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classification-tflite

Testing

We test this when you cut a PR by running scripts/test.sh. This in turn just runs the model and then runs pytest which will run everything in tests/. Our testing here isn't overly complex and we have no code coverage or anything so please keep up good hygiene and if you make a change to training.py that would requires a test (i.e. you've made a change and you had to manually test something different), add that test condition somewhere to tests/

Usage

In order to submit this script with custom arguments, you must use the Viam CLI. One such example is included below:

viam train submit custom with-upload --dataset-id=<DATASET-ID> --model-org-id=<ORG-ID> --model-name=classification --model-type=<DESIRED_TYPE> --framework=tflite --path=<REPO-TAR-PATH> --script-name=classification_script --args=num_epochs=3,labels="'green_square blue_star'"

Be sure to note that labels is surrounded with single quotes then enclosed with double quotes to ensure it is submitted properly. If you are running the script from a previous version or from the website, you will not be able to use custom arguments.

Workflows

Pull Request

When you submit a pull request a workflow will run using our common workflows that will lint check your code, build it in the docker image we us in production (tensorflow/tensorflow:2.11.1-gpu) and run the test file you specify.

The default test files is scripts/test.sh. If this changes you will need to update .github/workflows/pull_request.yaml so that it's

jobs:
  build:
    uses: viam-modules/common-workflows/.github/workflows/lint_and_test.yaml
    with:
      test_script_name: NEW_TEST_FILE_NAME

Main

Upon merging to main a workflow will automatically update the module in viam-dev allowing for people to use your latest changes. The configs you can (but shouldn't!) play with are:

  1. framework -- DO NOT CHANGE THIS! This is a tflite script and will always be (see: repo name)
  2. script_name -- This is what the name will be in the registry. If you change this, it will make a new training script in the registry. Be aware
  3. model_type -- single_label_classification

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