from ggml import lib, ffi
from ggml.utils import init, copy, numpy
import numpy as np
ctx = init(mem_size=12*1024*1024) n = 256
n_threads = 4
a = lib.ggml_new_tensor_1d(ctx, lib.GGML_TYPE_Q5_K, n)
b = lib.ggml_new_tensor_1d(ctx, lib.GGML_TYPE_F32, n) sum = lib.ggml_add(ctx, a, b)
gf = ffi.new('struct ggml_cgraph*')
lib.ggml_build_forward_expand(gf, sum)
copy(np.array([i for i in range(n)], np.float32), a)
copy(np.array([i*100 for i in range(n)], np.float32), b)
lib.ggml_graph_compute_with_ctx(ctx, gf, n_threads)
print(numpy(a, allow_copy=True))
print(numpy(b))
print(numpy(sum, allow_copy=True))