Struct re_types::datatypes::TensorDimension

pub struct TensorDimension {
    pub size: u64,
    pub name: Option<ArrowString>,
}

Datatype: A single dimension within a multi-dimensional tensor.

Fields

size: u64

The length of this dimension.

name: Option<ArrowString>

The name of this dimension, e.g. “width”, “height”, “channel”, “batch’, ….

Implementations

impl TensorDimension

pub fn height(size: u64) -> Self

Create a new dimension with a given size, and the name “height”.

pub fn width(size: u64) -> Self

Create a new dimension with a given size, and the name “width”.

pub fn depth(size: u64) -> Self

Create a new dimension with a given size, and the name “depth”.

pub fn named(size: u64, name: impl Into<ArrowString>) -> Self

Create a named dimension.

pub fn unnamed(size: u64) -> Self

Create an unnamed dimension.

Trait Implementations

impl Clone for TensorDimension

fn clone(&self) -> TensorDimension

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for TensorDimension

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

Formats the value using the given formatter.

impl Default for TensorDimension

fn default() -> TensorDimension

Returns the “default value” for a type.

impl Display for TensorDimension

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

Formats the value using the given formatter.

impl<'a> From<&'a TensorDimension> for Cow<'a, TensorDimension>

fn from(value: &'a TensorDimension) -> Self

Converts to this type from the input type.

impl<'a> From<TensorDimension> for Cow<'a, TensorDimension>

fn from(value: TensorDimension) -> Self

Converts to this type from the input type.

impl Loggable for TensorDimension

type Name = DatatypeName

fn name() -> Self::Name

The fully-qualified name of this loggable, e.g. rerun.datatypes.Vec2D.

fn arrow_datatype() -> DataType

The underlying arrow2::datatypes::DataType, excluding datatype extensions.

fn to_arrow_opt<'a>( data: impl IntoIterator<Item = Option<impl Into<Cow<'a, Self>>>> ) -> SerializationResult<Box<dyn Array>>

where Self: Clone + 'a,

Given an iterator of options of owned or reference values to the current Loggable, serializes them into an Arrow array. The Arrow array’s datatype will match Loggable::arrow_field.

fn from_arrow_opt( arrow_data: &dyn Array ) -> DeserializationResult<Vec<Option<Self>>>

where Self: Sized,

Given an Arrow array, deserializes it into a collection of optional Loggables.

fn extended_arrow_datatype() -> DataType

The underlying arrow2::datatypes::DataType, including datatype extensions.

fn arrow_field() -> Field

The underlying arrow2::datatypes::Field, including datatype extensions.

fn to_arrow<'a>( data: impl IntoIterator<Item = impl Into<Cow<'a, Self>>> ) -> Result<Box<dyn Array>, SerializationError>

where Self: 'a,

Given an iterator of owned or reference values to the current Loggable, serializes them into an Arrow array. The Arrow array’s datatype will match Loggable::arrow_field.

fn from_arrow( data: &(dyn Array + 'static) ) -> Result<Vec<Self>, DeserializationError>

Given an Arrow array, deserializes it into a collection of Loggables.

impl PartialEq for TensorDimension

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

This method tests for self and other values to be equal, and is used by ==.

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

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

impl SizeBytes for TensorDimension

fn heap_size_bytes(&self) -> u64

Returns the total size of self on the heap, in bytes.

fn is_pod() -> bool

Is Self just plain old data?

fn total_size_bytes(&self) -> u64

Returns the total size of self in bytes, accounting for both stack and heap space.

fn stack_size_bytes(&self) -> u64

Returns the total size of self on the stack, in bytes.

impl Eq for TensorDimension

impl StructuralPartialEq for TensorDimension