-**mmcv-full**: comprehensive, with full features and various CUDA ops out of box. It takes longer time to build.
-**mmcv**: lite, without CUDA ops but all other features, similar to mmcv\<1.0.0. It is useful when you do not need those CUDA ops.
-**mmcv**: comprehensive, with full features and various CUDA ops out of box. It takes longer time to build.
-**mmcv-lite**: lite, without CUDA ops but all other features, similar to mmcv\<1.0.0. It is useful when you do not need those CUDA ops.
**Note**: Do not install both versions in the same environment, otherwise you may encounter errors like `ModuleNotFound`. You need to uninstall one before installing the other. `Installing the full version is highly recommended if CUDA is available`.
a. Install the full version.
Before installing mmcv-full, make sure that PyTorch has been successfully installed following the [official guide](https://pytorch.org/).
Before installing mmcv, make sure that PyTorch has been successfully installed following the [official guide](https://pytorch.org/).
We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA versions to simplify the building for **Linux and Windows systems**. In addition, you can run [check_installation.py](.dev_scripts/check_installation.py) to check the installation of mmcv-full after running the installation commands.
We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA versions to simplify the building for **Linux and Windows systems**. In addition, you can run [check_installation.py](.dev_scripts/check_installation.py) to check the installation of mmcv after running the installation commands.
i. Install the latest version.
The rule for installing the latest `mmcv-full` is as follows:
The rule for installing the latest `mmcv` is as follows:
**Note**: mmcv-full is only compiled on PyTorch 1.x.0 because the compatibility usually holds between 1.x.0 and 1.x.1. If your PyTorch version is 1.x.1, you can install mmcv-full compiled with PyTorch 1.x.0 and it usually works well. For example, if your PyTorch version is 1.8.1 and CUDA version is 11.1, you can use the following command to install mmcv-full.
**Note**: mmcv is only compiled on PyTorch 1.x.0 because the compatibility usually holds between 1.x.0 and 1.x.1. If your PyTorch version is 1.x.1, you can install mmcv compiled with PyTorch 1.x.0 and it usually works well. For example, if your PyTorch version is 1.8.1 and CUDA version is 11.1, you can use the following command to install mmcv.
**Note**: The pre-built packages provided above do not include all versions of mmcv-full, you can click on the corresponding links to see the supported versions. For example, you can click [cu102-torch1.8.0](https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/index.html) and you can see that `cu102-torch1.8.0` only provides 1.3.0 and above versions of mmcv-full. In addition, We no longer provide `mmcv-full` pre-built packages compiled with `PyTorch 1.3 & 1.4` since v1.3.17. You can find previous versions that compiled with PyTorch 1.3 & 1.4 [here](./docs/en/get_started/previous_versions.md). The compatibility is still ensured in our CI, but we will discard the support of PyTorch 1.3 & 1.4 next year.
**Note**: mmcv-full does not provide pre-built packages for `cu102-torch1.11` and `cu92-torch*` on Windows.
**Note**: mmcv does not provide pre-built packages for `cu102-torch1.11` and `cu92-torch*` on Windows.
Another way is to compile locally by running
```python
pipinstallmmcv-full
pipinstall'mmcv>=2.0.0rc1'
```
Note that the local compiling may take up to 10 mins.
...
...
@@ -238,7 +236,7 @@ Note that the local compiling may take up to 10 mins.
b. Install the lite version.
```python
pipinstallmmcv
pipinstallmmcv-lite
```
If you would like to build MMCV from source, please refer to the [guide](https://mmcv.readthedocs.io/en/latest/get_started/build.html).
There are two `Dockerfile` files to build docker images, one to build an image with the mmcv-full pre-built package and the other with the mmcv development environment.
There are two `Dockerfile` files to build docker images, one to build an image with the mmcv pre-built package and the other with the mmcv development environment.
The [Dockerfile](release/Dockerfile) installs latest released version of mmcv-full by default, but you can specify mmcv versions to install expected versions.
The [Dockerfile](release/Dockerfile) installs latest released version of mmcv by default, but you can specify mmcv versions to install expected versions.
-**mmcv-full**: comprehensive, with full features and various CUDA ops out of box. It takes longer time to build.
-**mmcv**: lite, without CUDA ops but all other features, similar to mmcv\<1.0.0. It is useful when you do not need those CUDA ops.
-**mmcv**: comprehensive, with full features and various CUDA ops out of box. It takes longer time to build.
-**mmcv-lite**: lite, without CUDA ops but all other features, similar to mmcv\<1.0.0. It is useful when you do not need those CUDA ops.
```{warning}
Do not install both versions in the same environment, otherwise you may encounter errors like `ModuleNotFound`. You need to uninstall one before installing the other. `Installing the full version is highly recommended if CUDA is avaliable`.
...
...
@@ -11,51 +11,51 @@ Do not install both versions in the same environment, otherwise you may encounte
a. Install the full version.
Before installing mmcv-full, make sure that PyTorch has been successfully installed following the [official guide](https://pytorch.org/).
Before installing mmcv, make sure that PyTorch has been successfully installed following the [official guide](https://pytorch.org/).
We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA versions to simplify the building for **Linux and Windows systems**. In addition, you can run [check_installation.py](.dev_scripts/check_installation.py) to check the installation of mmcv-full after running the installation commands.
We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA versions to simplify the building for **Linux and Windows systems**. In addition, you can run [check_installation.py](.dev_scripts/check_installation.py) to check the installation of mmcv after running the installation commands.
i. Install the latest version.
The rule for installing the latest `mmcv-full` is as follows:
The rule for installing the latest `mmcv` is as follows:
The pre-built packages provided above do not include all versions of mmcv-full, you can click on the corresponding links to see the supported versions. For example, if you click [cu102-torch1.8.0](https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/index.html), you can see that `cu102-torch1.8.0` only provides 1.3.0 and above versions of mmcv-full. In addition, We no longer provide `mmcv-full` pre-built packages compiled with `PyTorch 1.3 & 1.4` since v1.3.17. You can find previous versions that compiled with PyTorch 1.3 & 1.4 [here](./previous_versions.md). The compatibility is still ensured in our CI, but we will discard the support of PyTorch 1.3 & 1.4 next year.
```
```{note}
mmcv-full does not provide pre-built packages for `cu102-torch1.11` and `cu92-torch*` on Windows.
mmcv does not provide pre-built packages for `cu102-torch1.11` and `cu92-torch*` on Windows.
```
Another way is to compile locally by running
```python
pipinstallmmcv-full
pipinstall'mmcv>=2.0.0rc1'
```
Note that the local compiling may take up to 10 mins.
...
...
@@ -174,7 +170,7 @@ Note that the local compiling may take up to 10 mins.
b. Install the lite version.
```python
pipinstallmmcv
pipinstallmmcv-lite
```
If you would like to build MMCV from source, please refer to the [guide](https://mmcv.readthedocs.io/en/latest/get_started/build.html).