Function check_gradient

tests/test-grad0.cpp:211–293

}

static bool check_gradient(
        const char * op_name,
        struct ggml_context * ctx0,
        struct ggml_tensor * x[],
        struct ggml_tensor * f,
        int ndims,
        int nargs,
        float eps,
        float max_error_abs,
        float max_error_rel) {

    static int n_threads = -1;
    if (n_threads < 0) {
        n_threads = GGML_DEFAULT_N_THREADS;

        const char *env = getenv("GGML_N_THREADS");
        if (env) {
            n_threads = atoi(env);
        }

        printf("GGML_N_THREADS = %d\n", n_threads);
    }

    struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, GGML_DEFAULT_GRAPH_SIZE, true);
    struct ggml_cgraph * gb = ggml_new_graph_custom(ctx0, GGML_DEFAULT_GRAPH_SIZE, true);
    ggml_build_forward_expand(gf, f);
    ggml_graph_cpy(gf, gb);
    ggml_build_backward_expand(ctx0, gf, gb, false);

    ggml_graph_compute_with_ctx(ctx0, gf, n_threads);

    ggml_graph_reset  (gf);
    ggml_set_f32      (f->grad, 1.0f);

    ggml_graph_compute_with_ctx(ctx0, gb, n_threads);

    // ggml_graph_dump_dot(gf, NULL, "test-grad0-forward.dot");
    // ggml_graph_dump_dot(gb, gf,  "test-grad0-backward.dot");

    for (int i = 0; i < nargs; ++i) {
        const int nelements = ggml_nelements(x[i]);
        for (int k = 0; k < nelements; ++k) {
            // compute gradient using finite differences
            const float x0 = ggml_get_f32_1d(x[i], k);
            const float xm = x0 - eps;
            const float xp = x0 + eps;
            ggml_set_f32_1d(x[i], k, xp);

            ggml_graph_compute_with_ctx(ctx0, gf, n_threads);

            const double f0 = ggml_get_f32_1d(f, 0);

            ggml_set_f32_1d(x[i], k, xm);

            ggml_graph_compute_with_ctx(ctx0, gf, n_threads);

            const double f1 = ggml_get_f32_1d(f, 0);
            const double g0 = (f0 - f1)/(2.0*(double) eps);