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README.md and INSTALL.md updates

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Summary: misc updates

Reviewed By: davidsonic

Differential Revision: D42072730

fbshipit-source-id: fc885d14346083bd6493f18e9d965b35a8d4bdfd
This commit is contained in:
Jeremy Reizenstein
2022-12-15 16:15:45 -08:00
committed by Facebook GitHub Bot
parent c773830b88
commit 3bbe26124a
2 changed files with 9 additions and 6 deletions
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12
INSTALL.md
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@@ -8,8 +8,8 @@
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.
- Linux or macOS or Windows
- Python 3.6, 3.7, 3.8 or 3.9
- PyTorch 1.8.0, 1.8.1, 1.9.0, 1.9.1, 1.10.0, 1.10.1, 1.10.2, 1.11.0 or 1.12.0.
- Python 3.8, 3.9 or 3.10
- PyTorch 1.9.0, 1.9.1, 1.10.0, 1.10.1, 1.10.2, 1.11.0, 1.12.0, 1.12.1 or 1.13.0.
- torchvision that matches the PyTorch installation. You can install them together as explained at pytorch.org to make sure of this.
- gcc & g++ ≥ 4.9
- [fvcore](https://github.com/facebookresearch/fvcore)
@@ -21,11 +21,11 @@ The runtime dependencies can be installed by running:
```
conda create -n pytorch3d python=3.9
conda activate pytorch3d
conda install -c pytorch pytorch=1.9.1 torchvision cudatoolkit=10.2
conda install -c pytorch pytorch=1.9.1 torchvision cudatoolkit=11.6
conda install -c fvcore -c iopath -c conda-forge fvcore iopath
```
For the CUB build time dependency, if you are using conda, you can continue with
For the CUB build time dependency, which you only need if you have CUDA older than 11.7, if you are using conda, you can continue with
```
conda install -c bottler nvidiacub
```
@@ -78,14 +78,14 @@ Or, to install a nightly (non-official, alpha) build:
conda install pytorch3d -c pytorch3d-nightly
```
### 2. Install from PyPI, on Mac only.
This works with pytorch 1.12.0 only. The build is CPU only.
This works with pytorch 1.13.0 only. The build is CPU only.
```
pip install pytorch3d
```
### 3. Install wheels for Linux
We have prebuilt wheels with CUDA for Linux for PyTorch 1.11.0, for each of the supported CUDA versions,
for Python 3.7, 3.8 and 3.9. This is for ease of use on Google Colab.
for Python 3.8 and 3.9. This is for ease of use on Google Colab.
These are installed in a special way.
For example, to install for Python 3.8, PyTorch 1.11.0 and CUDA 11.3
```