Hi all, I have recently read Jeff’s book and the Numenta white paper, and am very interested in getting started with NuPIC. Unfortunately, I am having some trouble getting a clean installation.
My environment is a Rackspace cloud VM running: - Ubuntu 14.10 (Utopic Unicorn) - Python 2.7.8 - mysql Ver 14.14 Distrib 5.6.19, for debian-linux-gnu (x86_64) using EditLine wrapper I installed NuPIC as follows: [[ # apt-get install python-pip # apt-get install python-dev # pip install numpy # pip install https://s3-us-west-2.amazonaws.com/artifacts.numenta.org/numenta/nupic/releases/nupic-0.1.3-cp27-none-linux_x86_64.whl <https://s3-us-west-2.amazonaws.com/artifacts.numenta.org/numenta/nupic/releases/nupic-0.1.3-cp27-none-linux_x86_64.whl> ]] …and then attempted to run the “hot gym” predication example: [[ # cd ~/nupic/examples/opf/clients/hotgym/prediction/one_gym # ./swarm.py ]] The output of the swarm run is provided below my signature. Unfortunately, the numpy and nupic installations as well as the hotgym example as seem to have significant numbers of python errors. The errors are both trivial and apparently problematic, such as API changes. The swarm run shows, for example, a TypeError. Should I expect this example to “just work” in the 0.13 release, or is my environment too new? Would a downgrade of Ubuntu or Python “fix” the problem? Does anyone have other suggestions? Thanks in advance! Regards, Dave -- http://about.me/david_wood The output of the swarm run was: [[ This script runs a swarm on the input data (rec-center-hourly.csv) and creates a model parameters file in the `model_params` directory containing the best model found by the swarm. Dumps a bunch of crud to stdout because that is just what swarming does at this point. You really don't need to pay any attention to it. ================================================= = Swarming on rec-center-hourly data... = Medium swarm. Sit back and relax, this could take awhile. ================================================= Generating experiment files in directory: /root/nupic/examples/opf/clients/hotgym/prediction/one_gym/swarm... Writing 313 lines... Writing 113 lines... done. None Successfully submitted new HyperSearch job, jobID=1002 Evaluated 0 models HyperSearch finished! Worker completion message: None Results from all experiments: ---------------------------------------------------------------- Generating experiment files in directory: /tmp/tmpBvtweU... Writing 313 lines... Writing 113 lines... done. None json.loads(jobInfo.results) raised an exception. Here is some info to help with debugging: jobInfo: _jobInfoNamedTuple(jobId=1002, client=u'GRP', clientInfo=u'', clientKey=u'', cmdLine=u'$HYPERSEARCH', params=u'{"hsVersion": "v2", "maxModels": null, "persistentJobGUID": "8090e46e-ba32-11e4-ad72-bc764e202244", "useTerminators": false, "description": {"includedFields": [{"fieldName": "timestamp", "fieldType": "datetime"}, {"maxValue": 53.0, "fieldName": "kw_energy_consumption", "fieldType": "float", "minValue": 0.0}], "streamDef": {"info": "kw_energy_consumption", "version": 1, "streams": [{"info": "Rec Center", "source": "file://rec-center-hourly.csv", "columns": ["*"]}]}, "inferenceType": "TemporalMultiStep", "inferenceArgs": {"predictionSteps": [1], "predictedField": "kw_energy_consumption"}, "iterationCount": -1, "swarmSize": "medium"}}', jobHash='\x80\x90\xe4o\xba2\x11\xe4\xadr\xbcvN "D', status=u'notStarted', completionReason=None, completionMsg=None, workerCompletionReason=u'success', workerCompletionMsg=None, cancel=0, startTime=None, endTime=None, results=None, engJobType=u'hypersearch', minimumWorkers=1, maximumWorkers=4, priority=0, engAllocateNewWorkers=1, engUntendedDeadWorkers=0, numFailedWorkers=0, lastFailedWorkerErrorMsg=None, engCleaningStatus=u'notdone', genBaseDescription=None, genPermutations=None, engLastUpdateTime=datetime.datetime(2015, 2, 22, 1, 31, 19), engCjmConnId=None, engWorkerState=None, engStatus=None, engModelMilestones=None) jobInfo.results: None EXCEPTION: expected string or buffer Traceback (most recent call last): File "./swarm.py", line 109, in <module> swarm(INPUT_FILE) File "./swarm.py", line 101, in swarm modelParams = swarmForBestModelParams(SWARM_DESCRIPTION, name) File "./swarm.py", line 78, in swarmForBestModelParams verbosity=0 File "/usr/local/lib/python2.7/dist-packages/nupic/swarming/permutations_runner.py", line 276, in runWithConfig return _runAction(runOptions) File "/usr/local/lib/python2.7/dist-packages/nupic/swarming/permutations_runner.py", line 217, in _runAction returnValue = _runHyperSearch(runOptions) File "/usr/local/lib/python2.7/dist-packages/nupic/swarming/permutations_runner.py", line 160, in _runHyperSearch metricsKeys=search.getDiscoveredMetricsKeys()) File "/usr/local/lib/python2.7/dist-packages/nupic/swarming/permutations_runner.py", line 825, in generateReport results = json.loads(jobInfo.results) File "/usr/local/lib/python2.7/dist-packages/nupic/support/object_json.py", line 163, in loads json.loads(s, object_hook=objectDecoderHook, **kwargs)) File "/usr/lib/python2.7/json/__init__.py", line 351, in loads return cls(encoding=encoding, **kw).decode(s) File "/usr/lib/python2.7/json/decoder.py", line 366, in decode obj, end = self.raw_decode(s, idx=_w(s, 0).end()) TypeError: expected string or buffer ]]
