What does it mean when a covariance matrix values are all the same in hmmlearn - GMMHMM?

Question

I am working with GMMHMM from hmm learn for speaker recognition. After training the model, I found that all the values in the covariance matrix (covars_) all have the same values. I initialised my hmm as follows

model = hmm.GMMHMM(n_components=5, n_mix = 3, n_iter=100, covariance_type='diag)

fitted it with samples that were MFCC features extracted from voice data.

model.fit(X,lengths)

after printing out model.covars_, my output looked something like what is printed out below

[[[1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392] [1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392] [1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392 1.00120392]]

This was for a single state but the value was exactly the same for all states.

Is there a reason for this?