Load whole model from pickle

[helena_Thielen]

Hey everybody,

I try to save my trained models with a pickle.
I already read this http://nupic.docs.numenta.org/1.0.3/guides/serialization.html#deprecated-serialization-methods whole page, but can’t find the solution for me…

I am performing a cross validation (I know this is not was HTM is made for…but we have to compare performances…so what to do )
So I have 7 trainings and test sets.
After finishing my training for one model, I save it into a list.
When I trained all models I pickle the list with a simple expression:

with open("model.pkl", "w") as f:
     pickle.dump(models, f)

where models is the list containing all my models.
All that works fine. (even saving the models in a list and using just one of them afterwards is working).

Now my problem (for which i was not able to find a solution here in the forum even with hours of reading )
I load the models from the pickle again with:

with open("model.pkl") as f:
     reloaded_models = pickle.load(f)

when I now want to make a prediction I get the following error:

      assert not self.__restoringFromState
AssertionError

in nupic/frameworks/opf/htm_prediction_model.py"

How can I fix this bug?
I really need my models in pickle… soo any help would be really appreciated.

Thank you all very much in advance.
Best,
Helena

[rhyolight]

I searched the forum and found these two topics referring to __restoringFromState:

Making a deep copy of an OPF model

Hello! I have an instance of an OPF model (the same one used in the numenta detector in NAB, actually) that I’d like to make a deep copy of in my code. The simplest solution (trying “model_copy = copy.deepcopy(model)”) does not work. When trying to do model_copy.run(), it breaks because self.__restoringFromState gets set to true inside model_copy which doesn’t pass an assert statement. Could somebody explain or point me in the direction of documentation which explains how to make deep copies o…

AssertionError: Using nupic with Spark

No I am not pickling the model anywhere. MODEL_PARAMS = { # Type of model that the rest of these parameters apply to. 'model': "HTMPrediction", # Version that specifies the format of the config. 'version': 1, # Intermediate variables used to compute fields in modelParams and also # referenced from the control section. 'aggregationInfo': { 'days': 0, 'fields': [(u'c1', 'sum'), (u'c0', 'first')], 'hours': 1, 'microseconds': 0, 'millis…

Do either of these threads help?

[helena_Thielen]

unfortunately no… I read both before even opening this new topic… but they doen’t help me.
The thing is:
I calculate the models.
I can work with all the results and to prediction and everything. But as soon as I pickle and reload them i get this error…
I also checked the code in nupic/frameworks/opf/htm_prediction_model.py … I tried to manually set the __restoringFromState variable. But even this does not work…

So I am lost

[rhyolight]

Did you try the new way of saving using writeToFile and readFromFile? If you can’t just put models in a list and pickle them, you’ll need to keep track of the sp and tm files separately for each model.

To get to the algorithm instances, see this post.

[helena_Thielen]

Hey =)
Thank you very much for your help.
So after saving the model instances with

@rhyolight

• model._getSPRegion().getSelf().getAlgorithmInstance() gets you the SP
• model._getTPRegion().getSelf().getAlgorithmInstance() gets you the TM

How can I build a model from that? Is there any link to the docs where this is explained?

Thanks again

[rhyolight]

Just like the first section of the docs show:

with open("out.tmp", "wb") as f:
  sp1.writeToFile(f)

with open("out.tmp", "rb") as f:
  sp2 = SpatialPooler.readFromFile(f)

Same with TM.

[helena_Thielen]

Thanks for your reply.

this is clear! But afterwards??? I do have the instances for SP and TM.
How can I build a whole model with these??
I want to do some more predictions and tests.

[rhyolight]

Can you create an OPF model in the same way, then try to replace the algorithm instances in the model that you’ve resurrected from disk? This is hacky, but I would try it. See:

numenta/nupic/blob/50c5fd0dc94f2ffb205544ed11fe82ad5bb0de18/src/nupic/regions/sp_region.py#L765-L770

numenta/nupic/blob/50c5fd0dc94f2ffb205544ed11fe82ad5bb0de18/src/nupic/regions/tm_region.py#L698-L704

• replace the SP model._getSPREgioon().getSelf()._sfdr with the resurrected SP instance
• replace the TM model._getTPRegion().getSelf(). _tfdr with the resurrected TM instance

I’m not sure if this will work, I have never tried it!

[helena_Thielen]

Thanks a lot!! I will try that