def operate(self):
"""Perform all jobs assigned to the surgeon.
"""
# Operate on each node in self.nodes by order of decreasing depth.
sorted_nodes = sorted(
self.nodes,
reverse=True,
key=lambda x: utils.get_node_depth(self.model, x))
for node in sorted_nodes:
# Rebuild submodel up to this node
sub_output_nodes = utils.get_node_inbound_nodes(node)
outputs, output_masks = self._rebuild_graph(
self.model.inputs, sub_output_nodes)
# Perform surgery at this node
kwargs = self._kwargs_map[node]
self._mod_func_map[node](node, outputs, output_masks, **kwargs)
# Finish rebuilding model
output_nodes = []
for output in self.model.outputs:
layer, node_index, tensor_index = output._keras_history
output_nodes.append(get_inbound_nodes(layer)[node_index])
new_outputs, _ = self._rebuild_graph(self.model.inputs, output_nodes)
new_model = self._model_cls(self.model.inputs, new_outputs)
if self._copy:
return utils.clean_copy(new_model, self._custom_objects)
else:
return new_model
def operate(self):
"""Perform all jobs assigned to the surgeon.
"""
# Operate on each node in self.nodes by order of decreasing depth.
sorted_nodes = sorted(
self.nodes,
reverse=True,
key=lambda x: utils.get_node_depth(self.model, x))
for node in sorted_nodes:
# Rebuild submodel up to this node
sub_output_nodes = utils.get__inbound_nodes(node)
outputs, output_masks = self._rebuild_graph(
self.model.inputs, sub_output_nodes)
# Perform surgery at this node
kwargs = self._kwargs_map[node]
self._mod_func_map[node](node, outputs, output_masks, **kwargs)
# Finish rebuilding model
output_nodes = [
self.model.output_layers[i]._inbound_nodes[node_index] for i,
node_index in enumerate(self.model.output_layers_node_indices)
]
new_outputs, _ = self._rebuild_graph(self.model.inputs, output_nodes)
new_model = Model(self.model.inputs, new_outputs)
if self._copy:
return utils.clean_copy(new_model)
else:
return new_model