If you are mainly interested in using CIRCT from Python scripts, you need to compile both LLVM/MLIR and CIRCT with Python bindings enabled. Furthermore, you must use a unified build, where LLVM/MLIR and CIRCT are compiled together in one step.
CIRCT also includes an experimental, opinionated frontend for CIRCT's Python bindings, called PyCDE.
CIRCT provides a setup.py
script that take care of configuring and building LLVM/MLIR, CIRCT, and CIRCT's Python bindings. You can install the CIRCT Python bindings with the pip install
command:
$ cd circt
$ pip install lib/Bindings/Python
If you just want to build the wheel, use the pip wheel
command:
$ cd circt
$ pip wheel lib/Bindings/Python
This will create a circt_core-<version>-<python version>-<platform>.whl
file in the root of the repo.
There are some environment variables you can set to control the script. These should be prefixed to the above command(s), or export
ed in your shell.
To specify an existing CMake build directory, you can set CIRCT_CMAKE_BUILD_DIR
:
export CIRCT_CMAKE_BUILD_DIR=/path/to/your/build/dir
To specify an alternate LLVM directory, you can set CIRCT_LLVM_DIR
:
export CIRCT_LLVM_DIR=/path/to/your/llvm
Finally, you can set other environment variables to control CMake. By default, the script uses the same settings as Manual Compilation below. It is recommended to use Ninja and CCache, which can be accomplished with:
export CMAKE_GENERATOR=Ninja CMAKE_C_COMPILER_LAUNCHER=ccache CMAKE_CXX_COMPILER_LAUNCHER=ccache
All other CMake environment variables can also be used.
To manually compile LLVM/MLIR, CIRCT, and CIRCT's Python bindings, you can use a single CMake invocation like this:
$ cd circt
$ mkdir build
$ cd build
$ cmake -G Ninja ../llvm/llvm \
-DCMAKE_BUILD_TYPE=Debug \
-DLLVM_ENABLE_PROJECTS=mlir \
-DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_EXTERNAL_PROJECTS=circt \
-DLLVM_EXTERNAL_CIRCT_SOURCE_DIR=.. \
-DMLIR_ENABLE_BINDINGS_PYTHON=ON \
-DCIRCT_BINDINGS_PYTHON_ENABLED=ON
Afterwards, use ninja check-circt-integration
to ensure that the bindings work. (This will now additionally spin up a couple of Python scripts to test that they are accessible.)
If you want to try the bindings fresh from the compiler without installation, you need to ensure Python can find the generated modules:
export PYTHONPATH="$PWD/llvm/build/tools/circt/python_packages/circt_core"
If you are installing CIRCT through ninja install
anyway, the libraries and Python modules will be installed into the correct location automatically.
Now you are able to use the CIRCT dialects and infrastructure from a Python interpreter and script:
# silicon.py
import circt
from circt.ir import Context, InsertionPoint, IntegerType, Location, Module
from circt.dialects import hw, comb
with Context() as ctx, Location.unknown():
circt.register_dialects(ctx)
i42 = IntegerType.get_signless(42)
m = Module.create()
with InsertionPoint(m.body):
def magic(module):
xor = comb.XorOp.create(module.a, module.b)
return {"c": xor}
hw.HWModuleOp(name="magic",
input_ports=[("a", i42), ("b", i42)],
output_ports=[("c", i42)],
body_builder=magic)
print(m)
Running this script through python3 silicon.py
should print the following MLIR:
module {
hw.module @magic(%a: i42, %b: i42) -> (c: i42) {
%0 = comb.xor %a, %b : i42
hw.output %0 : i42
}
}