Function test_epoch_vs_fit

smallthinker/tests/test-opt.cpp:434–474

}

static std::pair<int, int> test_epoch_vs_fit(ggml_backend_sched_t backend_sched, ggml_backend_t backend) {
    int ntest = 0;
    int npass = 0;

    float weights_epoch;
    float weights_fit;

    {
        struct helper_ctx_data cd = helper_get_ctx_data(backend_sched, backend, /*init_opt_ctx =*/ true);
        ggml_opt_dataset_t dataset = cd.dataset_unsupervised;

        ggml_opt_dataset_shuffle(cd.opt_ctx, dataset, -1);
        ggml_opt_epoch(cd.opt_ctx, dataset, cd.result, nullptr, ndata, nullptr, nullptr);

        ggml_backend_tensor_get(cd.weights, &weights_epoch, 0, ggml_nbytes(cd.weights));
        helper_free_ctx_data(cd);
    }
    {
        struct helper_ctx_data cd = helper_get_ctx_data(backend_sched, backend, /*init_opt_ctx =*/ false);
        ggml_opt_dataset_t dataset = cd.dataset_unsupervised;

        ggml_opt_fit(backend_sched, cd.ctx_compute, cd.inputs, cd.outputs, dataset,
            GGML_OPT_LOSS_TYPE_SUM, ggml_opt_get_default_optimizer_params, 1, 1, 0.0f, true);

        ggml_backend_tensor_get(cd.weights, &weights_fit, 0, ggml_nbytes(cd.weights));
        helper_free_ctx_data(cd);
    }

    const bool subtest_ok = weights_epoch == weights_fit;

    printf("  %s(): ", __func__);
    if (subtest_ok) {
        printf("\033[1;32mOK\033[0m\n");
        npass++;
    } else {
        printf("\033[1;31mFAIL\033[0m\n");
    }
    ntest++;

    return std::make_pair(npass, ntest);
}

static void helper_after_test_idata_split(
        const char * func, const bool high_level, const int epoch,