Compatibility

Supported operations

Here are the operations you can use inside the function you are compiling:

Some of these operations are not supported between two encrypted values. A detailed error will be raised if you try to do something that is not supported.

Supported Python operators.

• __abs__

• __add__

• __and__

• __eq__

• __floordiv__

• __ge__

• __getitem__

• __gt__

• __invert__

• __le__

• __lshift__

• __lt__

• __matmul__

• __mod__

• __mul__

• __ne__

• __neg__

• __or__

• __pos__

• __pow__

• __radd__

• __rand__

• __rfloordiv__

• __rlshift__

• __rmatmul__

• __rmod__

• __rmul__

• __ror__

• __round__

• __rpow__

• __rrshift__

• __rshift__

• __rsub__

• __rtruediv__

• __rxor__

• __sub__

• __truediv__

• __xor__

Supported NumPy functions.

• np.absolute

• np.add

• np.arccos

• np.arccosh

• np.arcsin

• np.arcsinh

• np.arctan

• np.arctan2

• np.arctanh

• np.around

• np.bitwise_and

• np.bitwise_or

• np.bitwise_xor

• np.broadcast_to

• np.cbrt

• np.ceil

• np.clip

• np.concatenate

• np.copysign

• np.cos

• np.cosh

• np.deg2rad

• np.degrees

• np.dot

• np.equal

• np.exp

• np.exp2

• np.expand_dims

• np.expm1

• np.fabs

• np.float_power

• np.floor

• np.floor_divide

• np.fmax

• np.fmin

• np.fmod

• np.gcd

• np.greater

• np.greater_equal

• np.heaviside

• np.hypot

• np.invert

• np.isfinite

• np.isinf

• np.isnan

• np.lcm

• np.ldexp

• np.left_shift

• np.less

• np.less_equal

• np.log

• np.log10

• np.log1p

• np.log2

• np.logaddexp

• np.logaddexp2

• np.logical_and

• np.logical_not

• np.logical_or

• np.logical_xor

• np.matmul

• np.maximum

• np.minimum

• np.multiply

• np.negative

• np.nextafter

• np.not_equal

• np.ones_like

• np.positive

• np.power

• np.rad2deg

• np.radians

• np.reciprocal

• np.remainder

• np.reshape

• np.right_shift

• np.rint

• np.round

• np.sign

• np.signbit

• np.sin

• np.sinh

• np.spacing

• np.sqrt

• np.square

• np.subtract

• np.sum

• np.tan

• np.tanh

• np.transpose

• np.true_divide

• np.trunc

• np.where

• np.zeros_like

Supported ndarray methods.

• np.ndarray.astype

• np.ndarray.clip

• np.ndarray.dot

• np.ndarray.flatten

• np.ndarray.reshape

• np.ndarray.transpose

Supported ndarray properties.

• np.ndarray.shape

• np.ndarray.ndim

• np.ndarray.size

• np.ndarray.T

Limitations

Control flow constraints.

Some Python control flow statements are not supported. You cannot have an if statement or a while statement for which the condition depends on an encrypted value. However, such statements are supported with constant values (e.g., for i in range(SOME_CONSTANT), if os.environ.get("SOME_FEATURE") == "ON":).

Type constraints.

You cannot have floating-point inputs or floating-point outputs. You can have floating-point intermediate values as long as they can be converted to an integer Table Lookup (e.g., (60 * np.sin(x)).astype(np.int64)).

Bit width constraints.

There is a limit on the bit width of encrypted values. We are constantly working on increasing this bit width. If you go above the limit, you will get an error.