Addressed memory leak on CUDA devices (#108)

* Addressed memory leak on CUDA devices
* Removed gpg check for cibuild
* Updated cibuildwheels to 2.19.0

.github/workflows/publish.yml

@@ -20,17 +20,17 @@ jobs:
       - if: ${{ env.ACT }}
         run: pip install pipx 
       - name: Build wheels
-        uses: pypa/cibuildwheel@v2.14.1
+        uses: pypa/cibuildwheel@v2.19.0
         env:
           CIBW_BUILD_VERBOSITY: 2
-          CIBW_BUILD: "cp3{8,9,10}*"
+          CIBW_BUILD: "cp3{8,9,10,11}*"
           CIBW_SKIP: "*musllinux*"
           CIBW_ARCHS: x86_64
           # Note: We need 2_28 because libcaer requires recent linux headers
           CIBW_BUILD_FRONTEND: "pip"
           CIBW_MANYLINUX_X86_64_IMAGE: manylinux_2_28
           CIBW_BEFORE_BUILD: "rm -rf {project}/_skbuild"
-          CIBW_BEFORE_ALL_LINUX: 'yum install -y lz4-devel libgusb-devel SDL2-devel'
+          CIBW_BEFORE_ALL_LINUX: 'yum install -y lz4-devel libgusb-devel SDL2-devel --nogpgcheck'
           CIBW_REPAIR_WHEEL_COMMAND: 'source .github/deps/fix_path.sh && auditwheel repair -w {dest_dir} {wheel}'
 
       - uses: actions/upload-artifact@v3

docs/install.md

@@ -29,7 +29,7 @@ If you need to specify a different C++ compiler, be sure to also specify it for
 AEStream can read from [Inivation](https://gitlab.com/inivation/dv/libcaer/) or [Prophesee](https://github.com/prophesee-ai/openeb/) event cameras, *given that the drivers are installed*.
 **Please make sure the drivers are installed before installing aestream** (step 1 below).
 
-1. Follow the instructions at https://gitlab.com/inivation/dv/libcaer/ to install the Inivation drivers and/or https://github.com/prophesee-ai/openeb/ to install the Prophesee drivers
+1. Follow the instructions at [Inivation libcaer](https://gitlab.com/inivation/dv/libcaer/) to install the Inivation drivers and/or [Prophesee Openeb](https://github.com/prophesee-ai/openeb/) to install the Prophesee drivers
 2. Install AEStream with pip: `pip install aestream --no-binary aestream -v`
     * The `--no-binary` flag forces pip to recompile aestream for your system, which will detect the event camera drivers, if present.
     * The `-v` flag enables verbose output, which will show you if the drivers were detected
@@ -66,7 +66,7 @@ To avoid this, we recomment using `--no-build-isolation` in the pip install, but
 git clone https://github.com/aestream/aestream
 cd aestream
 # Install build dependencies
-pip install scikit-build-core setuptools_scm pathspec
+pip install scikit-build-core setuptools_scm pathspec nanobind
 # Build aestream, but without build isolation
 # Any future compilation will *only* compile the files you changed
 pip install --no-build-isolation .

src/python/tensor_buffer.cpp

@@ -154,8 +154,18 @@ inline tensor_type BufferPointer::to_tensor_type() {
   float *ptr = data.release();
   int32_t device_type =
       device == "cuda" ? nb::device::cuda::value : nb::device::cpu::value;
-  return tensor_type(ptr, 2, s, nb::handle(), /* owner */
-                     nullptr,                 /* strides */
+  nb::capsule owner;
+  #ifdef USE_CUDA
+    if (device == "cuda") {
+      owner = nb::capsule(ptr, [](void *p) noexcept { free_memory_cuda((float *)p); });
+    } else {
+  #endif
+      owner = nb::capsule(ptr, [](void *p) noexcept { delete[] (float *) p; });
+  #ifdef USE_CUDA
+    }
+  #endif
+  return tensor_type(ptr, 2, s, owner, /* owner */
+                     nullptr,          /* strides */
                      nanobind::dtype<float>(), device_type);
 }