change reindex

python/paddle/fluid/tests/unittests/test_graph_reindex.py

@@ -213,13 +213,13 @@ def test_reindex_result(self):
         index_buffer = paddle.full([self.num_nodes], -1, dtype="int32")
 
         reindex_src, reindex_dst, out_nodes = \
-            paddle.geometric.graph_reindex(x, neighbors, count)
+            paddle.geometric.reindex_graph(x, neighbors, count)
         np.testing.assert_allclose(self.reindex_src, reindex_src, rtol=1e-05)
         np.testing.assert_allclose(self.reindex_dst, reindex_dst, rtol=1e-05)
         np.testing.assert_allclose(self.out_nodes, out_nodes, rtol=1e-05)
 
         reindex_src, reindex_dst, out_nodes = \
-            paddle.geometric.graph_reindex(x, neighbors, count,
+            paddle.geometric.reindex_graph(x, neighbors, count,
                                           value_buffer, index_buffer,
                                           has_buffer_hashtable=True)
         np.testing.assert_allclose(self.reindex_src, reindex_src, rtol=1e-05)
@@ -235,7 +235,7 @@ def test_heter_reindex_result(self):
         count = paddle.concat([count, count])
 
         reindex_src, reindex_dst, out_nodes = \
-            paddle.geometric.graph_reindex(x, neighbors, count)
+            paddle.geometric.reindex_graph(x, neighbors, count)
         np.testing.assert_allclose(self.reindex_src,
                                    reindex_src[:self.neighbors.shape[0]],
                                    rtol=1e-05)
@@ -276,7 +276,7 @@ def test_heter_reindex_result_v2(self):
         reindex_dst = np.array(reindex_dst, dtype="int64")
 
         reindex_src_, reindex_dst_, out_nodes_ = \
-            paddle.geometric.graph_reindex(paddle.to_tensor(x),
+            paddle.geometric.reindex_graph(paddle.to_tensor(x),
                                           paddle.to_tensor(neighbors),
                                           paddle.to_tensor(counts))
         np.testing.assert_allclose(reindex_src, reindex_src_, rtol=1e-05)
@@ -311,7 +311,7 @@ def test_heter_reindex_result_v3(self):
         neighbors = [paddle.to_tensor(neighbors1), paddle.to_tensor(neighbors2)]
         count = [paddle.to_tensor(count1), paddle.to_tensor(count2)]
         reindex_src_, reindex_dst_, out_nodes_ = \
-            paddle.geometric.heter_graph_reindex(paddle.to_tensor(x),
+            paddle.geometric.reindex_heter_graph(paddle.to_tensor(x),
                                                  neighbors, count)
         np.testing.assert_allclose(reindex_src, reindex_src_, rtol=1e-05)
         np.testing.assert_allclose(reindex_dst, reindex_dst_, rtol=1e-05)
@@ -337,9 +337,9 @@ def test_reindex_result_static(self):
                                               dtype="int32")
 
             reindex_src_1, reindex_dst_1, out_nodes_1 = \
-                paddle.geometric.graph_reindex(x, neighbors, count)
+                paddle.geometric.reindex_graph(x, neighbors, count)
             reindex_src_2, reindex_dst_2, out_nodes_2 = \
-                paddle.geometric.graph_reindex(x, neighbors, count,
+                paddle.geometric.reindex_graph(x, neighbors, count,
                                               value_buffer, index_buffer,
                                               has_buffer_hashtable=True)
 
@@ -420,11 +420,11 @@ def test_heter_reindex_result_static(self):
                                               dtype="int32")
 
             reindex_src_1, reindex_dst_1, out_nodes_1 = \
-                paddle.geometric.heter_graph_reindex(x,
+                paddle.geometric.reindex_heter_graph(x,
                                                      [neighbors1, neighbors2],
                                                      [count1, count2])
             reindex_src_2, reindex_dst_2, out_nodes_2 = \
-                paddle.geometric.heter_graph_reindex(x,
+                paddle.geometric.reindex_heter_graph(x,
                                                      [neighbors1, neighbors2],
                                                      [count1, count2],
                                                      value_buffer, index_buffer,

python/paddle/geometric/__init__.py

@@ -19,8 +19,8 @@
 from .math import segment_mean  # noqa: F401
 from .math import segment_min  # noqa: F401
 from .math import segment_max  # noqa: F401
-from .sampling import graph_reindex  # noqa: F401
-from .sampling import heter_graph_reindex  # noqa: F401
+from .reindex import reindex_graph  # noqa: F401
+from .reindex import reindex_heter_graph  # noqa: F401
 from .sampling import sample_neighbors  # noqa: F401
 
 __all__ = [
@@ -31,7 +31,7 @@
     'segment_mean',
     'segment_min',
     'segment_max',
-    'graph_reindex',
-    'heter_graph_reindex',
+    'reindex_graph',
+    'reindex_heter_graph',
     'sample_neighbors',
 ]

python/paddle/geometric/sampling/graph_reindex.py → python/paddle/geometric/reindex.py

@@ -22,15 +22,15 @@
 __all__ = []
 
 
-def graph_reindex(x,
+def reindex_graph(x,
                   neighbors,
                   count,
                   value_buffer=None,
                   index_buffer=None,
                   has_buffer_hashtable=False,
                   name=None):
     """
-    Graph Reindex API.
+    Reindex Graph API.
 
     This API is mainly used in Graph Learning domain, which should be used
     in conjunction with `graph_sample_neighbors` API. And the main purpose
@@ -41,7 +41,7 @@ def graph_reindex(x,
         The number in x should be unique, otherwise it would cause potential errors.
     We will reindex all the nodes from 0. 
 
-    Take input nodes x = [0, 1, 2] as an example. 
+    Take input nodes x = [0, 1, 2] as an example.
     If we have neighbors = [8, 9, 0, 4, 7, 6, 7], and count = [2, 3, 2], 
     then we know that the neighbors of 0 is [8, 9], the neighbors of 1
     is [0, 4, 7], and the neighbors of 2 is [6, 7]. 
@@ -89,7 +89,7 @@ def graph_reindex(x,
         count = paddle.to_tensor(count, dtype="int32")
 
         reindex_src, reindex_dst, out_nodes = \
-             paddle.geometric.graph_reindex(x, neighbors, count)
+             paddle.geometric.reindex_graph(x, neighbors, count)
         # reindex_src: [3, 4, 0, 5, 6, 7, 6]
         # reindex_dst: [0, 0, 1, 1, 1, 2, 2]
         # out_nodes: [0, 1, 2, 8, 9, 4, 7, 6]
@@ -117,7 +117,7 @@ def graph_reindex(x,
         check_variable_and_dtype(index_buffer, "HashTable_Index", ("int32"),
                                  "graph_reindex")
 
-    helper = LayerHelper("graph_reindex", **locals())
+    helper = LayerHelper("reindex_graph", **locals())
     reindex_src = helper.create_variable_for_type_inference(dtype=x.dtype)
     reindex_dst = helper.create_variable_for_type_inference(dtype=x.dtype)
     out_nodes = helper.create_variable_for_type_inference(dtype=x.dtype)
@@ -143,15 +143,15 @@ def graph_reindex(x,
     return reindex_src, reindex_dst, out_nodes
 
 
-def heter_graph_reindex(x,
+def reindex_heter_graph(x,
                         neighbors,
                         count,
                         value_buffer=None,
                         index_buffer=None,
                         has_buffer_hashtable=False,
                         name=None):
     """
-    HeterGraph Reindex API.
+    Reindex HeterGraph API.
 
     This API is mainly used in Graph Learning domain, which should be used
     in conjunction with `graph_sample_neighbors` API. And the main purpose
@@ -160,7 +160,7 @@ def heter_graph_reindex(x,
 
     **Notes**:
         The number in x should be unique, otherwise it would cause potential errors.
-    We support multi-edge-types neighbors reindexing in heter_graph_reindex api. 
+    We support multi-edge-types neighbors reindexing in reindex_heter_graph api. 
     We will reindex all the nodes from 0.
 
     Take input nodes x = [0, 1, 2] as an example.
@@ -219,7 +219,7 @@ def heter_graph_reindex(x,
         neighbors = [neighbors_a, neighbors_b]
         count = [count_a, count_b]
         reindex_src, reindex_dst, out_nodes = \
-             paddle.geometric.heter_graph_reindex(x, neighbors, count)
+             paddle.geometric.reindex_heter_graph(x, neighbors, count)
         # reindex_src: [3, 4, 0, 5, 6, 7, 6, 0, 2, 8, 9, 1]
         # reindex_dst: [0, 0, 1, 1, 1, 2, 2, 0, 1, 1, 1, 2]
         # out_nodes: [0, 1, 2, 8, 9, 4, 7, 6, 3, 5]
@@ -258,7 +258,7 @@ def heter_graph_reindex(x,
         check_variable_and_dtype(index_buffer, "HashTable_Index", ("int32"),
                                  "graph_reindex")
 
-    helper = LayerHelper("heter_graph_reindex", **locals())
+    helper = LayerHelper("reindex_heter_graph", **locals())
     reindex_src = helper.create_variable_for_type_inference(dtype=x.dtype)
     reindex_dst = helper.create_variable_for_type_inference(dtype=x.dtype)
     out_nodes = helper.create_variable_for_type_inference(dtype=x.dtype)

python/paddle/geometric/sampling/__init__.py

@@ -12,12 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from .graph_reindex import graph_reindex  # noqa: F401
-from .graph_reindex import heter_graph_reindex  # noqa: F401
 from .neighbors import sample_neighbors  # noqa: F401
 
 __all__ = [
-    'graph_reindex',
-    'heter_graph_reindex',
     'sample_neighbors',
 ]