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ea8c728 | 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 | """Evaluator for matrix multiplication tensor decomposition (n=2, m=4, p=5)."""
import subprocess, sys, json
BENCHMARK = 32 # benchmark rank
def evaluate(program_path):
script = f"""
import json, sys, os, time
import numpy as np
sys.path.insert(0, os.path.dirname(r'{program_path}'))
module_name = os.path.splitext(os.path.basename(r'{program_path}'))[0]
start = time.time()
try:
program = __import__(module_name)
decomposition, n, m, p, loss, rank = program.run()
except Exception as e:
print(json.dumps({{"error": str(e)}})); sys.exit(0)
eval_time = time.time() - start
U, V, W = decomposition
U, V, W = np.array(U), np.array(V), np.array(W)
if U.shape != (n*m, rank) or V.shape != (m*p, rank) or W.shape != (n*p, rank):
print(json.dumps({{"error": f"bad shapes U={{U.shape}} V={{V.shape}} W={{W.shape}}"}})); sys.exit(0)
T = np.zeros((n*m, m*p, n*p))
for i in range(n):
for j in range(m):
for k in range(p):
T[i*m+j, j*p+k, k*n+i] = 1
R = np.einsum("ir,jr,kr->ijk", U, V, W)
if not np.array_equal(T, R):
print(json.dumps({{"error": "decomposition does not match tensor"}})); sys.exit(0)
score = {BENCHMARK} / rank
print(json.dumps({{"combined_score": score, "rank": rank, "eval_time": eval_time}}))
"""
try:
r = subprocess.run([sys.executable, "-c", script], capture_output=True, text=True, timeout=600)
for line in reversed(r.stdout.strip().splitlines()):
if line.strip().startswith("{"): return json.loads(line.strip())
return {{"combined_score": 0.0, "error": r.stderr[-500:]}}
except Exception as e:
return {{"combined_score": 0.0, "error": str(e)}}
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