- prepares support for tensor types
- introduce _n_in and n_in() and requires_mix_values_func() for
IntermediateNode to know if they require a function to mix input values and
determine output value
- update BaseTracer to pass the class _mix_values_func to IntermediateNodes
that need it
- update NPTracer to stay consistent with current behavior regarding values
mixing
- refactor to take a function to generate the propore BaseValue to store in
its output
- refactor BaseTracer to force inheriting tracers to indicate how to build
a ConstantInput tracer
- remove "as import" for intermediate in hnumpy/tracing.py
- update compile to manage python dtypes
- add a helper function to determine BaseDataType of a constant python
scalar, int or float in dtype_helpers.py
- make BaseTracer type agnostic
- make ConstantInput type agnostic
- rename make_integer_to_hold_ints to make_integer_to_hold
- accept any values as input as we don't know which type this function will
be called with
- rename get_bits_to_represent_int to
get_bits_to_represent_value_as_integer
- add _is_encrypted to BaseValue
- remove EncryptedValue and ClearValue classes
- add a ScalarValue class
- add two helpers EncryptedValue and ClearValue which create a ScalarValue
either encrypted or not when passed a data_type
- rename to mix_scalar_values_determine_holding_dtype
- change typing
- add an helper script to serialize make commands
- serialize mypy commands as they may overwrite each others cache
- format coverage command to avoid being ridiculously long
- allow to construct graph from an existing networkx MultiDiGraph
- add a function to remove nodes unreachable from the outputs of the graph
- return the evaluated output when calling the OPGraph
This changes the semantics of `HLFHE.dot_eint_int` from memref-based
reference semantics to tensor-based value semantics. The former:
"HLFHE.dot_eint_int"(%arg0, %arg1, %arg2) :
(memref<Nx!HLFHE.eint<0>>, memref<Nxi32>, memref<!HLFHE.eint<0>>) -> ()
becomes:
"HLFHE.dot_eint_int"(%arg0, %arg1) :
(tensor<Nx!HLFHE.eint<0>>, tensor<Nxi32>) -> !HLFHE.eint<0>
As a side effect, data-flow analyses become much easier. With the
previous memref type of the plaintext argument it is difficult to
check whether the plaintext values are statically defined constants or
originate from a memory region changed at execution time (e.g., for
analyses evaluating the impact on noise). Changing the plaintext type
from `memref` to `vector` makes such analyses significantly easier.
