Struct arrow_format::ipc::SparseTensor

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

Fields

type_: Type

shape: Vec<TensorDim>

non_zero_length: i64

sparse_index: SparseTensorIndex

data: Buffer

Implementations

impl SparseTensor

pub fn create( builder: &mut Builder, type_: impl WriteAsUnion<Type>, shape: impl WriteAs<Offset<[Offset<TensorDim>]>>, non_zero_length: impl WriteAsDefault<i64, i64>, sparse_index: impl WriteAsUnion<SparseTensorIndex>, 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 PartialEq for SparseTensor

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

impl VectorWrite<Offset<SparseTensor>> for SparseTensor

impl WriteAs<Offset<SparseTensor>> for SparseTensor

impl WriteAsOffset<SparseTensor> for SparseTensor

impl WriteAsOptional<Offset<SparseTensor>> for SparseTensor