diff --git a/giant/cli.py b/giant/cli.py index fb2b090..6636d40 100644 --- a/giant/cli.py +++ b/giant/cli.py @@ -1,9 +1,12 @@ from collections import Counter +from datetime import datetime, timezone from enum import Enum from pathlib import Path from typing import Optional +import uuid as uuid_mod import numpy as np +import yaml import torch import typer from typing_extensions import Annotated @@ -39,6 +42,46 @@ from giant.sample import sample_flow app = typer.Typer(no_args_is_help=True) +_CEPH_PREDICTIONS = Path("/ceph/lbogner/geant_steps/predictions") + + +def _resolve_prediction_output( + data: Path, out: Path | None +) -> tuple[Path, Path, str]: + """Return (out_path, resolved_dataset_path, pred_uuid). + + When *out* is None the output path is derived from *data*: + - under /ceph/ → fixed central store with a UUID filename + - elsewhere → sibling of *data* with a UUID filename + """ + dataset_path = data.resolve() + pred_uuid = str(uuid_mod.uuid4()) + if out is None: + if str(dataset_path).startswith("/ceph/"): + out = _CEPH_PREDICTIONS / f"{pred_uuid}.parquet" + else: + out = data.parent / f"{pred_uuid}.parquet" + return out, dataset_path, pred_uuid + + +def _write_prediction_ref( + checkpoint: Path, + pred_uuid: str, + out: Path, + dataset_path: Path, +) -> Path: + """Write a YAML sidecar in the checkpoint directory and return its path.""" + ref = { + "prediction_id": pred_uuid, + "output": str(out), + "dataset": str(dataset_path), + "checkpoint": str(checkpoint.resolve()), + "timestamp": datetime.now(timezone.utc).isoformat(), + } + ref_path = checkpoint.parent / f"{pred_uuid}.yaml" + ref_path.write_text(yaml.dump(ref, default_flow_style=False, sort_keys=False)) + return ref_path + @app.callback() def _main() -> None: @@ -331,12 +374,8 @@ def predict( gconfig.warn_if_checkpoint_config_mismatch(checkpoint) # --- Output path --- - if out is None: - stem = data.stem if data.is_file() else data.name - suffix = ( - "_predicted_local.parquet" if coord == Coord.local else "_predicted.parquet" - ) - out = data.parent / f"{stem}{suffix}" + out, dataset_path, pred_uuid = _resolve_prediction_output(data, out) + out.parent.mkdir(parents=True, exist_ok=True) typer.echo(f"output: {out}") # --- Stream input, generate predictions, write output --- @@ -494,6 +533,9 @@ def predict( if writer is not None: writer.close() + ref_path = _write_prediction_ref(checkpoint, pred_uuid, out, dataset_path) + typer.echo(f"reference: {ref_path}") + if skipped: codes = ", ".join( f"{pdg} ({count})" for pdg, count in sorted(unknown_pdg_counts.items()) diff --git a/pyproject.toml b/pyproject.toml index e6935e6..4e93ee0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -10,6 +10,7 @@ dependencies = [ "pyarrow>=16,<25", "tqdm>=4.60,<5", "typer>=0.12,<1", + "pyyaml>=6,<7", ] [project.optional-dependencies] diff --git a/tests/test_cli_predict.py b/tests/test_cli_predict.py new file mode 100644 index 0000000..be501ca --- /dev/null +++ b/tests/test_cli_predict.py @@ -0,0 +1,131 @@ +import uuid + +import yaml + +from giant.cli import _CEPH_PREDICTIONS, _resolve_prediction_output, _write_prediction_ref + + +# --------------------------------------------------------------------------- +# _resolve_prediction_output +# --------------------------------------------------------------------------- + + +def test_non_ceph_path_goes_to_data_parent(tmp_path): + data = tmp_path / "pools" / "pbwo4" / "full.manifest" + out, dataset_path, pred_uuid = _resolve_prediction_output(data, None) + + assert out.parent == data.parent + assert out.name == f"{pred_uuid}.parquet" + assert dataset_path == data.resolve() + + +def test_ceph_path_goes_to_central_store(tmp_path, monkeypatch): + # Patch resolve() so /ceph/... exists on any machine running the tests. + ceph_data = _CEPH_PREDICTIONS.parent / "pools" / "pbwo4" / "full.manifest" + monkeypatch.setattr( + "giant.cli.Path.resolve", + lambda self: ceph_data if self == ceph_data else self.absolute(), + ) + out, _, pred_uuid = _resolve_prediction_output(ceph_data, None) + + assert out.parent == _CEPH_PREDICTIONS + assert out.name == f"{pred_uuid}.parquet" + + +def test_explicit_out_is_used_as_is(tmp_path): + data = tmp_path / "data.parquet" + explicit = tmp_path / "my_output.parquet" + out, _, _ = _resolve_prediction_output(data, explicit) + + assert out == explicit + + +def test_uuid_is_valid(tmp_path): + data = tmp_path / "data.parquet" + _, _, pred_uuid = _resolve_prediction_output(data, None) + parsed = uuid.UUID(pred_uuid) + assert parsed.version == 4 + + +def test_each_call_produces_a_distinct_uuid(tmp_path): + data = tmp_path / "data.parquet" + _, _, uuid1 = _resolve_prediction_output(data, None) + _, _, uuid2 = _resolve_prediction_output(data, None) + assert uuid1 != uuid2 + + +def test_dataset_path_is_resolved(tmp_path): + data = tmp_path / "data.parquet" + _, dataset_path, _ = _resolve_prediction_output(data, None) + assert dataset_path.is_absolute() + + +# --------------------------------------------------------------------------- +# _write_prediction_ref +# --------------------------------------------------------------------------- + + +def test_ref_file_created_in_checkpoint_dir(tmp_path): + ckpt_dir = tmp_path / "checkpoints" / "run1" + ckpt_dir.mkdir(parents=True) + checkpoint = ckpt_dir / "best.pt" + checkpoint.touch() + + out = tmp_path / "predictions" / "abc.parquet" + dataset = tmp_path / "pools" / "pbwo4" / "full.manifest" + pred_uuid = str(uuid.uuid4()) + + ref_path = _write_prediction_ref(checkpoint, pred_uuid, out, dataset) + + assert ref_path == ckpt_dir / f"{pred_uuid}.yaml" + assert ref_path.exists() + + +def test_ref_yaml_contains_expected_fields(tmp_path): + ckpt_dir = tmp_path / "checkpoints" + ckpt_dir.mkdir() + checkpoint = ckpt_dir / "best.pt" + checkpoint.touch() + + out = tmp_path / "pred.parquet" + dataset = tmp_path / "full.manifest" + pred_uuid = str(uuid.uuid4()) + + ref_path = _write_prediction_ref(checkpoint, pred_uuid, out, dataset) + data = yaml.safe_load(ref_path.read_text()) + + assert data["prediction_id"] == pred_uuid + assert data["output"] == str(out) + assert data["dataset"] == str(dataset) + assert data["checkpoint"] == str(checkpoint.resolve()) + assert "timestamp" in data + + +def test_ref_timestamp_is_iso_format(tmp_path): + from datetime import datetime + + ckpt_dir = tmp_path / "checkpoints" + ckpt_dir.mkdir() + checkpoint = ckpt_dir / "best.pt" + checkpoint.touch() + + pred_uuid = str(uuid.uuid4()) + ref_path = _write_prediction_ref(checkpoint, pred_uuid, tmp_path / "p.parquet", tmp_path / "d") + data = yaml.safe_load(ref_path.read_text()) + + # Must parse without error and be timezone-aware (UTC). + ts = datetime.fromisoformat(data["timestamp"]) + assert ts.tzinfo is not None + + +def test_ref_checkpoint_path_is_absolute(tmp_path): + ckpt_dir = tmp_path / "checkpoints" + ckpt_dir.mkdir() + checkpoint = ckpt_dir / "best.pt" + checkpoint.touch() + + pred_uuid = 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