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Test failing with tensorflow 2.17 #96

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EWitting opened this issue Oct 22, 2024 · 2 comments
Open

Test failing with tensorflow 2.17 #96

EWitting opened this issue Oct 22, 2024 · 2 comments

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@EWitting
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EWitting commented Oct 22, 2024

System information

  • Windows 11
  • Python 3.11.9
  • DeepTables 0.2.6
  • Tensorflow 2.17.0

Describe the current behavior
Running the standard test snippet, as well as trying to train a model, fails on:

  File "C:\Me\Epoch\Code\mcts\.venv\Lib\site-packages\deeptables\models\deeptable.py", line 363, in fit
    history = model.fit(X, y, batch_size=batch_size, epochs=epochs, verbose=verbose, shuffle=shuffle,
    history = model.fit(X, y, batch_size=batch_size, epochs=epochs, verbose=verbose, shuffle=shuffle,
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Me\Epoch\Code\mcts\.venv\Lib\site-packages\deeptables\models\deepmodel.py", line 106, in fit
    history = self.model.fit(train_data,
              ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Me\Epoch\Code\mcts\.venv\Lib\site-packages\keras\src\utils\traceback_utils.py", line 122, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "C:\Me\Epoch\Code\mcts\.venv\Lib\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 'max_queue_size'

Standalone code to reproduce the issue
python -c "from deeptables.utils.quicktest import test; test()"

Suspected cause
max_queue_size ,workers, and use_multiprocessing are passed. These appear to not exist in tensorflow 2.17, although they did in older versions. Downgrading to tensorflow==2.15.0 made the test pass. I am reporting this as a bug as there is no constraint mentioned anywhere about supported versions, only >2.4 in the requirements.txt.

@EWitting EWitting changed the title Test failing with tensorflow non-gpu Test failing with tensorflow 2.17 Oct 22, 2024
@Pun-it
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Pun-it commented Nov 13, 2024

Use TensorFlow 2.15.0 or below, as far as I am aware support for 2.15.0 > is not available.

@oaksharks
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@EWitting @Pun-it ,
Hey guys, glad to tell you that now it works with tensorflow up to version 2.18 on master branch latest code.

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