mirror of
https://github.com/facebookresearch/pytorch3d.git
synced 2025-08-02 03:42:50 +08:00
25d2e2c8b7
Summary: Use a consistent case for PyTorch3D (matching the logo...): replace all occurrences of PyTorch3d with PyTorch3D across the codebase (including documentation and notebooks) Reviewed By: wanyenlo, gkioxari Differential Revision: D20427546 fbshipit-source-id: 8c7697f51434c51e99b7fe271935932c72a1d9b9
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
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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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- CUDA 9.2 or 10.0 or 10.1
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- [fvcore](https://github.com/facebookresearch/fvcore)
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These can be installed by running:
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```
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conda create -n pytorch3d python=3.6
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conda activate pytorch3d
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conda install -c pytorch pytorch torchvision cudatoolkit=10.0
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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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