rohitg00/ai-engineering-from-scratch · error · ValueError

k {k} not in [1, N={n}]

Error message

k {k} not in [1, N={n}]

What it means

Error "k {k} not in [1, N={n}]" thrown in rohitg00/ai-engineering-from-scratch.

Source

Thrown at phases/19-capstone-projects/63-multimodal-eval/code/main.py:86

@dataclass
class EvalSuite:
    retrieval: list[RetrievalPair]
    vqa: list[VQATriple]
    caps: list[CaptionSample]


def recall_at_k(sim: torch.Tensor, k: int) -> tuple[float, float]:
    """Return (i2t, t2i) recall@k.

    sim is (N, N) where row i is the similarity of image i to every caption.
    """
    if sim.dim() != 2 or sim.shape[0] != sim.shape[1]:
        raise ValueError(f"sim must be square (N, N), got {tuple(sim.shape)}")
    n = sim.shape[0]
    if k < 1 or k > n:
        raise ValueError(f"k {k} not in [1, N={n}]")

    targets = torch.arange(n, device=sim.device)

    topk_i2t = sim.topk(k, dim=1).indices
    hits_i2t = (topk_i2t == targets.unsqueeze(1)).any(dim=1).float().mean().item()

    sim_t = sim.T
    topk_t2i = sim_t.topk(k, dim=1).indices
    hits_t2i = (topk_t2i == targets.unsqueeze(1)).any(dim=1).float().mean().item()

    return hits_i2t, hits_t2i


def vqa_exact_match(predictions: list[int], references: list[int]) -> float:
    if len(predictions) != len(references):
        raise ValueError(f"length mismatch: pred {len(predictions)} vs ref {len(references)}")
    if not predictions:
        return 0.0

View on GitHub (pinned to 39ea8a1c6d)

When it happens

Trigger: Thrown at phases/19-capstone-projects/63-multimodal-eval/code/main.py:86 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of rohitg00/ai-engineering-from-scratch@39ea8a1c6d (2026-08-26). Data as JSON: /api/errors/69c9b65fa537a88e. Report an issue: GitHub.