adds versioning for release

README.md

@@ -1,2 +1,2 @@
 # graph-diffusers
-Diffusion patterns for graph machine learning
+Diffusion patterns for graph machine learning based on GraphBLAS.

graph_diffusers/__init__.py

@@ -1,4 +1,5 @@
 from graph_diffusers import models, operators, io
+from graph_diffusers._version import __version__
 
 __all__ = [
     "models",

graph_diffusers/_version.py

@@ -0,0 +1 @@
+__version__ = "0.0.0"

graph_diffusers/io/torch.py

@@ -1,15 +1,19 @@
 import graphblas as gb
-from typing import TYPE_CHECKING, Optional, Union, Hashable
+from typing import TYPE_CHECKING, Optional, Hashable
 import functools as ft
 import torch
-from torch_sparse import SparseTensor
 import warnings
+from graph_diffusers import _extras
 
 if TYPE_CHECKING:
     from graph_diffusers._typing import _GraphblasModule as gb
     from numpy.typing import DTypeLike
 
-# TODO check if torch_sparse installed
+if _extras.TORCH_SPARSE:
+    from torch_sparse import SparseTensor as _SparseTensor
+else:
+
+    class _SparseTensor: ...
 
 
 def torch_to_graphblas(
@@ -19,7 +23,7 @@ def torch_to_graphblas(
     weighted: bool = False,
     dtype: "Optional[DTypeLike]" = None,
 ) -> gb.Matrix:
-    if isinstance(edge_index, SparseTensor):
+    if isinstance(edge_index, _SparseTensor):
         return torch_sparse_tensor_to_graphblas(edge_index, weighted=weighted, dtype=dtype)
     if edge_index.is_sparse_csr:
         return torch_sparse_csr_to_graphblas(edge_index, weighted=weighted, dtype=dtype)
@@ -37,30 +41,33 @@ def torch_sparse_csr_to_graphblas(
     return _torch_sparse_csr_to_graphblas(adj_t, weighted=weighted, dtype=dtype)
 
 
-def torch_sparse_tensor_to_graphblas(
-    adj_t: SparseTensor, *, weighted: bool = False, dtype: "Optional[DTypeLike]" = None
-) -> gb.Matrix:
-    return torch_sparse_csr_to_graphblas(
-        adj_t.to_torch_sparse_csr_tensor(),
-        weighted=weighted,
-        dtype=dtype,
-    )
-
-
 def torch_edge_index_to_graphblas(
-    edge_index: Union[torch.Tensor, SparseTensor],
+    edge_index: torch.Tensor,
     *,
     num_nodes: Optional[int] = None,
     dtype: "Optional[DTypeLike]" = None,
 ) -> gb.Matrix:
     if not isinstance(dtype, Hashable):
         warnings.warn(
-            f"Unhashable dtype {dtype} passed when converting from torch to graphblas." "The result will not be cached."
+            f"Unhashable dtype {dtype} passed when converting from torch to graphblas. The result will not be cached."
         )
         return _torch_edge_index_to_graphblas.__wrapped__(edge_index, num_nodes=num_nodes, dtype=dtype)
     return _torch_edge_index_to_graphblas(edge_index, num_nodes=num_nodes, dtype=dtype)
 
 
+if _extras.TORCH_SPARSE:
+    import torch_sparse
+
+    def torch_sparse_tensor_to_graphblas(
+        adj_t: torch_sparse.SparseTensor, *, weighted: bool = False, dtype: "Optional[DTypeLike]" = None
+    ) -> gb.Matrix:
+        return torch_sparse_csr_to_graphblas(
+            adj_t.to_torch_sparse_csr_tensor(),
+            weighted=weighted,
+            dtype=dtype,
+        )
+
+
 @ft.lru_cache(maxsize=1)
 def _torch_sparse_csr_to_graphblas(
     adj_t: torch.Tensor,

pyproject.toml

@@ -1,10 +1,28 @@
 [tool.poetry]
 name = "graph-diffusers"
-version = "0.1.0-dev"
-description = "Diffusion operators for graph machine learning"
+version = "0.0.0"
+description = "Diffusion operators for graph machine learning based on GraphBLAS"
 authors = ["Aaron Zolnai-Lucas <[email protected]>"]
 license = "MIT"
 readme = "README.md"
+classifiers = [
+    "License :: OSI Approved :: MIT License",
+    "Operating System :: OS Independent",
+    "Topic :: Scientific/Engineering",
+    "Topic :: Scientific/Engineering :: Mathematics",
+    "Topic :: Scientific/Engineering :: Artificial Intelligence",
+    "Intended Audience :: Developers",
+    "Intended Audience :: Science/Research",
+    "Intended Audience :: Education",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.8",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",    
+    "Programming Language :: Python :: 3.12"    
+
+]
+urls = { Homepage = "https://github.com/aaronzo/graph-diffusers" }
 
 [[tool.poetry.source]]
 name = "pytorch-cpu"

release.sh

@@ -0,0 +1,56 @@
+#!/bin/sh
+set -e
+
+repository="$1"
+version="$2"
+
+cwd=$(pwd)
+cd `dirname $0`
+
+if [ -z "$repository" ]; then
+    echo "Usage: $0 <repository> <version>"
+    exit 1
+fi
+
+if [ -z "$version" ]; then
+    echo "Usage: $0 <repository> <version>"
+    exit 1
+fi
+
+echo "Running poetry lock and install ..."
+poetry lock --no-update
+poetry install
+
+echo "Setting package version ..."
+poetry version $2
+echo "__version__ = \"$2\"" > graph_diffusers/_version.py
+
+echo "Running tests ..."
+poetry run pytest tests/
+
+echo "Running tests without torch_sparse ..."
+poetry run pip uninstall -y torch_sparse
+poetry run pytest tests/
+
+echo "Running tests without torch ..."
+poetry run pip uninstall -y torch
+poetry run pytest tests/
+
+echo "Restoring environment ..."
+poetry install
+
+echo "Cleaning up dist/ ..."
+rm -rf dist/
+
+echo "Publishing to $repository ..."
+poetry publish \
+    --repository $repository \
+    --build \
+    --no-interaction
+
+git tag -m "Release $version" $version
+git push origin $version
+
+echo "Done!"
+
+cd $cwd