def function_testcase_helper(node: NodeProto, input_types: List[TypeProto],
name: Text) -> List[NodeProto]:
test_op = node.op_type
op_prefix = test_op + "_" + name + "_expanded_function_"
schema = onnx.defs.get_schema(test_op, node.domain)
if schema.has_function: # type: ignore
function_proto = schema.function_body # type: ignore
elif schema.has_context_dependent_function: # type: ignore
function_proto_str = schema.get_context_dependent_function(
node.SerializeToString(),
[t.SerializeToString() for t in input_types]) # type: ignore
function_proto = FunctionProto()
function_proto.ParseFromString(function_proto_str)
else:
return []
for attr in schema.attributes:
if attr in [a.name for a in node.attribute]:
continue
if schema.attributes[attr].default_value:
node.attribute.extend([schema.attributes[attr].default_value])
# function_proto.attributes
node_list = function_expand_helper(node, function_proto, op_prefix)
return node_list
def _rename_edges_helper(internal_node: NodeProto,
rename_helper: Callable[[Text], Text],
attribute_map: Dict[Text, AttributeProto],
prefix: Text) -> NodeProto:
new_node = NodeProto()
new_node.CopyFrom(internal_node)
new_node.ClearField("input")
new_node.ClearField("output")
new_node.ClearField("attribute")
for internal_name in internal_node.input:
new_node.input.append(rename_helper(internal_name))
for internal_name in internal_node.output:
new_node.output.append(rename_helper(internal_name))
for attr in internal_node.attribute:
if attr.HasField("ref_attr_name"):
if attr.ref_attr_name in attribute_map:
new_attr = AttributeProto()
new_attr.CopyFrom(
attribute_map[attr.ref_attr_name]) # type: ignore
new_attr.name = attr.name
new_node.attribute.extend([new_attr])
else:
new_attr = AttributeProto()
new_attr.CopyFrom(attr)
if attr.type == AttributeProto.GRAPH:
new_graph = new_attr.g
sg_rename = {}
for in_desc in new_graph.input:
sg_rename[
in_desc.name] = in_desc.name = prefix + in_desc.name
for out_desc in new_graph.output:
sg_rename[
out_desc.name] = out_desc.name = prefix + out_desc.name
for init_desc in new_graph.initializer:
sg_rename[init_desc.
name] = init_desc.name = prefix + init_desc.name
for sparse_init_desc in new_graph.sparse_initializer:
sg_rename[sparse_init_desc.values.name] = sparse_init_desc.values.name = prefix + \
sparse_init_desc.values.name
for sparse_init_desc in new_graph.sparse_initializer:
sg_rename[sparse_init_desc.indices.name] = sparse_init_desc.indices.name = prefix + \
sparse_init_desc.indices.name
def subgraph_rename_helper(name: Text) -> Any:
if name in sg_rename:
return sg_rename[name]
else:
return rename_helper(name)
new_nodes = [
_rename_edges_helper(node_desc, subgraph_rename_helper,
attribute_map, prefix)
for node_desc in new_graph.node
]
new_graph.ClearField("node")
new_graph.node.extend(new_nodes)
new_node.attribute.extend([new_attr])
return new_node
def function_expand_helper(
node, # type: NodeProto
function_proto, # type: FunctionProto
op_prefix # type: Text
): # type: (...) -> List[NodeProto]
node_list = []
io_names_map = dict()
attribute_map = dict((a.name, a) for a in node.attribute)
for idx in range(len(function_proto.input)):
io_names_map[function_proto.input[idx]] = node.input[idx] \
if idx in range(len(node.input)) else ""
for idx in range(len(function_proto.output)):
# Even if the node has been created with optional outputs missing, we
# can't assume that the function body handles this correctly, such as in
# the case that output is also an intermediate value.
# So we only add a name mapping if the output is present. An internal
# name will be generated if the missing output is used, the same as any
# other internal tensor.
if idx in range(len(node.output)) and node.output[idx] != "":
io_names_map[function_proto.output[idx]] = node.output[idx]
for internal_node in function_proto.node:
new_node = NodeProto()
new_node.CopyFrom(internal_node)
new_node.ClearField("input")
new_node.ClearField("output")
new_node.ClearField("attribute")
for internal_name in internal_node.input:
if internal_name in io_names_map:
new_node.input.append(io_names_map[internal_name])
else:
new_node.input.append(op_prefix + internal_name)
for internal_name in internal_node.output:
if internal_name in io_names_map:
new_node.output.append(io_names_map[internal_name])
else:
new_node.output.append(op_prefix + internal_name)
for attr in internal_node.attribute:
if attr.HasField("ref_attr_name"):
if attr.ref_attr_name in attribute_map:
new_attr = AttributeProto()
new_attr.CopyFrom(
attribute_map[attr.ref_attr_name]) # type: ignore
new_attr.name = attr.name
new_node.attribute.extend([new_attr])
else:
new_attr = AttributeProto()
new_attr.CopyFrom(attr)
new_node.attribute.extend([new_attr])
node_list.append(new_node)
return node_list
def function_expand_helper(
node, # type: NodeProto
function_proto, # type: FunctionProto
op_prefix # type: Text
): # type: (...) -> List[NodeProto]
node_list = []
input_names_map = dict()
output_names_map = dict()
attribute_map = node.attribute
for idx in range(len(function_proto.input)):
input_names_map[function_proto.input[idx]] = node.input[idx] \
if idx in range(len(node.input)) else ""
for idx in range(len(function_proto.output)):
output_names_map[function_proto.output[idx]] = node.output[idx] \
if idx in range(len(node.output)) else ""
for internal_node in function_proto.node:
new_node = NodeProto()
new_node.CopyFrom(internal_node)
new_node.ClearField("input")
new_node.ClearField("output")
new_node.ClearField("attribute")
for internal_name in internal_node.input:
if internal_name in input_names_map:
new_node.input.append(input_names_map[internal_name])
else:
new_node.input.append(op_prefix + internal_name)
for internal_name in internal_node.output:
if internal_name in output_names_map:
new_node.output.append(output_names_map[internal_name])
else:
new_node.output.append(op_prefix + internal_name)
for attr in internal_node.attribute:
if attr.HasField("ref_attr_name"):
if attr.ref_attr_name in attribute_map:
new_attr = AttributeProto()
new_attr.CopyFrom(
attribute_map[attr.ref_attr_name]) # type: ignore
new_node.attribute.extend([new_attr])
else:
new_attr = AttributeProto()
new_attr.CopyFrom(attr)
new_node.attribute.extend([new_attr])
node_list.append(new_node)
return node_list
