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AutogradContext

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pub struct AutogradContext {
  // private fields
}

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AutogradContext::AutogradContext

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fn AutogradContext::AutogradContext() -> AutogradContext

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AutogradContext::clear_graph

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fn AutogradContext::clear_graph(self : AutogradContext) -> Unit

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AutogradContext::zero_grad

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fn AutogradContext::zero_grad(self : AutogradContext) -> Unit

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Tensor

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pub struct Tensor {
  // private fields
}

impl Add for Tensor
impl Div for Tensor
impl Mul for Tensor
impl Neg for Tensor
impl Sub for Tensor

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Tensor::add

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fn Tensor::add(self : Tensor, that : Tensor) -> Tensor

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Tensor::assign_parameter_data

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fn Tensor::assign_parameter_data(self : Tensor, data : Array[Double]) -> Unit

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Tensor::backward

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fn Tensor::backward(self : Tensor) -> Unit

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Tensor::cross_entropy

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fn Tensor::cross_entropy(self : Tensor, targets : TokenIds) -> Tensor

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Tensor::data

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fn Tensor::data(self : Tensor) -> Array[Double]

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Tensor::div

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fn Tensor::div(self : Tensor, that : Tensor) -> Tensor

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Tensor::exp

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fn Tensor::exp(self : Tensor) -> Tensor

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Tensor::from_array

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fn Tensor::from_array(data : Array[Double], shape : Array[Int]) -> Tensor

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Tensor::gather_rows

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fn Tensor::gather_rows(self : Tensor, ids : TokenIds) -> Tensor

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Tensor::gelu

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fn Tensor::gelu(self : Tensor) -> Tensor

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Tensor::grad

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fn Tensor::grad(self : Tensor) -> Tensor?

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Tensor::layer_norm

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fn Tensor::layer_norm(self : Tensor, weight : Tensor, bias : Tensor, eps : Double) -> Tensor

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Tensor::log

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fn Tensor::log(self : Tensor) -> Tensor

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Tensor::matmul

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fn Tensor::matmul(self : Tensor, that : Tensor) -> Tensor

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Tensor::mean

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fn Tensor::mean(self : Tensor) -> Tensor

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Tensor::mul

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fn Tensor::mul(self : Tensor, that : Tensor) -> Tensor

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Tensor::neg

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fn Tensor::neg(self : Tensor) -> Tensor

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Tensor::numel

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fn Tensor::numel(self : Tensor) -> Int

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Tensor::ones

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fn Tensor::ones(shape : Array[Int]) -> Tensor

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Tensor::parameter

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fn Tensor::parameter(ctx : AutogradContext, data : Array[Double], shape : Array[Int]) -> Tensor

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Tensor::randn

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fn Tensor::randn(ctx : AutogradContext, shape : Array[Int], rng : 
Rand) -> Tensor

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Tensor::relu

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fn Tensor::relu(self : Tensor) -> Tensor

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Tensor::requires_grad

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fn Tensor::requires_grad(self : Tensor) -> Bool

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Tensor::reshape

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fn Tensor::reshape(self : Tensor, shape : Array[Int]) -> Tensor

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Tensor::scalar

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fn Tensor::scalar(value : Double) -> Tensor

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Tensor::shape

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fn Tensor::shape(self : Tensor) -> Array[Int]

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Tensor::softmax

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fn Tensor::softmax(self : Tensor, axis : Int) -> Tensor

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Tensor::sub

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fn Tensor::sub(self : Tensor, that : Tensor) -> Tensor

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Tensor::sum

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fn Tensor::sum(self : Tensor) -> Tensor

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Tensor::swap_axes

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fn Tensor::swap_axes(self : Tensor, axis_a : Int, axis_b : Int) -> Tensor

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Tensor::transpose2d

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fn Tensor::transpose2d(self : Tensor) -> Tensor

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Tensor::zeros

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fn Tensor::zeros(shape : Array[Int]) -> Tensor

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TokenIds

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pub struct TokenIds {
  // private fields
}

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TokenIds::TokenIds

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fn TokenIds::TokenIds(data : Array[Int], shape : Array[Int]) -> TokenIds

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TokenIds::data

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fn TokenIds::data(self : TokenIds) -> Array[Int]

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TokenIds::shape

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fn TokenIds::shape(self : TokenIds) -> Array[Int]

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check_grad

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fn check_grad(values : Array[Double], shape : Array[Int], f : (Tensor) -> Tensor, eps? : Double, tol? : Double) -> Bool

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