chore: import upstream snapshot with attribution

python/paddle/distributed/auto_parallel/static/cluster_v2.py

@@ -0,0 +1,129 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from enum import IntEnum, unique
+
+import numpy as np
+
+from paddle.framework import core
+
+
+@unique
+class DeviceType(IntEnum):
+    UNKNOWN = 0
+    CPU = 1
+    GPU = 2
+    XPU = 3
+    DCU = 5
+    NIC = 6
+
+
+@unique
+class LinkType(IntEnum):
+    UNKNOWN = 0
+    LOC = 1
+    SYS = 2
+    PHB = 3
+    PIX = 4
+    PIB = 5
+    NVL = 6
+    NVB = 7
+    NET = 8
+
+
+class DeviceMesh(core.DeviceMesh):
+    r"""
+    The class `DeviceMesh` describes the topology of physical devices.
+
+    Args:
+        mesh (list|numpy.array): an N-dimensional array describes the topology
+            of logical processes.
+        dim_names (list, optional): the i-th element of this list gives the name of the
+            i-th dimension.
+
+    Returns:
+        None
+
+    Examples:
+        .. code-block:: pycon
+
+            >>> # doctest: +REQUIRES(env:DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> paddle.enable_static()
+
+            >>> mesh = dist.DeviceMesh([[2, 4, 5], [0, 1, 3]])
+            >>> assert mesh.shape == [2, 3]
+            >>> assert mesh.device_ids == [2, 4, 5, 0, 1, 3]
+
+    """
+
+    def __init__(self, name, mesh, dim_names=None):
+        self._name = name
+
+        if not isinstance(mesh, list) and not isinstance(mesh, np.ndarray):
+            raise ValueError(
+                'The mesh must be an instance of list or np.ndarray.'
+            )
+        if isinstance(mesh, list):
+            mesh = np.array(mesh)
+
+        self._mesh = mesh
+
+        self._shape = list(self._mesh.shape)
+
+        self._device_ids = self._mesh.flatten().tolist()
+        assert all(isinstance(p, int) for p in self._device_ids), (
+            "All elements of the mesh be integer"
+        )
+        assert min(self._device_ids) >= 0, (
+            'All elements of the mesh must be >= 0.'
+        )
+        unique_device_ids = set(self._device_ids)
+        assert len(unique_device_ids) == len(self._device_ids), (
+            'All elements of the mesh must be unique.'
+        )
+
+        if dim_names is not None:
+            assert len(dim_names) == len(self._shape), (
+                "The length of dims_names must be same as the shape of the mesh."
+            )
+            self._dim_names = dim_names
+        else:
+            self._dim_names = ["d" + str(i) for i in range(len(self._shape))]
+
+        # Follow the requirement for using pybind11
+        core.DeviceMesh.__init__(
+            self, self._name, self._shape, self._device_ids, self._dim_names
+        )
+
+    @property
+    def mesh(self):
+        return self._mesh
+
+
+# class Cluster:
+#     """
+#     The cluster represents the hardware resource.
+#     """
+
+#     def __init__(self):
+#         self._device_meshes = {}
+
+#     def device_mesh(self, device_mesh_name):
+#         return self._device_meshes[device_mesh_name]
+
+#     def add_device_mesh(self, device_mesh):
+#         self._device_meshes[device_mesh.name] = device_mesh