openvino.inference_engine.ExecutableNetwork¶

class openvino.inference_engine.ExecutableNetwork¶

This class represents a network instance loaded to plugin and ready for inference.

__init__()¶: There is no explicit class constructor. To make a valid instance of ExecutableNetwork, use IECore.load_network() method of the IECore class.

Methods

`__delattr__`(name, /)	Implement delattr(self, name).
`__dir__`()	Default dir() implementation.
`__eq__`(value, /)	Return self==value.
`__format__`(format_spec, /)	Default object formatter.
`__ge__`(value, /)	Return self>=value.
`__getattribute__`(name, /)	Return getattr(self, name).
`__gt__`(value, /)	Return self>value.
`__hash__`()	Return hash(self).
`__init__`	There is no explicit class constructor.
`__init_subclass__`	This method is called when a class is subclassed.
`__le__`(value, /)	Return self<=value.
`__lt__`(value, /)	Return self<value.
`__ne__`(value, /)	Return self!=value.
`__new__`(**kwargs)
`__reduce__`	ExecutableNetwork.__reduce_cython__(self)
`__reduce_ex__`(protocol, /)	Helper for pickle.
`__repr__`()	Return repr(self).
`__setattr__`(name, value, /)	Implement setattr(self, name, value).
`__setstate__`	ExecutableNetwork.__setstate_cython__(self, __pyx_state)
`__sizeof__`()	Size of object in memory, in bytes.
`__str__`()	Return str(self).
`__subclasshook__`	Abstract classes can override this to customize issubclass().
`export`(self, unicode model_file)	Exports the current executable network.
`get_config`(self, unicode config_name)	Gets configuration for current executable network.
`get_exec_graph_info`(self)	Gets executable graph information from a device
`get_idle_request_id`(self)	Get idle request ID
`get_metric`(self, unicode metric_name)	Gets general runtime metric for an executable network.
`infer`(self[, inputs])	Starts synchronous inference for the first infer request of the executable network and returns output data.
`set_config`(self, dict config)
`start_async`(self, request_id[, inputs])	Starts asynchronous inference for specified infer request.
`wait`(self[, num_requests, timeout])	Waits when the result from any request becomes available.

Attributes

`__pyx_vtable__`
`_infer_requests`	_infer_requests: object
`_requests`	_requests: object
`input_info`	A dictionary that maps input layer names to InputInfoCPtr objects
`outputs`	A dictionary that maps output layer names to CDataPtr objects
`requests`	A tuple of `InferRequest` instances

__class__¶: alias of type

__delattr__(name, /)¶: Implement delattr(self, name).

__dir__()¶: Default dir() implementation.

__eq__(value, /)¶: Return self==value.

__format__(format_spec, /)¶: Default object formatter.

__ge__(value, /)¶: Return self>=value.

__getattribute__(name, /)¶: Return getattr(self, name).

__gt__(value, /)¶: Return self>value.

__hash__()¶: Return hash(self).

__init__()¶: There is no explicit class constructor. To make a valid instance of ExecutableNetwork, use IECore.load_network() method of the IECore class.

__init_subclass__()¶

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__(value, /)¶: Return self<=value.

__lt__(value, /)¶: Return self<value.

__ne__(value, /)¶: Return self!=value.

__new__(**kwargs)¶

__pyx_vtable__ = <capsule object NULL>¶

__reduce__()¶: ExecutableNetwork.__reduce_cython__(self)

__reduce_ex__(protocol, /)¶: Helper for pickle.

__repr__()¶: Return repr(self).

__setattr__(name, value, /)¶: Implement setattr(self, name, value).

__setstate__()¶: ExecutableNetwork.__setstate_cython__(self, __pyx_state)

__sizeof__()¶: Size of object in memory, in bytes.

__str__()¶: Return str(self).

__subclasshook__()¶

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

_infer_requests¶: _infer_requests: object

_requests¶: _requests: object

export(self, unicode model_file: str)¶

Exports the current executable network.

Parameters: model_file – Full path to the target exported file location
Returns: None

ie = IECore()
net = ie.read_network(model=path_to_xml_file, weights=path_to_bin_file)
exec_net = ie.load_network(network=net, device_name="MYRIAD", num_requests=2)
exec_net.export(path_to_file_to_save)

get_config(self, unicode config_name: str)¶

Gets configuration for current executable network. The method is responsible to extract information which affects executable network execution

Parameters: config_name – A configuration parameter name to request.
Returns: A configuration value corresponding to a configuration key.

Usage example:

ie = IECore()
net = ie.read_network(model=path_to_xml_file, weights=path_to_bin_file)
exec_net = ie.load_network(net, "CPU")
config = exec_net.get_config("CPU_BIND_THREAD")

get_exec_graph_info(self)¶

Gets executable graph information from a device

Returns: An instance of IENetwork

Usage example:

ie_core = IECore()
net = ie_core.read_network(model=path_to_xml_file, weights=path_to_bin_file)
exec_net = ie_core.load_network(net, device, num_requests=2)
exec_graph = exec_net.get_exec_graph_info()

get_idle_request_id(self)¶

Get idle request ID

Returns: Request index

get_metric(self, unicode metric_name: str)¶

Gets general runtime metric for an executable network. It can be network name, actual device ID on which executable network is running or all other properties which cannot be changed dynamically.

Parameters: metric_name – A metric name to request.
Returns: A metric value corresponding to a metric key.

Usage example:

ie = IECore()
net = ie.read_network(model=path_to_xml_file, weights=path_to_bin_file)
exec_net = ie.load_network(net, "CPU")
exec_net.get_metric("NETWORK_NAME")

infer(self, inputs=None)¶

Starts synchronous inference for the first infer request of the executable network and returns output data. Wraps InferRequest.infer() method of the InferRequest class

Parameters: inputs – A dictionary that maps input layer names to numpy.ndarray objects of proper shape with input data for the layer
Returns: A dictionary that maps output layer names to numpy.ndarray objects with output data of the layer

Usage example:

ie_core = IECore()
net = ie_core.read_network(model=path_to_xml_file, weights=path_to_bin_file)
exec_net = ie_core.load_network(network=net, device_name="CPU", num_requests=2)
res = exec_net.infer({'data': img})
res
{'prob': array([[[[2.83426580e-08]],
              [[2.40166020e-08]],
              [[1.29469613e-09]],
              [[2.95946148e-08]]
              ......
             ]])}

input_info¶: A dictionary that maps input layer names to InputInfoCPtr objects

outputs¶: A dictionary that maps output layer names to CDataPtr objects

requests¶: A tuple of InferRequest instances

set_config(self, dict config: dict)¶

start_async(self, request_id, inputs=None)¶

Starts asynchronous inference for specified infer request. Wraps InferRequest.async_infer() method of the InferRequest class.

Parameters

request_id – Index of infer request to start inference
inputs – A dictionary that maps input layer names to numpy.ndarray objects of proper shape with input data for the layer

Returns

A handler of specified infer request, which is an instance of the InferRequest class.

Usage example:

infer_request_handle = exec_net.start_async(request_id=0, inputs={input_blob: image})
infer_status = infer_request_handle.wait()
res = infer_request_handle.output_blobs[out_blob_name]

wait(self, num_requests=None, timeout=None)¶

Waits when the result from any request becomes available. Blocks until specified timeout elapses or the result.

Parameters

num_requests – Number of idle requests for which wait. If not specified, num_requests value is set to number of requests by default.
timeout – Time to wait in milliseconds or special (0, -1) cases described above. If not specified, timeout value is set to -1 by default.

Returns

Request status code: OK or RESULT_NOT_READY

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