it seems that the numpy random seed is NOT being randomized in each parallel process as expected (getting the same outcome of numpy random processes in all parallel jobs!).
Potential solution:
Reseed NumPy random generator in DataGenerator class methods with np.random.seed().
Problem: When using the 'parallel' option to generate data with f3dasm, i.e.,
experiment_data.evaluate(data_generator=my_generator, mode='parallel')
it seems that the numpy random seed is NOT being randomized in each parallel process as expected (getting the same outcome of numpy random processes in all parallel jobs!).
Potential solution: Reseed NumPy random generator in DataGenerator class methods with
np.random.seed()
.