LEIP Models

class models.Model(options: ModelOptions, framework: Framework, source_file: Optional[Union[str, PathLike]] = None)

Abstract class representing an ML model in a supported framework.

Parameters

  • options (ModelOptions) –

  • framework (Framework) –

  • source_file (Union[str, PathLike]) –

dict() → dict

Gives a serializable dict version of the model. This includes:

options

The options used to load and configure the model.

source_file

The name of the source file from which it was loaded, if any.

source_file_md5_hash

An MD5 hash of the source file.

source_file_size

Source file size in bytes.

framework

The framework of the model.

inputs

A list of input objects with names, shapes and types.

outputs

A list of output objects with names, shapes and types.

weights_count

The amount of tensors in the model.

weights_size

The sum of sizes of all tensors in the model.

weights_data_type

The data type(s) of the tensors in the model.

Returns

Options and metrics as a dict.

Return type

dict

abstract infer(single_input: ndarray) → Tuple[List[ndarray], float]

Runs inference from a numpy array.

Parameters

single_input (ndarray) – A numpy array that will be sent to the model. The array must be of the right type and shape.

Returns

  • list – A list of all the outputs of the model.

  • float – Number of seconds inference took.

Return type

Tuple[List[ndarray], float]

abstract property inputs: List[models.tensors.TensorSpec]

Determines the inputs to the model.

Returns

A list of input objects with names, shapes and types.

Return type

list

abstract property outputs: List[models.tensors.TensorSpec]

Determines the outputs of the model.

Returns

A list of output objects with names, shapes and types.

Return type

list

abstract property weights: List[models.tensors.Tensor]

Determines the tensors of the model.

Returns

A list of all the tensors in the model.

Return type

list

models.load_model(path: Union[str, PathLike], options: ModelOptions = ModelOptions(inference=InferenceOptions(context='cpu', host='localhost', port='50051'), input_names=[], output_names=[], input_shapes=[], remove_nodes=[], custom_objects=None, crc=None, metadata={}, processors_path=None, preprocessor=None, postprocessor=None, output_format='classifier', task_family='classification'), load_baseline_options_from_json: bool = True) → Model

Load a supported model from disk.

Parameters

  • path (Union[str, PathLike]) – Directory or file path to the model files(s). Alternatively, the name of model which has already been installed on an LOR instance.

  • options (ModelOptions) – Options to configure the model. These may also come from a model_schema.json file in the same folder as the model files. Any options defined here override those in that file.

  • load_baseline_options_from_json (bool) – Indicates if model options should also be loaded from model_schema.json file.

Returns

Loaded model object.

Return type

Model

Raises

NotRecognizedModel – If a supported model was not found at the given path, or if the framework needed for it is not installed.

leip.load_compilable_model(path: Union[str, PathLike], options: ModelOptions = ModelOptions(inference=InferenceOptions(context='cpu', host='localhost', port='50051'), input_names=[], output_names=[], input_shapes=[], remove_nodes=[], custom_objects=None, crc=None, metadata={}, processors_path=None, preprocessor=None, postprocessor=None, output_format='classifier', task_family='classification'), load_baseline_options_from_json: bool = True) → CompilableModel

Load a compilable model from disk.

Parameters

  • path (Union[str, PathLike]) – Directory or file path to the model files(s).

  • options (ModelOptions) – Options to configure the model. These may also come from a model_schema.json file in the same folder as the model files. Any options defined here override those in that file.

  • load_baseline_options_from_json (bool) – Indicates if model options should also be loaded from model_schema.json file.

Returns

Loaded model object.

Return type

CompilableModel

Raises

NotRecognizedModel – If a supported model was not found at the given path, or if the framework needed for it is not installed.

class leip.CompilableModel(options: ModelOptions, framework: Framework, source_file: Optional[Union[str, PathLike]] = None)

Abstract class representing a compilable ML model in a supported framework. This class adds additional methods on top of Model that are used when compiling or optimizing a model.

Parameters

  • options (ModelOptions) –

  • framework (Framework) –

  • source_file (Union[str, PathLike]) –