| .. Licensed to the Apache Software Foundation (ASF) under one |
| or more contributor license agreements. See the NOTICE file |
| distributed with this work for additional information |
| regarding copyright ownership. The ASF licenses this file |
| to you under the Apache License, Version 2.0 (the |
| "License"); you may not use this file except in compliance |
| with the License. You may obtain a copy of the License at |
| |
| .. http://www.apache.org/licenses/LICENSE-2.0 |
| |
| .. Unless required by applicable law or agreed to in writing, |
| software distributed under the License is distributed on an |
| "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| KIND, either express or implied. See the License for the |
| specific language governing permissions and limitations |
| under the License. |
| |
| .. _installation: |
| |
| Installing TVM |
| ============== |
| |
| .. toctree:: |
| :maxdepth: 2 |
| |
| from_source |
| docker |
| nnpack |
| |
| Visit the :ref:`install TVM from source <install-from-source>` page to install TVM from the source code. Installing |
| from source gives you the maximum flexibility to configure the build effectively from the official source releases. |
| If you are interested in deploying to mobile or embedded devices, you do not need to |
| install the entire TVM stack on your device. Instead, you only need the runtime and can install using the |
| :ref:`deployment and integration guide <deploy-and-integration>`. |
| |
| If you would like to quickly try out TVM or run some demo and tutorials, you |
| can :ref:`install from Docker <docker-images>`. You can also use TVM locally through ``pip``. |
| |
| .. code-block:: |
| |
| # Linux/MacOS CPU build only! |
| # See tlcpack.ai for other pre-built binaries including CUDA |
| pip install apache-tvm |
| |
| For more details on installation of pre-built binaries, visit `tlcpack.ai <https://tlcpack.ai>`_. |