
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keys = sorted({path for run in runs for path, _ in _leaves(run.params)})
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if len(runs) < 2:
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return keys
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return [
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key
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for key in keys
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if len({json.dumps(_dig(run.params, key), sort_keys=True) for run in runs}) > 1
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]
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def _scored(runs: list[Run]) -> list[str]:
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"""A run's final numbers: every number its declared outputs carry, however
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deep it sits. A flag is not a number, and neither is a label."""
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@@ -557,9 +538,9 @@ def export_runs(
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"""One row per run: what it was given, what it scored, what code it ran.
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The arm-comparison table. Inputs are columns rather than one JSON blob —
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by default the ones that vary across the selection, which is the sweep
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axis; ``params`` names them instead. ``metrics`` narrows the final numbers
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to a few of a run's declared outputs.
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every input the selection recorded, so the schema is the same whichever
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runs are asked for; ``params`` narrows it. ``metrics`` narrows the final
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numbers to a few of a run's declared outputs.
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Both take dotted paths into a record a node returned:
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``metrics=final_metrics.train_loss,test_metrics.known.perfect`` selects
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@@ -567,7 +548,9 @@ def export_runs(
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depth.
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"""
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runs = _selected(session, flow, status, group, ids, since, until)
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inputs = [part for part in params.split(",") if part] or _varying(runs)
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inputs = [part for part in params.split(",") if part] or sorted(
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{path for run in runs for path, _ in _leaves(run.params)}
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)
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scores = [part for part in metrics.split(",") if part] or _scored(runs)
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columns = [
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*RUN_COLUMNS,
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@@ -1394,7 +1394,7 @@ def add_parsers(subparsers: Any) -> None:
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metavar="A,B",
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help=(
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"the inputs to put in columns, dotted into a record "
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"(default: the ones that vary)"
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"(default: every input the runs recorded)"
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),
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)
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sub.add_argument(
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@@ -428,9 +428,9 @@ class Client:
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) -> list[dict[str, Any]]:
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"""One row per run: its inputs as columns, its final numbers, its code.
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The arm-comparison table. The inputs kept are the ones that vary
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across the selection unless ``params`` names them, which is the axis a
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sweep is read along.
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The arm-comparison table. Every input the selection recorded is a
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column, so the schema does not depend on which runs were asked for;
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``params`` narrows it to the axis a sweep is read along.
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"""
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query: dict[str, Any] = {}
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if params:
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