Felipe97/llama-cpp-compiled

1#include "common.h"2#include "llama.h"3#include "ggml.h"4 5#include <string>6#include <vector>7#include <math.h>8 9namespace mean {10 11static void run(12        const std::vector<struct ggml_tensor *> & v_input, // shape of v_input[0]: [n_embd, n_samples]13        const std::vector<struct ggml_tensor *> & v_output) {14    printf("%s: Running mean...\n", __func__);15    for (size_t il = 0; il < v_input.size(); ++il) {16        // prepare output vector17        struct ggml_tensor * ctrl_out = v_output[il];18        ggml_format_name(ctrl_out, "direction.%zu", il+1);19 20        // calculate mean vector21        struct ggml_tensor * t_layer = v_input[il];22        GGML_ASSERT(t_layer->ne[0] == ctrl_out->ne[0]); // == n_embd23        for (int ic = 0; ic < t_layer->ne[0]; ic++) {24            float f = 0.0;25            for (int ir = 0; ir < t_layer->ne[1]; ir++) {26                f += ggml_get_f32_nd(t_layer, ic, ir, 0, 0);27            }28            f /= t_layer->ne[1];29            ggml_set_f32_1d(ctrl_out, ic, f);30        }31 32        // normalize output vector33        float norm = 0.0;34        for (int i = 0; i < ggml_nelements(ctrl_out); i++) {35            float f = ggml_get_f32_1d(ctrl_out, i);36            norm += f*f;37        }38        norm = sqrt(norm);39        for (int i = 0; i < ggml_nelements(ctrl_out); i++) {40            float f = ggml_get_f32_1d(ctrl_out, i);41            ggml_set_f32_1d(ctrl_out, i, f / norm);42        }43 44        printf("%s: Done layer %d / %d\n", __func__, (int) il+1, (int) v_input.size());45    }46}47 48}49