Enum Framework 

pub enum Framework {
    PyTorch,
    TensorFlow,
    Jax,
    HuggingFaceTransformers,
    OnnxRuntime,
    ScikitLearn,
    Candle,
    Burn,
    FramewerxRmi,
}

AI frameworks with curated agentic profiles.

Variants

PyTorch

TensorFlow

Jax

HuggingFaceTransformers

OnnxRuntime

ScikitLearn

Candle

Burn

FramewerxRmi

RecursiveMachineIntelligence (RMI) — the built-in agentic-first framework of MachineGenetics (MechGen): self-describing ontology + manifest, binary-first effect-typed compute. Scored on the same axes as everything else.

Implementations

impl Framework

pub fn all() -> [Framework; 9]

All profiled frameworks, in fixed (deterministic) order.

pub fn name(self) -> &'static str

Canonical lowercase name.

pub fn from_name(name: &str) -> Option<Framework>

Parse a (case-insensitive) name; accepts common aliases (torch, tf, hf, scikit-learn, rmi, ort).

Trait Implementations

impl Clone for Framework

fn clone(&self) -> Framework

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Copy for Framework

impl Debug for Framework

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Eq for Framework

impl Hash for Framework

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl PartialEq for Framework

fn eq(&self, other: &Framework) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for Framework

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for Framework