waylay-ml-adapter-base 0.1.1

ml-adapter base classes.

waylay-ml-adapter-base

Provides the ml_adapter.base module for the Waylay ML Adapter solution.

To use an ML Adapter in a Waylay plugin or webscript, use the adapter relevant to your machine learning framework:

• waylay-ml-adapter-numpy for generic models that use numpy data representation
• waylay-ml-adapter-sklearn for scikit-learn models.
• waylay-ml-adapter-torch for pytorch models.

This waylay-ml-adapter-base module provides the framework for these adapters. Only if you would need to create an adapter utility for another framework, you would install this module separately:

pip install waylay-ml-adapter-base

Classes exported by ml_adapter.base

The module ml_adapter.base exports the following classes

PythonMLAdapter

ml_adapter.base.assets.python_ml.PythonMLAdapter extending ml_adapter.base.assets.python.PythonFunctionAdapter

Base adapter for a python ML function.

Adds methods to intialize the manifest and script for a python plugin or webscript.

• as_webscript() initializes the manifest and script for a webscript that uses an ML Adapter.
• as_plug() initializes the manifest and script for a rule plugin that uses an ML Adapter.

PythonFunctionAdapter

ml_adapter.base.assets.python.PythonFunctionAdapter extending ml_adapter.base.assets.manifest.WithManifest

Adapter for python based plugs or webscripts.

• requirements handles the dependency file (at requirements.txt)
• lib handles the libraries that are uploaded with the function archive itself. (at lib/*.tar.gz)
• main_script handles the main script of the function (main.py)
• scripts handles other utility scripts of the function (*.py)

NodeFunctionAdapter

ml_adapter.base.assets.node.NodeFunctionAdapter extending ml_adapter.base.assets.manifest.WithManifest

Adapter for node based plugs or webscripts.

• package handles the project file (at package.json)
• main_script handles the main script of the function (index.js or index.ts)
• scripts handles other utility scripts of the function (*.js,*.ts)

WithManifest

ml_adapter.base.assets.manifest.WithManifest extending ml_adapter.base.assets.mixin.WithAssets

Mixin for a configuration that has a waylay function manifest file.

Adds methods to manage the function manifest of a waylay plugin or webscript.

• manifest returns the manifest asset of the function archive at plug.json or webscript.json.

ModelAdapter

ml_adapter.base.adapter.ModelAdapter

Model Adapter base.

Provides the basic contract for exposing a model to a waylay plugin or webscript.

• Delegates to a marshaller to map the remote, json-compatible python data structures from and to the native tensor data structures for the ML framework.
• Delegates to a invoker to find the model method to be called.
• The call method maps remote requests and invokes the model method.
• The call_remote method tests the round trip serialization, encoding native data request to remotable and back before invoking call.

TensorModelAdapter

ml_adapter.base.adapter.TensorModelAdapter extending ml_adapter.base.adapter.ModelAdapter

Model adapter that uses (dicts of) tensors as inputs and outputs.

Requests are mapped to the model invocation using named parameters, falling back to mapping the "main" entry to the first positional parameter.

ModelAdapterBase

ml_adapter.base.adapter.ModelAdapterBase extending ml_adapter.base.adapter.TensorModelAdapter, ml_adapter.base.assets.python_ml.PythonMLAdapter, ml_adapter.base.model.access.WithModel

Generic model adapter for plugs and webscripts.

• supports creation of waylay webscript and plug functions
• pluggable tensor marshalling (DEFAULT_MARSHALLER = NoMarshaller)
• pluggable model loading (dill, joblib, selfserializing, custom) configured by MODEL_ASSET_CLASSES and MODEL_CLASS

WithAssets

ml_adapter.base.assets.mixin.WithAssets

Mixin for a configuration backed by assets.

Manages assets of the the plugin or webscript.

Used read-only within a deployed adapter to e.g. load the model definition.

Used read/write within the ml_tool to edit the assets of a plugin or webscript.

WithOpenapi

ml_adapter.base.assets.openapi.WithOpenapi extending ml_adapter.base.assets.mixin.WithAssets

Mixin for a configuration that has an openapi description.

Adds methods to a WithAssets adapter to manage the openapi description of waylay plugin or webscript.

• openapi returns an asset of type OpenApiAsset (normally at openapi.json)

WithModel

ml_adapter.base.model.access.WithModel extending ml_adapter.base.assets.mixin.WithAssets

Holder of model assets.

Adds methods to a WithAssets adapter to manage the model instance. A model can either be:

• given as model in the constructor of the adapter
• loaded from model_path in the assets
• loaded with a model_class (using an optional model_path)

The MODEL_ASSET_CLASSES configured on the adapter define the methods to load a model. Defaults are

• DillModelAsset (".dill", ".pkl", "*.pickle" files)
• JoblibModelAsset (".joblib", ".joblib.gz" files)
• SelfSerializingModelAsset ("*.sav" files)

If no MODEL_ASSET_CLASSES are configured, the model can only be set by the contructor (using the model or model_class parameters)

SelfSerializingModelAsset

ml_adapter.base.model.serialize.SelfSerializingModelAsset extending ml_adapter.base.model.base.ModelAsset

Model asset with own serialization methods.

Reads/writes the model from model.sav using the save and load methods defined on the model_class.

DillModelAsset

ml_adapter.base.model.dill.DillModelAsset extending ml_adapter.base.model.base.ModelAsset

Model asset for dill-serialized models.

Reads/writes the model from paths like model.dill, model.pkl, model.pickle using dill serialisation.

JoblibModelAsset

ml_adapter.base.model.joblib.JoblibModelAsset extending ml_adapter.base.model.base.ModelAsset

Model asset with joblib serialization.

Reads/writes the model from model.joblib or model.joblib.gz using joblib serialisation.

Marshaller

ml_adapter.base.marshall.base.Marshaller extending ml_adapter.base.marshall.base.RequestMarshaller, ml_adapter.base.marshall.base.ResponseMarshaller

Abstract base class to marshall inference requests and responses.

Methods used to invoke the model in a plugin or webscript:

• map_request() maps remote requests (generic type RREQ) to native requests (generic type MREQ)
• map_response() maps native responses (generic type MRES) to remote a response (generic type RRES)

Methods used to test roundtrip encoding in a client:

• encode_request() encodes a native request to a remote request that can be sent to a waylay function.
• decode_response() decodes a remote response from a function to native a response.