Enum tc_collection::tensor::sparse::SparseView

pub enum SparseView<Txn, FE> {
    Bool(SparseTensor<Txn, FE, SparseAccess<Txn, FE, u8>>),
    C32((SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>, SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>)),
    C64((SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>, SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>)),
    F32(SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>),
    F64(SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>),
    I16(SparseTensor<Txn, FE, SparseAccess<Txn, FE, i16>>),
    I32(SparseTensor<Txn, FE, SparseAccess<Txn, FE, i32>>),
    I64(SparseTensor<Txn, FE, SparseAccess<Txn, FE, i64>>),
    U8(SparseTensor<Txn, FE, SparseAccess<Txn, FE, u8>>),
    U16(SparseTensor<Txn, FE, SparseAccess<Txn, FE, u16>>),
    U32(SparseTensor<Txn, FE, SparseAccess<Txn, FE, u32>>),
    U64(SparseTensor<Txn, FE, SparseAccess<Txn, FE, u64>>),
}

Variants

Bool(SparseTensor<Txn, FE, SparseAccess<Txn, FE, u8>>)

C32((SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>, SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>))

C64((SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>, SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>))

F32(SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>)

F64(SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>)

I16(SparseTensor<Txn, FE, SparseAccess<Txn, FE, i16>>)

I32(SparseTensor<Txn, FE, SparseAccess<Txn, FE, i32>>)

I64(SparseTensor<Txn, FE, SparseAccess<Txn, FE, i64>>)

U8(SparseTensor<Txn, FE, SparseAccess<Txn, FE, u8>>)

U16(SparseTensor<Txn, FE, SparseAccess<Txn, FE, u16>>)

U32(SparseTensor<Txn, FE, SparseAccess<Txn, FE, u32>>)

U64(SparseTensor<Txn, FE, SparseAccess<Txn, FE, u64>>)

Implementations

impl<Txn, FE> SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node> + Clone,

pub async fn into_elements( self, txn_id: TxnId ) -> TCResult<Pin<Box<dyn Stream<Item = TCResult<(Coord, Number)>> + Send>>>

Trait Implementations

impl<Txn, FE> Clone for SparseView<Txn, FE>

fn clone(&self) -> Self

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<Txn, FE> CopyFrom<FE, SparseView<Txn, FE>> for SparseBase<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node> + Clone,

fn copy_from<'life0, 'async_trait>( txn: &'life0 Txn, store: Dir<FE>, instance: SparseView<Txn, FE> ) -> Pin<Box<dyn Future<Output = TCResult<Self>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Copy a new instance of Self from an existing instance.

impl<Txn: ThreadSafe, FE: ThreadSafe> Debug for SparseView<Txn, FE>

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

Formats the value using the given formatter.

impl<Txn, FE> From<(SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>, SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>)> for SparseView<Txn, FE>

fn from( tensors: (SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>, SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>) ) -> Self

Converts to this type from the input type.

impl<Txn, FE> From<(SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>, SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>)> for SparseView<Txn, FE>

fn from( tensors: (SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>, SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>) ) -> Self

Converts to this type from the input type.

impl<Txn, FE> From<Sparse<Txn, FE>> for SparseView<Txn, FE>

fn from(sparse: Sparse<Txn, FE>) -> Self

Converts to this type from the input type.

impl<Txn, FE> From<SparseBase<Txn, FE>> for SparseView<Txn, FE>

fn from(base: SparseBase<Txn, FE>) -> Self

Converts to this type from the input type.

impl<Txn, FE> From<SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>> for SparseView<Txn, FE>

fn from(tensor: SparseTensor<Txn, FE, SparseAccess<Txn, FE, f32>>) -> Self

Converts to this type from the input type.

impl<Txn, FE> From<SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>> for SparseView<Txn, FE>

fn from(tensor: SparseTensor<Txn, FE, SparseAccess<Txn, FE, f64>>) -> Self

Converts to this type from the input type.

impl<Txn, FE> From<SparseView<Txn, FE>> for Sparse<Txn, FE>

fn from(view: SparseView<Txn, FE>) -> Self

Converts to this type from the input type.

impl<Txn, FE> From<SparseView<Txn, FE>> for Tensor<Txn, FE>

fn from(sparse: SparseView<Txn, FE>) -> Self

Converts to this type from the input type.

impl<State> Route<State> for SparseView<State::Txn, State::FE>

where State: StateInstance + From<Tensor<State::Txn, State::FE>> + From<Tuple<Value>>, State::Class: From<NumberType>, State::FE: DenseCacheFile + AsType<Node>, Number: TryCastFrom<State>, Tensor<State::Txn, State::FE>: TryCastFrom<State>, Value: TryCastFrom<State>, bool: TryCastFrom<State>,

fn route<'a>( &'a self, path: &'a [PathSegment] ) -> Option<Box<dyn Handler<'a, State> + 'a>>

impl<Txn, FE> TensorBoolean<SparseView<Txn, FE>> for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type Combine = SparseView<Txn, FE>

The result type of a boolean operation.

type LeftCombine = SparseView<Txn, FE>

The result type of a boolean operation which may ignore right-hand values.

fn and(self, other: Self) -> TCResult<Self::LeftCombine>

Logical and

fn or(self, other: Self) -> TCResult<Self::Combine>

Logical or

fn xor(self, other: Self) -> TCResult<Self::Combine>

Logical xor

impl<Txn, FE> TensorBooleanConst for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node> + Clone,

type Combine = SparseView<Txn, FE>

The return type of a boolean operation.

fn and_const(self, other: Number) -> TCResult<Self::Combine>

Logical and

fn or_const(self, other: Number) -> TCResult<Self::Combine>

Logical or

fn xor_const(self, other: Number) -> TCResult<Self::Combine>

Logical xor

impl<Txn, FE> TensorCast for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type Cast = SparseView<Txn, FE>

fn cast_into(self, dtype: NumberType) -> TCResult<Self::Cast>

Cast this tensor into the given dtype.

impl<Txn, FE> TensorCompare<SparseView<Txn, FE>> for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type Compare = SparseView<Txn, FE>

The result of a comparison operation

fn eq(self, other: Self) -> TCResult<Self::Compare>

Element-wise equality

fn gt(self, other: Self) -> TCResult<Self::Compare>

Element-wise greater-than

fn ge(self, other: Self) -> TCResult<Self::Compare>

Element-wise greater-or-equal

fn lt(self, other: Self) -> TCResult<Self::Compare>

Element-wise less-than

fn le(self, other: Self) -> TCResult<Self::Compare>

Element-wise less-or-equal

fn ne(self, other: Self) -> TCResult<Self::Compare>

Element-wise not-equal

impl<Txn, FE> TensorCompareConst for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type Compare = SparseView<Txn, FE>

The result of a comparison operation

fn eq_const(self, other: Number) -> TCResult<Self::Compare>

Element-wise equality

fn gt_const(self, other: Number) -> TCResult<Self::Compare>

Element-wise greater-than

fn ge_const(self, other: Number) -> TCResult<Self::Compare>

Element-wise greater-or-equal

fn lt_const(self, other: Number) -> TCResult<Self::Compare>

Element-wise less-than

fn le_const(self, other: Number) -> TCResult<Self::Compare>

Element-wise less-or-equal

fn ne_const(self, other: Number) -> TCResult<Self::Compare>

Element-wise not-equal

impl<Txn, FE> TensorCond<SparseView<Txn, FE>, SparseView<Txn, FE>> for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node> + Clone,

type Cond = SparseView<Txn, FE>

The type of Tensor returned by cond

fn cond(self, then: Self, or_else: Self) -> TCResult<Self::Cond>

Use this tensor as a condition to select elements from then or or_else.

impl<Txn, FE> TensorConvert for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type Dense = DenseView<Txn, FE>

A dense representation of this Tensor

type Sparse = SparseView<Txn, FE>

A sparse representation of this Tensor

fn into_dense(self) -> Self::Dense

Return a dense representation of this Tensor.

fn into_sparse(self) -> Self::Sparse

Return a sparse representation of this Tensor.

impl<Txn, FE> TensorDiagonal for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type Diagonal = SparseView<Txn, FE>

The type of Tensor returned by diagonal

fn diagonal(self) -> TCResult<Self::Diagonal>

impl<Txn: ThreadSafe, FE: ThreadSafe> TensorInstance for SparseView<Txn, FE>

fn dtype(&self) -> NumberType

fn shape(&self) -> &Shape

fn ndim(&self) -> usize

fn size(&self) -> u64

fn schema(&self) -> Schema

impl<Txn, FE> TensorMatMul<SparseView<Txn, FE>> for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type MatMul = SparseView<Txn, FE>

The type of Tensor returned by matmul

fn matmul(self, other: Self) -> TCResult<Self::MatMul>

impl<Txn, FE> TensorMath<SparseView<Txn, FE>> for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type Combine = SparseView<Txn, FE>

The result type of a math operation

type LeftCombine = SparseView<Txn, FE>

The result type of a math operation which may ignore right-hand-side values

fn add(self, other: Self) -> TCResult<Self::Combine>

Add two tensors together.

fn div(self, other: Self) -> TCResult<Self::LeftCombine>

Divide self by other.

fn log(self, base: Self) -> TCResult<Self::LeftCombine>

Element-wise logarithm of self with respect to the given base.

fn mul(self, other: Self) -> TCResult<Self::LeftCombine>

Multiply two tensors together.

fn pow(self, other: Self) -> TCResult<Self::LeftCombine>

Raise self to the power of other.

fn sub(self, other: Self) -> TCResult<Self::Combine>

Subtract other from self.

impl<Txn, FE> TensorMathConst for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type Combine = SparseView<Txn, FE>

The return type of a math operation

fn add_const(self, other: Number) -> TCResult<Self::Combine>

Add a constant to this tensor

fn div_const(self, other: Number) -> TCResult<Self::Combine>

Divide self by other.

fn log_const(self, base: Number) -> TCResult<Self::Combine>

Element-wise logarithm

fn mul_const(self, other: Number) -> TCResult<Self::Combine>

Multiply self by other.

fn pow_const(self, other: Number) -> TCResult<Self::Combine>

Raise self to the power other.

fn sub_const(self, other: Number) -> TCResult<Self::Combine>

Subtract other from self.

impl<Txn: ThreadSafe, FE: ThreadSafe> TensorPermitRead for SparseView<Txn, FE>

fn read_permit<'life0, 'async_trait>( &'life0 self, txn_id: TxnId, range: Range ) -> Pin<Box<dyn Future<Output = TCResult<SmallVec<[PermitRead<Range>; 16]>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Acquire a read lock on the given range of this tensor.

impl<Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>> TensorRead for SparseView<Txn, FE>

fn read_value<'async_trait>( self, txn_id: TxnId, coord: Coord ) -> Pin<Box<dyn Future<Output = TCResult<Number>> + Send + 'async_trait>>

where Self: 'async_trait,

Read a single value from this Tensor.

impl<Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>> TensorReduce for SparseView<Txn, FE>

type Reduce = SparseView<Txn, FE>

The result type of a reduce operation

fn all<'async_trait>( self, txn_id: TxnId ) -> Pin<Box<dyn Future<Output = TCResult<bool>> + Send + 'async_trait>>

where Self: 'async_trait,

Return true if all elements in this Tensor are nonzero.

fn any<'async_trait>( self, txn_id: TxnId ) -> Pin<Box<dyn Future<Output = TCResult<bool>> + Send + 'async_trait>>

where Self: 'async_trait,

Return true if any element in this Tensor is nonzero.

fn max(self, axes: Axes, keepdims: bool) -> TCResult<Self::Reduce>

Return the maximum of this Tensor along the given axis.

fn max_all<'async_trait>( self, txn_id: TxnId ) -> Pin<Box<dyn Future<Output = TCResult<Number>> + Send + 'async_trait>>

where Self: 'async_trait,

Return the maximum element in this Tensor.

fn min(self, axes: Axes, keepdims: bool) -> TCResult<Self::Reduce>

Return the minimum of this Tensor along the given axis.

fn min_all<'async_trait>( self, txn_id: TxnId ) -> Pin<Box<dyn Future<Output = TCResult<Number>> + Send + 'async_trait>>

where Self: 'async_trait,

Return the minimum element in this Tensor.

fn product(self, axes: Axes, keepdims: bool) -> TCResult<Self::Reduce>

Return the product of this Tensor along the given axis.

fn product_all<'async_trait>( self, txn_id: TxnId ) -> Pin<Box<dyn Future<Output = TCResult<Number>> + Send + 'async_trait>>

where Self: 'async_trait,

Return the product of all elements in this Tensor.

fn sum(self, axes: Axes, keepdims: bool) -> TCResult<Self::Reduce>

Return the sum of this Tensor along the given axis.

fn sum_all<'async_trait>( self, txn_id: TxnId ) -> Pin<Box<dyn Future<Output = TCResult<Number>> + Send + 'async_trait>>

where Self: 'async_trait,

Return the sum of all elements in this Tensor.

impl<Txn, FE> TensorTransform for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type Broadcast = SparseView<Txn, FE>

A broadcast Tensor

type Expand = SparseView<Txn, FE>

A Tensor with an expanded dimension

type Reshape = SparseView<Txn, FE>

A reshaped Tensor

type Slice = SparseView<Txn, FE>

A Tensor slice

type Transpose = SparseView<Txn, FE>

A transposed Tensor

fn broadcast(self, shape: Shape) -> TCResult<Self::Broadcast>

Broadcast this Tensor to the given shape.

fn expand(self, axes: Axes) -> TCResult<Self::Expand>

Insert a new dimension of size 1 at each of the given axes.

fn reshape(self, shape: Shape) -> TCResult<Self::Reshape>

Change the shape of this Tensor.

fn slice(self, range: Range) -> TCResult<Self::Slice>

Return a slice of this Tensor with the given range.

fn transpose(self, permutation: Option<Axes>) -> TCResult<Self::Transpose>

Transpose this Tensor by reordering its axes according to the given permutation. If no permutation is given, the axes will be reversed.

impl<Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>> TensorTrig for SparseView<Txn, FE>

type Unary = SparseView<Txn, FE>

The return type of a unary operation

fn asin(self) -> TCResult<Self::Unary>

Element-wise arcsine

fn sin(self) -> TCResult<Self::Unary>

Element-wise sine

fn sinh(self) -> TCResult<Self::Unary>

Element-wise hyperbolic sine

fn acos(self) -> TCResult<Self::Unary>

Element-wise arccosine

fn cos(self) -> TCResult<Self::Unary>

Element-wise cosine

fn cosh(self) -> TCResult<Self::Unary>

Element-wise hyperbolic cosine

fn atan(self) -> TCResult<Self::Unary>

Element-wise arctangent

fn tan(self) -> TCResult<Self::Unary>

Element-wise tangent

fn tanh(self) -> TCResult<Self::Unary>

Element-wise hyperbolic tangent

impl<Txn, FE> TensorUnary for SparseView<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node>,

type Unary = SparseView<Txn, FE>

The return type of a unary operation

fn abs(self) -> TCResult<Self::Unary>

Element-wise absolute value

fn exp(self) -> TCResult<Self::Unary>

Element-wise exponentiation

fn ln(self) -> TCResult<Self::Unary>

Element-wise natural logarithm

fn round(self) -> TCResult<Self::Unary>

Element-wise round to the nearest integer

impl<Txn: ThreadSafe, FE: ThreadSafe> TensorUnaryBoolean for SparseView<Txn, FE>

type Unary = SparseView<Txn, FE>

The return type of a unary operation

fn not(self) -> TCResult<Self::Unary>

Element-wise logical not

impl<Txn, FE> TensorWriteDual<SparseView<Txn, FE>> for SparseBase<Txn, FE>

where Txn: Transaction<FE>, FE: DenseCacheFile + AsType<Node> + ThreadSafe,

fn write<'async_trait>( self, txn_id: TxnId, range: Range, value: SparseView<Txn, FE> ) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>>

where Self: 'async_trait,

Overwrite the slice of this Tensor given by Range with the given value.