Module dfdx::feature_flags

Information about the available feature flags.

Default features:

• “std”
• “fast-alloc”
• “cpu-par-matmul”

Quick start

Cuda:

dfdx = { version = "...", default-features = False, features = ["std", "cuda"]}

Cpu:

dfdx = { version = "...", default-features = False, features = ["std", "cpu-par-matmul"]}

“std”

Enabled by default

Enables usage of the standard library. Otherwise no_std_compat is used.

Example:

dfdx = { version = "...", default-features = false }

Note that allocations are necessary, so the no_std_compat dependency looks like:

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

“fast-alloc”

Enabled by default

Turns off fallible allocations for Cpu, which is substantially faster.

“no-std”

Used to enable “no-std-compat” and turn on ![no_std].

Example:

dfdx = { version = "...", default-features = false, features = ["no-std"] }

“cuda”

Enables the Cuda device and other goodies. Must have the cuda toolkit and nvcc installed on your system.

Example:

dfdx = { version = "...", features = ["cuda"] }

“cpu-seq-matmul”

Used to enable using matrixmultiply for matmul operations.

“cpu-par-matmul”

Used to enable the threading feature of matrixmultiply. This makes matmuls substantially faster!

“cpu-mkl-matmul”

Enables using the Intel MKL libraries (assuming you installed it already) for matrix multiplication.

Linking is currently tested & verified on the following platforms:

• Windows
• Linux
• macOS

Example:

dfdx = { version = "...", features = ["cpu-mkl-matmul"] }

Installing Intel MKL libraries

It’s pretty easy!

You will need to install Intel MKL on your own from this page.

build.rs will fail helpfully if you don’t have the correct path/environment variables.

“numpy”

Enables saving and loading arrays to .npy files, and saving and loading nn to .npz files.

Example:

dfdx = { version = "...", features = ["numpy"] }

“safetensors”

Enables saving and loading tensors/nn to .safetensors files.

Example:

dfdx = { version = "...", features = ["safetensors"] }

“nightly”

Enables using all features that currently require the nightly rust compiler.

Example:

dfdx = { version = "...", features = ["nightly"] }