Rename SortAggr to SortAggregation (#5085)

* rename sortaggr

* add changelog

* fix text on name

CHANGELOG.md

@@ -39,7 +39,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added the `bias` vector to the `GCN` model definition in the "Create Message Passing Networks" tutorial ([#4755](https://github.com/pyg-team/pytorch_geometric/pull/4755))
 - Added `transforms.RootedSubgraph` interface with two implementations: `RootedEgoNets` and `RootedRWSubgraph` ([#3926](https://github.com/pyg-team/pytorch_geometric/pull/3926))
 - Added `ptr` vectors for `follow_batch` attributes within `Batch.from_data_list` ([#4723](https://github.com/pyg-team/pytorch_geometric/pull/4723))
-- Added `torch_geometric.nn.aggr` package ([#4687](https://github.com/pyg-team/pytorch_geometric/pull/4687), [#4721](https://github.com/pyg-team/pytorch_geometric/pull/4721), [#4731](https://github.com/pyg-team/pytorch_geometric/pull/4731), [#4762](https://github.com/pyg-team/pytorch_geometric/pull/4762), [#4749](https://github.com/pyg-team/pytorch_geometric/pull/4749), [#4779](https://github.com/pyg-team/pytorch_geometric/pull/4779), [#4863](https://github.com/pyg-team/pytorch_geometric/pull/4863), [#4864](https://github.com/pyg-team/pytorch_geometric/pull/4864), [#4865](https://github.com/pyg-team/pytorch_geometric/pull/4865), [#4866](https://github.com/pyg-team/pytorch_geometric/pull/4866), [#4872](https://github.com/pyg-team/pytorch_geometric/pull/4872), [#4934](https://github.com/pyg-team/pytorch_geometric/pull/4934), [#4935](https://github.com/pyg-team/pytorch_geometric/pull/4935), [#4957](https://github.com/pyg-team/pytorch_geometric/pull/4957), [#4973](https://github.com/pyg-team/pytorch_geometric/pull/4973), [#4973](https://github.com/pyg-team/pytorch_geometric/pull/4973), [#4986](https://github.com/pyg-team/pytorch_geometric/pull/4986), [#4995](https://github.com/pyg-team/pytorch_geometric/pull/4995), [#5000](https://github.com/pyg-team/pytorch_geometric/pull/5000), [#5034](https://github.com/pyg-team/pytorch_geometric/pull/5034), [#5036](https://github.com/pyg-team/pytorch_geometric/pull/5036), [#5039](https://github.com/pyg-team/pytorch_geometric/issues/5039), [#4522](https://github.com/pyg-team/pytorch_geometric/pull/4522), [#5033](https://github.com/pyg-team/pytorch_geometric/pull/5033]))
+- Added `torch_geometric.nn.aggr` package ([#4687](https://github.com/pyg-team/pytorch_geometric/pull/4687), [#4721](https://github.com/pyg-team/pytorch_geometric/pull/4721), [#4731](https://github.com/pyg-team/pytorch_geometric/pull/4731), [#4762](https://github.com/pyg-team/pytorch_geometric/pull/4762), [#4749](https://github.com/pyg-team/pytorch_geometric/pull/4749), [#4779](https://github.com/pyg-team/pytorch_geometric/pull/4779), [#4863](https://github.com/pyg-team/pytorch_geometric/pull/4863), [#4864](https://github.com/pyg-team/pytorch_geometric/pull/4864), [#4865](https://github.com/pyg-team/pytorch_geometric/pull/4865), [#4866](https://github.com/pyg-team/pytorch_geometric/pull/4866), [#4872](https://github.com/pyg-team/pytorch_geometric/pull/4872), [#4934](https://github.com/pyg-team/pytorch_geometric/pull/4934), [#4935](https://github.com/pyg-team/pytorch_geometric/pull/4935), [#4957](https://github.com/pyg-team/pytorch_geometric/pull/4957), [#4973](https://github.com/pyg-team/pytorch_geometric/pull/4973), [#4973](https://github.com/pyg-team/pytorch_geometric/pull/4973), [#4986](https://github.com/pyg-team/pytorch_geometric/pull/4986), [#4995](https://github.com/pyg-team/pytorch_geometric/pull/4995), [#5000](https://github.com/pyg-team/pytorch_geometric/pull/5000), [#5034](https://github.com/pyg-team/pytorch_geometric/pull/5034), [#5036](https://github.com/pyg-team/pytorch_geometric/pull/5036), [#5039](https://github.com/pyg-team/pytorch_geometric/issues/5039), [#4522](https://github.com/pyg-team/pytorch_geometric/pull/4522), [#5033](https://github.com/pyg-team/pytorch_geometric/pull/5033]), [#5085](https://github.com/pyg-team/pytorch_geometric/pull/5085))
 - Added the `DimeNet++` model ([#4432](https://github.com/pyg-team/pytorch_geometric/pull/4432), [#4699](https://github.com/pyg-team/pytorch_geometric/pull/4699), [#4700](https://github.com/pyg-team/pytorch_geometric/pull/4700), [#4800](https://github.com/pyg-team/pytorch_geometric/pull/4800))
 - Added an example of using PyG with PyTorch Ignite ([#4487](https://github.com/pyg-team/pytorch_geometric/pull/4487))
 - Added `GroupAddRev` module with support for reducing training GPU memory ([#4671](https://github.com/pyg-team/pytorch_geometric/pull/4671), [#4701](https://github.com/pyg-team/pytorch_geometric/pull/4701), [#4715](https://github.com/pyg-team/pytorch_geometric/pull/4715), [#4730](https://github.com/pyg-team/pytorch_geometric/pull/4730))

test/nn/aggr/test_sort.py

@@ -1,15 +1,15 @@
 import torch
 
-from torch_geometric.nn.aggr import SortAggr
+from torch_geometric.nn.aggr import SortAggregation
 
 
 def test_sort_aggregation_pool():
     N_1, N_2 = 4, 6
     x = torch.randn(N_1 + N_2, 4)
     index = torch.tensor([0 for _ in range(N_1)] + [1 for _ in range(N_2)])
 
-    aggr = SortAggr(k=5)
-    assert str(aggr) == 'SortAggr(k=5)'
+    aggr = SortAggregation(k=5)
+    assert str(aggr) == 'SortAggregation(k=5)'
 
     out = aggr(x, index)
     assert out.size() == (2, 5 * 4)
@@ -36,8 +36,8 @@ def test_sort_aggregation_pool_smaller_than_k():
     index = torch.tensor([0 for _ in range(N_1)] + [1 for _ in range(N_2)])
 
     # Set k which is bigger than both N_1=4 and N_2=6.
-    aggr = SortAggr(k=10)
-    assert str(aggr) == 'SortAggr(k=10)'
+    aggr = SortAggregation(k=10)
+    assert str(aggr) == 'SortAggregation(k=10)'
 
     out = aggr(x, index)
     assert out.size() == (2, 10 * 4)
@@ -64,8 +64,8 @@ def test_global_sort_pool_dim_size():
     x = torch.randn(N_1 + N_2, 4)
     index = torch.tensor([0 for _ in range(N_1)] + [1 for _ in range(N_2)])
 
-    aggr = SortAggr(k=5)
-    assert str(aggr) == 'SortAggr(k=5)'
+    aggr = SortAggregation(k=5)
+    assert str(aggr) == 'SortAggregation(k=5)'
 
     # expand batch output by 1
     out = aggr(x, index, dim_size=3)

torch_geometric/nn/aggr/__init__.py

@@ -15,7 +15,7 @@
 from .set2set import Set2Set
 from .scaler import DegreeScalerAggregation
 from .equilibrium import EquilibriumAggregation
-from .sort import SortAggr
+from .sort import SortAggregation
 from .gmt import GraphMultisetTransformer
 from .attention import AttentionalAggregation
 
@@ -34,7 +34,7 @@
     'LSTMAggregation',
     'Set2Set',
     'DegreeScalerAggregation',
-    'SortAggr',
+    'SortAggregation',
     'GraphMultisetTransformer',
     'AttentionalAggregation',
     'EquilibriumAggregation',

torch_geometric/nn/aggr/sort.py

@@ -6,7 +6,7 @@
 from torch_geometric.nn.aggr import Aggregation
 
 
-class SortAggr(Aggregation):
+class SortAggregation(Aggregation):
     r"""The pooling operator from the `"An End-to-End Deep Learning
     Architecture for Graph Classification"
     <https://www.cse.wustl.edu/~muhan/papers/AAAI_2018_DGCNN.pdf>`_ paper,

torch_geometric/nn/glob.py

@@ -8,7 +8,7 @@
     AttentionalAggregation,
     GraphMultisetTransformer,
     Set2Set,
-    SortAggr,
+    SortAggregation,
 )
 
 Set2Set = deprecated(
@@ -36,7 +36,7 @@ def __call__(self, x, batch=None, size=None):
     func_name='nn.glob.global_sort_pool',
 )
 def global_sort_pool(x, index, k):
-    module = SortAggr(k=k)
+    module = SortAggregation(k=k)
     return module(x, index=index)