Struct SparseTensor

pub struct SparseTensor {
    pub type_: Type,
    pub shape: Vec<TensorDim>,
    pub non_zero_length: i64,
    pub sparse_index: SparseTensorIndex,
    pub data: Buffer,
}

The table SparseTensor in the namespace org.apache.arrow.flatbuf

Generated from these locations:

• Table SparseTensor in the file SparseTensor.fbs:209

Fields

type_: Type

The type of data contained in a value cell. Currently only fixed-width value types are supported, no strings or nested types.

shape: Vec<TensorDim>

The dimensions of the tensor, optionally named.

non_zero_length: i64

The number of non-zero values in a sparse tensor.

sparse_index: SparseTensorIndex

Sparse tensor index

data: Buffer

The location and size of the tensor’s data

Implementations

impl SparseTensor

pub fn builder() -> SparseTensorBuilder<()>

Creates a SparseTensorBuilder for serializing an instance of this table.

pub fn create( builder: &mut Builder, field_type_: impl WriteAsUnion<Type>, field_shape: impl WriteAs<Offset<[Offset<TensorDim>]>>, field_non_zero_length: impl WriteAsDefault<i64, i64>, field_sparse_index: impl WriteAsUnion<SparseTensorIndex>, field_data: impl WriteAs<Buffer>, ) -> Offset<Self>

Trait Implementations

impl Clone for SparseTensor

fn clone(&self) -> SparseTensor

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for SparseTensor

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for SparseTensor

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Hash for SparseTensor

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 Ord for SparseTensor

fn cmp(&self, other: &SparseTensor) -> Ordering

This method returns an Ordering between self and other.

fn max(self, other: Self) -> Self

where Self: Sized,

Compares and returns the maximum of two values.

fn min(self, other: Self) -> Self

where Self: Sized,

Compares and returns the minimum of two values.

fn clamp(self, min: Self, max: Self) -> Self

where Self: Sized,

Restrict a value to a certain interval.

impl PartialEq for SparseTensor

fn eq(&self, other: &SparseTensor) -> 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 PartialOrd for SparseTensor

fn partial_cmp(&self, other: &SparseTensor) -> Option<Ordering>

This method returns an ordering between self and other values if one exists.

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

Tests less than (for self and other) and is used by the < operator.

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

Tests less than or equal to (for self and other) and is used by the <= operator.

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

Tests greater than (for self and other) and is used by the > operator.

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

Tests greater than or equal to (for self and other) and is used by the >= operator.

impl Serialize for SparseTensor

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl<'a> TryFrom<SparseTensorRef<'a>> for SparseTensor

type Error = Error

The type returned in the event of a conversion error.

fn try_from(value: SparseTensorRef<'a>) -> Result<Self>

Performs the conversion.

impl Eq for SparseTensor

impl StructuralPartialEq for SparseTensor

impl VectorWrite<Offset<SparseTensor>> for SparseTensor

Safety

The planus compiler generates implementations that initialize the bytes in write_values.

impl WriteAs<Offset<SparseTensor>> for SparseTensor

impl WriteAsOffset<SparseTensor> for SparseTensor

impl<T0: WriteAsUnion<Type>, T1: WriteAs<Offset<[Offset<TensorDim>]>>, T2: WriteAsDefault<i64, i64>, T3: WriteAsUnion<SparseTensorIndex>, T4: WriteAs<Buffer>> WriteAsOffset<SparseTensor> for SparseTensorBuilder<(T0, T1, T2, T3, T4)>

impl WriteAsOptional<Offset<SparseTensor>> for SparseTensor