dfdx 0.10.0

[package]

name = "dfdx"

version = "0.10.0"

edition = "2021"

license = "MIT OR Apache-2.0"



description = "Ergonomic auto differentiation in Rust, with pytorch like apis."

homepage = "https://github.com/coreylowman/dfdx"

documentation = "https://docs.rs/dfdx"

repository = "https://github.com/coreylowman/dfdx"

readme = "README.md"



keywords = [

    "deep-learning",

    "neural-network",

    "backprop",

    "tensor",

    "autodiff",

]



# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html



[package.metadata.docs.rs]

features = ["nightly", "numpy"]



[dependencies]

no-std-compat = { version = "0.4.1", default-features = false, features = [ "alloc", "compat_hash" ] }

rand = { version = "0.8.5", default-features = false, features = ["std_rng"] }

rand_distr = { version = "0.4.3", default-features = false, features = ["std_math"] }

matrixmultiply = { version = "0.3.2", default-features = false }

zip = { version = "0.6.2", default-features = false, optional = true }

cblas-sys = { version = "0.1.4", default-features = false, optional = true }

libc = { version = "0.2", default-features = false, optional = true }



[features]

default = ["std", "numpy"]

std = ["no-std-compat/std", "rand/std", "rand_distr/std"]

nightly = []

numpy = ["dep:zip", "std"]

cblas = ["dep:cblas-sys", "dep:libc"]

intel-mkl = ["cblas"]



[dev-dependencies]

rand = "0.8.5"

tempfile = "3.3.0"

mnist = "0.5.0"

indicatif = "0.16.2"



[build-dependencies]

rustc_version = "0.4.0"