class_docstr: Space of parameterized discrete surfaces.
  
  Each surface is sampled with fixed `n_vertices` vertices and `n_faces`
  faces in :math:`\mathbb{R}^3`.
  
  Each individual surface is represented by a 2d-array of shape
  `[n_vertices, 3]`. This space corresponds to the space of immersions
  defined below, i.e. the
  space of smooth functions from a template to manifold :math:`M`
  into :math:`\mathbb{R}^3`, with non-vanishing Jacobian.
  
  .. math::
      Imm(M,\mathbb{R}^3)=\{ f \in C^{\infty}(M, \mathbb{R}^3)
      \|Df(x)\|\neq 0 \forall x \in M \}.
  
  Parameters
  ----------
  faces : integer array-like, shape=[n_faces, 3]
      Triangulation of the surface.
      Each face is given by 3 indices that indicate its vertices.
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docstr: Sample discrete surfaces.
  
  This sample random discrete surfaces with the correct number of vertices.
  
  Parameters
  ----------
  n_samples : int
      Number of surfaces to sample.
      Optional, Default=1
  
  Returns
  -------
  vertices : array-like, shape=[n_samples, n_vertices, 3]
      Vertices for a batch of points in the space of discrete surfaces.
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code: def random_point(self, n_samples=1):
      """Sample discrete surfaces.
  
      This sample random discrete surfaces with the correct number of vertices.
  
      Parameters
      ----------
      n_samples : int
          Number of surfaces to sample.
          Optional, Default=1
  
      Returns
      -------
      vertices : array-like, shape=[n_samples, n_vertices, 3]
          Vertices for a batch of points in the space of discrete surfaces.
      """
      vertices = self.ambient_manifold.random_point(
          n_samples * self.n_vertices
      )
      vertices = gs.reshape(vertices, (n_samples, self.n_vertices, 3))
      return vertices[0] if n_samples == 1 else vertices
  
imports: import math
  import geomstats.backend
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.manifold import Manifold
  from geomstats.geometry.riemannian_metric import RiemannianMetric
  from geomstats.numerics.optimizers import ScipyMinimize
label_desc: Use image node_id 7 for calling the DiscreteSurfaces obj's underlying member method code with example usage: obj.random_point(n_samples) and returns: unknown