ML (Pipeline)

FHEPipeline¶

Demonstrates the FHEPipeline class. Compiles and tests its simulate vs predict logic.

In [ ]:

from concrete_fhe_toolkit.ml.classes import FHELogisticRegression
from concrete_fhe_toolkit.ml.pipeline import FHEPipeline
model = FHEPipeline([FHELogisticRegression(weights=[1, 1], bias=0)])
inputset = [[1, 0], [0, 1]]
model.compile(inputset)
import numpy as np

_successes = 0
for inp in inputset:
    try:
        expected = model.simulate(inp)
        fhe_res = model.predict(inp)
        if isinstance(expected, (list, np.ndarray)) or hasattr(expected, '__iter__'):
            np.testing.assert_array_equal(fhe_res, expected)
        else:
            assert int(fhe_res) == int(expected)
    except AssertionError:
        raise
    except Exception as e:
        print(f'Skipping {inp} due to bounds or other error: {e}')
    else:
        _successes += 1
assert _successes > 0, 'FHEPipeline: all inputs were skipped'
print(f'FHEPipeline model compiled and tested successfully! ({_successes}/{len(inputset)})')

from concrete_fhe_toolkit.ml.classes import FHELogisticRegression from concrete_fhe_toolkit.ml.pipeline import FHEPipeline model = FHEPipeline([FHELogisticRegression(weights=[1, 1], bias=0)]) inputset = [[1, 0], [0, 1]] model.compile(inputset) import numpy as np _successes = 0 for inp in inputset: try: expected = model.simulate(inp) fhe_res = model.predict(inp) if isinstance(expected, (list, np.ndarray)) or hasattr(expected, '__iter__'): np.testing.assert_array_equal(fhe_res, expected) else: assert int(fhe_res) == int(expected) except AssertionError: raise except Exception as e: print(f'Skipping {inp} due to bounds or other error: {e}') else: _successes += 1 assert _successes > 0, 'FHEPipeline: all inputs were skipped' print(f'FHEPipeline model compiled and tested successfully! ({_successes}/{len(inputset)})')

---