mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-26 03:14:35 +00:00
add google magika inference example (ggml/748)
* add magika inference example * ggml : fix unaligned accesses in custom ops * ggml : fix FP32 GELU for values that exceed the FP16 range * use ggml_pool_1d * add README * Update README.md * pad inputs if the files are too small * cleanup ggml-ci
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ggml.c
48
ggml.c
@ -1608,11 +1608,17 @@ inline static void ggml_vec_gelu_f16(const int n, ggml_fp16_t * y, const ggml_fp
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inline static void ggml_vec_gelu_f32(const int n, float * y, const float * x) {
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inline static void ggml_vec_gelu_f32(const int n, float * y, const float * x) {
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uint16_t t;
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uint16_t t;
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for (int i = 0; i < n; ++i) {
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for (int i = 0; i < n; ++i) {
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if (x[i] <= -10.0f) {
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y[i] = 0.0f;
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} else if (x[i] >= 10.0f) {
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y[i] = x[i];
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} else {
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ggml_fp16_t fp16 = GGML_FP32_TO_FP16(x[i]);
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ggml_fp16_t fp16 = GGML_FP32_TO_FP16(x[i]);
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memcpy(&t, &fp16, sizeof(uint16_t));
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memcpy(&t, &fp16, sizeof(uint16_t));
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y[i] = GGML_FP16_TO_FP32(ggml_table_gelu_f16[t]);
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y[i] = GGML_FP16_TO_FP32(ggml_table_gelu_f16[t]);
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}
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}
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}
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}
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}
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#else
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#else
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inline static void ggml_vec_gelu_f32(const int n, float * y, const float * x) {
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inline static void ggml_vec_gelu_f32(const int n, float * y, const float * x) {
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for (int i = 0; i < n; ++i) {
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for (int i = 0; i < n; ++i) {
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@ -5780,11 +5786,13 @@ struct ggml_tensor * ggml_pool_1d(
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is_node = true;
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is_node = true;
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}
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}
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const int64_t ne[2] = {
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const int64_t ne[4] = {
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ggml_calc_pool_output_size(a->ne[0], k0, s0, p0),
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ggml_calc_pool_output_size(a->ne[0], k0, s0, p0),
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a->ne[1],
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a->ne[1],
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a->ne[2],
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a->ne[3],
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};
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};
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struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, 2, ne);
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struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne);
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int32_t params[] = { op, k0, s0, p0 };
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int32_t params[] = { op, k0, s0, p0 };
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ggml_set_op_params(result, params, sizeof(params));
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ggml_set_op_params(result, params, sizeof(params));
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@ -15081,9 +15089,10 @@ static void ggml_compute_forward_map_custom1(
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return;
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return;
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}
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}
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struct ggml_map_custom1_op_params * p = (struct ggml_map_custom1_op_params *) dst->op_params;
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struct ggml_map_custom1_op_params p;
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memcpy(&p, dst->op_params, sizeof(p));
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p->fun(dst, a, params->ith, params->nth, p->userdata);
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p.fun(dst, a, params->ith, params->nth, p.userdata);
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}
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}
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// ggml_compute_forward_map_custom2
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// ggml_compute_forward_map_custom2
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@ -15099,9 +15108,10 @@ static void ggml_compute_forward_map_custom2(
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return;
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return;
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}
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}
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struct ggml_map_custom2_op_params * p = (struct ggml_map_custom2_op_params *) dst->op_params;
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struct ggml_map_custom2_op_params p;
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memcpy(&p, dst->op_params, sizeof(p));
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p->fun(dst, a, b, params->ith, params->nth, p->userdata);
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p.fun(dst, a, b, params->ith, params->nth, p.userdata);
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}
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}
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// ggml_compute_forward_map_custom3
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// ggml_compute_forward_map_custom3
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@ -15118,9 +15128,10 @@ static void ggml_compute_forward_map_custom3(
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return;
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return;
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}
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}
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struct ggml_map_custom3_op_params * p = (struct ggml_map_custom3_op_params *) dst->op_params;
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struct ggml_map_custom3_op_params p;
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memcpy(&p, dst->op_params, sizeof(p));
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p->fun(dst, a, b, c, params->ith, params->nth, p->userdata);
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p.fun(dst, a, b, c, params->ith, params->nth, p.userdata);
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}
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}
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// ggml_compute_forward_cross_entropy_loss
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// ggml_compute_forward_cross_entropy_loss
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@ -17386,29 +17397,32 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) {
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} break;
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} break;
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case GGML_OP_MAP_CUSTOM1:
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case GGML_OP_MAP_CUSTOM1:
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{
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{
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struct ggml_map_custom1_op_params * p = (struct ggml_map_custom1_op_params *) node->op_params;
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struct ggml_map_custom1_op_params p;
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if (p->n_tasks == GGML_N_TASKS_MAX) {
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memcpy(&p, node->op_params, sizeof(p));
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if (p.n_tasks == GGML_N_TASKS_MAX) {
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n_tasks = n_threads;
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n_tasks = n_threads;
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} else {
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} else {
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n_tasks = MIN(p->n_tasks, n_threads);
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n_tasks = MIN(p.n_tasks, n_threads);
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}
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}
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} break;
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} break;
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case GGML_OP_MAP_CUSTOM2:
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case GGML_OP_MAP_CUSTOM2:
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{
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{
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struct ggml_map_custom2_op_params * p = (struct ggml_map_custom2_op_params *) node->op_params;
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struct ggml_map_custom2_op_params p;
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if (p->n_tasks == GGML_N_TASKS_MAX) {
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memcpy(&p, node->op_params, sizeof(p));
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if (p.n_tasks == GGML_N_TASKS_MAX) {
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n_tasks = n_threads;
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n_tasks = n_threads;
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} else {
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} else {
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n_tasks = MIN(p->n_tasks, n_threads);
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n_tasks = MIN(p.n_tasks, n_threads);
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}
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}
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} break;
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} break;
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case GGML_OP_MAP_CUSTOM3:
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case GGML_OP_MAP_CUSTOM3:
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{
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{
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struct ggml_map_custom3_op_params * p = (struct ggml_map_custom3_op_params *) node->op_params;
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struct ggml_map_custom3_op_params p;
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if (p->n_tasks == GGML_N_TASKS_MAX) {
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memcpy(&p, node->op_params, sizeof(p));
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if (p.n_tasks == GGML_N_TASKS_MAX) {
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n_tasks = n_threads;
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n_tasks = n_threads;
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} else {
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} else {
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n_tasks = MIN(p->n_tasks, n_threads);
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n_tasks = MIN(p.n_tasks, n_threads);
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}
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}
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} break;
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} break;
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case GGML_OP_CROSS_ENTROPY_LOSS:
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case GGML_OP_CROSS_ENTROPY_LOSS:
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