Environment Setup
=================

First check whether the current system environment meets ubuntu 22.04 and python 3.10. If not, please proceed to the next section *Basic Environment Configuration*; if satisfied, jump directly to *Install tpu_mlir*.

.. _env setup:

Basic Environment Configuration
---------------------------------
If you do not meet the above system environment, you need to use Docker, download the required image file from DockerHub https://hub.docker.com/r/sophgo/tpuc_dev, or use the following command to pull the image directly:


.. code-block:: shell
   :linenos:

   $ docker pull sophgo/tpuc_dev:v3.4

If the pulling fails, you can download the required image file from the official website development materials https://developer.sophgo.com/site/index/material/86/all.html, or use the following command to download and load the image:

.. code-block:: shell
   :linenos:

   $ wget https://sophon-assets.sophon.cn/sophon-prod-s3/drive/25/04/15/16/tpuc_dev_v3.4.tar.gz
   $ docker load -i tpuc_dev_v3.4.tar.gz


If you are using docker for the first time, you can execute the following commands to install and configure it (only for the first time):


.. _docker configuration:

.. code-block:: shell
   :linenos:

   $ sudo apt install docker.io
   $ sudo systemctl start docker
   $ sudo systemctl enable docker
   $ sudo groupadd docker
   $ sudo usermod -aG docker $USER
   $ newgrp docker

.. _docker container_setup:

If you download the image file, make sure the image file is in the current directory, and then create a container in the current directory as follows:


.. code-block:: shell

  # use --privileged to get root permission, if you don't need root permission, please remove this parameter
  $ docker run --privileged --name myname -v $PWD:/workspace -it sophgo/tpuc_dev:v3.4

where ``myname`` is the name of the container, which can be customized; ``$PWD`` is the current directory, synchronized with the container's ``/workspace`` directory.

Subsequent chapters assume that the user is already in the ``/workspace`` directory inside docker.


Install tpu_mlir
----------------------
Currently supported 2 methods to install, which are online and offline installation.

**Online installation**

Download and install directly from pypi, the latest version will be installed by default:

.. code-block:: shell

   $ pip install tpu_mlir

**Offline installation**

Download `tpu_mlir-*-py3-none-any.whl` from `Assets <https://github.com/sophgo/tpu-mlir/releases/>`_ on Github, then install with pip:

.. code-block:: shell

   $ pip install tpu_mlir-*-py3-none-any.whl

Install the dependency of tpu_mlir
------------------

tpu_mlir requires different dependencies when processing models of different frameworks, Both the online and offline installation methods require additional dependencies to be installed.

**Online installation**

For model files generated by ``onnx`` or ``torch`` when online installation, use the following command to install additional dependency environments:

.. code-block:: shell

   # install onnx dependency
   $ pip install tpu_mlir[onnx]
   # install torch dependency
   $ pip install tpu_mlir[torch]

There are 5 config currently supported:

.. code-block:: shell

   onnx, torch, tensorflow, caffe, paddle

You can install multiple dependency config in one command, or use ``all`` to install all dependencies:

.. code-block:: shell

   # install onnx, torch, caffe dependency at the same time
   $ pip install tpu_mlir[onnx,torch,caffe]
   # install all dependency
   $ pip install tpu_mlir[all]

**Offline installation**

Similarly, the offline installation method allows you to install additional dependencies using the following command:

.. code-block:: shell

   # install onnx dependency
   $ pip install tpu_mlir-*-py3-none-any.whl[onnx]
   # install all dependency
   $ pip install tpu_mlir-*-py3-none-any.whl[all]