Struct burn::tensor::repr::QuantizedTensorDescription

pub struct QuantizedTensorDescription {
    pub tensor: TensorDescription,
    pub qparams: QuantizationParametersDescription,
    pub scheme: QuantizationScheme,
}

A quantized tensor description represents a snapshot of a quantized tensor when it was used.

Fields

tensor: TensorDescription

The quantized tensor.

qparams: QuantizationParametersDescription

The quantization parameters.

scheme: QuantizationScheme

The quantization scheme

Trait Implementations

impl Clone for QuantizedTensorDescription

fn clone(&self) -> QuantizedTensorDescription

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for QuantizedTensorDescription

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for QuantizedTensorDescription

fn deserialize<__D>( __deserializer: __D, ) -> Result<QuantizedTensorDescription, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Hash for QuantizedTensorDescription

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

where __H: Hasher,

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 QuantizedTensorDescription

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

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Eq for QuantizedTensorDescription

impl StructuralPartialEq for QuantizedTensorDescription