vbatts/llama.cpp
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simple : restore examples, imatrix will serve as a demo

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Georgi Gerganov 2024-01-17 15:24:18 +02:00
parent 012ecec506
commit 200dcaf799
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GPG key ID: BF970631944C16B7
2 changed files with 2 additions and 51 deletions
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49
examples/simple/simple.cpp
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@ -6,49 +6,11 @@
#include <string>
#include <vector>
// a function that can be called for every computed node during graph evaluation
// the user can choose to whether to observe the data of the node depending on the tensor parameters
static bool observe_compute(struct ggml_tensor * t, bool ask, void * user_data) {
GGML_UNUSED(user_data);
// the scheduler is asking us if we want to observe this node
if (ask) {
// check if name contains soft_max (customize to your needs)
return strstr(t->name, "soft_max") != 0;
}
// print the node info
printf("%s: t->name = %32s, t->op = %12s, [%5d, %5d, %5d, %5d]\n",
__func__, t->name, ggml_op_name(t->op), (int) t->ne[0], (int) t->ne[1], (int) t->ne[2], (int) t->ne[3]);
// this will copy the data to host memory (if needed)
static std::vector<float> t_data;
const bool is_host = ggml_backend_buffer_is_host(t->buffer);
if (!is_host) {
t_data.resize(ggml_nelements(t));
ggml_backend_tensor_get(t, t_data.data(), 0, ggml_nbytes(t));
}
const float * data = is_host ? (const float *) t->data : t_data.data();
// print first row
for (int i = 0; i < t->ne[0]; i++) {
printf("%8.4f ", data[i]);
}
printf("\n");
return true;
}
int main(int argc, char ** argv) {
gpt_params params;
bool observe = false;
if (argc == 1 || argv[1][0] == '-') {
printf("usage: %s MODEL_PATH [PROMPT] [OBSERV]\n" , argv[0]);
printf("usage: %s MODEL_PATH [PROMPT]\n" , argv[0]);
return 1 ;
}
@ -60,10 +22,6 @@ int main(int argc, char ** argv) {
params.prompt = argv[2];
}
if (argc >= 4) {
observe = !!atoi(argv[3]);
}
if (params.prompt.empty()) {
params.prompt = "Hello my name is";
}
@ -79,7 +37,7 @@ int main(int argc, char ** argv) {
llama_model_params model_params = llama_model_default_params();
model_params.n_gpu_layers = 99; // offload all layers to the GPU
// model_params.n_gpu_layers = 99; // offload all layers to the GPU
llama_model * model = llama_load_model_from_file(params.model.c_str(), model_params);
@ -97,9 +55,6 @@ int main(int argc, char ** argv) {
ctx_params.n_threads = params.n_threads;
ctx_params.n_threads_batch = params.n_threads_batch == -1 ? params.n_threads : params.n_threads_batch;
ctx_params.cb_eval = observe ? observe_compute : NULL;
ctx_params.cb_eval_user_data = NULL;
llama_context * ctx = llama_new_context_with_model(model, ctx_params);
if (ctx == NULL) {

4
ggml-backend.c
View file

@ -1384,10 +1384,6 @@ static void sched_reset(ggml_backend_sched_t sched) {
memset(sched->node_talloc, 0, sizeof(sched->node_talloc[0]) * hash_size);
memset(sched->node_copies, 0, sizeof(sched->node_copies[0]) * hash_size);
// TODO: should we clear the callbacks?
//sched->callback_eval = NULL;
//sched->callback_eval_user_data = NULL;
sched->is_reset = true;
}