Struct auto_diff::op::loss::CrossEntropyLoss

pub struct CrossEntropyLoss { /* private fields */ }

CrossEntropyLoss

Implementations

impl CrossEntropyLoss

pub fn new() -> CrossEntropyLoss

Trait Implementations

impl Default for CrossEntropyLoss

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for CrossEntropyLoss

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

Deserialize this value from the given Serde deserializer.

impl OpTrait for CrossEntropyLoss

fn apply(&self, input: &[Tensor], output: &[Tensor])

The first is the prediction, the second input is the label ORDER IS IMPORTANT, SECOND ARGUMENT WON’T GET GRADEINT.

fn grad(&self, input: &[Tensor], output_grad: &[Tensor], input_grad: &[Tensor])

Given the forward input value and backward output_grad, Update weight gradient. return backward input gradeint.

fn get_values(&self) -> Vec<Tensor>

access weight values

fn get_grads(&self) -> Vec<Tensor>

access gradient values

fn get_name(&self) -> &'static str

A conventional name for the op

fn get_input_size(&self) -> usize

The number of input needs by this op.

fn get_output_size(&self) -> usize

The number of output produced by this op.

fn set_values(&self, _v: &[Tensor])

fn as_any(&self) -> &dyn Any

impl Serialize for CrossEntropyLoss

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

Serialize this value into the given Serde serializer.