Compatibility

Supported operations

This document lists the operations you can use inside the function that you are compiling.

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

Concrete doesn not support some control flow statements, including the if and while statement when the condition depends on an encrypted value. However, control flow statements with constant values are allowed, for example, for i in range(SOME_CONSTANT), if os.environ.get("SOME_FEATURE") == "ON":.

Type constraints

Floating-point inputs or floating-point outputs are not supported. You can have floating-point intermediate values as long as they can be converted to an integer Table Lookup, for example, (60 * np.sin(x)).astype(np.int64).

Bit width constraints

Bit width of encrypted values has a limit. We are constantly working on increasing the bit width limit. Exceeding this limit will trigger an error.