29 lines
1.1 KiB
Python
29 lines
1.1 KiB
Python
"""Reconstruct regimes_e4b.pt from the exp4_e4b.log table (the scan's
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torch.save crashed on a relative path; the printed table is complete).
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Provenance note stored in the tensor dict: jbar from 150/256 prompts."""
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import re
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import torch
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sensor, motor, persist, content = [], [], [], []
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pat = re.compile(
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r"^L\s*(\d+) \| ([\d.]+)\s*#* *\| ([\d.]+)\s*#* *\| ([\d.]+) \| ([\d.]+)")
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for line in open("results/exp4_e4b.log"):
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m = pat.match(line.strip())
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if m:
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_, s, mo, p, c = m.groups()
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sensor.append(float(s))
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motor.append(float(mo))
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persist.append(float(p))
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content.append(float(c))
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assert len(sensor) == 42, len(sensor)
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torch.save({"sensor": torch.tensor(sensor), "motor": torch.tensor(motor),
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"persist": torch.tensor(persist),
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"content": torch.tensor(content),
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"note": "reconstructed from exp4_e4b.log; jbar 150/256 prompts"},
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"results/regimes_e4b.pt")
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print("saved 42 layers")
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print("sensor peak: L%d = %.2f" % (sensor.index(max(sensor)), max(sensor)))
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print("motor >=0.1 from: L%d" % next(
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i for i, v in enumerate(motor) if v >= 0.1))
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