def describe_template_defns(template_defns: Tuple[ir.TemplateDefn, ...], identifier_generator: Iterator[str]):
return header_to_cpp(ir.Header(template_defns=template_defns,
check_if_error_specializations=(),
toplevel_content=(),
public_names=frozenset(),
split_template_name_by_old_name_and_result_element_name=()),
identifier_generator,
coverage_collection_enabled=False)
def describe_toplevel_elems(toplevel_elems: Tuple[Union[ir.StaticAssert, ir.ConstantDef, ir.Typedef], ...],
identifier_generator: Iterator[str]):
return header_to_cpp(ir.Header(template_defns=(),
toplevel_content=toplevel_elems,
public_names=frozenset(),
split_template_name_by_old_name_and_result_element_name=(),
check_if_error_specializations=()),
identifier_generator,
coverage_collection_enabled=False)
def describe_template_defns(template_defns: List[ir.TemplateDefn],
identifier_generator: Iterator[str]):
return header_to_cpp(
ir.Header(
template_defns=template_defns,
check_if_error_specializations=[],
toplevel_content=[],
public_names=set(),
split_template_name_by_old_name_and_result_element_name=dict()),
identifier_generator)
def describe_toplevel_elems(toplevel_elems: List[Union[ir.StaticAssert,
ir.ConstantDef,
ir.Typedef]],
identifier_generator: Iterator[str]):
return header_to_cpp(
ir.Header(
template_defns=[],
toplevel_content=toplevel_elems,
public_names=set(),
split_template_name_by_old_name_and_result_element_name=dict(),
check_if_error_specializations=[]), identifier_generator)
def replace_metafunction_calls_with_split_template_calls(header,
new_template_defns,
split_template_name_by_old_name_and_result_element_name):
transformation = ReplaceMetafunctionCallWithSplitTemplateCallTransformation(
split_template_name_by_old_name_and_result_element_name)
return transformation.transform_header(
ir.Header(template_defns=new_template_defns,
toplevel_content=header.toplevel_content,
public_names=header.public_names,
split_template_name_by_old_name_and_result_element_name=split_template_name_by_old_name_and_result_element_name,
check_if_error_specializations=header.check_if_error_specializations))
def remove_unused_toplevel_elems(header: ir.Header,
linking_final_header: bool):
toplevel_elem_names = {
elem.name
for elem in itertools.chain(header.toplevel_content,
header.template_defns)
if not isinstance(elem, (ir.StaticAssert, ir.NoOpStmt))
}
public_names = header.public_names
if not linking_final_header:
public_names = public_names.union(
split_name for _, split_name in
header.split_template_name_by_old_name_and_result_element_name)
elem_dependency_graph = nx.DiGraph()
for elem in itertools.chain(header.template_defns,
header.toplevel_content):
if isinstance(elem, (ir.TemplateDefn, ir.ConstantDef, ir.Typedef)):
elem_name = elem.name
else:
# We'll use a dummy name for non-template toplevel elems.
elem_name = ''
elem_dependency_graph.add_node(elem_name)
if elem_name in public_names or (isinstance(
elem, (ir.ConstantDef, ir.Typedef)) and any(
isinstance(expr, ir.TemplateInstantiation)
and expr.instantiation_might_trigger_static_asserts
for expr in elem.transitive_subexpressions)):
# We also add an edge from the node '' to all toplevel defns that must remain, so that we can use '' as a source below.
elem_dependency_graph.add_edge('', elem_name)
for identifier in elem.referenced_identifiers:
if identifier in toplevel_elem_names:
elem_dependency_graph.add_edge(elem_name, identifier)
elem_dependency_graph.add_node('')
used_elem_names = nx.single_source_shortest_path(elem_dependency_graph,
source='').keys()
return ir.Header(
template_defns=tuple(template_defn
for template_defn in header.template_defns
if template_defn.name in used_elem_names),
toplevel_content=tuple(
elem for elem in header.toplevel_content
if isinstance(elem, (ir.StaticAssert, ir.NoOpStmt))
or elem.name in used_elem_names),
public_names=header.public_names,
split_template_name_by_old_name_and_result_element_name=header.
split_template_name_by_old_name_and_result_element_name,
check_if_error_specializations=header.check_if_error_specializations)
def transform_header(self, header: ir.Header) -> ir.Header:
writer = ToplevelWriter()
with self.set_writer(writer):
for template_defn in header.template_defns:
self.transform_template_defn(template_defn)
for elem in header.toplevel_content:
self.transform_toplevel_elem(elem)
check_if_error_specializations = tuple(
self.transform_template_specialization(specialization)
for specialization in header.check_if_error_specializations)
return ir.Header(
template_defns=tuple(writer.template_defns),
toplevel_content=tuple(writer.toplevel_elems),
public_names=header.public_names,
split_template_name_by_old_name_and_result_element_name=header.
split_template_name_by_old_name_and_result_element_name,
check_if_error_specializations=check_if_error_specializations)
def replace_metafunction_calls_with_split_template_calls(
header, new_template_defns,
split_template_name_by_old_name_and_result_element_name: Dict[Tuple[str,
str],
str]
) -> ir.Header:
transformation = ReplaceMetafunctionCallWithSplitTemplateCallTransformation(
split_template_name_by_old_name_and_result_element_name)
return transformation.transform_header(
ir.Header(
template_defns=new_template_defns,
toplevel_content=header.toplevel_content,
public_names=header.public_names,
split_template_name_by_old_name_and_result_element_name=tuple(
(k, v) for k, v in
split_template_name_by_old_name_and_result_element_name.items(
)),
check_if_error_specializations=header.
check_if_error_specializations))
def _optimize_header_second_pass(
header: ir.Header, identifier_generator: Iterator[str],
context_object_file_content: ObjectFileContent):
new_template_defns = {elem.name: elem for elem in header.template_defns}
template_dependency_graph = compute_template_dependency_graph(
header.template_defns, new_template_defns)
template_dependency_graph_transitive_closure = nx.transitive_closure(
template_dependency_graph)
assert isinstance(template_dependency_graph_transitive_closure, nx.DiGraph)
optimizations = [
lambda template_defn: perform_template_inlining(
template_defn, {
other_node
for other_node in template_dependency_graph_transitive_closure.
successors(template_defn.name)
if not template_dependency_graph_transitive_closure.has_edge(
other_node, template_defn.name)
}, new_template_defns, identifier_generator,
context_object_file_content),
lambda template_defn: perform_local_optimizations_on_template_defn(
template_defn,
identifier_generator,
inline_template_instantiations_with_multiple_references=False),
]
for connected_component in reversed(
list(
compute_condensation_in_topological_order(
template_dependency_graph))):
def optimize(template_name: str):
new_template_defns[
template_name], needs_another_loop = combine_optimizations(
new_template_defns[template_name], optimizations)
return None, needs_another_loop
_iterate_optimization(
None, lambda _: optimize_list(
sorted(connected_component,
key=lambda node: new_template_defns[node].name), lambda
template_name: optimize(template_name)),
len(connected_component), lambda _: '\n'.join(
template_defn_to_cpp_simple(new_template_defns[template_name],
identifier_generator)
for template_name in connected_component))
optimizations = [
lambda toplevel_content: perform_template_inlining_on_toplevel_elems(
toplevel_content, new_template_defns.keys(), new_template_defns,
identifier_generator, context_object_file_content),
lambda toplevel_content: perform_local_optimizations_on_toplevel_elems(
toplevel_content,
identifier_generator,
inline_template_instantiations_with_multiple_references=False),
]
toplevel_content = _iterate_optimization(
header.toplevel_content, lambda toplevel_content:
combine_optimizations(toplevel_content, optimizations),
len(header.toplevel_content), lambda toplevel_content: '\n'.join(
toplevel_elem_to_cpp_simple(elem, identifier_generator)
for elem in toplevel_content))
return ir.Header(
template_defns=tuple(new_template_defns[template_defn.name]
for template_defn in header.template_defns),
toplevel_content=toplevel_content,
public_names=header.public_names,
split_template_name_by_old_name_and_result_element_name=header.
split_template_name_by_old_name_and_result_element_name,
check_if_error_specializations=header.check_if_error_specializations)
