Spaces:
Running
Running
File size: 5,334 Bytes
e0f5bb6 | 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 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 | """Route 4: mandatory assumption-satisfying falsification attempt for Claim 5."""
from __future__ import annotations
import json
from pathlib import Path
def run(output_dir: Path) -> dict[str, object]:
output_dir.mkdir(parents=True, exist_ok=True)
exact_contract = {
"statement": (
"For the paper's ResNet and CNN improved-WGAN experiments on "
"CIFAR-10 and STL-10, smaller beta and larger rho empirically tend "
"to produce lower cumulative AvgS, and lower AvgS tends to coincide "
"with higher Inception Score."
),
"domain": [
"actual GAN training",
"ResNet and CNN architectures",
"CIFAR-10 and STL-10",
"paper-defined cumulative parameter-gradient L1 AvgS",
"Inception Score from the corresponding trained models",
],
"quantifier": (
"qualitative empirical tendency across settings, not a universal "
"strict ordering for every adjacent momentum pair or seed"
),
}
candidates = [
{
"name": "beta_minus_point5_vs_minus_point3_reported_IS",
"evidence": {
"beta_minus_point5": [7.002, 6.878, 6.761, 7.520],
"beta_minus_point3": [7.087, 7.181, 7.010, 7.791],
},
"gan_domain_satisfied": True,
"all_required_joint_gradient_and_is_evidence_present": False,
"contradicts_exact_tendency_quantifier": False,
"rejection_reason": (
"Every smaller-beta IS is lower for this one adjacent pair, "
"but the source claim says 'tend' and no per-run joint AvgS/IS "
"data are available. This refutes only a stronger universal claim."
),
},
{
"name": "table2_fixed_beta_metadata_mismatch",
"gan_domain_satisfied": True,
"all_required_joint_gradient_and_is_evidence_present": False,
"contradicts_exact_tendency_quantifier": False,
"rejection_reason": (
"The mismatch makes the experiment ambiguous; it is not a "
"performance counterexample."
),
},
{
"name": "quadratic_rho_point95_point99_reversal",
"gan_domain_satisfied": False,
"all_required_joint_gradient_and_is_evidence_present": False,
"contradicts_exact_tendency_quantifier": False,
"rejection_reason": (
"The analytic quadratic is interaction-dominated but is not a "
"ResNet/CNN GAN on CIFAR-10 or STL-10."
),
},
{
"name": "synthetic_full_shape_cpu_profile",
"gan_domain_satisfied": False,
"all_required_joint_gradient_and_is_evidence_present": False,
"contradicts_exact_tendency_quantifier": False,
"rejection_reason": (
"Synthetic tensors measure runtime only and contain neither "
"dataset training nor Inception Scores."
),
},
]
universalized_control = {
"statement": "IS is strictly nondecreasing whenever beta becomes smaller.",
"is_the_paper_exact_quantifier": False,
"counterexample": "beta=-0.5 has lower reported IS than beta=-0.3 in all four settings",
"counterexample_detected": all(
smaller < larger
for smaller, larger in zip(
candidates[0]["evidence"]["beta_minus_point5"],
candidates[0]["evidence"]["beta_minus_point3"],
)
),
}
valid_candidates = [
candidate["name"]
for candidate in candidates
if candidate["gan_domain_satisfied"]
and candidate["all_required_joint_gradient_and_is_evidence_present"]
and candidate["contradicts_exact_tendency_quantifier"]
]
payload = {
"claim": 5,
"route": 4,
"route_name": "mandatory falsification",
"exact_contract": exact_contract,
"primary_sources": [
{
"name": "paper HTML",
"sha256": "c7ebf813dc871eba1c0c93542fcf0a7d599c7c4d44a543a0000270ce48ae7998",
"anchors": ["Section 5", "Appendix D", "Tables 1-2"],
},
{
"name": "Improved Training of Wasserstein GANs",
"arxiv": "1704.00028",
"role": "framework reference, not proof of the target implementation",
},
],
"candidates": candidates,
"universalized_negative_control": universalized_control,
"valid_assumption_satisfying_counterexamples": valid_candidates,
"falsification_established": bool(valid_candidates),
"verdict": "FALSIFIED" if valid_candidates else "BLOCKED",
"unblockers": [
"author executable code and exact configurations",
"raw per-run cumulative gradient and Inception Score data",
"resolved fixed-beta setting for the rho sweep",
"sufficient CPU budget for the independently calibrated full campaign",
],
}
(output_dir / "claim5_route4_falsification.json").write_text(
json.dumps(payload, indent=2) + "\n"
)
return payload
|