deps: bump PyTorch CUDA requirements

.github/workflows/build.yml

@@ -37,8 +37,8 @@ concurrency:
   cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 env:
-  CUDA_VERSION: "11.6"
-  TEST_TORCH_SPECS: "cpu cu113 cu116"
+  CUDA_VERSION: "11.7"
+  TEST_TORCH_SPECS: "cpu cu116"
 
 jobs:
   build-sdist:

.github/workflows/lint.yml

@@ -36,7 +36,7 @@ jobs:
         uses: Jimver/cuda-toolkit@v0.2.7
         id: cuda-toolkit
         with:
-          cuda: "11.6.2"
+          cuda: "11.7.1"
           method: network
           sub-packages: '["nvcc"]'
       - run: |

.github/workflows/tests.yml

@@ -47,7 +47,7 @@ jobs:
         uses: Jimver/cuda-toolkit@v0.2.7
         id: cuda-toolkit
         with:
-          cuda: "11.6.2"
+          cuda: "11.7.1"
           method: network
           sub-packages: '["nvcc"]'
       - run: |

Dockerfile

@@ -7,7 +7,7 @@
 #   $ docker build --target devel --tag torchopt-devel:latest .
 #
 
-ARG cuda_docker_tag="11.6.2-cudnn8-devel-ubuntu20.04"
+ARG cuda_docker_tag="11.7.1-cudnn8-devel-ubuntu22.04"
 FROM nvidia/cuda:"${cuda_docker_tag}" AS builder
 
 ENV DEBIAN_FRONTEND=noninteractive

README.md

@@ -240,10 +240,10 @@ Requirements
 pip3 install torchopt
 ```
 
-If the minimum version of PyTorch is not satisfied, `pip` will install/upgrade it for you. Please be careful about the `torch` build for CPU / CUDA support (e.g. `cpu`, `cu102`, `cu113`). You may need to specify the extra index URL for the `torch` package:
+If the minimum version of PyTorch is not satisfied, `pip` will install/upgrade it for you. Please be careful about the `torch` build for CPU / CUDA support (e.g. `cpu`, `cu116`, `cu117`). You may need to specify the extra index URL for the `torch` package:
 
 ```bash
-pip3 install torchopt --extra-index-url https://download.pytorch.org/whl/cu116
+pip3 install torchopt --extra-index-url https://download.pytorch.org/whl/cu117
 ```
 
 See <https://pytorch.org> for more information about installing PyTorch.

conda-recipe.yaml

@@ -1,3 +1,18 @@
+# Copyright 2022 MetaOPT Team. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+#
 # Create virtual environment with command:
 #
 #   $ CONDA_OVERRIDE_CUDA=11.7 conda env create --file conda-recipe.yaml
@@ -8,7 +23,6 @@ name: torchopt
 channels:
   - pytorch
   - defaults
-  - nvidia/label/cuda-11.6.2
   - nvidia
   - conda-forge
 
@@ -30,16 +44,16 @@ dependencies:
   - wandb
 
   # Device select
-  - nvidia::cudatoolkit = 11.6
+  - pytorch::pytorch-cuda = 11.7
   - cudnn
 
   # Build toolchain
   - cmake >= 3.4
   - make
   - cxx-compiler
   - gxx = 10
-  - nvidia/label/cuda-11.6.2::cuda-nvcc
-  - nvidia/label/cuda-11.6.2::cuda-cudart-dev
+  - nvidia::cuda-nvcc
+  - nvidia::cuda-cudart-dev
   - patchelf >= 0.9
   - pybind11
 

docs/conda-recipe.yaml

@@ -31,7 +31,7 @@ dependencies:
 
   # Learning
   - pytorch::pytorch >= 1.13  # sync with project.dependencies
-  - pytorch::pytorch-mutex = *=*cpu*
+  - pytorch::cpuonly
   - pip:
       - torchviz
       - sphinxcontrib-katex  # for documentation
@@ -43,8 +43,8 @@ dependencies:
   - make
   - cxx-compiler
   - gxx = 10
-  - nvidia/label/cuda-11.6.2::cuda-nvcc
-  - nvidia/label/cuda-11.6.2::cuda-cudart-dev
+  - nvidia/label/cuda-11.7.1::cuda-nvcc
+  - nvidia/label/cuda-11.7.1::cuda-cudart-dev
   - pybind11
 
   # Misc

docs/source/developer/contributing.rst

@@ -91,8 +91,8 @@ To build compatible **manylinux2014** (:pep:`599`) wheels for distribution, you
 
     pip3 install --upgrade cibuildwheel
 
-    export TEST_TORCH_SPECS="cpu cu113 cu116"  # `torch` builds for testing
-    export CUDA_VERSION="11.6"                 # version of `nvcc` for compilation
+    export TEST_TORCH_SPECS="cpu cu116"  # `torch` builds for testing
+    export CUDA_VERSION="11.7"           # version of `nvcc` for compilation
     python3 -m cibuildwheel --platform=linux --output-dir=wheelhouse --config-file=pyproject.toml
 
 It will install the CUDA compiler with ``CUDA_VERSION`` in the build container. Then build wheel binaries for all supported CPython versions. The outputs will be placed in the ``wheelhouse`` directory.

examples/requirements.txt

@@ -1,4 +1,4 @@
---extra-index-url https://download.pytorch.org/whl/cu116
+--extra-index-url https://download.pytorch.org/whl/cu117
 torch >= 1.13
 torchvision
 

pyproject.toml

@@ -100,8 +100,8 @@ build-verbosity = 3
 environment.USE_FP16 = "ON"
 environment.CUDACXX = "/usr/local/cuda/bin/nvcc"
 environment.TORCH_CUDA_ARCH_LIST = "Common"
-environment.DEFAULT_CUDA_VERSION = "11.6"
-environment.DEFAULT_TEST_TORCH_SPECS = "cpu cu113 cu116"
+environment.DEFAULT_CUDA_VERSION = "11.7"
+environment.DEFAULT_TEST_TORCH_SPECS = "cpu cu116"
 environment-pass = ["CUDA_VERSION", "TEST_TORCH_SPECS"]
 container-engine = "docker"
 

tests/requirements.txt

@@ -1,4 +1,4 @@
---extra-index-url https://download.pytorch.org/whl/cu116
+--extra-index-url https://download.pytorch.org/whl/cu117
 torch >= 1.13
 
 --requirement ../requirements.txt

tutorials/requirements.txt

@@ -1,4 +1,4 @@
---extra-index-url https://download.pytorch.org/whl/cu116
+--extra-index-url https://download.pytorch.org/whl/cu117
 # Sync with project.dependencies
 torch >= 1.13
 torchvision