parametric 0.1.0

A crate providing the trait and a derive macro to bridge complex, hierarchical data structures with optimization algorithms that use flat parameter vectors.
Documentation 
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[dependencies.array-init]
version = "2.1.0"

[dependencies.ndarray]
optional = true
version = "0.16.1"

[dependencies.parametric_derive]
optional = true
version = "0.1.0"

[dev-dependencies.fastrand]
version = "2.3.0"

[[example]]
name = "derive_cap"
path = "examples/derive_cap.rs"

[[example]]
name = "mlp"
path = "examples/mlp.rs"

[features]
default = ["derive"]
derive = ["dep:parametric_derive"]
ndarray = ["dep:ndarray"]

[lib]
name = "parametric"
path = "src/lib.rs"

[package]
authors = ["Ilya Lisunov <huggbeat@gmail.com>"]
autobenches = false
autobins = false
autoexamples = false
autolib = false
autotests = false
build = false
categories = ["rust-patterns", "mathematics", "simulation"]
description = "A crate providing the trait and a derive macro to bridge complex, hierarchical data structures with optimization algorithms that use flat parameter vectors."
edition = "2024"
homepage = "https://github.com/ogau/parametric"
keywords = ["metaprogramming", "parametrization", "reparameterization", "machine-learning", "optimization"]
license = "MIT OR Apache-2.0"
name = "parametric"
readme = "README.md"
repository = "https://github.com/ogau/parametric"
resolver = "2"
version = "0.1.0"