I started with the default tutorial (link) which is on CTM. When I reach the optimization part:
optimizer=Optimizer()
optimization_result = optimizer.optimize(
model, dataset, npmi, search_space, number_of_call=optimization_runs,
model_runs=model_runs, save_models=True,
extra_metrics=None, # to keep track of other metrics
save_path='results/test_ctm//')
I receive the following error:
AttributeError: module 'numpy' has no attribute 'int'.
`np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
Then I tried modifying the optimizer by substituting np.int with int in skopt. However, the same problem occurred with transformers library. I believe the version of NumPy has to be downgraded for these libraries to work.
Description
I'm trying to run optimization on models.
What I Did
I started with the default tutorial (link) which is on CTM. When I reach the optimization part:
I receive the following error:
Then I tried modifying the
optimizer
by substitutingnp.int
withint
in skopt. However, the same problem occurred with transformers library. I believe the version of NumPy has to be downgraded for these libraries to work.