class_docstr: Class for the metric of the n-dimensional hyperbolic space.
  
  Class for the metric of the n-dimensional hyperbolic space
  as embedded in the Poincaré half space model.
docstr: Compute the inner-product of two tangent vectors at a base point.
  
  Parameters
  ----------
  tangent_vec_a : array-like, shape=[..., dim + 1]
      First tangent vector at base point.
  tangent_vec_b : array-like, shape=[..., dim + 1]
      Second tangent vector at base point.
  base_point : array-like, shape=[..., dim + 1]
      Point in hyperbolic space.
  
  Returns
  -------
  inner_prod : array-like, shape=[..., 1]
      Inner-product of the two tangent vectors.
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code: def inner_product(self, tangent_vec_a, tangent_vec_b, base_point):
      """Compute the inner-product of two tangent vectors at a base point.
  
      Parameters
      ----------
      tangent_vec_a : array-like, shape=[..., dim + 1]
          First tangent vector at base point.
      tangent_vec_b : array-like, shape=[..., dim + 1]
          Second tangent vector at base point.
      base_point : array-like, shape=[..., dim + 1]
          Point in hyperbolic space.
  
      Returns
      -------
      inner_prod : array-like, shape=[..., 1]
          Inner-product of the two tangent vectors.
      """
      inner_prod = gs.sum(tangent_vec_a * tangent_vec_b, axis=-1)
      return inner_prod / base_point[..., -1] ** 2
  
imports: import math
  import geomstats.backend
  from geomstats.geometry._hyperbolic import _Hyperbolic
  from geomstats.geometry.base import VectorSpaceOpenSet
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.poincare_ball import PoincareBall
  from geomstats.geometry.riemannian_metric import RiemannianMetric
  from geomstats.vectorization import repeat_out
label_desc: Use image node_id 2 for calling the PoincareHalfSpaceMetric obj's underlying member method code with example usage: obj.inner_product(tangent_vec_a, tangent_vec_b, base_point) and returns: unknown