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.