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3 Commits

Author SHA1 Message Date
Pascal 4f37f51972 server: accept null sampling params (#25538)
* server: accept null sampling params

Extend the schema validation to treat a null value as absent, so
clients can send null on nullable params (temperature, top_p, ...)
to request the server default. This matches the OpenAI spec and the
json_value convention used elsewhere.

Add has_field() to skip null in the field eval guards.

* has_field -> has_value​
2026-07-10 22:07:29 +02:00
eduardopessin c749cb0417 llama : make tensor-split regex patterns static (#24710)
llama_meta_device_get_split_state() recompiled 29 std::regex on every call.
In -sm tensor mode the callback runs once per tensor per token, so this
dominated the decode thread in profiling. Mark them static const so they are
compiled once. Kept inside the function (local statics are thread-safe since
C++11). Patterns are literal and stateless, so behavior is unchanged.
2026-07-10 19:04:12 +02:00
Max Krasnyansky 67776eaee5 hexagon: improve ARGSORT performance for small tensors (#25512)
* hex-sort: add efficient bitomic sort in hvx regs up to 1024 elements

* hex-sort: fix inverted vrors

* hex-sort: specialize sort functions for the common cases

* hex-sort: add tracing and local context
2026-07-10 09:06:06 -07:00
4 changed files with 280 additions and 54 deletions
+2 -2
View File
@@ -31,7 +31,6 @@ add_library(${HTP_LIB} SHARED
get-rows-ops.c
cpy-ops.c
repeat-ops.c
argsort-ops.c
ssm-conv.c
cumsum-ops.c
fill-ops.c
@@ -39,8 +38,9 @@ add_library(${HTP_LIB} SHARED
diag-ops.c
solve-tri-ops.c
pad-ops.c
matmul-ops.c
flash-attn-ops.c
matmul-ops.c
argsort-ops.c
)
target_compile_definitions(${HTP_LIB} PRIVATE
+239 -19
View File
@@ -22,6 +22,8 @@
struct htp_argsort_context {
struct htp_ops_context * octx;
uint32_t nrows_per_thread;
uint8_t * vtcm_base;
size_t vtcm_per_thread;
};
static inline bool all_greater_f32(HVX_Vector x, HVX_Vector y)
@@ -170,7 +172,208 @@ int32_t argosrt_ramp_lut[32] __attribute__((aligned(VLEN))) = {
16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31
};
static void htp_argsort_f32(unsigned int n, unsigned int i, void * data) {
__attribute__((always_inline))
static inline void vec_cas(HVX_Vector * X_val, HVX_Vector * X_idx, HVX_Vector * Y_val, HVX_Vector * Y_idx, bool asc) {
HVX_VectorPred pred = asc ? Q6_Q_vcmp_gt_VsfVsf(*X_val, *Y_val)
: Q6_Q_vcmp_gt_VsfVsf(*Y_val, *X_val);
HVX_Vector next_X_val = Q6_V_vmux_QVV(pred, *Y_val, *X_val);
HVX_Vector next_Y_val = Q6_V_vmux_QVV(pred, *X_val, *Y_val);
HVX_Vector next_X_idx = Q6_V_vmux_QVV(pred, *Y_idx, *X_idx);
HVX_Vector Y_tmp_idx = Q6_V_vmux_QVV(pred, *X_idx, *Y_idx);
*X_val = next_X_val;
*Y_val = next_Y_val;
*X_idx = next_X_idx;
*Y_idx = Y_tmp_idx;
}
__attribute__((always_inline))
static inline void bitonic_cas_32(HVX_Vector * V, HVX_Vector * I, int d, HVX_VectorPred dir_mask, HVX_Vector idx_vec, HVX_Vector zero_vec) {
HVX_VectorPred mask_left;
HVX_Vector V_rot_left, V_rot_right;
HVX_Vector I_rot_left, I_rot_right;
if (d == 1) {
mask_left = Q6_Q_vcmp_eq_VwVw(Q6_V_vand_VV(idx_vec, Q6_V_vsplat_R(1)), zero_vec);
V_rot_left = Q6_V_vror_VR(*V, 4);
V_rot_right = Q6_V_vror_VR(*V, 124);
I_rot_left = Q6_V_vror_VR(*I, 4);
I_rot_right = Q6_V_vror_VR(*I, 124);
} else if (d == 2) {
mask_left = Q6_Q_vcmp_eq_VwVw(Q6_V_vand_VV(idx_vec, Q6_V_vsplat_R(2)), zero_vec);
V_rot_left = Q6_V_vror_VR(*V, 8);
V_rot_right = Q6_V_vror_VR(*V, 120);
I_rot_left = Q6_V_vror_VR(*I, 8);
I_rot_right = Q6_V_vror_VR(*I, 120);
} else if (d == 4) {
mask_left = Q6_Q_vcmp_eq_VwVw(Q6_V_vand_VV(idx_vec, Q6_V_vsplat_R(4)), zero_vec);
V_rot_left = Q6_V_vror_VR(*V, 16);
V_rot_right = Q6_V_vror_VR(*V, 112);
I_rot_left = Q6_V_vror_VR(*I, 16);
I_rot_right = Q6_V_vror_VR(*I, 112);
} else if (d == 8) {
mask_left = Q6_Q_vcmp_eq_VwVw(Q6_V_vand_VV(idx_vec, Q6_V_vsplat_R(8)), zero_vec);
V_rot_left = Q6_V_vror_VR(*V, 32);
V_rot_right = Q6_V_vror_VR(*V, 96);
I_rot_left = Q6_V_vror_VR(*I, 32);
I_rot_right = Q6_V_vror_VR(*I, 96);
} else { // d == 16
mask_left = Q6_Q_vcmp_eq_VwVw(Q6_V_vand_VV(idx_vec, Q6_V_vsplat_R(16)), zero_vec);
V_rot_left = Q6_V_vror_VR(*V, 64);
V_rot_right = Q6_V_vror_VR(*V, 64);
I_rot_left = Q6_V_vror_VR(*I, 64);
I_rot_right = Q6_V_vror_VR(*I, 64);
}
HVX_Vector V_paired = Q6_V_vmux_QVV(mask_left, V_rot_left, V_rot_right);
HVX_Vector I_paired = Q6_V_vmux_QVV(mask_left, I_rot_left, I_rot_right);
HVX_VectorPred V_gt_Vpaired = Q6_Q_vcmp_gt_VsfVsf(*V, V_paired);
HVX_VectorPred Vpaired_gt_V = Q6_Q_vcmp_gt_VsfVsf(V_paired, *V);
HVX_VectorPred mask_right = Q6_Q_not_Q(mask_left);
HVX_VectorPred Q_asc = Q6_Q_or_QQ(
Q6_Q_and_QQ(mask_left, V_gt_Vpaired),
Q6_Q_and_QQ(Vpaired_gt_V, mask_right)
);
HVX_VectorPred Q_swap = Q6_Q_or_QQ(
Q6_Q_and_QQ(dir_mask, Q_asc),
Q6_Q_and_QQ(Q6_Q_not_Q(dir_mask), Q6_Q_not_Q(Q_asc))
);
*V = Q6_V_vmux_QVV(Q_swap, V_paired, *V);
*I = Q6_V_vmux_QVV(Q_swap, I_paired, *I);
}
__attribute__((always_inline))
static inline void bitonic_sort_generic_hvx(uint8_t * values, uint8_t * indices, int K, bool asc_order) {
HVX_Vector V[32];
HVX_Vector I[32];
HVX_Vector zero_vec = Q6_V_vzero();
HVX_Vector idx_vec = *(HVX_Vector *)argosrt_ramp_lut;
// Load values and initialize indices
for (int v = 0; v < K; v++) {
V[v] = *(HVX_Vector *)(values + v * 128);
I[v] = Q6_Vw_vadd_VwVw(idx_vec, Q6_V_vsplat_R(v * 32));
}
HVX_VectorPred pred_all_1s = Q6_Q_vcmp_eq_VwVw(zero_vec, zero_vec);
HVX_VectorPred pred_all_0s = Q6_Q_not_Q(pred_all_1s);
int M = 5;
while ((1 << (M - 5)) < K) M++;
for (int s = 1; s <= M; s++) {
for (int stage_d = s - 1; stage_d >= 0; stage_d--) {
int d = 1 << stage_d;
if (d >= 32) {
int v_dist = d / 32;
for (int v1 = 0; v1 < K; v1++) {
if ((v1 & v_dist) == 0) {
int v2 = v1 + v_dist;
bool asc = (s < M) ? ((((v1 * 32) >> s) % 2) == 0) : asc_order;
vec_cas(&V[v1], &I[v1], &V[v2], &I[v2], asc);
}
}
} else {
if (s < 5) {
HVX_VectorPred dir_mask = Q6_Q_vcmp_eq_VwVw(Q6_V_vand_VV(idx_vec, Q6_V_vsplat_R(1 << s)), zero_vec);
for (int v = 0; v < K; v++) {
bitonic_cas_32(&V[v], &I[v], d, dir_mask, idx_vec, zero_vec);
}
} else {
for (int v = 0; v < K; v++) {
bool asc = (s < M) ? ((((v * 32) >> s) % 2) == 0) : asc_order;
HVX_VectorPred dir_mask = asc ? pred_all_1s : pred_all_0s;
bitonic_cas_32(&V[v], &I[v], d, dir_mask, idx_vec, zero_vec);
}
}
}
}
}
// Write back sorted values and indices
for (int v = 0; v < K; v++) {
*(HVX_Vector *)(values + v * 128) = V[v];
*(HVX_Vector *)(indices + v * 128) = I[v];
}
}
__attribute__((always_inline))
static inline void sort32_f32_hvx(uint8_t * values, uint8_t * indices, enum ggml_sort_order order) {
bitonic_sort_generic_hvx(values, indices, 1, order == GGML_SORT_ORDER_ASC);
}
__attribute__((always_inline))
static inline void sort64_f32_hvx(uint8_t * values, uint8_t * indices, enum ggml_sort_order order) {
bitonic_sort_generic_hvx(values, indices, 2, order == GGML_SORT_ORDER_ASC);
}
__attribute__((always_inline))
static inline void sort128_f32_hvx(uint8_t * values, uint8_t * indices, enum ggml_sort_order order) {
bitonic_sort_generic_hvx(values, indices, 4, order == GGML_SORT_ORDER_ASC);
}
__attribute__((always_inline))
static inline void sort256_f32_hvx(uint8_t * values, uint8_t * indices, enum ggml_sort_order order) {
bitonic_sort_generic_hvx(values, indices, 8, order == GGML_SORT_ORDER_ASC);
}
__attribute__((always_inline))
static inline void sort512_f32_hvx(uint8_t * values, uint8_t * indices, enum ggml_sort_order order) {
bitonic_sort_generic_hvx(values, indices, 16, order == GGML_SORT_ORDER_ASC);
}
__attribute__((always_inline))
static inline void sort1024_f32_hvx(uint8_t * values, uint8_t * indices, enum ggml_sort_order order) {
bitonic_sort_generic_hvx(values, indices, 32, order == GGML_SORT_ORDER_ASC);
}
#define HTP_ARGSORT_FN(ne00, order_name, order_enum, sort_fn) \
static void htp_argsort_f32_##ne00##_##order_name(unsigned int n, unsigned int i, void * data) { \
struct htp_argsort_context * actx = (struct htp_argsort_context *)data; \
struct htp_ops_context * octx = actx->octx; \
const struct htp_tensor * src0 = octx->src[0]; \
const struct htp_tensor * dst = octx->dst; \
uint8_t * spad = actx->vtcm_base + actx->vtcm_per_thread * i; \
uint32_t total_rows = src0->ne[1] * src0->ne[2] * src0->ne[3]; \
uint32_t rows_per_thread = actx->nrows_per_thread; \
uint32_t start_row = rows_per_thread * i; \
uint32_t end_row = MIN(start_row + rows_per_thread, total_rows); \
size_t values_size = hex_round_up(ne00 * sizeof(float), 128); \
float * values_buf = (float *) spad; \
int32_t * indices_buf = (int32_t *) (spad + values_size); \
uint32_t nb01 = src0->nb[1]; \
uint32_t nb1 = dst->nb[1]; \
struct htp_thread_trace * tr = octx->ctx ? &octx->ctx->trace[i] : NULL; \
htp_trace_event_start(tr, HTP_TRACE_EVT_HVX_COMP, start_row); \
for (uint32_t r = start_row; r < end_row; r++) { \
uint32_t src_offset = r * nb01; \
uint32_t dst_offset = r * nb1; \
uint8_t * src_ptr = (uint8_t *) src0->data + src_offset; \
uint8_t * dst_ptr = (uint8_t *) dst->data + dst_offset; \
hex_l2fetch(src_ptr, ne00 * sizeof(float), ne00 * sizeof(float), 1); \
hvx_copy_f32_au((uint8_t*)values_buf, src_ptr, ne00); \
sort_fn((uint8_t*)values_buf, (uint8_t*)indices_buf, order_enum); \
hvx_copy_f32_ua(dst_ptr, (const uint8_t *) indices_buf, ne00); \
} \
htp_trace_event_stop(tr, HTP_TRACE_EVT_HVX_COMP, start_row); \
}
HTP_ARGSORT_FN(32, asc, GGML_SORT_ORDER_ASC, sort32_f32_hvx)
HTP_ARGSORT_FN(32, dsc, GGML_SORT_ORDER_DESC, sort32_f32_hvx)
HTP_ARGSORT_FN(64, asc, GGML_SORT_ORDER_ASC, sort64_f32_hvx)
HTP_ARGSORT_FN(64, dsc, GGML_SORT_ORDER_DESC, sort64_f32_hvx)
HTP_ARGSORT_FN(128, asc, GGML_SORT_ORDER_ASC, sort128_f32_hvx)
HTP_ARGSORT_FN(128, dsc, GGML_SORT_ORDER_DESC, sort128_f32_hvx)
HTP_ARGSORT_FN(256, asc, GGML_SORT_ORDER_ASC, sort256_f32_hvx)
HTP_ARGSORT_FN(256, dsc, GGML_SORT_ORDER_DESC, sort256_f32_hvx)
HTP_ARGSORT_FN(512, asc, GGML_SORT_ORDER_ASC, sort512_f32_hvx)
HTP_ARGSORT_FN(512, dsc, GGML_SORT_ORDER_DESC, sort512_f32_hvx)
HTP_ARGSORT_FN(1024, asc, GGML_SORT_ORDER_ASC, sort1024_f32_hvx)
HTP_ARGSORT_FN(1024, dsc, GGML_SORT_ORDER_DESC, sort1024_f32_hvx)
static void htp_argsort_f32_fallback(unsigned int n, unsigned int i, void * data) {
struct htp_argsort_context * actx = (struct htp_argsort_context *)data;
struct htp_ops_context * octx = actx->octx;
@@ -179,7 +382,7 @@ static void htp_argsort_f32(unsigned int n, unsigned int i, void * data) {
const struct htp_tensor * dst = octx->dst;
// Scratchpad memory
uint8_t * spad = octx->src0_spad.data + octx->src0_spad.size_per_thread * i;
uint8_t * spad = actx->vtcm_base + actx->vtcm_per_thread * i;
// Dimensions
uint32_t ne00 = src0->ne[0];
@@ -188,12 +391,8 @@ static void htp_argsort_f32(unsigned int n, unsigned int i, void * data) {
uint32_t ne03 = src0->ne[3];
uint32_t nb01 = src0->nb[1];
//uint32_t nb02 = src0->nb[2];
//uint32_t nb03 = src0->nb[3];
uint32_t nb1 = dst->nb[1];
//uint32_t nb2 = dst->nb[2];
//uint32_t nb3 = dst->nb[3];
// Sort order
enum ggml_sort_order order = (enum ggml_sort_order) octx->op_params[0];
@@ -204,20 +403,17 @@ static void htp_argsort_f32(unsigned int n, unsigned int i, void * data) {
uint32_t start_row = rows_per_thread * i;
uint32_t end_row = MIN(start_row + rows_per_thread, total_rows);
// Scratchpad layout:
// We need space for one row of float data (values) and one row of int32 indices.
// values: ne00 * sizeof(float)
// indices: ne00 * sizeof(int32_t)
// Padded to 128 bytes.
size_t values_size = hex_round_up(ne00 * sizeof(float), 128);
size_t num_vec_ind_values = hmx_ceil_div(ne00, VLEN/(sizeof(int32_t)));
uint32_t num_vec_ind_values = hmx_ceil_div(ne00, VLEN/(sizeof(int32_t)));
float * values_buf = (float *) spad;
int32_t * indices_buf = (int32_t *) (spad + values_size);
HVX_Vector * indices_buf_vec = (HVX_Vector *) (spad + values_size);
const HVX_Vector ind_init_vec = *(HVX_Vector *)argosrt_ramp_lut;
const HVX_Vector ind_diff_vec = Q6_V_vsplat_R(32);
struct htp_thread_trace * tr = octx->ctx ? &octx->ctx->trace[i] : NULL;
htp_trace_event_start(tr, HTP_TRACE_EVT_HVX_COMP, start_row);
for (uint32_t r = start_row; r < end_row; r++) {
uint32_t src_offset = r * nb01;
uint32_t dst_offset = r * nb1;
@@ -245,6 +441,8 @@ static void htp_argsort_f32(unsigned int n, unsigned int i, void * data) {
// Copy indices back to DDR
hvx_copy_f32_ua(dst_ptr, (const uint8_t *) indices_buf, ne00);
}
htp_trace_event_stop(tr, HTP_TRACE_EVT_HVX_COMP, start_row);
}
int op_argsort(struct htp_ops_context * octx) {
@@ -273,11 +471,6 @@ int op_argsort(struct htp_ops_context * octx) {
return HTP_STATUS_VTCM_TOO_SMALL;
}
octx->src0_spad.data = octx->ctx->vtcm_base;
octx->src0_spad.size = total_spad_size;
octx->src0_spad.size_per_thread = spad_per_thread;
octx->src0_spad.src = NULL;
FARF(HIGH, "argsort: %ux%ux%ux%u -> %ux%ux%ux%u (0x%x, 0x%x)",
octx->src[0]->ne[0], octx->src[0]->ne[1], octx->src[0]->ne[2], octx->src[0]->ne[3],
octx->dst->ne[0], octx->dst->ne[1], octx->dst->ne[2], octx->dst->ne[3],
@@ -286,9 +479,36 @@ int op_argsort(struct htp_ops_context * octx) {
struct htp_argsort_context actx;
actx.octx = octx;
actx.nrows_per_thread = (total_rows + n_threads - 1) / n_threads;
actx.vtcm_base = (uint8_t *) octx->ctx->vtcm_base;
actx.vtcm_per_thread = spad_per_thread;
enum ggml_sort_order order = (enum ggml_sort_order) octx->op_params[0];
worker_callback_t job_func = htp_argsort_f32_fallback;
if (order == GGML_SORT_ORDER_ASC) {
switch (ne00) {
case 1024: job_func = htp_argsort_f32_1024_asc; break;
case 512: job_func = htp_argsort_f32_512_asc; break;
case 256: job_func = htp_argsort_f32_256_asc; break;
case 128: job_func = htp_argsort_f32_128_asc; break;
case 64: job_func = htp_argsort_f32_64_asc; break;
case 32: job_func = htp_argsort_f32_32_asc; break;
default: job_func = htp_argsort_f32_fallback; break;
}
} else {
switch (ne00) {
case 1024: job_func = htp_argsort_f32_1024_dsc; break;
case 512: job_func = htp_argsort_f32_512_dsc; break;
case 256: job_func = htp_argsort_f32_256_dsc; break;
case 128: job_func = htp_argsort_f32_128_dsc; break;
case 64: job_func = htp_argsort_f32_64_dsc; break;
case 32: job_func = htp_argsort_f32_32_dsc; break;
default: job_func = htp_argsort_f32_fallback; break;
}
}
// Run jobs
worker_pool_run_func(octx->ctx->worker_pool, htp_argsort_f32, &actx, n_threads);
worker_pool_run_func(octx->ctx->worker_pool, job_func, &actx, n_threads);
return HTP_STATUS_OK;
}
+29 -29
View File
@@ -336,38 +336,38 @@ struct ggml_backend_meta_split_state llama_meta_device_get_split_state(const str
const llama_hparams & hparams = ud->model->hparams;
const std::string tensor_name = tensor->name;
const std::regex pattern_q_weight ("blk\\.\\d*\\.attn_q.weight");
const std::regex pattern_kv_weight ("blk\\.\\d*\\.attn_(k|v).weight");
const std::regex pattern_qkv_weight ("blk\\.\\d*\\.attn_qkv.weight");
const std::regex pattern_q_bias ("blk\\.\\d*\\.attn_q\\.bias");
const std::regex pattern_kv_bias ("blk\\.\\d*\\.attn_(k|v)\\.bias");
const std::regex pattern_qkv_bias ("blk\\.\\d*\\.attn_qkv.bias");
const std::regex pattern_qk_norm ("blk\\.\\d*\\.attn_(q|k)_norm\\.weight");
const std::regex pattern_kv_cache ("cache_(k|v)_l\\d*");
const std::regex pattern_attn_sinks ("blk\\.\\d*\\.attn_sinks.weight");
const std::regex pattern_attn_out_weight ("blk\\.\\d*\\.attn_output.weight");
const std::regex pattern_attn_out_bias ("blk\\.\\d*\\.attn_output.bias");
const std::regex pattern_attn_gate_weight("blk\\.\\d*\\.attn_gate.weight");
static const std::regex pattern_q_weight ("blk\\.\\d*\\.attn_q.weight");
static const std::regex pattern_kv_weight ("blk\\.\\d*\\.attn_(k|v).weight");
static const std::regex pattern_qkv_weight ("blk\\.\\d*\\.attn_qkv.weight");
static const std::regex pattern_q_bias ("blk\\.\\d*\\.attn_q\\.bias");
static const std::regex pattern_kv_bias ("blk\\.\\d*\\.attn_(k|v)\\.bias");
static const std::regex pattern_qkv_bias ("blk\\.\\d*\\.attn_qkv.bias");
static const std::regex pattern_qk_norm ("blk\\.\\d*\\.attn_(q|k)_norm\\.weight");
static const std::regex pattern_kv_cache ("cache_(k|v)_l\\d*");
static const std::regex pattern_attn_sinks ("blk\\.\\d*\\.attn_sinks.weight");
static const std::regex pattern_attn_out_weight ("blk\\.\\d*\\.attn_output.weight");
static const std::regex pattern_attn_out_bias ("blk\\.\\d*\\.attn_output.bias");
static const std::regex pattern_attn_gate_weight("blk\\.\\d*\\.attn_gate.weight");
const std::regex pattern_ssm_dt ("blk\\.\\d*\\.ssm_dt.bias");
const std::regex pattern_ssm_a ("blk\\.\\d*\\.ssm_a");
const std::regex pattern_ssm_alpha ("blk\\.\\d*\\.ssm_alpha.weight");
const std::regex pattern_ssm_beta ("blk\\.\\d*\\.ssm_beta.weight");
const std::regex pattern_ssm_beta_alpha ("blk\\.\\d*\\.ssm_ba.weight");
const std::regex pattern_r_cache ("cache_r_l\\d*");
const std::regex pattern_s_cache ("cache_s_l\\d*");
const std::regex pattern_ssm_conv1d ("blk\\.\\d*\\.ssm_conv1d.weight");
const std::regex pattern_ssm_out_weight ("blk\\.\\d*\\.ssm_out.weight");
static const std::regex pattern_ssm_dt ("blk\\.\\d*\\.ssm_dt.bias");
static const std::regex pattern_ssm_a ("blk\\.\\d*\\.ssm_a");
static const std::regex pattern_ssm_alpha ("blk\\.\\d*\\.ssm_alpha.weight");
static const std::regex pattern_ssm_beta ("blk\\.\\d*\\.ssm_beta.weight");
static const std::regex pattern_ssm_beta_alpha ("blk\\.\\d*\\.ssm_ba.weight");
static const std::regex pattern_r_cache ("cache_r_l\\d*");
static const std::regex pattern_s_cache ("cache_s_l\\d*");
static const std::regex pattern_ssm_conv1d ("blk\\.\\d*\\.ssm_conv1d.weight");
static const std::regex pattern_ssm_out_weight ("blk\\.\\d*\\.ssm_out.weight");
const std::regex pattern_ffn_up_gate_weight("blk\\.\\d*\\.ffn_(up|gate)(_exps)?.weight");
const std::regex pattern_ffn_up_gate_bias ("blk\\.\\d*\\.ffn_(up|gate)(_exps)?.bias");
const std::regex pattern_ffn_gate_up_weight("blk\\.\\d*\\.ffn_gate_up(_exps)?.weight");
const std::regex pattern_ffn_down_weight ("blk\\.\\d*\\.ffn_down(_exps)?.weight");
const std::regex pattern_ffn_down_bias ("blk\\.\\d*\\.ffn_down.bias");
const std::regex pattern_ffn_down_exps_bias("blk\\.\\d*\\.ffn_down_exps.bias");
static const std::regex pattern_ffn_up_gate_weight("blk\\.\\d*\\.ffn_(up|gate)(_exps)?.weight");
static const std::regex pattern_ffn_up_gate_bias ("blk\\.\\d*\\.ffn_(up|gate)(_exps)?.bias");
static const std::regex pattern_ffn_gate_up_weight("blk\\.\\d*\\.ffn_gate_up(_exps)?.weight");
static const std::regex pattern_ffn_down_weight ("blk\\.\\d*\\.ffn_down(_exps)?.weight");
static const std::regex pattern_ffn_down_bias ("blk\\.\\d*\\.ffn_down.bias");
static const std::regex pattern_ffn_down_exps_bias("blk\\.\\d*\\.ffn_down_exps.bias");
const std::regex pattern_output_weight("output\\.weight");
const std::regex pattern_output_bias ("output\\.bias");
static const std::regex pattern_output_weight("output\\.weight");
static const std::regex pattern_output_bias ("output\\.bias");
struct tensor_config {
ggml_backend_meta_split_axis axis;
+10 -4
View File
@@ -568,10 +568,16 @@ static void handle_with_catch(const char * name, std::function<void()> func) {
}
}
// treat a null value as absent so clients can send null to request the server default
static bool has_value(const json & data, const char * n) {
auto it = data.find(n);
return it != data.end() && !it->is_null();
}
template <typename T>
void field_num<T>::eval(field_eval_context & ctx, const json & data) {
for (const auto & n : name) {
if (data.contains(n)) {
if (has_value(data, n)) {
handle_with_catch(n, [&]() {
if (custom_handler) {
custom_handler(ctx, data);
@@ -593,7 +599,7 @@ void field_num<T>::eval(field_eval_context & ctx, const json & data) {
void field_str::eval(field_eval_context & ctx, const json & data) {
GGML_ASSERT(custom_handler);
for (const auto & n : name) {
if (data.contains(n)) {
if (has_value(data, n)) {
handle_with_catch(n, [&]() {
custom_handler(ctx, data);
});
@@ -604,7 +610,7 @@ void field_str::eval(field_eval_context & ctx, const json & data) {
void field_bool::eval(field_eval_context & ctx, const json & data) {
for (const auto & n : name) {
if (data.contains(n)) {
if (has_value(data, n)) {
handle_with_catch(n, [&]() {
if (custom_handler) {
custom_handler(ctx, data);
@@ -620,7 +626,7 @@ void field_bool::eval(field_eval_context & ctx, const json & data) {
void field_json::eval(field_eval_context & ctx, const json & data) {
GGML_ASSERT(custom_handler);
for (const auto & n : name) {
if (data.contains(n)) {
if (has_value(data, n)) {
handle_with_catch(n, [&]() {
custom_handler(ctx, data);
});