Enum DynTensor 

pub enum DynTensor {
    F32(StructuredTensor<f32>),
    F64(StructuredTensor<f64>),
    C32(StructuredTensor<Complex<f32>>),
    C64(StructuredTensor<Complex<f64>>),
}

Runtime tensor wrapper for a fixed supported dtype set.

DynTensor is the canonical dynamic primal tensor type shared by tenferro frontends. Each variant carries a StructuredTensor<T>, so dense tensors and structured special cases such as Diag share the same container.

Examples

use tenferro_internal_frontend_core::{DynTensor, ScalarType, StructuredTensor};
use tenferro_tensor::{MemoryOrder, Tensor};

let t = Tensor::<f64>::from_slice(&[1.0, 2.0], &[2], MemoryOrder::ColumnMajor).unwrap();
let x: DynTensor = StructuredTensor::from(t).into();
assert_eq!(x.scalar_type(), ScalarType::F64);

Variants

F32(StructuredTensor<f32>)

F64(StructuredTensor<f64>)

C32(StructuredTensor<Complex<f32>>)

C64(StructuredTensor<Complex<f64>>)

Implementations

impl DynTensor

pub fn scalar_type(&self) -> ScalarType

Returns runtime scalar type.

Examples

use tenferro_internal_frontend_core::{DynTensor, ScalarType, StructuredTensor};
use tenferro_tensor::{MemoryOrder, Tensor};

let t = Tensor::<f32>::from_slice(&[1.0], &[1], MemoryOrder::ColumnMajor).unwrap();
let x: DynTensor = StructuredTensor::from(t).into();
assert_eq!(x.scalar_type(), ScalarType::F32);

pub fn dims(&self) -> &[usize]

Returns logical dimensions of the underlying tensor.

pub fn axis_classes(&self) -> &[usize]

Returns axis equivalence classes of the structured layout.

pub fn is_dense(&self) -> bool

Returns true when the structured payload is dense.

pub fn is_diag(&self) -> bool

Returns true when the structured payload is diagonal.

pub fn to_dense(&self) -> Result<DynTensor, Error>

Materializes a dense snapshot with the same logical tensor values.

pub fn ndim(&self) -> usize

pub fn len(&self) -> usize

pub fn is_empty(&self) -> bool

pub fn as_f32(&self) -> Option<&StructuredTensor<f32>>

pub fn as_f64(&self) -> Option<&StructuredTensor<f64>>

pub fn as_c32(&self) -> Option<&StructuredTensor<Complex<f32>>>

pub fn as_c64(&self) -> Option<&StructuredTensor<Complex<f64>>>

pub fn payload_f32(&self) -> Option<&Tensor<f32>>

pub fn payload_f64(&self) -> Option<&Tensor<f64>>

pub fn payload_c32(&self) -> Option<&Tensor<Complex<f32>>>

pub fn payload_c64(&self) -> Option<&Tensor<Complex<f64>>>

pub fn try_sub(&self, rhs: &DynTensor) -> Result<DynTensor, Error>

pub fn abs_tensor(&self) -> Result<DynTensor, Error>

pub fn max(&self) -> Result<DynTensor, Error>

pub fn max_as_f64(&self) -> Result<f64, Error>

pub fn max_abs_diff(&self, rhs: &DynTensor) -> Result<f64, Error>

Trait Implementations

impl Clone for DynTensor

fn clone(&self) -> DynTensor

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for DynTensor

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

Formats the value using the given formatter.

impl Differentiable for DynTensor

type Tangent = DynTensor

The tangent type for this value.

fn zero_tangent(&self) -> <DynTensor as Differentiable>::Tangent

Returns the zero tangent for this value (additive identity).

fn accumulate_tangent( a: <DynTensor as Differentiable>::Tangent, b: &<DynTensor as Differentiable>::Tangent, ) -> <DynTensor as Differentiable>::Tangent

Accumulates (adds) two tangents: a + b.

fn num_elements(&self) -> usize

Returns the number of scalar elements in this value.

fn seed_cotangent(&self) -> <DynTensor as Differentiable>::Tangent

Returns the seed cotangent for reverse-mode pullback.

impl From<StructuredTensor<Complex<f32>>> for DynTensor

fn from(value: StructuredTensor<Complex<f32>>) -> DynTensor

Converts to this type from the input type.

impl From<StructuredTensor<Complex<f64>>> for DynTensor

fn from(value: StructuredTensor<Complex<f64>>) -> DynTensor

Converts to this type from the input type.

impl From<StructuredTensor<f32>> for DynTensor

fn from(value: StructuredTensor<f32>) -> DynTensor

Converts to this type from the input type.

impl From<StructuredTensor<f64>> for DynTensor

fn from(value: StructuredTensor<f64>) -> DynTensor

Converts to this type from the input type.

impl From<Tensor<Complex<f32>>> for DynTensor

fn from(value: Tensor<Complex<f32>>) -> DynTensor

Converts to this type from the input type.

impl From<Tensor<Complex<f64>>> for DynTensor

fn from(value: Tensor<Complex<f64>>) -> DynTensor

Converts to this type from the input type.

impl From<Tensor<f32>> for DynTensor

fn from(value: Tensor<f32>) -> DynTensor

Converts to this type from the input type.

impl From<Tensor<f64>> for DynTensor

fn from(value: Tensor<f64>) -> DynTensor

Converts to this type from the input type.

impl LinearizableOp<DynTensor> for AddOp

type Linearized = AddLinearized

fn primal(&self, inputs: &[&DynTensor]) -> AdResult<Vec<DynTensor>>

fn input_schema(&self, _inputs: &[&DynTensor]) -> AdResult<Schema>

fn output_schema( &self, _inputs: &[&DynTensor], _outputs: &[DynTensor], ) -> AdResult<Schema>

fn linearize( &self, _inputs: &[&DynTensor], _outputs: &[DynTensor], ) -> AdResult<Self::Linearized>

fn checkpoint_hint(&self) -> CheckpointHint

Return a retain-vs-replay hint for the runtime checkpoint policy.

fn apply(&self, inputs: &[&Value<V>]) -> Result<Vec<Value<V>>, AutodiffError>

where Self: Sized + Clone,

fn apply_one(&self, inputs: &[&Value<V>]) -> Result<Value<V>, AutodiffError>

where Self: Sized + Clone,

impl LinearizableOp<DynTensor> for EinsumOp

type Linearized = EinsumLinearized

fn primal(&self, inputs: &[&DynTensor]) -> AdResult<Vec<DynTensor>>

fn input_schema(&self, inputs: &[&DynTensor]) -> AdResult<Schema>

fn output_schema( &self, _inputs: &[&DynTensor], _outputs: &[DynTensor], ) -> AdResult<Schema>

fn linearize( &self, inputs: &[&DynTensor], _outputs: &[DynTensor], ) -> AdResult<Self::Linearized>

fn checkpoint_hint(&self) -> CheckpointHint

Return a retain-vs-replay hint for the runtime checkpoint policy.

fn apply(&self, inputs: &[&Value<V>]) -> Result<Vec<Value<V>>, AutodiffError>

where Self: Sized + Clone,

fn apply_one(&self, inputs: &[&Value<V>]) -> Result<Value<V>, AutodiffError>

where Self: Sized + Clone,

impl LinearizableOp<DynTensor> for ExpOp

type Linearized = ExpLinearized

fn primal(&self, inputs: &[&DynTensor]) -> AdResult<Vec<DynTensor>>

fn input_schema(&self, _inputs: &[&DynTensor]) -> AdResult<Schema>

fn output_schema( &self, _inputs: &[&DynTensor], _outputs: &[DynTensor], ) -> AdResult<Schema>

fn linearize( &self, _inputs: &[&DynTensor], outputs: &[DynTensor], ) -> AdResult<Self::Linearized>

fn checkpoint_hint(&self) -> CheckpointHint

Return a retain-vs-replay hint for the runtime checkpoint policy.

fn apply(&self, inputs: &[&Value<V>]) -> Result<Vec<Value<V>>, AutodiffError>

where Self: Sized + Clone,

fn apply_one(&self, inputs: &[&Value<V>]) -> Result<Value<V>, AutodiffError>

where Self: Sized + Clone,

impl LinearizableOp<DynTensor> for SumOp

type Linearized = SumLinearized

fn primal(&self, inputs: &[&DynTensor]) -> AdResult<Vec<DynTensor>>

fn input_schema(&self, _inputs: &[&DynTensor]) -> AdResult<Schema>

fn output_schema( &self, _inputs: &[&DynTensor], _outputs: &[DynTensor], ) -> AdResult<Schema>

fn linearize( &self, inputs: &[&DynTensor], _outputs: &[DynTensor], ) -> AdResult<Self::Linearized>

fn checkpoint_hint(&self) -> CheckpointHint

Return a retain-vs-replay hint for the runtime checkpoint policy.

fn apply(&self, inputs: &[&Value<V>]) -> Result<Vec<Value<V>>, AutodiffError>

where Self: Sized + Clone,

fn apply_one(&self, inputs: &[&Value<V>]) -> Result<Value<V>, AutodiffError>

where Self: Sized + Clone,