Error in variable count when assigning sample method #2413
Description
I came across this error after a fresh install of python 3.5 and the latest versions of theano and pymc3. When I assign a step method to a variable, the resulting call to NUTS() as the remaining variables get auto-assigned generates the following error :
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-7-8f98cb09c8eb> in <module>()
2 x = pm.Normal('x')
3 y = pm.Normal('y')
----> 4 pm.sample(draws=10,tune=10, step=[pm.Metropolis(vars=[x])])
5
~\Anaconda3\lib\site-packages\pymc3\sampling.py in sample(draws, step, init, n_init, start, trace, chain, njobs, tune, nuts_kwargs, step_kwargs, progressbar, model, random_seed, live_plot, discard_tuned_samples, live_plot_kwargs, **kwargs)
247 start = start_
248 else:
--> 249 step = assign_step_methods(model, step, step_kwargs=step_kwargs)
250
251 if njobs is None:
~\Anaconda3\lib\site-packages\pymc3\sampling.py in assign_step_methods(model, step, methods, step_kwargs)
90 args = step_kwargs.get(step_class.name, {})
91 used_keys.add(step_class.name)
---> 92 step = step_class(vars=vars, **args)
93 steps.append(step)
94
~\Anaconda3\lib\site-packages\pymc3\step_methods\hmc\nuts.py in __init__(self, vars, Emax, target_accept, gamma, k, t0, adapt_step_size, max_treedepth, on_error, **kwargs)
147 `pm.sample` to the desired number of tuning steps.
148 """
--> 149 super(NUTS, self).__init__(vars, use_single_leapfrog=True, **kwargs)
150
151 self.Emax = Emax
~\Anaconda3\lib\site-packages\pymc3\step_methods\hmc\base_hmc.py in __init__(self, vars, scaling, step_scale, is_cov, model, blocked, use_single_leapfrog, potential, integrator, **theano_kwargs)
62
63 self.H, self.compute_energy, self.compute_velocity, self.leapfrog, self.dlogp = get_theano_hamiltonian_functions(
---> 64 vars, shared, model.logpt, self.potential, use_single_leapfrog, integrator, **theano_kwargs)
65
66 super(BaseHMC, self).__init__(vars, shared, blocked=blocked)
~\Anaconda3\lib\site-packages\pymc3\step_methods\hmc\trajectory.py in get_theano_hamiltonian_functions(model_vars, shared, logpt, potential, use_single_leapfrog, integrator, **theano_kwargs)
122 """
123 H, q, dlogp = _theano_hamiltonian(model_vars, shared, logpt, potential)
--> 124 energy_function, p = _theano_energy_function(H, q, **theano_kwargs)
125 velocity_function = _theano_velocity_function(H, p, **theano_kwargs)
126 if use_single_leapfrog:
~\Anaconda3\lib\site-packages\pymc3\step_methods\hmc\trajectory.py in _theano_energy_function(H, q, **theano_kwargs)
51 p = tt.vector('p')
52 p.tag.test_value = q.tag.test_value
---> 53 total_energy = H.pot.energy(p) - H.logp(q)
54 energy_function = theano.function(inputs=[q, p], outputs=total_energy, **theano_kwargs)
55 energy_function.trust_input = True
~\Anaconda3\lib\site-packages\pymc3\step_methods\hmc\quadpotential.py in energy(self, x)
96
97 def energy(self, x):
---> 98 return .5 * x.dot(self.v * x)
99
100
~\Anaconda3\lib\site-packages\theano\tensor\var.py in __rmul__(self, other)
231
232 def __rmul__(self, other):
--> 233 return theano.tensor.basic.mul(other, self)
...
ValueError: Input dimension mis-match. (input[0].shape[0] = 2, input[1].shape[0] = 1)
The "..." stands in place of the traceback through theano, as I believe the issue here is in pymc3.
This occurs on the simplest of models that I created to reproduce the error. I initialized two variables and set one to Metropolis. You can see the code here:
import pymc3 as pm
with pm.Model() as m:
x = pm.Normal('x')
y = pm.Normal('y')
pm.sample(step=[pm.Metropolis(vars=[x])])
It appears that the energy function is expecting a value with the shape of the number of variables in the full model but only getting the number variables assigned to NUTS.
It runs fine when auto-assigning NUTS to the full model though.