1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
|
#!/usr/bin/env python3
"""Run the anonymous KAFT MVP from the command line."""
from __future__ import annotations
import argparse
import pandas as pd
from kaft_mvp import MVPConfig, run_mvp
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--device", default="cpu")
parser.add_argument("--seeds", default="0,1,2")
parser.add_argument("--epochs", type=int, default=200)
parser.add_argument("--diagnostic-epochs", type=int, default=100)
parser.add_argument("--output-dir", default="artifacts")
args = parser.parse_args()
seeds = tuple(int(value) for value in args.seeds.split(","))
config = MVPConfig(
seeds=seeds,
epochs=args.epochs,
diagnostic_epochs=args.diagnostic_epochs,
device=args.device,
)
payload = run_mvp(config=config, output_dir=args.output_dir)
print("\nBP versus KAFT")
print(pd.DataFrame(payload["summary"]).to_string(index=False))
diagnostic = pd.DataFrame(
[
{
"seed": row["seed"],
"all_weight_grads_zero": row[
"all_weight_gradients_exact_zero"
],
"output_adjacent_error": row[
"output_adjacent_error_frobenius"
],
"hidden_probe_percent": 100.0
* row["standardized_penultimate_probe_accuracy"],
}
for row in payload["gradient_diagnostics"]
]
)
print("\n10-layer BP diagnostic")
print(diagnostic.to_string(index=False))
print(f"\nArtifacts written to {args.output_dir}/")
if __name__ == "__main__":
main()
|
