Revert "Topo service (#75)" (#85)

This reverts commit 764b601.

bluefog/torch/__init__.py

@@ -14,6 +14,10 @@
 # limitations under the License.
 # ==============================================================================
 
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import collections
 import os
 import torch
@@ -26,10 +30,10 @@
     DistributedWinPutOptimizer,
     DistributedAllreduceOptimizer,
     DistributedNeighborAllreduceOptimizer,
-    DistributedHierarchicalNeighborAllreduceOptimizer,
+    DistributedHierarchicalNeighborAllreduceOptimizer
 )
 
-check_extension("bluefog.torch", __file__, "mpi_lib")
+check_extension('bluefog.torch', __file__, 'mpi_lib')
 
 from bluefog.torch.mpi_ops import init, shutdown
 from bluefog.torch.mpi_ops import size, local_size, rank, local_rank
@@ -70,38 +74,4 @@
 
 from bluefog.torch.mpi_ops import timeline_start_activity, timeline_end_activity
 from bluefog.torch.mpi_ops import timeline_context
-
-from bluefog.torch.utility import (
-    broadcast_optimizer_state,
-    broadcast_parameters,
-    allreduce_parameters,
-)
-
-from bluefog.common.topology_util import (
-    GetRecvWeights,
-    GetSendWeights,
-    IsRegularGraph,
-    IsTopologyEquivalent,
-)
-
-from bluefog.common.topology_util import (
-    ExponentialTwoGraph,
-    ExponentialGraph,
-    FullyConnectedGraph,
-    MeshGrid2DGraph,
-    RingGraph,
-    StarGraph,
-    SymmetricExponentialGraph,
-)
-
-from bluefog.common.topology_util import (
-    GetDynamicOnePeerSendRecvRanks,
-    GetExp2DynamicSendRecvMachineRanks,
-    GetInnerOuterRingDynamicSendRecvRanks,
-    GetInnerOuterExpo2DynamicSendRecvRanks,
-)
-
-from bluefog.torch.topology_util import (
-    InferSourceFromDestinationRanks,
-    InferDestinationFromSourceRanks,
-)
+from bluefog.torch.utility import broadcast_optimizer_state, broadcast_parameters, allreduce_parameters

bluefog/torch/utility.py

@@ -14,10 +14,8 @@
 # limitations under the License.
 # ==============================================================================
 
-from typing import Any, List, Optional
 import collections
 
-import numpy as np
 import torch
 import bluefog.torch as bf
 

test/torch_basics_test.py

@@ -28,18 +28,8 @@
 
 from common import mpi_env_rank_and_size
 import bluefog.torch as bf
-from bluefog.torch import (
-    ExponentialGraph,
-    RingGraph,
-    StarGraph,
-    MeshGrid2DGraph,
-    FullyConnectedGraph,
-)
-from bluefog.torch import (
-    IsTopologyEquivalent,
-    InferDestinationFromSourceRanks,
-    InferSourceFromDestinationRanks,
-)
+from bluefog.common.topology_util import ExponentialGraph, RingGraph, RingGraph
+from bluefog.common.topology_util import IsTopologyEquivalent
 
 warnings.filterwarnings("ignore", message="numpy.dtype size changed")
 warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
@@ -85,12 +75,10 @@ def test_set_topology_fail_with_win_create(self):
 
         if size == 1:
             expected_topology = nx.from_numpy_array(
-                np.array([[0.5]]), create_using=nx.DiGraph
-            )
+                np.array([[0.5]]), create_using=nx.DiGraph)
         elif size == 2:
             expected_topology = nx.from_numpy_array(
-                np.array([[0, 0.2], [0.2, 0]]), create_using=nx.DiGraph
-            )
+                np.array([[0, 0.2], [0.2, 0]]), create_using=nx.DiGraph)
         else:
             expected_topology = RingGraph(size)
 
@@ -108,16 +96,10 @@ def test_set_and_load_topology(self):
         bf.init()
         size = bf.size()
         if size == 4:
-            expected_topology = nx.DiGraph(
-                np.array(
-                    [
-                        [1 / 3.0, 1 / 3.0, 1 / 3.0, 0.0],
-                        [0.0, 1 / 3.0, 1 / 3.0, 1 / 3.0],
-                        [1 / 3.0, 0.0, 1 / 3.0, 1 / 3.0],
-                        [1 / 3.0, 1 / 3.0, 0.0, 1 / 3.0],
-                    ]
-                )
-            )
+            expected_topology = nx.DiGraph(np.array(
+                [[1/3., 1/3., 1/3., 0.], [0., 1/3., 1/3., 1/3.],
+                 [1/3., 0., 1/3., 1/3.], [1/3., 1/3., 0., 1/3.]]
+            ))
         elif size == 1:
             expected_topology = nx.DiGraph(np.array([[1.0]]))
         else:
@@ -131,81 +113,37 @@ def test_in_out_neighbors_expo2(self):
         rank = bf.rank()
         size = bf.size()
         assert bf.set_topology(ExponentialGraph(size))
-        in_neighbors = bf.in_neighbor_ranks()
+        in_neighobrs = bf.in_neighbor_ranks()
         out_neighbors = bf.out_neighbor_ranks()
 
         degree = int(np.ceil(np.log2(size)))
-        expected_in_neighbors = sorted([(rank - 2 ** i) % size for i in range(degree)])
-        expected_out_neighbors = sorted([(rank + 2 ** i) % size for i in range(degree)])
-        assert sorted(in_neighbors) == expected_in_neighbors
+        expected_in_neighbors = sorted([(rank - 2**i) %
+                                        size for i in range(degree)])
+        expected_out_neighbors = sorted([(rank + 2**i) %
+                                         size for i in range(degree)])
+        assert sorted(in_neighobrs) == expected_in_neighbors
         assert sorted(out_neighbors) == expected_out_neighbors
 
     def test_in_out_neighbors_biring(self):
         bf.init()
         rank = bf.rank()
         size = bf.size()
         assert bf.set_topology(RingGraph(size))
-        in_neighbors = bf.in_neighbor_ranks()
+        in_neighobrs = bf.in_neighbor_ranks()
         out_neighbors = bf.out_neighbor_ranks()
 
-        expected_in_neighbors = list(set(map(lambda x: x % size, [rank - 1, rank + 1])))
-        expected_out_neighbors = list(
-            set(map(lambda x: x % size, [rank - 1, rank + 1]))
-        )
+        expected_in_neighbors = list(set(
+            map(lambda x: x % size, [rank - 1, rank + 1])))
+        expected_out_neighbors = list(set(
+            map(lambda x: x % size, [rank - 1, rank + 1])))
 
         if size <= 1:
             expected_in_neighbors = []
             expected_out_neighbors = []
 
-        assert sorted(in_neighbors) == expected_in_neighbors
+        assert sorted(in_neighobrs) == expected_in_neighbors
         assert sorted(out_neighbors) == expected_out_neighbors
 
 
-@pytest.mark.parametrize(
-    "topo_func",
-    [ExponentialGraph, RingGraph, StarGraph, MeshGrid2DGraph, FullyConnectedGraph],
-)
-def test_infer_destination_from_source_ranks(topo_func):
-    bf.init()
-    size = bf.size()
-    bf.set_topology(topo_func(size))
-    topo = bf.load_topology()
-    in_neighbors = bf.in_neighbor_ranks()
-    out_neighbors = bf.out_neighbor_ranks()
-
-    # Make the W into average rule.
-    expected_W = (nx.to_numpy_array(topo) > 0).astype(float)
-    expected_W /= expected_W.sum(axis=0)
-
-    src_ranks, W = InferDestinationFromSourceRanks(
-        src_ranks=in_neighbors, construct_adjacency_matrix=True
-    )
-    assert sorted(src_ranks) == out_neighbors
-    np.testing.assert_allclose(W, expected_W)
-
-
-@pytest.mark.parametrize(
-    "topo_func",
-    [ExponentialGraph, RingGraph, StarGraph, MeshGrid2DGraph, FullyConnectedGraph],
-)
-def test_infer_source_from_destination_ranks(topo_func):
-    bf.init()
-    size = bf.size()
-    bf.set_topology(topo_func(size))
-    topo = bf.load_topology()
-    in_neighbors = bf.in_neighbor_ranks()
-    out_neighbors = bf.out_neighbor_ranks()
-
-    # Make the W into average rule.
-    expected_W = (nx.to_numpy_array(topo) > 0).astype(float)
-    expected_W /= expected_W.sum(axis=0)
-
-    dst_ranks, W = InferSourceFromDestinationRanks(
-        dst_ranks=out_neighbors, construct_adjacency_matrix=True
-    )
-    assert sorted(dst_ranks) == in_neighbors
-    np.testing.assert_allclose(W, expected_W)
-
-
 if __name__ == "__main__":
     unittest.main()