When determining the maximum MANP and precision, the `MaxMANPPass`
only takes into account results generated by an operation, but ignores
function parameters. However, encrypted function parameters are
assumed to have a MANP value of 1 and can have an arbitrary
precision. This patch takes into account function arguments by using
their default MANP values and the extracting their precision.
Add support for `tensor.extract` operations in the MANP pass. This
currently only supports extract operations on tensors of encrypted
integers, which are passed as function arguments, e.g.:
func @extract_ith(%t: tensor<10x!HLFHE.eint<5>>, %i: index) -> !HLFHE.eint<5>{
%c = tensor.extract %t[%i] : tensor<10x!HLFHE.eint<5>>
return %c : !HLFHE.eint<5>
}
This pass calculates the squared Minimal Arithmetic Noise Padding
(MANP) for each operation using the MANP pass and extracts the maximum
(non-squared) Minimal Arithmetic Noise Padding and the maximum
ecrypted integer width from.
This pass calculates the squared Minimal Arithmetic Noise Padding
(MANP) for each operation of a function and stores the result in an
integer attribute named "sqMANP". This metric is identical to the
squared 2-norm of the constant vector of an equivalent dot product
between a vector of encrypted integers resulting directly from an
encryption and a vector of plaintext constants.
The pass supports the following operations:
- HLFHE.dot_eint_int
- HLFHE.zero
- HLFHE.add_eint_int
- HLFHE.add_eint
- HLFHE.sub_int_eint
- HLFHE.mul_eint_int
- HLFHE.apply_lookup_table
If any other operation is encountered, the pass conservatively
fails. The pass further makes the optimistic assumption that all
values passed to a function are either the direct result of an
encryption of a noise-refreshing operation.
