def test_name_looks_like_port_number(self):
nodes = {
'input_id': {
'type': 'Parameter',
'kind': 'op',
'op': 'Parameter',
'name': '0'
},
'conv_id': {
'type': 'Convolution',
'kind': 'op',
'op': 'NotPlaceholder',
'name': '1'
},
'relu_id': {
'type': 'ReLU',
'kind': 'op',
'op': 'NotPlaceholder',
'name': '2'
},
}
edges = [
('input_id', 'conv_id'),
('conv_id', 'relu_id'),
]
graph = build_graph(nodes, edges)
node_id, direction, port = get_node_id_with_ports(graph, '0:2')
self.assertEqual(node_id, 'relu_id')
self.assertEqual(direction, 'in')
self.assertEqual(port, 0)
def find_and_replace_pattern(self, graph: Graph):
values = graph.graph['cmd_params'].mean_scale_values
input_nodes = graph.get_op_nodes(op='Parameter')
if not isinstance(values, dict):
# The case when input names to apply mean/scales weren't specified
if len(values) != len(input_nodes):
raise Error('Numbers of inputs and mean/scale values do not match. ' + refer_to_faq_msg(61))
data = np.copy(values)
values = {}
for idx, node in enumerate(input_nodes):
values.update(
{
node.soft_get('name', node.id): {
'mean': data[idx][0],
'scale': data[idx][1]
}
}
)
for node_name, node_mean_scale_values in values.items():
node_id = None
node_name = get_node_name_with_port_from_input_value(node_name)
try:
node_id, direction, port = get_node_id_with_ports(graph, node_name, skip_if_no_port=False)
assert direction != 'out', 'Only input port can be specified for mean/scale application'
except Error as e:
log.warning('node_name {} is not found in graph'.format(node_name))
if Node(graph, node_id) not in input_nodes:
# if the user cutted-off input of the network then input node name specified in the --scale_values
# or --mean_values doesn't correspond to a real input node generated by Model Optimizer. But
# the information about initial input node name is stored in Placeholder's attribute 'initial_node_name'
new_node_id = None
for placeholder in input_nodes:
try:
placeholder_port = int(placeholder.id.split("_")[-1])
except Exception as ex:
log.debug('Can not get the port number from the node {}'.format(placeholder.id))
log.debug('Port will be defined as None')
port = None
if placeholder.has('initial_node_name') and placeholder.initial_node_name == node_id and (
port is None or placeholder_port == port):
new_node_id = placeholder.id
break
if new_node_id is None:
raise Error('Input with name {} wasn\'t found!'.format(node_name) +
refer_to_faq_msg(83))
node_id = new_node_id
input_node = Node(graph, node_id)
AddMeanScaleValues.apply_scale(graph, input_node, node_mean_scale_values)
AddMeanScaleValues.apply_mean_value(graph, input_node, node_mean_scale_values)
def test_no_port1(self):
node_id, direction, port = get_node_id_with_ports(
self.graph, '1input1')
self.assertEqual(node_id, 'conv_id')
self.assertEqual(direction, 'port')
self.assertEqual(port, None)
def test_in_port2(self):
node_id, direction, port = get_node_id_with_ports(
self.graph, '0:relu:0')
self.assertEqual(node_id, 'squeeze_id')
self.assertEqual(direction, 'in')
self.assertEqual(port, 0)
def test_in_port1(self):
node_id, direction, port = get_node_id_with_ports(
self.graph, '0:1input1')
self.assertEqual(node_id, 'conv_id')
self.assertEqual(direction, 'in')
self.assertEqual(port, 0)
def test_out_port(self):
node_id, direction, port = get_node_id_with_ports(
self.graph, '1input1:0:0')
self.assertEqual(node_id, 'input_id')
self.assertEqual(direction, 'out')
self.assertEqual(port, 0)
