vbatts/llama.cpp
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renamed ggml_backend functions
changed ggml_buffer and ggml_backend to always be used as pointers
rename ggml_tensor::params -> op_params
This commit is contained in:
slaren 2023-07-17 19:03:51 +02:00
parent 1102ff56db
commit 295f85654a
8 changed files with 640 additions and 365 deletions
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78
ggml.c
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@ -4393,7 +4393,7 @@ struct ggml_context * ggml_init(struct ggml_init_params params) {
/*.compute_type =*/ params.compute_type,
};
ggml_backend_reset_buffer(params.buffer);
ggml_backend_buffer_reset(params.buffer->backend_buffer);
GGML_ASSERT(ctx->mem_buffer != NULL);
@ -4526,17 +4526,17 @@ struct ggml_tensor * ggml_new_tensor_impl(
/*.ne =*/ { 1, 1, 1, 1 },
/*.nb =*/ { 0, 0, 0, 0 },
/*.op =*/ GGML_OP_NONE,
/*.op_params =*/ { 0 },
/*.is_param =*/ false,
/*.grad =*/ NULL,
/*.src =*/ { NULL },
/*.node_id =*/ -1,
/*.perf_runs =*/ 0,
/*.perf_cycles =*/ 0,
/*.perf_time_us =*/ 0,
/*.params =*/ { 0 },
/*.data =*/ data,
/*.name =*/ { 0 },
/*.extra =*/ NULL,
/*.visited =*/ false,
/*.pad =*/ { 0 },
};
@ -4551,7 +4551,7 @@ struct ggml_tensor * ggml_new_tensor_impl(
}
if (data == NULL && !ctx->no_alloc) {
ggml_backend_alloc_tensor(ctx->buffer, result);
ggml_backend_buffer_tensor_alloc(ctx->buffer->backend_buffer, result);
}
// TODO: this should not be needed as long as we don't rely on aligned SIMD loads
@ -4730,7 +4730,7 @@ struct ggml_tensor * ggml_set_f32(struct ggml_tensor * tensor, float value) {
}
*/
for (int i = 0; i < ggml_nelements(tensor); i++) {
ggml_backend_set_tensor(tensor, &value, sizeof(float)*i, sizeof(float));
ggml_backend_tensor_set(tensor, &value, sizeof(float)*i, sizeof(float));
}
} break;
default:
@ -4839,7 +4839,7 @@ float ggml_get_f32_1d(const struct ggml_tensor * tensor, int i) {
GGML_ASSERT(tensor->nb[0] == sizeof(float));
//return ((float *)(tensor->data))[i];
float value;
ggml_backend_get_tensor(tensor, &value, sizeof(float)*i, sizeof(float));
ggml_backend_tensor_get(tensor, &value, sizeof(float)*i, sizeof(float));
return value;
} break;
default:
@ -4912,6 +4912,11 @@ struct ggml_tensor * ggml_format_name(struct ggml_tensor * tensor, const char *
return tensor;
}
static void ggml_set_op_params(struct ggml_tensor * tensor, void * params, size_t params_size) {
GGML_ASSERT(params_size <= GGML_MAX_OP_PARAMS);
memcpy(tensor->op_params, params, params_size);
}
struct ggml_tensor * ggml_view_tensor(
struct ggml_context * ctx,
const struct ggml_tensor * src) {
@ -6385,8 +6390,7 @@ struct ggml_tensor * ggml_view_1d(
struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 1, &ne0, (char *) a->data + offset);
ggml_format_name(result, "%s (view)", a->name);
assert(GGML_MAX_OP_PARAMS >= sizeof(offset));
memcpy(result->params, &offset, sizeof(offset));
ggml_set_op_params(result, &offset, sizeof(offset));
result->op = GGML_OP_VIEW;
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
@ -6417,8 +6421,7 @@ struct ggml_tensor * ggml_view_2d(
struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 2, ne, (char *) a->data + offset);
ggml_format_name(result, "%s (view)", a->name);
assert(GGML_MAX_OP_PARAMS >= sizeof(offset));
memcpy(result->params, &offset, sizeof(offset));
ggml_set_op_params(result, &offset, sizeof(offset));
result->nb[1] = nb1;
result->nb[2] = result->nb[1]*ne1;
@ -6455,8 +6458,7 @@ struct ggml_tensor * ggml_view_3d(
struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 3, ne, (char *) a->data + offset);
ggml_format_name(result, "%s (view)", a->name);
assert(GGML_MAX_OP_PARAMS >= sizeof(offset));
memcpy(result->params, &offset, sizeof(offset));
ggml_set_op_params(result, &offset, sizeof(offset));
result->nb[1] = nb1;
result->nb[2] = nb2;
@ -6495,8 +6497,7 @@ struct ggml_tensor * ggml_view_4d(
struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 4, ne, (char *) a->data + offset);
ggml_format_name(result, "%s (view)", a->name);
assert(GGML_MAX_OP_PARAMS >= sizeof(offset));
memcpy(result->params, &offset, sizeof(offset));
ggml_set_op_params(result, &offset, sizeof(offset));
result->nb[1] = nb1;
result->nb[2] = nb2;
@ -6569,8 +6570,7 @@ struct ggml_tensor * ggml_permute(
result->src[1] = NULL;
int32_t params[] = { axis0, axis1, axis2, axis3 };
assert(GGML_MAX_OP_PARAMS >= sizeof(params));
memcpy(result->params, params, sizeof(params));
ggml_set_op_params(result, &params, sizeof(params));
return result;
}
@ -6694,8 +6694,7 @@ struct ggml_tensor * ggml_diag_mask_inf_impl(
struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
int32_t params[] = { n_past, inplace ? 1 : 0 };
assert(GGML_MAX_OP_PARAMS >= sizeof(params));
memcpy(result->params, params, sizeof(params));
ggml_set_op_params(result, &params, sizeof(params));
result->op = GGML_OP_DIAG_MASK_INF;
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
@ -6854,12 +6853,10 @@ struct ggml_tensor * ggml_rope_impl(
struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
// TODO: just use a struct
int32_t params[6] = { n_past, n_dims, mode, n_ctx };
memcpy(params + 4, &freq_base, sizeof(float));
memcpy(params + 5, &freq_scale, sizeof(float));
assert(GGML_MAX_OP_PARAMS >= sizeof(params));
memcpy(result->params, &params, sizeof(params));
ggml_set_op_params(result, &params, sizeof(params));
result->op = GGML_OP_ROPE;
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
@ -11392,8 +11389,8 @@ static void ggml_compute_forward_diag_mask_f32(
const int ith = params->ith;
const int nth = params->nth;
const int n_past = ((int32_t *) dst->params)[0];
const bool inplace = (bool)((int32_t *) dst->params)[1];
const int n_past = ((int32_t *) dst->op_params)[0];
const bool inplace = (bool)((int32_t *) dst->op_params)[1];
GGML_ASSERT(n_past >= 0);
@ -11910,12 +11907,12 @@ static void ggml_compute_forward_rope_f32(
float freq_base;
float freq_scale;
const int n_past = ((int32_t *) dst->params)[0];
const int n_dims = ((int32_t *) dst->params)[1];
const int mode = ((int32_t *) dst->params)[2];
const int n_ctx = ((int32_t *) dst->params)[3];
memcpy(&freq_base, (int32_t *) dst->params + 4, sizeof(float));
memcpy(&freq_scale, (int32_t *) dst->params + 5, sizeof(float));
const int n_past = ((int32_t *) dst->op_params)[0];
const int n_dims = ((int32_t *) dst->op_params)[1];
const int mode = ((int32_t *) dst->op_params)[2];
const int n_ctx = ((int32_t *) dst->op_params)[3];
memcpy(&freq_base, (int32_t *) dst->op_params + 4, sizeof(float));
memcpy(&freq_scale, (int32_t *) dst->op_params + 5, sizeof(float));
assert(n_past >= 0);
@ -12039,12 +12036,12 @@ static void ggml_compute_forward_rope_f16(
float freq_base;
float freq_scale;
const int n_past = ((int32_t *) dst->params)[0];
const int n_dims = ((int32_t *) dst->params)[1];
const int mode = ((int32_t *) dst->params)[2];
const int n_ctx = ((int32_t *) dst->params)[3];
memcpy(&freq_base, (int32_t *) dst->params + 4, sizeof(float));
memcpy(&freq_scale, (int32_t *) dst->params + 5, sizeof(float));
const int n_past = ((int32_t *) dst->op_params)[0];
const int n_dims = ((int32_t *) dst->op_params)[1];
const int mode = ((int32_t *) dst->op_params)[2];
const int n_ctx = ((int32_t *) dst->op_params)[3];
memcpy(&freq_base, (int32_t *) dst->op_params + 4, sizeof(float));
memcpy(&freq_scale, (int32_t *) dst->op_params + 5, sizeof(float));
assert(n_past >= 0);
@ -15810,10 +15807,9 @@ static void ggml_visit_parents(struct ggml_cgraph * cgraph, struct ggml_tensor *
}
// check if already visited
if (node->visited) {
if (node->node_id != -1) {
return;
}
node->visited = true;
for (int i = 0; i < GGML_MAX_SRC; ++i) {
if (node->src[i]) {
@ -15821,6 +15817,8 @@ static void ggml_visit_parents(struct ggml_cgraph * cgraph, struct ggml_tensor *
}
}
//node->id = cgraph->n_nodes + cgraph->n_leafs;
// TODO: add ggml_dependency instead of checking for NULL
if (node->op == GGML_OP_NONE && node->src[0] == NULL && node->src[1] == NULL && node->grad == NULL) {
// reached a leaf node, not part of the gradient graph (e.g. a constant)
@ -15830,6 +15828,7 @@ static void ggml_visit_parents(struct ggml_cgraph * cgraph, struct ggml_tensor *
ggml_format_name(node, "leaf_%d", cgraph->n_leafs);
}
node->node_id = cgraph->n_leafs;
cgraph->leafs[cgraph->n_leafs] = node;
cgraph->n_leafs++;
} else {
@ -15839,6 +15838,7 @@ static void ggml_visit_parents(struct ggml_cgraph * cgraph, struct ggml_tensor *
ggml_format_name(node, "node_%d", cgraph->n_nodes);
}
node->node_id = cgraph->n_nodes;
cgraph->nodes[cgraph->n_nodes] = node;
cgraph->grads[cgraph->n_nodes] = node->grad;
cgraph->n_nodes++;
@ -15872,10 +15872,10 @@ void ggml_build_forward_expand(struct ggml_cgraph * cgraph, struct ggml_tensor *
// TODO: this can be removed when ggml_build_forward_expand is removed
void ggml_graph_close(struct ggml_cgraph * cgraph) {
for (int i = 0; i < cgraph->n_nodes; ++i) {
cgraph->nodes[i]->visited = false;
cgraph->nodes[i]->node_id = -1;
}
for (int i = 0; i < cgraph->n_leafs; ++i) {
cgraph->leafs[i]->visited = false;
cgraph->leafs[i]->node_id = -1;
}
cgraph->closed = true;
}