Trait auto_diff::op::OpTrait

pub trait OpTrait {
    fn get_name(&self) -> String;
    fn get_input_size(&self) -> usize;
    fn get_output_size(&self) -> usize;
    fn apply(&mut self, input: &[&Tensor], output: &[&Tensor]);
    fn grad(
        &self, 
        input: &[&Tensor], 
        output_grad: &[&Tensor], 
        input_grad: &[&Tensor]
    );
    fn get_values(&self) -> Vec<&Tensor>;
    fn set_values(&self, v: &[Tensor]);
    fn get_grads(&self) -> Vec<&Tensor>;

    fn call(&mut self, input: &[&Tensor]) -> Vec<Tensor> { ... }
}

All op is OpTrait

Required methods

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

Forward pass

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 set_values(&self, v: &[Tensor])

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

access gradient values

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Provided methods

fn call(&mut self, input: &[&Tensor]) -> Vec<Tensor>

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Implementors

impl OpTrait for Conv2d

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

Forward pass

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 set_values(&self, v: &[Tensor])

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

access gradient values

impl OpTrait for Linear

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

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

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

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

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

impl OpTrait for Add

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

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

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

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

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

impl OpTrait for Div

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

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

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

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

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

impl OpTrait for Mul

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

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

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

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

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

impl OpTrait for Sub

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

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

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

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

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

impl OpTrait for BCEWithLogitsLoss

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

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

access gradient values

impl OpTrait for CrossEntropyLoss

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

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

access gradient values

impl OpTrait for MSELoss

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

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

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

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

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

impl OpTrait for ELU

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

Forward pass

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

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

access gradient values

impl OpTrait for ReLU

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

Forward pass

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

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

access gradient values

impl OpTrait for Sigmoid

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

The first is the prediction, the second input is the label

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

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

access gradient values

impl OpTrait for Sine

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

Forward pass

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

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

access gradient values

impl OpTrait for Nop

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

fn apply(&mut self, _input: &[&Tensor], _output: &[&Tensor])

Forward pass

fn grad(
    &self,
    _input: &[&Tensor],
    _output_grad: &[&Tensor],
    _input_grad: &[&Tensor]
)

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

access weight values

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

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

access gradient values

impl OpTrait for View

fn get_name(&self) -> String

fn get_input_size(&self) -> usize

fn get_output_size(&self) -> usize

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

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

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

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

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

access gradient values

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