ggml_hardsigmoid: Hard Sigmoid Activation (Graph)

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Hard Sigmoid Activation (Graph)

Description

Creates a graph node for Hard Sigmoid activation. HardSigmoid(x) = ReLU6(x + 3) / 6 = min(max(0, x + 3), 6) / 6. A computationally efficient approximation of the sigmoid function.

Usage

ggml_hardsigmoid(ctx, a)

Arguments

ctx	GGML context
a	Input tensor

Value

Tensor representing the Hard Sigmoid operation

Examples

ctx <- ggml_init(16 * 1024 * 1024)
a <- ggml_new_tensor_1d(ctx, GGML_TYPE_F32, 5)
ggml_set_f32(a, c(-4, -1, 0, 1, 4))
r <- ggml_hardsigmoid(ctx, a)
graph <- ggml_build_forward_expand(ctx, r)
ggml_graph_compute(ctx, graph)
result <- ggml_get_f32(r)  # [0, 0.333, 0.5, 0.667, 1]
ggml_free(ctx)

ggmlR documentation built on July 14, 2026, 1:08 a.m.