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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.

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