Repo Organization

The TurnkeyML source code has a few major top-level directories:

• docs: documentation for the entire project.
• examples: example scripts for use with the TurnkeyML tools.
  • examples/turnkey/cli: tutorial series starting in examples/turnkey/cli/readme.md to help learn the turnkey CLI.
    • examples/turnkey/cli/scripts: example scripts that can be fed as input into the turnkey CLI. These scripts each have a docstring that recommends one or more turnkey CLI commands to try out.
  • examples/turnkey/api: examples scripts that invoke Tools via APIs.
• models: the corpora of models that makes up the TurnkeyML models (see the models readme).
  • Each subdirectory under models represents a corpus of models pulled from somewhere on the internet. For example, models/torch_hub is a corpus of models from Torch Hub.
• src/turnkeyml: source code for the TurnkeyML package.
  • src/turnkeyml/tools: implements Tool and defines the tools built in to turnkey.
  • src/turnkeyml/sequence: implements Sequence and defines the plugin API for Tools.
  • src/turnkeyml/run: implements BaseRT, an abstract base class that defines TurnkeyML's vendor-agnostic benchmarking functionality. This module also includes the runtime and device plugin APIs and the built-in runtimes and devices.
  • src/turnkeyml/cli: implements the turnkey CLI.
  • src/turnkeyml/common: functions common to the other modules.
  • src/turnkeyml/version.py: defines the package version number.
  • src/turnkeyml/state.py: implements the State class.
  • src/turnkeyml/files_api.py: implements the evaluate_files() API, which is the top-level API called by the CLI.
• test: tests for the TurnkeyML tools.
  • test/turnkey/analysis.py: tests focusing on the discover Tool.
  • test/turnkey/cli.py: tests focusing on top-level CLI features.

Tool Classes

All of the logic for actually building models is contained in Tool classes. Generally, a FirstTool class obtains a model, and each subsequent Tool is a model-to-model transformation. For example:

• the Discover(FirstTool) (aka discover in the CLI) obtains a PyTorch model instance from a python script.
• the ExportPytorchModel(Tool) (aka export-pytorch in the CLI) transforms a PyTorch model instance into an ONNX model file.

Composability

Tools are designed to be composable, for example, there are already a few ONNX-to-ONNX Tools defined in src/turnkeyml/tools/onnx.py that could sequenced in any order.

This composability is facilitated by the State class, which is how Tools communicate with each other. Every Tool takes an instance of State as input and then returns an instance of State. For example:

• Discover(FirstTool) takes a freshly initialized instance of State as input, and modifies it so that state.result points to a PyTorch model.
• ExportPytorchModel(Tool) takes a PyTorch model in state.result then modifies State such that state.result points to the exported ONNX file.

Implementation

See tools.py for a definition of each method of Tool that must be implemented to create a new Tool subclass.