ie_api.IENetwork Class Reference

This class contains the information about the network model read from IR and allows you to manipulate with some model parameters such as layers affinity and output layers. More...

Public Member Functions
def	__init__ (self, model, weights, init_from_buffer)
	Class constructor. More...
def	name (self)
	Name of the loaded network.
def	input_info (self)
	A dictionary that maps input layer names to InputInfoPtr objects.
def	inputs (self)
def	outputs (self)
	A dictionary that maps output layer names to DataPtr objects.
def	batch_size (self)
	Batch size of the network. More...
def	batch_size (self, batch)
def	add_outputs (self, outputs)
	Marks any intermediate layer as output layer to retrieve the inference results from the specified layers. More...
def	serialize (self, path_to_xml, path_to_bin)
	Serializes the network and stores it in files. More...
def	reshape (self, input_shapes)
	Reshapes the network to change spatial dimensions, batch size, or any dimension. More...

Data Fields
	name
	Name of the loaded network.
	input_info
	A dictionary that maps input layer names to InputInfoPtr objects.
	inputs
	outputs
	A dictionary that maps output layer names to DataPtr objects.
	batch_size
	Batch size of the network. More...

Detailed Description

This class contains the information about the network model read from IR and allows you to manipulate with some model parameters such as layers affinity and output layers.

Constructor & Destructor Documentation

__init__()

def ie_api.IENetwork.__init__	(		self,
			model,
			weights,
			init_from_buffer
	)

Class constructor.

Note

Reading networks using IENetwork constructor is deprecated. Please, use IECore.read_network() method instead.

Parameters

model	A .xml file of the IR or PyCapsule containing smart pointer to nGraph function. In case of passing a .xml file attribute value can be a string path or bytes with file content depending on init_from_buffer attribute value
weights	A .bin file of the IR. Depending on init_from_buffer value, can be a string path or bytes with file content.
init_from_buffer	Defines the way of how model and weights attributes are interpreted. If False, attributes are interpreted as strings with paths to .xml and .bin files of IR. If True, they are interpreted as Python bytes object with .xml and .bin files content. Ignored in case of IENetwork object initialization from nGraph function.

Returns

Instance of IENetwork class

Usage example:
Initializing IENetwork object from IR files:

net = IENetwork(model=path_to_xml_file, weights=path_to_bin_file)

Initializing IENetwork object bytes with content of IR files:

with open(path_to_bin_file, 'rb') as f:
    bin = f.read()
with open(path_to_xml_file, 'rb') as f:
    xml = f.read()
net = IENetwork(model=xml, weights=bin, init_from_buffer=True)

Member Function Documentation

add_outputs()

def ie_api.IENetwork.add_outputs	(		self,
			outputs
	)

Marks any intermediate layer as output layer to retrieve the inference results from the specified layers.

Parameters

outputs

List of layers to be set as model outputs. The list can contain strings with layer names to be set as outputs or tuples with layer name as first element and output port id as second element. In case of setting one layer as output, string or tuple with one layer can be provided.

Returns

None

Usage example:

ie = IECore()
net = ie.read_network(model=path_to_xml_file, weights=path_to_bin_file)
net.add_outputs(["conv5_1', conv2_1', (split_2, 1)])]

batch_size()

def ie_api.IENetwork.batch_size

(

self

)

Batch size of the network.

Provides getter and setter interfaces to get and modify the network batch size. For example:

ie = IECore()
net = ie.read_network(model=path_to_xml_file, weights=path_to_bin_file)
print(net.batch_size)
net.batch_size = 4
print(net.batch_size)
print(net.input_info['data'].input_data.shape)

inputs()

def ie_api.IENetwork.inputs

(

self

)

Note

The property is deprecated. Please use the input_info property to get the map of inputs

A dictionary that maps input layer names to DataPtr objects

reshape()

def ie_api.IENetwork.reshape	(		self,
			input_shapes
	)

Reshapes the network to change spatial dimensions, batch size, or any dimension.

Note

Before using this method, make sure that the target shape is applicable for the network. Changing the network shape to an arbitrary value may lead to unpredictable behaviour.

Parameters

input_shapes

A dictionary that maps input layer names to tuples with the target shape

Returns

None

Usage example:

ie = IECore()
net = ie.read_network(model=path_to_xml_file, weights=path_to_bin_file)
input_layer = next(iter(net.input_info))
n, c, h, w = net.input_info[input_layer].input_data.shape
net.reshape({input_layer: (n, c, h*2, w*2)})

serialize()

def ie_api.IENetwork.serialize	(		self,
			path_to_xml,
			path_to_bin
	)

Serializes the network and stores it in files.

Parameters

path_to_xml	Path to a file, where a serialized model will be stored
path_to_bin	Path to a file, where serialized weights will be stored

Returns

None

Usage example:

ie = IECore()
net = ie.read_network(model=path_to_xml, weights=path_to_bin)
net.serialize(path_to_xml, path_to_bin)

Field Documentation

batch_size

ie_api.IENetwork.batch_size

Batch size of the network.

Provides getter and setter interfaces to get and modify the network batch size. For example:

ie = IECore()
net = ie.read_network(model=path_to_xml_file, weights=path_to_bin_file)
print(net.batch_size)
net.batch_size = 4
print(net.batch_size)
print(net.input_info['data'].input_data.shape)

inputs

ie_api.IENetwork.inputs

Note

The property is deprecated. Please use the input_info property to get the map of inputs

A dictionary that maps input layer names to DataPtr objects

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The documentation for this class was generated from the following file:

• ie_api.pyx