class NestedSDFG(CodeNode):
""" An SDFG state node that contains an SDFG of its own, runnable using
the data dependencies specified using its connectors.
It is encouraged to use nested SDFGs instead of coarse-grained tasklets
since they are analyzable with respect to transformations.
@note: A nested SDFG cannot create recursion (one of its parent SDFGs).
"""
# NOTE: We cannot use SDFG as the type because of an import loop
sdfg = SDFGReferenceProperty(desc="The SDFG", allow_none=True)
schedule = Property(dtype=dtypes.ScheduleType,
desc="SDFG schedule",
allow_none=True,
choices=dtypes.ScheduleType,
from_string=lambda x: dtypes.ScheduleType[x],
default=dtypes.ScheduleType.Default)
symbol_mapping = DictProperty(
key_type=str,
value_type=dace.symbolic.pystr_to_symbolic,
desc="Mapping between internal symbols and their values, expressed as "
"symbolic expressions")
debuginfo = DebugInfoProperty()
is_collapsed = Property(dtype=bool,
desc="Show this node/scope/state as collapsed",
default=False)
instrument = Property(choices=dtypes.InstrumentationType,
desc="Measure execution statistics with given method",
default=dtypes.InstrumentationType.No_Instrumentation)
def __init__(self,
label,
sdfg,
inputs: Set[str],
outputs: Set[str],
symbol_mapping: Dict[str, Any] = None,
schedule=dtypes.ScheduleType.Default,
location=None,
debuginfo=None):
super(NestedSDFG, self).__init__(label, location, inputs, outputs)
# Properties
self.sdfg = sdfg
self.symbol_mapping = symbol_mapping or {}
self.schedule = schedule
self.debuginfo = debuginfo
@staticmethod
def from_json(json_obj, context=None):
from dace import SDFG # Avoid import loop
# We have to load the SDFG first.
ret = NestedSDFG("nolabel", SDFG('nosdfg'), {}, {})
dace.serialize.set_properties_from_json(ret, json_obj, context)
if context and 'sdfg_state' in context:
ret.sdfg.parent = context['sdfg_state']
if context and 'sdfg' in context:
ret.sdfg.parent_sdfg = context['sdfg']
ret.sdfg.parent_nsdfg_node = ret
ret.sdfg.update_sdfg_list([])
return ret
@property
def free_symbols(self) -> Set[str]:
return set().union(
*(map(str,
pystr_to_symbolic(v).free_symbols)
for v in self.symbol_mapping.values()),
*(map(str,
pystr_to_symbolic(v).free_symbols)
for v in self.location.values()))
def infer_connector_types(self, sdfg, state):
# Avoid import loop
from dace.sdfg.infer_types import infer_connector_types
# Infer internal connector types
infer_connector_types(self.sdfg)
def __str__(self):
if not self.label:
return "SDFG"
else:
return self.label
def validate(self, sdfg, state):
if not dtypes.validate_name(self.label):
raise NameError('Invalid nested SDFG name "%s"' % self.label)
for in_conn in self.in_connectors:
if not dtypes.validate_name(in_conn):
raise NameError('Invalid input connector "%s"' % in_conn)
for out_conn in self.out_connectors:
if not dtypes.validate_name(out_conn):
raise NameError('Invalid output connector "%s"' % out_conn)
connectors = self.in_connectors.keys() | self.out_connectors.keys()
for dname, desc in self.sdfg.arrays.items():
# TODO(later): Disallow scalars without access nodes (so that this
# check passes for them too).
if isinstance(desc, data.Scalar):
continue
if not desc.transient and dname not in connectors:
raise NameError('Data descriptor "%s" not found in nested '
'SDFG connectors' % dname)
if dname in connectors and desc.transient:
raise NameError(
'"%s" is a connector but its corresponding array is transient'
% dname)
# Validate undefined symbols
symbols = set(k for k in self.sdfg.free_symbols if k not in connectors)
missing_symbols = [s for s in symbols if s not in self.symbol_mapping]
if missing_symbols:
raise ValueError('Missing symbols on nested SDFG: %s' %
(missing_symbols))
# Recursively validate nested SDFG
self.sdfg.validate()
class NestedSDFG(CodeNode):
""" An SDFG state node that contains an SDFG of its own, runnable using
the data dependencies specified using its connectors.
It is encouraged to use nested SDFGs instead of coarse-grained tasklets
since they are analyzable with respect to transformations.
@note: A nested SDFG cannot create recursion (one of its parent SDFGs).
"""
label = Property(dtype=str, desc="Name of the SDFG")
# NOTE: We cannot use SDFG as the type because of an import loop
sdfg = SDFGReferenceProperty(dtype=graph.OrderedDiGraph, desc="The SDFG")
schedule = Property(dtype=dtypes.ScheduleType,
desc="SDFG schedule",
choices=dtypes.ScheduleType,
from_string=lambda x: dtypes.ScheduleType[x])
location = Property(dtype=str, desc="SDFG execution location descriptor")
debuginfo = DebugInfoProperty()
is_collapsed = Property(dtype=bool,
desc="Show this node/scope/state as collapsed",
default=False)
instrument = Property(
choices=dtypes.InstrumentationType,
desc="Measure execution statistics with given method",
default=dtypes.InstrumentationType.No_Instrumentation)
def __init__(self,
label,
sdfg,
inputs: Set[str],
outputs: Set[str],
schedule=dtypes.ScheduleType.Default,
location="-1",
debuginfo=None):
super(NestedSDFG, self).__init__(inputs, outputs)
# Properties
self.label = label
self.sdfg = sdfg
self.schedule = schedule
self.location = location
self.debuginfo = debuginfo
@staticmethod
def from_json(json_obj, context=None):
from dace import SDFG # Avoid import loop
# We have to load the SDFG first.
ret = NestedSDFG("nolabel", SDFG('nosdfg'), set(), set())
dace.serialize.set_properties_from_json(ret, json_obj, context)
if context and 'sdfg_state' in context:
ret.sdfg.parent = context['sdfg_state']
if context and 'sdfg' in context:
ret.sdfg.parent_sdfg = context['sdfg']
return ret
def draw_node(self, sdfg, graph):
return dot.draw_node(sdfg, graph, self, shape="doubleoctagon")
def __str__(self):
if not self.label:
return "SDFG"
else:
return self.label
def validate(self, sdfg, state):
if not data.validate_name(self.label):
raise NameError('Invalid nested SDFG name "%s"' % self.label)
for in_conn in self.in_connectors:
if not data.validate_name(in_conn):
raise NameError('Invalid input connector "%s"' % in_conn)
for out_conn in self.out_connectors:
if not data.validate_name(out_conn):
raise NameError('Invalid output connector "%s"' % out_conn)
# Recursively validate nested SDFG
self.sdfg.validate()