A decoding HMM has 3 parameters. But I am bit confused in tensorflow's HMM parameters and I'm not clear with docs https://www.tensorflow.org/probability/api_docs/python/tfp/distributions/HiddenMarkovModel?version=nightly
tfp.distributions.HiddenMarkovModel( initial_distribution, transition_distribution, observation_distribution, num_steps, validate_args=False, allow_nan_stats=True, time_varying_observation_distribution=False, name='HiddenMarkovModel' )
Here we give 3 parameter and initialize the class that I got it.
posterior_mode( observations, mask=None, name='posterior_mode' )
Now what is observation here for decoding ? Then also please about num_steps parameters. I want it use in my pos tagger and I didn't understand example given Thank you.