deps(torch): support PyTorch 2.0+ only (#215)

.github/workflows/build.yml

@@ -37,8 +37,8 @@ concurrency:
   cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 env:
-  CUDA_VERSION: "11.7"
-  TEST_TORCH_SPECS: "cpu cu116"
+  CUDA_VERSION: "12.1"
+  TEST_TORCH_SPECS: "cpu cu118"
 
 jobs:
   build:

.github/workflows/lint.yml

@@ -16,7 +16,7 @@ concurrency:
   cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 env:
-  CUDA_VERSION: "11.7"
+  CUDA_VERSION: "12.1"
 
 jobs:
   lint:

.github/workflows/tests.yml

@@ -27,7 +27,7 @@ concurrency:
   cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 env:
-  CUDA_VERSION: "11.7"
+  CUDA_VERSION: "12.1"
 
 jobs:
   test:

.pre-commit-config.yaml

@@ -26,11 +26,11 @@ repos:
       - id: debug-statements
       - id: double-quote-string-fixer
   - repo: https://github.com/pre-commit/mirrors-clang-format
-    rev: v18.1.4
+    rev: v18.1.5
     hooks:
       - id: clang-format
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.4.3
+    rev: v0.4.4
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]

CHANGELOG.md

@@ -25,7 +25,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Removed
 
--
+- Drop PyTorch 1.x support by [@XuehaiPan](https://github.com/XuehaiPan) in [#215](https://github.com/metaopt/torchopt/pull/215).
 
 ------
 

CMakeLists.txt

@@ -17,7 +17,7 @@ cmake_minimum_required(VERSION 3.11)  # for FetchContent
 project(torchopt LANGUAGES CXX)
 
 include(FetchContent)
-set(PYBIND11_VERSION v2.11.1)
+set(PYBIND11_VERSION v2.12.0)
 
 if(NOT CMAKE_BUILD_TYPE)
     set(CMAKE_BUILD_TYPE Release)

Dockerfile

@@ -7,7 +7,7 @@
 #   $ docker build --target devel --tag torchopt-devel:latest .
 #
 
-ARG cuda_docker_tag="11.7.1-cudnn8-devel-ubuntu22.04"
+ARG cuda_docker_tag="12.1.0-cudnn8-devel-ubuntu22.04"
 FROM nvidia/cuda:"${cuda_docker_tag}" AS builder
 
 ENV DEBIAN_FRONTEND=noninteractive

Makefile

@@ -236,7 +236,11 @@ docker-devel:
 docker: docker-base docker-devel
 
 docker-run-base: docker-base
-	docker run --network=host --gpus=all -v /:/host -h ubuntu -it $(PROJECT_NAME):$(COMMIT_HASH)
+	docker run -it --network=host --gpus=all --shm-size=4gb -v /:/host -v "${PWD}:/workspace" \
+		-h ubuntu -w /workspace $(PROJECT_NAME):$(COMMIT_HASH)
 
 docker-run-devel: docker-devel
-	docker run --network=host --gpus=all -v /:/host -h ubuntu -it $(PROJECT_NAME)-devel:$(COMMIT_HASH)
+	docker run -it --network=host --gpus=all --shm-size=4gb -v /:/host -v "${PWD}:/workspace" \
+		-h ubuntu -w /workspace $(PROJECT_NAME)-devel:$(COMMIT_HASH)
+
+docker-run: docker-run-base

README.md

@@ -425,11 +425,11 @@ Then run the following command to install TorchOpt from PyPI ([![PyPI](https://i
 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`, `cu116`, `cu117`).
+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`, `cu118`, `cu121`).
 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/cu117
+pip3 install torchopt --extra-index-url https://download.pytorch.org/whl/cu121
 ```
 
 See <https://pytorch.org> for more information about installing PyTorch.
@@ -450,7 +450,7 @@ git clone https://github.com/metaopt/torchopt.git
 cd torchopt
 
 # You may need `CONDA_OVERRIDE_CUDA` if conda fails to detect the NVIDIA driver (e.g. in docker or WSL2)
-CONDA_OVERRIDE_CUDA=11.7 conda env create --file conda-recipe-minimal.yaml
+CONDA_OVERRIDE_CUDA=12.1 conda env create --file conda-recipe-minimal.yaml
 
 conda activate torchopt
 make install-editable  # or run `pip3 install --no-build-isolation --editable .`

conda-recipe-minimal-cpu.yaml

@@ -26,11 +26,11 @@ channels:
   - conda-forge
 
 dependencies:
-  - python = 3.10
+  - python = 3.11
   - pip
 
   # Learning
-  - pytorch::pytorch >= 1.13  # sync with project.dependencies
+  - pytorch::pytorch >= 2.0  # sync with project.dependencies
   - pytorch::torchvision
   - pytorch::pytorch-mutex = *=*cpu*
   - pip:
@@ -40,10 +40,10 @@ dependencies:
   - cmake >= 3.11
   - make
   - cxx-compiler
-  - pybind11 >= 2.10.1
+  - pybind11 >= 2.11.1
 
   # Misc
   - optree >= 0.4.1
-  - typing-extensions >= 4.0.0
+  - typing-extensions
   - numpy
   - python-graphviz

conda-recipe-minimal.yaml

@@ -15,41 +15,41 @@
 #
 # Create virtual environment with command:
 #
-#   $ CONDA_OVERRIDE_CUDA=11.7 conda env create --file conda-recipe-minimal.yaml
+#   $ CONDA_OVERRIDE_CUDA=12.1 conda env create --file conda-recipe-minimal.yaml
 #
 
 name: torchopt
 
 channels:
   - pytorch
-  - nvidia/label/cuda-11.7.1
+  - nvidia/label/cuda-12.1.0
   - defaults
   - conda-forge
 
 dependencies:
-  - python = 3.10
+  - python = 3.11
   - pip
 
   # Learning
-  - pytorch::pytorch >= 1.13  # sync with project.dependencies
+  - pytorch::pytorch >= 2.0  # sync with project.dependencies
   - pytorch::torchvision
   - pytorch::pytorch-mutex = *=*cuda*
   - pip:
       - torchviz
 
   # Device select
-  - nvidia/label/cuda-11.7.1::cuda-toolkit = 11.7
+  - nvidia/label/cuda-12.1.0::cuda-toolkit = 12.1
 
   # Build toolchain
   - cmake >= 3.11
   - make
   - cxx-compiler
-  - nvidia/label/cuda-11.7.1::cuda-nvcc
-  - nvidia/label/cuda-11.7.1::cuda-cudart-dev
-  - pybind11 >= 2.10.1
+  - nvidia/label/cuda-12.1.0::cuda-nvcc
+  - nvidia/label/cuda-12.1.0::cuda-cudart-dev
+  - pybind11 >= 2.11.1
 
   # Misc
   - optree >= 0.4.1
-  - typing-extensions >= 4.0.0
+  - typing-extensions
   - numpy
   - python-graphviz

conda-recipe.yaml

@@ -15,49 +15,49 @@
 #
 # Create virtual environment with command:
 #
-#   $ CONDA_OVERRIDE_CUDA=11.7 conda env create --file conda-recipe.yaml
+#   $ CONDA_OVERRIDE_CUDA=12.1 conda env create --file conda-recipe.yaml
 #
 
 name: torchopt
 
 channels:
   - pytorch
-  - nvidia/label/cuda-11.7.1
+  - nvidia/label/cuda-12.1.0
   - defaults
   - conda-forge
 
 dependencies:
-  - python = 3.10
+  - python = 3.11
   - pip
 
   # Learning
-  - pytorch::pytorch >= 1.13  # sync with project.dependencies
+  - pytorch::pytorch >= 2.0  # sync with project.dependencies
   - pytorch::torchvision
   - pytorch::pytorch-mutex = *=*cuda*
   - pip:
       - torchviz
       - sphinxcontrib-katex  # for documentation
-  - jax                      # for tutorials
-  - jaxlib                   # for tutorials
-  - optax                    # for tutorials
-  - jaxopt                   # for tests
+  - conda-forge::jax         # for tutorials
+  - conda-forge::jaxlib      # for tutorials
+  - conda-forge::optax       # for tutorials
+  - conda-forge::jaxopt      # for tests
   - tensorboard              # for examples
 
   # Device select
-  - nvidia/label/cuda-11.7.1::cuda-toolkit = 11.7
+  - nvidia/label/cuda-12.1.0::cuda-toolkit = 12.1
 
   # Build toolchain
   - cmake >= 3.11
   - make
   - cxx-compiler
-  - nvidia/label/cuda-11.7.1::cuda-nvcc
-  - nvidia/label/cuda-11.7.1::cuda-cudart-dev
+  - nvidia/label/cuda-12.1.0::cuda-nvcc
+  - nvidia/label/cuda-12.1.0::cuda-cudart-dev
   - patchelf >= 0.14
-  - pybind11 >= 2.10.1
+  - pybind11 >= 2.11.1
 
   # Misc
   - optree >= 0.4.1
-  - typing-extensions >= 4.0.0
+  - typing-extensions
   - numpy
   - matplotlib-base
   - seaborn
@@ -83,10 +83,10 @@ dependencies:
   - pytest
   - pytest-cov
   - pytest-xdist
-  - isort >= 5.11.0
-  - conda-forge::black-jupyter >= 22.6.0
-  - pylint >= 2.15.0
-  - mypy >= 0.990
+  - isort
+  - conda-forge::black-jupyter
+  - pylint
+  - mypy
   - flake8
   - flake8-bugbear
   - flake8-comprehensions
@@ -96,8 +96,8 @@ dependencies:
   - ruff
   - doc8
   - pydocstyle
-  - clang-format >= 14
-  - clang-tools >= 14  # clang-tidy
-  - cpplint
+  - conda-forge::clang-format >= 14
+  - conda-forge::clang-tools >= 14  # clang-tidy
+  - conda-forge::cpplint
   - conda-forge::pre-commit
   - conda-forge::identify

docs/conda-recipe.yaml

@@ -15,23 +15,23 @@
 #
 # Create virtual environment with command:
 #
-#   $ CONDA_OVERRIDE_CUDA=11.7 conda env create --file docs/conda-recipe.yaml
+#   $ CONDA_OVERRIDE_CUDA=12.1 conda env create --file docs/conda-recipe.yaml
 #
 
 name: torchopt-docs
 
 channels:
   - pytorch
-  - nvidia/label/cuda-11.7.1
+  - nvidia/label/cuda-12.1.0
   - defaults
   - conda-forge
 
 dependencies:
-  - python = 3.10
+  - python = 3.11
   - pip
 
   # Learning
-  - pytorch::pytorch >= 1.13  # sync with project.dependencies
+  - pytorch::pytorch >= 2.0  # sync with project.dependencies
   - pytorch::cpuonly
   - pytorch::pytorch-mutex = *=*cpu*
   - pip:
@@ -42,13 +42,13 @@ dependencies:
   - cmake >= 3.11
   - make
   - cxx-compiler
-  - nvidia/label/cuda-11.7.1::cuda-nvcc
-  - nvidia/label/cuda-11.7.1::cuda-cudart-dev
-  - pybind11 >= 2.10.1
+  - nvidia/label/cuda-12.1.0::cuda-nvcc
+  - nvidia/label/cuda-12.1.0::cuda-cudart-dev
+  - pybind11 >= 2.11.1
 
   # Misc
   - optree >= 0.4.1
-  - typing-extensions >= 4.0.0
+  - typing-extensions
   - numpy
   - matplotlib-base
   - seaborn

docs/requirements.txt

@@ -1,6 +1,6 @@
 --extra-index-url https://download.pytorch.org/whl/cpu
 # Sync with project.dependencies
-torch >= 1.13
+torch >= 2.0
 
 --requirement ../requirements.txt
 

docs/source/developer/contributing.rst

@@ -17,7 +17,7 @@ Before contributing to TorchOpt, please follow the instructions below to setup.
 .. code-block:: bash
 
     # You may need `CONDA_OVERRIDE_CUDA` if conda fails to detect the NVIDIA driver (e.g. in docker or WSL2)
-    CONDA_OVERRIDE_CUDA=11.7 conda env create --file conda-recipe.yaml
+    CONDA_OVERRIDE_CUDA=12.1 conda env create --file conda-recipe.yaml
 
     conda activate torchopt
 
@@ -91,14 +91,14 @@ To build compatible **manylinux2014** (:pep:`599`) wheels for distribution, you
 
     pip3 install --upgrade cibuildwheel
 
-    export TEST_TORCH_SPECS="cpu cu116"  # `torch` builds for testing
-    export CUDA_VERSION="11.7"           # version of `nvcc` for compilation
+    export TEST_TORCH_SPECS="cpu cu118"  # `torch` builds for testing
+    export CUDA_VERSION="12.1"           # 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.
 
 To build a wheel for a specific CPython version, you can use the |CIBW_BUILD|_ environment variable.
-For example, the following command will build a wheel for Python 3.7:
+For example, the following command will build a wheel for Python 3.8:
 
 .. code-block:: bash
 

docs/source/index.rst

@@ -42,7 +42,7 @@ You can use the following commands with `conda <https://github.com/conda/conda>`
     cd torchopt
 
     # You may need `CONDA_OVERRIDE_CUDA` if conda fails to detect the NVIDIA driver (e.g. in docker or WSL2)
-    CONDA_OVERRIDE_CUDA=11.7 conda env create --file conda-recipe-minimal.yaml
+    CONDA_OVERRIDE_CUDA=12.1 conda env create --file conda-recipe-minimal.yaml
 
     conda activate torchopt
 

examples/requirements.txt

@@ -1,5 +1,5 @@
---extra-index-url https://download.pytorch.org/whl/cu117
-torch >= 1.13
+--extra-index-url https://download.pytorch.org/whl/cu121
+torch >= 2.0
 torchvision
 
 --requirement ../requirements.txt