def perform_local_optimizations(elems: List,
identifier_generator: Iterator[str],
apply_transformation: Callable[[List, Transformation], Tuple[List, bool]],
describe_elems: Callable[[List], str],
inline_template_instantiations_with_multiple_references: bool):
optimizations = [
('remove_no_op_stmts()', RemoveNoOpStmtsTransformation(identifier_generator)),
('normalize_template_defn()', NormalizeExpressionsTransformation(identifier_generator)),
('perform_common_subexpression_normalization()', CommonSubexpressionEliminationTransformation()),
('perform_constant_folding()', ConstantFoldingTransformation(inline_template_instantiations_with_multiple_references)),
('perform_expression_simplification()', ExpressionSimplificationTransformation()),
]
optimizations = [lambda elems,
optimization_name=optimization_name,
transformation=transformation:
apply_elem_optimization(elems,
lambda: apply_transformation(elems, transformation),
describe_elems,
optimization_name)
for optimization_name, transformation in optimizations]
return combine_optimizations(elems, optimizations)
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
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)