Instead of having one `getSQManp` implementation per op with a lot of repetition, the noise
calculation is now modular.
- Ops that implements`UnaryEint`/`BinaryInt`/`BinaryEint` interfaces share the operand noise
presence check.
- For many scalar ops no further calculation is needed. If it's not the case, an op can override
`sqMANP`.
- Integer operand types lookups are abstracted into `BinaryInt::operandIntType()`
- Finding largest operand value for a type is abstracted into `BinaryInt::operandMaxConstant`
- Noise calculation for matmul ops is simplified and it's now general enough to work for
`matmul_eint_int`, `matmul_int_eint` and `dot_eint_int` at once.
Key serialization for transfers between nodes in clusters was broken
since the changes introduced to separate keys from key parameters and
introduction of support for multi-key (ref
cacffadbd2).
This commit restores functionality for distributing keys to non-shared
memory nodes.
This changes the order of batching variants for binary TFHE
operations, such that batching of both operands is favored over
batching of a single operand.
The current batching pass only supports batching of operations that
have a single batchable operand, that can only be batched in one way
and that operate on scalar values. However, this does not allow for
efficient batching of all arithmetic operations in TFHE, since these
are often applied to pairs of scalar values from tensors, to tensors
and scalars or to tensors that can be grouped in higher-order tensors.
This commit introduces three new features for batching:
1. Support of multiple batchable operands
The operation interface for batching now allows for the
specification of multiple batchable operands. This set can be
composed of any subset of an operation's operands, i.e., it is
not limited to sets of operands with contiguous operand indexes.
2. Support for multiple batching variants
To account for multiple kinds of batching, the batching operation
interface `BatchableOpInterface` now supports variants. The
batching pass attempts to batch an operation by trying the
batching variants expressed via the interface in order until it
succeeds.
3. Support for batching of tensor values
Some operations that could be batched already operate on tensor
values. The new batching pass detects those patterns and groups
the batchable tensors' values into higher-dimensional tensors.
