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Centralize and document TRACE tags using X-macros (#7657)

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* Introduce X-macro-based trace tag definition
- Created trace_tags.def to centralize TRACE tag definitions
- Each tag includes a symbolic name and description
- Set up enum class TraceTag for type-safe usage in TRACE macros

* Add script to generate Markdown documentation from trace_tags.def
- Python script parses trace_tags.def and outputs trace_tags.md

* Refactor TRACE_NEW to prepend TraceTag and pass enum to is_trace_enabled

* trace: improve trace tag handling system with hierarchical tagging

- Introduce hierarchical tag-class structure: enabling a tag class activates all child tags
- Unify TRACE, STRACE, SCTRACE, and CTRACE under enum TraceTag
- Implement initial version of trace_tag.def using X(tag, tag_class, description)
  (class names and descriptions to be refined in a future update)

* trace: replace all string-based TRACE tags with enum TraceTag
- Migrated all TRACE, STRACE, SCTRACE, and CTRACE macros to use enum TraceTag values instead of raw string literals

* trace : add cstring header

* trace : Add Markdown documentation generation from trace_tags.def via mk_api_doc.py

* trace : rename macro parameter 'class' to 'tag_class' and remove Unicode comment in trace_tags.h.

* trace : Add TODO comment for future implementation of tag_class activation

* trace : Disable code related to tag_class until implementation is ready (#7663).
This commit is contained in:
LeeYoungJoon 2025-05-28 22:31:25 +09:00 • committed by GitHub
parent d766292dab
commit 0a93ff515d
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583 changed files with 8698 additions and 7299 deletions
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10
src/math/lp/horner.cpp
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@ -39,9 +39,9 @@ bool horner::row_has_monomial_to_refine(const T& row) const {
// Returns true if the row has at least two monomials sharing a variable
template <typename T>
bool horner::row_is_interesting(const T& row) const {
TRACE("nla_solver_details", c().print_row(row, tout););
TRACE(nla_solver_details, c().print_row(row, tout););
if (row.size() > c().params().arith_nl_horner_row_length_limit()) {
TRACE("nla_solver_details", tout << "disregard\n";);
TRACE(nla_solver_details, tout << "disregard\n";);
return false;
}
SASSERT(row_has_monomial_to_refine(row));
@ -68,7 +68,7 @@ bool horner::row_is_interesting(const T& row) const {
}
bool horner::lemmas_on_expr(cross_nested& cn, nex_sum* e) {
TRACE("nla_horner", tout << "e = " << *e << "\n";);
TRACE(nla_horner, tout << "e = " << *e << "\n";);
cn.run(e);
return cn.done();
}
@ -81,7 +81,7 @@ bool horner::lemmas_on_row(const T& row) {
create_sum_from_row(row, m_nex_creator, m_row_sum, dep);
c().set_active_vars_weights(m_nex_creator); // without this call the comparisons will be incorrect
nex* e = m_nex_creator.simplify(m_row_sum.mk());
TRACE("nla_horner", tout << "e = " << * e << "\n";);
TRACE(nla_horner, tout << "e = " << * e << "\n";);
if (e->get_degree() < 2)
return false;
if (!e->is_sum())
@ -99,7 +99,7 @@ bool horner::lemmas_on_row(const T& row) {
bool horner::horner_lemmas() {
if (!c().params().arith_nl_horner()) {
TRACE("nla_solver", tout << "not generating horner lemmas\n";);
TRACE(nla_solver, tout << "not generating horner lemmas\n";);
return false;
}
c().lp_settings().stats().m_horner_calls++;