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ggml : address review comments on alloc_buffer_n

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- restore GGML_LOG_ERROR on buffer alloc / tensor init failure in the
  default impl (name the failing tensor)
- check the malloc result and drop the _impl indirection in
  ggml_backend_alloc_ctx_tensors_from_buft
- remove comments that restate the code
- fix the TAG_ALLOC_SHARED_BUFFER_SPLIT typo

Assisted-by: pi:llama.cpp/Qwen3.8-27B
This commit is contained in:
Georgi Gerganov
2026-09-24 16:47:39 +03:00
parent 046ed1fc6f
commit 999c58eeef
2 changed files with 13 additions and 15 deletions
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ggml/src/ggml-alloc.c
+5 -8
View File
@@ -1117,11 +1117,9 @@ size_t ggml_gallocr_get_buffer_size(ggml_gallocr_t galloc, int buffer_id) {
// utils
static ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors_from_buft_impl(
struct ggml_context * ctx, ggml_backend_buffer_type_t buft) {
ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors_from_buft(struct ggml_context * ctx, ggml_backend_buffer_type_t buft) {
GGML_ASSERT(ggml_get_no_alloc(ctx) == true);
// collect tensors into a list
int n_tensors = 0;
for (struct ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
n_tensors++;
@@ -1131,6 +1129,9 @@ static ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors_from_buft_impl(
}
struct ggml_tensor ** tensors = (struct ggml_tensor **) malloc(n_tensors * sizeof(struct ggml_tensor *));
if (tensors == NULL) {
return NULL;
}
int i = 0;
for (struct ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
tensors[i++] = t;
@@ -1141,11 +1142,7 @@ static ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors_from_buft_impl(
return buffer;
}
ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors_from_buft(struct ggml_context * ctx, ggml_backend_buffer_type_t buft) {
return ggml_backend_alloc_ctx_tensors_from_buft_impl(ctx, buft);
}
// TODO [TAG_ALLOC_SAHRED_BUFFER_SPLIT]: reuse shared buffer-splitting logic from ggml_backend_buft_alloc_buffer_n_default
// TODO [TAG_ALLOC_SHARED_BUFFER_SPLIT]: reuse shared buffer-splitting logic from ggml_backend_buft_alloc_buffer_n_default
size_t ggml_backend_alloc_ctx_tensors_from_buft_size(struct ggml_context * ctx, ggml_backend_buffer_type_t buft) {
GGML_ASSERT(ggml_get_no_alloc(ctx) == true);
ggml/src/ggml-backend.cpp
+8 -7
View File
@@ -45,7 +45,7 @@ ggml_backend_buffer_t ggml_backend_buft_alloc_buffer(ggml_backend_buffer_type_t
return buft->iface.alloc_buffer(buft, size);
}
// TODO [TAG_ALLOC_SAHRED_BUFFER_SPLIT]: extract shared buffer-splitting logic with ggml_backend_alloc_ctx_tensors_from_buft_size
// TODO [TAG_ALLOC_SHARED_BUFFER_SPLIT]: extract shared buffer-splitting logic with ggml_backend_alloc_ctx_tensors_from_buft_size
// default implementation of alloc_buffer_n
// allocates tensors from a list into one or more buffers of the given type
static ggml_backend_buffer_t ggml_backend_buft_alloc_buffer_n_default(ggml_backend_buffer_type_t buft, struct ggml_tensor ** tensors, int n_tensors) {
@@ -69,9 +69,9 @@ static ggml_backend_buffer_t ggml_backend_buft_alloc_buffer_n_default(ggml_backe
// flush the current buffer if adding this tensor would exceed max_size, or if we are at the end
bool should_flush = (i == n_tensors) || (cur_buf_size > 0 && (cur_buf_size + this_size) > max_size);
if (should_flush && cur_buf_size > 0) {
// allocate the buffer with the computed size for this range
ggml_backend_buffer_t buffer = ggml_backend_buft_alloc_buffer(buft, cur_buf_size);
if (buffer == NULL) {
GGML_LOG_ERROR("%s: failed to allocate %s buffer of size %zu\n", __func__, ggml_backend_buft_name(buft), cur_buf_size);
for (size_t b = 0; b < n_buffers; b++) {
ggml_backend_buffer_free(buffers[b]);
}
@@ -81,18 +81,18 @@ static ggml_backend_buffer_t ggml_backend_buft_alloc_buffer_n_default(ggml_backe
struct ggml_tallocr tallocr = ggml_tallocr_new(buffer);
// allocate tensors in the current buffer
bool ok = true;
struct ggml_tensor * t_failed = NULL;
for (int j = first; j < i; j++) {
struct ggml_tensor * t = tensors[j];
if (t->data == NULL) {
if (t->view_src == NULL) {
if (ggml_tallocr_alloc(&tallocr, t) != GGML_STATUS_SUCCESS) {
ok = false;
t_failed = t;
break;
}
} else if (t->buffer == NULL) {
if (ggml_backend_view_init(t) != GGML_STATUS_SUCCESS) {
ok = false;
t_failed = t;
break;
}
}
@@ -100,13 +100,14 @@ static ggml_backend_buffer_t ggml_backend_buft_alloc_buffer_n_default(ggml_backe
if (t->view_src != NULL && t->buffer == NULL) {
// view of a pre-allocated tensor
if (ggml_backend_view_init(t) != GGML_STATUS_SUCCESS) {
ok = false;
t_failed = t;
break;
}
}
}
}
if (!ok) {
if (t_failed != NULL) {
GGML_LOG_ERROR("%s: failed to initialize tensor %s\n", __func__, t_failed->name);
for (size_t b = 0; b < n_buffers; b++) {
ggml_backend_buffer_free(buffers[b]);
}