mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-24 02:14:35 +00:00
ggml : sync latest ggml (custom operators)
This commit is contained in:
Georgi Gerganov
parent
c2a08f87b8
commit
bd34cdde38
369
ggml.c
369
ggml.c
@ -1,5 +1,5 @@
|
||||
// Defines CLOCK_MONOTONIC on Linux
|
||||
#define _GNU_SOURCE
|
||||
#define _GNU_SOURCE // Defines CLOCK_MONOTONIC on Linux
|
||||
#define _CRT_SECURE_NO_DEPRECATE // Disables ridiculous "unsafe" warnigns on Windows
|
||||
|
||||
#include "ggml.h"
|
||||
|
||||
@ -131,6 +131,34 @@ typedef void* thread_ret_t;
|
||||
#define GGML_MEM_ALIGN 16
|
||||
#endif
|
||||
|
||||
//
|
||||
// logging
|
||||
//
|
||||
|
||||
#if (GGML_DEBUG >= 1)
|
||||
#define GGML_PRINT_DEBUG(...) printf(__VA_ARGS__)
|
||||
#else
|
||||
#define GGML_PRINT_DEBUG(...)
|
||||
#endif
|
||||
|
||||
#if (GGML_DEBUG >= 5)
|
||||
#define GGML_PRINT_DEBUG_5(...) printf(__VA_ARGS__)
|
||||
#else
|
||||
#define GGML_PRINT_DEBUG_5(...)
|
||||
#endif
|
||||
|
||||
#if (GGML_DEBUG >= 10)
|
||||
#define GGML_PRINT_DEBUG_10(...) printf(__VA_ARGS__)
|
||||
#else
|
||||
#define GGML_PRINT_DEBUG_10(...)
|
||||
#endif
|
||||
|
||||
#define GGML_PRINT(...) printf(__VA_ARGS__)
|
||||
|
||||
//
|
||||
// end of logging block
|
||||
//
|
||||
|
||||
#if defined(_MSC_VER) || defined(__MINGW32__)
|
||||
#define GGML_ALIGNED_MALLOC(size) _aligned_malloc(size, GGML_MEM_ALIGN)
|
||||
#define GGML_ALIGNED_FREE(ptr) _aligned_free(ptr)
|
||||
@ -144,6 +172,17 @@ inline static void* ggml_aligned_malloc(size_t size) {
|
||||
#endif
|
||||
if (result != 0) {
|
||||
// Handle allocation failure
|
||||
const char *error_desc = "unknown allocation error";
|
||||
switch (result) {
|
||||
case EINVAL:
|
||||
error_desc = "invalid alignment value";
|
||||
break;
|
||||
case ENOMEM:
|
||||
error_desc = "insufficient memory";
|
||||
break;
|
||||
}
|
||||
GGML_PRINT("%s: %s (attempted to allocate %6.2f MB)\n",
|
||||
__func__, error_desc, size/(1024.0*1024.0));
|
||||
return NULL;
|
||||
}
|
||||
return aligned_memory;
|
||||
@ -3530,30 +3569,6 @@ inline static void ggml_vec_norm_inv_f32(const int n, float * s, const float * x
|
||||
*s = 1.f/(*s);
|
||||
}
|
||||
|
||||
//
|
||||
// logging
|
||||
//
|
||||
|
||||
#if (GGML_DEBUG >= 1)
|
||||
#define GGML_PRINT_DEBUG(...) printf(__VA_ARGS__)
|
||||
#else
|
||||
#define GGML_PRINT_DEBUG(...)
|
||||
#endif
|
||||
|
||||
#if (GGML_DEBUG >= 5)
|
||||
#define GGML_PRINT_DEBUG_5(...) printf(__VA_ARGS__)
|
||||
#else
|
||||
#define GGML_PRINT_DEBUG_5(...)
|
||||
#endif
|
||||
|
||||
#if (GGML_DEBUG >= 10)
|
||||
#define GGML_PRINT_DEBUG_10(...) printf(__VA_ARGS__)
|
||||
#else
|
||||
#define GGML_PRINT_DEBUG_10(...)
|
||||
#endif
|
||||
|
||||
#define GGML_PRINT(...) printf(__VA_ARGS__)
|
||||
|
||||
//
|
||||
// data types
|
||||
//
|
||||
@ -3713,11 +3728,15 @@ static const char * GGML_OP_NAME[GGML_OP_COUNT] = {
|
||||
"MAP_UNARY",
|
||||
"MAP_BINARY",
|
||||
|
||||
"MAP_CUSTOM1",
|
||||
"MAP_CUSTOM2",
|
||||
"MAP_CUSTOM3",
|
||||
|
||||
"CROSS_ENTROPY_LOSS",
|
||||
"CROSS_ENTROPY_LOSS_BACK",
|
||||
};
|
||||
|
||||
static_assert(GGML_OP_COUNT == 61, "GGML_OP_COUNT != 61");
|
||||
static_assert(GGML_OP_COUNT == 64, "GGML_OP_COUNT != 64");
|
||||
|
||||
static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
|
||||
"none",
|
||||
@ -3785,11 +3804,15 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
|
||||
"f(x)",
|
||||
"f(x,y)",
|
||||
|
||||
"custom(x)",
|
||||
"custom(x,y)",
|
||||
"custom(x,y,z)",
|
||||
|
||||
"cross_entropy_loss(x,y)",
|
||||
"cross_entropy_loss_back(x,y)",
|
||||
};
|
||||
|
||||
static_assert(GGML_OP_COUNT == 61, "GGML_OP_COUNT != 61");
|
||||
static_assert(GGML_OP_COUNT == 64, "GGML_OP_COUNT != 64");
|
||||
|
||||
static_assert(sizeof(struct ggml_object)%GGML_MEM_ALIGN == 0, "ggml_object size must be a multiple of GGML_MEM_ALIGN");
|
||||
static_assert(sizeof(struct ggml_tensor)%GGML_MEM_ALIGN == 0, "ggml_tensor size must be a multiple of GGML_MEM_ALIGN");
|
||||
@ -7094,9 +7117,14 @@ struct ggml_tensor * ggml_map_unary_impl_f32(
|
||||
is_node = true;
|
||||
}
|
||||
|
||||
struct ggml_tensor *result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
|
||||
|
||||
ggml_scratch_save(ctx);
|
||||
|
||||
struct ggml_tensor * addr_tensor = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, sizeof(void *) / sizeof(int32_t));
|
||||
*((void (**)(void))addr_tensor->data) = (void (*)(void))fun;
|
||||
struct ggml_tensor *result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
|
||||
|
||||
ggml_scratch_load(ctx);
|
||||
|
||||
result->op = GGML_OP_MAP_UNARY;
|
||||
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
|
||||
@ -7136,9 +7164,14 @@ struct ggml_tensor * ggml_map_binary_impl_f32(
|
||||
is_node = true;
|
||||
}
|
||||
|
||||
struct ggml_tensor *result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
|
||||
|
||||
ggml_scratch_save(ctx);
|
||||
|
||||
struct ggml_tensor * addr_tensor = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, sizeof(void *) / sizeof(int32_t));
|
||||
*((void (**)(void))addr_tensor->data) = (void (*)(void))fun;
|
||||
struct ggml_tensor *result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
|
||||
|
||||
ggml_scratch_load(ctx);
|
||||
|
||||
result->op = GGML_OP_MAP_BINARY;
|
||||
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
|
||||
@ -7165,6 +7198,150 @@ struct ggml_tensor * ggml_map_binary_inplace_f32(
|
||||
return ggml_map_binary_impl_f32(ctx, a, b, fun, true);
|
||||
}
|
||||
|
||||
// ggml_map_custom1
|
||||
|
||||
struct ggml_tensor * ggml_map_custom1_impl_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
const ggml_custom1_op_f32_t fun,
|
||||
bool inplace) {
|
||||
bool is_node = false;
|
||||
|
||||
if (!inplace && a->grad) {
|
||||
is_node = true;
|
||||
}
|
||||
|
||||
struct ggml_tensor *result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
|
||||
|
||||
ggml_scratch_save(ctx);
|
||||
|
||||
struct ggml_tensor * addr_tensor = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, sizeof(void *) / sizeof(int32_t));
|
||||
*((void (**)(void))addr_tensor->data) = (void (*)(void))fun;
|
||||
|
||||
ggml_scratch_load(ctx);
|
||||
|
||||
result->op = GGML_OP_MAP_CUSTOM1;
|
||||
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
|
||||
result->src0 = a;
|
||||
result->opt[0] = addr_tensor;
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
struct ggml_tensor * ggml_map_custom1_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
const ggml_custom1_op_f32_t fun) {
|
||||
return ggml_map_custom1_impl_f32(ctx, a, fun, false);
|
||||
}
|
||||
|
||||
struct ggml_tensor * ggml_map_custom1_inplace_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
const ggml_custom1_op_f32_t fun) {
|
||||
return ggml_map_custom1_impl_f32(ctx, a, fun, true);
|
||||
}
|
||||
|
||||
// ggml_map_custom2
|
||||
|
||||
struct ggml_tensor * ggml_map_custom2_impl_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
const ggml_custom2_op_f32_t fun,
|
||||
bool inplace) {
|
||||
bool is_node = false;
|
||||
|
||||
if (!inplace && (a->grad || b->grad)) {
|
||||
is_node = true;
|
||||
}
|
||||
|
||||
struct ggml_tensor *result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
|
||||
|
||||
ggml_scratch_save(ctx);
|
||||
|
||||
struct ggml_tensor * addr_tensor = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, sizeof(void *) / sizeof(int32_t));
|
||||
*((void (**)(void))addr_tensor->data) = (void (*)(void))fun;
|
||||
|
||||
ggml_scratch_load(ctx);
|
||||
|
||||
result->op = GGML_OP_MAP_CUSTOM2;
|
||||
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
|
||||
result->src0 = a;
|
||||
result->src1 = b;
|
||||
result->opt[0] = addr_tensor;
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
struct ggml_tensor * ggml_map_custom2_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
const ggml_custom2_op_f32_t fun) {
|
||||
return ggml_map_custom2_impl_f32(ctx, a, b, fun, false);
|
||||
}
|
||||
|
||||
struct ggml_tensor * ggml_map_custom2_inplace_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
const ggml_custom2_op_f32_t fun) {
|
||||
return ggml_map_custom2_impl_f32(ctx, a, b, fun, true);
|
||||
}
|
||||
|
||||
// ggml_map_custom3
|
||||
|
||||
struct ggml_tensor * ggml_map_custom3_impl_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
struct ggml_tensor * c,
|
||||
const ggml_custom3_op_f32_t fun,
|
||||
bool inplace) {
|
||||
bool is_node = false;
|
||||
|
||||
if (!inplace && (a->grad || b->grad || c->grad)) {
|
||||
is_node = true;
|
||||
}
|
||||
|
||||
struct ggml_tensor *result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
|
||||
|
||||
ggml_scratch_save(ctx);
|
||||
|
||||
struct ggml_tensor * addr_tensor = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, sizeof(void *) / sizeof(int32_t));
|
||||
*((void (**)(void))addr_tensor->data) = (void (*)(void))fun;
|
||||
|
||||
ggml_scratch_load(ctx);
|
||||
|
||||
result->op = GGML_OP_MAP_CUSTOM3;
|
||||
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
|
||||
result->src0 = a;
|
||||
result->src1 = b;
|
||||
result->opt[0] = addr_tensor;
|
||||
result->opt[1] = c;
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
struct ggml_tensor * ggml_map_custom3_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
struct ggml_tensor * c,
|
||||
const ggml_custom3_op_f32_t fun) {
|
||||
return ggml_map_custom3_impl_f32(ctx, a, b, c, fun, false);
|
||||
}
|
||||
|
||||
struct ggml_tensor * ggml_map_custom3_inplace_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
struct ggml_tensor * c,
|
||||
const ggml_custom3_op_f32_t fun) {
|
||||
return ggml_map_custom3_impl_f32(ctx, a, b, c, fun, true);
|
||||
}
|
||||
|
||||
// ggml_cross_entropy_loss
|
||||
|
||||
struct ggml_tensor * ggml_cross_entropy_loss(
|
||||
@ -14621,6 +14798,114 @@ static void ggml_compute_forward_map_binary(
|
||||
}
|
||||
}
|
||||
|
||||
// ggml_compute_forward_map_custom1
|
||||
|
||||
static void ggml_compute_forward_map_custom1_f32(
|
||||
const struct ggml_compute_params * params,
|
||||
const struct ggml_tensor * a,
|
||||
struct ggml_tensor * dst,
|
||||
const ggml_custom1_op_f32_t fun) {
|
||||
assert(params->ith == 0);
|
||||
|
||||
if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
|
||||
return;
|
||||
}
|
||||
|
||||
fun(dst, a);
|
||||
}
|
||||
|
||||
|
||||
static void ggml_compute_forward_map_custom1(
|
||||
const struct ggml_compute_params * params,
|
||||
const struct ggml_tensor * a,
|
||||
struct ggml_tensor * dst,
|
||||
const ggml_custom1_op_f32_t fun) {
|
||||
switch (a->type) {
|
||||
case GGML_TYPE_F32:
|
||||
{
|
||||
ggml_compute_forward_map_custom1_f32(params, a, dst, fun);
|
||||
} break;
|
||||
default:
|
||||
{
|
||||
GGML_ASSERT(false);
|
||||
} break;
|
||||
}
|
||||
}
|
||||
|
||||
// ggml_compute_forward_map_custom2
|
||||
|
||||
static void ggml_compute_forward_map_custom2_f32(
|
||||
const struct ggml_compute_params * params,
|
||||
const struct ggml_tensor * a,
|
||||
const struct ggml_tensor * b,
|
||||
struct ggml_tensor * dst,
|
||||
const ggml_custom2_op_f32_t fun) {
|
||||
assert(params->ith == 0);
|
||||
|
||||
if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
|
||||
return;
|
||||
}
|
||||
|
||||
fun(dst, a, b);
|
||||
}
|
||||
|
||||
|
||||
static void ggml_compute_forward_map_custom2(
|
||||
const struct ggml_compute_params * params,
|
||||
const struct ggml_tensor * a,
|
||||
const struct ggml_tensor * b,
|
||||
struct ggml_tensor * dst,
|
||||
const ggml_custom2_op_f32_t fun) {
|
||||
switch (a->type) {
|
||||
case GGML_TYPE_F32:
|
||||
{
|
||||
ggml_compute_forward_map_custom2_f32(params, a, b, dst, fun);
|
||||
} break;
|
||||
default:
|
||||
{
|
||||
GGML_ASSERT(false);
|
||||
} break;
|
||||
}
|
||||
}
|
||||
|
||||
// ggml_compute_forward_map_custom3
|
||||
|
||||
static void ggml_compute_forward_map_custom3_f32(
|
||||
const struct ggml_compute_params * params,
|
||||
const struct ggml_tensor * a,
|
||||
const struct ggml_tensor * b,
|
||||
const struct ggml_tensor * c,
|
||||
struct ggml_tensor * dst,
|
||||
const ggml_custom3_op_f32_t fun) {
|
||||
assert(params->ith == 0);
|
||||
|
||||
if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
|
||||
return;
|
||||
}
|
||||
|
||||
fun(dst, a, b, c);
|
||||
}
|
||||
|
||||
|
||||
static void ggml_compute_forward_map_custom3(
|
||||
const struct ggml_compute_params * params,
|
||||
const struct ggml_tensor * a,
|
||||
const struct ggml_tensor * b,
|
||||
const struct ggml_tensor * c,
|
||||
struct ggml_tensor * dst,
|
||||
const ggml_custom3_op_f32_t fun) {
|
||||
switch (a->type) {
|
||||
case GGML_TYPE_F32:
|
||||
{
|
||||
ggml_compute_forward_map_custom3_f32(params, a, b, c, dst, fun);
|
||||
} break;
|
||||
default:
|
||||
{
|
||||
GGML_ASSERT(false);
|
||||
} break;
|
||||
}
|
||||
}
|
||||
|
||||
// ggml_compute_forward_cross_entropy_loss
|
||||
|
||||
static void ggml_compute_forward_cross_entropy_loss_f32(
|
||||
@ -15158,6 +15443,24 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm
|
||||
ggml_compute_forward_map_binary(params, tensor->src0, tensor->src1, tensor, fun);
|
||||
}
|
||||
break;
|
||||
case GGML_OP_MAP_CUSTOM1:
|
||||
{
|
||||
const ggml_custom1_op_f32_t fun = *((ggml_custom1_op_f32_t *)tensor->opt[0]->data);
|
||||
ggml_compute_forward_map_custom1(params, tensor->src0, tensor, fun);
|
||||
}
|
||||
break;
|
||||
case GGML_OP_MAP_CUSTOM2:
|
||||
{
|
||||
const ggml_custom2_op_f32_t fun = *((ggml_custom2_op_f32_t *)tensor->opt[0]->data);
|
||||
ggml_compute_forward_map_custom2(params, tensor->src0, tensor->src1, tensor, fun);
|
||||
}
|
||||
break;
|
||||
case GGML_OP_MAP_CUSTOM3:
|
||||
{
|
||||
const ggml_custom3_op_f32_t fun = *((ggml_custom3_op_f32_t *)tensor->opt[0]->data);
|
||||
ggml_compute_forward_map_custom3(params, tensor->src0, tensor->src1, tensor->opt[1], tensor, fun);
|
||||
}
|
||||
break;
|
||||
case GGML_OP_CROSS_ENTROPY_LOSS:
|
||||
{
|
||||
ggml_compute_forward_cross_entropy_loss(params, tensor->src0, tensor->src1, tensor);
|
||||
@ -15964,6 +16267,9 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
|
||||
case GGML_OP_WIN_UNPART:
|
||||
case GGML_OP_MAP_UNARY:
|
||||
case GGML_OP_MAP_BINARY:
|
||||
case GGML_OP_MAP_CUSTOM1:
|
||||
case GGML_OP_MAP_CUSTOM2:
|
||||
case GGML_OP_MAP_CUSTOM3:
|
||||
{
|
||||
GGML_ASSERT(false); // not supported
|
||||
} break;
|
||||
@ -16605,6 +16911,9 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
|
||||
case GGML_OP_WIN_UNPART:
|
||||
case GGML_OP_MAP_UNARY:
|
||||
case GGML_OP_MAP_BINARY:
|
||||
case GGML_OP_MAP_CUSTOM1:
|
||||
case GGML_OP_MAP_CUSTOM2:
|
||||
case GGML_OP_MAP_CUSTOM3:
|
||||
{
|
||||
node->n_tasks = 1;
|
||||
} break;
|
||||
|
||||
60
ggml.h
60
ggml.h
@ -345,6 +345,10 @@ extern "C" {
|
||||
GGML_OP_MAP_UNARY,
|
||||
GGML_OP_MAP_BINARY,
|
||||
|
||||
GGML_OP_MAP_CUSTOM1,
|
||||
GGML_OP_MAP_CUSTOM2,
|
||||
GGML_OP_MAP_CUSTOM3,
|
||||
|
||||
GGML_OP_CROSS_ENTROPY_LOSS,
|
||||
GGML_OP_CROSS_ENTROPY_LOSS_BACK,
|
||||
|
||||
@ -1167,21 +1171,73 @@ extern "C" {
|
||||
int h0,
|
||||
int w);
|
||||
|
||||
// Mapping operations
|
||||
typedef void (*ggml_unary_op_f32_t)(const int, float *, const float *);
|
||||
// custom operators
|
||||
|
||||
typedef void (*ggml_unary_op_f32_t) (const int, float *, const float *);
|
||||
typedef void (*ggml_binary_op_f32_t)(const int, float *, const float *, const float *);
|
||||
|
||||
typedef void (*ggml_custom1_op_f32_t)(struct ggml_tensor *, const struct ggml_tensor *);
|
||||
typedef void (*ggml_custom2_op_f32_t)(struct ggml_tensor *, const struct ggml_tensor *, const struct ggml_tensor *);
|
||||
typedef void (*ggml_custom3_op_f32_t)(struct ggml_tensor *, const struct ggml_tensor *, const struct ggml_tensor *, const struct ggml_tensor *);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_map_unary_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
ggml_unary_op_f32_t fun);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_map_unary_inplace_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
ggml_unary_op_f32_t fun);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_map_binary_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
ggml_binary_op_f32_t fun);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_map_binary_inplace_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
ggml_binary_op_f32_t fun);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_map_custom1_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
ggml_custom1_op_f32_t fun);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_map_custom1_inplace_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
ggml_custom1_op_f32_t fun);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_map_custom2_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
ggml_custom2_op_f32_t fun);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_map_custom2_inplace_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
ggml_custom2_op_f32_t fun);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_map_custom3_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
struct ggml_tensor * c,
|
||||
ggml_custom3_op_f32_t fun);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_map_custom3_inplace_f32(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b,
|
||||
struct ggml_tensor * c,
|
||||
ggml_custom3_op_f32_t fun);
|
||||
|
||||
// loss function
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_cross_entropy_loss(
|
||||
|
||||
Loading…
Reference in New Issue
Block a user