Struct tc_tensor::SparseTensor

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pub struct SparseTensor<FD, FS, D, T, A> { /* private fields */ }

Expand description

A Tensor stored as a Table of Coords and [Number] values

Implementations

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impl<FD, FS, D, T, A> SparseTensor<FD, FS, D, T, A>

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pub fn into_inner(self) -> A

Consume this SparseTensor and return its accessor.

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impl<FD, FS, D, T> SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<BTreeType> + From<TensorType>,

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pub async fn create(dir: &D, schema: Schema, txn_id: TxnId) -> TCResult<Self>

Create a new SparseTensor with the given schema

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pub async fn tile(
 txn: T,
 tensor: SparseTensor<FD, FS, D, T, SparseAccessor<FD, FS, D, T>>,
 multiples: Vec<u64>
) -> TCResult<Self>

Tile the given tensor into a new SparseTensor

Trait Implementations

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impl<FD: Clone, FS: Clone, D: Clone, T: Clone, A: Clone> Clone for SparseTensor<FD, FS, D, T, A>

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fn clone(&self) -> SparseTensor<FD, FS, D, T, A>

Returns a copy of the value. Read more

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

Performs copy-assignment from source. Read more

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impl<FD, FS, D, T, A> CopyFrom<D, SparseTensor<FD, FS, D, T, A>> for SparseTable<FD, FS, D, T> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 A: SparseAccess<FD, FS, D, T>,
 D::FileClass: From<BTreeType> + From<TensorType>,

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fn copy_from<'life0, 'async_trait>(
 instance: SparseTensor<FD, FS, D, T, A>,
 store: D,
 txn: &'life0 T
) -> Pin<Box<dyn Future<Output = TCResult<Self>> + Send + 'async_trait>> where
 'life0: 'async_trait,
 Self: 'async_trait,

Copy a new instance of Self from an existing instance.

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impl<FD, FS, D, T, A> CopyFrom<D, SparseTensor<FD, FS, D, T, A>> for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<BTreeType> + From<TensorType>,
 A: SparseAccess<FD, FS, D, T>,

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fn copy_from<'life0, 'async_trait>(
 instance: SparseTensor<FD, FS, D, T, A>,
 store: Self::Store,
 txn: &'life0 Self::Txn
) -> Pin<Box<dyn Future<Output = TCResult<Self>> + Send + 'async_trait>> where
 'life0: 'async_trait,
 Self: 'async_trait,

Copy a new instance of Self from an existing instance.

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impl<FD, FS, D, T, A> Display for SparseTensor<FD, FS, D, T, A>

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

Formats the value using the given formatter. Read more

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impl<FD, FS, D, T, A> From<A> for SparseTensor<FD, FS, D, T, A>

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fn from(accessor: A) -> Self

Converts to this type from the input type.

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impl<FD, FS, D, T, A> From<SparseTensor<FD, FS, D, T, A>> for Tensor<FD, FS, D, T> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 A: SparseAccess<FD, FS, D, T>,
 D::FileClass: From<TensorType>,

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fn from(sparse: SparseTensor<FD, FS, D, T, A>) -> Self

Converts to this type from the input type.

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impl<FD, FS, D, T> FromStream for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<BTreeType> + From<TensorType>,

type Context = T

The decoding context of this type, useful in situations where the stream to be decoded may be too large to hold in main memory. Read more

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fn from_stream<'life0, 'async_trait, De>(
 txn: T,
 decoder: &'life0 mut De
) -> Pin<Box<dyn Future<Output = Result<Self, De::Error>> + Send + 'async_trait>> where
 De: 'async_trait + Decoder,
 'life0: 'async_trait,
 Self: 'async_trait,

Parse this value using the given Decoder.

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impl<FD, FS, D, T, A> Instance for SparseTensor<FD, FS, D, T, A> where
Self: Send + Sync,

type Class = TensorType

The Class type of this instance

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fn class(&self) -> Self::Class

Returns the [Class] of this instance.

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impl<'en, FD, FS, D, T, A> IntoView<'en, D> for SparseTensor<FD, FS, D, T, A> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<TensorType>,
 A: SparseAccess<FD, FS, D, T>,

type Txn = T

type View = SparseTensorView<'en>

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fn into_view<'async_trait>(
 self,
 txn: Self::Txn
) -> Pin<Box<dyn Future<Output = TCResult<Self::View>> + Send + 'async_trait>> where
 Self: 'async_trait,

Return a View which can be encoded with en::IntoStream.

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impl<FD, FS, D, T> Persist<D> for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<BTreeType> + From<TensorType>,

type Schema = Schema

type Store = D

type Txn = T

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fn schema(&self) -> &Self::Schema

Return the schema of this persistent state.

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fn load<'life0, 'async_trait>(
 txn: &'life0 Self::Txn,
 schema: Self::Schema,
 store: Self::Store
) -> Pin<Box<dyn Future<Output = TCResult<Self>> + Send + 'async_trait>> where
 'life0: 'async_trait,
 Self: 'async_trait,

Load a saved state from persistent storage.

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impl<FD, FS, D, T> Restore<D> for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<BTreeType> + From<TensorType>,

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fn restore<'life0, 'life1, 'async_trait>(
 &'life0 self,
 backup: &'life1 Self,
 txn_id: TxnId
) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where
 'life0: 'async_trait,
 'life1: 'async_trait,
 Self: 'async_trait,

Restore this persistent state from a backup.

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impl<FD, FS, D, T, A> TensorAccess for SparseTensor<FD, FS, D, T, A> where
 FD: File<Array>,
 FS: File<Node>,
 D: Dir,
 T: Transaction<D>,
 A: SparseAccess<FD, FS, D, T>,

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fn dtype(&self) -> NumberType

The datatype of this Tensor

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fn ndim(&self) -> usize

The number of dimensions of this Tensor

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fn shape(&self) -> &Shape

The shape of this Tensor

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fn size(&self) -> u64

The number of elements in this Tensor

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impl<FD, FS, D, T, L, R> TensorBoolean<SparseTensor<FD, FS, D, T, R>> for SparseTensor<FD, FS, D, T, L> where
 FD: File<Array>,
 FS: File<Node>,
 D: Dir,
 T: Transaction<D>,
 L: SparseAccess<FD, FS, D, T>,
 R: SparseAccess<FD, FS, D, T>,

type Combine = SparseTensor<FD, FS, D, T, SparseCombinator<FD, FS, D, T, L, R>>

The result type of a boolean operation.

type LeftCombine = SparseTensor<FD, FS, D, T, SparseLeftCombinator<FD, FS, D, T, L, R>>

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

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fn and(
self,
other: SparseTensor<FD, FS, D, T, R>
) -> TCResult<Self::LeftCombine>

Logical and

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fn or(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Combine>

Logical or

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fn xor(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Combine>

Logical xor

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impl<FD, FS, D, T, A> TensorBoolean<Tensor<FD, FS, D, T>> for SparseTensor<FD, FS, D, T, A> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<TensorType>,
 A: SparseAccess<FD, FS, D, T>,

type Combine = Tensor<FD, FS, D, T>

The result type of a boolean operation.

type LeftCombine = Tensor<FD, FS, D, T>

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

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fn and(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

Logical and

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fn or(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

Logical or

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fn xor(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

Logical xor

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impl<FD, FS, D, T, A> TensorBooleanConst for SparseTensor<FD, FS, D, T, A> where
 FD: File<Array>,
 FS: File<Node>,
 D: Dir,
 T: Transaction<D>,
 A: SparseAccess<FD, FS, D, T>,
 Self: TensorInstance,
 <Self as TensorInstance>::Dense: TensorBooleanConst,

type Combine = SparseTensor<FD, FS, D, T, SparseConstCombinator<FD, FS, D, T, A>>

The return type of a boolean operation.

type DenseCombine = <<SparseTensor<FD, FS, D, T, A> as TensorInstance>::Dense as TensorBooleanConst>::DenseCombine

The return type of a boolean operation with a result expected to be dense.

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

Logical and

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

Logical or

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

Logical xor

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impl<FD, FS, D, T, L, R> TensorCompare<SparseTensor<FD, FS, D, T, R>> for SparseTensor<FD, FS, D, T, L> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<TensorType>,
 L: SparseAccess<FD, FS, D, T>,
 R: SparseAccess<FD, FS, D, T>,

type Compare = SparseTensor<FD, FS, D, T, SparseCombinator<FD, FS, D, T, L, R>>

The result of a comparison operation

type Dense = DenseTensor<FD, FS, D, T, BlockListSparse<FD, FS, D, T, SparseCombinator<FD, FS, D, T, L, R>>>

The result of a comparison operation which can only return a dense Tensor

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fn eq(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Dense>

Element-wise equality

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fn gt(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Compare>

Element-wise greater-than

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fn gte(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Dense>

Element-wise greater-or-equal

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fn lt(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Compare>

Element-wise less-than

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fn lte(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Dense>

Element-wise less-or-equal

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fn ne(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Compare>

Element-wise not-equal

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impl<FD, FS, D, T, A> TensorCompare<Tensor<FD, FS, D, T>> for SparseTensor<FD, FS, D, T, A> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<TensorType>,
 A: SparseAccess<FD, FS, D, T>,

type Compare = Tensor<FD, FS, D, T>

The result of a comparison operation

type Dense = Tensor<FD, FS, D, T>

The result of a comparison operation which can only return a dense Tensor

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fn eq(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Dense>

Element-wise equality

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fn gt(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Compare>

Element-wise greater-than

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fn gte(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Dense>

Element-wise greater-or-equal

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fn lt(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Compare>

Element-wise less-than

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fn lte(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Dense>

Element-wise less-or-equal

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fn ne(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Compare>

Element-wise not-equal

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impl<FD, FS, D, T, A> TensorCompareConst for SparseTensor<FD, FS, D, T, A>

type Compare = SparseTensor<FD, FS, D, T, SparseConstCombinator<FD, FS, D, T, A>>

The result of a comparison operation

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

Element-wise equality

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

Element-wise greater-than

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

Element-wise greater-or-equal

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

Element-wise less-than

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

Element-wise less-or-equal

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

Element-wise not-equal

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impl<FD, FS, D, T, A> TensorDiagonal<D> for SparseTensor<FD, FS, D, T, A> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 A: SparseAccess<FD, FS, D, T>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<BTreeType> + From<TensorType>,
 SparseTable<FD, FS, D, T>: ReadValueAt<D, Txn = T>,

type Txn = T

The type of Transaction to expect

type Diagonal = SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>>

The type of Tensor returned by diagonal

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fn diagonal<'async_trait>(
 self,
 txn: Self::Txn
) -> Pin<Box<dyn Future<Output = TCResult<Self::Diagonal>> + Send + 'async_trait>> where
 Self: 'async_trait,

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impl<FD, FS, D, T, L> TensorDualIO<D, SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>>> for SparseTensor<FD, FS, D, T, L> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<TensorType>,
 L: SparseWrite<FD, FS, D, T>,

type Txn = T

The type of Transaction to expect

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fn write<'async_trait>(
 self,
 txn: T,
 bounds: Bounds,
 other: SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>>
) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where
 Self: 'async_trait,

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

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impl<FD, FS, D, T, A> TensorDualIO<D, Tensor<FD, FS, D, T>> for SparseTensor<FD, FS, D, T, A> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<BTreeType> + From<TensorType>,
 A: SparseWrite<FD, FS, D, T>,

type Txn = T

The type of Transaction to expect

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fn write<'async_trait>(
 self,
 txn: Self::Txn,
 bounds: Bounds,
 other: Tensor<FD, FS, D, T>
) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where
 Self: 'async_trait,

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

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impl<FD, FS, D, T, A> TensorIO<D> for SparseTensor<FD, FS, D, T, A> where
 FD: File<Array>,
 FS: File<Node>,
 D: Dir,
 T: Transaction<D>,
 A: SparseWrite<FD, FS, D, T>,

type Txn = T

The type of Transaction to expect

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

Read a single value from this Tensor.

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fn write_value<'life0, 'async_trait>(
 &'life0 self,
 txn_id: TxnId,
 bounds: Bounds,
 value: Number
) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where
 'life0: 'async_trait,
 Self: 'async_trait,

Write a single value to the slice of this Tensor with the given Bounds.

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fn write_value_at<'life0, 'async_trait>(
 &'life0 self,
 txn_id: TxnId,
 coord: Coord,
 value: Number
) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where
 'life0: 'async_trait,
 Self: 'async_trait,

Overwrite a single element of this Tensor.

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impl<FD, FS, D, T, A> TensorIndex<D> for SparseTensor<FD, FS, D, T, A> where
 FD: File<Array>,
 FS: File<Node>,
 D: Dir,
 T: Transaction<D>,
 A: SparseWrite<FD, FS, D, T>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<BTreeType> + From<TensorType>,

type Txn = T

The type of Transaction to expect

type Index = SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>>

The type of Tensor returned by argmax.

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fn argmax<'async_trait>(
 self,
 txn: Self::Txn,
 axis: usize
) -> Pin<Box<dyn Future<Output = TCResult<Self::Index>> + Send + 'async_trait>> where
 Self: 'async_trait,

Return the indices of the maximum values in this Tensor along the given axis.

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fn argmax_all<'async_trait>(
 self,
 txn: Self::Txn
) -> Pin<Box<dyn Future<Output = TCResult<u64>> + Send + 'async_trait>> where
 Self: 'async_trait,

Return the offset of the maximum value in this Tensor.

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impl<FD, FS, D, T, A> TensorInstance for SparseTensor<FD, FS, D, T, A>

type Dense = DenseTensor<FD, FS, D, T, BlockListSparse<FD, FS, D, T, A>>

A dense representation of this Tensor

type Sparse = SparseTensor<FD, FS, D, T, A>

A sparse representation of this Tensor

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fn into_dense(self) -> Self::Dense

Return a dense representation of this Tensor.

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fn into_sparse(self) -> Self::Sparse

Return a sparse representation of this Tensor.

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impl<FD, FS, D, T, L, R> TensorMath<D, SparseTensor<FD, FS, D, T, R>> for SparseTensor<FD, FS, D, T, L> where
 FD: File<Array>,
 FS: File<Node>,
 D: Dir,
 T: Transaction<D>,
 L: SparseAccess<FD, FS, D, T>,
 R: SparseAccess<FD, FS, D, T>,

type Combine = SparseTensor<FD, FS, D, T, SparseCombinator<FD, FS, D, T, L, R>>

The result type of a math operation

type LeftCombine = SparseTensor<FD, FS, D, T, SparseLeftCombinator<FD, FS, D, T, L, R>>

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

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fn add(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Combine>

Add two tensors together.

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fn div(
self,
other: SparseTensor<FD, FS, D, T, R>
) -> TCResult<Self::LeftCombine>

Divide self by other.

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fn log(self, base: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::LeftCombine>

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

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fn mul(
self,
other: SparseTensor<FD, FS, D, T, R>
) -> TCResult<Self::LeftCombine>

Multiply two tensors together.

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fn pow(
self,
other: SparseTensor<FD, FS, D, T, R>
) -> TCResult<Self::LeftCombine>

Raise self to the power of other.

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fn sub(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Combine>

Subtract other from self.

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impl<FD, FS, D, T, A> TensorMath<D, Tensor<FD, FS, D, T>> for SparseTensor<FD, FS, D, T, A> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<TensorType>,
 A: SparseAccess<FD, FS, D, T>,

type Combine = Tensor<FD, FS, D, T>

The result type of a math operation

type LeftCombine = Tensor<FD, FS, D, T>

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

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fn add(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

Add two tensors together.

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fn div(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

Divide self by other.

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fn log(self, base: Tensor<FD, FS, D, T>) -> TCResult<Self::LeftCombine>

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

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fn mul(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

Multiply two tensors together.

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fn pow(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

Raise self to the power of other.

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fn sub(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

Subtract other from self.

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impl<FD, FS, D, T, A> TensorMathConst for SparseTensor<FD, FS, D, T, A> where
 FD: File<Array>,
 FS: File<Node>,
 D: Dir,
 T: Transaction<D>,
 A: SparseAccess<FD, FS, D, T>,
 Self: TensorInstance,
 <Self as TensorInstance>::Dense: TensorMathConst,

type Combine = SparseTensor<FD, FS, D, T, SparseConstCombinator<FD, FS, D, T, A>>

The return type of a math operation

type DenseCombine = <<SparseTensor<FD, FS, D, T, A> as TensorInstance>::Dense as TensorMathConst>::DenseCombine

The return type of a math operation with a result expected to be dense

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

Add a constant to this tensor

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

Divide self by other.

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

Element-wise logarithm

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

Multiply self by other.

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

Raise self to the power other.

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

Subtract other from self.

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impl<FD, FS, D, T> TensorPersist for SparseTensor<FD, FS, D, T, SparseAccessor<FD, FS, D, T>>

type Persistent = SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>>

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fn as_persistent(self) -> Option<Self::Persistent>

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impl<FD, FS, D, T, A> TensorReduce<D> for SparseTensor<FD, FS, D, T, A> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<TensorType>,
 A: SparseAccess<FD, FS, D, T>,
 Self: TensorInstance,
 <Self as TensorInstance>::Dense: TensorReduce<D, Txn = T> + Send + Sync,

type Txn = T

The type of Transaction to expect

type Reduce = SparseTensor<FD, FS, D, T, SparseReduce<FD, FS, D, T>>

The result type of a reduce operation

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fn max(self, axis: usize, keepdims: bool) -> TCResult<Self::Reduce>

Return the maximum of this Tensor along the given axis.

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fn max_all(&self, txn: Self::Txn) -> TCBoxTryFuture<'_, Number>

Return the maximum element in this Tensor.

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fn min(self, axis: usize, keepdims: bool) -> TCResult<Self::Reduce>

Return the minimum of this Tensor along the given axis.

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fn min_all(&self, txn: Self::Txn) -> TCBoxTryFuture<'_, Number>

Return the minimum element in this Tensor.

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fn product(self, axis: usize, keepdims: bool) -> TCResult<Self::Reduce>

Return the product of this Tensor along the given axis.

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fn product_all(&self, txn: T) -> TCBoxTryFuture<'_, Number>

Return the product of all elements in this Tensor.

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fn sum(self, axis: usize, keepdims: bool) -> TCResult<Self::Reduce>

Return the sum of this Tensor along the given axis.

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fn sum_all(&self, txn: T) -> TCBoxTryFuture<'_, Number>

Return the sum of all elements in this Tensor.

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impl<FD, FS, D, T, A> TensorTransform for SparseTensor<FD, FS, D, T, A> where
 D: Dir,
 T: Transaction<D>,
 FD: File<Array>,
 FS: File<Node>,
 D::File: AsType<FD> + AsType<FS>,
 D::FileClass: From<TensorType>,
 A: SparseAccess<FD, FS, D, T>,

type Broadcast = SparseTensor<FD, FS, D, T, SparseAccessor<FD, FS, D, T>>

A broadcast Tensor

type Cast = SparseTensor<FD, FS, D, T, SparseCast<FD, FS, D, T, A>>

A type-cast Tensor

type Expand = SparseTensor<FD, FS, D, T, SparseExpand<FD, FS, D, T, A>>

A Tensor with an expanded dimension

type Flip = SparseTensor<FD, FS, D, T, SparseFlip<FD, FS, D, T, A>>

A Tensor flipped around one axis

type Reshape = SparseTensor<FD, FS, D, T, SparseReshape<FD, FS, D, T, A>>

A reshaped Tensor

type Slice = SparseTensor<FD, FS, D, T, <A as SparseAccess<FD, FS, D, T>>::Slice>

A Tensor slice

type Transpose = SparseTensor<FD, FS, D, T, SparseAccessor<FD, FS, D, T>>

A transposed Tensor

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

Broadcast this Tensor to the given shape.

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

Cast this Tensor to the given dtype.

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fn expand_dims(self, axis: usize) -> TCResult<Self::Expand>

Insert a new dimension of size 1 at the given axis.

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fn flip(self, axis: usize) -> TCResult<Self::Flip>

Flip this Tensor around the given axis.

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

Change the shape of this Tensor.

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fn slice(self, bounds: Bounds) -> TCResult<Self::Slice>

Return a slice of this Tensor with the given bounds.

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fn transpose(self, permutation: Option<Vec<usize>>) -> 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. Read more

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impl<FD, FS, D, T, A> TensorTrig for SparseTensor<FD, FS, D, T, A> where
 FD: File<Array>,
 FS: File<Node>,
 D: Dir,
 T: Transaction<D>,
 A: SparseAccess<FD, FS, D, T>,

type Unary = SparseTensor<FD, FS, D, T, SparseUnary<FD, FS, D, T>>

The return type of a unary operation

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

Element-wise arcsine

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

Element-wise sine

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

Element-wise hyperbolic sine

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fn asinh(&self) -> TCResult<Self::Unary>

Element-wise hyperbolic arcsine

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

Element-wise arccosine

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

Element-wise cosine

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

Element-wise hyperbolic cosine

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fn acosh(&self) -> TCResult<Self::Unary>

Element-wise hyperbolic arccosine

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

Element-wise arctangent

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

Element-wise tangent

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

Element-wise hyperbolic tangent

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fn atanh(&self) -> TCResult<Self::Unary>

Element-wise hyperbolic arctangent

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impl<FD, FS, D, T, A> TensorUnary<D> for SparseTensor<FD, FS, D, T, A> where
 FD: File<Array>,
 FS: File<Node>,
 D: Dir,
 T: Transaction<D>,
 A: SparseAccess<FD, FS, D, T>,

type Txn = T

The type of Transaction to expect

type Unary = SparseTensor<FD, FS, D, T, SparseUnary<FD, FS, D, T>>

The return type of a unary operation

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

Element-wise absolute value

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

Element-wise exponentiation

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

Element-wise natural logarithm

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

Element-wise round to the nearest integer

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fn all<'async_trait>(
 self,
 txn: Self::Txn
) -> Pin<Box<dyn Future<Output = TCResult<bool>> + Send + 'async_trait>> where
 Self: 'async_trait,

Return true if all elements in this Tensor are nonzero.

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fn any<'async_trait>(
 self,
 txn: Self::Txn
) -> Pin<Box<dyn Future<Output = TCResult<bool>> + Send + 'async_trait>> where
 Self: 'async_trait,

Return true if any element in this Tensor is nonzero.

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

Element-wise logical not

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impl<FD, FS, D, T> Transact for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where
Self: Send + Sync,
SparseTable<FD, FS, D, T>: Transact + Send + Sync,

source

fn commit<'life0, 'life1, 'async_trait>(
 &'life0 self,
 txn_id: &'life1 TxnId
) -> Pin<Box<dyn Future<Output = ()> + Send + 'async_trait>> where
 'life0: 'async_trait,
 'life1: 'async_trait,
 Self: 'async_trait,

Commit this transaction.

source

fn finalize<'life0, 'life1, 'async_trait>(
 &'life0 self,
 txn_id: &'life1 TxnId
) -> Pin<Box<dyn Future<Output = ()> + Send + 'async_trait>> where
 'life0: 'async_trait,
 'life1: 'async_trait,
 Self: 'async_trait,

Delete any version data specific to this transaction.

Auto Trait Implementations

impl<FD, FS, D, T, A> RefUnwindSafe for SparseTensor<FD, FS, D, T, A> where
 A: RefUnwindSafe,
 D: RefUnwindSafe,
 FD: RefUnwindSafe,
 FS: RefUnwindSafe,
 T: RefUnwindSafe,

impl<FD, FS, D, T, A> Send for SparseTensor<FD, FS, D, T, A> where
 A: Send,
 D: Send,
 FD: Send,
 FS: Send,
 T: Send,

impl<FD, FS, D, T, A> Sync for SparseTensor<FD, FS, D, T, A> where
 A: Sync,
 D: Sync,
 FD: Sync,
 FS: Sync,
 T: Sync,

impl<FD, FS, D, T, A> Unpin for SparseTensor<FD, FS, D, T, A> where
 A: Unpin,
 D: Unpin,
 FD: Unpin,
 FS: Unpin,
 T: Unpin,

impl<FD, FS, D, T, A> UnwindSafe for SparseTensor<FD, FS, D, T, A> where
 A: UnwindSafe,
 D: UnwindSafe,
 FD: UnwindSafe,
 FS: UnwindSafe,
 T: UnwindSafe,

Blanket Implementations

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impl<T> Any for T where
T: 'static + ?Sized,

source

fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more

source

impl<T> Borrow<T> for T where
T: ?Sized,

const: unstable · source

fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more

source

impl<T> BorrowMut<T> for T where
T: ?Sized,

const: unstable · source

fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more

source

impl<F, T> CastFrom<F> for T where
T: From<F>,

source

fn cast_from(f: F) -> T

Cast an instance of T into an instance of Self.

source

impl<T, F> CastInto<F> for T where
F: CastFrom<T>,

source

fn cast_into(self) -> F

Cast an instance of Self into an instance of T.

source

impl<T> From<!> for T

const: unstable · source

fn from(t: !) -> T

Converts to this type from the input type.

source

impl<T> From<T> for T

const: unstable · source

fn from(t: T) -> T

Returns the argument unchanged.

source

impl<T, U> Into for T where
U: From<T>,

const: unstable · source

fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

source

impl<F> Match for F

source

fn matches<T>(&self) -> bool where
T: TryCastFrom<Self>,

Returns true if self can be cast into the target type T.

source

impl<T> Same<T> for T

type Output = T

Should always be Self

source

impl<T> ToOwned for T where
T: Clone,

type Owned = T

The resulting type after obtaining ownership.

source

fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more

source

fn clone_into(&self, target: &mut T)

🔬 This is a nightly-only experimental API. (toowned_clone_into)

Uses borrowed data to replace owned data, usually by cloning. Read more

source

impl<T> ToString for T where
T: Display + ?Sized,

source

default fn to_string(&self) -> String

Converts the given value to a String. Read more

source

impl<F, T> TryCastFrom<F> for T where
T: CastFrom<F>,

source

fn can_cast_from(&F) -> bool

Test if value can be cast into Self.

source

fn opt_cast_from(f: F) -> Option<T>

Returns Some(Self) if the source value can be cast into Self, otherwise None.

source

fn try_cast_from<Err, OnErr>(value: T, on_err: OnErr) -> Result<Self, Err> where
OnErr: FnOnce(&T) -> Err,

Returns Ok(Self) if the source value can be cast into Self, otherwise calls on_err.

source

impl<F, T> TryCastInto<T> for F where
T: TryCastFrom<F>,

source

fn can_cast_into(&self) -> bool

Test if self can be cast into T.

source

fn opt_cast_into(self) -> Option<T>

Returns Some(T) if self can be cast into T, otherwise None.

source

fn try_cast_into<Err, OnErr>(self, on_err: OnErr) -> Result<T, Err> where
OnErr: FnOnce(&Self) -> Err,

Returns Ok(T) if self can be cast into T, otherwise calls on_err.

source

impl<T, U> TryFrom for T where
U: Into<T>,

type Error = Infallible

The type returned in the event of a conversion error.

const: unstable · source

fn try_from(value: U) -> Result<T, <T as TryFrom>::Error>

Performs the conversion.

source

impl<T, U> TryInto for T where
U: TryFrom<T>,

type Error = >::Error

The type returned in the event of a conversion error.

const: unstable · source

fn try_into(self) -> Result<U, >::Error>

Performs the conversion.

Struct tc_tensor::SparseTensor

Implementations

impl<FD, FS, D, T, A> SparseTensor<FD, FS, D, T, A>

pub fn into_inner(self) -> A

impl<FD, FS, D, T> SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where D: Dir, T: Transaction<D>, FD: File<Array>, FS: File<Node>, D::File: AsType<FD> + AsType<FS>, D::FileClass: From<BTreeType> + From<TensorType>,

pub async fn create(dir: &D, schema: Schema, txn_id: TxnId) -> TCResult<Self>

pub async fn tile( txn: T, tensor: SparseTensor<FD, FS, D, T, SparseAccessor<FD, FS, D, T>>, multiples: Vec<u64>) -> TCResult<Self>

Trait Implementations

impl<FD: Clone, FS: Clone, D: Clone, T: Clone, A: Clone> Clone for SparseTensor<FD, FS, D, T, A>

fn clone(&self) -> SparseTensor<FD, FS, D, T, A>

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

impl<FD, FS, D, T, A> CopyFrom<D, SparseTensor<FD, FS, D, T, A>> for SparseTable<FD, FS, D, T> where D: Dir, T: Transaction<D>, FD: File<Array>, FS: File<Node>, D::File: AsType<FD> + AsType<FS>, A: SparseAccess<FD, FS, D, T>, D::FileClass: From<BTreeType> + From<TensorType>,

fn copy_from<'life0, 'async_trait>( instance: SparseTensor<FD, FS, D, T, A>, store: D, txn: &'life0 T) -> Pin<Box<dyn Future<Output = TCResult<Self>> + Send + 'async_trait>> where 'life0: 'async_trait, Self: 'async_trait,

fn copy_from<'life0, 'async_trait>( instance: SparseTensor<FD, FS, D, T, A>, store: Self::Store, txn: &'life0 Self::Txn) -> Pin<Box<dyn Future<Output = TCResult<Self>> + Send + 'async_trait>> where 'life0: 'async_trait, Self: 'async_trait,

impl<FD, FS, D, T, A> Display for SparseTensor<FD, FS, D, T, A>

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

impl<FD, FS, D, T, A> From<A> for SparseTensor<FD, FS, D, T, A>

fn from(accessor: A) -> Self

impl<FD, FS, D, T, A> From<SparseTensor<FD, FS, D, T, A>> for Tensor<FD, FS, D, T> where D: Dir, T: Transaction<D>, FD: File<Array>, FS: File<Node>, D::File: AsType<FD> + AsType<FS>, A: SparseAccess<FD, FS, D, T>, D::FileClass: From<TensorType>,

fn from(sparse: SparseTensor<FD, FS, D, T, A>) -> Self

impl<FD, FS, D, T> FromStream for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where D: Dir, T: Transaction<D>, FD: File<Array>, FS: File<Node>, D::File: AsType<FD> + AsType<FS>, D::FileClass: From<BTreeType> + From<TensorType>,

type Context = T

fn from_stream<'life0, 'async_trait, De>( txn: T, decoder: &'life0 mut De) -> Pin<Box<dyn Future<Output = Result<Self, De::Error>> + Send + 'async_trait>> where De: 'async_trait + Decoder, 'life0: 'async_trait, Self: 'async_trait,

impl<FD, FS, D, T, A> Instance for SparseTensor<FD, FS, D, T, A> where Self: Send + Sync,

type Class = TensorType

fn class(&self) -> Self::Class

impl<'en, FD, FS, D, T, A> IntoView<'en, D> for SparseTensor<FD, FS, D, T, A> where D: Dir, T: Transaction<D>, FD: File<Array>, FS: File<Node>, D::File: AsType<FD> + AsType<FS>, D::FileClass: From<TensorType>, A: SparseAccess<FD, FS, D, T>,

type Txn = T

type View = SparseTensorView<'en>

fn into_view<'async_trait>( self, txn: Self::Txn) -> Pin<Box<dyn Future<Output = TCResult<Self::View>> + Send + 'async_trait>> where Self: 'async_trait,

impl<FD, FS, D, T> Persist<D> for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where D: Dir, T: Transaction<D>, FD: File<Array>, FS: File<Node>, D::File: AsType<FD> + AsType<FS>, D::FileClass: From<BTreeType> + From<TensorType>,

type Schema = Schema

type Store = D

type Txn = T

fn schema(&self) -> &Self::Schema

fn load<'life0, 'async_trait>( txn: &'life0 Self::Txn, schema: Self::Schema, store: Self::Store) -> Pin<Box<dyn Future<Output = TCResult<Self>> + Send + 'async_trait>> where 'life0: 'async_trait, Self: 'async_trait,

impl<FD, FS, D, T> Restore<D> for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where D: Dir, T: Transaction<D>, FD: File<Array>, FS: File<Node>, D::File: AsType<FD> + AsType<FS>, D::FileClass: From<BTreeType> + From<TensorType>,

fn restore<'life0, 'life1, 'async_trait>( &'life0 self, backup: &'life1 Self, txn_id: TxnId) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where 'life0: 'async_trait, 'life1: 'async_trait, Self: 'async_trait,

impl<FD, FS, D, T, A> TensorAccess for SparseTensor<FD, FS, D, T, A> where FD: File<Array>, FS: File<Node>, D: Dir, T: Transaction<D>, A: SparseAccess<FD, FS, D, T>,

fn dtype(&self) -> NumberType

fn ndim(&self) -> usize

fn shape(&self) -> &Shape

fn size(&self) -> u64

impl<FD, FS, D, T, L, R> TensorBoolean<SparseTensor<FD, FS, D, T, R>> for SparseTensor<FD, FS, D, T, L> where FD: File<Array>, FS: File<Node>, D: Dir, T: Transaction<D>, L: SparseAccess<FD, FS, D, T>, R: SparseAccess<FD, FS, D, T>,

type Combine = SparseTensor<FD, FS, D, T, SparseCombinator<FD, FS, D, T, L, R>>

type LeftCombine = SparseTensor<FD, FS, D, T, SparseLeftCombinator<FD, FS, D, T, L, R>>

fn and( self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::LeftCombine>

fn or(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Combine>

fn xor(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Combine>

impl<FD, FS, D, T, A> TensorBoolean<Tensor<FD, FS, D, T>> for SparseTensor<FD, FS, D, T, A> where D: Dir, T: Transaction<D>, FD: File<Array>, FS: File<Node>, D::File: AsType<FD> + AsType<FS>, D::FileClass: From<TensorType>, A: SparseAccess<FD, FS, D, T>,

type Combine = Tensor<FD, FS, D, T>

type LeftCombine = Tensor<FD, FS, D, T>

fn and(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

fn or(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

fn xor(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Combine>

impl<FD, FS, D, T, A> TensorBooleanConst for SparseTensor<FD, FS, D, T, A> where FD: File<Array>, FS: File<Node>, D: Dir, T: Transaction<D>, A: SparseAccess<FD, FS, D, T>, Self: TensorInstance, <Self as TensorInstance>::Dense: TensorBooleanConst,

type Combine = SparseTensor<FD, FS, D, T, SparseConstCombinator<FD, FS, D, T, A>>

type DenseCombine = <<SparseTensor<FD, FS, D, T, A> as TensorInstance>::Dense as TensorBooleanConst>::DenseCombine

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

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

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

impl<FD, FS, D, T, L, R> TensorCompare<SparseTensor<FD, FS, D, T, R>> for SparseTensor<FD, FS, D, T, L> where D: Dir, T: Transaction<D>, FD: File<Array>, FS: File<Node>, D::File: AsType<FD> + AsType<FS>, D::FileClass: From<TensorType>, L: SparseAccess<FD, FS, D, T>, R: SparseAccess<FD, FS, D, T>,

type Compare = SparseTensor<FD, FS, D, T, SparseCombinator<FD, FS, D, T, L, R>>

type Dense = DenseTensor<FD, FS, D, T, BlockListSparse<FD, FS, D, T, SparseCombinator<FD, FS, D, T, L, R>>>

fn eq(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Dense>

fn gt(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Compare>

fn gte(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Dense>

fn lt(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Compare>

fn lte(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Dense>

fn ne(self, other: SparseTensor<FD, FS, D, T, R>) -> TCResult<Self::Compare>

impl<FD, FS, D, T, A> TensorCompare<Tensor<FD, FS, D, T>> for SparseTensor<FD, FS, D, T, A> where D: Dir, T: Transaction<D>, FD: File<Array>, FS: File<Node>, D::File: AsType<FD> + AsType<FS>, D::FileClass: From<TensorType>, A: SparseAccess<FD, FS, D, T>,

type Compare = Tensor<FD, FS, D, T>

type Dense = Tensor<FD, FS, D, T>

fn eq(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Dense>

fn gt(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Compare>

fn gte(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Dense>

fn lt(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Compare>

fn lte(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Dense>

fn ne(self, other: Tensor<FD, FS, D, T>) -> TCResult<Self::Compare>

impl<FD, FS, D, T, A> TensorCompareConst for SparseTensor<FD, FS, D, T, A>

impl<FD, FS, D, T> SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<BTreeType> + From<TensorType>,

pub async fn tile(
txn: T,
tensor: SparseTensor<FD, FS, D, T, SparseAccessor<FD, FS, D, T>>,
multiples: Vec<u64>
) -> TCResult<Self>

impl<FD, FS, D, T, A> CopyFrom<D, SparseTensor<FD, FS, D, T, A>> for SparseTable<FD, FS, D, T> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
A: SparseAccess<FD, FS, D, T>,
D::FileClass: From<BTreeType> + From<TensorType>,

fn copy_from<'life0, 'async_trait>(
instance: SparseTensor<FD, FS, D, T, A>,
store: D,
txn: &'life0 T
) -> Pin<Box<dyn Future<Output = TCResult<Self>> + Send + 'async_trait>> where
'life0: 'async_trait,
Self: 'async_trait,

fn copy_from<'life0, 'async_trait>(
instance: SparseTensor<FD, FS, D, T, A>,
store: Self::Store,
txn: &'life0 Self::Txn
) -> Pin<Box<dyn Future<Output = TCResult<Self>> + Send + 'async_trait>> where
'life0: 'async_trait,
Self: 'async_trait,

impl<FD, FS, D, T, A> From<SparseTensor<FD, FS, D, T, A>> for Tensor<FD, FS, D, T> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
A: SparseAccess<FD, FS, D, T>,
D::FileClass: From<TensorType>,

impl<FD, FS, D, T> FromStream for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<BTreeType> + From<TensorType>,

fn from_stream<'life0, 'async_trait, De>(
txn: T,
decoder: &'life0 mut De
) -> Pin<Box<dyn Future<Output = Result<Self, De::Error>> + Send + 'async_trait>> where
De: 'async_trait + Decoder,
'life0: 'async_trait,
Self: 'async_trait,

impl<FD, FS, D, T, A> Instance for SparseTensor<FD, FS, D, T, A> where
Self: Send + Sync,

impl<'en, FD, FS, D, T, A> IntoView<'en, D> for SparseTensor<FD, FS, D, T, A> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<TensorType>,
A: SparseAccess<FD, FS, D, T>,

fn into_view<'async_trait>(
self,
txn: Self::Txn
) -> Pin<Box<dyn Future<Output = TCResult<Self::View>> + Send + 'async_trait>> where
Self: 'async_trait,

impl<FD, FS, D, T> Persist<D> for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<BTreeType> + From<TensorType>,

fn load<'life0, 'async_trait>(
txn: &'life0 Self::Txn,
schema: Self::Schema,
store: Self::Store
) -> Pin<Box<dyn Future<Output = TCResult<Self>> + Send + 'async_trait>> where
'life0: 'async_trait,
Self: 'async_trait,

impl<FD, FS, D, T> Restore<D> for SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<BTreeType> + From<TensorType>,

fn restore<'life0, 'life1, 'async_trait>(
&'life0 self,
backup: &'life1 Self,
txn_id: TxnId
) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where
'life0: 'async_trait,
'life1: 'async_trait,
Self: 'async_trait,

impl<FD, FS, D, T, A> TensorAccess for SparseTensor<FD, FS, D, T, A> where
FD: File<Array>,
FS: File<Node>,
D: Dir,
T: Transaction<D>,
A: SparseAccess<FD, FS, D, T>,

impl<FD, FS, D, T, L, R> TensorBoolean<SparseTensor<FD, FS, D, T, R>> for SparseTensor<FD, FS, D, T, L> where
FD: File<Array>,
FS: File<Node>,
D: Dir,
T: Transaction<D>,
L: SparseAccess<FD, FS, D, T>,
R: SparseAccess<FD, FS, D, T>,

fn and(
self,
other: SparseTensor<FD, FS, D, T, R>
) -> TCResult<Self::LeftCombine>

impl<FD, FS, D, T, A> TensorBoolean<Tensor<FD, FS, D, T>> for SparseTensor<FD, FS, D, T, A> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<TensorType>,
A: SparseAccess<FD, FS, D, T>,

impl<FD, FS, D, T, A> TensorBooleanConst for SparseTensor<FD, FS, D, T, A> where
FD: File<Array>,
FS: File<Node>,
D: Dir,
T: Transaction<D>,
A: SparseAccess<FD, FS, D, T>,
Self: TensorInstance,
<Self as TensorInstance>::Dense: TensorBooleanConst,

impl<FD, FS, D, T, L, R> TensorCompare<SparseTensor<FD, FS, D, T, R>> for SparseTensor<FD, FS, D, T, L> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<TensorType>,
L: SparseAccess<FD, FS, D, T>,
R: SparseAccess<FD, FS, D, T>,

impl<FD, FS, D, T, A> TensorCompare<Tensor<FD, FS, D, T>> for SparseTensor<FD, FS, D, T, A> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<TensorType>,
A: SparseAccess<FD, FS, D, T>,

fn diagonal<'async_trait>(
self,
txn: Self::Txn
) -> Pin<Box<dyn Future<Output = TCResult<Self::Diagonal>> + Send + 'async_trait>> where
Self: 'async_trait,

impl<FD, FS, D, T, L> TensorDualIO<D, SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>>> for SparseTensor<FD, FS, D, T, L> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<TensorType>,
L: SparseWrite<FD, FS, D, T>,

fn write<'async_trait>(
self,
txn: T,
bounds: Bounds,
other: SparseTensor<FD, FS, D, T, SparseTable<FD, FS, D, T>>
) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where
Self: 'async_trait,

impl<FD, FS, D, T, A> TensorDualIO<D, Tensor<FD, FS, D, T>> for SparseTensor<FD, FS, D, T, A> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<BTreeType> + From<TensorType>,
A: SparseWrite<FD, FS, D, T>,

fn write<'async_trait>(
self,
txn: Self::Txn,
bounds: Bounds,
other: Tensor<FD, FS, D, T>
) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where
Self: 'async_trait,

impl<FD, FS, D, T, A> TensorIO<D> for SparseTensor<FD, FS, D, T, A> where
FD: File<Array>,
FS: File<Node>,
D: Dir,
T: Transaction<D>,
A: SparseWrite<FD, FS, D, T>,

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

fn write_value<'life0, 'async_trait>(
&'life0 self,
txn_id: TxnId,
bounds: Bounds,
value: Number
) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where
'life0: 'async_trait,
Self: 'async_trait,

fn write_value_at<'life0, 'async_trait>(
&'life0 self,
txn_id: TxnId,
coord: Coord,
value: Number
) -> Pin<Box<dyn Future<Output = TCResult<()>> + Send + 'async_trait>> where
'life0: 'async_trait,
Self: 'async_trait,

impl<FD, FS, D, T, A> TensorIndex<D> for SparseTensor<FD, FS, D, T, A> where
FD: File<Array>,
FS: File<Node>,
D: Dir,
T: Transaction<D>,
A: SparseWrite<FD, FS, D, T>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<BTreeType> + From<TensorType>,

fn argmax<'async_trait>(
self,
txn: Self::Txn,
axis: usize
) -> Pin<Box<dyn Future<Output = TCResult<Self::Index>> + Send + 'async_trait>> where
Self: 'async_trait,

fn argmax_all<'async_trait>(
self,
txn: Self::Txn
) -> Pin<Box<dyn Future<Output = TCResult<u64>> + Send + 'async_trait>> where
Self: 'async_trait,

impl<FD, FS, D, T, L, R> TensorMath<D, SparseTensor<FD, FS, D, T, R>> for SparseTensor<FD, FS, D, T, L> where
FD: File<Array>,
FS: File<Node>,
D: Dir,
T: Transaction<D>,
L: SparseAccess<FD, FS, D, T>,
R: SparseAccess<FD, FS, D, T>,

fn div(
self,
other: SparseTensor<FD, FS, D, T, R>
) -> TCResult<Self::LeftCombine>

fn mul(
self,
other: SparseTensor<FD, FS, D, T, R>
) -> TCResult<Self::LeftCombine>

fn pow(
self,
other: SparseTensor<FD, FS, D, T, R>
) -> TCResult<Self::LeftCombine>

impl<FD, FS, D, T, A> TensorMath<D, Tensor<FD, FS, D, T>> for SparseTensor<FD, FS, D, T, A> where
D: Dir,
T: Transaction<D>,
FD: File<Array>,
FS: File<Node>,
D::File: AsType<FD> + AsType<FS>,
D::FileClass: From<TensorType>,
A: SparseAccess<FD, FS, D, T>,

impl<FD, FS, D, T, A> TensorMathConst for SparseTensor<FD, FS, D, T, A> where
FD: File<Array>,
FS: File<Node>,
D: Dir,
T: Transaction<D>,
A: SparseAccess<FD, FS, D, T>,
Self: TensorInstance,
<Self as TensorInstance>::Dense: TensorMathConst,