burn/burn-core/Cargo.toml

116 lines
3.9 KiB
TOML

[package]
authors = ["nathanielsimard <nathaniel.simard.42@gmail.com>"]
categories = ["science", "no-std", "embedded", "wasm"]
description = "Flexible and Comprehensive Deep Learning Framework in Rust"
edition.workspace = true
keywords = ["deep-learning", "machine-learning", "tensor", "pytorch", "ndarray"]
license.workspace = true
name = "burn-core"
readme.workspace = true
repository = "https://github.com/tracel-ai/burn/tree/main/burn-core"
version.workspace = true
[features]
default = [
"std",
"burn-dataset?/default",
"burn-ndarray?/default",
"burn-candle?/default",
"burn-wgpu?/default",
"burn-fusion?/default",
"burn-tch?/default",
"burn-dataset?/default",
"burn-common/default",
"burn-tensor/default",
]
std = [
"flate2",
"log",
"rand/std",
"rmp-serde",
"serde/std",
"serde_json/std",
"bincode/std",
"half/std",
"burn-ndarray?/std",
"burn-candle?/std",
"burn-wgpu?/std",
"burn-fusion?/std",
"burn-common/std",
"burn-tensor/std",
]
dataset = ["burn-dataset"]
sqlite = ["burn-dataset?/sqlite"]
sqlite-bundled = ["burn-dataset?/sqlite-bundled"]
wasm-sync = ["burn-tensor/wasm-sync", "burn-common/wasm-sync"]
# Backend
autodiff = ["burn-autodiff"]
fusion = ["burn-fusion", "burn-wgpu?/fusion"]
## Backend features
cuda = ["burn-candle?/cuda"]
accelerate = ["burn-candle?/accelerate", "burn-ndarray?/blas-accelerate"]
openblas = ["burn-ndarray?/blas-openblas"]
openblas-system = ["burn-ndarray?/blas-openblas-system"]
blas-netlib = ["burn-ndarray?/blas-netlib"]
ndarray = ["burn-ndarray"]
tch = ["burn-tch"]
candle = ["burn-candle"]
wgpu = ["burn-wgpu"]
# Serialization formats
experimental-named-tensor = ["burn-tensor/experimental-named-tensor"]
test-tch = ["tch"] # To use tch during testing, default uses ndarray.
test-wgpu = ["wgpu"] # To use wgpu during testing, default uses ndarray.
[dependencies]
# ** Please make sure all dependencies support no_std when std is disabled **
burn-common = { path = "../burn-common", version = "0.12.0", default-features = false }
burn-dataset = { path = "../burn-dataset", version = "0.12.0", optional = true, default-features = false }
burn-derive = { path = "../burn-derive", version = "0.12.0" }
burn-tensor = { path = "../burn-tensor", version = "0.12.0", default-features = false }
# Backends
burn-ndarray = { path = "../burn-ndarray", version = "0.12.0", optional = true, default-features = false }
burn-wgpu = { path = "../burn-wgpu", version = "0.12.0", optional = true }
burn-autodiff = { path = "../burn-autodiff", version = "0.12.0", optional = true }
burn-fusion = { path = "../burn-fusion", version = "0.12.0", optional = true }
burn-tch = { path = "../burn-tch", version = "0.12.0", optional = true }
burn-candle = { path = "../burn-candle", version = "0.12.0", optional = true }
derive-new = { workspace = true }
libm = { workspace = true }
log = { workspace = true, optional = true }
rand = { workspace = true, features = ["std_rng"] } # Default enables std
# Using in place of use std::sync::Mutex when std is disabled
spin = { workspace = true, features = ["mutex", "spin_mutex"] }
# The same implementation of HashMap in std but with no_std support (only alloc crate is needed)
hashbrown = { workspace = true, features = ["serde"] } # no_std compatible
# Serialize Deserialize
flate2 = { workspace = true, optional = true }
serde = { workspace = true, features = ["derive"] }
bincode = { workspace = true }
half = { workspace = true }
rmp-serde = { workspace = true, optional = true }
serde_json = { workspace = true, features = ["alloc"] } #Default enables std
[dev-dependencies]
tempfile = { workspace = true }
burn-dataset = { path = "../burn-dataset", version = "0.12.0", features = [
"fake",
] }
burn-ndarray = { path = "../burn-ndarray", version = "0.12.0", default-features = false }
burn-autodiff = { path = "../burn-autodiff", version = "0.12.0" }