chore: import upstream snapshot with attribution

2026-07-13 13:35:51 +08:00
commit c36a561cd8
2172 changed files with 455595 additions and 0 deletions
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+"""Sampling Graphs."""
+
+from typing import Dict, Union
+
+import torch
+
+
+__all__ = ["SamplingGraph"]
+
+
+class SamplingGraph:
+    r"""Class for sampling graph."""
+
+    def __init__(self):
+        pass
+
+    def __repr__(self) -> str:
+        """Return a string representation of the graph.
+
+        Returns
+        -------
+        str
+            String representation of the graph.
+        """
+        raise NotImplementedError
+
+    @property
+    def num_nodes(self) -> Union[int, Dict[str, int]]:
+        """The number of nodes in the graph.
+        - If the graph is homogenous, returns an integer.
+        - If the graph is heterogenous, returns a dictionary.
+
+        Returns
+        -------
+        Union[int, Dict[str, int]]
+            The number of nodes. Integer indicates the total nodes number of a
+            homogenous graph; dict indicates nodes number per node types of a
+            heterogenous graph.
+        """
+        raise NotImplementedError
+
+    @property
+    def num_edges(self) -> Union[int, Dict[str, int]]:
+        """The number of edges in the graph.
+        - If the graph is homogenous, returns an integer.
+        - If the graph is heterogenous, returns a dictionary.
+
+        Returns
+        -------
+        Union[int, Dict[str, int]]
+            The number of edges. Integer indicates the total edges number of a
+            homogenous graph; dict indicates edges number per edge types of a
+            heterogenous graph.
+        """
+        raise NotImplementedError
+
+    def copy_to_shared_memory(self, shared_memory_name: str) -> "SamplingGraph":
+        """Copy the graph to shared memory.
+
+        Parameters
+        ----------
+        shared_memory_name : str
+            Name of the shared memory.
+
+        Returns
+        -------
+        SamplingGraph
+            The copied SamplingGraph object on shared memory.
+        """
+        raise NotImplementedError
+
+    # pylint: disable=invalid-name
+    def to(self, device: torch.device) -> "SamplingGraph":
+        """Copy graph to the specified device.
+
+        Parameters
+        ----------
+        device : torch.device
+            The destination device.
+
+        Returns
+        -------
+        SamplingGraph
+            The graph on the specified device.
+        """
+        raise NotImplementedError