mirror of
https://github.com/ikawrakow/ik_llama.cpp.git
synced 2026-02-24 23:24:13 +00:00
Revert "Do not quantize activations if not necessary (#79)"
This reverts commit 0bf4d99774.
This commit is contained in:
@@ -724,7 +724,6 @@ extern "C" {
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// since https://github.com/ggerganov/ggml/issues/287
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struct ggml_cplan {
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size_t work_size; // size of work buffer, calculated by `ggml_graph_plan()`
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size_t q_size;
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uint8_t * work_data; // work buffer, to be allocated by caller before calling to `ggml_graph_compute()`
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int n_threads;
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@@ -2586,7 +2586,6 @@ struct ggml_compute_params {
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// work buffer for all threads
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size_t wsize;
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size_t qsize;
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void * wdata;
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struct ggml_compute_state_shared * shared;
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@@ -14110,12 +14109,7 @@ UseGgmlGemm1:;
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#endif
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if (src1->type != vec_dot_type) {
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char * wdata = (char *)params->wdata + params->wsize - params->qsize;
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if (strncmp(src1->name, wdata - GGML_MAX_NAME, GGML_MAX_NAME) == 0) {
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goto AlreadyQuantized;
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}
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wdata += GGML_MAX_NAME;
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char * wdata = params->wdata;
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#if IK_PRINT_TIMING
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int64_t t1 = ggml_time_us();
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@@ -14125,7 +14119,7 @@ UseGgmlGemm1:;
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const size_t nbw2 = nbw1*ne11;
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const size_t nbw3 = nbw2*ne12;
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assert(params->qsize >= ne13*nbw3);
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assert(params->wsize >= ne13*nbw3);
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GGML_ASSERT(src1->type == GGML_TYPE_F32);
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for (int64_t i13 = 0; i13 < ne13; ++i13) {
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@@ -14157,17 +14151,14 @@ UseGgmlGemm1:;
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#endif
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if (ith == 0) {
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wdata -= GGML_MAX_NAME;
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memcpy(wdata, src1->name, GGML_MAX_NAME);
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// Every thread starts at ith, so the first unprocessed chunk is nth. This save a bit of coordination right at the start.
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//atomic_store(¶ms->shared->current_chunk, nth);
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}
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AlreadyQuantized:;
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ggml_barrier(params->shared);
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}
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const void * wdata = (src1->type == vec_dot_type) ? src1->data
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: (const void *)((const char *)params->wdata + params->wsize - params->qsize + GGML_MAX_NAME);
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const void * wdata = (src1->type == vec_dot_type) ? src1->data : params->wdata;
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#if GGML_USE_IQK_MULMAT
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if (src1->type != vec_dot_type && dst->type == GGML_TYPE_F32) {
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@@ -14354,10 +14345,9 @@ static void ggml_compute_forward_mul_mat_id(
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const int n_ids = ids->ne[0]; // n_expert_used
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const int n_as = ne02; // n_expert
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char * qdata = (char *)params->wdata + params->wsize - params->qsize;
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char * wdata_src1_end = (src1->type == vec_dot_type) ? qdata :
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qdata + GGML_PAD(GGML_MAX_NAME + ggml_row_size(vec_dot_type, ggml_nelements(src1)), sizeof(int64_t));
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char * wdata_src1_end = (src1->type == vec_dot_type) ?
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(char *) params->wdata :
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(char *) params->wdata + GGML_PAD(ggml_row_size(vec_dot_type, ggml_nelements(src1)), sizeof(int64_t));
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struct mmid_row_mapping {
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int32_t i1;
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@@ -14367,19 +14357,14 @@ static void ggml_compute_forward_mul_mat_id(
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int64_t * matrix_row_counts = (int64_t *) (wdata_src1_end); // [n_as]
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struct mmid_row_mapping * matrix_rows = (struct mmid_row_mapping *)(matrix_row_counts + n_as); // [n_as][ne11]
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bool store_name = false;
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if (src1->type != vec_dot_type) {
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if (strncmp(src1->name, qdata, GGML_MAX_NAME) == 0) {
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goto QuantizationAlreadyDone;
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}
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store_name = true;
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char * wdata = qdata + GGML_MAX_NAME;
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char * wdata = params->wdata;
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const size_t nbw1 = ggml_row_size(vec_dot_type, ne10);
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const size_t nbw2 = nbw1*ne11;
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const size_t nbw3 = nbw2*ne12;
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assert(params->qsize >= ne13*nbw3);
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assert(params->wsize >= ne13*nbw3);
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GGML_ASSERT(src1->type == GGML_TYPE_F32);
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for (int64_t i13 = 0; i13 < ne13; ++i13) {
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@@ -14395,12 +14380,7 @@ static void ggml_compute_forward_mul_mat_id(
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#define MMID_MATRIX_ROW(row_id, i1) matrix_rows[(row_id)*ne12 + (i1)]
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QuantizationAlreadyDone:;
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if (ith == 0) {
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if (store_name) {
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memcpy(qdata, src1->name, GGML_MAX_NAME);
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}
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// initialize matrix_row_counts
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memset(matrix_row_counts, 0, n_as*sizeof(int64_t));
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@@ -14429,7 +14409,7 @@ QuantizationAlreadyDone:;
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const char * src0_cur = (const char *) src0->data + cur_a*nb02;
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const void * wdata = (src1->type == vec_dot_type) ? src1->data : qdata + GGML_MAX_NAME;
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const void * wdata = (src1->type == vec_dot_type) ? src1->data : params->wdata;
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const size_t row_size = ggml_row_size(vec_dot_type, ne10);
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const int64_t nr0 = ne01; // src0 rows
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@@ -21017,7 +20997,6 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa
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}
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size_t work_size = 0;
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size_t q_size = 0;
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struct ggml_cplan cplan;
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memset(&cplan, 0, sizeof(struct ggml_cplan));
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@@ -21033,7 +21012,6 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa
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max_tasks = MAX(max_tasks, n_tasks);
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size_t cur = 0;
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size_t cur_q = 0;
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switch (node->op) {
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case GGML_OP_CPY:
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@@ -21064,8 +21042,7 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa
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const enum ggml_type vec_dot_type = type_traits[node->src[0]->type].vec_dot_type;
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if (node->src[1]->type != vec_dot_type) {
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cur_q = ggml_row_size(vec_dot_type, node->src[1]->ne[0]) * ggml_nrows(node->src[1]);
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//cur_q = ggml_row_size(vec_dot_type, ggml_nelements(node->src[1]));
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cur = ggml_row_size(vec_dot_type, node->src[1]->ne[0]) * ggml_nrows(node->src[1]);
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}
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} break;
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case GGML_OP_MUL_MAT_ID:
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@@ -21075,13 +21052,12 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa
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const struct ggml_tensor * src1 = node->src[1];
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const enum ggml_type vec_dot_type = type_traits[src0->type].vec_dot_type;
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if (src1->type != vec_dot_type) {
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cur_q += ggml_row_size(vec_dot_type, node->src[1]->ne[0]) * ggml_nrows(node->src[1]);
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//cur_q += ggml_row_size(vec_dot_type, ggml_nelements(src1));
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cur += ggml_row_size(vec_dot_type, node->src[1]->ne[0]) * ggml_nrows(node->src[1]);
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}
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const int n_as = src0->ne[2];
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cur_q += GGML_PAD(cur, sizeof(int64_t)); // align
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cur_q += n_as * sizeof(int64_t); // matrix_row_counts
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cur_q += n_as * src1->ne[2] * sizeof(int64_t); // matrix_rows
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cur += GGML_PAD(cur, sizeof(int64_t)); // align
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cur += n_as * sizeof(int64_t); // matrix_row_counts
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cur += n_as * src1->ne[2] * sizeof(int64_t); // matrix_rows
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} break;
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case GGML_OP_OUT_PROD:
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{
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@@ -21170,20 +21146,14 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa
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}
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work_size = MAX(work_size, cur);
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q_size = MAX(q_size, cur_q);
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}
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if (work_size > 0) {
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work_size += CACHE_LINE_SIZE*(n_threads - 1);
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}
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if (q_size > 0) {
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q_size += GGML_MAX_NAME;
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}
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work_size += q_size;
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cplan.n_threads = MIN(max_tasks, n_threads);
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cplan.work_size = work_size;
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cplan.q_size = q_size;
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cplan.work_data = NULL;
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return cplan;
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@@ -21201,7 +21171,6 @@ static thread_ret_t ggml_graph_compute_thread(void * data) {
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/*.ith =*/ state->ith,
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/*.nth =*/ state->shared->n_threads,
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/*.wsize =*/ cplan->work_size,
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/*.qsize =*/ cplan->q_size,
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/*.wdata =*/ cplan->work_data,
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/*.shared=*/ state->shared,
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};
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