hpt 0.1.3

High Performance Tensor (HPT) - A fast, efficient, and user-friendly tensor computation library for Rust
Documentation 
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use hpt_common::axis::axis::{process_axes, Axis};
use hpt_common::error::base::TensorError;
use hpt_traits::tensor::{CommonBounds, TensorInfo};
use hpt_types::type_promote::{Cmp, NormalOut};

use crate::backend::Cpu;
use crate::ops::IndexReduce;
use crate::{
    backends::cpu::utils::reduce::reduce::{argmax, argmin},
    tensor_base::_Tensor,
};
use hpt_allocator::traits::{Allocator, AllocatorOutputRetrive};

impl<T, const DEVICE: usize, Al> IndexReduce for _Tensor<T, Cpu, DEVICE, Al>
where
    T: CommonBounds + NormalOut<Output = T> + Cmp<T, Output = bool>,
    Al: Allocator + 'static + Send + Sync,
    Al::Output: AllocatorOutputRetrive,
{
    type Output = _Tensor<i64, Cpu, DEVICE, Al>;

    fn argmax<S: Into<Axis>>(
        &self,
        axis: S,
        keep_dims: bool,
    ) -> std::result::Result<Self::Output, TensorError> {
        let axes: Vec<usize> = process_axes(axis, self.ndim())?;
        argmax(self, axes, 0, keep_dims, None)
    }

    fn argmin<S: Into<Axis>>(
        &self,
        axis: S,
        keep_dims: bool,
    ) -> std::result::Result<Self::Output, TensorError> {
        let axes: Vec<usize> = process_axes(axis, self.ndim())?;
        argmin(self, axes, 0, keep_dims, None)
    }
}