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llama.cpp
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Improve debug util; Eliminate nop ReshapeReshape

This commit is contained in:
Yu, Zijun 2025-09-10 15:38:15 +08:00 committed by Mustafa Cavus
parent 0f7b253cb3
commit 2ad1147b9b
3 changed files with 65 additions and 24 deletions
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27
ggml/src/ggml-openvino/ggml-decoder.cpp
View File

@ -154,22 +154,22 @@ void GgmlOvDecoder::set_input_output(ggml_tensor* node, bool naive) {
// Add model outputs, if called for the whole graph
if (naive) {
m_model_output_names.push_back(node->name);
m_model_output_names.push_back(node_name);
} else if (!m_node) {
// Model outputs are tensors with GGML_TENSOR_FLAG_OUTPUT flag and kv_caches
static std::set<std::string> debug_output_names = {};
// Workaround: the final tensor "result_output" does not have GGML_TENSOR_FLAG_OUTPUT flag set in cgraph
if (node->buffer->usage == GGML_BACKEND_BUFFER_USAGE_ANY || node->flags & GGML_TENSOR_FLAG_OUTPUT ||
std::string(node->name).find("result") == 0 || debug_output_names.count(node->name)) {
auto name = node->view_src ? std::string(node->view_src->name) : std::string(node->name);
if (node->buffer->usage == GGML_BACKEND_BUFFER_USAGE_ANY) {
assert(name.find("cache_k") == 0 || name.find("cache_v") == 0);
if (node->op == GGML_OP_SET_ROWS || node->flags & GGML_TENSOR_FLAG_OUTPUT || node_name.find("result") == 0 ||
debug_output_names.count(node_name)) {
if (node->op == GGML_OP_SET_ROWS) {
assert(node_name.find("cache_k") == 0 || node_name.find("cache_v") == 0);
if (auto it = std::find(m_kv_names.begin(), m_kv_names.end(), node_name); it == m_kv_names.end()) {
m_kv_names.push_back(node_name);
}
}
if (auto it = std::find(m_model_output_names.begin(), m_model_output_names.end(), name);
if (auto it = std::find(m_model_output_names.begin(), m_model_output_names.end(), node_name);
it == m_model_output_names.end()) {
m_model_output_names.push_back(name);
}
if (auto it = std::find(m_kv_names.begin(), m_kv_names.end(), name); it == m_kv_names.end()) {
m_kv_names.push_back(name);
m_model_output_names.push_back(node_name);
}
}
}
@ -177,7 +177,10 @@ void GgmlOvDecoder::set_input_output(ggml_tensor* node, bool naive) {
if (m_node) {
switch (node->op) {
case GGML_OP_RESHAPE: {
if (node->ne[0] * node->ne[1] == node->src[0]->ne[0]) {
if (node->src[0]->op == GGML_OP_RESHAPE && node->src[0]->src[0]->ne[0] == node->ne[0] &&
node->src[0]->src[0]->ne[1] == node->ne[1]) {
m_op_case = 4;
} else if (node->ne[0] * node->ne[1] == node->src[0]->ne[0]) {
m_op_case = 1;
} else if (node->src[0]->ne[0] * node->src[0]->ne[1] == node->ne[0]) {
m_op_case = 2;

7
ggml/src/ggml-openvino/openvino/op/reshape.cpp
View File

@ -23,7 +23,8 @@ OutputVector translate_reshape(const NodeContext& context) {
}
int op_case = context.get_op_case();
FRONT_END_CHECK_IMPLEMENTED(op_case == 1 || op_case == 2 || op_case == 3, "Unsupported RESHAPE case");
FRONT_END_CHECK_IMPLEMENTED(op_case == 1 || op_case == 2 || op_case == 3 || op_case == 4,
"Unsupported RESHAPE case");
auto output_shape = context.get_output_shape(0).to_shape();
std::shared_ptr<ov::Node> new_shape_node;
@ -37,9 +38,11 @@ OutputVector translate_reshape(const NodeContext& context) {
ov::op::v0::Constant::create(ov::element::i64,
{3},
std::vector<int64_t>{(int64_t)output_shape[0], -1, (int64_t)output_shape[2]});
} else {
} else if (op_case == 3) {
new_shape_node =
ov::op::v0::Constant::create(ov::element::i64, {3}, std::vector<int64_t>{(int64_t) output_shape[0], -1, 1});
} else if (op_case == 4) {
return {context.get_input(0).get_node_shared_ptr()->input_value(0)};
}
auto res = std::make_shared<ov::op::v1::Reshape>(context.get_input(0), new_shape_node, false);
return rename_outputs_with_suffix({res}, context.get_name());

55
ggml/src/ggml-openvino/utils.cpp
View File

@ -6,6 +6,8 @@
#include <cstddef>
#include <cstdint>
#include <cstdlib>
#include <iomanip>
#include <iostream>
#include <memory>
#include <mutex>
#include <openvino/core/any.hpp>
@ -418,17 +420,50 @@ void print_output_tensor_info(const std::string& name, const ov::Tensor& tensor,
std::map<std::string, void*>& output_dst) {
std::cout << "Output name: " << name << ", Output shape: " << tensor.get_shape()
<< ", Address: " << output_dst[name] << std::endl;
auto print_float_stats = [](const std::string& type_name, size_t size, auto get_value) {
if (size == 0) {
return;
}
float first = get_value(0);
float min = first;
float max = first;
double sum = first;
for (size_t i = 1; i < size; ++i) {
float v = get_value(i);
if (v < min) {
min = v;
}
if (v > max) {
max = v;
}
sum += v;
}
double mean = sum / size;
std::cout << std::right << std::setw(6) << type_name << std::right << std::setw(12) << "First" << std::setw(12)
<< "Min" << std::setw(12) << "Max" << std::setw(12) << "Mean" << std::endl;
std::cout << std::right << std::setw(6) << "" << std::right << std::setw(12) << first << std::setw(12) << min
<< std::setw(12) << max << std::setw(12) << mean << std::endl;
};
switch (tensor.get_element_type()) {
case ov::element::f32:
std::cout << *(tensor.data<float>()) << std::endl;
std::cout << checksum(tensor.data(), tensor.get_byte_size()) << std::endl;
break;
case ov::element::f16:
std::cout << *(tensor.data<ov::float16>()) << std::endl;
std::cout << checksum(tensor.data(), tensor.get_byte_size()) << std::endl;
break;
default:
break;
case ov::element::f32: {
const float* data = tensor.data<float>();
size_t size = tensor.get_size();
print_float_stats("[f32]", size, [data](size_t i) { return data[i]; });
break;
}
case ov::element::f16: {
const ov::float16* data = tensor.data<ov::float16>();
size_t size = tensor.get_size();
print_float_stats("[f16]", size, [data](size_t i) { return static_cast<float>(data[i]); });
break;
}
default:
break;
}
}