How to Run CausalBench
You can use the python notebook attached, or follow along this page to get CausalBench into action.
Install CausalBench,
Please follow the installation guide for installing CausalBench.
Install the latest version of CausalBench package on pip:
pip install causalbench-asu
Create a context
context1: Context = Context.create(module_id=10,
name='Context1',
description='Test static context',
task='discovery.static',
datasets=[(dataset1, {'data': 'file1', 'ground_truth': 'file2'})],
models=[model1, model2],
metrics=[metric1, metric2])
Download a pre-set context
Downloading a pre-set context (or any component) is straightforward, create a context object, and provide the module_id
and version
you'd like to download from the CausalBench context repository.
context1: Context = Context(module_id=1, version=1)
Upload a component
You can publish any component with the publish()
function. Publish function takes in the public
boolean argument which is False
by default. In case you wish to publish directly as public, set the argument as True
.
context1.publish(public=True)
Run a benchmark
With a set context, running a benchmark is done with execute()
function.
run: Run = context1.execute()
This will execute the benchmark.
You can also print the run using print(run)
command.
Upload results
Uploading results works the same as uploading any component, by using the publish()
function.
run.publish(public=True)
Example CausalBench Execution:
This example will fetch a context, execute it, and upload the results.
from causalbench.modules import Run
from causalbench.modules.context import Context
def main():
# Select and fetch the Context
context1: Context = Context(module_id=1, version=1)
# Run selected Context
run: Run = context1.execute()
# Print Run execution results
print(run)
# Publish the Run
run.publish()
if __name__ == '__main__':
main()