Enum MemoryLayout 

pub enum MemoryLayout {
    NCHW,
    NHWC,
    CHWN,
    BSF,
    SBF,
}

Memory layout formats

Variants

NCHW

Batch, Channel, Height, Width (PyTorch default)

NHWC

Batch, Height, Width, Channel (TensorFlow default, Tensor Core friendly)

CHWN

Channel, Height, Width, Batch (rarely used)

BSF

Batch, Sequence, Features (for transformers)

SBF

Sequence, Batch, Features (for RNNs)

Trait Implementations

impl Clone for MemoryLayout

fn clone(&self) -> MemoryLayout

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for MemoryLayout

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Hash for MemoryLayout

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl PartialEq for MemoryLayout

fn eq(&self, other: &MemoryLayout) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Copy for MemoryLayout

impl Eq for MemoryLayout

impl StructuralPartialEq for MemoryLayout