code: def _compute_cosine_similarity(u: np.ndarray, v: np.ndarray):
      """Computes cosine similarity between two embeddings."""
  
      if len(u) <= 0:
          raise ValueError(
              "Cannot compute cosing similarity on empty embeddings."
          )
  
      norm_u = np.linalg.norm(u)
      norm_v = np.linalg.norm(v)
  
      if norm_u <= 0 or norm_v <= 0:
          raise ValueError(
              "Cannot compute cosine similarity on embedding with 0 norm."
          )
  
      return u.dot(v) / (norm_u * norm_v)
  
imports: import numpy
  from mediapipe.tasks.python.components.containers import embedding_result
label_desc: Use image node_id 1 for calling a global function with example usage: _compute_cosine_similarity(u, v) and returns: unknown