tensorflowjs: The Python Package for TensorFlow.js

The tensorflowjs pip package contains libraries and tools for TensorFlow.js.

Use following command to install the library with support of interactive CLI:

pip install tensorflowjs[wizard]

Then, run the following to see a list of CLI options

tensorflowjs_converter --help

or, use the wizard

tensorflowjs_wizard

Alternatively, run the converter via its Bazel target. This must be run from withing the tfjs repo:

yarn bazel run //tfjs-converter/python/tensorflowjs/converters:converter -- --help

Development

The python tests are run with Bazel.

yarn bazel test //tfjs-converter/python/...

Alternatively, run yarn run-python-tests to run the above command.

To debug a specific test case, use the --test_filter option. For example,

yarn bazel test //tfjs-converter/python/tensorflowjs/converters:tf_saved_model_conversion_v2_test --test_filter=ConvertTest.test_convert_saved_model_v1

Interactive debugging with breakpoints is supported by debugpy in VSCode. To enable debugging, put this code at the top of the test file you want to debug.

import debugpy
debugpy.listen(('localhost', 5724))
print("Waiting for debugger to connect. See tfjs-converter python README")
debugpy.wait_for_client()

You may also need to add the following dependency to the test target in the Bazel BUILD file if it's not already present.

"//tfjs-converter/python/tensorflowjs:expect_debugpy_installed"

Then, run the test with bazel run --config=debugpy and connect the VSCode debugger by selecting the Python: Attach (Converter) option.