vbatts/llama.cpp
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c++ in baby-llama example

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use c++ includes instead of c includes
use std::min, std::max instead of MIN, MAX macros
This commit is contained in:
xaedes 2023-05-08 16:56:41 +02:00
parent dea9c9359a
commit 0d72207ac3
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1 changed files with 9 additions and 14 deletions
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23
examples/baby-llama/baby-llama.cpp
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@ -1,13 +1,8 @@
#include "ggml.h"
#include <vector>
#include <assert.h>
#include <cassert>
#include <random>
#include <string.h>
#undef MIN
#undef MAX
#define MIN(a, b) ((a) < (b) ? (a) : (b))
#define MAX(a, b) ((a) > (b) ? (a) : (b))
#include <cstring>
float frand() {
return (float)rand()/(float)RAND_MAX;
@ -1068,7 +1063,7 @@ void get_example_targets(int example_id, struct ggml_tensor * tokens_input, stru
float z = (y+1.0f)*0.5f; // scale to [0..1]
z += (frand()-0.5f)*(randomness/n_vocab);
z = (z < 0.0f) ? 0.0f : (z > 1.0f) ? 1.0f : z; // clamp to [0..1]
int token = MAX(1,MIN(1+(int)(z*(float)(n_vocab-1)), n_vocab-1));
int token = std::max(1,std::min(1+(int)(z*(float)(n_vocab-1)), n_vocab-1));
ggml_set_f32_1d(targets, (i-1)*n_vocab + token, +1.0f);
if (i<n_tokens) {
ggml_set_i32_1d(tokens_input, i, token);
@ -1119,7 +1114,7 @@ int main(int argc, char ** argv) {
model.hparams.n_mult = 2;
model.hparams.n_head = 8;
model.hparams.n_layer = 1;
model.hparams.n_rot = MIN(16, model.hparams.n_embd / model.hparams.n_head);
model.hparams.n_rot = std::min(16u, model.hparams.n_embd / model.hparams.n_head);
// model.hparams.n_embd = 32;
// model.hparams.n_mult = 2;
@ -1225,12 +1220,12 @@ int main(int argc, char ** argv) {
// struct ggml_tensor * e = cross_entropy_loss(ctx0, targets1, logits1);
// struct ggml_tensor * e = square_error_loss(ctx0, targets1, logits1);
// struct ggml_tensor * e = ggml_add(ctx0,
// square_error_loss(ctx0, targets1, logits1),
// square_error_loss(ctx0, targets2, logits2));
struct ggml_tensor * e = ggml_add(ctx0,
cross_entropy_loss(ctx0, targets1, logits1),
cross_entropy_loss(ctx0, targets2, logits2));
square_error_loss(ctx0, targets1, logits1),
square_error_loss(ctx0, targets2, logits2));
// struct ggml_tensor * e = ggml_add(ctx0,
// cross_entropy_loss(ctx0, targets1, logits1),
// cross_entropy_loss(ctx0, targets2, logits2));
// struct ggml_tensor * e = ggml_add(ctx0,
// ggml_add(ctx0,
// cross_entropy_loss(ctx0, targets1, logits1),