Issue in Tuto-GUDHI-optimization with the use of LowerStarSimplexTreeLayer

[VincentRouvreau]

Tested with gudhi 3.10.1, 3.11.0 and 3.12.0, same result.

The stack:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[28], line 9
      5 
      6 losses, dgms, betas = [], [], []
      7 for epoch in range(100+1):
      8     with tf.GradientTape() as tape:
----> 9         dgm = layer.call(beta)[0][0]
     10         # Minimize all points except the three most persistent ones
     11         top3 = np.argsort(dgm[:,1]-dgm[:,0]).ravel()[::-1][3:]
     12         loss =  tf.reduce_sum(tf.square(tf.matmul(X, -beta) - Y)) \

File [~/miniconda/envs/TDA-tutorial/lib/python3.12/site-packages/gudhi/tensorflow/lower_star_simplex_tree_layer.py:115](http://localhost:8888/home/gailuron/miniconda/envs/TDA-tutorial/lib/python3.12/site-packages/gudhi/tensorflow/lower_star_simplex_tree_layer.py#line=114), in LowerStarSimplexTreeLayer.call(self, filtration)
    105 """
    106 Compute lower-star persistence diagram associated to a function defined on the vertices of the simplex tree
    107 
   (...)    112     List[Tuple[tf.Tensor,tf.Tensor]]: List of lower-star persistence diagrams. The length of this list is the same than that of dimensions, i.e., there is one persistence diagram per homology dimension provided in the input list dimensions. Moreover, the finite and essential parts of the persistence diagrams are provided separately: each element of this list is a tuple of size two that contains the finite and essential parts of the corresponding persistence diagram, of shapes [num_finite_points, 2] and [num_essential_points, 1] respectively
    113 """
    114 # Don't try to compute gradients for the vertex pairs
--> 115 indices = _LowerStarSimplexTree(
    116     self.simplextree, filtration.numpy(), self.dimensions, self.hcf, self.pdm
    117 )
    118 # Get persistence diagrams
    119 self.dgms = []

File [~/miniconda/envs/TDA-tutorial/lib/python3.12/site-packages/gudhi/tensorflow/lower_star_simplex_tree_layer.py:36](http://localhost:8888/home/gailuron/miniconda/envs/TDA-tutorial/lib/python3.12/site-packages/gudhi/tensorflow/lower_star_simplex_tree_layer.py#line=35), in _LowerStarSimplexTree(simplextree, filtration, dimensions, homology_coeff_field, persistence_dim_max)
     34 # Assign new filtration values
     35 for i in range(simplextree.num_vertices()):
---> 36     simplextree.assign_filtration([i], filtration[i])
     37 simplextree.make_filtration_non_decreasing()
     39 # Compute persistence diagram

TypeError: assign_filtration(): incompatible function arguments. The following argument types are supported:
    1. assign_filtration(self, simplex: collections.abc.Sequence[int], filtration: float) -> None

Invoked with types: gudhi.simplex_tree.SimplexTree, list, ndarray