echidna 0.9.0

A high-performance automatic differentiation library for Rust
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
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
261
262
263
264
265
266
267
268
269

#![cfg_attr(docsrs, feature(doc_cfg))]
#![warn(missing_docs)]
//! # echidna
//!
//! A high-performance automatic differentiation (AD) library for Rust.
//!
//! echidna provides forward-mode, reverse-mode, bytecode-graph-mode, and Taylor-mode
//! automatic differentiation. Write standard Rust numeric code and get exact derivatives
//! automatically -- no symbolic rewriting, no numerical finite differences.
//!
//! # Examples
//!
//! Compute the gradient of f(x, y) = x^2 + y^2:
//!
//! ```
//! let g = echidna::grad(|x: &[echidna::Reverse<f64>]| {
//!     x[0] * x[0] + x[1] * x[1]
//! }, &[3.0, 4.0]);
//! assert!((g[0] - 6.0).abs() < 1e-10);
//! assert!((g[1] - 8.0).abs() < 1e-10);
//! ```
//!
//! Forward-mode with `Dual<f64>`:
//!
//! ```
//! use echidna::{Dual, Float};
//!
//! let x = Dual::new(2.0_f64, 1.0); // seed derivative = 1
//! let y = x.sin() + x * x;
//! assert!((y.eps - (2.0_f64.cos() + 4.0)).abs() < 1e-10);
//! ```
//!
//! # AD Modes
//!
//! | Mode | Type | Best for | Description |
//! |------|------|----------|-------------|
//! | Forward | [`Dual<F>`] | Few inputs, many outputs | Propagates tangent vectors (JVP) |
//! | Reverse | [`Reverse<F>`] | Many inputs, few outputs | Adept-style two-stack tape, `Copy`, 12 bytes for f64 |
//! | Bytecode tape | [`BytecodeTape`] + [`BReverse<F>`] | Record-once evaluate-many | Graph mode enabling Hessians, sparse derivatives, GPU acceleration, checkpointing. Requires `bytecode` feature. |
//! | Taylor | [`Taylor<F, K>`] | Higher-order derivatives | Univariate Taylor propagation. Requires `taylor` feature. |
//! | Batched forward | [`DualVec<F, N>`] | Vectorised Jacobians/Hessians | N tangent directions simultaneously |
//!
//! # Feature Flags
//!
//! | Feature | Default | Description |
//! |---------|---------|-------------|
//! | `simba` | yes | simba / approx trait integration |
//! | `bytecode` | no | [`BytecodeTape`] graph-mode AD |
//! | `parallel` | no | Rayon parallel evaluation (implies `bytecode`) |
//! | `taylor` | no | Taylor-mode AD ([`Taylor<F, K>`], [`TaylorDyn<F>`]) |
//! | `laurent` | no | Laurent series for singularity analysis (implies `taylor`) |
//! | `stde` | no | Stochastic Taylor Derivative Estimators (implies `bytecode` + `taylor`) |
//! | `diffop` | no | Arbitrary differential operator evaluation via jet coefficients (implies `bytecode` + `taylor`) |
//! | `serde` | no | Serialization support via serde |
//! | `faer` | no | faer linear algebra integration (implies `bytecode`) |
//! | `nalgebra` | no | nalgebra linear algebra integration (implies `bytecode`) |
//! | `ndarray` | no | ndarray integration (implies `bytecode`) |
//! | `gpu-wgpu` | no | GPU acceleration via wgpu (implies `bytecode`) |
//! | `gpu-cuda` | no | GPU acceleration via CUDA (implies `bytecode`) |
//!
//! # Core Types
//!
//! **Always available:**
//! - [`Dual<F>`] -- forward-mode dual number
//! - [`Reverse<F>`] -- reverse-mode AD variable
//! - [`DualVec<F, N>`] -- batched forward-mode (N tangent directions)
//! - [`Scalar`] -- trait for writing AD-generic code
//! - [`Float`] -- trait for underlying floating-point types
//! - Type aliases: [`Dual64`], [`Dual32`], [`DualVec64`], [`DualVec32`],
//!   [`Reverse64`], [`Reverse32`]
//!
//! **With `bytecode`:**
//! - [`BytecodeTape`] -- recorded computation graph
//! - [`BReverse<F>`] -- reverse-mode variable for bytecode evaluation
//! - [`CustomOp`] / [`CustomOpHandle`] -- user-defined tape operations
//! - Type aliases: [`BReverse64`], [`BReverse32`]
//!
//! **With `taylor`:**
//! - [`Taylor<F, K>`] -- fixed-order Taylor coefficients
//! - [`TaylorDyn<F>`] -- dynamic-order Taylor coefficients
//! - Type aliases: [`Taylor64`], [`Taylor32`], [`TaylorDyn64`], [`TaylorDyn32`]
//!
//! **With `laurent`:**
//! - [`Laurent<F, K>`] -- Laurent series with negative-order terms
//!
//! # Getting Started
//!
//! - **Gradients**: use [`grad()`] -- it manages the reverse-mode tape automatically.
//! - **Jacobians**: use [`jacobian()`] (forward mode) or [`sparse_jacobian()`]
//!   (sparse, requires `bytecode`).
//! - **Hessians**: use [`hessian()`] or [`sparse_hessian()`] (requires `bytecode`).
//! - **AD-generic code**: write functions as `fn foo<T: Scalar>(x: T) -> T` and they
//!   work with any AD type.
//! - **Tape reuse (performance)**: use [`record()`] to build a [`BytecodeTape`], then
//!   call methods on it for repeated evaluation (requires `bytecode`).

/// Compile-time assertion that a type is `Send + Sync + 'static`.
///
/// Use on error types so that a future variant carrying a non-`Send` /
/// non-`Sync` / non-`'static` payload produces a build-time failure at
/// the type definition rather than at the (often distant) call site
/// where the error type meets an `async` boundary or a threadpool.
///
/// # Example
///
/// ```
/// # use echidna::assert_send_sync;
/// pub enum MyError { Bad, Other }
/// assert_send_sync!(MyError);
/// ```
#[macro_export]
macro_rules! assert_send_sync {
    ($t:ty) => {
        const _: fn() = || {
            fn assert_send_sync<T: Send + Sync + 'static>() {}
            assert_send_sync::<$t>();
        };
    };
}

pub mod api;
pub mod dual;
pub mod dual_vec;
pub mod float;
pub mod kernels;
pub mod reverse;
pub mod scalar;
pub mod tape;
mod traits;

#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub mod breverse;
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub mod bytecode_tape;
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub mod checkpoint;
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub mod cross_country;
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub mod nonsmooth;
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub mod opcode;
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub mod sparse;

#[cfg_attr(docsrs, doc(cfg(feature = "taylor")))]
#[cfg(feature = "taylor")]
pub mod taylor;
#[cfg_attr(docsrs, doc(cfg(feature = "taylor")))]
#[cfg(feature = "taylor")]
pub mod taylor_dyn;
#[cfg_attr(docsrs, doc(cfg(feature = "taylor")))]
#[cfg(feature = "taylor")]
pub mod taylor_ops;

#[cfg_attr(docsrs, doc(cfg(feature = "laurent")))]
#[cfg(feature = "laurent")]
pub mod laurent;

#[cfg_attr(docsrs, doc(cfg(feature = "stde")))]
#[cfg(feature = "stde")]
pub mod stde;

#[cfg_attr(docsrs, doc(cfg(feature = "diffop")))]
#[cfg(feature = "diffop")]
pub mod diffop;

#[cfg_attr(docsrs, doc(cfg(any(feature = "gpu-wgpu", feature = "gpu-cuda"))))]
#[cfg(any(feature = "gpu-wgpu", feature = "gpu-cuda"))]
pub mod gpu;

#[cfg_attr(docsrs, doc(cfg(feature = "faer")))]
#[cfg(feature = "faer")]
pub mod faer_support;
#[cfg_attr(docsrs, doc(cfg(feature = "nalgebra")))]
#[cfg(feature = "nalgebra")]
pub mod nalgebra_support;
#[cfg_attr(docsrs, doc(cfg(feature = "ndarray")))]
#[cfg(feature = "ndarray")]
pub mod ndarray_support;

pub use api::{grad, jacobian, jvp, vjp};
pub use dual::Dual;
pub use dual_vec::DualVec;
pub use float::Float;
pub use reverse::Reverse;
pub use scalar::Scalar;

#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub use api::{
    composed_hvp, hessian, hessian_vec, hvp, record, record_multi, sparse_hessian,
    sparse_hessian_vec, sparse_jacobian,
};
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub use breverse::BReverse;
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub use bytecode_tape::{BytecodeTape, CustomOp, CustomOpHandle};
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub use checkpoint::{
    grad_checkpointed, grad_checkpointed_disk, grad_checkpointed_online,
    grad_checkpointed_with_hints,
};
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub use nonsmooth::{ClarkeError, KinkEntry, NonsmoothInfo};
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub use sparse::{CsrPattern, JacobianSparsityPattern, SparsityPattern};

#[cfg_attr(docsrs, doc(cfg(feature = "laurent")))]
#[cfg(feature = "laurent")]
pub use laurent::Laurent;

#[cfg_attr(docsrs, doc(cfg(feature = "taylor")))]
#[cfg(feature = "taylor")]
pub use taylor::Taylor;
#[cfg_attr(docsrs, doc(cfg(feature = "taylor")))]
#[cfg(feature = "taylor")]
pub use taylor_dyn::{TaylorArena, TaylorDyn, TaylorDynGuard};

/// Type alias for forward-mode dual numbers over `f64`.
pub type Dual64 = Dual<f64>;
/// Type alias for forward-mode dual numbers over `f32`.
pub type Dual32 = Dual<f32>;
/// Type alias for batched forward-mode dual numbers over `f64`.
pub type DualVec64<const N: usize> = DualVec<f64, N>;
/// Type alias for batched forward-mode dual numbers over `f32`.
pub type DualVec32<const N: usize> = DualVec<f32, N>;
/// Type alias for reverse-mode variables over `f64`.
pub type Reverse64 = Reverse<f64>;
/// Type alias for reverse-mode variables over `f32`.
pub type Reverse32 = Reverse<f32>;

/// Type alias for bytecode-tape reverse-mode variables over `f64`.
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub type BReverse64 = BReverse<f64>;
/// Type alias for bytecode-tape reverse-mode variables over `f32`.
#[cfg_attr(docsrs, doc(cfg(feature = "bytecode")))]
#[cfg(feature = "bytecode")]
pub type BReverse32 = BReverse<f32>;

/// Type alias for Taylor coefficients over `f64` with K coefficients.
#[cfg_attr(docsrs, doc(cfg(feature = "taylor")))]
#[cfg(feature = "taylor")]
pub type Taylor64<const K: usize> = Taylor<f64, K>;
/// Type alias for Taylor coefficients over `f32` with K coefficients.
#[cfg_attr(docsrs, doc(cfg(feature = "taylor")))]
#[cfg(feature = "taylor")]
pub type Taylor32<const K: usize> = Taylor<f32, K>;
/// Type alias for dynamic Taylor coefficients over `f64`.
#[cfg_attr(docsrs, doc(cfg(feature = "taylor")))]
#[cfg(feature = "taylor")]
pub type TaylorDyn64 = TaylorDyn<f64>;
/// Type alias for dynamic Taylor coefficients over `f32`.
#[cfg_attr(docsrs, doc(cfg(feature = "taylor")))]
#[cfg(feature = "taylor")]
pub type TaylorDyn32 = TaylorDyn<f32>;