Struct CpuBackend 

pub struct CpuBackend;

Reference CPU backend. Dispatches its opset onto ndarray kernels; storage is ArrayD<f32> end-to-end.

Implementations

impl CpuBackend

pub fn new() -> Self

Construct a fresh backend.

pub fn alloc_tensor(&self, shape: Vec<i64>) -> CpuTensor

Allocate a zero-initialised tensor with the given shape. Single allocation seam for future pool / arena strategies.

pub fn wrap_array(&self, array: ArrayD<f32>) -> CpuTensor

Wrap a kernel-produced ArrayD<f32> as a CpuTensor. Single wrapping seam for future pool / arena strategies.

Trait Implementations

impl AnyComponent for CpuBackend

fn as_any(&self) -> &dyn Any

Downcast view - immutable.

fn as_any_mut(&mut self) -> &mut dyn Any

Downcast view - mutable.

impl Backend for CpuBackend

bb::Backend Contract impl. Overrides execute to run through graph_walker::execute_graph rather than the default per-op walker.

fn materialize_from_wire( &self, type_hash: u64, bytes: Vec<u8>, ) -> Result<Self::Tensor, Self::Error>

Decode wire bytes inside the backend so the CpuTensor carries the ingress byte charge for slot-table release on overwrite. v1 uses bincode.

type Error = BackendError

Library-maker-defined error type. The From<BackendWalkError> bound lets the default per-op / execute_graph_via_per_op walker surface graph-validation failures as typed errors instead of panicking on peer-supplied or malformed GraphProto bodies.

type Tensor = CpuTensor

Native tensor representation.

fn execute( &self, graph: &GraphProto, inputs: HashMap<String, Self::Tensor>, _attrs: BackendAttrs<'_>, ) -> Result<HashMap<String, Self::Tensor>, Self::Error>

Execute every NodeProto in graph.node against the value env inputs. Returns the subset of values named in graph.output.

fn add( &self, a: &Self::Tensor, b: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Element-wise a + b with NumPy broadcasting.

fn sub( &self, a: &Self::Tensor, b: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Element-wise a - b with NumPy broadcasting.

fn mul( &self, a: &Self::Tensor, b: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Element-wise a * b with NumPy broadcasting.

fn div( &self, a: &Self::Tensor, b: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Element-wise a / b with NumPy broadcasting.

fn neg(&self, a: &Self::Tensor) -> Result<Self::Tensor, Self::Error>

Element-wise unary negation.

fn abs(&self, a: &Self::Tensor) -> Result<Self::Tensor, Self::Error>

Element-wise absolute value.

fn sqrt(&self, a: &Self::Tensor) -> Result<Self::Tensor, Self::Error>

Element-wise square root.

fn pow( &self, a: &Self::Tensor, b: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Element-wise a ** b with NumPy broadcasting.

fn exp(&self, a: &Self::Tensor) -> Result<Self::Tensor, Self::Error>

Element-wise natural exponential.

fn log(&self, a: &Self::Tensor) -> Result<Self::Tensor, Self::Error>

Element-wise natural logarithm.

fn matmul( &self, a: &Self::Tensor, b: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Matrix multiplication (NumPy semantics: 2-D × 2-D + batched higher-rank broadcasting).

fn reduce_sum( &self, a: &Self::Tensor, axes: &[i64], keepdims: bool, ) -> Result<Self::Tensor, Self::Error>

Sum-reduce a along axes. keepdims = true preserves the reduced dims as length-1.

fn reduce_mean( &self, a: &Self::Tensor, axes: &[i64], keepdims: bool, ) -> Result<Self::Tensor, Self::Error>

Mean-reduce a along axes.

fn reduce_max( &self, a: &Self::Tensor, axes: &[i64], keepdims: bool, ) -> Result<Self::Tensor, Self::Error>

Max-reduce a along axes.

fn reduce_min( &self, a: &Self::Tensor, axes: &[i64], keepdims: bool, ) -> Result<Self::Tensor, Self::Error>

Min-reduce a along axes.

fn reshape( &self, a: &Self::Tensor, shape: &[i64], ) -> Result<Self::Tensor, Self::Error>

Reshape a to the given dims. Total element count must match.

fn transpose( &self, a: &Self::Tensor, perm: &[i64], ) -> Result<Self::Tensor, Self::Error>

Transpose axes. Empty perm reverses all dims.

fn concat( &self, inputs: &[&Self::Tensor], axis: i64, ) -> Result<Self::Tensor, Self::Error>

Concatenate inputs along axis.

fn slice( &self, a: &Self::Tensor, starts: &[i64], ends: &[i64], axes: &[i64], steps: &[i64], ) -> Result<Self::Tensor, Self::Error>

NumPy-style slice. Empty axes defaults to all dims; empty steps defaults to 1 per axis.

fn split( &self, a: &Self::Tensor, axis: i64, sizes: &[i64], ) -> Result<Vec<Self::Tensor>, Self::Error>

Split a along axis into parts of the given sizes. Empty sizes means equal-sized splits (count comes from the consumer side downstream).

fn squeeze( &self, a: &Self::Tensor, axes: &[i64], ) -> Result<Self::Tensor, Self::Error>

Remove dimensions of size 1. Empty axes removes all size-1 dims.

fn unsqueeze( &self, a: &Self::Tensor, axes: &[i64], ) -> Result<Self::Tensor, Self::Error>

Insert dimensions of size 1 at the given axes.

fn identity(&self, a: &Self::Tensor) -> Result<Self::Tensor, Self::Error>

Identity / clone — pass-through useful for graph rewrites.

fn cast( &self, a: &Self::Tensor, dtype: i32, ) -> Result<Self::Tensor, Self::Error>

Cast to the given ONNX DataType enum value (matches bb_ir::proto::onnx::tensor_proto::DataType).

fn equal( &self, a: &Self::Tensor, b: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Element-wise a == b. Result is boolean-typed.

fn greater( &self, a: &Self::Tensor, b: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Element-wise a > b. Result is boolean-typed.

fn less( &self, a: &Self::Tensor, b: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Element-wise a < b. Result is boolean-typed.

fn where( &self, cond: &Self::Tensor, t: &Self::Tensor, f: &Self::Tensor, ) -> Result<Self::Tensor, Self::Error>

Element-wise ternary: where cond { t } else { f }. Named r#where to dodge the reserved Rust keyword.

fn constant(&self, value: TensorProto) -> Result<Self::Tensor, Self::Error>

Materialize a constant from an ONNX TensorProto. The value attribute on the ONNX Constant op carries the data; rank, dtype, raw bytes all come from the proto.

fn gather( &self, data: &Self::Tensor, indices: &Self::Tensor, axis: i64, ) -> Result<Self::Tensor, Self::Error>

Gather slices of data along axis indexed by indices.

fn dispatch( &self, graph: &GraphProto, inputs: HashMap<String, Self::Tensor>, attrs: BackendAttrs<'_>, completion: CompletionHandle<HashMap<String, Self::Tensor>, Self::Error>, ) -> ContractResponse<HashMap<String, Self::Tensor>, Self::Error>

Dispatch a BackendSubgraph carrier — the engine-facing entry point for whole-subgraph execution.

impl BackendRuntime for CpuBackend

type Error = OpError

Backend-impl-specific error type.

fn extension_opsets(&self) -> Vec<AtomicOpsetDecl>

Additional opsets this backend supports beyond atomic_opset. Default empty - backends that ship pure ai.onnx v1 need not override.

fn materialize_from_wire( &self, type_hash: u64, bytes: Vec<u8>, ) -> Result<Box<dyn SlotValue>, BackendMaterializeError>

Engine-side bridge for Backend::materialize_from_wire. The derive forwards (type_hash, bytes) through the user’s Contract method and re-boxes the typed Self::Tensor into a [BackendTensorCarrier] wrapped in Box<dyn SlotValue> so the engine can install it in the slot table without knowing the backend’s concrete tensor type. Returns BackendMaterializeError on backend error; the engine surfaces this as crate::bus::WireReceiveErrorKind::BackendMaterializeFailed.

fn atomic_opset(&self) -> AtomicOpsetDecl

Atomic-op opset this impl owns at minimum - ai.onnx v1.

fn dispatch_atomic( &mut self, op_type: &str, _inputs: &[(&str, &dyn SlotValue)], _ctx: &mut RuntimeResourceRef<'_>, ) -> Result<DispatchResult, Self::Error>

Dispatch a single op or BackendSubgraph carrier. For primitive ops (Add, Mul, …) each arm builds a one-node GraphProto and calls Backend::execute. For the BackendSubgraph op_type, the embedded GraphProto body rides on the carrier NodeProto’s "body" attribute and the derive arm calls Backend::dispatch so user overrides (caching, async) reach the engine.

impl Clone for CpuBackend

fn clone(&self) -> CpuBackend

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl ConcreteComponent for CpuBackend

const TYPE_NAME: &'static str = "bytesandbrains::backends::cpu::CpuBackend"

Stable identifier. Convention: <crate>::<TypeName>.

const PACKAGE: ComponentPackage = ComponentPackage::Framework

Origin tag; defaults to Application.

type Config = ()

Per-deployment config. Use () for stateless concretes.

type Error = Infallible

Error from Self::new; use Infallible if construction can’t fail.

fn new(_config: &Self::Config) -> Result<Self, Self::Error>

Construct from &Self::Config. Install calls this once per slot.

fn serialize(&self) -> Vec<u8>

Serialize state to bytes, including config-derived fields.

fn restore(bytes: &[u8]) -> Result<Self, RestoreError>

Reconstruct from serialize output.

const DEPENDENCIES: &'static [DependencyDecl] = _

Sibling components this depends on. Populated by the bb::Concrete derive from #[bb::depends(...)].

impl Debug for CpuBackend

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

Formats the value using the given formatter.

impl Default for CpuBackend

fn default() -> CpuBackend

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for CpuBackend

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for CpuBackend

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

where __S: Serializer,

Serialize this value into the given Serde serializer.