Struct BackendSlot 

pub struct BackendSlot;

Generic Backend slot. Carries the ai.onnx v1 DSL catalog (48 methods). Outputs are typed &TYPE_TENSOR_F32. The BackendSubgraph carrier is compiler-emitted, not a DSL method.

Implementations

impl BackendSlot

pub fn zeros(&self, g: &mut Graph, dims: Vec<i64>) -> Output

Zeros(dims) - zero-initialized tensor of given shape.

pub fn ones(&self, g: &mut Graph, dims: Vec<i64>) -> Output

Ones(dims) - one-initialized tensor of given shape.

pub fn constant(&self, g: &mut Graph, value: TensorProto) -> Output

Constant(value) - embedded literal tensor.

pub fn add(&self, g: &mut Graph, a: Output, b: Output) -> Output

Add - element-wise a + b.

pub fn sub(&self, g: &mut Graph, a: Output, b: Output) -> Output

Sub - element-wise a - b.

pub fn mul(&self, g: &mut Graph, a: Output, b: Output) -> Output

Mul - element-wise a * b.

pub fn div(&self, g: &mut Graph, a: Output, b: Output) -> Output

Div - element-wise a / b.

pub fn neg(&self, g: &mut Graph, t: Output) -> Output

Neg - element-wise negation.

pub fn abs(&self, g: &mut Graph, t: Output) -> Output

Abs - element-wise absolute value.

pub fn sqrt(&self, g: &mut Graph, t: Output) -> Output

Sqrt - element-wise square root.

pub fn exp(&self, g: &mut Graph, t: Output) -> Output

Exp - element-wise natural exponential.

pub fn log(&self, g: &mut Graph, t: Output) -> Output

Log - element-wise natural logarithm.

pub fn pow(&self, g: &mut Graph, a: Output, b: Output) -> Output

Pow - element-wise a ** b.

pub fn matmul(&self, g: &mut Graph, a: Output, b: Output) -> Output

MatMul - matrix multiplication (canonical example).

pub fn gemm( &self, g: &mut Graph, a: Output, b: Output, c: Option<Output>, alpha: f32, beta: f32, trans_a: bool, trans_b: bool, ) -> Output

Gemm - alpha * (a @ b) + beta * c with optional transpose.

pub fn dot(&self, g: &mut Graph, a: Output, b: Output) -> Output

Dot - dot product (reduces along last axis for higher rank).

pub fn relu(&self, g: &mut Graph, t: Output) -> Output

Relu - max(0, x).

pub fn sigmoid(&self, g: &mut Graph, t: Output) -> Output

Sigmoid - 1 / (1 + exp(-x)).

pub fn tanh(&self, g: &mut Graph, t: Output) -> Output

Tanh - hyperbolic tangent.

pub fn softmax(&self, g: &mut Graph, t: Output, axis: i64) -> Output

Softmax(axis) - softmax along the given axis.

pub fn leaky_relu(&self, g: &mut Graph, t: Output, alpha: f32) -> Output

LeakyRelu(alpha) - x if x > 0 else alpha * x.

pub fn gelu(&self, g: &mut Graph, t: Output) -> Output

Gelu - Gaussian Error Linear Unit.

pub fn reshape(&self, g: &mut Graph, t: Output, dims: Vec<i64>) -> Output

Reshape(dims) - reshape to given dims.

pub fn transpose( &self, g: &mut Graph, t: Output, perm: Option<Vec<i64>>, ) -> Output

Transpose(perm) - None reverses all dims.

pub fn concat(&self, g: &mut Graph, tensors: Vec<Output>, axis: i64) -> Output

Concat(axis) - concatenate tensors along axis.

pub fn split( &self, g: &mut Graph, t: Output, axis: i64, sizes: Vec<i64>, ) -> Vec<Output>

Split(axis, sizes) - split into N parts. Returns one Output per size.

pub fn slice( &self, g: &mut Graph, t: Output, starts: Vec<i64>, ends: Vec<i64>, axes: Option<Vec<i64>>, steps: Option<Vec<i64>>, ) -> Output

Slice(starts, ends, axes?, steps?) - NumPy-style slice.

pub fn squeeze( &self, g: &mut Graph, t: Output, axes: Option<Vec<i64>>, ) -> Output

Squeeze(axes?) - remove length-1 dimensions.

pub fn unsqueeze(&self, g: &mut Graph, t: Output, axes: Vec<i64>) -> Output

Unsqueeze(axes) - insert length-1 dimensions.

pub fn identity(&self, g: &mut Graph, t: Output) -> Output

Identity - clone pass-through.

pub fn cast(&self, g: &mut Graph, t: Output, to_elem_type: i32) -> Output

Cast(to) - cast to the given ONNX DataType enum value.

pub fn reduce_sum( &self, g: &mut Graph, t: Output, axes: Option<Vec<i64>>, keepdims: bool, ) -> Output

ReduceSum(axes?, keepdims).

pub fn reduce_mean( &self, g: &mut Graph, t: Output, axes: Option<Vec<i64>>, keepdims: bool, ) -> Output

ReduceMean(axes?, keepdims).

pub fn reduce_max( &self, g: &mut Graph, t: Output, axes: Option<Vec<i64>>, keepdims: bool, ) -> Output

ReduceMax(axes?, keepdims).

pub fn reduce_min( &self, g: &mut Graph, t: Output, axes: Option<Vec<i64>>, keepdims: bool, ) -> Output

ReduceMin(axes?, keepdims).

pub fn equal(&self, g: &mut Graph, a: Output, b: Output) -> Output

Equal - element-wise a == b (bool tensor).

pub fn greater(&self, g: &mut Graph, a: Output, b: Output) -> Output

Greater - element-wise a > b (bool tensor).

pub fn less(&self, g: &mut Graph, a: Output, b: Output) -> Output

Less - element-wise a < b (bool tensor).

pub fn batch_normalization( &self, g: &mut Graph, input: Output, scale: Output, bias: Output, mean: Output, variance: Output, epsilon: f32, momentum: f32, ) -> Output

BatchNormalization(epsilon, momentum).

pub fn layer_normalization( &self, g: &mut Graph, input: Output, scale: Output, bias: Option<Output>, axis: i64, epsilon: f32, ) -> Output

LayerNormalization(axis, epsilon).

pub fn conv( &self, g: &mut Graph, input: Output, weight: Output, bias: Option<Output>, kernel_shape: Vec<i64>, strides: Vec<i64>, pads: Vec<i64>, dilations: Vec<i64>, group: i64, ) -> Output

Conv(kernel_shape, strides, pads, dilations, group).

pub fn max_pool( &self, g: &mut Graph, input: Output, kernel_shape: Vec<i64>, strides: Vec<i64>, pads: Vec<i64>, ) -> Output

MaxPool(kernel_shape, strides, pads).

pub fn average_pool( &self, g: &mut Graph, input: Output, kernel_shape: Vec<i64>, strides: Vec<i64>, pads: Vec<i64>, count_include_pad: bool, ) -> Output

AveragePool(kernel_shape, strides, pads, count_include_pad).

pub fn global_average_pool(&self, g: &mut Graph, input: Output) -> Output

GlobalAveragePool - collapse spatial dims to length 1.

pub fn gather( &self, g: &mut Graph, data: Output, indices: Output, axis: i64, ) -> Output

Gather(axis).

pub fn scatter( &self, g: &mut Graph, data: Output, indices: Output, updates: Output, axis: i64, ) -> Output

Scatter(axis).

pub fn if_op( &self, g: &mut Graph, cond: Output, then_branch: GraphProto, else_branch: GraphProto, n_outputs: usize, ) -> Vec<Output>

If(then_branch, else_branch) - both branches are sub-graphs carried on AttributeProto.g per IR_AND_DSL.md Part 2 line 80. Returns one Output per branch output.

pub fn loop_op( &self, g: &mut Graph, max_trip_count: Option<Output>, cond: Option<Output>, body: GraphProto, initial: Vec<Output>, n_outputs: usize, ) -> Vec<Output>

Loop(body) - execute body until cond becomes false or max_trip_count is reached.

Trait Implementations

impl Clone for BackendSlot

fn clone(&self) -> BackendSlot

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Copy for BackendSlot

impl Debug for BackendSlot

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

Formats the value using the given formatter.

impl Default for BackendSlot

fn default() -> BackendSlot

Returns the “default value” for a type.