Please follow the instructions in the screenshots provided and use that to implement the code given below. Done in python 3.10 or later please.    class WeightedAdjacencyMatrix :     """A weighted graph represented as a matrix."""     __slots__ = ['_W']     def __init__(self, size, edges=[], weights=[]) :         """Initializes a weighted adjacency matrix for a graph with size nodes.         Graph is initialized with size nodes and a specified set of         edges and edge weights.                  Keyword arguments:         size -- Number of nodes of the graph.         edges -- a list of ordered pairs (2-tuples) indicating the                  edges of the graph.  The default value is an empty list                  which means no edges by default.         weights -- a list of weights for the edges, which should be the same                    length as the edges list.  The position of a value in                    the weights list corresponds to the edge in the same                    position of the edges list.         """         pass # replace this pass statement with the code needed to implement this       def add_edge(self, u, v, weight) :         """Adds an undirected edge between u to v with the specified weight.         Keyword arguments:         u -- vertex id (0-based index)         v -- vertex id (0-based index)         weight -- edge weight         """         pass # replace this pass statement with the code needed to implement this     def floyd_warshall(self) :         """Floyd Warshall algorithm for all pairs shortest paths.         Returns a matrix D consisting of the weights of the shortest         paths between all pairs of vertices, and a matrix P for         the predecessors matrix (what the textbook called PI).         This method MUST NOT change the weight matrix of the graph         itself.           """         # Your return statement will look something like this one         # in the comment on the following line.  That returns         # the two matrices, with the D matrix first.  The return None         # is just a placeholder so that this is valid Python syntax before         # you've completed the assignment.  This comment line is         # more like what it should look like:         # return D, P         return None class WeightedDirectedAdjacencyMatrix(WeightedAdjacencyMatrix) :     """A weighted digraph represented as a matrix."""     def add_edge(self, u, v, weight) :         """Adds a directed edge from u to v with the specified weight.         Keyword arguments:         u -- source vertex id (0-based index)         v -- target vertex id (0-based index)         weight -- edge weight         """         pass # replace this pass statement with the code needed to implement this      def test_floyd_warshall() :     """See assignment instructions at top."""     pass # replace this pass statement with the code needed to implement this

Please follow the instructions in the screenshots provided and use that to implement the code given below. Done in python 3.10 or later please. 

class WeightedAdjacencyMatrix :
    """A weighted graph represented as a matrix."""

    __slots__ = ['_W']

    def __init__(self, size, edges=[], weights=[]) :
        """Initializes a weighted adjacency matrix for a graph with size nodes.

        Graph is initialized with size nodes and a specified set of
        edges and edge weights.
        
        Keyword arguments:
        size -- Number of nodes of the graph.
        edges -- a list of ordered pairs (2-tuples) indicating the
                 edges of the graph.  The default value is an empty list
                 which means no edges by default.
        weights -- a list of weights for the edges, which should be the same
                   length as the edges list.  The position of a value in
                   the weights list corresponds to the edge in the same
                   position of the edges list.
        """
        pass # replace this pass statement with the code needed to implement this

    def add_edge(self, u, v, weight) :
        """Adds an undirected edge between u to v with the specified weight.

        Keyword arguments:
        u -- vertex id (0-based index)
        v -- vertex id (0-based index)
        weight -- edge weight
        """
        pass # replace this pass statement with the code needed to implement this

    def floyd_warshall(self) :
        """Floyd Warshall algorithm for all pairs shortest paths.

        Returns a matrix D consisting of the weights of the shortest
        paths between all pairs of vertices, and a matrix P for
        the predecessors matrix (what the textbook called PI).
        This method MUST NOT change the weight matrix of the graph
        itself.  
        """
        # Your return statement will look something like this one
        # in the comment on the following line.  That returns
        # the two matrices, with the D matrix first.  The return None
        # is just a placeholder so that this is valid Python syntax before
        # you've completed the assignment.  This comment line is
        # more like what it should look like:
        # return D, P
        return None

class WeightedDirectedAdjacencyMatrix(WeightedAdjacencyMatrix) :
    """A weighted digraph represented as a matrix."""

    def add_edge(self, u, v, weight) :
        """Adds a directed edge from u to v with the specified weight.

        Keyword arguments:
        u -- source vertex id (0-based index)
        v -- target vertex id (0-based index)
        weight -- edge weight
        """
        pass # replace this pass statement with the code needed to implement this
    

def test_floyd_warshall() :
    """See assignment instructions at top."""
    pass # replace this pass statement with the code needed to implement this