rotta_rs 0.0.5

a Deep Learning library with rust language
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142

use std::vec;

use crate::rotta_rs_module::{ arrayy::{ negative_indexing, MultipleSum, RecFlatten } };

#[derive(Clone, Debug)]
pub struct Arrayy {
    pub value: Vec<f64>,
    pub shape: Vec<usize>,
}

impl Arrayy {
    // create

    pub fn new<T: RecFlatten>(arr: T) -> Arrayy {
        let (shape, vector) = arr.rec_flatten();
        Arrayy::from_vector(shape, vector)
    }

    pub fn from_vector(shape: Vec<usize>, vector: Vec<f64>) -> Arrayy {
        let length = shape.as_slice().multiple_sum();

        if length != vector.len() {
            panic!("shape and length of vector not same");
        }

        let arr = Arrayy {
            value: vector,
            shape: shape,
        };

        arr
    }

    pub fn zeros(shape: Vec<usize>) -> Arrayy {
        let length = shape.as_slice().multiple_sum();

        let arr = Arrayy {
            shape,
            value: vec![0.0; length],
        };
        arr
    }

    pub fn ones(shape: Vec<usize>) -> Arrayy {
        let length = shape.as_slice().multiple_sum();

        let arr = Arrayy {
            shape,
            value: vec![1.0; length],
        };
        arr
    }

    pub fn arrayy_from_shape_fn<F: FnMut() -> f64>(shape: Vec<usize>, mut f: F) -> Arrayy {
        let len = shape.multiple_sum();
        let mut vector = Vec::with_capacity(len);
        for _ in 0..len {
            vector.push(f());
        }

        Arrayy::from_vector(shape, vector)
    }

    pub fn arrayy_from_element(shape: Vec<usize>, element: f64) -> Arrayy {
        let len = shape.multiple_sum();
        let mut vector = Vec::with_capacity(len);
        for _ in 0..len {
            vector.push(element);
        }

        Arrayy::from_vector(shape, vector)
    }

    pub fn arange(start: usize, stop: usize, step: usize) -> Arrayy {
        let mut vector = Vec::new();

        for i in (start..stop).step_by(step) {
            vector.push(i as f64);
        }

        Arrayy::from_vector(vec![vector.len()], vector)
    }

    // get
    pub fn index(&self, index: Vec<i32>) -> Arrayy {
        let shape = self.shape.clone();
        let index = negative_indexing(&self.shape, index).unwrap();

        let mut out = 0;
        let mut count = 1;
        let slicing = (&self.shape[index.len()..]).multiple_sum();
        let mut new_shape = self.shape[index.len()..].to_vec();
        if new_shape.is_empty() {
            new_shape.push(1);
        }

        for index in index {
            let multiple = (&shape[count..]).multiple_sum();
            let pointing = index * multiple;
            out += pointing;

            count += 1;
        }

        let arrayy = Arrayy::from_vector(new_shape, self.value[out..out + slicing].to_vec());

        arrayy
    }

    pub fn index_mut(&mut self, index: Vec<i32>, value: Arrayy) {
        let shape = self.shape.clone();
        let index = negative_indexing(&self.shape, index).unwrap();
        let slicing = (&self.shape[index.len()..]).multiple_sum();

        let mut out = 0;
        let mut count = 1;
        for index in index {
            let multiple = (&shape[count..]).multiple_sum();
            let pointing = index * multiple;
            out += pointing;

            count += 1;
        }

        // println!("slicing => {}..{}", out, out + slicing);

        self.value[out..out + slicing].copy_from_slice(&value.value[..]);
    }

    // method
    pub fn map<F: FnMut(&f64) -> f64>(&self, f: F) -> Arrayy {
        let vector = self.value.iter().map(f).collect::<Vec<f64>>();

        Arrayy::from_vector(self.shape.clone(), vector)
    }

    // update
    pub fn update_from(&mut self, arr: Arrayy) {
        self.value = arr.value;
        self.shape = arr.shape;
    }
}