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nn.leaky_relu
fn leaky_relu(inputs: @Tensor<T>, alpha: @T) -> Tensor<T>
Applies the leaky rectified linear unit (Leaky ReLU) activation function element-wise to a given tensor.
The Leaky ReLU function is defined as f(x) = alpha * x if x < 0, f(x) = x otherwise, where x is the input element.
inputs(@Tensor<T>) - A snapshot of a tensor to which the Leaky ReLU function will be applied.alpha(@T) - A snapshot of a fixed point scalar that defines the alpha value of the Leaky ReLU function.
A new fixed point tensor with the same shape as the input tensor and the Leaky ReLU function applied element-wise.
Constrain input and output types to fixed point tensors.
use array::{ArrayTrait, SpanTrait};
use orion::operators::tensor::{TensorTrait, Tensor, FP8x23};
use orion::operators::nn::{NNTrait, FP8x23NN};
use orion::numbers::{FP8x23, FixedTrait};
fn leaky_relu_example() -> Tensor<FP8x23> {
let tensor = TensorTrait::<FP8x23>::new(
shape: array![2, 3].span(),
data: array![
FixedTrait::new(1, false),
FixedTrait::new(2, false),
FixedTrait::new(1, true),
FixedTrait::new(2, true),
FixedTrait::new(0, false),
FixedTrait::new(0, false),
]
.span(),
);
let alpha = FixedTrait::from_felt(838861); // 0.1
return NNTrait::leaky_relu(@tensor, @alpha);
}
>>> [[8388608, 16777216, 838861], [1677722, 0, 0]]
// The fixed point representation of
[[1, 2, 0.1], [0.2, 0, 0]]
Last modified 2mo ago