Initial Commit

src/decentralizepy/mappings/Linear.py

+from decentralizepy.mappings.Mapping import Mapping
+
+
+class Linear(Mapping):
+    """
+    This class defines the mapping:
+        uid = machine_id * procs_per_machine + rank
+    """
+
+    def __init__(self, n_machines, procs_per_machine):
+        """
+        Constructor
+        Parameters
+        ----------
+        n_machines : int
+            Number of machines involved in learning
+        procs_per_machine : int
+            Number of processes spawned per machine
+        """
+        super().__init__(n_machines * procs_per_machine)
+        self.n_machines = n_machines
+        self.procs_per_machine = procs_per_machine
+
+    def get_uid(self, rank: int, machine_id: int):
+        """
+        Gives the global unique identifier of the node
+        Parameters
+        ----------
+        rank : int
+            Node's rank on its machine
+        machine_id : int
+            node's machine in the cluster
+        Returns
+        -------
+        int
+            the unique identifier
+        """
+        return machine_id * self.procs_per_machine + rank
+
+    def get_machine_and_rank(self, uid: int):
+        """
+        Gives the rank and machine_id of the node
+        Parameters
+        ----------
+        uid : int
+            globally unique identifier of the node
+        Returns
+        -------
+        2-tuple
+            a tuple of machine_id and rank
+        """
+        return (uid // self.procs_per_machine), (uid % self.procs_per_machine)

src/decentralizepy/mappings/Mapping.py

+class Mapping:
+    """
+    This class defines the bidirectional mapping between:
+        1. The unique identifier
+        2. machine_id and rank
+    """
+
+    def __init__(self, n_procs):
+        """
+        Constructor
+        """
+        self.n_procs = n_procs
+
+    def get_uid(self, rank: int, machine_id: int):
+        """
+        Gives the global unique identifier of the node
+        Parameters
+        ----------
+        rank : int
+            Node's rank on its machine
+        machine_id : int
+            node's machine in the cluster
+        Returns
+        -------
+        int
+            the unique identifier
+        """
+
+        raise NotImplementedError
+
+    def get_machine_and_rank(self, uid: int):
+        """
+        Gives the rank and machine_id of the node
+        Parameters
+        ----------
+        uid : int
+            globally unique identifier of the node
+        Returns
+        -------
+        2-tuple
+            a tuple of machine_id and rank
+        """
+
+        raise NotImplementedError

src/decentralizepy/mappings/__init__.py

+from .Linear import Linear
+from .Mapping import Mapping

src/decentralizepy/node/Node.py

+class Node:
+    """
+    This class defines the node (entity that performs learning, sharing and communication).
+    """
+
+    def __init__(self, rank, mapping, graph, options):
+        """
+        Constructor
+        Parameters
+        ----------
+        rank : int
+            Rank of process local to the machine
+        mapping : decentralizepy.mappings
+            The object containing the mapping rank <--> uid
+        graph : decentralizepy.graphs
+            The object containing the global graph
+        dataset : decentralizepy.datasets class
+            The class whose object will be instantiated to init the dataset
+        """
+        self.rank = rank
+        self.graph = graph
+        self.mapping = mapping
+        self.options = options
+
+    def __get_item__(self, i):
+        """
+        Function to get the item with index i.
+        Parameters
+        ----------
+        i : int
+            Index
+        Returns
+        -------
+        2-tuple
+            A tuple of the ith data sample and it's corresponding label
+        """
+        return self.x[i], self.y[i]