def get_tf_edges(node: Node):
"""
By TF/NX node find all inputs and return list of all edges.
Edge direction represents data flow (from source op to this node).
So the resulting list contains all input edges for a given node.
Edge attributes: 'in' is index of input port for a given node, 'out' is an index
of output port of some other node that produces input data for this node.
"""
edge_list = []
for in_port, src_node_id in enumerate(node.pb.input):
src_node, src_port = get_tf_node_port(src_node_id)
cf_flag = False
if src_node[0] == '^':
src_node = src_node[1:]
cf_flag = True
edge = (
src_node,
node.id,
{
'in': in_port,
'out': src_port,
'fw_tensor_debug_info': [
(src_node_id, src_port)
], # debug anchor for a framework tensor name and port
'in_attrs': ['in', 'control_flow_edge', 'permutation'],
'out_attrs': ['out', 'permutation'],
'data_attrs': ['fw_tensor_debug_info'],
'control_flow_edge': cf_flag
})
edge_list.append(edge)
return edge_list
def add_placeholders_to_subgraph(node: Node):
"""
Adds placeholders to the node's list of protobufs based on input nodes to the subgraph (the value of
'internal_input_node_name' property).
The function also updates input tensors for nodes which consume output of nodes that were replaced with
placeholders.
:param node: the node to add placeholders to.
:return: None
"""
inputs_replacements = list()
for index, (in_data_node,
edge_attrs) in enumerate(node.get_sorted_inputs()):
if 'control_flow_edge' in edge_attrs and edge_attrs[
'control_flow_edge']:
continue
if 'internal_input_node_name' in edge_attrs.keys():
input_tensor_name = edge_attrs['internal_input_node_name']
else:
input_tensor_name = node['pb'].input[index]
input_node_name, port = get_tf_node_port(input_tensor_name)
placeholder_name = placeholder_name_for_node(input_node_name, port)
edge_attrs['placeholder_name'] = placeholder_name
in_node = node.in_node(index)
assert in_node.shape is not None
if placeholder_name not in node['pbs'].keys():
placeholder = tf_v1.placeholder(determine_data_type(in_node),
in_node.shape, placeholder_name)
inputs_replacements.append((input_tensor_name, placeholder_name))
add_node_def_to_subgraph(node,
placeholder.op.node_def,
is_input=True)
log.debug(
"Added placeholder with name '{}'".format(placeholder_name))
# update initial input names to a transposed ones
for old_input_tensor_name, new_name in inputs_replacements:
update_input_in_pbs(node, old_input_tensor_name, new_name)
def create_tf_edge(src_node_id: str, dst_node_id: str, in_port: int):
"""
Creates an edge for given nodes and input port.
"""
src_node, src_port = get_tf_node_port(src_node_id)
tensor_name = src_node + ":" + str(src_port)
cf_flag = False
if src_node[0] == '^':
src_node = src_node[1:]
cf_flag = True
return (src_node, dst_node_id, {
'in': in_port,
'out': src_port,
# debug anchor for a framework name, out port and tensor name
'fw_tensor_debug_info': [(src_node_id, src_port, tensor_name)],
'in_attrs': ['in', 'control_flow_edge', 'permutation'],
'out_attrs': ['out', 'permutation'],
'data_attrs': ['fw_tensor_debug_info'],
'control_flow_edge': cf_flag
})
