Blocks
The blocks CLI tool creates different blocks types that are used in organizational features such as:
Transformation blocks - to transform large sets of data efficiently.
Deployment blocks - to build personalized firmware using your own data or to create custom libraries.
Custom DSP blocks - to create and host your custom signal processing techniques and use them directly in your projects.
Custom machine learning models - to use your custom neural network architectures and load pre-trained weights, with Keras, PyTorch and scikit-learn.
With the blocks CLI tool, you can create new blocks, run them locally, and push them to Edge Impulse infrastructure so we can host them for you. Edge Impulse blocks can be written in any language, and are based on Docker container for maximum flexibility.
As an example here, we will show how to create a transformation block.
You can create a new block by running:
When you're done developing the block you can push it to Edge Impulse via:
The metadata about the block (which organization it belongs to, block ID) is saved in .ei-block-config
, which you should commit. To view this data in a convenient format, run:
Block runner
Rather than only running custom blocks in the cloud, the edge-impulse-blocks runner
command lets developers download, configure, and run custom blocks entirely on their local machine, making testing and development much faster. The options depend on the type of block being run, and they can be viewed by using the help menu:
As seen above, the runner
accepts a list of relevant option flags along with a variable number of extra arguments that get passed to the Docker container at runtime for extra flexibility. As an example, here is what happens when edge-impulse-blocks runner
is used on a file transformation block:
Best of all, the runner
only downloads data when it isn't present locally, thus saving time and bandwidth.
Block structure
Transformation blocks use Docker containers, a virtualization technique which lets developers package up an application with all dependencies in a single package. Thus, every block needs at least a Dockerfile
. This is a file describing how to build the container that powers the block, and it has information about the dependencies for the block - like a list of Python packages your block needs. This Dockerfile
needs to declare an ENTRYPOINT
: a command that needs to run when the container starts.
An example of a Python container is:
Which takes a base-image with Python 3.7.5, then installs all dependencies listed in requirements.txt
, and finally starts a script called transform.py
.
Note: Do not use a WORKDIR under /home! The /home path will be mounted in by Edge Impulse, making your files inaccessible.
Note: If you use a different programming language, make sure to use ENTRYPOINT
to specify the application to execute, rather than RUN
or CMD
.
Besides your Dockerfile
you'll also need the application files, in the example above transform.py
and requirements.txt
. You can place these in the same folder.
Excluding files
When pushing a new block all files in your folder are archived and sent to Edge Impulse, where the container is built. You can exclude files by creating a file called .ei-ignore
in the root folder of your block. You can either set absolute paths here, or use wildcards to exclude many files. For example:
Clearing configuration
To clear the configuration, run:
This resets the CLI configuration and will prompt you to log in again.
API Key
You can use an API key to authenticate with:
Note that this resets the CLI configuration and automatically configures your organization.
Other options
--dev
- lists development servers, use in conjunction with--clean
.
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