def expand_library_node(json_in):
"""
Expand a specific library node in a given SDFG. If no specific library node
is provided, expand all library nodes in the given SDFG.
:param json_in: The entire provided request JSON.
"""
old_meta = utils.disable_save_metadata()
sdfg = None
try:
loaded = utils.load_sdfg_from_json(json_in['sdfg'])
if loaded['error'] is not None:
return loaded['error']
sdfg = loaded['sdfg']
except KeyError:
return {
'error': {
'message': 'Failed to expand library node',
'details': 'No SDFG provided',
},
}
try:
sdfg_id, state_id, node_id = json_in['nodeId']
except KeyError:
sdfg_id, state_id, node_id = None, None, None
if sdfg_id is None:
sdfg.expand_library_nodes()
else:
context_sdfg = sdfg.sdfg_list[sdfg_id]
state = context_sdfg.node(state_id)
node = state.node(node_id)
if isinstance(node, nodes.LibraryNode):
node.expand(context_sdfg, state)
else:
return {
'error': {
'message': 'Failed to expand library node',
'details': 'The provided node is not a valid library node',
},
}
new_sdfg = sdfg.to_json()
utils.restore_save_metadata(old_meta)
return {
'sdfg': new_sdfg,
}
def reapply_history_until(sdfg_json, index):
"""
Rewind a given SDFG back to a specific point in its history by reapplying
all transformations until a given index in its history to its original
state.
:param sdfg_json: The SDFG to rewind.
:param index: Index of the last history item to apply.
"""
old_meta = utils.disable_save_metadata()
loaded = utils.load_sdfg_from_json(sdfg_json)
if loaded['error'] is not None:
return loaded['error']
sdfg = loaded['sdfg']
original_sdfg = sdfg.orig_sdfg
history = sdfg.transformation_hist
for i in range(index + 1):
transformation = history[i]
try:
if isinstance(transformation, SubgraphTransformation):
transformation.apply(
original_sdfg.sdfg_list[transformation.sdfg_id])
else:
transformation.apply_pattern(
original_sdfg.sdfg_list[transformation.sdfg_id])
except Exception as e:
print(traceback.format_exc(), file=sys.stderr)
sys.stderr.flush()
return {
'error': {
'message':
'Failed to play back the transformation history',
'details': utils.get_exception_message(e),
},
}
new_sdfg = original_sdfg.to_json()
utils.restore_save_metadata(old_meta)
return {
'sdfg': new_sdfg,
}
def apply_transformation(sdfg_json, transformation_json):
old_meta = utils.disable_save_metadata()
loaded = utils.load_sdfg_from_json(sdfg_json)
if loaded['error'] is not None:
return loaded['error']
sdfg = loaded['sdfg']
try:
transformation = serialize.from_json(transformation_json)
except Exception as e:
print(traceback.format_exc(), file=sys.stderr)
sys.stderr.flush()
return {
'error': {
'message': 'Failed to parse the applied transformation',
'details': utils.get_exception_message(e),
},
}
try:
target_sdfg = sdfg.sdfg_list[transformation.sdfg_id]
if isinstance(transformation, SubgraphTransformation):
sdfg.append_transformation(transformation)
transformation.apply(target_sdfg)
else:
transformation.apply_pattern(target_sdfg)
except Exception as e:
print(traceback.format_exc(), file=sys.stderr)
sys.stderr.flush()
return {
'error': {
'message': 'Failed to apply the transformation to the SDFG',
'details': utils.get_exception_message(e),
},
}
new_sdfg = sdfg.to_json()
utils.restore_save_metadata(old_meta)
return {
'sdfg': new_sdfg,
}
def compile_sdfg(path, suppress_instrumentation=False):
# We lazy import DaCe, not to break cyclic imports, but to avoid any large
# delays when booting in daemon mode.
from dace.codegen.compiled_sdfg import CompiledSDFG
old_meta = disable_save_metadata()
loaded = load_sdfg_from_file(path)
if loaded['error'] is not None:
return loaded['error']
sdfg = loaded['sdfg']
if suppress_instrumentation:
_sdfg_remove_instrumentations(sdfg)
compiled_sdfg: CompiledSDFG = sdfg.compile()
restore_save_metadata(old_meta)
return {
'filename': compiled_sdfg.filename,
}
def remove_sdfg_elements(sdfg_json, uuids):
from dace.sdfg.graph import Edge
old_meta = disable_save_metadata()
loaded = load_sdfg_from_json(sdfg_json)
if loaded['error'] is not None:
return loaded['error']
sdfg = loaded['sdfg']
elements = []
for uuid in uuids:
elements.append(find_graph_element_by_uuid(sdfg, uuid))
for element_ret in elements:
element = element_ret['element']
parent = element_ret['parent']
if parent is not None and element is not None:
if isinstance(element, Edge):
parent.remove_edge(element)
else:
parent.remove_node(element)
else:
return {
'error': {
'message': 'Failed to delete element',
'details': 'Element or parent not found',
},
}
new_sdfg = sdfg.to_json()
restore_save_metadata(old_meta)
return {
'sdfg': new_sdfg,
}
def insert_sdfg_element(sdfg_str, type, parent_uuid, edge_a_uuid):
sdfg_answer = load_sdfg_from_json(sdfg_str)
sdfg = sdfg_answer['sdfg']
uuid = 'error'
ret = find_graph_element_by_uuid(sdfg, parent_uuid)
parent = ret['element']
libname = None
if type is not None and isinstance(type, str):
split_type = type.split('|')
if len(split_type) == 2:
type = split_type[0]
libname = split_type[1]
if type == 'SDFGState':
if parent is None:
parent = sdfg
elif isinstance(parent, nodes.NestedSDFG):
parent = parent.sdfg
state = parent.add_state()
uuid = [get_uuid(state)]
elif type == 'AccessNode':
arrays = list(parent.parent.arrays.keys())
if len(arrays) == 0:
parent.parent.add_array('tmp', [1], dtype=dtypes.float64)
arrays = list(parent.parent.arrays.keys())
node = parent.add_access(arrays[0])
uuid = [get_uuid(node, parent)]
elif type == 'Map':
map_entry, map_exit = parent.add_map('map', dict(i='0:1'))
uuid = [get_uuid(map_entry, parent), get_uuid(map_exit, parent)]
elif type == 'Consume':
consume_entry, consume_exit = parent.add_consume('consume', ('i', '1'))
uuid = [get_uuid(consume_entry, parent), get_uuid(consume_exit, parent)]
elif type == 'Tasklet':
tasklet = parent.add_tasklet(
name='placeholder',
inputs={'in'},
outputs={'out'},
code='')
uuid = [get_uuid(tasklet, parent)]
elif type == 'NestedSDFG':
sub_sdfg = SDFG('nested_sdfg')
sub_sdfg.add_array('in', [1], dtypes.float32)
sub_sdfg.add_array('out', [1], dtypes.float32)
nsdfg = parent.add_nested_sdfg(sub_sdfg, sdfg, {'in'}, {'out'})
uuid = [get_uuid(nsdfg, parent)]
elif type == 'LibraryNode':
if libname is None:
return {
'error': {
'message': 'Failed to add library node',
'details': 'Must provide a valid library node type',
},
}
libnode_class = pydoc.locate(libname)
libnode = libnode_class()
parent.add_node(libnode)
uuid = [get_uuid(libnode, parent)]
elif type == 'Edge':
edge_start_ret = find_graph_element_by_uuid(sdfg, edge_a_uuid)
edge_start = edge_start_ret['element']
edge_parent = edge_start_ret['parent']
if edge_start is not None:
if edge_parent is None:
edge_parent = sdfg
if isinstance(edge_parent, SDFGState):
if not (isinstance(edge_start, nodes.Node) and
isinstance(parent, nodes.Node)):
return {
'error': {
'message': 'Failed to add edge',
'details': 'Must connect two nodes or two states',
},
}
memlet = Memlet()
edge_parent.add_edge(edge_start, None, parent, None, memlet)
elif isinstance(edge_parent, SDFG):
if not (isinstance(edge_start, SDFGState) and
isinstance(parent, SDFGState)):
return {
'error': {
'message': 'Failed to add edge',
'details': 'Must connect two nodes or two states',
},
}
isedge = InterstateEdge()
edge_parent.add_edge(edge_start, parent, isedge)
uuid = ['NONE']
else:
raise ValueError('No edge starting point provided')
old_meta = disable_save_metadata()
new_sdfg_str = sdfg.to_json()
restore_save_metadata(old_meta)
return {
'sdfg': new_sdfg_str,
'uuid': uuid,
}
def get_transformations(sdfg_json, selected_elements):
# We lazy import DaCe, not to break cyclic imports, but to avoid any large
# delays when booting in daemon mode.
from dace.transformation.optimizer import SDFGOptimizer
from dace.sdfg.graph import SubgraphView
old_meta = utils.disable_save_metadata()
loaded = utils.load_sdfg_from_json(sdfg_json)
if loaded['error'] is not None:
return loaded['error']
sdfg = loaded['sdfg']
optimizer = SDFGOptimizer(sdfg)
matches = optimizer.get_pattern_matches()
transformations = []
docstrings = {}
for transformation in matches:
transformations.append(transformation.to_json())
docstrings[type(transformation).__name__] = transformation.__doc__
selected_states = [
utils.sdfg_find_state_from_element(sdfg, n) for n in selected_elements
if n['type'] == 'state'
]
selected_nodes = [
utils.sdfg_find_node_from_element(sdfg, n) for n in selected_elements
if n['type'] == 'node'
]
selected_sdfg_ids = list(set(elem['sdfgId'] for elem in selected_elements))
selected_sdfg = sdfg
if len(selected_sdfg_ids) > 1:
return {
'transformations': transformations,
'docstrings': docstrings,
'warnings': 'More than one SDFG selected, ignoring subgraph',
}
elif len(selected_sdfg_ids) == 1:
selected_sdfg = sdfg.sdfg_list[selected_sdfg_ids[0]]
subgraph = None
if len(selected_states) > 0:
subgraph = SubgraphView(selected_sdfg, selected_states)
else:
violated = False
state = None
for node in selected_nodes:
if state is None:
state = node.state
elif state != node.state:
violated = True
break
if not violated and state is not None:
subgraph = SubgraphView(state, selected_nodes)
if subgraph is not None:
extensions = SubgraphTransformation.extensions()
for xform in extensions:
xform_data = extensions[xform]
if ('singlestate' in xform_data and xform_data['singlestate']
and len(selected_states) > 0):
continue
xform_obj = xform(subgraph)
if xform_obj.can_be_applied(selected_sdfg, subgraph):
transformations.append(xform_obj.to_json())
docstrings[xform.__name__] = xform_obj.__doc__
utils.restore_save_metadata(old_meta)
return {
'transformations': transformations,
'docstrings': docstrings,
}
