Extract giant train/new-run's CLI override mapping into a table-driven function (issues.md Issues 3 & 4)

train()'s ~140-line hand-written flag->config translation (three different
ad hoc "more specific flag wins" patterns) and new_run()'s near-verbatim
copy are replaced by a shared FlagSpec/FLAG_SPECS table and
overrides_from_flags() in config.py, reused by both commands. This makes
the override/precedence logic directly unit-testable without CliRunner,
closing coverage gaps that had zero tests (e.g. --emb-dim/--conditioning
dual-axis fan-out, three of four WGAN knob legs, --stage2-generator
overriding --mode, router's stage1-only asymmetry).

No CLI flags, help text, or precedence semantics changed --
`giant train --help`/`giant new-run --help` are byte-identical before and
after, and all previously-passing CliRunner tests still pass unmodified.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

tests/test_cli_train_overrides.py

@@ -94,3 +94,83 @@ def test_wgan_knobs_split_per_stage(monkeypatch, tmp_path):
     assert cfg["stage1_model"]["wgan"]["gp_weight"] == 10.0
     assert cfg["stage2_model"]["wgan"]["n_critic"] == 5
     assert cfg["stage2_model"]["wgan"]["gp_weight"] == 2.5
+
+
+def test_batch_size_invalid_string_errors(monkeypatch, tmp_path):
+    monkeypatch.setattr(cli, "run_train_job", lambda *a, **kw: None)
+    result = runner.invoke(
+        cli.app,
+        ["train", "dummy.parquet", "--out", str(tmp_path / "run"), "--batch-size", "not-a-number"],
+    )
+    assert result.exit_code == 1
+    assert "--batch-size must be an integer or 'auto'" in result.output
+
+
+def test_out_dir_resolution_prefers_explicit_out_over_resume(monkeypatch, tmp_path):
+    captured: dict = {}
+
+    def _fake_run_train_job(*, data, cfg, out_dir, **kwargs):
+        captured["out_dir"] = out_dir
+
+    monkeypatch.setattr(cli, "run_train_job", _fake_run_train_job)
+
+    resume_dir = tmp_path / "resumed_run"
+    resume_dir.mkdir()
+    (resume_dir / "last.pt").touch()
+    explicit_out = tmp_path / "explicit_run"
+
+    result = runner.invoke(
+        cli.app,
+        ["train", "dummy.parquet", "--out", str(explicit_out), "--resume", str(resume_dir / "last.pt")],
+    )
+    assert result.exit_code == 0, result.output
+    assert captured["out_dir"] == explicit_out
+
+
+def test_out_dir_resolution_falls_back_to_resume_parent(monkeypatch, tmp_path):
+    captured: dict = {}
+
+    def _fake_run_train_job(*, data, cfg, out_dir, **kwargs):
+        captured["out_dir"] = out_dir
+
+    monkeypatch.setattr(cli, "run_train_job", _fake_run_train_job)
+
+    resume_dir = tmp_path / "resumed_run"
+    resume_dir.mkdir()
+    (resume_dir / "last.pt").touch()
+
+    result = runner.invoke(cli.app, ["train", "dummy.parquet", "--resume", str(resume_dir / "last.pt")])
+    assert result.exit_code == 0, result.output
+    assert captured["out_dir"] == resume_dir
+
+
+def test_out_dir_resolution_defaults_when_neither_out_nor_resume_given(monkeypatch, tmp_path):
+    captured: dict = {}
+
+    def _fake_run_train_job(*, data, cfg, out_dir, **kwargs):
+        captured["out_dir"] = out_dir
+
+    monkeypatch.setattr(cli, "run_train_job", _fake_run_train_job)
+    monkeypatch.chdir(tmp_path)
+
+    result = runner.invoke(cli.app, ["train", "dummy.parquet"])
+    assert result.exit_code == 0, result.output
+    assert captured["out_dir"] == Path("checkpoints") / cli.gconfig.default_out_dir_name(cli.gconfig.DEFAULT_CONFIG)
+
+
+def test_batch_size_auto_estimates_and_echoes(monkeypatch, tmp_path):
+    captured: dict = {}
+
+    def _fake_run_train_job(*, data, cfg, out_dir, num_workers, **kwargs):
+        captured["batch_size"] = cfg["train"]["batch_size"]
+
+    monkeypatch.setattr(cli, "run_train_job", _fake_run_train_job)
+    monkeypatch.setattr(cli.gconfig, "estimate_batch_size", lambda hidden_dim, n_blocks, device: 123)
+
+    result = runner.invoke(
+        cli.app,
+        ["train", "dummy.parquet", "--out", str(tmp_path / "run"), "--batch-size", "auto"],
+    )
+    assert result.exit_code == 0, result.output
+    assert captured["batch_size"] == 123
+    assert "batch_size: 123 (auto-estimated from free GPU memory)" in result.output