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NOTE: Refer to the online documentation to properly view this file

Command-Line

This describes how to enable and use the MLTK command-line interface.

This assumes the MLTK has been [installed](../installation.md) and is available on the command prompt.

Command Basics

Enable Python Virtual Environment

If you're using a Python virtual environment as described in the installation guide, ensure you 'activate' it to make the mltk command accessible on the command prompt:

.. tab-set::

   .. tab-item:: Windows

      .. code-block:: shell

         .\mltk_pyvenv\Scripts\activate.bat

   .. tab-item:: Linux

      .. code-block:: shell

         source ./mltk_pyvenv/bin/activate

Command Format

All MLTK commands are accessible via the mltk command-line command.
The mltk command expects arguments with the format:

mltk <operation> [<arguments>] [<options> ...]

Where:

  • <operation> - The specific operation to perform (e.g. profile, train, etc.)
  • <arguments> - Operation-specific arguments (e.g. The name of an ML model)
  • <options> - Additional flags & arguments to give to the operation

Help

All MLTK commands provide details about their supported arguments/options by appending the --help option, e.g.:

mltk --help
mltk profile --help
mltk train --help

Supported Operations

The following operations are supported by the mltk command:

Name Description
profile Profile a model to determine how efficiently is may run on hardware
train Train a model and generate a .mltk.zip archive containing a .tflite model file
tensorboard Monitor/profile the training of a model using Tensorboard
ssh Train a model on a remote cloud server via SSH
evaluate Evaluate a trained model to determine how accurate it is
quantize Quantize a trained model to reduce its memory footprint
summarize Generate a text summary of a model
view View a model's graph in an interactive visualizer
update_params Update the parameters embedded into a generated .tflite model file
view_audio Visualize the spectrograms generated by the Audio Feature Generator
classify_audio Classify real-time audio from a development board's or PC's microphone
classify_image Classify images from an RGB camera connected to a development board
fingerprint_reader View fingerprint images from a fingerprint module connected to a development board
commander Run the Silicon Lab's Simplicity Commander utility 
To get more information about a specific operation, issue the command:  

    mltk <operation> --help

.. toctree::
   :maxdepth: 1
   :hidden:

   ./profile
   ./train
   ./tensorboard
   ./ssh
   ./evaluate
   ./quantize
   ./summarize
   ./view
   ./update_params
   ./view_audio
   ./classify_audio
   ./classify_image
   ./fingerprint_reader
   ./commander