Archetype: A generic n-dimensional Tensor. More...

#include <rerun/archetypes/tensor.hpp>

Public Types
using	IndicatorComponent = rerun::components::IndicatorComponent< IndicatorComponentName >
	Indicator component, used to identify the archetype when converting to a list of components.

Public Member Functions
	Tensor (Collection< datatypes::TensorDimension > shape, datatypes::TensorBuffer buffer)
	New Tensor from dimensions and tensor buffer.

template<typename TElement >
	Tensor (Collection< datatypes::TensorDimension > shape, const TElement *data_)
	New tensor from dimensions and pointer to tensor data.

Tensor	with_dim_names (Collection< std::string > names) &&
	Update the `names` of the contained `TensorData` dimensions.

	Tensor (Tensor &&other)=default

	Tensor (rerun::components::TensorData _data)

size_t	num_instances () const
	Returns the number of primary instances of this archetype.

Public Attributes
rerun::components::TensorData	data
	The tensor data.

Static Public Attributes
static constexpr const char	IndicatorComponentName [] = "rerun.components.TensorIndicator"

Detailed Description

Archetype: A generic n-dimensional Tensor.

Since the underlying rerun::datatypes::TensorData uses rerun::Collection internally, data can be passed in without a copy from raw pointers or by reference from std::vector/std::array/c-arrays. If needed, this "borrow-behavior" can be extended by defining your own rerun::CollectionAdapter.

Example

Simple tensor

#include <rerun.hpp>
 
#include <algorithm> // std::generate
#include <random>
#include <vector>
 
int main() {
    const auto rec = rerun::RecordingStream("rerun_example_tensor");
    rec.spawn().exit_on_failure();
 
    std::default_random_engine gen;
    // On MSVC uint8_t distributions are not supported.
    std::uniform_int_distribution<int> dist(0, 255);
 
    std::vector<uint8_t> data(8 * 6 * 3 * 5);
    std::generate(data.begin(), data.end(), [&] { return static_cast<uint8_t>(dist(gen)); });
 
    rec.log(
        "tensor",
        rerun::Tensor({8, 6, 3, 5}, data).with_dim_names({"width", "height", "channel", "batch"})
    );
}

Constructor & Destructor Documentation

◆ Tensor()

template<typename TElement >

rerun::archetypes::Tensor::Tensor	(	Collection< datatypes::TensorDimension >	shape,
		const TElement *	data_
	)

inlineexplicit

New tensor from dimensions and pointer to tensor data.

Type must be one of the types supported by rerun::datatypes::TensorData.

Parameters

shape	Shape of the image. Determines the number of elements expected to be in `data`.
data_	Target of the pointer must outlive the archetype.

Member Function Documentation

◆ with_dim_names()

Tensor rerun::archetypes::Tensor::with_dim_names ( Collection< std::string > names ) &&

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 call Error::handle and then proceed to only update the subset of names that it can.

The documentation for this struct was generated from the following file:

rerun/archetypes/tensor.hpp

Public Types

Public Member Functions

Public Attributes