mirror of
https://github.com/facebookresearch/pytorch3d.git
synced 2025-08-02 03:42:50 +08:00
a53a2d3731
Summary: Add conda packages for pytorch 1.5. Make wheels be only pytorch 1.5. Note that pytorch 1.4 has conda packages for cuda 9.2, 10.0 and 10.1, whilst pytorch 1.5 has packages for cuda 9.2, 10.1 and 10.2. We mirror these choices. Reviewed By: nikhilaravi Differential Revision: D21157392 fbshipit-source-id: 2f7311e6a83774a6d6c8afb8110b8bd9f37f1454
131 lines
3.6 KiB
Markdown
131 lines
3.6 KiB
Markdown
# Installation
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## Requirements
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### Core library
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The core library is written in PyTorch. Several components have underlying implementation in CUDA for improved performance. A subset of these components have CPU implementations in C++/Pytorch. It is advised to use PyTorch3D with GPU support in order to use all the features.
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- Linux or macOS or Windows
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- Python ≥ 3.6
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- PyTorch 1.4 or 1.5
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- torchvision that matches the PyTorch installation. You can install them together at pytorch.org to make sure of this.
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- gcc & g++ ≥ 4.9
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- [fvcore](https://github.com/facebookresearch/fvcore)
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- If CUDA is to be used, use at least version 9.2.
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These can be installed by running:
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```
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conda create -n pytorch3d python=3.8
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conda activate pytorch3d
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conda install -c pytorch pytorch torchvision cudatoolkit=10.2
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conda install -c conda-forge -c fvcore fvcore
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```
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### Tests/Linting and Demos
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For developing on top of PyTorch3D or contributing, you will need to run the linter and tests. If you want to run any of the notebook tutorials as `docs/tutorials` you will also need matplotlib.
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- scikit-image
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- black
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- isort
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- flake8
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- matplotlib
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- tdqm
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- jupyter
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- imageio
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These can be installed by running:
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```
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# Demos
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conda install jupyter
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pip install scikit-image matplotlib imageio
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# Tests/Linting
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pip install black isort flake8 flake8-bugbear flake8-comprehensions
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```
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## Installing prebuilt binaries for PyTorch3D
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After installing the above dependencies, run one of the following commands:
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### 1. Install with CUDA support from Anaconda Cloud, on Linux only
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```
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# Anaconda Cloud
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conda install pytorch3d -c pytorch3d
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```
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Or, to install a nightly (non-official, alpha) build:
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```
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# Anaconda Cloud
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conda install pytorch3d -c pytorch3d-nightly
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```
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### 2. Install without CUDA support from PyPI, on Linux and Mac
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```
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pip install pytorch3d
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```
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## Building / installing from source.
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CUDA support will be included if CUDA is enabled or if the environment variable
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`FORCE_CUDA` is set to `1`.
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### 1. Install from GitHub
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```
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pip install 'git+https://github.com/facebookresearch/pytorch3d.git'
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```
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**Install from Github on macOS:**
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```
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MACOSX_DEPLOYMENT_TARGET=10.14 CC=clang CXX=clang++ pip install 'git+https://github.com/facebookresearch/pytorch3d.git'
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```
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### 2. Install from a local clone
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```
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git clone https://github.com/facebookresearch/pytorch3d.git
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cd pytorch3d && pip install -e .
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```
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To rebuild after installing from a local clone run, `rm -rf build/ **/*.so` then `pip install -e .`. You often need to rebuild pytorch3d after reinstalling PyTorch.
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**Install from local clone on macOS:**
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```
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MACOSX_DEPLOYMENT_TARGET=10.14 CC=clang CXX=clang++ pip install -e .
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```
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**Install from local clone on Windows:**
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If you are using pre-compiled pytorch 1.4 and torchvision 0.5, you should make the following changes to the pytorch source code to successfully compile with Visual Studio 2019 (MSVC 19.16.27034) and CUDA 10.1.
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Change python/Lib/site-packages/torch/include/csrc/jit/script/module.h
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L466, 476, 493, 506, 536
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```
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-static constexpr *
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+static const *
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```
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Change python/Lib/site-packages/torch/include/csrc/jit/argument_spec.h
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L190
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```
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-static constexpr size_t DEPTH_LIMIT = 128;
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+static const size_t DEPTH_LIMIT = 128;
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```
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Change python/Lib/site-packages/torch/include/pybind11/cast.h
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L1449
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```
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-explicit operator type&() { return *(this->value); }
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+explicit operator type& () { return *((type*)(this->value)); }
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```
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After patching, you can go to "x64 Native Tools Command Prompt for VS 2019" to compile and install
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```
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cd pytorch3d
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python3 setup.py install
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```
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After installing, verify whether all unit tests have passed
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```
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cd tests
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python3 -m unittest discover -p *.py
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```
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