def replace_sub_graph(self, graph: Graph, external_match: dict):
loop_node = external_match['while']
body_graph = loop_node['body']
body_pattern = KerasRNNOutputConcatenation.get_body_pattern()
internal_matches = find_subgraph_match_to_pattern(
body_graph, body_pattern)
if len(internal_matches) == 1:
internal_match = internal_matches[0]
reserve_port_idx = compute_input_port_idx(
external_match['reserve'], loop_node)
stack_port_idx = external_match['stack'].in_port(
0).get_source().idx
# check that back edges connect correct Parameter and Result nodes in the body
# check connections between body input ports and external inputs ports of Loop node
# check connections between body output ports and external output ports of Loop node
if Loop.back_edge_exists(loop_node.back_edges, internal_match['concatenation_result'].internal_layer_id,
internal_match['container'].internal_layer_id) and \
Loop.back_edge_exists(loop_node.back_edges,
internal_match['increment_iteration_result'].internal_layer_id,
internal_match['current_iteration'].internal_layer_id) and \
Loop.inter_edge_exists(loop_node.input_port_map, reserve_port_idx,
internal_match['container'].internal_layer_id) and \
Loop.inter_edge_exists(loop_node.output_port_map, stack_port_idx,
internal_match['concatenation_result'].internal_layer_id):
KerasRNNOutputConcatenation.transform_keras_rnn_output_concatenation(
external_match, internal_match)
def replace_sub_graph(self, graph: Graph, external_match: dict):
loop_node = external_match['while']
body_graph = loop_node['body']
body_pattern = KerasRNNInputSlicing.get_body_pattern()
internal_matches = find_subgraph_match_to_pattern(
body_graph, body_pattern)
# a case of multiple matches is not handled since it is not clear how to select corresponding match
if len(internal_matches) == 1:
internal_match = internal_matches[0]
loop_node = external_match['while']
unstack_port_idx = compute_input_port_idx(
external_match['unstack'], loop_node)
# check that back edges connect correct Parameter and Result nodes in the body
# check connections between body input ports and external inputs ports of Loop node
if Loop.back_edge_exists(loop_node.back_edges,
internal_match['increment_iteration_result'].internal_layer_id,
internal_match['current_iteration'].internal_layer_id) and \
Loop.inter_edge_exists(loop_node.input_port_map, unstack_port_idx,
internal_match['tensor_list'].internal_layer_id):
# only if inter-graph match passed it starts to process the sub-graph
KerasRNNInputSlicing.transform_keras_rnn_input_slicing(
external_match, internal_match)