vbatts/llama.cpp
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sync : ggml (#5452)

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* ggml-alloc : v3 (ggml/727)

* ggml-alloc v3

ggml-ci

* fix ci

ggml-ci

* whisper : check for backend buffer allocation failures

* whisper : avoid leaks when initialization fails

* cleanup

ggml-ci

* style fixes

ggml-ci

* sync : ggml

* update llama.cpp, clip.cpp, export-lora.cpp

* update finetune.cpp, train-text-from-scratch.cpp

ggml-ci

* ggml-backend : reduce alignment to 32 to match gguf and fix mmap

---------

Co-authored-by: slaren <slarengh@gmail.com>
This commit is contained in:
Georgi Gerganov 2024-02-12 09:16:06 +02:00 • committed by GitHub
parent 3bdc4cd0f5
commit 3b169441df
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GPG key ID: B5690EEEBB952194
12 changed files with 1287 additions and 1362 deletions
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28
ggml.c
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@ -2649,7 +2649,7 @@ static struct ggml_tensor * ggml_new_tensor_impl(
/*.nb =*/ { 0, 0, 0, 0 },
/*.op =*/ GGML_OP_NONE,
/*.op_params =*/ { 0 },
/*.is_param =*/ false,
/*.flags =*/ 0,
/*.grad =*/ NULL,
/*.src =*/ { NULL },
/*.perf_runs =*/ 0,
@ -6551,7 +6551,7 @@ struct ggml_tensor * ggml_cross_entropy_loss_back(
void ggml_set_param(
struct ggml_context * ctx,
struct ggml_tensor * tensor) {
tensor->is_param = true;
tensor->flags |= GGML_TENSOR_FLAG_PARAM;
GGML_ASSERT(tensor->grad == NULL);
tensor->grad = ggml_dup_tensor(ctx, tensor);
@ -15367,7 +15367,7 @@ static struct ggml_tensor * ggml_recompute_graph_node(
return NULL;
}
if (node->is_param) {
if (node->flags & GGML_TENSOR_FLAG_PARAM) {
return node;
}
@ -15401,7 +15401,7 @@ static struct ggml_tensor * ggml_recompute_graph_node(
clone->op = node->op;
clone->grad = node->grad;
clone->is_param = node->is_param;
clone->flags = node->flags;
clone->extra = node->extra;
for (int k = 0; k < GGML_MAX_DIMS; ++k) {
clone->nb[k] = node->nb[k];
@ -16433,7 +16433,7 @@ void ggml_build_backward_expand(struct ggml_context * ctx, struct ggml_cgraph *
for (int i = 0; i < gf->n_nodes; i++) {
struct ggml_tensor * node = gf->nodes[i];
if (node->is_param) {
if (node->flags & GGML_TENSOR_FLAG_PARAM) {
GGML_PRINT_DEBUG("%s: found root node %p\n", __func__, (void *) node);
ggml_build_forward_expand(gb, node->grad);
}
@ -17918,7 +17918,7 @@ void ggml_graph_print(const struct ggml_cgraph * cgraph) {
GGML_PRINT(" - %3d: [ %5" PRId64 ", %5" PRId64 ", %5" PRId64 "] %16s %s (%3d) cpu = %7.3f / %7.3f ms, wall = %7.3f / %7.3f ms\n",
i,
node->ne[0], node->ne[1], node->ne[2],
ggml_op_name(node->op), node->is_param ? "x" : node->grad ? "g" : " ", node->perf_runs,
ggml_op_name(node->op), (node->flags & GGML_TENSOR_FLAG_PARAM) ? "x" : node->grad ? "g" : " ", node->perf_runs,
(double) node->perf_cycles / (double) ggml_cycles_per_ms(),
(double) node->perf_cycles / (double) ggml_cycles_per_ms() / (double) node->perf_runs,
(double) node->perf_time_us / 1000.0,
@ -18011,7 +18011,7 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph
continue;
}
if (node->is_param) {
if (node->flags & GGML_TENSOR_FLAG_PARAM) {
snprintf(color, sizeof(color), "yellow");
} else if (node->grad) {
if (ggml_graph_find(gf, node)) {
@ -18185,7 +18185,7 @@ static enum ggml_opt_result ggml_opt_adam(
int np = 0;
int64_t nx = 0;
for (int i = 0; i < gf->n_nodes; ++i) {
if (gf->nodes[i]->is_param) {
if (gf->nodes[i]->flags & GGML_TENSOR_FLAG_PARAM) {
GGML_PRINT_DEBUG("found param %d: grad->op = %d\n", np, gf->nodes[i]->grad->op);
GGML_ASSERT(np < GGML_MAX_PARAMS);
@ -18548,7 +18548,7 @@ static enum ggml_opt_result ggml_opt_lbfgs(
int np = 0;
int nx = 0;
for (int i = 0; i < gf->n_nodes; ++i) {
if (gf->nodes[i]->is_param) {
if (gf->nodes[i]->flags & GGML_TENSOR_FLAG_PARAM) {
GGML_PRINT_DEBUG("found param %d: grad->op = %d\n", np, gf->nodes[i]->grad->op);
GGML_ASSERT(np < GGML_MAX_PARAMS);
@ -19023,6 +19023,16 @@ enum ggml_opt_result ggml_opt_resume_g(
////////////////////////////////////////////////////////////////////////////////
void ggml_set_input(struct ggml_tensor * tensor) {
tensor->flags |= GGML_TENSOR_FLAG_INPUT;
}
void ggml_set_output(struct ggml_tensor * tensor) {
tensor->flags |= GGML_TENSOR_FLAG_OUTPUT;
}
////////////////////////////////////////////////////////////////////////////////
void ggml_quantize_init(enum ggml_type type) {
ggml_critical_section_start();