Struct re_sdk::Tensor

pub struct Tensor {
    pub data: TensorData,
}

Archetype: A generic n-dimensional Tensor.

Example

Simple Tensor

use ndarray::{Array, ShapeBuilder};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let rec = rerun::RecordingStreamBuilder::new("rerun_example_tensor_simple").spawn()?;

    let mut data = Array::<u8, _>::default((8, 6, 3, 5).f());
    data.map_inplace(|x| *x = rand::random());

    let tensor =
        rerun::Tensor::try_from(data)?.with_dim_names(["width", "height", "channel", "batch"]);
    rec.log("tensor", &tensor)?;

    Ok(())
}

Fields

data: TensorData

The tensor data

Implementations

impl Tensor

pub const NUM_COMPONENTS: usize = 3usize

impl Tensor

pub fn new(data: impl Into<TensorData>) -> Tensor

impl Tensor

pub fn data(&self) -> &TensorData

pub fn try_from<T>(data: T) -> Result<Tensor, <T as TryInto<TensorData>>::Error>where T: TryInto<TensorData>,

Try to construct a Tensor from anything that can be converted into TensorData

This is useful for constructing a tensor from an ndarray.

pub fn with_dim_names( self, names: impl IntoIterator<Item = impl Into<ArrowString>> ) -> Tensor

Update the names of the contained TensorData dimensions.

Any existing Dimension names will be overwritten.

If too many, or too few names are provided, this function will warn and only update the subset of names that it can.

Trait Implementations

impl Archetype for Tensor

type Indicator = GenericIndicatorComponent<Tensor>

The associated indicator component, whose presence indicates that the high-level archetype-based APIs were used to log the data.

fn name() -> ArchetypeName

The fully-qualified name of this archetype, e.g. rerun.archetypes.Points2D.

fn indicator() -> MaybeOwnedComponentBatch<'static>

Creates a ComponentBatch out of the associated Self::Indicator component.

fn required_components() -> Cow<'static, [ComponentName]>

Returns the names of all components that must be provided by the user when constructing this archetype.

fn recommended_components() -> Cow<'static, [ComponentName]>

Returns the names of all components that should be provided by the user when constructing this archetype.

fn optional_components() -> Cow<'static, [ComponentName]>

Returns the names of all components that may be provided by the user when constructing this archetype.

fn all_components() -> Cow<'static, [ComponentName]>

Returns the names of all components that must, should and may be provided by the user when constructing this archetype.

fn from_arrow( arrow_data: impl IntoIterator<Item = (Field, Box<dyn Array>)> ) -> Result<Tensor, DeserializationError>

Given an iterator of Arrow arrays and their respective field metadata, deserializes them into this archetype.

impl AsComponents for Tensor

fn as_component_batches(&self) -> Vec<MaybeOwnedComponentBatch<'_>>

Exposes the object’s contents as a set of ComponentBatchs.

fn num_instances(&self) -> usize

The number of instances in each batch.

fn to_arrow(&self) -> Result<Vec<(Field, Box<dyn Array>)>, SerializationError>

Serializes all non-null Components of this bundle into Arrow arrays.

impl Clone for Tensor

fn clone(&self) -> Tensor

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Tensor

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

Formats the value using the given formatter.

impl PartialEq for Tensor

fn eq(&self, other: &Tensor) -> 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 StructuralPartialEq for Tensor