152 make tensor flow optional

[teubert]

This PR accomplishes 2 things

1. Makes installing tensor flow optional using [datadriven] option, and
2. Updates configuration from old setup.py to new pyproject.toml

Now to install with tensorflow you must use the following command
pip install progpy[datadriven] or pip install '.[datadriven]' (for local copy)

Also updated LSTM to give a more descriptive error if tensor flow isn't installed and updated documentation of LSTM to add note.

How to test:

• Create a new venv
• Install progpy local copy (pip install -e .) , run tests. data tests should fail and give useful error.
• Clear out venv
• install progpy local copy, with datadriven (pip install -e '.[datadriven]'), run tests. all should pass

[github-actions]

Thank you for opening this PR. Each PR into dev requires a code review. For the code review, look at the following:

• Reviewer (someone other than author) should look for bugs, efficiency, readability, testing, and coverage in examples (if relevant).
• Ensure that each PR adding a new feature should include a test verifying that feature.
• All errors from static analysis must be resolved.
• Review the test coverage reports (if there is a change) - will be added as comment on PR if there is a change
• Review the software benchmarking results (if there is a change) - will be added as comment on PR
• Any added dependencies are included in requirements.txt, setup.py, and dev_guide.rst (this document)
• All warnings from static analysis must be reviewed and resolved - if deemed appropriate.

[teubert]

Unfortunately, the way things are setup the new test config will not take effect until this is merged. So surrogates and data tests will fail and have to be tested manually

[jason-watkins]

Seems to mostly be working, but I do get this error on (I think) all of the tensorflow tests:

======================================================================
ERROR: test_lstm_simple (tests.test_data_model.TestDataModel)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/jason/code/nasa/progpy/tests/test_data_model.py", line 127, in test_lstm_simple
    m = self._test_simple_case(LSTMStateTransitionModel, window=5, epochs=20, max_error=3)
  File "/home/jason/code/nasa/progpy/tests/test_data_model.py", line 48, in _test_simple_case
    m2 = DataModelType.from_data(
  File "/home/jason/code/nasa/progpy/src/progpy/data_models/lstm_model.py", line 598, in from_data
    history = model.fit(
  File "/home/jason/code/nasa/progpy_venv/lib/python3.10/site-packages/keras/src/utils/traceback_utils.py", line 122, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/home/jason/code/nasa/progpy_venv/lib/python3.10/site-packages/keras/src/utils/traceback_utils.py", line 117, in error_handler
    return fn(*args, **kwargs)
TypeError: TensorFlowTrainer.fit() got an unexpected keyword argument 'workers'

Could be related to the fact that I am running this in Windows WSL?

[teubert]

Seems to mostly be working, but I do get this error on (I think) all of the tensorflow tests:

======================================================================

ERROR: test_lstm_simple (tests.test_data_model.TestDataModel)

----------------------------------------------------------------------

Traceback (most recent call last):

  File "/home/jason/code/nasa/progpy/tests/test_data_model.py", line 127, in test_lstm_simple

    m = self._test_simple_case(LSTMStateTransitionModel, window=5, epochs=20, max_error=3)

  File "/home/jason/code/nasa/progpy/tests/test_data_model.py", line 48, in _test_simple_case

    m2 = DataModelType.from_data(

  File "/home/jason/code/nasa/progpy/src/progpy/data_models/lstm_model.py", line 598, in from_data

    history = model.fit(

  File "/home/jason/code/nasa/progpy_venv/lib/python3.10/site-packages/keras/src/utils/traceback_utils.py", line 122, in error_handler

    raise e.with_traceback(filtered_tb) from None

  File "/home/jason/code/nasa/progpy_venv/lib/python3.10/site-packages/keras/src/utils/traceback_utils.py", line 117, in error_handler

    return fn(*args, **kwargs)

TypeError: TensorFlowTrainer.fit() got an unexpected keyword argument 'workers'

Could be related to the fact that I am running this in Windows WSL?

Well that's frustrating. It should be working on windows. But tensorflow is VERY sensitive to os and version. I'll open a new issue to investigate that.

I'll also be updating to use keras 3 for this release. That might fix this issue too. But I'll open a bug report to track it