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Zoo Manager Module

degirum.zoo_manager.ZooManager

Class that manages a model zoo.

A model zoo in terminology of PySDK is a collection of AI models and simultaneously an ML inference engine type and location.

Depending on the deployment location, there are several types of model zoos supported by PySDK:

  • Local model zoo: Deployed on the local file system of the PySDK installation host. Inferences are performed on the same host using AI accelerators installed on that host.
  • AI server model zoo: Deployed on remote host with DeGirum AI server running on that host. Inferences are performed by DeGirum AI server on that remote host.
  • Cloud Platform model zoo: Deployed on DeGirum Cloud Platform. Inferences are performed by DeGirum Cloud Platform servers.

The type of the model zoo is defined by the URL string which you pass as zoo_url parameter into the constructor.

Zoo manager provides the following functionality:

  • List and search models available in the connected model zoo.
  • Create AI model handling objects to perform AI inferences.
  • Request various AI model parameters.

degirum.zoo_manager.ZooManager.__init__(inference_host_address, zoo_url, token)

Constructor.

Note

Typically, you never construct ZooManager objects yourself -- instead you call degirum.connect function to create ZooManager instances for you.

For the description of arguments see degirum.connect

degirum.zoo_manager.ZooManager.list_models(*args, **kwargs)

Get a list of names of AI models available in the connected model zoo which match specified filtering criteria.

Other Parameters:

Name Type Description
model_family str

Model family name filter.

  • When you pass a string, it will be used as search substring in the model name. For example, "yolo", "mobilenet".

  • You may also pass re.Pattern object. In this case it will do regular expression pattern search.

runtime str

Runtime agent type -- string or list of strings of runtime agent types.

device str

Target inference device -- string or list of strings of device names.

device_type str

Target inference device(s) -- string or list of strings of full device type names in "RUNTIME/DEVICE" format.

precision str

Model calculation precision - string or list of strings of model precision labels.

Possible labels: "quant", "float".

pruned str

Model density -- string or list of strings of model density labels.

Possible labels: "dense", "pruned".

Returns:

Type Description
List[str]

The list of model name strings matching specified filtering criteria. Use a string from that list as a parameter of degirum.zoo_manager.ZooManager.load_model method.

Example

Find all models of "yolo" family capable to run either on CPU or on DeGirum Orca AI accelerator from all registered model zoos:

    yolo_model_list = zoo_manager.list_models("yolo", device=["cpu", "orca"])

degirum.zoo_manager.ZooManager.load_model(model_name, **kwargs)

Create and return the model handling object for given model name.

Parameters:

Name Type Description Default
model_name str

Model name string identifying the model to load. It should exactly match the model name as it is returned by degirum.zoo_manager.ZooManager.list_models method.

required
**kwargs any

you may pass arbitrary model properties to be assigned to the model object in a form of property=value

{}

Returns:

Type Description
Model

Model handling object. Using this object you perform AI inferences on this model and also configure various model properties, which define how to do input image preprocessing and inference result post-processing:

Inference result object degirum.postprocessor.InferenceResults returned by degirum.model.Model.predict method allows you to access AI inference results:

degirum.zoo_manager.ZooManager.model_info(model_name)

Request model parameters for given model name.

Parameters:

Name Type Description Default
model_name str

Model name string. It should exactly match the model name as it is returned by degirum.zoo_manager.ZooManager.list_models method.

required

Returns:

Type Description
ModelParams

Model parameter object which provides read-only access to all model parameters.

Note

You cannot modify actual model parameters -- any changes of model parameter object returned by this method are not applied to the real model. Use properties of model handling objects returned by degirum.zoo_manager.ZooManager.load_model method to change parameters of that particular model instance on the fly.

degirum.zoo_manager.ZooManager.supported_device_types()

Get runtime/device type names, which are available in the inference system.

Returns:

Type Description
list

list of runtime/device type names; each element is a string in a format "RUNTIME/DEVICE"

degirum.zoo_manager.ZooManager.system_info(update=False)

Return host system information dictionary

Parameters:

Name Type Description Default
update bool

force update system information, otherwise take from cache

False

Returns:

Type Description
dict

host system information dictionary. Format: {"Devices": {"<runtime>/<device>": {<device_info>}, ...}, ["Software Version": "<version>"]}