Getting Started with Python

NOTE: Iree's Python API is currently being reworked. Some of these instructions may be in a state of flux as they document the end state.

IREE has two primary Python APIs:

  • Compiler API: pyiree.compiler2, pyiree.compiler2.tf
  • Runtime API: pyiree.tf

There are additional ancillary modules that are not part of the public API.

Prerequisites

You should already have IREE cloned and building on your machine. See the other getting started guides for instructions.

Note:
    Support is only complete with CMake.

Minimally, the following CMake flags must be specified:

  • -DIREE_BUILD_PYTHON_BINDINGS=ON
  • -DIREE_BUILD_TENSORFLOW_COMPILER=ON: Optional. Also builds the TensorFlow compiler integration.

If building any parts of TensorFlow, you must have a working bazel command on your path. See the relevant “OS with Bazel” getting started doc for more information.

Python Setup

Install Python 3 >= 3.6 and pip, if needed.

Note:
    If using pyenv (or an interpreter manager that depends on it like asdf), you'll need to use --enable-shared during interpreter installation.

(Recommended) Setup a virtual environment with venv (or your preferred mechanism):

# Note that venv is only available in python3 and is therefore a good check
# that you are in fact running a python3 binary.
$ python -m venv .venv
$ source .venv/bin/activate
# When done: run 'deactivate'

Install packages:

$ python -m pip install --upgrade pip
$ python -m pip install numpy absl-py

# If using the TensorFlow integration
$ python -m pip install tf-nightly

Building

From the parent directory of the IREE git repository clone, create and enter a build directory, such as:

$ mkdir iree-build
$ cd iree-build

Then build like this:

# Also include -DIREE_BUILD_TENSORFLOW_COMPILER=ON if you want the TF compiler.
$ cmake ../iree -G Ninja \
    -DCMAKE_C_COMPILER=clang \
    -DCMAKE_CXX_COMPILER=clang++ \
    -DIREE_BUILD_PYTHON_BINDINGS=ON  .
$ cmake --build .

Running Python Tests

We continue to assume that we are in the build directory where we made the build in the previous section.

To run tests for core Python bindings built with CMake:

$ ctest -L bindings/python

To run tests for the TensorFlow integration, which include end-to-end backend comparison tests:

# TODO: Revisit once more patches land.
$ ctest -L integrations/tensorflow/e2e

# Or run individually as:
$ export PYTHONPATH=$(pwd)/bindings/python
# This is a Python 3 program. On some systems, such as Debian derivatives,
# use 'python3' instead of 'python'.
$ python ../iree/integrations/tensorflow/e2e/simple_arithmetic_test.py \
    --target_backends=iree_vmla --artifacts_dir=/tmp/artifacts

Using Colab

There are some sample colabs in the colab folder. If you have built the project with CMake/ninja and set your PYTHONPATH to the bindings/python directory in the build dir (or installed per below), you should be able to start a kernel by following the stock instructions at https://colab.research.google.com/ .

Installing and Packaging

There is a setup.py in the bindings/python directory under the build dir. To install into your (hopefully isolated) virtual env:

# See the above note about python3, and the above step setting PYTHONPATH.
python bindings/python/setup.py install

To create wheels (platform dependent and locked to your Python version without further config):

python bindings/python/setup.py bdist_wheel

Note that it is often helpful to differentiate between the environment used to build and the one used to install. While this is just “normal” python knowledge, here is an incantation to do so:

# From parent/build environment.
python -m pip freeze > /tmp/requirements.txt
deactivate  # If already in an environment

# Enter new scratch environment.
python -m venv ./.venv-scratch
source ./.venv-scratch/bin/activate
python -m pip install -r /tmp/requirements.txt

# Install IREE into the new environment.
python bindings/python/setup.py install