ggml_get_rows: Get Rows by Indices (Graph)

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Get Rows by Indices (Graph)

Description

Creates a graph node that extracts rows from a tensor by index. This is commonly used for embedding lookup in LLMs.

Usage

ggml_get_rows(ctx, a, b)

Arguments

ctx	GGML context
a	Data tensor of shape [n_embd, n_rows, ...] - the embedding table
b	Index tensor (int32) of shape [n_indices] - which rows to extract

Details

This operation is fundamental for embedding lookup in transformers: given a vocabulary embedding matrix and token indices, it retrieves the corresponding embedding vectors.

Value

Tensor of shape [n_embd, n_indices, ...] containing the selected rows

Examples

ctx <- ggml_init(16 * 1024 * 1024)
# Create embedding matrix: 10 tokens, 4-dim embeddings
embeddings <- ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 4, 10)
ggml_set_f32(embeddings, rnorm(40))
# Token indices to look up
indices <- ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 3)
ggml_set_i32(indices, c(0L, 5L, 2L))
# Get embeddings for tokens 0, 5, 2
result <- ggml_get_rows(ctx, embeddings, indices)
graph <- ggml_build_forward_expand(ctx, result)
ggml_graph_compute(ctx, graph)
ggml_free(ctx)

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