def __init__(self, graph):
import keras
self.graph = graph
self.layers = []
for layer in graph.layer_list:
self.layers.append(to_real_keras_layer(layer))
# Construct the keras graph.
# Input
topo_node_list = self.graph.topological_order
output_id = topo_node_list[-1]
input_id = topo_node_list[0]
input_tensor = keras.layers.Input(
shape=graph.node_list[input_id].shape)
node_list = deepcopy(self.graph.node_list)
node_list[input_id] = input_tensor
# Output
for v in topo_node_list:
for u, layer_id in self.graph.reverse_adj_list[v]:
layer = self.graph.layer_list[layer_id]
keras_layer = self.layers[layer_id]
if isinstance(layer, (StubAdd, StubConcatenate)):
edge_input_tensor = list(
map(lambda x: node_list[x],
self.graph.layer_id_to_input_node_ids[layer_id]))
else:
edge_input_tensor = node_list[u]
temp_tensor = keras_layer(edge_input_tensor)
node_list[v] = temp_tensor
output_tensor = node_list[output_id]
self.model = keras.models.Model(inputs=input_tensor,
outputs=output_tensor)
if graph.weighted:
for index, layer in enumerate(self.layers):
set_stub_weight_to_keras(self.graph.layer_list[index], layer)
def __init__(self, graph):
self.graph = graph
self.layers = []
for layer in graph.layer_list:
self.layers.append(to_real_keras_layer(layer))
# Construct the keras graph.
# Input
topo_node_list = self.graph.topological_order
output_id = topo_node_list[-1]
input_id = topo_node_list[0]
input_tensor = keras.layers.Input(shape=graph.node_list[input_id].shape)
node_list = deepcopy(self.graph.node_list)
node_list[input_id] = input_tensor
# Output
for v in topo_node_list:
for u, layer_id in self.graph.reverse_adj_list[v]:
layer = self.graph.layer_list[layer_id]
keras_layer = self.layers[layer_id]
if isinstance(layer, (StubAdd, StubConcatenate)):
edge_input_tensor = list(map(lambda x: node_list[x],
self.graph.layer_id_to_input_node_ids[layer_id]))
else:
edge_input_tensor = node_list[u]
temp_tensor = keras_layer(edge_input_tensor)
node_list[v] = temp_tensor
output_tensor = node_list[output_id]
self.model = keras.models.Model(inputs=input_tensor, outputs=output_tensor)
if graph.weighted:
for index, layer in enumerate(self.layers):
set_stub_weight_to_keras(self.graph.layer_list[index], layer)