class_docstr: Class for the space of complex matrices (m, n).
  
  Parameters
  ----------
  m, n : int
      Integers representing the shapes of the matrices: m x n.
docstr: Sample from a uniform distribution in a complex cube.
  
  Parameters
  ----------
  n_samples : int
      Number of samples.
      Optional, default: 1.
  bound : float
      Bound of the interval in which to sample each entry.
      Optional, default: 1.
  
  Returns
  -------
  point : array-like, shape=[..., m, n]
      Sample.
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code: def random_point(self, n_samples=1, bound=1.0):
      """Sample from a uniform distribution in a complex cube.
  
      Parameters
      ----------
      n_samples : int
          Number of samples.
          Optional, default: 1.
      bound : float
          Bound of the interval in which to sample each entry.
          Optional, default: 1.
  
      Returns
      -------
      point : array-like, shape=[..., m, n]
          Sample.
      """
      cdtype = gs.get_default_cdtype()
  
      size = (n_samples,) + self.shape if n_samples != 1 else self.shape
      point = gs.cast(
          bound * (gs.random.rand(*size) - 0.5), dtype=cdtype
      )
      point += 1j * gs.cast(
          bound * (gs.random.rand(*size) - 0.5), dtype=cdtype
      )
      return point
  
imports: import geomstats.backend
  import geomstats.errors
  from geomstats.geometry.base import ComplexMatrixVectorSpace
  from geomstats.geometry.hermitian import HermitianMetric
  from geomstats.geometry.matrices import Matrices
  from geomstats.vectorization import repeat_out
label_desc: Use image node_id 10 for calling the ComplexMatrices obj's underlying member method code with example usage: obj.random_point(n_samples, bound) and returns: point