[NN] Renaming NearestNeighborGraph to KNNGraph (#802)

* initial commit

* second commit

* another commit

* change docstring

* migrating to dgl.nn

* fixes

* docs

* lint

* multiple fixes

* doc

* renaming nearest neighbor graph

examples/pytorch/pointcloud/model.py

 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from dgl.nn.pytorch import NearestNeighborGraph, EdgeConv
+from dgl.nn.pytorch import KNNGraph, EdgeConv
 
 class Model(nn.Module):
     def __init__(self, k, feature_dims, emb_dims, output_classes, input_dims=3,
                  dropout_prob=0.5):
         super(Model, self).__init__()
 
-        self.nng = NearestNeighborGraph(k)
+        self.nng = KNNGraph(k)
         self.conv = nn.ModuleList()
 
         self.num_layers = len(feature_dims)

python/dgl/nn/pytorch/factory.py

 """Modules that transforms between graphs and between graph and tensors."""
 import torch.nn as nn
-from ...transform import nearest_neighbor_graph, segmented_nearest_neighbor_graph
+from ...transform import knn_graph, segmented_knn_graph
 
 def pairwise_squared_distance(x):
     '''
@@ -11,7 +11,7 @@ def pairwise_squared_distance(x):
     return x2s + x2s.transpose(-1, -2) - 2 * x @ x.transpose(-1, -2)
 
 
-class NearestNeighborGraph(nn.Module):
+class KNNGraph(nn.Module):
     r"""Layer that transforms one point set into a graph, or a batch of
     point sets with the same number of points into a union of those graphs.
 
@@ -28,7 +28,7 @@ class NearestNeighborGraph(nn.Module):
         The number of neighbors
     """
     def __init__(self, k):
-        super(NearestNeighborGraph, self).__init__()
+        super(KNNGraph, self).__init__()
         self.k = k
 
     #pylint: disable=invalid-name
@@ -46,10 +46,10 @@ class NearestNeighborGraph(nn.Module):
         -------
         A DGLGraph with no features.
         """
-        return nearest_neighbor_graph(x, self.k)
+        return knn_graph(x, self.k)
 
 
-class SegmentedNearestNeighborGraph(nn.Module):
+class SegmentedKNNGraph(nn.Module):
     r"""Layer that transforms one point set into a graph, or a batch of
     point sets with different number of points into a union of those graphs.
 
@@ -80,7 +80,7 @@ class SegmentedNearestNeighborGraph(nn.Module):
     - A DGLGraph with no features.
     """
     def __init__(self, k):
-        super(SegmentedNearestNeighborGraph, self).__init__()
+        super(SegmentedKNNGraph, self).__init__()
         self.k = k
 
     #pylint: disable=invalid-name
@@ -100,4 +100,4 @@ class SegmentedNearestNeighborGraph(nn.Module):
         -------
         A DGLGraph with no features.
         """
-        return segmented_nearest_neighbor_graph(x, self.k, segs)
+        return segmented_knn_graph(x, self.k, segs)

python/dgl/transform.py

@@ -10,7 +10,7 @@ from .batched_graph import BatchedDGLGraph, unbatch
 
 
 __all__ = ['line_graph', 'khop_adj', 'khop_graph', 'reverse', 'to_simple_graph', 'to_bidirected',
-           'laplacian_lambda_max', 'nearest_neighbor_graph', 'segmented_nearest_neighbor_graph']
+           'laplacian_lambda_max', 'knn_graph', 'segmented_knn_graph']
 
 
 def pairwise_squared_distance(x):
@@ -23,7 +23,7 @@ def pairwise_squared_distance(x):
     return x2s + F.swapaxes(x2s, -1, -2) - 2 * x @ F.swapaxes(x, -1, -2)
 
 #pylint: disable=invalid-name
-def nearest_neighbor_graph(x, k):
+def knn_graph(x, k):
     """Transforms the given point set to a directed graph, whose coordinates
     are given as a matrix. The predecessors of each point are its k-nearest
     neighbors.
@@ -69,7 +69,7 @@ def nearest_neighbor_graph(x, k):
     return g
 
 #pylint: disable=invalid-name
-def segmented_nearest_neighbor_graph(x, k, segs):
+def segmented_knn_graph(x, k, segs):
     """Transforms the given point set to a directed graph, whose coordinates
     are given as a matrix.  The predecessors of each point are its k-nearest
     neighbors.