def replace_properties_dict(node: Any,
repl: Dict[str, str],
symrepl: Dict[symbolic.SymbolicType, symbolic.SymbolicType] = None):
symrepl = symrepl or {
symbolic.pystr_to_symbolic(symname):
symbolic.pystr_to_symbolic(new_name) if isinstance(new_name, str) else new_name
for symname, new_name in repl.items()
}
for propclass, propval in node.properties():
if propval is None:
continue
pname = propclass.attr_name
if isinstance(propclass, properties.SymbolicProperty):
setattr(node, pname, propval.subs(symrepl))
elif isinstance(propclass, properties.DataProperty):
if propval in repl:
setattr(node, pname, repl[propval])
elif isinstance(propclass, (properties.RangeProperty, properties.ShapeProperty)):
setattr(node, pname, _replsym(list(propval), symrepl))
elif isinstance(propclass, properties.CodeProperty):
# Don't replace variables that appear as an input or an output
# connector, as this should shadow the outer declaration.
reduced_repl = set(repl.keys())
if hasattr(node, 'in_connectors'):
reduced_repl -= set(node.in_connectors.keys()) | set(node.out_connectors.keys())
reduced_repl = {k: repl[k] for k in reduced_repl}
code = propval.code
if isinstance(code, str) and code:
lang = propval.language
if lang is dtypes.Language.CPP: # Replace in C++ code
prefix = ''
tokenized = tokenize_cpp.findall(code)
for name, new_name in reduced_repl.items():
if name not in tokenized:
continue
# Use local variables and shadowing to replace
replacement = f'auto {name} = {cppunparse.pyexpr2cpp(new_name)};\n'
prefix = replacement + prefix
if prefix:
propval.code = prefix + code
else:
warnings.warn('Replacement of %s with %s was not made '
'for string tasklet code of language %s' % (name, new_name, lang))
elif propval.code is not None:
afr = ASTFindReplace(reduced_repl)
for stmt in propval.code:
afr.visit(stmt)
elif (isinstance(propclass, properties.DictProperty) and pname == 'symbol_mapping'):
# Symbol mappings for nested SDFGs
for symname, sym_mapping in propval.items():
try:
propval[symname] = symbolic.pystr_to_symbolic(str(sym_mapping)).subs(symrepl)
except AttributeError: # If the symbolified value has no subs
pass
def replace_properties(node: Any, symrepl: Dict[symbolic.symbol, symbolic.SymbolicType], name: str, new_name: str):
for propclass, propval in node.properties():
if propval is None:
continue
pname = propclass.attr_name
if isinstance(propclass, properties.SymbolicProperty):
setattr(node, pname, propval.subs(symrepl))
elif isinstance(propclass, properties.DataProperty):
if propval == name:
setattr(node, pname, new_name)
elif isinstance(propclass, (properties.RangeProperty, properties.ShapeProperty)):
setattr(node, pname, _replsym(list(propval), symrepl))
elif isinstance(propclass, properties.CodeProperty):
# Don't replace variables that appear as an input or an output
# connector, as this should shadow the outer declaration.
if hasattr(node, 'in_connectors'):
if name in node.in_connectors:
continue
if hasattr(node, 'out_connectors'):
if name in node.out_connectors:
continue
if isinstance(propval.code, str):
if str(name) != str(new_name):
lang = propval.language
newcode = propval.code
if not re.findall(r'[^\w]%s[^\w]' % name, newcode):
continue
if lang is dtypes.Language.CPP: # Replace in C++ code
# Avoid import loop
from dace.codegen.targets.cpp import sym2cpp
# Use local variables and shadowing to replace
replacement = 'auto %s = %s;\n' % (name, sym2cpp(new_name))
propval.code = replacement + newcode
else:
warnings.warn('Replacement of %s with %s was not made '
'for string tasklet code of language %s' % (name, new_name, lang))
elif propval.code is not None:
afr = ASTFindReplace({name: symbolic.symstr(new_name)})
for stmt in propval.code:
afr.visit(stmt)
elif (isinstance(propclass, properties.DictProperty) and pname == 'symbol_mapping'):
# Symbol mappings for nested SDFGs
for symname, sym_mapping in propval.items():
try:
propval[symname] = symbolic.pystr_to_symbolic(str(sym_mapping)).subs(symrepl)
except AttributeError: # If the symbolified value has no subs
pass
def instantiate_loop(
self,
sdfg: sd.SDFG,
loop_states: List[sd.SDFGState],
loop_subgraph: gr.SubgraphView,
itervar: str,
value: symbolic.SymbolicType,
state_suffix=None,
):
# Using to/from JSON copies faster than deepcopy (which will also
# copy the parent SDFG)
new_states = [
sd.SDFGState.from_json(s.to_json(), context={'sdfg': sdfg})
for s in loop_states
]
# Replace iterate with value in each state
for state in new_states:
state.set_label(state.label + '_' + itervar + '_' + (
state_suffix if state_suffix is not None else '%d' % value))
state.replace(itervar, value)
# Add subgraph to original SDFG
for edge in loop_subgraph.edges():
src = new_states[loop_states.index(edge.src)]
dst = new_states[loop_states.index(edge.dst)]
# Replace conditions in subgraph edges
data: sd.InterstateEdge = copy.deepcopy(edge.data)
if data.condition:
ASTFindReplace({itervar: str(value)}).visit(data.condition)
sdfg.add_edge(src, dst, data)
return new_states
def replace_properties(node: Any, name: str, new_name: str):
if str(name) == str(new_name):
return
symrepl = {
symbolic.symbol(name):
symbolic.pystr_to_symbolic(new_name)
if isinstance(new_name, str) else new_name
}
for propclass, propval in node.properties():
if propval is None:
continue
pname = propclass.attr_name
if isinstance(propclass, properties.SymbolicProperty):
setattr(node, pname, propval.subs(symrepl))
elif isinstance(propclass, properties.DataProperty):
if propval == name:
setattr(node, pname, new_name)
elif isinstance(propclass,
(properties.RangeProperty, properties.ShapeProperty)):
setattr(node, pname, _replsym(list(propval), symrepl))
elif isinstance(propclass, properties.CodeProperty):
if isinstance(propval.code, str):
if str(name) != str(new_name):
lang = propval.language
newcode = propval.code
if not re.findall(r'[^\w]%s[^\w]' % name, newcode):
continue
if lang is dtypes.Language.CPP: # Replace in C++ code
# Use local variables and shadowing to replace
replacement = 'auto %s = %s;\n' % (name, new_name)
propval.code = replacement + newcode
else:
warnings.warn(
'Replacement of %s with %s was not made '
'for string tasklet code of language %s' %
(name, new_name, lang))
elif propval.code is not None:
for stmt in propval.code:
ASTFindReplace({name: new_name}).visit(stmt)
elif (isinstance(propclass, properties.DictProperty)
and pname == 'symbol_mapping'):
# Symbol mappings for nested SDFGs
for symname, sym_mapping in propval.items():
propval[symname] = sym_mapping.subs(symrepl)
def apply(self, sdfg):
# Obtain loop information
guard: sd.SDFGState = sdfg.node(self.subgraph[DetectLoop._loop_guard])
begin: sd.SDFGState = sdfg.node(self.subgraph[DetectLoop._loop_begin])
after_state: sd.SDFGState = sdfg.node(
self.subgraph[DetectLoop._exit_state])
# Obtain iteration variable, range, and stride
guard_inedges = sdfg.in_edges(guard)
condition_edge = sdfg.edges_between(guard, begin)[0]
itervar = list(guard_inedges[0].data.assignments.keys())[0]
condition = condition_edge.data.condition_sympy()
rng = LoopUnroll._loop_range(itervar, guard_inedges, condition)
# Loop must be unrollable
if self.count == 0 and any(
symbolic.issymbolic(r, sdfg.constants) for r in rng):
raise ValueError('Loop cannot be fully unrolled, size is symbolic')
if self.count != 0:
raise NotImplementedError # TODO(later)
# Find the state prior to the loop
if rng[0] == symbolic.pystr_to_symbolic(
guard_inedges[0].data.assignments[itervar]):
before_state: sd.SDFGState = guard_inedges[0].src
last_state: sd.SDFGState = guard_inedges[1].src
else:
before_state: sd.SDFGState = guard_inedges[1].src
last_state: sd.SDFGState = guard_inedges[0].src
# Get loop states
loop_states = list(
sdutil.dfs_topological_sort(
sdfg,
sources=[begin],
condition=lambda _, child: child != guard))
first_id = loop_states.index(begin)
last_id = loop_states.index(last_state)
loop_subgraph = gr.SubgraphView(sdfg, loop_states)
# Evaluate the real values of the loop
start, end, stride = (symbolic.evaluate(r, sdfg.constants)
for r in rng)
# Create states for loop subgraph
unrolled_states = []
for i in range(start, end + 1, stride):
# Using to/from JSON copies faster than deepcopy (which will also
# copy the parent SDFG)
new_states = [
sd.SDFGState.from_json(s.to_json(), context={'sdfg': sdfg})
for s in loop_states
]
# Replace iterate with value in each state
for state in new_states:
state.set_label(state.label + '_%s_%d' % (itervar, i))
state.replace(itervar, i)
# Add subgraph to original SDFG
for edge in loop_subgraph.edges():
src = new_states[loop_states.index(edge.src)]
dst = new_states[loop_states.index(edge.dst)]
# Replace conditions in subgraph edges
data: sd.InterstateEdge = copy.deepcopy(edge.data)
if data.condition:
ASTFindReplace({itervar: str(i)}).visit(data.condition)
sdfg.add_edge(src, dst, data)
# Connect iterations with unconditional edges
if len(unrolled_states) > 0:
sdfg.add_edge(unrolled_states[-1][1], new_states[first_id],
sd.InterstateEdge())
unrolled_states.append((new_states[first_id], new_states[last_id]))
# Connect new states to before and after states without conditions
if unrolled_states:
sdfg.add_edge(before_state, unrolled_states[0][0],
sd.InterstateEdge())
sdfg.add_edge(unrolled_states[-1][1], after_state,
sd.InterstateEdge())
# Remove old states from SDFG
sdfg.remove_nodes_from([guard] + loop_states)