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tensor.reduce_l2
fn reduce_l2(self: @Tensor<T>, axis: usize, keepdims: bool) -> Tensor<T>;
Computes the L2 norm of the input tensor's elements along the provided axes.
self(@Tensor<T>) - The input tensor.axis(usize) - The dimension to reduce.keepdims(bool) - If true, retains reduced dimensions with length 1.
- Panics if axis is not in the range of the input tensor's dimensions.
A new
Tensor<T> instance with the specified axis reduced by summing its elements.fn reduce_l2_example() -> Tensor {
let mut shape = ArrayTrait::<usize>::new();
shape.append(2);
shape.append(2);
let mut data = ArrayTrait::new();
data.append(FixedTrait::new_unscaled(1, false));
data.append(FixedTrait::new_unscaled(2, false));
data.append(FixedTrait::new_unscaled(3, false));
data.append(FixedTrait::new_unscaled(5, false));
let tensor = TensorTrait::<FP8x23>::new(shape.span(), data.span());
We can call `reduce_l2` function as follows.
return tensor.reduce_l2(axis: 1, keepdims: true);
}
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Last modified 20d ago