def _add_relationships_linked_to_root_object_perception(
*,
original_graph: DiGraph,
output_graph: DiGraph,
matched_nodes: AbstractSet[PerceptionGraphNode],
matched_object_node: ObjectSemanticNode,
) -> None:
# We take two graphs as input because we are assuming object-internal properties
# have already been deleted from the output_graph, so we have to look for them
# in the original, unaltered graph
root_node = _get_root_object_perception(original_graph, matched_nodes)
linked_properties_and_labels: List[Tuple[PerceptionGraphNode,
EdgeLabel]] = []
for pred in original_graph.predecessors(root_node):
edge_label = _get_edge_label(original_graph, pred, root_node)
if edge_equals_ignoring_temporal_scope(edge_label, HAS_PROPERTY_LABEL):
linked_properties_and_labels.append((pred, edge_label))
for (linked_property_node, edge_label) in linked_properties_and_labels:
output_graph.add_edge(linked_property_node,
matched_object_node,
label=edge_label)
linked_properties_and_labels.clear()
for succ in original_graph.successors(root_node):
edge_label = _get_edge_label(original_graph, root_node, succ)
if edge_equals_ignoring_temporal_scope(edge_label, HAS_PROPERTY_LABEL):
linked_properties_and_labels.append((succ, edge_label))
for (linked_property_node, edge_label) in linked_properties_and_labels:
output_graph.add_edge(matched_object_node,
linked_property_node,
label=edge_label)
def replace_match_root_with_object_semantic_node(
object_semantic_node: ObjectSemanticNode,
current_perception: PerceptionGraph,
pattern_match: PerceptionGraphPatternMatch,
) -> PerceptionGraph:
"""
Internal function to replace the root node of the perception matched by the object pattern
with an `ObjectSemanticNode`.
The `ObjectSemanticNode` inherits both the root node's internal relationships and all external
relationships involving either the root node or its children.
"""
perception_digraph = current_perception.copy_as_digraph()
perception_digraph.add_node(object_semantic_node)
matched_subgraph_nodes: ImmutableSet[PerceptionGraphNode] = immutableset(
pattern_match.matched_sub_graph._graph.nodes, # pylint:disable=protected-access
disable_order_check=True,
)
root = _get_root_object_perception(perception_digraph,
matched_subgraph_nodes)
# Multiple sub-objects of a matched object may link to the same property
# (for example, to a color shared by all the parts).
# In this case, we want the shared object node to link to this property only once.
external_properties: Set[Union[OntologyNode, ObjectSemanticNode]] = set()
for matched_subgraph_node in matched_subgraph_nodes:
if isinstance(matched_subgraph_node, ObjectSemanticNode):
raise RuntimeError(
f"We do not currently allow object recognitions to themselves "
f"operate over other object recognitions, but got match "
f"{pattern_match.matched_sub_graph}")
# A pattern might refer to shared parts of the world like the learner
# or the ground, and we don't want the replacement root to inherit the
# shared world item's relationships.
if matched_subgraph_node in SHARED_WORLD_ITEMS:
continue
# If there is an edge from the matched sub-graph to a node outside it,
# also add an edge from the object match node to that node.
for matched_subgraph_node_successor in perception_digraph.successors(
matched_subgraph_node):
edge_label = _get_edge_label(perception_digraph,
matched_subgraph_node,
matched_subgraph_node_successor)
# don't want to add edges which are internal to the matched sub-graph
if matched_subgraph_node_successor not in matched_subgraph_nodes:
if edge_equals_ignoring_temporal_scope(edge_label,
HAS_PROPERTY_LABEL):
# Prevent multiple `has-property` assertions to the same color node
# On a recognized object
if matched_subgraph_node_successor[
0] in external_properties or matched_subgraph_node_successor[
0] in {
SMALLER_THAN,
BIGGER_THAN,
}:
if (perception_digraph.degree(
matched_subgraph_node_successor) != 1):
raise_graph_exception(
f"Node {matched_subgraph_node_successor} "
f"appears to be a duplicate property node, "
f"but has degree != 1",
current_perception,
)
continue
else:
external_properties.add(
matched_subgraph_node_successor[0])
perception_digraph.add_edge(
object_semantic_node,
matched_subgraph_node_successor,
label=edge_label,
)
# If there is an edge to the matched sub-graph from a node outside it,
# also add an edge to the object match node from that node.
for matched_subgraph_node_predecessor in perception_digraph.predecessors(
matched_subgraph_node):
edge_label = _get_edge_label(
perception_digraph,
matched_subgraph_node_predecessor,
matched_subgraph_node,
)
# don't want to add edges which are internal to the matched sub-graph
if matched_subgraph_node_predecessor not in matched_subgraph_nodes:
if edge_equals_ignoring_temporal_scope(edge_label,
HAS_PROPERTY_LABEL):
# Prevent multiple `has-property` assertions to the same color node
# On a recognized object
if isinstance(matched_subgraph_node_predecessor,
ObjectSemanticNode):
prop = matched_subgraph_node_predecessor
else:
prop = matched_subgraph_node_predecessor[0]
if prop in external_properties:
if (perception_digraph.degree(
matched_subgraph_node_predecessor) != 1):
raise_graph_exception(
f"Node {matched_subgraph_node_predecessor} "
f"appears to be a duplicate property node, "
f"but has degree != 1",
current_perception,
)
continue
else:
external_properties.add(prop)
perception_digraph.add_edge(
matched_subgraph_node_predecessor,
object_semantic_node,
label=edge_label,
)
if root in SHARED_WORLD_ITEMS:
raise RuntimeError(
f"Pattern match root cannot be a shared world item, "
f"but got match {pattern_match}")
perception_digraph.remove_node(root)
# We want to re-add any relationships linked directly to the root node of an object.
# Example: water is a liquid
# Example: this hand is a part of this person
# These may be relevant to learning verb semantics
# (e.g. you can only drink a liquid)
_add_relationships_linked_to_root_object_perception(
original_graph=current_perception.copy_as_digraph(),
output_graph=perception_digraph,
matched_nodes=matched_subgraph_nodes,
matched_object_node=object_semantic_node,
)
return PerceptionGraph(perception_digraph,
dynamic=current_perception.dynamic)
def replace_match_with_object_graph_node(
matched_object_node: ObjectSemanticNode,
current_perception: PerceptionGraph,
pattern_match: PerceptionGraphPatternMatch,
) -> PerceptionGraphWithReplacedObjectResult:
"""
Internal function to replace the nodes of the perception matched by the object pattern
with an `ObjectSemanticNode`.
Any external relationships those nodes had is inherited by the `ObjectSemanticNode`.
"""
perception_digraph = current_perception.copy_as_digraph()
perception_digraph.add_node(matched_object_node)
matched_subgraph_nodes: ImmutableSet[PerceptionGraphNode] = immutableset(
[
node for node in pattern_match.matched_sub_graph._graph.nodes # pylint:disable=protected-access
if node in perception_digraph.nodes
],
disable_order_check=True,
)
# Multiple sub-objects of a matched object may link to the same property
# (for example, to a color shared by all the parts).
# In this case, we want the shared object node to link to this property only once.
external_properties: Set[Union[OntologyNode, ObjectSemanticNode]] = set()
duplicate_nodes_to_remove: List[PerceptionGraphNode] = []
for matched_subgraph_node in matched_subgraph_nodes:
if isinstance(matched_subgraph_node, ObjectSemanticNode):
raise RuntimeError(
f"We do not currently allow object recognitions to themselves "
f"operate over other object recognitions, but got match "
f"{pattern_match.matched_sub_graph}")
# A pattern might refer to shared parts of the world like the learner
# or the ground, and we don't want the replacement root to inherit the
# shared world item's relationships.
if matched_subgraph_node in SHARED_WORLD_ITEMS:
continue
# If there is an edge from the matched sub-graph to a node outside it,
# also add an edge from the object match node to that node.
for matched_subgraph_node_successor in perception_digraph.successors(
matched_subgraph_node):
edge_label = _get_edge_label(perception_digraph,
matched_subgraph_node,
matched_subgraph_node_successor)
# don't want to add edges which are internal to the matched sub-graph
if matched_subgraph_node_successor not in matched_subgraph_nodes:
if edge_equals_ignoring_temporal_scope(edge_label,
HAS_PROPERTY_LABEL):
# Prevent multiple `has-property` assertions to the same color node
# On a recognized object
# Also prevent size relations from being inherited on root object.
if matched_subgraph_node_successor[
0] in external_properties or matched_subgraph_node_successor[
0] in {
SMALLER_THAN,
BIGGER_THAN,
ABOUT_THE_SAME_SIZE_AS_LEARNER,
}:
if (perception_digraph.degree(
matched_subgraph_node_successor) != 1):
raise_graph_exception(
f"Node {matched_subgraph_node_successor} "
f"appears to be a duplicate property node, "
f"but has degree != 1",
current_perception,
)
duplicate_nodes_to_remove.append(
matched_subgraph_node_successor)
continue
else:
external_properties.add(
matched_subgraph_node_successor[0])
perception_digraph.add_edge(matched_object_node,
matched_subgraph_node_successor,
label=edge_label)
# If there is an edge to the matched sub-graph from a node outside it,
# also add an edge to the object match node from that node.
for matched_subgraph_node_predecessor in perception_digraph.predecessors(
matched_subgraph_node):
edge_label = _get_edge_label(
perception_digraph,
matched_subgraph_node_predecessor,
matched_subgraph_node,
)
# don't want to add edges which are internal to the matched sub-graph
if matched_subgraph_node_predecessor not in matched_subgraph_nodes:
if edge_equals_ignoring_temporal_scope(edge_label,
HAS_PROPERTY_LABEL):
# Prevent multiple `has-property` assertions to the same color node
# On a recognized object
if isinstance(matched_subgraph_node_predecessor,
ObjectSemanticNode):
prop = matched_subgraph_node_predecessor
else:
prop = matched_subgraph_node_predecessor[0]
if prop in external_properties:
if (perception_digraph.degree(
matched_subgraph_node_predecessor) != 1):
raise_graph_exception(
f"Node {matched_subgraph_node_predecessor} "
f"appears to be a duplicate property node, "
f"but has degree != 1",
current_perception,
)
duplicate_nodes_to_remove.append(
matched_subgraph_node_predecessor)
continue
else:
external_properties.add(prop)
perception_digraph.add_edge(
matched_subgraph_node_predecessor,
matched_object_node,
label=edge_label,
)
# Remove all matched nodes which are not shared world items (e.g. gravity, the learner)
to_remove = immutableset([
matched_node for matched_node in matched_subgraph_nodes
if matched_node not in SHARED_WORLD_ITEMS
] + duplicate_nodes_to_remove)
perception_digraph.remove_nodes_from(to_remove)
# We want to re-add any properties linked directly to the root node of an object.
# Example: water is a liquid
# These may be relevant to learning verb semantics
# (e.g. you can only drink a liquid)
_add_external_properties_linked_to_root_object_perception(
original_graph=current_perception.copy_as_digraph(),
output_graph=perception_digraph,
matched_nodes=matched_subgraph_nodes,
matched_object_node=matched_object_node,
)
# We also want to re-add any relationships directly linked to the root node of an object.
# These may have been overwritten when iterating over the matched nodes.
# Example: ball is behind table
_add_external_relationships_linked_to_root_object_perception(
original_graph=current_perception.copy_as_digraph(),
output_graph=perception_digraph,
matched_nodes=matched_subgraph_nodes,
matched_object_node=matched_object_node,
)
return PerceptionGraphWithReplacedObjectResult(
PerceptionGraph(perception_digraph,
dynamic=current_perception.dynamic), to_remove)
