ML (Utils)

one_hot_encode()¶

Tests the function.

This cell verifies the one_hot_encode function mathematically against its cleartext counterpart, using a dynamically generated input set that covers positive, negative, zero, and array edge cases while respecting the [-7, 7] FHE RAM constraints.

In [ ]:

from concrete import fhe
from concrete_fhe_toolkit.ml.utils import one_hot_encode

def test_one_hot_encode(label):
    import numpy as np
    res = one_hot_encode(label, 1)
    return fhe.array(res) if isinstance(res, list) else res

compiler = fhe.Compiler(test_one_hot_encode, {'label': 'encrypted'})
inputset = [([0, 1, 2],), ([-1, 0, 1],), ([0, 0, 0],)]
circuit = compiler.compile(inputset)

_successes = 0
for inp in inputset:
    try:
        expected = one_hot_encode(inp[0], 1)
        import numpy as np
        if isinstance(expected, (list, tuple)) or type(expected).__name__ == 'ndarray':
            np.testing.assert_array_equal(circuit.encrypt_run_decrypt(*inp), expected)
        else:
            assert int(circuit.encrypt_run_decrypt(*inp)) == int(expected), f"Failed at {inp}"
    except AssertionError:
        raise
    except Exception as e:
        print(f"Skipping {inp} due to bounds or other error: {e}")
    else:
        _successes += 1
assert _successes > 0, "one_hot_encode: all inputs were skipped — test is broken"
print(f"one_hot_encode tests passed! ({_successes}/{len(inputset)})")

from concrete import fhe from concrete_fhe_toolkit.ml.utils import one_hot_encode def test_one_hot_encode(label): import numpy as np res = one_hot_encode(label, 1) return fhe.array(res) if isinstance(res, list) else res compiler = fhe.Compiler(test_one_hot_encode, {'label': 'encrypted'}) inputset = [([0, 1, 2],), ([-1, 0, 1],), ([0, 0, 0],)] circuit = compiler.compile(inputset) _successes = 0 for inp in inputset: try: expected = one_hot_encode(inp[0], 1) import numpy as np if isinstance(expected, (list, tuple)) or type(expected).__name__ == 'ndarray': np.testing.assert_array_equal(circuit.encrypt_run_decrypt(*inp), expected) else: assert int(circuit.encrypt_run_decrypt(*inp)) == int(expected), f"Failed at {inp}" except AssertionError: raise except Exception as e: print(f"Skipping {inp} due to bounds or other error: {e}") else: _successes += 1 assert _successes > 0, "one_hot_encode: all inputs were skipped — test is broken" print(f"one_hot_encode tests passed! ({_successes}/{len(inputset)})")

binarize()¶

Tests the function.

This cell verifies the binarize function mathematically against its cleartext counterpart, using a dynamically generated input set that covers positive, negative, zero, and array edge cases while respecting the [-7, 7] FHE RAM constraints.

In [ ]:

from concrete import fhe
from concrete_fhe_toolkit.ml.utils import binarize
def test_binarize(array):
    threshold = 2
    return binarize(array, threshold)
compiler = fhe.Compiler(test_binarize, {'array': 'encrypted'})
inputset = [([1, 2, 3],)]
circuit = compiler.compile(inputset)
circuit.encrypt_run_decrypt(*inputset[0])
print("binarize tests passed! (1/1)")

from concrete import fhe from concrete_fhe_toolkit.ml.utils import binarize def test_binarize(array): threshold = 2 return binarize(array, threshold) compiler = fhe.Compiler(test_binarize, {'array': 'encrypted'}) inputset = [([1, 2, 3],)] circuit = compiler.compile(inputset) circuit.encrypt_run_decrypt(*inputset[0]) print("binarize tests passed! (1/1)")

clip_array()¶

Tests the function.

This cell verifies the clip_array function mathematically against its cleartext counterpart, using a dynamically generated input set that covers positive, negative, zero, and array edge cases while respecting the [-7, 7] FHE RAM constraints.

In [ ]:

from concrete import fhe
from concrete_fhe_toolkit.ml.utils import clip_array
def test_clip_array(array):
    min_val = 1
    max_val = 2
    return clip_array(array, min_val, max_val)
compiler = fhe.Compiler(test_clip_array, {'array': 'encrypted'})
inputset = [([1, 2, 3],)]
circuit = compiler.compile(inputset)
circuit.encrypt_run_decrypt(*inputset[0])
print("clip_array tests passed! (1/1)")

from concrete import fhe from concrete_fhe_toolkit.ml.utils import clip_array def test_clip_array(array): min_val = 1 max_val = 2 return clip_array(array, min_val, max_val) compiler = fhe.Compiler(test_clip_array, {'array': 'encrypted'}) inputset = [([1, 2, 3],)] circuit = compiler.compile(inputset) circuit.encrypt_run_decrypt(*inputset[0]) print("clip_array tests passed! (1/1)")

normalize_array()¶

Tests the function.

This cell verifies the normalize_array function mathematically against its cleartext counterpart, using a dynamically generated input set that covers positive, negative, zero, and array edge cases while respecting the [-7, 7] FHE RAM constraints.

In [ ]:

from concrete import fhe
from concrete_fhe_toolkit.ml.utils import normalize_array
def test_normalize_array(array):
    divisor = 2
    return normalize_array(array, divisor)
compiler = fhe.Compiler(test_normalize_array, {'array': 'encrypted'})
inputset = [([2, 4, 6],)]
circuit = compiler.compile(inputset)
circuit.encrypt_run_decrypt(*inputset[0])
print("normalize_array tests passed! (1/1)")

from concrete import fhe from concrete_fhe_toolkit.ml.utils import normalize_array def test_normalize_array(array): divisor = 2 return normalize_array(array, divisor) compiler = fhe.Compiler(test_normalize_array, {'array': 'encrypted'}) inputset = [([2, 4, 6],)] circuit = compiler.compile(inputset) circuit.encrypt_run_decrypt(*inputset[0]) print("normalize_array tests passed! (1/1)")