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Run the CPU program suite against a threshold-computer variant.
Loads weights, instantiates GenericThresholdCPU, runs each program from
cpu_programs.SUITE, and verifies expected memory contents at HALT.
Usage:
python test_cpu.py # default: 1KB variant, fast
python test_cpu.py --model neural_computer.safetensors # 64KB canonical, slow
python test_cpu.py --only fib,sum_n # subset of suite
"""
from __future__ import annotations
import argparse
import os
import sys
import time
from pathlib import Path
import torch
from safetensors import safe_open
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from eval_all import GenericThresholdCPU, get_manifest
from cpu_programs import SUITE
def load_tensors(path: Path):
out = {}
with safe_open(str(path), framework="pt") as f:
for name in f.keys():
out[name] = f.get_tensor(name).float()
return out
def run_program(cpu: GenericThresholdCPU, mem, max_cycles: int):
addr_mask = (1 << cpu.addr_bits) - 1
state = {
"pc": 0,
"regs": [0] * 4,
"flags": [0] * 4,
"mem": list(mem),
"halted": False,
"sp": addr_mask,
}
t0 = time.perf_counter()
final, cycles = cpu.run(state, max_cycles=max_cycles)
return final, cycles, time.perf_counter() - t0
def check_expected(final, expected: dict) -> tuple[bool, list[str]]:
failures = []
for addr, want in expected.items():
got = final["mem"][addr]
if got != want:
failures.append(f"M[0x{addr:04X}] = {got} (expected {want})")
return (len(failures) == 0), failures
def main() -> int:
parser = argparse.ArgumentParser(description="Run the CPU program suite")
parser.add_argument(
"--model", type=str,
default=os.path.join(os.path.dirname(__file__),
"variants", "neural_computer8_small.safetensors"),
help="Path to .safetensors variant",
)
parser.add_argument(
"--only", type=str, default="",
help="Comma-separated subset of program names to run",
)
args = parser.parse_args()
print(f"Loading {args.model}")
tensors = load_tensors(Path(args.model))
manifest = get_manifest(tensors)
print(f"Manifest: data={manifest['data_bits']}-bit, addr={manifest['addr_bits']}-bit, "
f"mem={manifest['memory_bytes']}B")
if manifest["memory_bytes"] < 256:
print(f"ERROR: variant has {manifest['memory_bytes']}B memory; "
f"the suite needs at least 256B (scratchpad).")
return 2
cpu = GenericThresholdCPU(tensors)
only = set(s.strip() for s in args.only.split(",") if s.strip())
print()
print("=" * 80)
print(f" CPU PROGRAM SUITE ({manifest['memory_bytes']}B mem, {manifest['data_bits']}-bit ALU)")
print("=" * 80)
pass_count = 0
fail_count = 0
skip_count = 0
for name, builder in SUITE:
if only and name not in only:
skip_count += 1
continue
try:
mem, expected, max_cycles, desc = builder(manifest["memory_bytes"])
except Exception as e:
print(f" {name:18} BUILD ERROR: {e}")
fail_count += 1
continue
if len(mem) != manifest["memory_bytes"]:
print(f" {name:18} SKIP (program built {len(mem)}B, "
f"variant has {manifest['memory_bytes']}B)")
skip_count += 1
continue
final, cycles, elapsed = run_program(cpu, mem, max_cycles)
ok, failures = check_expected(final, expected)
if ok and not final["halted"]:
ok = False
failures.append(f"did not HALT within {max_cycles} cycles")
status = "PASS" if ok else "FAIL"
if ok:
pass_count += 1
else:
fail_count += 1
print(f" {name:18} {status} ({cycles:>3} cyc, {elapsed:>5.2f}s) {desc}")
if not ok:
for f in failures[:6]:
print(f" - {f}")
print()
print("=" * 80)
total = pass_count + fail_count
print(f" PASS: {pass_count}/{total} FAIL: {fail_count}/{total} SKIP: {skip_count}")
return 0 if fail_count == 0 else 1
if __name__ == "__main__":
sys.exit(main())
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