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
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
use itertools::izip;
use rand::distributions::uniform::SampleUniform;
use std::{
    f64,
    ops::{AddAssign, Div, Range, Sub},
    sync::{
        atomic::{AtomicBool, AtomicU64, AtomicU8, Ordering},
        Arc, Mutex,
    },
    thread,
    time::Duration,
};

use crate::util::{poll, update_execution_position, Polling};

/// [Grid search](https://en.wikipedia.org/wiki/Hyperparameter_optimization#Grid_search)
///
/// Evaluate all combinations of values from the 3 values where:
/// - Value 1 covers `10` values at equal intervals from `0..10` (`0,1,2,3,4,5,6,7,8,9`).
/// - Value 2 covers `11` values at equal intervals from `5..15`.
/// - Value 3 covers `12` values at equal intervals from `10..20`.
///
/// Printing progress every `10ms` and exiting early if a value is found which is less than or equal to `15.`.
/// ```
/// use std::sync::Arc;
/// use simple_optimization::{grid_search, Polling};
/// fn simple_function(list: &[f64; 3], _: Option<Arc<()>>) -> f64 { list.iter().sum() }
/// let best = grid_search(
///     [0f64..10f64, 5f64..15f64, 10f64..20f64], // Value ranges.
///     simple_function, // Evaluation function.
///     None, //  No additional evaluation data.
///     // Polling every `10ms`, printing progress (`true`), exiting early if `15.` or less is reached, and not printing thread execution data (`false`).
///     Some(Polling { poll_rate: 5, printing: true, early_exit_minimum: Some(15.), thread_execution_reporting: false }),
///     // Take `10` samples along range `0` (`0..10`), `11` along range `1` (`5..15`)
///     //  and `12` along range `2` (`10..20`).
///     // In total taking `10*11*12=1320` samples.
///     [10,11,12],
/// );
/// assert_eq!(simple_function(&best, None), 15.);
/// ```
pub fn grid_search<
    A: 'static + Send + Sync,
    T: 'static
        + Copy
        + Send
        + Sync
        + Default
        + SampleUniform
        + PartialOrd
        + AddAssign
        + Sub<Output = T>
        + Div<Output = T>
        + num::FromPrimitive,
    const N: usize,
>(
    // Generics
    ranges: [Range<T>; N],
    f: fn(&[T; N], Option<Arc<A>>) -> f64,
    evaluation_data: Option<Arc<A>>,
    polling: Option<Polling>,
    // Specifics
    points: [u64; N],
) -> [T; N] {
    // Compute step sizes
    let mut steps = [Default::default(); N];
    for (r, k, s) in izip!(ranges.iter(), points.iter(), steps.iter_mut()) {
        *s = (r.end - r.start) / T::from_u64(*k).unwrap();
    }

    // Compute point values
    let point_values: Vec<Vec<T>> = izip!(ranges.iter(), points.iter(), steps.iter())
        .map(|(r, k, s)| {
            (0..*k)
                .scan(r.start, |state, _| {
                    // Do this so the first value is `r.start` instead of `r.start+s` and the last value is `r.end-s` instead of r.end`.
                    let prev_state = *state;
                    *state += *s;
                    Some(prev_state)
                })
                .collect()
        })
        .collect();

    // Search points
    let mut start = [Default::default(); N];
    for (s, p) in start.iter_mut().zip(point_values.iter()) {
        *s = p[0];
    }
    let (_, params) = thread_search(f, evaluation_data, polling, &point_values, start);
    return params;

    fn thread_search<
        A: 'static + Send + Sync,
        T: 'static
            + Copy
            + Send
            + Sync
            + Default
            + SampleUniform
            + PartialOrd
            + AddAssign
            + Sub<Output = T>
            + Div<Output = T>
            + num::FromPrimitive,
        const N: usize,
    >(
        // Generics
        f: fn(&[T; N], Option<Arc<A>>) -> f64,
        evaluation_data: Option<Arc<A>>,
        polling: Option<Polling>,
        // Specifics
        point_values: &Vec<Vec<T>>,
        mut point: [T; N],
    ) -> (f64, [T; N]) {
        // Could just `assert!(N>0)` and not handle it, but this handles it fine.
        if 0 == point_values.len() {
            return (f(&point, evaluation_data), point);
        }

        let thread_exit = Arc::new(AtomicBool::new(false));
        // (handles,counters)
        let (handles, links): (Vec<_>, Vec<_>) = point_values[0]
            .iter()
            .map(|p_value| {
                point[0] = *p_value;
                let point_values_clone = point_values.clone();
                let counter = Arc::new(AtomicU64::new(0));
                let thread_best = Arc::new(Mutex::new(f64::MAX));
                let thread_execution_position = Arc::new(AtomicU8::new(0));
                let thread_execution_time = Arc::new([
                    Mutex::new((Duration::new(0, 0), 0)),
                    Mutex::new((Duration::new(0, 0), 0)),
                ]);

                let counter_clone = counter.clone();
                let thread_best_clone = thread_best.clone();
                let thread_exit_clone = thread_exit.clone();
                let evaluation_data_clone = evaluation_data.clone();
                let thread_execution_position_clone = thread_execution_position.clone();
                let thread_execution_time_clone = thread_execution_time.clone();
                (
                    thread::spawn(move || {
                        search(
                            // Generics
                            &point_values_clone,
                            f,
                            evaluation_data_clone,
                            counter_clone,
                            thread_best_clone,
                            thread_exit_clone,
                            thread_execution_position_clone,
                            thread_execution_time_clone,
                            // Specifics
                            point,
                            1,
                        )
                    }),
                    (
                        counter,
                        (
                            thread_best,
                            (thread_execution_position, thread_execution_time),
                        ),
                    ),
                )
            })
            .unzip();
        let (counters, links): (Vec<Arc<AtomicU64>>, Vec<_>) = links.into_iter().unzip();
        let (thread_bests, links): (Vec<Arc<Mutex<f64>>>, Vec<_>) = links.into_iter().unzip();
        let (thread_execution_positions, thread_execution_times) = links.into_iter().unzip();

        if let Some(poll_data) = polling {
            let iterations = point_values.iter().map(|pvs| pvs.len() as u64).product();
            poll(
                poll_data,
                counters,
                0,
                iterations,
                thread_bests,
                thread_exit,
                thread_execution_positions,
                thread_execution_times,
            );
        }

        let joins: Vec<_> = handles.into_iter().map(|h| h.join().unwrap()).collect();
        let (value, params) =
            joins
                .into_iter()
                .fold((f64::MAX, [Default::default(); N]), |(bv, bp), (v, p)| {
                    if v < bv {
                        (v, p)
                    } else {
                        (bv, bp)
                    }
                });
        return (value, params);
    }
    fn search<
        A: 'static + Send + Sync,
        T: 'static
            + Copy
            + Send
            + Sync
            + Default
            + SampleUniform
            + PartialOrd
            + AddAssign
            + Sub<Output = T>
            + Div<Output = T>
            + num::FromPrimitive,
        const N: usize,
    >(
        // Generics
        point_values: &Vec<Vec<T>>,
        f: fn(&[T; N], Option<Arc<A>>) -> f64,
        evaluation_data: Option<Arc<A>>,
        counter: Arc<AtomicU64>,
        best: Arc<Mutex<f64>>,
        thread_exit: Arc<AtomicBool>,
        thread_execution_position: Arc<AtomicU8>,
        thread_execution_times: Arc<[Mutex<(Duration, u64)>; 2]>,
        // Specifics
        mut point: [T; N],
        index: usize,
    ) -> (f64, [T; N]) {
        if index == point_values.len() {
            // panic!("hit here");
            counter.fetch_add(1, Ordering::SeqCst);
            return (f(&point, evaluation_data), point);
        }

        let mut best_value = f64::MAX;
        let mut best_params = [Default::default(); N];
        for p_value in point_values[index].iter() {
            point[index] = *p_value;
            let (value, params) = search(
                point_values,
                f,
                evaluation_data.clone(),
                counter.clone(),
                best.clone(),
                thread_exit.clone(),
                thread_execution_position.clone(),
                thread_execution_times.clone(),
                point,
                index + 1,
            );
            if value < best_value {
                best_value = value;
                best_params = params;
                *best.lock().unwrap() = best_value;
            }
            if thread_exit.load(Ordering::SeqCst) {
                break;
            }
        }
        return (best_value, best_params);
    }
}