Struct autograd::tensor::TensorBuilder

pub struct TensorBuilder<F: Float> { /* fields omitted */ }

Builder for ag::Tensor returned by Tensor::builder.

This structure is required only when constructing user-defined Op.

use autograd as ag;
use ag::tensor::Input;

struct DummyOp {
   a: f32
}

impl ag::op::Op<f32> for DummyOp {
    fn compute(&self, _: &mut ag::op::ComputeContext<f32>) {}
    fn grad(&self, _: &mut ag::op::GradientContext<f32>) {}
}

ag::with(|g: &mut ag::Graph<f32>| {
    let input = &g.zeros(&[0]);
    let my_output: ag::Tensor<_> = ag::Tensor::builder()
        .set_inputs(&[
            Input::new(input), // immutable input
            Input::new_mut(input) // mutable input
        ])
        .build(g, DummyOp {a: 42.});
});

Implementations

impl<'graph, F: Float> TensorBuilder<F>

pub fn set_differentiable(self, differentiable: bool) -> TensorBuilder<F>

pub fn set_inputs(self, a: &[Input]) -> TensorBuilder<F>

Sets input tensors. See also Input.

pub fn set_inputs_vec(self, a: Vec<Input>) -> TensorBuilder<F>

Sets input tensors (vector). See also Input.

pub fn set_backprop_inputs(self, a: &[Input]) -> TensorBuilder<F>

Sets inputs for backprop.

Not required unless backprop-inputs are differs from normal-case inputs

pub fn build<O>(self, graph: &'graph Graph<F>, op: O) -> Tensor<'graph, F> where
    O: Op<F> + 'static, 

Finalizes this builder and creates a tensor with given Op in the graph.