code: def _debiased_dot_product_similarity_helper(
      xty,
      sum_squared_rows_x,
      sum_squared_rows_y,
      squared_norm_x,
      squared_norm_y,
      n,
  ):
      """Helper for computing debiased dot product similarity (i.e. linear HSIC)."""
      # This formula can be derived by manipulating the unbiased estimator from
      # Song et al. (2007).
      return (
          xty
          - n / (n - 2.0) * sum_squared_rows_x.dot(sum_squared_rows_y)
          + squared_norm_x * squared_norm_y / ((n - 1) * (n - 2))
      )
  
imports: import numpy
label_desc: Use image node_id 5 for calling a global function with example usage: _debiased_dot_product_similarity_helper(xty, sum_squared_rows_x, sum_squared_rows_y, squared_norm_x, squared_norm_y, n) and returns: unknown