diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h index 452c967b0..a5447ecdf 100644 --- a/ggml/include/ggml.h +++ b/ggml/include/ggml.h @@ -507,17 +507,12 @@ extern "C" { GGML_OP_UNARY, - GGML_OP_MAP_UNARY, - GGML_OP_MAP_BINARY, - - GGML_OP_MAP_CUSTOM1_F32, - GGML_OP_MAP_CUSTOM2_F32, - GGML_OP_MAP_CUSTOM3_F32, - GGML_OP_MAP_CUSTOM1, GGML_OP_MAP_CUSTOM2, GGML_OP_MAP_CUSTOM3, + GGML_OP_CUSTOM, + GGML_OP_CROSS_ENTROPY_LOSS, GGML_OP_CROSS_ENTROPY_LOSS_BACK, GGML_OP_OPT_STEP_ADAMW, @@ -1916,83 +1911,6 @@ extern "C" { // 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_DEPRECATED(GGML_API struct ggml_tensor * ggml_map_unary_f32( - struct ggml_context * ctx, - struct ggml_tensor * a, - ggml_unary_op_f32_t fun), - "use ggml_map_custom1 instead"); - - GGML_DEPRECATED(GGML_API struct ggml_tensor * ggml_map_unary_inplace_f32( - struct ggml_context * ctx, - struct ggml_tensor * a, - ggml_unary_op_f32_t fun), - "use ggml_map_custom1_inplace instead"); - - GGML_DEPRECATED(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), - "use ggml_map_custom2 instead"); - - GGML_DEPRECATED(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), - "use ggml_map_custom2_inplace instead"); - - GGML_DEPRECATED(GGML_API struct ggml_tensor * ggml_map_custom1_f32( - struct ggml_context * ctx, - struct ggml_tensor * a, - ggml_custom1_op_f32_t fun), - "use ggml_map_custom1 instead"); - - GGML_DEPRECATED(GGML_API struct ggml_tensor * ggml_map_custom1_inplace_f32( - struct ggml_context * ctx, - struct ggml_tensor * a, - ggml_custom1_op_f32_t fun), - "use ggml_map_custom1_inplace instead"); - - GGML_DEPRECATED(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), - "use ggml_map_custom2 instead"); - - GGML_DEPRECATED(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), - "use ggml_map_custom2_inplace instead"); - - GGML_DEPRECATED(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), - "use ggml_map_custom3 instead"); - - GGML_DEPRECATED(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), - "use ggml_map_custom3_inplace instead"); - - // custom operators v2 - typedef void (*ggml_custom1_op_t)(struct ggml_tensor * dst , const struct ggml_tensor * a, int ith, int nth, void * userdata); typedef void (*ggml_custom2_op_t)(struct ggml_tensor * dst , const struct ggml_tensor * a, const struct ggml_tensor * b, int ith, int nth, void * userdata); typedef void (*ggml_custom3_op_t)(struct ggml_tensor * dst , const struct ggml_tensor * a, const struct ggml_tensor * b, const struct ggml_tensor * c, int ith, int nth, void * userdata); @@ -2048,6 +1966,30 @@ extern "C" { int n_tasks, void * userdata); + typedef void (*ggml_custom_op_t)(struct ggml_tensor * dst , int ith, int nth, void * userdata); + + GGML_API struct ggml_tensor * ggml_custom_4d( + struct ggml_context * ctx, + enum ggml_type type, + int64_t ne0, + int64_t ne1, + int64_t ne2, + int64_t ne3, + struct ggml_tensor ** args, + int n_args, + ggml_custom_op_t fun, + int n_tasks, + void * userdata); + + GGML_API struct ggml_tensor * ggml_custom_inplace( + struct ggml_context * ctx, + struct ggml_tensor * a, + struct ggml_tensor ** args, + int n_args, + ggml_custom_op_t fun, + int n_tasks, + void * userdata); + // loss function GGML_API struct ggml_tensor * ggml_cross_entropy_loss( diff --git a/ggml/src/ggml-cpu/ggml-cpu.c b/ggml/src/ggml-cpu/ggml-cpu.c index 34618c27a..504003287 100644 --- a/ggml/src/ggml-cpu/ggml-cpu.c +++ b/ggml/src/ggml-cpu/ggml-cpu.c @@ -2027,41 +2027,6 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm { ggml_compute_forward_rwkv_wkv7(params, tensor); } break; - case GGML_OP_MAP_UNARY: - { - ggml_unary_op_f32_t fun; - memcpy(&fun, tensor->op_params, sizeof(fun)); - ggml_compute_forward_map_unary(params, tensor, fun); - } - break; - case GGML_OP_MAP_BINARY: - { - ggml_binary_op_f32_t fun; - memcpy(&fun, tensor->op_params, sizeof(fun)); - ggml_compute_forward_map_binary(params, tensor, fun); - } - break; - case GGML_OP_MAP_CUSTOM1_F32: - { - ggml_custom1_op_f32_t fun; - memcpy(&fun, tensor->op_params, sizeof(fun)); - ggml_compute_forward_map_custom1_f32(params, tensor, fun); - } - break; - case GGML_OP_MAP_CUSTOM2_F32: - { - ggml_custom2_op_f32_t fun; - memcpy(&fun, tensor->op_params, sizeof(fun)); - ggml_compute_forward_map_custom2_f32(params, tensor, fun); - } - break; - case GGML_OP_MAP_CUSTOM3_F32: - { - ggml_custom3_op_f32_t fun; - memcpy(&fun, tensor->op_params, sizeof(fun)); - ggml_compute_forward_map_custom3_f32(params, tensor, fun); - } - break; case GGML_OP_MAP_CUSTOM1: { ggml_compute_forward_map_custom1(params, tensor); @@ -2077,6 +2042,11 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm ggml_compute_forward_map_custom3(params, tensor); } break; + case GGML_OP_CUSTOM: + { + ggml_compute_forward_custom(params, tensor); + } + break; case GGML_OP_CROSS_ENTROPY_LOSS: { ggml_compute_forward_cross_entropy_loss(params, tensor); @@ -2328,11 +2298,6 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) { case GGML_OP_WIN_PART: case GGML_OP_WIN_UNPART: case GGML_OP_GET_REL_POS: - case GGML_OP_MAP_UNARY: - case GGML_OP_MAP_BINARY: - case GGML_OP_MAP_CUSTOM1_F32: - case GGML_OP_MAP_CUSTOM2_F32: - case GGML_OP_MAP_CUSTOM3_F32: { n_tasks = 1; } break; @@ -2366,6 +2331,16 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) { n_tasks = MIN(p.n_tasks, n_threads); } } break; + case GGML_OP_CUSTOM: + { + struct ggml_custom_op_params p; + memcpy(&p, node->op_params, sizeof(p)); + if (p.n_tasks == GGML_N_TASKS_MAX) { + n_tasks = n_threads; + } else { + n_tasks = MIN(p.n_tasks, n_threads); + } + } break; case GGML_OP_CROSS_ENTROPY_LOSS: case GGML_OP_CROSS_ENTROPY_LOSS_BACK: case GGML_OP_OPT_STEP_ADAMW: diff --git a/ggml/src/ggml-cpu/ops.cpp b/ggml/src/ggml-cpu/ops.cpp index f63656be5..36b98152e 100644 --- a/ggml/src/ggml-cpu/ops.cpp +++ b/ggml/src/ggml-cpu/ops.cpp @@ -8268,152 +8268,6 @@ void ggml_compute_forward_rwkv_wkv7( } } -// ggml_compute_forward_map_unary - -static void ggml_compute_forward_map_unary_f32( - const ggml_compute_params * params, - ggml_tensor * dst, - const ggml_unary_op_f32_t fun) { - - const ggml_tensor * src0 = dst->src[0]; - - if (params->ith != 0) { - return; - } - - assert(ggml_is_contiguous_1(src0)); - assert(ggml_is_contiguous_1(dst)); - assert(ggml_are_same_shape(src0, dst)); - - const int n = ggml_nrows(src0); - const int nc = src0->ne[0]; - - for (int i = 0; i < n; i++) { - fun(nc, - (float *) ((char *) dst->data + i*( dst->nb[1])), - (float *) ((char *) src0->data + i*(src0->nb[1]))); - } -} - -void ggml_compute_forward_map_unary( - const ggml_compute_params * params, - ggml_tensor * dst, - const ggml_unary_op_f32_t fun) { - - const ggml_tensor * src0 = dst->src[0]; - - switch (src0->type) { - case GGML_TYPE_F32: - { - ggml_compute_forward_map_unary_f32(params, dst, fun); - } break; - default: - { - GGML_ABORT("fatal error"); - } - } -} - -// ggml_compute_forward_map_binary - -static void ggml_compute_forward_map_binary_f32( - const ggml_compute_params * params, - ggml_tensor * dst, - const ggml_binary_op_f32_t fun) { - - const ggml_tensor * src0 = dst->src[0]; - const ggml_tensor * src1 = dst->src[1]; - - if (params->ith != 0) { - return; - } - - assert(ggml_is_contiguous_1(src0)); - assert(ggml_is_contiguous_1(src1)); - assert(ggml_is_contiguous_1(dst)); - assert(ggml_are_same_shape(src0, src1) && ggml_are_same_shape(src0, dst)); - - const int n = ggml_nrows(src0); - const int nc = src0->ne[0]; - - for (int i = 0; i < n; i++) { - fun(nc, - (float *) ((char *) dst->data + i*( dst->nb[1])), - (float *) ((char *) src0->data + i*(src0->nb[1])), - (float *) ((char *) src1->data + i*(src1->nb[1]))); - } -} - -void ggml_compute_forward_map_binary( - const ggml_compute_params * params, - ggml_tensor * dst, - const ggml_binary_op_f32_t fun) { - - const ggml_tensor * src0 = dst->src[0]; - - switch (src0->type) { - case GGML_TYPE_F32: - { - ggml_compute_forward_map_binary_f32(params, dst, fun); - } break; - default: - { - GGML_ABORT("fatal error"); - } - } -} - -// ggml_compute_forward_map_custom1 - -void ggml_compute_forward_map_custom1_f32( - const ggml_compute_params * params, - ggml_tensor * dst, - const ggml_custom1_op_f32_t fun) { - - const ggml_tensor * a = dst->src[0]; - - if (params->ith != 0) { - return; - } - - fun(dst, a); -} - -// ggml_compute_forward_map_custom2 - -void ggml_compute_forward_map_custom2_f32( - const ggml_compute_params * params, - ggml_tensor * dst, - const ggml_custom2_op_f32_t fun) { - - const ggml_tensor * a = dst->src[0]; - const ggml_tensor * b = dst->src[1]; - - if (params->ith != 0) { - return; - } - - fun(dst, a, b); -} - -// ggml_compute_forward_map_custom3 - -void ggml_compute_forward_map_custom3_f32( - const ggml_compute_params * params, - ggml_tensor * dst, - const ggml_custom3_op_f32_t fun) { - - const ggml_tensor * a = dst->src[0]; - const ggml_tensor * b = dst->src[1]; - const ggml_tensor * c = dst->src[1]; - - if (params->ith != 0) { - return; - } - - fun(dst, a, b, c); -} - // ggml_compute_forward_map_custom1 void ggml_compute_forward_map_custom1( @@ -8459,6 +8313,18 @@ void ggml_compute_forward_map_custom3( p.fun(dst, a, b, c, params->ith, params->nth, p.userdata); } +// ggml_compute_forward_custom + +void ggml_compute_forward_custom( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + struct ggml_custom_op_params p; + memcpy(&p, dst->op_params, sizeof(p)); + + p.fun(dst, params->ith, params->nth, p.userdata); +} + // ggml_compute_forward_cross_entropy_loss static void ggml_compute_forward_cross_entropy_loss_f32( diff --git a/ggml/src/ggml-cpu/ops.h b/ggml/src/ggml-cpu/ops.h index d43fbc1fc..410a37204 100644 --- a/ggml/src/ggml-cpu/ops.h +++ b/ggml/src/ggml-cpu/ops.h @@ -96,29 +96,10 @@ void ggml_compute_forward_add_rel_pos(const struct ggml_compute_params * params, void ggml_compute_forward_rwkv_wkv6(const struct ggml_compute_params * params, struct ggml_tensor * dst); void ggml_compute_forward_rwkv_wkv7(const struct ggml_compute_params * params, struct ggml_tensor * dst); void ggml_compute_forward_gla(const struct ggml_compute_params * params, struct ggml_tensor * dst); -void ggml_compute_forward_map_unary( - const struct ggml_compute_params * params, - struct ggml_tensor * dst, - const ggml_unary_op_f32_t fun); -void ggml_compute_forward_map_binary( - const struct ggml_compute_params * params, - struct ggml_tensor * dst, - const ggml_binary_op_f32_t fun); -void ggml_compute_forward_map_custom1_f32( - const struct ggml_compute_params * params, - struct ggml_tensor * dst, - const ggml_custom1_op_f32_t fun); -void ggml_compute_forward_map_custom2_f32( - const struct ggml_compute_params * params, - struct ggml_tensor * dst, - const ggml_custom2_op_f32_t fun); -void ggml_compute_forward_map_custom3_f32( - const struct ggml_compute_params * params, - struct ggml_tensor * dst, - const ggml_custom3_op_f32_t fun); void ggml_compute_forward_map_custom1(const struct ggml_compute_params * params, struct ggml_tensor * dst); void ggml_compute_forward_map_custom2(const struct ggml_compute_params * params, struct ggml_tensor * dst); void ggml_compute_forward_map_custom3(const struct ggml_compute_params * params, struct ggml_tensor * dst); +void ggml_compute_forward_custom(const struct ggml_compute_params * params, struct ggml_tensor * dst); void ggml_compute_forward_cross_entropy_loss(const struct ggml_compute_params * params, struct ggml_tensor * dst); void ggml_compute_forward_cross_entropy_loss_back(const struct ggml_compute_params * params, struct ggml_tensor * dst); void ggml_compute_forward_opt_step_adamw(const struct ggml_compute_params * params, struct ggml_tensor * dst); diff --git a/ggml/src/ggml-impl.h b/ggml/src/ggml-impl.h index caa6b9dba..13a3857cf 100644 --- a/ggml/src/ggml-impl.h +++ b/ggml/src/ggml-impl.h @@ -140,8 +140,14 @@ struct ggml_map_custom2_op_params { struct ggml_map_custom3_op_params { ggml_custom3_op_t fun; - int n_tasks; - void * userdata; + int n_tasks; + void * userdata; +}; + +struct ggml_custom_op_params { + ggml_custom_op_t fun; + int n_tasks; + void * userdata; }; // bitset diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index 3e274d6ae..98a0f6164 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -982,23 +982,18 @@ static const char * GGML_OP_NAME[GGML_OP_COUNT] = { "UNARY", - "MAP_UNARY", - "MAP_BINARY", - - "MAP_CUSTOM1_F32", - "MAP_CUSTOM2_F32", - "MAP_CUSTOM3_F32", - "MAP_CUSTOM1", "MAP_CUSTOM2", "MAP_CUSTOM3", + "CUSTOM", + "CROSS_ENTROPY_LOSS", "CROSS_ENTROPY_LOSS_BACK", "OPT_STEP_ADAMW", }; -static_assert(GGML_OP_COUNT == 85, "GGML_OP_COUNT != 85"); +static_assert(GGML_OP_COUNT == 81, "GGML_OP_COUNT != 81"); static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = { "none", @@ -1081,23 +1076,18 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = { "unary(x)", - "f(x)", - "f(x,y)", - - "custom_f32(x)", - "custom_f32(x,y)", - "custom_f32(x,y,z)", + "map_custom(x)", + "map_custom(x,y)", + "map_custom(x,y,z)", "custom(x)", - "custom(x,y)", - "custom(x,y,z)", "cross_entropy_loss(x,y)", "cross_entropy_loss_back(x,y)", "adamw(x)", }; -static_assert(GGML_OP_COUNT == 85, "GGML_OP_COUNT != 85"); +static_assert(GGML_OP_COUNT == 81, "GGML_OP_COUNT != 81"); static_assert(GGML_OP_POOL_COUNT == 2, "GGML_OP_POOL_COUNT != 2"); @@ -4842,179 +4832,6 @@ struct ggml_tensor * ggml_unary_inplace( return ggml_unary_impl(ctx, a, op, true); } -// ggml_map_unary - -static struct ggml_tensor * ggml_map_unary_impl_f32( - struct ggml_context * ctx, - struct ggml_tensor * a, - const ggml_unary_op_f32_t fun, - bool inplace) { - struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a); - - ggml_set_op_params(result, (const void *) &fun, sizeof(fun)); - - result->op = GGML_OP_MAP_UNARY; - result->src[0] = a; - - return result; -} - -struct ggml_tensor * ggml_map_unary_f32( - struct ggml_context * ctx, - struct ggml_tensor * a, - const ggml_unary_op_f32_t fun) { - return ggml_map_unary_impl_f32(ctx, a, fun, false); -} - -struct ggml_tensor * ggml_map_unary_inplace_f32( - struct ggml_context * ctx, - struct ggml_tensor * a, - const ggml_unary_op_f32_t fun) { - return ggml_map_unary_impl_f32(ctx, a, fun, true); -} - -// ggml_map_binary - -static struct ggml_tensor * ggml_map_binary_impl_f32( - struct ggml_context * ctx, - struct ggml_tensor * a, - struct ggml_tensor * b, - const ggml_binary_op_f32_t fun, - bool inplace) { - GGML_ASSERT(ggml_are_same_shape(a, b)); - - struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a); - - ggml_set_op_params(result, (const void *) &fun, sizeof(fun)); - - result->op = GGML_OP_MAP_BINARY; - result->src[0] = a; - result->src[1] = b; - - return result; -} - -struct ggml_tensor * ggml_map_binary_f32( - struct ggml_context * ctx, - struct ggml_tensor * a, - struct ggml_tensor * b, - const ggml_binary_op_f32_t fun) { - return ggml_map_binary_impl_f32(ctx, a, b, fun, false); -} - -struct ggml_tensor * ggml_map_binary_inplace_f32( - struct ggml_context * ctx, - struct ggml_tensor * a, - struct ggml_tensor * b, - const ggml_binary_op_f32_t fun) { - return ggml_map_binary_impl_f32(ctx, a, b, fun, true); -} - -// ggml_map_custom1_f32 - -static 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) { - struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a); - - ggml_set_op_params(result, (const void *) &fun, sizeof(fun)); - - result->op = GGML_OP_MAP_CUSTOM1_F32; - result->src[0] = a; - - 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_f32 - -static 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) { - struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a); - - ggml_set_op_params(result, (const void *) &fun, sizeof(fun)); - - result->op = GGML_OP_MAP_CUSTOM2_F32; - result->src[0] = a; - result->src[1] = b; - - 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_f32 - -static 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) { - struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a); - - ggml_set_op_params(result, (const void *) &fun, sizeof(fun)); - - result->op = GGML_OP_MAP_CUSTOM3_F32; - result->src[0] = a; - result->src[1] = b; - result->src[2] = 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_map_custom1 static struct ggml_tensor * ggml_map_custom1_impl( @@ -5033,7 +4850,7 @@ static struct ggml_tensor * ggml_map_custom1_impl( /*.n_tasks =*/ n_tasks, /*.userdata =*/ userdata }; - ggml_set_op_params(result, (const void *) ¶ms, sizeof(params)); + ggml_set_op_params(result, ¶ms, sizeof(params)); result->op = GGML_OP_MAP_CUSTOM1; result->src[0] = a; @@ -5078,7 +4895,7 @@ static struct ggml_tensor * ggml_map_custom2_impl( /*.n_tasks =*/ n_tasks, /*.userdata =*/ userdata }; - ggml_set_op_params(result, (const void *) ¶ms, sizeof(params)); + ggml_set_op_params(result, ¶ms, sizeof(params)); result->op = GGML_OP_MAP_CUSTOM2; result->src[0] = a; @@ -5127,7 +4944,7 @@ static struct ggml_tensor * ggml_map_custom3_impl( /*.n_tasks =*/ n_tasks, /*.userdata =*/ userdata }; - ggml_set_op_params(result, (const void *) ¶ms, sizeof(params)); + ggml_set_op_params(result, ¶ms, sizeof(params)); result->op = GGML_OP_MAP_CUSTOM3; result->src[0] = a; @@ -5159,6 +4976,66 @@ struct ggml_tensor * ggml_map_custom3_inplace( return ggml_map_custom3_impl(ctx, a, b, c, fun, n_tasks, userdata, true); } +struct ggml_tensor * ggml_custom_4d( + struct ggml_context * ctx, + enum ggml_type type, + int64_t ne0, + int64_t ne1, + int64_t ne2, + int64_t ne3, + struct ggml_tensor ** args, + int n_args, + ggml_custom_op_t fun, + int n_tasks, + void * userdata) { + + GGML_ASSERT(n_args < GGML_MAX_SRC); + + struct ggml_tensor * result = ggml_new_tensor_4d(ctx, type, ne0, ne1, ne2, ne3); + + struct ggml_custom_op_params params = { + /*.fun =*/ fun, + /*.n_tasks =*/ n_tasks, + /*.userdata =*/ userdata + }; + ggml_set_op_params(result, ¶ms, sizeof(params)); + + result->op = GGML_OP_CUSTOM; + for (int i = 0; i < n_args; i++) { + result->src[i] = args[i]; + } + + return result; +} + +struct ggml_tensor * ggml_custom_inplace( + struct ggml_context * ctx, + struct ggml_tensor * a, + struct ggml_tensor ** args, + int n_args, + ggml_custom_op_t fun, + int n_tasks, + void * userdata) { + + GGML_ASSERT(n_args < GGML_MAX_SRC - 1); + + struct ggml_tensor * result = ggml_view_tensor(ctx, a); + + struct ggml_custom_op_params params = { + /*.fun =*/ fun, + /*.n_tasks =*/ n_tasks, + /*.userdata =*/ userdata + }; + ggml_set_op_params(result, ¶ms, sizeof(params)); + + result->op = GGML_OP_CUSTOM; + result->src[0] = a; + for (int i = 0; i < n_args; i++) { + result->src[i + 1] = args[i]; + } + + return result; +} // ggml_cross_entropy_loss struct ggml_tensor * ggml_cross_entropy_loss(