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Fix failing LinRegHMM test #378

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Oct 15, 2024
Merged

Fix failing LinRegHMM test #378

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4 changes: 1 addition & 3 deletions dynamax/hidden_markov_model/models/test_models.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
import pytest
from datetime import datetime
import jax.numpy as jnp
import jax.random as jr
from jax import vmap
Expand All @@ -21,7 +20,7 @@
(models.LowRankGaussianHMM, dict(num_states=4, emission_dim=3, emission_rank=1), None),
(models.GaussianMixtureHMM, dict(num_states=4, num_components=2, emission_dim=3, emission_prior_mean_concentration=1.0), None),
(models.DiagonalGaussianMixtureHMM, dict(num_states=4, num_components=2, emission_dim=3, emission_prior_mean_concentration=1.0), None),
(models.LinearRegressionHMM, dict(num_states=4, emission_dim=3, input_dim=5), jnp.ones((NUM_TIMESTEPS, 5))),
(models.LinearRegressionHMM, dict(num_states=3, emission_dim=3, input_dim=5), jr.normal(jr.PRNGKey(0),(NUM_TIMESTEPS, 5))),
(models.LogisticRegressionHMM, dict(num_states=4, input_dim=5), jnp.ones((NUM_TIMESTEPS, 5))),
(models.MultinomialHMM, dict(num_states=4, emission_dim=3, num_classes=5, num_trials=10), None),
(models.PoissonHMM, dict(num_states=4, emission_dim=3), None),
Expand All @@ -31,7 +30,6 @@
@pytest.mark.parametrize(["cls", "kwargs", "inputs"], CONFIGS)
def test_sample_and_fit(cls, kwargs, inputs):
hmm = cls(**kwargs)
#key1, key2 = jr.split(jr.PRNGKey(int(datetime.now().timestamp())))
key1, key2 = jr.split(jr.PRNGKey(42))
params, param_props = hmm.initialize(key1)
states, emissions = hmm.sample(params, key2, num_timesteps=NUM_TIMESTEPS, inputs=inputs)
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