ggml_upscale: Upscale Tensor (Graph)

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Upscale Tensor (Graph)

Description

Upscales tensor by multiplying ne0 and ne1 by scale factor. Supports different interpolation modes for image upscaling.

Usage

ggml_upscale(ctx, a, scale_factor, mode = 0L)

GGML_SCALE_MODE_NEAREST

GGML_SCALE_MODE_BILINEAR

GGML_SCALE_MODE_BICUBIC

Arguments

ctx	GGML context
a	Input tensor (typically 2D or 4D for images)
scale_factor	Integer scale factor (e.g., 2 = double size)
mode	Scale mode constant (see details)

Format

An object of class integer of length 1.

An object of class integer of length 1.

An object of class integer of length 1.

Details

Scale mode constants:

• GGML_SCALE_MODE_NEAREST (0): Nearest neighbor interpolation - fastest, pixelated

• GGML_SCALE_MODE_BILINEAR (1): Bilinear interpolation - smooth, good balance

• GGML_SCALE_MODE_BICUBIC (2): Bicubic interpolation - smoothest, most compute

Value

Upscaled tensor with dimensions multiplied by scale_factor

Examples

ctx <- ggml_init(16 * 1024 * 1024)
img <- ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 8, 8)
ggml_set_f32(img, rnorm(64))

# Nearest neighbor (fastest, pixelated)
up_nearest <- ggml_upscale(ctx, img, 2, GGML_SCALE_MODE_NEAREST)

# Bilinear (smooth)
up_bilinear <- ggml_upscale(ctx, img, 2, GGML_SCALE_MODE_BILINEAR)

# Bicubic (smoothest)
up_bicubic <- ggml_upscale(ctx, img, 2, GGML_SCALE_MODE_BICUBIC)

graph <- ggml_build_forward_expand(ctx, up_nearest)
ggml_graph_compute(ctx, graph)
# Result is 16x16
ggml_free(ctx)

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