cosine_similarity not defined about autodistill HOT 2 OPEN

def cosine_similarity(a: np.array, b: np.array) -> np.array:
    """
    Calculate the cosine similarity between two vectors.

    Args:
        a: The first vector.
        b: The second vector.

    Returns:
        The cosine similarity between the two vectors.
    """
    return float(np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b)))

def compare_embeddings(
    image_embedding: np.array,
    comparison_embeddings: List[np.array],
    distance_metric="cosine",
):
    """
    Calculate the similarity between an image embedding and all embeddings in a list.

    Args:
        image_embedding: The embedding of the image to compare.
        comparison_embeddings: A list of embeddings to compare against.
        distance_metric: The distance metric to use. Currently only supports "cosine".

    Returns:
        A list of similarity scores.
    """
    if distance_metric == "cosine":
        comparisons = []

        for comparison_embedding in comparison_embeddings:
            comparisons.append(
                cosine_similarity(
                    image_embedding.reshape(-1), comparison_embedding.reshape(-1)
                )
            )

        return sv.Classifications(
            class_id=np.array([i for i in range(len(comparisons))]),
            confidence=np.array(comparisons).flatten(),
        )
    else:
        raise NotImplementedError(
            f"Distance metric {distance_metric} is not supported."
        )
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