Enum TrainingTier 

pub enum TrainingTier {
    Open,
    Verified,
    Confidential,
}

Trust tier selected by the sponsor at task posting. Defines what the trainer hardware must provide and how rewards/penalties scale.

Per AI.md §7.3.3: training compute is TEE-optional (Open tier), key custody and verification are TEE-mandatory in every tier.

Variants

Open

Any GPU or CPU, no TEE attestation required for training compute. Trust comes from stake bonding, Byzantine-robust aggregation, and redundant fragment assignment. Default and cheapest.

Verified

Trainer posts a TEE attestation per round binding {program hash, data shard hash, model hash, DID}. Higher reward weight.

Confidential

TEE-resident training. Data is sealed to the enclave; the host OS never sees cleartext. Used for private datasets.

Implementations

impl TrainingTier

pub fn from_str_lossy(s: &str) -> Self

Parse a tier from a string label (case-insensitive). Falls back to Open for unknown labels.

Trait Implementations

impl Clone for TrainingTier

fn clone(&self) -> TrainingTier

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Copy for TrainingTier

impl Debug for TrainingTier

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

Formats the value using the given formatter.

impl Default for TrainingTier

fn default() -> TrainingTier

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for TrainingTier

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for TrainingTier

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

Formats the value using the given formatter.

impl Eq for TrainingTier

impl Hash for TrainingTier

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 TrainingTier

fn eq(&self, other: &TrainingTier) -> 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 TrainingTier

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 TrainingTier