update

CHANGELOG.md

@@ -10,7 +10,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Enabled `LinkNeighborLoader` to return number of sampled nodes and edges per hop ([#7516](https://github.com/pyg-team/pytorch_geometric/pull/7516))
 - Added the `HM` personalized fashion recommendation dataset ([#7515](https://github.com/pyg-team/pytorch_geometric/pull/7515))
 - Added the `GraphMixer` model ([#7501](https://github.com/pyg-team/pytorch_geometric/pull/7501))
-- Added the `disable_dynamic_shape` experimental flag ([#7246](https://github.com/pyg-team/pytorch_geometric/pull/7246))
+- Added the `disable_dynamic_shape` experimental flag ([#7246](https://github.com/pyg-team/pytorch_geometric/pull/7246), [#7534](https://github.com/pyg-team/pytorch_geometric/pull/7534))
 - Added the option to override `use_segmm` selection in `HeteroLinear` ([#7474](https://github.com/pyg-team/pytorch_geometric/pull/7474))
 - Added the `MovieLens-1M` heterogeneous dataset ([#7479](https://github.com/pyg-team/pytorch_geometric/pull/7479))
 - Added a CPU-based and GPU-based `map_index` implementation ([#7493](https://github.com/pyg-team/pytorch_geometric/pull/7493))
@@ -94,8 +94,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added an optional `batch_size` and `max_num_nodes` arguments to `MemPooling` layer ([#7239](https://github.com/pyg-team/pytorch_geometric/pull/7239))
 - Fixed training issues of the GraphGPS example ([#7377](https://github.com/pyg-team/pytorch_geometric/pull/7377))
 - Allowed `CaptumExplainer` to be called multiple times in a row ([#7391](https://github.com/pyg-team/pytorch_geometric/pull/7391))
-- Added usage of disable_dynamic_shape decorator in aggregation layers ([#7534](https://github.com/pyg-team/pytorch_geometric/pull/7534))
-
 
 ### Removed
 

torch_geometric/nn/aggr/base.py

@@ -59,7 +59,6 @@ class Aggregation(torch.nn.Module):
         - **output:** graph features :math:`(*, |\mathcal{G}|, F_{out})` or
           node features :math:`(*, |\mathcal{V}|, F_{out})`
     """
-    @disable_dynamic_shapes(required_args=['dim_size', 'max_num_elements'])
     def forward(
         self,
         x: Tensor,

torch_geometric/nn/aggr/mlp.py

@@ -2,7 +2,6 @@
 
 from torch import Tensor
 
-from torch_geometric.experimental import disable_dynamic_shapes
 from torch_geometric.nn.aggr import Aggregation
 
 
@@ -23,7 +22,6 @@ class MLPAggregation(Aggregation):
         **kwargs (optional): Additional arguments of
             :class:`torch_geometric.nn.models.MLP`.
     """
-    @disable_dynamic_shapes(required_args=['max_num_elements'])
     def __init__(self, in_channels: int, out_channels: int,
                  max_num_elements: int, **kwargs):
         super().__init__()