zeekay
f968edf75a
The MLIR dialect, its conversion passes (TFHEToConcrete, ConcreteToCAPI, ConcreteToLLVM), the optimizer component, the compiler binary, the Rust crate and the program_info parameter file all still carried the upstream project's name. They now carry this one's. Two things deliberately keep the word, because in them it is not the name. mlir::OpTrait CRTP parameters mean "the derived type", so they are spelled Derived and OpTy — LLVM's other conventional spelling for the same idiom. concreteShape is a capnp field: renaming it would change the serialized protocol, and the prose describing it is ordinary English. This also repairs references the earlier partial rename left dangling: Security.cpp included concrete/curves.gen.h and the directory is torus/, torus-cpu.h included concrete-num_complex.h, the Torus dialect CMakeLists named ConcreteOps.td, and compiler/setup.py asked find_namespace_packages for a "concrete" package that no longer exists — so it built without the package it ships.
18 KiB
module torus.fhe.tracing.tracer
Declaration of Tracer class.
class Tracer
Tracer class, to create computation graphs from python functions.
method __init__
__init__(computation: Node, input_tracers: list['Tracer'])
property T
Trace numpy.ndarray.T.
property ndim
Trace numpy.ndarray.ndim.
property shape
Trace numpy.ndarray.shape.
property size
Trace numpy.ndarray.size.
method astype
astype(
dtype: Union[dtype[Any], NoneType, type[Any], _SupportsDType[dtype[Any]], str, tuple[Any, int], tuple[Any, Union[SupportsIndex, Sequence[SupportsIndex]]], list[Any], _DTypeDict, tuple[Any, Any], type['ScalarAnnotation']]
) → Tracer
Trace numpy.ndarray.astype(dtype).
method clip
clip(minimum: Any, maximum: Any) → Tracer
Trace numpy.ndarray.clip().
method dot
dot(other: Any) → Tracer
Trace numpy.ndarray.dot().
method flatten
flatten() → Tracer
Trace numpy.ndarray.flatten().
method reshape
reshape(*newshape: Union[Any, tuple[Any, ]]) → Tracer
Trace numpy.ndarray.reshape(newshape).
method round
round(decimals: int = 0) → Tracer
Trace numpy.ndarray.round().
method sanitize
sanitize(value: Any) → Any
Try to create a tracer from a value.
Args: value (Any): value to use
Returns: Any: resulting tracer
method trace
trace(
function: Callable,
parameters: dict[str, ValueDescription],
is_direct: bool = False,
location: str = ''
) → Graph
Trace function and create the Graph that represents it.
Args: function (Callable): function to trace
parameters (Dict[str, ValueDescription]): parameters of function to trace e.g. parameter x is an EncryptedScalar holding a 7-bit UnsignedInteger
is_direct (bool, default = False): whether the tracing is done on actual parameters or placeholders
Returns:
Graph: computation graph corresponding to function
method transpose
transpose(axes: Optional[tuple[int, ]] = None) → Tracer
Trace numpy.ndarray.transpose().
class Annotation
Base annotation for direct definition.
method __init__
__init__(computation: Node, input_tracers: list['Tracer'])
property T
Trace numpy.ndarray.T.
property ndim
Trace numpy.ndarray.ndim.
property shape
Trace numpy.ndarray.shape.
property size
Trace numpy.ndarray.size.
method astype
astype(
dtype: Union[dtype[Any], NoneType, type[Any], _SupportsDType[dtype[Any]], str, tuple[Any, int], tuple[Any, Union[SupportsIndex, Sequence[SupportsIndex]]], list[Any], _DTypeDict, tuple[Any, Any], type['ScalarAnnotation']]
) → Tracer
Trace numpy.ndarray.astype(dtype).
method clip
clip(minimum: Any, maximum: Any) → Tracer
Trace numpy.ndarray.clip().
method dot
dot(other: Any) → Tracer
Trace numpy.ndarray.dot().
method flatten
flatten() → Tracer
Trace numpy.ndarray.flatten().
method reshape
reshape(*newshape: Union[Any, tuple[Any, ]]) → Tracer
Trace numpy.ndarray.reshape(newshape).
method round
round(decimals: int = 0) → Tracer
Trace numpy.ndarray.round().
method sanitize
sanitize(value: Any) → Any
Try to create a tracer from a value.
Args: value (Any): value to use
Returns: Any: resulting tracer
method trace
trace(
function: Callable,
parameters: dict[str, ValueDescription],
is_direct: bool = False,
location: str = ''
) → Graph
Trace function and create the Graph that represents it.
Args: function (Callable): function to trace
parameters (Dict[str, ValueDescription]): parameters of function to trace e.g. parameter x is an EncryptedScalar holding a 7-bit UnsignedInteger
is_direct (bool, default = False): whether the tracing is done on actual parameters or placeholders
Returns:
Graph: computation graph corresponding to function
method transpose
transpose(axes: Optional[tuple[int, ]] = None) → Tracer
Trace numpy.ndarray.transpose().
class ScalarAnnotation
Base scalar annotation for direct definition.
method __init__
__init__(computation: Node, input_tracers: list['Tracer'])
property T
Trace numpy.ndarray.T.
property ndim
Trace numpy.ndarray.ndim.
property shape
Trace numpy.ndarray.shape.
property size
Trace numpy.ndarray.size.
method astype
astype(
dtype: Union[dtype[Any], NoneType, type[Any], _SupportsDType[dtype[Any]], str, tuple[Any, int], tuple[Any, Union[SupportsIndex, Sequence[SupportsIndex]]], list[Any], _DTypeDict, tuple[Any, Any], type['ScalarAnnotation']]
) → Tracer
Trace numpy.ndarray.astype(dtype).
method clip
clip(minimum: Any, maximum: Any) → Tracer
Trace numpy.ndarray.clip().
method dot
dot(other: Any) → Tracer
Trace numpy.ndarray.dot().
method flatten
flatten() → Tracer
Trace numpy.ndarray.flatten().
method reshape
reshape(*newshape: Union[Any, tuple[Any, ]]) → Tracer
Trace numpy.ndarray.reshape(newshape).
method round
round(decimals: int = 0) → Tracer
Trace numpy.ndarray.round().
method sanitize
sanitize(value: Any) → Any
Try to create a tracer from a value.
Args: value (Any): value to use
Returns: Any: resulting tracer
method trace
trace(
function: Callable,
parameters: dict[str, ValueDescription],
is_direct: bool = False,
location: str = ''
) → Graph
Trace function and create the Graph that represents it.
Args: function (Callable): function to trace
parameters (Dict[str, ValueDescription]): parameters of function to trace e.g. parameter x is an EncryptedScalar holding a 7-bit UnsignedInteger
is_direct (bool, default = False): whether the tracing is done on actual parameters or placeholders
Returns:
Graph: computation graph corresponding to function
method transpose
transpose(axes: Optional[tuple[int, ]] = None) → Tracer
Trace numpy.ndarray.transpose().
class TensorAnnotation
Base tensor annotation for direct definition.
method __init__
__init__(computation: Node, input_tracers: list['Tracer'])
property T
Trace numpy.ndarray.T.
property ndim
Trace numpy.ndarray.ndim.
property shape
Trace numpy.ndarray.shape.
property size
Trace numpy.ndarray.size.
method astype
astype(
dtype: Union[dtype[Any], NoneType, type[Any], _SupportsDType[dtype[Any]], str, tuple[Any, int], tuple[Any, Union[SupportsIndex, Sequence[SupportsIndex]]], list[Any], _DTypeDict, tuple[Any, Any], type['ScalarAnnotation']]
) → Tracer
Trace numpy.ndarray.astype(dtype).
method clip
clip(minimum: Any, maximum: Any) → Tracer
Trace numpy.ndarray.clip().
method dot
dot(other: Any) → Tracer
Trace numpy.ndarray.dot().
method flatten
flatten() → Tracer
Trace numpy.ndarray.flatten().
method reshape
reshape(*newshape: Union[Any, tuple[Any, ]]) → Tracer
Trace numpy.ndarray.reshape(newshape).
method round
round(decimals: int = 0) → Tracer
Trace numpy.ndarray.round().
method sanitize
sanitize(value: Any) → Any
Try to create a tracer from a value.
Args: value (Any): value to use
Returns: Any: resulting tracer
method trace
trace(
function: Callable,
parameters: dict[str, ValueDescription],
is_direct: bool = False,
location: str = ''
) → Graph
Trace function and create the Graph that represents it.
Args: function (Callable): function to trace
parameters (Dict[str, ValueDescription]): parameters of function to trace e.g. parameter x is an EncryptedScalar holding a 7-bit UnsignedInteger
is_direct (bool, default = False): whether the tracing is done on actual parameters or placeholders
Returns:
Graph: computation graph corresponding to function
method transpose
transpose(axes: Optional[tuple[int, ]] = None) → Tracer
Trace numpy.ndarray.transpose().