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CANN: Improve ACL graph matching (#16166)

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* CANN: improve ACL graph matching

Record `ne` and `nb` information for src tensors and include them in the
graph matching check. This enhances the robustness of ACL graph matching
by preventing incorrect matches when src tensors share the same data
address but differ in shape or stride.

* CANN: add op_params match
This commit is contained in:
Chenguang Li
2025-10-09 15:50:25 +08:00
committed by GitHub
parent d80d6d2400
commit aa4711d369
2 changed files with 45 additions and 12 deletions
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ggml/src/ggml-cann/ggml-cann.cpp
+37 -11
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@@ -2186,7 +2186,15 @@ static void add_lru_matched_graph_node_properties(
std::copy_n(node->nb, GGML_MAX_DIMS, prop.nb);
for (int src = 0; src < GGML_MAX_SRC; ++src) {
prop.src_address[src] = node->src[src] ? node->src[src]->data : nullptr;
if (node->src[src]) {
prop.src_address[src] = node->src[src]->data;
std::copy_n(node->src[src]->ne, GGML_MAX_DIMS, prop.src_ne[src]);
std::copy_n(node->src[src]->nb, GGML_MAX_DIMS, prop.src_nb[src]);
} else {
prop.src_address[src] = nullptr;
std::fill_n(prop.src_ne[src], GGML_MAX_DIMS, 0);
std::fill_n(prop.src_nb[src], GGML_MAX_DIMS, 0);
}
}
memcpy(prop.op_params, node->op_params, GGML_MAX_OP_PARAMS);
@@ -2206,14 +2214,18 @@ static void add_lru_matched_graph_node_properties(
* @param graph_node_properties The stored properties of a CANN graph node.
* @return true if all fields match (excluding GGML_OP_VIEW); false otherwise.
*/
static bool ggml_graph_node_has_matching_properties(ggml_tensor * node, ggml_graph_node_properties * graph_node_properties) {
static bool ggml_graph_node_has_matching_properties(
ggml_tensor * node,
ggml_graph_node_properties * graph_node_properties) {
if (node->data != graph_node_properties->node_address &&
node->op != GGML_OP_VIEW) {
node->op != GGML_OP_VIEW) {
return false;
}
if (node->op != graph_node_properties->node_op) {
return false;
}
for (int i = 0; i < GGML_MAX_DIMS; i++) {
if (node->ne[i] != graph_node_properties->ne[i]) {
return false;
@@ -2222,17 +2234,31 @@ static bool ggml_graph_node_has_matching_properties(ggml_tensor * node, ggml_gra
return false;
}
}
for (int i = 0; i < GGML_MAX_SRC; i++) {
if (node->src[i] &&
node->src[i]->data != graph_node_properties->src_address[i] &&
node->op != GGML_OP_VIEW
) {
return false;
if (node->src[i]) {
if (node->src[i]->data != graph_node_properties->src_address[i] &&
node->op != GGML_OP_VIEW) {
return false;
}
for (int d = 0; d < GGML_MAX_DIMS; d++) {
if (node->src[i]->ne[d] != graph_node_properties->src_ne[i][d]) {
return false;
}
if (node->src[i]->nb[d] != graph_node_properties->src_nb[i][d]) {
return false;
}
}
} else {
if (graph_node_properties->src_address[i] != nullptr) {
return false;
}
}
}
if (node->op == GGML_OP_SCALE &&
memcmp(graph_node_properties->op_params, node->op_params, GGML_MAX_OP_PARAMS) != 0) {
return false;
if (node->op == GGML_OP_SCALE || node->op == GGML_OP_UNARY || node->op == GGML_OP_GLU) {
return memcmp(graph_node_properties->op_params, node->op_params, GGML_MAX_OP_PARAMS) == 0;
}
return true;
}