[package]
authors = ["nathanielsimard <nathaniel.simard.42@gmail.com>"]
categories = ["science", "no-std", "embedded", "wasm"]
description = "Flexible and Comprehensive Deep Learning Framework in Rust"
documentation = "https://docs.rs/burn-core"
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/crates/burn-core"
version.workspace = true

[features]
dataset = ["burn-dataset"]
default = [
    "std",
    "burn-candle?/default",
    "burn-common/default",
    "burn-dataset?/default",
    "burn-ndarray?/default",
    "burn-tch?/default",
    "burn-tensor/default",
    "burn-wgpu?/default",
    "burn-cuda?/default",
    "burn-hip?/default",
    "burn-autodiff?/default",
]
doc = [
    "std",
    # Backends
    "dataset",
    "candle",
    "fusion",
    "ndarray",
    "tch",
    "wgpu",
    "cuda-jit",
    "hip-jit",
    "vision",
    "autodiff",
    "remote",
    "server",
    # Doc features
    "burn-candle/doc",
    "burn-common/doc",
    "burn-dataset/doc",
    "burn-ndarray/doc",
    "burn-tch/doc",
    "burn-tensor/doc",
    "burn-wgpu/doc",
    "burn-cuda/doc",
    "burn-hip/doc",
]
network = ["burn-common/network"]
sqlite = ["burn-dataset?/sqlite"]
sqlite-bundled = ["burn-dataset?/sqlite-bundled"]
std = [
    "burn-autodiff?/std",
    "bincode/std",
    "burn-candle?/std",
    "burn-common/std",
    "burn-ndarray?/std",
    "burn-tensor/std",
    "burn-wgpu?/std",
    "burn-cuda?/std",
    "burn-hip?/std",
    "flate2",
    "half/std",
    "log",
    "rand/std",
    "rmp-serde",
    "serde/std",
    "serde_json/std",
    "num-traits/std",
]
vision = ["burn-dataset?/vision", "burn-common/network"]

# Backend
autodiff = ["burn-autodiff"]
fusion = ["burn-wgpu?/fusion", "burn-cuda?/fusion"]

## Backend features
accelerate = ["burn-candle?/accelerate", "burn-ndarray?/blas-accelerate"]
autotune = ["burn-wgpu?/autotune"]
blas-netlib = ["burn-ndarray?/blas-netlib"]
metal = ["burn-candle?/metal"]
openblas = ["burn-ndarray?/blas-openblas"]
openblas-system = ["burn-ndarray?/blas-openblas-system"]
template = ["burn-wgpu?/template"]
remote = ["burn-remote/client"]
server = ["burn-remote/server"]

candle = ["burn-candle"]
candle-cuda = ["candle", "burn-candle/cuda"]
cuda-jit = ["burn-cuda"]
hip-jit = ["burn-hip"]
ndarray = ["burn-ndarray"]
tch = ["burn-tch"]
wgpu = ["burn-wgpu"]
wgpu-spirv = ["wgpu", "burn-wgpu/spirv"]

# Custom deserializer for Record that is helpful for importing data, such as PyTorch pt files.
record-item-custom-serde = ["thiserror", "regex"]

# Serialization formats
experimental-named-tensor = ["burn-tensor/experimental-named-tensor"]

# Backwards compatibility with previous serialized data format.
record-backward-compat = []

test-cuda = ["cuda-jit"] # To use cuda during testing, default uses ndarray.
test-hip = ["hip-jit"] # To use hip during testing, default uses ndarray.
test-tch = ["tch"] # To use tch during testing, default uses ndarray.
test-wgpu = ["wgpu"] # To use wgpu during testing, default uses ndarray.
test-wgpu-spirv = [
    "test-wgpu",
    "wgpu-spirv",
] # To use wgpu-spirv during testing, default uses ndarray.

[dependencies]

# ** Please make sure all dependencies support no_std when std is disabled **

burn-common = { path = "../burn-common", version = "0.16.0", default-features = false }
burn-dataset = { path = "../burn-dataset", version = "0.16.0", optional = true, default-features = false }
burn-derive = { path = "../burn-derive", version = "0.16.0" }
burn-tensor = { path = "../burn-tensor", version = "0.16.0", default-features = false }

# Backends
burn-autodiff = { path = "../burn-autodiff", version = "0.16.0", optional = true }
burn-candle = { path = "../burn-candle", version = "0.16.0", optional = true }
burn-cuda = { path = "../burn-cuda", version = "0.16.0", optional = true, default-features = false }
burn-hip = { path = "../burn-hip", version = "0.16.0", optional = true, default-features = false }
burn-ndarray = { path = "../burn-ndarray", version = "0.16.0", optional = true, default-features = false }
burn-tch = { path = "../burn-tch", version = "0.16.0", optional = true }
burn-wgpu = { path = "../burn-wgpu", version = "0.16.0", optional = true, default-features = false }
burn-remote = { path = "../burn-remote", version = "0.16.0", default-features = false, optional = true }

data-encoding = { workspace = true }
uuid = { workspace = true }

derive-new = { workspace = true }
log = { workspace = true, optional = true }
rand = { workspace = true, features = ["std_rng"] } # Default enables std

# 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"] }

ahash = { workspace = true }
bincode = { workspace = true }
half = { workspace = true }
num-traits = { workspace = true }
regex = { workspace = true, optional = true }
rmp-serde = { workspace = true, optional = true }
serde_json = { workspace = true, features = ["alloc"] } #Default enables std
spin = { workspace = true }                             # Using in place of use std::sync::Mutex when std is disabled
thiserror = { workspace = true, optional = true }

[target.'cfg(not(target_has_atomic = "ptr"))'.dependencies]
portable-atomic-util = { workspace = true }

[dev-dependencies]
burn-dataset = { path = "../burn-dataset", version = "0.16.0", features = [
    "fake",
] }
tempfile = { workspace = true }

burn-autodiff = { path = "../burn-autodiff", version = "0.16.0" }
burn-ndarray = { path = "../burn-ndarray", version = "0.16.0", default-features = false }

[package.metadata.docs.rs]
features = ["doc"]
rustdoc-args = ["--cfg", "docsrs"]