ciphercore_base/ops/pwl/
approx_sigmoid.rs

1//! Sigmoid(x) piecewise-linear approximation.
2use crate::custom_ops::CustomOperationBody;
3use crate::data_types::{Type, INT64};
4use crate::errors::Result;
5use crate::graphs::{Context, Graph};
6
7use serde::{Deserialize, Serialize};
8
9use super::approx_pointwise::{create_approximation, PWLConfig};
10
11/// A structure that defines the custom operation ApproxSigmoid that computes an approximate Sigmoid(x / (2 ** precision)) * (2 ** precision) using piecewise-linear approximation.
12///
13/// Sigmoid is a very commonly used function in ML: Sigmoid(x) = 1 / (1 + exp(-x)).
14/// So far this operation supports only INT64 scalar type.
15///
16/// # Custom operation arguments
17///
18/// - Node containing a signed 64-bit array or scalar to compute the sigmoid
19///
20/// # Custom operation returns
21///
22/// New ApproxSigmoid node
23///
24/// # Example
25///
26/// ```
27/// # use ciphercore_base::graphs::create_context;
28/// # use ciphercore_base::data_types::{scalar_type, array_type, INT64};
29/// # use ciphercore_base::custom_ops::{CustomOperation};
30/// # use ciphercore_base::ops::pwl::approx_sigmoid::ApproxSigmoid;
31/// let c = create_context().unwrap();
32/// let g = c.create_graph().unwrap();
33/// let t = array_type(vec![3], INT64);
34/// let x = g.input(t.clone()).unwrap();
35/// let n = g.custom_op(CustomOperation::new(ApproxSigmoid {precision: 4}), vec![x]).unwrap();
36///
37// TODO: generalize to other types.
38#[derive(Debug, Serialize, Deserialize, Eq, PartialEq, Hash)]
39pub struct ApproxSigmoid {
40    /// Assume that we're operating in fixed precision arithmetic with denominator 2 ** precision.
41    pub precision: u64,
42}
43
44#[typetag::serde]
45impl CustomOperationBody for ApproxSigmoid {
46    fn instantiate(&self, context: Context, arguments_types: Vec<Type>) -> Result<Graph> {
47        if arguments_types.len() != 1 {
48            return Err(runtime_error!(
49                "Invalid number of arguments for ApproxSigmoid"
50            ));
51        }
52        let t = arguments_types[0].clone();
53        if !t.is_scalar() && !t.is_array() {
54            return Err(runtime_error!(
55                "Argument in ApproxSigmoid must be a scalar or an array"
56            ));
57        }
58        let sc = t.get_scalar_type();
59        if sc != INT64 {
60            return Err(runtime_error!(
61                "Argument in ApproxSigmoid must consist of INT64's"
62            ));
63        }
64        if self.precision > 30 || self.precision == 0 {
65            return Err(runtime_error!("`precision` should be in range [1, 30]."));
66        }
67
68        let g = context.create_graph()?;
69        let arg = g.input(t)?;
70        // Choice of parameters:
71        // -- left/right: our typical use-case is precision=15, leading to minimum value around 3e-5. Sigmoid(-10) is 4.5e-5, so right=-left=10 is a reasonable choice with our precision;
72        // -- log_buckets: we look at max absolute difference to the real sigmoid. It looks as follows:
73        //    log_buckets=4 => 0.0163,
74        //    log_buckets=5 => 0.0045,
75        //    log_buckets=6 => 0.0012.
76        // After 5 segments, we're getting diminishing returns, so it doesn't make sense to go higher (for the sake of performance).
77        // -- flatten_left/flatten_right: sigmoid is flat on both sides.
78        let result = create_approximation(
79            arg,
80            |x| 1.0 / (1.0 + (-x).exp()),
81            -10.0,
82            10.0,
83            self.precision,
84            PWLConfig {
85                log_buckets: 5,
86                flatten_left: true,
87                flatten_right: true,
88            },
89        )?;
90        result.set_as_output()?;
91        g.finalize()?;
92        Ok(g)
93    }
94
95    fn get_name(&self) -> String {
96        format!("ApproxSigmoid(scaling_factor=2**{})", self.precision)
97    }
98}
99
100#[cfg(test)]
101mod tests {
102    use super::*;
103
104    use crate::custom_ops::run_instantiation_pass;
105    use crate::custom_ops::CustomOperation;
106    use crate::data_types::array_type;
107    use crate::data_types::scalar_type;
108    use crate::data_values::Value;
109    use crate::evaluators::random_evaluate;
110    use crate::graphs::util::simple_context;
111
112    fn scalar_helper(arg: i64, precision: u64) -> Result<i64> {
113        let c = simple_context(|g| {
114            let i = g.input(scalar_type(INT64))?;
115            g.custom_op(CustomOperation::new(ApproxSigmoid { precision }), vec![i])
116        })?;
117        let mapped_c = run_instantiation_pass(c)?;
118        let result = random_evaluate(
119            mapped_c.get_context().get_main_graph()?,
120            vec![Value::from_scalar(arg, INT64)?],
121        )?;
122        let res = result.to_i64(INT64)?;
123        Ok(res)
124    }
125
126    fn array_helper(arg: Vec<i64>) -> Result<Vec<i64>> {
127        let array_t = array_type(vec![arg.len() as u64], INT64);
128        let c = simple_context(|g| {
129            let i = g.input(array_t.clone())?;
130            g.custom_op(
131                CustomOperation::new(ApproxSigmoid { precision: 10 }),
132                vec![i],
133            )
134        })?;
135        let mapped_c = run_instantiation_pass(c)?;
136        let result = random_evaluate(
137            mapped_c.get_context().get_main_graph()?,
138            vec![Value::from_flattened_array(&arg, INT64)?],
139        )?;
140        result.to_flattened_array_i64(array_t)
141    }
142
143    fn sigmoid(x: f32) -> f32 {
144        1.0 / (1.0 + (-x).exp())
145    }
146
147    #[test]
148    fn test_approx_sigmoid_scalar() {
149        for i in (-5000..5000).step_by(1000) {
150            let expected = (sigmoid((i as f32) / 1024.0) * 1024.0) as i64;
151            let actual = scalar_helper(i, 10).unwrap();
152            let absolute_error = ((expected - actual).abs() as f64) / 1024.0;
153            assert!(absolute_error <= 0.01);
154        }
155    }
156
157    #[test]
158    fn test_approx_sigmoid_array() {
159        let arr: Vec<i64> = (-5000..5000).step_by(100).collect();
160        let res = array_helper(arr.clone()).unwrap();
161        for i in 0..arr.len() {
162            let expected = (sigmoid((arr[i] as f32) / 1024.0) * 1024.0) as i64;
163            let actual = res[i];
164            let absolute_error = ((expected - actual).abs() as f64) / 1024.0;
165            assert!(absolute_error <= 0.01);
166        }
167    }
168}
ciphercore_base/ops/pwl/approx_sigmoid.rs

ciphercore_base/ops/pwl/
approx_sigmoid.rs
