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Unverified Commit 84bbb714 authored by Matthias Fey's avatar Matthias Fey Committed by GitHub
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PyTorch 2.0 wheels (#169) 

* update

* update

* update

* update
parent 0e108717
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Showing with 128 additions and 115 deletions
.github/workflows/building-conda.yml
View file @ 84bbb714
...@@ -13,27 +13,18 @@ jobs: ...@@ -13,27 +13,18 @@ jobs:
# We have trouble building for Windows - drop for now. # We have trouble building for Windows - drop for now.
os: [ubuntu-18.04, macos-10.15] # windows-2019 os: [ubuntu-18.04, macos-10.15] # windows-2019
python-version: ['3.7', '3.8', '3.9', '3.10'] python-version: ['3.7', '3.8', '3.9', '3.10']
torch-version: [1.13.0] # [1.12.0, 1.13.0] torch-version: [1.13.0, 2.0.0]
cuda-version: ['cpu', 'cu102', 'cu113', 'cu116', 'cu117'] # We have trouble building for `cu116` due to PyTorch 1.13.0 bugs
cuda-version: ['cpu', 'cu117', 'cu118']
exclude: exclude:
- torch-version: 1.12.0 - torch-version: 2.0.0
cuda-version: 'cu117' python-version: '3.7'
- torch-version: 1.13.0
cuda-version: 'cu102'
- torch-version: 1.13.0 - torch-version: 1.13.0
cuda-version: 'cu113' cuda-version: 'cu118'
- os: macos-10.15
cuda-version: 'cu102'
- os: macos-10.15
cuda-version: 'cu113'
- os: macos-10.15
cuda-version: 'cu116'
- os: macos-10.15 - os: macos-10.15
cuda-version: 'cu117' cuda-version: 'cu117'
- os: windows-2019 - os: macos-10.15
cuda-version: 'cu102' cuda-version: 'cu118'
- os: windows-2019 # Complains about CUDA mismatch.
python-version: '3.7'
steps: steps:
- uses: actions/checkout@v2 - uses: actions/checkout@v2
......
.github/workflows/building.yml
View file @ 84bbb714
...@@ -11,26 +11,24 @@ jobs: ...@@ -11,26 +11,24 @@ jobs:
fail-fast: false fail-fast: false
matrix: matrix:
os: [ubuntu-18.04, macos-10.15, windows-2019] os: [ubuntu-18.04, macos-10.15, windows-2019]
python-version: ['3.7', '3.8', '3.9', '3.10'] python-version: ['3.7', '3.8', '3.9', '3.10', '3.11']
torch-version: [1.12.0, 1.13.0] torch-version: [1.13.0, 2.0.0]
cuda-version: ['cpu', 'cu102', 'cu113', 'cu116', 'cu117'] cuda-version: ['cpu', 'cu116', 'cu117', 'cu118']
exclude: exclude:
- torch-version: 1.12.0
cuda-version: 'cu117'
- torch-version: 1.13.0 - torch-version: 1.13.0
cuda-version: 'cu102' python-version: '3.11'
- torch-version: 2.0.0
python-version: '3.7'
- torch-version: 1.13.0 - torch-version: 1.13.0
cuda-version: 'cu113' cuda-version: 'cu118'
- os: macos-10.15 - torch-version: 2.0.0
cuda-version: 'cu102' cuda-version: 'cu116'
- os: macos-10.15
cuda-version: 'cu113'
- os: macos-10.15 - os: macos-10.15
cuda-version: 'cu116' cuda-version: 'cu116'
- os: macos-10.15 - os: macos-10.15
cuda-version: 'cu117' cuda-version: 'cu117'
- os: windows-2019 - os: macos-10.15
cuda-version: 'cu102' cuda-version: 'cu118'
steps: steps:
- uses: actions/checkout@v2 - uses: actions/checkout@v2
......
.github/workflows/cuda/cu118-Linux-env.sh 0 → 100644
View file @ 84bbb714
#!/bin/bash
CUDA_HOME=/usr/local/cuda-11.8
LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
PATH=${CUDA_HOME}/bin:${PATH}
export FORCE_CUDA=1
export TORCH_CUDA_ARCH_LIST="3.5;5.0+PTX;6.0;7.0;7.5;8.0;8.6"
.github/workflows/cuda/cu118-Linux.sh 0 → 100755
View file @ 84bbb714
#!/bin/bash
OS=ubuntu1804
wget -nv https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/cuda-${OS}.pin
sudo mv cuda-${OS}.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget -nv https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda-repo-${OS}-11-8-local_11.8.0-520.61.05-1_amd64.deb
sudo dpkg -i cuda-repo-${OS}-11-8-local_11.8.0-520.61.05-1_amd64.deb
sudo cp /var/cuda-repo-${OS}-11-8-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt-get -qq update
sudo apt install cuda-nvcc-11-8 cuda-libraries-dev-11-8
sudo apt clean
rm -f https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda-repo-${OS}-11-8-local_11.8.0-520.61.05-1_amd64.deb
.github/workflows/cuda/cu118-Windows-env.sh 0 → 100644
View file @ 84bbb714
#!/bin/bash
CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v11.8
PATH=${CUDA_HOME}/bin:$PATH
PATH=/c/Program\ Files\ \(x86\)/Microsoft\ Visual\ Studio/2017/BuildTools/MSBuild/15.0/Bin:$PATH
export FORCE_CUDA=1
export TORCH_CUDA_ARCH_LIST="6.0+PTX"
.github/workflows/cuda/cu118-Windows.sh 0 → 100755
View file @ 84bbb714
#!/bin/bash
# Install NVIDIA drivers, see:
# https://github.com/pytorch/vision/blob/master/packaging/windows/internal/cuda_install.bat#L99-L102
curl -k -L "https://drive.google.com/u/0/uc?id=1injUyo3lnarMgWyRcXqKg4UGnN0ysmuq&export=download" --output "/tmp/gpu_driver_dlls.zip"
7z x "/tmp/gpu_driver_dlls.zip" -o"/c/Windows/System32"
export CUDA_SHORT=11.8
export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.0/local_installers
export CUDA_FILE=cuda_${CUDA_SHORT}.0_522.06_windows.exe
# Install CUDA:
curl -k -L "${CUDA_URL}/${CUDA_FILE}" --output "${CUDA_FILE}"
echo ""
echo "Installing from ${CUDA_FILE}..."
PowerShell -Command "Start-Process -FilePath \"${CUDA_FILE}\" -ArgumentList \"-s nvcc_${CUDA_SHORT} cuobjdump_${CUDA_SHORT} nvprune_${CUDA_SHORT} cupti_${CUDA_SHORT} cublas_dev_${CUDA_SHORT} cudart_${CUDA_SHORT} cufft_dev_${CUDA_SHORT} curand_dev_${CUDA_SHORT} cusolver_dev_${CUDA_SHORT} cusparse_dev_${CUDA_SHORT} thrust_${CUDA_SHORT} npp_dev_${CUDA_SHORT} nvrtc_dev_${CUDA_SHORT} nvml_dev_${CUDA_SHORT}\" -Wait -NoNewWindow"
echo "Done!"
rm -f "${CUDA_FILE}"
.github/workflows/linting.yml
View file @ 84bbb714
...@@ -17,7 +17,7 @@ jobs: ...@@ -17,7 +17,7 @@ jobs:
- name: Set up Python - name: Set up Python
uses: actions/setup-python@v2 uses: actions/setup-python@v2
with: with:
python-version: 3.9 python-version: 3.8
- name: Install dependencies - name: Install dependencies
run: | run: |
...@@ -26,30 +26,3 @@ jobs: ...@@ -26,30 +26,3 @@ jobs:
- name: Run linting - name: Run linting
run: | run: |
flake8 . flake8 .
pyroma:
runs-on: ubuntu-latest
strategy:
matrix:
torch-version: [1.13.0]
steps:
- uses: actions/checkout@v2
- name: Set up Python
uses: actions/setup-python@v2
with:
python-version: 3.9
- name: Install PyTorch ${{ matrix.torch-version }}
run: |
pip install torch==${{ matrix.torch-version }} --extra-index-url https://download.pytorch.org/whl/cpu
- name: Install dependencies
run: |
pip install pyroma
- name: Check package metadata
run: |
pyroma --min=10 .
.github/workflows/testing.yml
View file @ 84bbb714
...@@ -15,8 +15,8 @@ jobs: ...@@ -15,8 +15,8 @@ jobs:
fail-fast: false fail-fast: false
matrix: matrix:
os: [ubuntu-latest, windows-latest] os: [ubuntu-latest, windows-latest]
python-version: [3.7] python-version: [3.8]
torch-version: [1.12.0, 1.13.0] torch-version: [1.13.0, 2.0.0]
steps: steps:
- uses: actions/checkout@v2 - uses: actions/checkout@v2
......
CMakeLists.txt
View file @ 84bbb714
cmake_minimum_required(VERSION 3.0) cmake_minimum_required(VERSION 3.0)
project(torchcluster) project(torchcluster)
set(CMAKE_CXX_STANDARD 14) set(CMAKE_CXX_STANDARD 14)
set(TORCHCLUSTER_VERSION 1.6.0) set(TORCHCLUSTER_VERSION 1.6.1)
option(WITH_CUDA "Enable CUDA support" OFF) option(WITH_CUDA "Enable CUDA support" OFF)
option(WITH_PYTHON "Link to Python when building" ON) option(WITH_PYTHON "Link to Python when building" ON)
......
README.md
View file @ 84bbb714
...@@ -43,39 +43,39 @@ conda install pytorch-cluster -c pyg ...@@ -43,39 +43,39 @@ conda install pytorch-cluster -c pyg
We alternatively provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://data.pyg.org/whl). We alternatively provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://data.pyg.org/whl).
#### PyTorch 1.13 #### PyTorch 2.0
To install the binaries for PyTorch 1.13.0, simply run To install the binaries for PyTorch 2.0.0, simply run
``` ```
pip install torch-spline-conv -f https://data.pyg.org/whl/torch-1.13.0+${CUDA}.html pip install torch-spline-conv -f https://data.pyg.org/whl/torch-2.0.0+${CUDA}.html
``` ```
where `${CUDA}` should be replaced by either `cpu`, `cu116`, or `cu117` depending on your PyTorch installation. where `${CUDA}` should be replaced by either `cpu`, `cu117`, or `cu118` depending on your PyTorch installation.
| | `cpu` | `cu116` | `cu117` | | | `cpu` | `cu117` | `cu118` |
|-------------|-------|---------|---------| |-------------|-------|---------|---------|
| **Linux** | ✅ | ✅ | ✅ | | **Linux** | ✅ | ✅ | ✅ |
| **Windows** | ✅ | ✅ | ✅ | | **Windows** | ✅ | ✅ | ✅ |
| **macOS** | ✅ | | | | **macOS** | ✅ | | |
#### PyTorch 1.12 #### PyTorch 1.13
To install the binaries for PyTorch 1.12.0, simply run To install the binaries for PyTorch 1.13.0, simply run
``` ```
pip install torch-spline-conv -f https://data.pyg.org/whl/torch-1.12.0+${CUDA}.html pip install torch-spline-conv -f https://data.pyg.org/whl/torch-1.13.0+${CUDA}.html
``` ```
where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu113`, or `cu116` depending on your PyTorch installation. where `${CUDA}` should be replaced by either `cpu`, `cu116`, or `cu117` depending on your PyTorch installation.
| | `cpu` | `cu102` | `cu113` | `cu116` | | | `cpu` | `cu116` | `cu117` |
|-------------|-------|---------|---------|---------| |-------------|-------|---------|---------|
| **Linux** | ✅ | ✅ | ✅ | ✅ | | **Linux** | ✅ | ✅ | ✅ |
| **Windows** | ✅ | | ✅ | ✅ | | **Windows** | ✅ | ✅ | ✅ |
| **macOS** | ✅ | | | | | **macOS** | ✅ | | |
**Note:** Binaries of older versions are also provided for PyTorch 1.4.0, PyTorch 1.5.0, PyTorch 1.6.0, PyTorch 1.7.0/1.7.1, PyTorch 1.8.0/1.8.1, PyTorch 1.9.0, PyTorch 1.10.0/1.10.1/1.10.2 and PyTorch 1.11.0 (following the same procedure). **Note:** Binaries of older versions are also provided for PyTorch 1.4.0, PyTorch 1.5.0, PyTorch 1.6.0, PyTorch 1.7.0/1.7.1, PyTorch 1.8.0/1.8.1, PyTorch 1.9.0, PyTorch 1.10.0/1.10.1/1.10.2, PyTorch 1.11.0 and PyTorch 1.12.0/1.12.1 (following the same procedure).
For older versions, you need to explicitly specify the latest supported version number or install via `pip install --no-index` in order to prevent a manual installation from source. For older versions, you need to explicitly specify the latest supported version number or install via `pip install --no-index` in order to prevent a manual installation from source.
You can look up the latest supported version number [here](https://data.pyg.org/whl). You can look up the latest supported version number [here](https://data.pyg.org/whl).
......
conda/pytorch-cluster/README.md
View file @ 84bbb714
``` ```
./build_conda.sh 3.9 1.13.0 cu116 # python, pytorch and cuda version ./build_conda.sh 3.9 2.0.0 cu117 # python, pytorch and cuda version
``` ```
conda/pytorch-cluster/build_conda.sh
View file @ 84bbb714
...@@ -10,6 +10,9 @@ if [ "${CUDA_VERSION}" = "cpu" ]; then ...@@ -10,6 +10,9 @@ if [ "${CUDA_VERSION}" = "cpu" ]; then
export CONDA_CUDATOOLKIT_CONSTRAINT="cpuonly # [not osx]" export CONDA_CUDATOOLKIT_CONSTRAINT="cpuonly # [not osx]"
else else
case $CUDA_VERSION in case $CUDA_VERSION in
cu118)
export CONDA_CUDATOOLKIT_CONSTRAINT="pytorch-cuda==11.8.*"
;;
cu117) cu117)
export CONDA_CUDATOOLKIT_CONSTRAINT="pytorch-cuda==11.7.*" export CONDA_CUDATOOLKIT_CONSTRAINT="pytorch-cuda==11.7.*"
;; ;;
......
conda/pytorch-cluster/meta.yaml
View file @ 84bbb714
package: package:
name: pytorch-cluster name: pytorch-cluster
version: 1.6.0 version: 1.6.1
source: source:
path: ../.. path: ../..
......
setup.py
View file @ 84bbb714
...@@ -11,7 +11,7 @@ from torch.__config__ import parallel_info ...@@ -11,7 +11,7 @@ from torch.__config__ import parallel_info
from torch.utils.cpp_extension import (CUDA_HOME, BuildExtension, CppExtension, from torch.utils.cpp_extension import (CUDA_HOME, BuildExtension, CppExtension,
CUDAExtension) CUDAExtension)
__version__ = '1.6.0' __version__ = '1.6.1'
URL = 'https://github.com/rusty1s/pytorch_cluster' URL = 'https://github.com/rusty1s/pytorch_cluster'
WITH_CUDA = False WITH_CUDA = False
......
test/test_nearest.py
View file @ 84bbb714
...@@ -38,33 +38,27 @@ def test_nearest(dtype, device): ...@@ -38,33 +38,27 @@ def test_nearest(dtype, device):
batch_x = tensor([0, 0, 0, 0, 1, 1, 1, 1], torch.long, device) batch_x = tensor([0, 0, 0, 0, 1, 1, 1, 1], torch.long, device)
batch_y = tensor([0, 0, 0, 0], torch.long, device) batch_y = tensor([0, 0, 0, 0], torch.long, device)
with pytest.raises(ValueError): with pytest.raises(ValueError):
out = nearest(x, y, batch_x, batch_y) nearest(x, y, batch_x, batch_y)
# Invalid input: instance 1 only in batch_x (implicitly as batch_y=None) # Invalid input: instance 1 only in batch_x (implicitly as batch_y=None)
with pytest.raises(ValueError): with pytest.raises(ValueError):
out = nearest(x, y, batch_x, batch_y=None) nearest(x, y, batch_x, batch_y=None)
# Valid input: instance 1 only in batch_y
batch_x = tensor([0, 0, 0, 0, 0, 0, 0, 0], torch.long, device)
batch_y = tensor([0, 0, 1, 1], torch.long, device)
out = nearest(x, y, batch_x, batch_y)
assert out.tolist() == [0, 0, 1, 1, 0, 0, 1, 1]
# Invalid input: instance 2 only in batch_x # Invalid input: instance 2 only in batch_x
# (i.e.instance in the middle missing) # (i.e.instance in the middle missing)
batch_x = tensor([0, 0, 1, 1, 2, 2, 3, 3], torch.long, device) batch_x = tensor([0, 0, 1, 1, 2, 2, 3, 3], torch.long, device)
batch_y = tensor([0, 1, 3, 3], torch.long, device) batch_y = tensor([0, 1, 3, 3], torch.long, device)
with pytest.raises(ValueError): with pytest.raises(ValueError):
out = nearest(x, y, batch_x, batch_y) nearest(x, y, batch_x, batch_y)
# Invalid input: batch_x unsorted # Invalid input: batch_x unsorted
batch_x = tensor([0, 0, 1, 0, 0, 0, 0], torch.long, device) batch_x = tensor([0, 0, 1, 0, 0, 0, 0], torch.long, device)
batch_y = tensor([0, 0, 1, 1], torch.long, device) batch_y = tensor([0, 0, 1, 1], torch.long, device)
with pytest.raises(ValueError): with pytest.raises(ValueError):
out = nearest(x, y, batch_x, batch_y) nearest(x, y, batch_x, batch_y)
# Invalid input: batch_y unsorted # Invalid input: batch_y unsorted
batch_x = tensor([0, 0, 0, 0, 1, 1, 1, 1], torch.long, device) batch_x = tensor([0, 0, 0, 0, 1, 1, 1, 1], torch.long, device)
batch_y = tensor([0, 0, 1, 0], torch.long, device) batch_y = tensor([0, 0, 1, 0], torch.long, device)
with pytest.raises(ValueError): with pytest.raises(ValueError):
out = nearest(x, y, batch_x, batch_y) nearest(x, y, batch_x, batch_y)
torch_cluster/__init__.py
View file @ 84bbb714
...@@ -3,7 +3,7 @@ import os.path as osp ...@@ -3,7 +3,7 @@ import os.path as osp
import torch import torch
__version__ = '1.6.0' __version__ = '1.6.1'
for library in [ for library in [
'_version', '_grid', '_graclus', '_fps', '_rw', '_sampler', '_nearest', '_version', '_grid', '_graclus', '_fps', '_rw', '_sampler', '_nearest',
......
torch_cluster/nearest.py
View file @ 84bbb714
from typing import Optional from typing import Optional
import torch
import scipy.cluster import scipy.cluster
import torch
def nearest(x: torch.Tensor, y: torch.Tensor, def nearest(
batch_x: Optional[torch.Tensor] = None, x: torch.Tensor,
batch_y: Optional[torch.Tensor] = None) -> torch.Tensor: y: torch.Tensor,
batch_x: Optional[torch.Tensor] = None,
batch_y: Optional[torch.Tensor] = None,
) -> torch.Tensor:
r"""Clusters points in :obj:`x` together which are nearest to a given query r"""Clusters points in :obj:`x` together which are nearest to a given query
point in :obj:`y`. point in :obj:`y`.
...@@ -43,9 +46,9 @@ def nearest(x: torch.Tensor, y: torch.Tensor, ...@@ -43,9 +46,9 @@ def nearest(x: torch.Tensor, y: torch.Tensor,
assert x.size(1) == y.size(1) assert x.size(1) == y.size(1)
if batch_x is not None and (batch_x[1:] - batch_x[:-1] < 0).any(): if batch_x is not None and (batch_x[1:] - batch_x[:-1] < 0).any():
raise ValueError("batch_x is not sorted") raise ValueError("'batch_x' is not sorted")
if batch_y is not None and (batch_y[1:] - batch_y[:-1] < 0).any(): if batch_y is not None and (batch_y[1:] - batch_y[:-1] < 0).any():
raise ValueError("batch_y is not sorted") raise ValueError("'batch_y' is not sorted")
if x.is_cuda: if x.is_cuda:
if batch_x is not None: if batch_x is not None:
...@@ -72,30 +75,32 @@ def nearest(x: torch.Tensor, y: torch.Tensor, ...@@ -72,30 +75,32 @@ def nearest(x: torch.Tensor, y: torch.Tensor,
else: else:
ptr_y = torch.tensor([0, y.size(0)], device=y.device) ptr_y = torch.tensor([0, y.size(0)], device=y.device)
# if an instance in batch_x is non-empty, it must be # If an instance in `batch_x` is non-empty, it must be non-empty in
# non-empty in batch_y as well # `batch_y `as well:
instance_nonempty_x = (ptr_x[:-1] != ptr_x[1:]) nonempty_ptr_x = (ptr_x[1:] - ptr_x[:-1]) > 0
instance_nonempty_y = (ptr_y[:len(ptr_x)-1] != ptr_y[1:len(ptr_x)]) nonempty_ptr_y = (ptr_y[1:] - ptr_y[:-1]) > 0
if (len(ptr_x) > len(ptr_y) or if not torch.equal(nonempty_ptr_x, nonempty_ptr_y):
(instance_nonempty_x & ~instance_nonempty_y).any()): raise ValueError("Some batch indices occur in 'batch_x' "
raise ValueError("Some batch index occurs in batch_x " "that do not occur in 'batch_y'")
"that does not occur in batch_y")
return torch.ops.torch_cluster.nearest(x, y, ptr_x, ptr_y) return torch.ops.torch_cluster.nearest(x, y, ptr_x, ptr_y)
else: else:
if (batch_x is None) != (batch_y is None):
raise ValueError("Either both or none of batch_x, batch_y " if batch_x is None and batch_y is not None:
"may be None") batch_x = x.new_zeros(x.size(0), dtype=torch.long)
if batch_y is None and batch_x is not None:
batch_y = y.new_zeros(y.size(0), dtype=torch.long)
# Translate and rescale x and y to [0, 1]. # Translate and rescale x and y to [0, 1].
if batch_x is not None and batch_y is not None: if batch_x is not None and batch_y is not None:
# if an instance in batch_x is non-empty, it must be # If an instance in `batch_x` is non-empty, it must be non-empty in
# non-empty in batch_y as well # `batch_y `as well:
if not torch.isin(torch.unique_consecutive(batch_x), unique_batch_x = batch_x.unique_consecutive()
torch.unique_consecutive(batch_y), unique_batch_y = batch_y.unique_consecutive()
assume_unique=True).all(): if not torch.equal(unique_batch_x, unique_batch_y):
raise ValueError("Some batch index occurs in batch_x " raise ValueError("Some batch indices occur in 'batch_x' "
"that does not occur in batch_y") "that do not occur in 'batch_y'")
assert x.dim() == 2 and batch_x.dim() == 1 assert x.dim() == 2 and batch_x.dim() == 1
assert y.dim() == 2 and batch_y.dim() == 1 assert y.dim() == 2 and batch_y.dim() == 1
......
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