rustyml 0.11.0

A high-performance machine learning & deep learning library in pure Rust, offering ML algorithms and neural network support
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

use crate::error::ModelError;

/// Validates that the learning rate is positive and finite.
///
/// # Parameters
///
/// * `learning_rate` - The learning rate value to validate
///
/// # Returns
///
/// - `Ok(())` if the learning rate is positive and finite
/// - `Err(ModelError::InputValidationError)` if the learning rate is not positive or not finite
pub(super) fn validate_learning_rate(learning_rate: f32) -> Result<(), ModelError> {
    if !(learning_rate > 0.0 && learning_rate.is_finite()) {
        return Err(ModelError::InputValidationError(format!(
            "learning_rate must be positive and finite, got {}",
            learning_rate
        )));
    }
    Ok(())
}

/// Validates that a decay rate (beta or rho) is in the range [0, 1) and finite.
///
/// # Parameters
///
/// - `value` - The decay rate value to validate
/// - `param_name` - The name of the parameter (for error messages)
///
/// # Returns
///
/// - `Ok(())` if the value is in the valid range and finite
/// - `Err(ModelError::InputValidationError)` if the value is out of range or not finite
pub(super) fn validate_decay_rate(value: f32, param_name: &str) -> Result<(), ModelError> {
    if !((0.0..1.0).contains(&value) && value.is_finite()) {
        return Err(ModelError::InputValidationError(format!(
            "{} must be in range [0, 1) and finite, got {}",
            param_name, value
        )));
    }
    Ok(())
}

/// Validates that epsilon is positive and finite.
///
/// # Parameters
///
/// - `epsilon` - The epsilon value to validate
///
/// # Returns
///
/// - `Ok(())` if epsilon is positive and finite
/// - `Err(ModelError::InputValidationError)` if epsilon is not positive or not finite
pub(super) fn validate_epsilon(epsilon: f32) -> Result<(), ModelError> {
    if !(epsilon > 0.0 && epsilon.is_finite()) {
        return Err(ModelError::InputValidationError(format!(
            "epsilon must be positive and finite, got {}",
            epsilon
        )));
    }
    Ok(())
}

/// Validates that a value is positive and finite.
///
/// # Parameters
///
/// - `value` - The value to validate
/// - `param_name` - The name of the parameter (for error messages)
///
/// # Returns
///
/// - `Ok(())` if the value is positive and finite
/// - `Err(ModelError::InputValidationError)` if the value is not positive or not finite
pub(super) fn validate_positive_finite(value: f32, param_name: &str) -> Result<(), ModelError> {
    if !(value > 0.0 && value.is_finite()) {
        return Err(ModelError::InputValidationError(format!(
            "{} must be positive and finite, got {}",
            param_name, value
        )));
    }
    Ok(())
}