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-rw-r--r--ggml.h89
1 files changed, 50 insertions, 39 deletions
diff --git a/ggml.h b/ggml.h
index 26654fc8..0118c99d 100644
--- a/ggml.h
+++ b/ggml.h
@@ -58,7 +58,8 @@
// {
// ...
//
-// struct ggml_cgraph gf = ggml_build_forward(f);
+// struct ggml_cgraph * gf = ggml_new_graph(ctx);
+// ggml_build_forward_expand(gf, f);
//
// // set the input variable and parameter values
// ggml_set_f32(x, 2.0f);
@@ -213,15 +214,14 @@
#define GGML_QNT_VERSION 2 // bump this on quantization format changes
#define GGML_QNT_VERSION_FACTOR 1000 // do not change this
-#define GGML_MAX_DIMS 4
-#define GGML_MAX_NODES 16384
-#define GGML_MAX_PARAMS 1024
-#define GGML_MAX_CONTEXTS 64
-#define GGML_MAX_SRC 6
-#define GGML_MAX_NAME 64
-#define GGML_MAX_OP_PARAMS 64
-#define GGML_DEFAULT_N_THREADS 4
-
+#define GGML_MAX_DIMS 4
+#define GGML_MAX_PARAMS 1024
+#define GGML_MAX_CONTEXTS 64
+#define GGML_MAX_SRC 6
+#define GGML_MAX_NAME 64
+#define GGML_MAX_OP_PARAMS 64
+#define GGML_DEFAULT_N_THREADS 4
+#define GGML_DEFAULT_GRAPH_SIZE 2048
#if UINTPTR_MAX == 0xFFFFFFFF
#define GGML_MEM_ALIGN 4
#else
@@ -245,7 +245,10 @@
do { \
if (!(x)) { \
fprintf(stderr, "GGML_ASSERT: %s:%d: %s\n", __FILE__, __LINE__, #x); \
- abort(); \
+ fflush(stderr); \
+ fflush(stdout); \
+ ggml_print_backtrace(); \
+ exit(1); \
} \
} while (0)
@@ -451,6 +454,7 @@ extern "C" {
GGML_UNARY_OP_GELU,
GGML_UNARY_OP_GELU_QUICK,
GGML_UNARY_OP_SILU,
+ GGML_UNARY_OP_LEAKY
};
enum ggml_object_type {
@@ -531,37 +535,33 @@ extern "C" {
int n_threads;
- // the `n_tasks` of nodes, 1:1 mapping to cgraph nodes
- int n_tasks[GGML_MAX_NODES];
-
// abort ggml_graph_compute when true
bool (*abort_callback)(void * data);
void * abort_callback_data;
};
- // next prime after GGML_MAX_NODES
- // #define GGML_GRAPH_HASHTABLE_SIZE 4099
- // next prime after GGML_MAX_NODES * 2 (nodes + leafs)
- // #define GGML_GRAPH_HASHTABLE_SIZE 8273
- // #define GGML_GRAPH_HASHTABLE_SIZE 16411
- #define GGML_GRAPH_HASHTABLE_SIZE 32771
-
enum ggml_cgraph_eval_order {
GGML_CGRAPH_EVAL_ORDER_LEFT_TO_RIGHT = 0,
GGML_CGRAPH_EVAL_ORDER_RIGHT_TO_LEFT,
GGML_CGRAPH_EVAL_ORDER_COUNT
};
+ struct ggml_hash_set {
+ size_t size;
+ struct ggml_tensor ** keys;
+ };
+
// computation graph
struct ggml_cgraph {
+ int size;
int n_nodes;
int n_leafs;
- struct ggml_tensor * nodes[GGML_MAX_NODES];
- struct ggml_tensor * grads[GGML_MAX_NODES];
- struct ggml_tensor * leafs[GGML_MAX_NODES];
+ struct ggml_tensor ** nodes;
+ struct ggml_tensor ** grads;
+ struct ggml_tensor ** leafs;
- void * visited_hash_table[GGML_GRAPH_HASHTABLE_SIZE];
+ struct ggml_hash_set visited_hash_table;
enum ggml_cgraph_eval_order order;
@@ -571,8 +571,6 @@ extern "C" {
int64_t perf_time_us;
};
- static const size_t GGML_GRAPH_SIZE = sizeof(struct ggml_cgraph);
-
// scratch buffer
struct ggml_scratch {
size_t offs;
@@ -617,6 +615,8 @@ extern "C" {
GGML_API int64_t ggml_cycles(void);
GGML_API int64_t ggml_cycles_per_ms(void);
+ GGML_API void ggml_print_backtrace(void);
+
GGML_API void ggml_numa_init(void); // call once for better performance on NUMA systems
GGML_API bool ggml_is_numa(void); // true if init detected that system has >1 NUMA node
@@ -709,7 +709,7 @@ extern "C" {
// Context tensor enumeration and lookup
GGML_API struct ggml_tensor * ggml_get_first_tensor(struct ggml_context * ctx);
GGML_API struct ggml_tensor * ggml_get_next_tensor (struct ggml_context * ctx, struct ggml_tensor * tensor);
- GGML_API struct ggml_tensor * ggml_get_tensor (struct ggml_context * ctx, const char * name);
+ GGML_API struct ggml_tensor * ggml_get_tensor(struct ggml_context * ctx, const char * name);
GGML_API struct ggml_tensor * ggml_set_zero(struct ggml_tensor * tensor);
GGML_API struct ggml_tensor * ggml_set_i32 (struct ggml_tensor * tensor, int32_t value);
@@ -943,6 +943,10 @@ extern "C" {
struct ggml_context * ctx,
struct ggml_tensor * a);
+ GGML_API struct ggml_tensor * ggml_leaky(
+ struct ggml_context * ctx,
+ struct ggml_tensor * a);
+
GGML_API struct ggml_tensor * ggml_relu_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a);
@@ -1482,6 +1486,8 @@ extern "C" {
int s0, // stride
int p0); // padding
+ // the result will have 2*p0 padding for the first dimension
+ // and 2*p1 padding for the second dimension
GGML_API struct ggml_tensor * ggml_pool_2d(
struct ggml_context * ctx,
struct ggml_tensor * a,
@@ -1490,8 +1496,8 @@ extern "C" {
int k1,
int s0,
int s1,
- int p0,
- int p1);
+ float p0,
+ float p1);
// nearest interpolate
// used in stable-diffusion
@@ -1732,19 +1738,22 @@ extern "C" {
GGML_API void ggml_build_forward_expand (struct ggml_cgraph * cgraph, struct ggml_tensor * tensor);
GGML_API void ggml_build_backward_expand(struct ggml_context * ctx, struct ggml_cgraph * gf, struct ggml_cgraph * gb, bool keep);
- GGML_API struct ggml_cgraph ggml_build_forward (struct ggml_tensor * tensor);
- GGML_API struct ggml_cgraph ggml_build_backward(struct ggml_context * ctx, struct ggml_cgraph * gf, bool keep);
-
// graph allocation in a context
- GGML_API struct ggml_cgraph * ggml_new_graph (struct ggml_context * ctx);
- GGML_API struct ggml_cgraph * ggml_build_forward_ctx(struct ggml_context * ctx, struct ggml_tensor * tensor);
+ GGML_API struct ggml_cgraph * ggml_new_graph (struct ggml_context * ctx); // size = GGML_DEFAULT_GRAPH_SIZE, grads = false
+ GGML_API struct ggml_cgraph * ggml_new_graph_custom (struct ggml_context * ctx, size_t size, bool grads);
+ GGML_API struct ggml_cgraph * ggml_graph_dup (struct ggml_context * ctx, struct ggml_cgraph * cgraph);
+ GGML_API struct ggml_cgraph * ggml_graph_view (struct ggml_context * ctx, struct ggml_cgraph * cgraph, int i0, int i1);
+ GGML_API void ggml_graph_cpy (struct ggml_cgraph * src, struct ggml_cgraph * dst);
+ GGML_API void ggml_graph_reset (struct ggml_cgraph * cgraph); // zero grads
+ GGML_API void ggml_graph_clear (struct ggml_cgraph * cgraph);
+
GGML_API size_t ggml_graph_overhead(void);
+ GGML_API size_t ggml_graph_overhead_custom(size_t size, bool grads);
// ggml_graph_plan() has to be called before ggml_graph_compute()
// when plan.work_size > 0, caller must allocate memory for plan.work_data
GGML_API struct ggml_cplan ggml_graph_plan (struct ggml_cgraph * cgraph, int n_threads /*= GGML_DEFAULT_N_THREADS*/);
- GGML_API int ggml_graph_compute(struct ggml_cgraph * cgraph, struct ggml_cplan * cplan);
- GGML_API void ggml_graph_reset (struct ggml_cgraph * cgraph);
+ GGML_API int ggml_graph_compute(struct ggml_cgraph * cgraph, struct ggml_cplan * cplan);
// same as ggml_graph_compute() but the work data is allocated as a part of the context
// note: the drawback of this API is that you must have ensured that the context has enough memory for the work data
@@ -1752,8 +1761,8 @@ extern "C" {
GGML_API struct ggml_tensor * ggml_graph_get_tensor(struct ggml_cgraph * cgraph, const char * name);
- GGML_API void ggml_graph_export(const struct ggml_cgraph * cgraph, const char * fname);
- GGML_API struct ggml_cgraph ggml_graph_import(const char * fname, struct ggml_context ** ctx_data, struct ggml_context ** ctx_eval);
+ GGML_API void ggml_graph_export(const struct ggml_cgraph * cgraph, const char * fname);
+ GGML_API struct ggml_cgraph * ggml_graph_import(const char * fname, struct ggml_context ** ctx_data, struct ggml_context ** ctx_eval);
// print info and performance information for the graph
GGML_API void ggml_graph_print(const struct ggml_cgraph * cgraph);
@@ -1816,6 +1825,8 @@ extern "C" {
struct ggml_opt_params {
enum ggml_opt_type type;
+ size_t graph_size;
+
int n_threads;
// delta-based convergence test
generated by cgit v1.2.3 (git 2.25.1) at 2025-08-16 09:49:01 +0000