ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter8/speech-sft-experiment/test_experiment.py

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+import importlib.util
+from pathlib import Path
+
+import torch
+
+
+HERE = Path(__file__).parent
+
+
+def load(name):
+    spec = importlib.util.spec_from_file_location(name, HERE / f"{name}.py")
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    return module
+
+
+def test_sesame_tag_categories_are_explicit():
+    sesame = load("run_sesame")
+    assert sesame.category("hello <laughs> there") == "laugh"
+    assert sesame.category("hello <giggle> there") == "giggle"
+    assert sesame.category("hello <sighs> there") == "sigh"
+    assert sesame.category("hello there") == "neutral"
+
+
+def test_orpheus_collator_masks_label_padding():
+    orpheus = load("run_orpheus")
+    rows = [
+        {"input_ids": [1, 2], "labels": [1, 2], "attention_mask": [1, 1]},
+        {"input_ids": [3], "labels": [3], "attention_mask": [1]},
+    ]
+    batch = orpheus.PadCollator(9)(rows)
+    assert batch["input_ids"].tolist() == [[1, 2], [3, 9]]
+    assert batch["labels"].tolist() == [[1, 2], [3, -100]]
+    assert batch["attention_mask"].tolist() == [[1, 1], [1, 0]]
+
+
+def test_sesame_collator_stacks_all_model_inputs():
+    sesame = load("run_sesame")
+    rows = [{"input_ids": torch.tensor([1, 2]), "labels": torch.tensor([3, 4])}] * 2
+    batch = sesame.TensorCollator()(rows)
+    assert batch["input_ids"].shape == (2, 2)
+    assert batch["labels"].shape == (2, 2)
+
+
+def test_sha256_is_stable(tmp_path):
+    analysis = load("analyze_campaign")
+    path = tmp_path / "artifact"
+    path.write_bytes(b"experiment-8-6")
+    assert analysis.sha256(path) == "b07a691b33e493299473b6323258c9d643b2981d6de43e8c8adc3c4edc222d15"