Enum GraphEncoding

#[repr(u8)]
pub enum GraphEncoding {
    Openvino = 0,
    Onnx = 1,
    Tensorflow = 2,
    Pytorch = 3,
    Tensorflowlite = 4,
    Ggml = 5,
    Autodetect = 6,
}

Describes the encoding of the graph. This allows the API to be implemented by various backends that encode (i.e., serialize) their graph IR with different formats.

Variants

Openvino = 0

Onnx = 1

Tensorflow = 2

Pytorch = 3

Tensorflowlite = 4

Ggml = 5

Autodetect = 6

Trait Implementations

impl Clone for GraphEncoding

fn clone(&self) -> GraphEncoding

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for GraphEncoding

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

Formats the value using the given formatter.

impl Display for GraphEncoding

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

Formats the value using the given formatter.

impl FromStr for GraphEncoding

type Err = GraphEncodingParseError

The associated error which can be returned from parsing.

fn from_str(s: &str) -> Result<Self, Self::Err>

Parses a string s to return a value of this type.

impl Hash for GraphEncoding

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 GraphEncoding

fn eq(&self, other: &GraphEncoding) -> 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 ComponentType for GraphEncoding

impl Copy for GraphEncoding

impl Eq for GraphEncoding

impl Lift for GraphEncoding

impl Lower for GraphEncoding

impl StructuralPartialEq for GraphEncoding