From 1b195a0c18aecdf799153d59f3760a90464864ff Mon Sep 17 00:00:00 2001 From: rusty1s Date: Fri, 16 Feb 2024 08:03:13 +0100 Subject: [PATCH] update --- CHANGELOG.md | 14 +++++++++++++- conda/pyg/meta.yaml | 2 +- conda/pytorch-geometric/meta.yaml | 2 +- docs/source/tutorial/distributed_pyg.rst | 2 +- pyproject.toml | 2 +- torch_geometric/__init__.py | 2 +- 6 files changed, 18 insertions(+), 6 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 454028d5a23a..48b58f339261 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,7 +3,19 @@ All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/). -## \[2.5.0\] - 2023-MM-DD +## \[2.6.0\] - 2024-MM-DD + +### Added + +### Changed + +### Deprecated + +### Fixed + +### Removed + +## \[2.5.0\] - 2024-02-16 ### Added diff --git a/conda/pyg/meta.yaml b/conda/pyg/meta.yaml index 2c13a88c3903..f23bfff627e0 100644 --- a/conda/pyg/meta.yaml +++ b/conda/pyg/meta.yaml @@ -1,6 +1,6 @@ package: name: pyg - version: 2.4.0 + version: 2.5.0 source: url: https://files.pythonhosted.org/packages/e6/6e/a596e2ddecc3b13a0d576495369a30309fb54c74fadf0bbca645bfbcaa2f/torch_geometric-2.4.0.tar.gz diff --git a/conda/pytorch-geometric/meta.yaml b/conda/pytorch-geometric/meta.yaml index b3e142fd09d6..37fd7f16e0bf 100644 --- a/conda/pytorch-geometric/meta.yaml +++ b/conda/pytorch-geometric/meta.yaml @@ -1,6 +1,6 @@ package: name: pytorch-geometric - version: 2.4.0 + version: 2.5.0 source: url: https://files.pythonhosted.org/packages/e6/6e/a596e2ddecc3b13a0d576495369a30309fb54c74fadf0bbca645bfbcaa2f/torch_geometric-2.4.0.tar.gz diff --git a/docs/source/tutorial/distributed_pyg.rst b/docs/source/tutorial/distributed_pyg.rst index 7564a9550f0b..667d84c356ab 100644 --- a/docs/source/tutorial/distributed_pyg.rst +++ b/docs/source/tutorial/distributed_pyg.rst @@ -57,7 +57,7 @@ Note that METIS requires undirected, homogeneous graphs as input. By default, METIS tries to balance the number of nodes of each type in each partition while minimizing the number of edges between partitions. This ensures that the resulting partitions provide maximal local access of neighbors, enabling samplers to perform local computations without the need for communication between different compute nodes. -Through this partitioning approach, every edge receives a distinct assignment, while "halo nodes" (1-hop neighbors that fall into a different partition) are replicated. +Through this partitioning approach, every node receives a distinct assignment, while "halo nodes" (1-hop neighbors that fall into a different partition) are replicated. Halo nodes ensure that neighbor sampling for a single node in a single layer stays purely local. .. figure:: ../_figures/dist_part.png diff --git a/pyproject.toml b/pyproject.toml index 89a4fe63e02b..f26e88ec1147 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend="flit_core.buildapi" [project] name="torch_geometric" -version="2.4.0" +version="2.5.0" authors=[ {name="Matthias Fey", email="matthias@pyg.org"}, ] diff --git a/torch_geometric/__init__.py b/torch_geometric/__init__.py index faf4d4ad22d7..47a42b88b180 100644 --- a/torch_geometric/__init__.py +++ b/torch_geometric/__init__.py @@ -22,7 +22,7 @@ contrib = LazyLoader('contrib', globals(), 'torch_geometric.contrib') graphgym = LazyLoader('graphgym', globals(), 'torch_geometric.graphgym') -__version__ = '2.4.0' +__version__ = '2.5.0' __all__ = [ 'EdgeIndex',