# pm.Potential without Theano?

**URL:** <https://discourse.pymc.io/t/pm-potential-without-theano/968>\
**Category:** Questions\
**Created:** [March 18, 2018, 10:39am UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968 "2018-03-18T10:39:35Z")\
**Posts on this page:** 15\
**Page:** 1

<div class="post-metadata">

**Author:** ![adamh](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/adamh/32/1684_2.png) [@adamh](https://discourse.pymc.io/u/adamh)\
**Post date:** [March 18, 2018, 10:39am UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/1 "2018-03-18T10:39:35Z")

</div>

When using potentials, Is it possible to define them in a way that does not “rely” on theano?

More specifically - I have a custom logp function which is already implemented and optimized for my usage. Following [this thread](https://discourse.pymc.io/t/how-to-set-up-a-custom-likelihood-function-for-two-variables/906), I’ve tried to do something like this:

```auto
def likelihood(params, data):
    return my_custom_logp(params,data)

with pm.Model() as m:    
    params = pm.Normal('params', mu=1.5, sd=0.3,shape=(3,))
    like = pm.Potential('like', likelihood(params, data))
    trace = pm.sample()

```

This raises the following exception:

```auto
TypeError: Cannot convert FreeRV to numpy.ndarray
Exception ignored in: 'custom_func.createFunction'
TypeError: Cannot convert FreeRV to numpy.ndarray
Segmentation fault (core dumped)

```

Which kills the python kernel.

Is this doable?

---

<div class="post-metadata">

**Author:** ![junpenglao](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/junpenglao/32/8_2.png) [@junpenglao](https://discourse.pymc.io/u/junpenglao)\
**Post date:** [March 18, 2018, 11:11am UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/2 "2018-03-18T11:11:09Z")

</div>

Maybe the easiest thing to try is wrapping the `likelihood` into a `theanoOps`: [http://deeplearning.net/software/theano/extending/extending\_theano.html#as-op-example](http://deeplearning.net/software/theano/extending/extending_theano.html#as-op-example)

---

<div class="post-metadata">

**Author:** ![adamh](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/adamh/32/1684_2.png) [@adamh](https://discourse.pymc.io/u/adamh)\
**Post date:** [March 18, 2018, 1:28pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/3 "2018-03-18T13:28:12Z")

</div>

Thanks for the quick response!

I’ve tried this, and I think I’m making some progress, but I’m not familiar enough with theano to makes this work. I dod:

```
import theano
import numpy as np
from theano import function
from theano.compile.ops import as_op
import my_func as me
import pymc3 as pm

@as_op(itypes=[theano.tensor.dvector, theano.tensor.dmatrix],
       otypes=[theano.tensor.dscalar])
def likelihood(params, data):
    return me.model.getLogProbability(data.astype('uint32')).sum()

x = theano.tensor.dvector()
y = theano.tensor.dmatrix()
f = function([x, y], likelihood(x, y))
theano.config.compute_test_value = 'ignore'

with pm.Model() as m:	
	params = pm.Normal('params', mu=1.5, sd=0.3,shape=(5,),dtype='float32')
	like = pm.Potential('like', f(params, data))    
	trace = pm.sample()

```

The error I’m getting is:

```
Expected an array-like object, but found a Variable: maybe you are trying to call a function on a (possibly shared) variable instead of a numeric array?

```

As far as I understand, the call `f(params,data)` is expecting `params` to be a vector (“numeric array”) but instead gets a theano Variable. Is there some way around this? I’ve tried casting but it didn’t work…

---

<div class="post-metadata">

**Author:** ![junpenglao](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/junpenglao/32/8_2.png) [@junpenglao](https://discourse.pymc.io/u/junpenglao)\
**Post date:** [March 18, 2018, 1:39pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/4 "2018-03-18T13:39:39Z")

</div>

try casting `data` into theano tensor: `theano.shared(data)`

---

<div class="post-metadata">

**Author:** ![adamh](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/adamh/32/1684_2.png) [@adamh](https://discourse.pymc.io/u/adamh)\
**Post date:** [March 18, 2018, 1:42pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/5 "2018-03-18T13:42:14Z")

</div>

I tried - it still raises the same error, and specifcally mentions the problem is with `params`:

```
Traceback (most recent call last):
  File "mcmc.py", line 57, in <module>
    like = pm.Potential('like', f(params,theano.shared(data)))    
  File "/home/user/miniconda3/lib/python3.6/site-packages/theano/compile/function_module.py", line 813, in __call__
    allow_downcast=s.allow_downcast)
  File "/home/user/miniconda3/lib/python3.6/site-packages/theano/tensor/type.py", line 87, in filter
    'Expected an array-like object, but found a Variable: '
TypeError: Bad input argument with name "params" to theano function with name "mcmc.py:51" at index 0 (0-based).  
Backtrace when that variable is created:

  File "mcmc.py", line 49, in <module>
    x = theano.tensor.dvector()
Expected an array-like object, but found a Variable: maybe you are trying to call a function on a (possibly shared) variable instead of a numeric array?
```

---

<div class="post-metadata">

**Author:** ![junpenglao](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/junpenglao/32/8_2.png) [@junpenglao](https://discourse.pymc.io/u/junpenglao)\
**Post date:** [March 18, 2018, 2:03pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/6 "2018-03-18T14:03:28Z")

</div>

How about:

```python
like = pm.Potential('like', likelihood(params, theano.shared(data)))

```

---

<div class="post-metadata">

**Author:** ![adamh](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/adamh/32/1684_2.png) [@adamh](https://discourse.pymc.io/u/adamh)\
**Post date:** [March 18, 2018, 4:06pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/7 "2018-03-18T16:06:48Z")

</div>

Thanks! Some more progress (I think), still not there yet. 🙂

Now the sampling process initializes, but then I get a different, looks-very-low-levelish exception:

(TL;DR - `JoblibValueError` and `TransportableException`)

```
Auto-assigning NUTS sampler...
Initializing NUTS using jitter+adapt_diag...
Initializing NUTS failed. Falling back to elementwise auto-assignment.
Multiprocess sampling (4 chains in 4 jobs)
Slice: [params]
  0%| | 0/1000 [00:00<?, ?it/s]

---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback: 
"""
Traceback (most recent call last):
  File "/home/user/miniconda3/lib/python3.6/site-packages/theano/compile/function_module.py", line 903, in __call__
    self.fn() if output_subset is None else\
ValueError: expected an ndarray

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/user/miniconda3/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 350, in __call__
    return self.func(*args, **kwargs)
  File "/home/user/miniconda3/lib/python3.6/site-packages/joblib/parallel.py", line 131, in __call__
    return [func(*args, **kwargs) for func, args, kwargs in self.items]
  File "/home/user/miniconda3/lib/python3.6/site-packages/joblib/parallel.py", line 131, in <listcomp>
    return [func(*args, **kwargs) for func, args, kwargs in self.items]
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py", line 526, in _sample
    for it, strace in enumerate(sampling):
  File "/home/user/miniconda3/lib/python3.6/site-packages/tqdm/_tqdm.py", line 962, in __iter__
    for obj in iterable:
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py", line 630, in _iter_sample
    point = step.step(point)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/step_methods/arraystep.py", line 129, in step
    apoint = self.astep(bij.map(point), *inputs)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/step_methods/slicer.py", line 56, in astep
    y = logp(q) - nr.standard_exponential()
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/blocking.py", line 257, in __call__
    return self.fa(self.fb(x))
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/model.py", line 1029, in __call__
    return self.f(**state)
  File "/home/user/miniconda3/lib/python3.6/site-packages/theano/compile/function_module.py", line 917, in __call__
    storage_map=getattr(self.fn, 'storage_map', None))
  File "/home/user/miniconda3/lib/python3.6/site-packages/theano/gof/link.py", line 325, in raise_with_op
    reraise(exc_type, exc_value, exc_trace)
  File "/home/user/miniconda3/lib/python3.6/site-packages/six.py", line 692, in reraise
    raise value.with_traceback(tb)
  File "/home/user/miniconda3/lib/python3.6/site-packages/theano/compile/function_module.py", line 903, in __call__
    self.fn() if output_subset is None else\
ValueError: expected an ndarray
Apply node that caused the error: MakeVector{dtype='float64'}(like)
Toposort index: 1
Inputs types: [TensorType(float64, scalar)]
Inputs shapes: [()]
Inputs strides: [()]
Inputs values: [-373.5]
Inputs type_num: [12]
Outputs clients: [[Sum{acc_dtype=float64}(MakeVector{dtype='float64'}.0)]]

....

___________________________________________________________________________"""

The above exception was the direct cause of the following exception:

TransportableException Traceback (most recent call last)
~/miniconda3/lib/python3.6/site-packages/joblib/parallel.py in retrieve(self)
    698 if getattr(self._backend, 'supports_timeout', False):
--> 699 self._output.extend(job.get(timeout=self.timeout))
    700 else:

~/miniconda3/lib/python3.6/multiprocessing/pool.py in get(self, timeout)
    643 else:
--> 644 raise self._value
    645 

TransportableException: TransportableException
___________________________________________________________________________
ValueError Sun Mar 18 16:09:41 2018
PID: 8972 Python 3.6.3: /home/user/miniconda3/bin/python
...........................................................................
/home/user/miniconda3/lib/python3.6/site-packages/joblib/parallel.py in __call__ (self=<joblib.parallel.BatchedCalls object>)
    126 def __init__ (self, iterator_slice):
    127 self.items = list(iterator_slice)
    128 self._size = len(self.items)
    129 
    130 def __call__ (self):
--> 131 return [func(*args, **kwargs) for func, args, kwargs in self.items]
        self.items = [(<function _sample>, (0, True, 507879474, {'params': array([1.5, 1.5, 1.5])}), {'draws': 1000, 'live_plot': False, 'live_plot_kwargs': None, 'model': <pymc3.model.Model object>, 'step': <pymc3.step_methods.slicer.Slice object>, 'trace': None, 'tune': 500})]
    132 
    133 def __len__ (self):
    134 return self._size

...

During handling of the above exception, another exception occurred:

JoblibValueError Traceback (most recent call last)
<ipython-input-2-3d46709a462a> in <module>()
     31 params = pm.Normal('params', mu=1.5, sd=0.3,shape=(n,))
     32 like = pm.Potential('like', likelihood(params,theano.shared(data)))
---> 33 trace = pm.sample()

~/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py in sample(draws, step, init, n_init, start, trace, chain_idx, chains, njobs, tune, nuts_kwargs, step_kwargs, progressbar, model, random_seed, live_plot, discard_tuned_samples, live_plot_kwargs, compute_convergence_checks, **kwargs)
    417 _print_step_hierarchy(step)
    418 try:
--> 419 trace = _mp_sample(**sample_args)
    420 except pickle.PickleError:
    421 _log.warn("Could not pickle model, sampling singlethreaded.")

~/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py in _mp_sample(**kwargs)
    947 jobs = (delayed(_sample)(*args, **kwargs)
    948 for args in zip(chain_nums, pbars, rseed, start))
--> 949 traces = Parallel(n_jobs=njobs)(jobs)
    950 return MultiTrace(traces)
    951 

~/miniconda3/lib/python3.6/site-packages/joblib/parallel.py in __call__ (self, iterable)
    787 # consumption.
    788 self._iterating = False
--> 789 self.retrieve()
    790 # Make sure that we get a last message telling us we are done
    791 elapsed_time = time.time() - self._start_time

~/miniconda3/lib/python3.6/site-packages/joblib/parallel.py in retrieve(self)
    738 exception = exception_type(report)
    739 
--> 740 raise exception
    741 
    742 def __call__ (self, iterable):

JoblibValueError: JoblibValueError
___________________________________________________________________________
Multiprocessing exception:
...........................................................................
/home/user/miniconda3/lib/python3.6/runpy.py in _run_module_as_main(mod_name='ipykernel_launcher', alter_argv=1)
    188 sys.exit(msg)
    189 main_globals = sys.modules[" __main__"]. __dict__
    190 if alter_argv:
    191 sys.argv[0] = mod_spec.origin
    192 return _run_code(code, main_globals, None,
--> 193 " __main__", mod_spec)
        mod_spec = ModuleSpec(name='ipykernel_launcher', loader=<_f...b/python3.6/site-packages/ipykernel_launcher.py')
    194 
    195 def run_module(mod_name, init_globals=None,
    196 run_name=None, alter_sys=False):
    197 """Execute a module's code without importing it

...........................................................................
/home/user/miniconda3/lib/python3.6/runpy.py in _run_code(code=<code object <module> at 0x7f81ebd054b0, file "/...3.6/site-packages/ipykernel_launcher.py", line 5>, run_globals={' __annotations__': {}, ' __builtins__': <module 'builtins' (built-in)>, ' __cached__': '/home/user/miniconda3/lib/python3.6/site-packages/ __pycache__ /ipykernel_launcher.cpython-36.pyc', ' __doc__': 'Entry point for launching an IPython kernel.\n\nTh...orts until\nafter removing the cwd from sys.path.\n', ' __file__': '/home/user/miniconda3/lib/python3.6/site-packages/ipykernel_launcher.py', ' __loader__': <_frozen_importlib_external.SourceFileLoader object>, ' __name__': ' __main__', ' __package__': '', ' __spec__': ModuleSpec(name='ipykernel_launcher', loader=<_f...b/python3.6/site-packages/ipykernel_launcher.py'), 'app': <module 'ipykernel.kernelapp' from '/home/user/m.../python3.6/site-packages/ipykernel/kernelapp.py'>, ...}, init_globals=None, mod_name=' __main__', mod_spec=ModuleSpec(name='ipykernel_launcher', loader=<_f...b/python3.6/site-packages/ipykernel_launcher.py'), pkg_name='', script_name=None)
     80 __cached__ = cached,
     81 __doc__ = None,
     82 __loader__ = loader,
     83 __package__ = pkg_name,
     84 __spec__ = mod_spec)
---> 85 exec(code, run_globals)
        code = <code object <module> at 0x7f81ebd054b0, file "/...3.6/site-packages/ipykernel_launcher.py", line 5>
        run_globals = {' __annotations__': {}, ' __builtins__': <module 'builtins' (built-in)>, ' __cached__': '/home/user/miniconda3/lib/python3.6/site-packages/ __pycache__ /ipykernel_launcher.cpython-36.pyc', ' __doc__': 'Entry point for launching an IPython kernel.\n\nTh...orts until\nafter removing the cwd from sys.path.\n', ' __file__': '/home/user/miniconda3/lib/python3.6/site-packages/ipykernel_launcher.py', ' __loader__': <_frozen_importlib_external.SourceFileLoader object>, ' __name__': ' __main__', ' __package__': '', ' __spec__': ModuleSpec(name='ipykernel_launcher', loader=<_f...b/python3.6/site-packages/ipykernel_launcher.py'), 'app': <module 'ipykernel.kernelapp' from '/home/user/m.../python3.6/site-packages/ipykernel/kernelapp.py'>, ...}
     86 return run_globals
     87 
     88 def _run_module_code(code, init_globals=None,
     89 mod_name=None, mod_spec=None,

```

Setting `njobs=1` gives a slightly different exception:

```
Auto-assigning NUTS sampler...
Initializing NUTS using jitter+adapt_diag...
Initializing NUTS failed. Falling back to elementwise auto-assignment.
Sequential sampling (2 chains in 1 job)
Slice: [params]
  0%| | 0/1000 [00:00<?, ?it/s]

---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
~/miniconda3/lib/python3.6/site-packages/theano/compile/function_module.py in __call__ (self, *args, **kwargs)
    902 outputs =\
--> 903 self.fn() if output_subset is None else\
    904 self.fn(output_subset=output_subset)

ValueError: expected an ndarray

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last)
<ipython-input-1-0be912d9bdd4> in <module>()
     31 params = pm.Normal('params', mu=1.5, sd=0.3,shape=(n,))
     32 like = pm.Potential('like', likelihood(params,theano.shared(data)))
---> 33 trace = pm.sample(njobs=1)

~/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py in sample(draws, step, init, n_init, start, trace, chain_idx, chains, njobs, tune, nuts_kwargs, step_kwargs, progressbar, model, random_seed, live_plot, discard_tuned_samples, live_plot_kwargs, compute_convergence_checks, **kwargs)
    437 _log.info('Sequential sampling ({} chains in 1 job)'.format(chains))
    438 _print_step_hierarchy(step)
--> 439 trace = _sample_many(**sample_args)
    440 
    441 discard = tune if discard_tuned_samples else 0

~/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py in _sample_many(draws, chain, chains, start, random_seed, step, **kwargs)
    480 for i in range(chains):
    481 trace = _sample(draws=draws, chain=chain + i, start=start[i],
--> 482 step=step, random_seed=random_seed[i], **kwargs)
    483 if trace is None:
    484 if len(traces) == 0:

~/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py in _sample(chain, progressbar, random_seed, start, draws, step, trace, tune, model, live_plot, live_plot_kwargs, **kwargs)
    524 try:
    525 strace = None
--> 526 for it, strace in enumerate(sampling):
    527 if live_plot:
    528 if live_plot_kwargs is None:

~/miniconda3/lib/python3.6/site-packages/tqdm/_tqdm.py in __iter__ (self)
    960 """, fp_write=getattr(self.fp, 'write', sys.stderr.write))
    961 
--> 962 for obj in iterable:
    963 yield obj
    964 # Update and possibly print the progressbar.

~/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py in _iter_sample(draws, step, start, trace, chain, tune, model, random_seed)
    628 strace.record(point)
    629 else:
--> 630 point = step.step(point)
    631 strace.record(point)
    632 yield strace

~/miniconda3/lib/python3.6/site-packages/pymc3/step_methods/arraystep.py in step(self, point)
    127 return bij.rmap(apoint), stats
    128 else:
--> 129 apoint = self.astep(bij.map(point), *inputs)
    130 return bij.rmap(apoint)
    131 

~/miniconda3/lib/python3.6/site-packages/pymc3/step_methods/slicer.py in astep(self, q0, logp)
     54 for i in range(len(q0)):
     55 # uniformly sample from 0 to p(q), but in log space
---> 56 y = logp(q) - nr.standard_exponential()
     57 ql[i] = q[i] - nr.uniform(0, self.w[i])
     58 qr[i] = q[i] + self.w[i]

~/miniconda3/lib/python3.6/site-packages/pymc3/blocking.py in __call__ (self, x)
    255 
    256 def __call__ (self, x):
--> 257 return self.fa(self.fb(x))

~/miniconda3/lib/python3.6/site-packages/pymc3/model.py in __call__ (self, state)
   1027 
   1028 def __call__ (self, state):
-> 1029 return self.f(**state)
   1030 
   1031 

~/miniconda3/lib/python3.6/site-packages/theano/compile/function_module.py in __call__ (self, *args, **kwargs)
    915 node=self.fn.nodes[self.fn.position_of_error],
    916 thunk=thunk,
--> 917 storage_map=getattr(self.fn, 'storage_map', None))
    918 else:
    919 # old-style linkers raise their own exceptions

~/miniconda3/lib/python3.6/site-packages/theano/gof/link.py in raise_with_op(node, thunk, exc_info, storage_map)
    323 # extra long error message in that case.
    324 pass
--> 325 reraise(exc_type, exc_value, exc_trace)
    326 
    327 

~/miniconda3/lib/python3.6/site-packages/six.py in reraise(tp, value, tb)
    690 value = tp()
    691 if value. __traceback__ is not tb:
--> 692 raise value.with_traceback(tb)
    693 raise value
    694 finally:

~/miniconda3/lib/python3.6/site-packages/theano/compile/function_module.py in __call__ (self, *args, **kwargs)
    901 try:
    902 outputs =\
--> 903 self.fn() if output_subset is None else\
    904 self.fn(output_subset=output_subset)
    905 except Exception:

ValueError: expected an ndarray
Apply node that caused the error: MakeVector{dtype='float64'}(like)
Toposort index: 1
Inputs types: [TensorType(float64, scalar)]
Inputs shapes: [()]
Inputs strides: [()]
Inputs values: [-348.0]
Inputs type_num: [12]
Outputs clients: [[Sum{acc_dtype=float64}(MakeVector{dtype='float64'}.0)]]

Backtrace when the node is created(use Theano flag traceback.limit=N to make it longer):
  File "/home/user/miniconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2910, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-1-0be912d9bdd4>", line 33, in <module>
    trace = pm.sample(njobs=1)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py", line 381, in sample
    step = assign_step_methods(model, step, step_kwargs=step_kwargs)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py", line 149, in assign_step_methods
    return instantiate_steppers(model, steps, selected_steps, step_kwargs)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py", line 70, in instantiate_steppers
    step = step_class(vars=vars, **args)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/step_methods/slicer.py", line 47, in __init__
    super(Slice, self). __init__ (vars, [self.model.fastlogp], **kwargs)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/model.py", line 190, in fastlogp
    return self.model.fastfn(self.logpt)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/model.py", line 666, in logpt
    logp_potentials = tt.sum([tt.sum(pot) for pot in self.potentials])

Debugprint of the apply node: 
MakeVector{dtype='float64'} [id A] <TensorType(float64, vector)> ''   
 |FromFunctionOp{likelihood} [id B] <TensorType(float64, scalar)> 'like'   

Storage map footprint:
 - <TensorType(float64, matrix)>, Shared Input, Shape: (500, 3), ElemSize: 8 Byte(s), TotalSize: 12000 Byte(s)
 - params, Input, Shape: (3,), ElemSize: 8 Byte(s), TotalSize: 24 Byte(s)
 - like, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
 - TensorConstant{(1,) of 0...0068542243}, Shape: (1,), ElemSize: 8 Byte(s), TotalSize: 8 Byte(s)
 - TensorConstant{(1,) of -1..1111111111}, Shape: (1,), ElemSize: 8 Byte(s), TotalSize: 8 Byte(s)
 - TensorConstant{(1,) of -1.5}, Shape: (1,), ElemSize: 8 Byte(s), TotalSize: 8 Byte(s)
 - TensorConstant{0.5}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
 - Sum{acc_dtype=float64}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
 TotalSize: 12072.0 Byte(s) 0.000 GB
 TotalSize inputs: 12056.0 Byte(s) 0.000 GB

```

Seems like the problem is with the type of the function return value?

---

<div class="post-metadata">

**Author:** ![junpenglao](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/junpenglao/32/8_2.png) [@junpenglao](https://discourse.pymc.io/u/junpenglao)\
**Post date:** [March 18, 2018, 4:50pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/8 "2018-03-18T16:50:24Z")

</div>

Could you please try

```python
    trace = pm.sample(step = pm.Metropolis())

```

Also check the output of

```auto
m.logp(m.test_point)

```

---

<div class="post-metadata">

**Author:** ![adamh](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/adamh/32/1684_2.png) [@adamh](https://discourse.pymc.io/u/adamh)\
**Post date:** [March 18, 2018, 5:27pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/9 "2018-03-18T17:27:19Z")

</div>

Still looks like a type mismatch somewhere (I think):

```
Sequential sampling (2 chains in 1 job)
Metropolis: [params]
  0%| | 0/1000 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "/home/user/miniconda3/lib/python3.6/site-packages/theano/compile/function_module.py", line 903, in __call__
    self.fn() if output_subset is None else\
ValueError: expected an ndarray

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "mcmc.py", line 58, in <module>
    trace = pm.sample(step=pm.Metropolis(),njobs=1)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py", line 439, in sample
    trace = _sample_many(**sample_args)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py", line 482, in _sample_many
    step=step, random_seed=random_seed[i], **kwargs)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py", line 526, in _sample
    for it, strace in enumerate(sampling):
  File "/home/user/miniconda3/lib/python3.6/site-packages/tqdm/_tqdm.py", line 962, in __iter__
    for obj in iterable:
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/sampling.py", line 624, in _iter_sample
    point, states = step.step(point)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/step_methods/arraystep.py", line 162, in step
    apoint, stats = self.astep(self.bij.map(point))
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/step_methods/metropolis.py", line 162, in astep
    accept = self.delta_logp(q, q0)
  File "/home/user/miniconda3/lib/python3.6/site-packages/theano/compile/function_module.py", line 917, in __call__
    storage_map=getattr(self.fn, 'storage_map', None))
  File "/home/user/miniconda3/lib/python3.6/site-packages/theano/gof/link.py", line 325, in raise_with_op
    reraise(exc_type, exc_value, exc_trace)
  File "/home/user/miniconda3/lib/python3.6/site-packages/six.py", line 692, in reraise
    raise value.with_traceback(tb)
  File "/home/user/miniconda3/lib/python3.6/site-packages/theano/compile/function_module.py", line 903, in __call__
    self.fn() if output_subset is None else\
ValueError: expected an ndarray
Apply node that caused the error: MakeVector{dtype='float64'}(like)
Toposort index: 11
Inputs types: [TensorType(float64, scalar)]
Inputs shapes: [()]
Inputs strides: [()]
Inputs values: [-309.92989822093455]
Inputs type_num: [12]
Outputs clients: [[Sum{acc_dtype=float64}(MakeVector{dtype='float64'}.0)]]

Backtrace when the node is created(use Theano flag traceback.limit=N to make it longer):
  File "mcmc.py", line 58, in <module>
    trace = pm.sample(step=pm.Metropolis(),njobs=1)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/step_methods/metropolis.py", line 136, in __init__
    self.delta_logp = delta_logp(model.logpt, vars, shared)
  File "/home/user/miniconda3/lib/python3.6/site-packages/pymc3/model.py", line 666, in logpt
    logp_potentials = tt.sum([tt.sum(pot) for pot in self.potentials])

Debugprint of the apply node: 
MakeVector{dtype='float64'} [id A] <TensorType(float64, vector)> ''   
 |FromFunctionOp{likelihood} [id B] <TensorType(float64, scalar)> 'like'   

Storage map footprint:
 - <TensorType(float64, matrix)>, Shared Input, Shape: (500, 3), ElemSize: 8 Byte(s), TotalSize: 12000 Byte(s)
 - inarray1, Input, Shape: (3,), ElemSize: 8 Byte(s), TotalSize: 24 Byte(s)
 - inarray, Input, Shape: (3,), ElemSize: 8 Byte(s), TotalSize: 24 Byte(s)
 - Constant{0}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
 - Constant{3}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
 - TensorConstant{(1,) of 0...0068542243}, Shape: (1,), ElemSize: 8 Byte(s), TotalSize: 8 Byte(s)
 - TensorConstant{(1,) of -1..1111111111}, Shape: (1,), ElemSize: 8 Byte(s), TotalSize: 8 Byte(s)
 - TensorConstant{(1,) of -1.5}, Shape: (1,), ElemSize: 8 Byte(s), TotalSize: 8 Byte(s)
 - TensorConstant{0.5}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
 - like, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
 - Sum{acc_dtype=float64}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
 TotalSize: 12112.0 Byte(s) 0.000 GB
 TotalSize inputs: 12096.0 Byte(s) 0.000 GB

```

Regarding `m.logp(m.test_point)` - if I comment out `pm.sample` (which throws the exception) and add `m.logp(m.test_point)` instead, I get the same error. Is this the usage you intended?

---

<div class="post-metadata">

**Author:** ![junpenglao](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/junpenglao/32/8_2.png) [@junpenglao](https://discourse.pymc.io/u/junpenglao)\
**Post date:** [March 18, 2018, 5:33pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/10 "2018-03-18T17:33:02Z")

</div>

Yes that’s what I meant - it is a way to check if the model is setup correctly

> [@Get nan or inf from model.logp (model.test point) is an attestation of incorrectly configured model?](https://discourse.pymc.io/t/get-nan-or-inf-from-model-logp-model-test-point-is-an-attestation-of-incorrectly-configured-model/111/11):
>
> A few thoughts: 1, In your model, the observed part you are doing: with model: ... mz = pm.Uniform("mz", lower=0, upper=1, observed=mz\_freq) M = pm.Binomial("M", n=Yp, p=mz, observed=loss\_shifte However, the node mz is not doing anything, since there is no prior on mz, in effect, this is equivalent to mz = mz\_freq 2, Since we got -inf from model.logp (model.logp(model.test\_point)), we want to identify which RV node is causing the problem. @aseyboldt suggest doing model.bijection.…

in this case, it means the evaluation of logp is still not correct. How about setting the input to theano tensor ivector?

```python
@as_op(itypes=[theano.tensor.dvector, theano.tensor.ivector],
       otypes=[theano.tensor.dscalar])
def likelihood(params, data):
    return me.model.getLogProbability(data).sum()

```

---

<div class="post-metadata">

**Author:** ![adamh](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/adamh/32/1684_2.png) [@adamh](https://discourse.pymc.io/u/adamh)\
**Post date:** [March 18, 2018, 5:38pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/11 "2018-03-18T17:38:47Z")

</div>

But the observed data in this case is a matrix, not a vector… why should this work? Or am I missing something?

EDIT:  
When it raises `ValueError: expected an ndarray` - do you have an idea which object was expected to be of this type?

---

<div class="post-metadata">

**Author:** ![junpenglao](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/junpenglao/32/8_2.png) [@junpenglao](https://discourse.pymc.io/u/junpenglao)\
**Post date:** [March 18, 2018, 6:03pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/12 "2018-03-18T18:03:27Z")

</div>

In your liklihood function, seems that it’s not evaluated on `params`? Could you please try rewriting the function to actually evaluated on `params` and `data`?

---

<div class="post-metadata">

**Author:** ![adamh](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/adamh/32/1684_2.png) [@adamh](https://discourse.pymc.io/u/adamh)\
**Post date:** [March 19, 2018, 1:41pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/13 "2018-03-19T13:41:41Z")

</div>

This is just because I wrote a shorter version of the likelihood to make everything shorter and more readable, sorry about that. The full function is:

```
@as_op(itypes=[theano.tensor.dvector, theano.tensor.ivector],
       otypes=[theano.tensor.dscalar])
def likelihood(params, data):
    model = me.Model(params)
    return model.getLogProbability(data).sum()

```

So it’s probably not there… I tried the `ivector` version but it didn’t work.

The `me.Model` function uses an external C code - is there any chance the `as_op` decorator is having trouble because of this?

---

<div class="post-metadata">

**Author:** ![junpenglao](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/junpenglao/32/8_2.png) [@junpenglao](https://discourse.pymc.io/u/junpenglao)\
**Post date:** [March 19, 2018, 2:14pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/14 "2018-03-19T14:14:54Z")

</div>

I am not completely sure - but the problem is either `itypes` or `otypes`. How about changing the `otypes` to `theano.tensor.dvector`? Otherwise, since `data` is already set maybe remove that from the input so that the input to likelihood is `likelihood(params)`

---

<div class="post-metadata">

**Author:** ![adamh](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/adamh/32/1684_2.png) [@adamh](https://discourse.pymc.io/u/adamh)\
**Post date:** [March 20, 2018, 8:11pm UTC](https://discourse.pymc.io/t/pm-potential-without-theano/968/15 "2018-03-20T20:11:50Z")

</div>

Perfect! Now it’s working (also with `njobs` \> 1).`

Solution:

- Changed `otypes` to `theano.tensor.dvector`.
- Changed `return model.getLogProbability(data).sum()` to `return np.array(model.getLogProbability(data).sum()).reshape((1,))`

This returns an array instead of a number, which (I assume) theano handles better for some reason. Somehow related to [this](https://discuss.mxnet.io/t/rank-0-arrays-in-mxnet-aka-pi-is-wrong/108) post?

Thanks for all your help! Now to make sure the whole thing actually converges. 🙂 `