def createTMs(includeCPP = True,<EOL>includePy = True,<EOL>numCols = <NUM_LIT:100>,<EOL>cellsPerCol = <NUM_LIT:4>,<EOL>activationThreshold = <NUM_LIT:3>,<EOL>minThreshold = <NUM_LIT:3>,<EOL>newSynapseCount = <NUM_LIT:3>,<EOL>initialPerm = <NUM_LIT>,<EOL>permanenceInc = <NUM_LIT:0.1>,<EOL>permanenceDec = <NUM_LIT:0.0>,<EOL>globalDecay = <NUM_LIT:0.0>,<EOL>pamLength = <NUM_LIT:0>,<EOL>checkSynapseConsistency = True,<EOL>maxInfBacktrack = <NUM_LIT:0>,<EOL>maxLrnBacktrack = <NUM_LIT:0>,<EOL>**kwargs<EOL>):
<EOL>connectedPerm = <NUM_LIT:0.5><EOL>tms = dict()<EOL>if includeCPP:<EOL><INDENT>if VERBOSITY >= <NUM_LIT:2>:<EOL><INDENT>print("<STR_LIT>")<EOL><DEDENT>cpp_tm = BacktrackingTMCPP(numberOfCols = numCols, cellsPerColumn = cellsPerCol,<EOL>initialPerm = initialPerm, connectedPerm = connectedPerm,<EOL>minThreshold = minThreshold, newSynapseCount = newSynapseCount,<EOL>permanenceInc = permanenceInc, permanenceDec = permanenceDec,<EOL>activationThreshold = activationThreshold,<EOL>globalDecay = globalDecay, burnIn = <NUM_LIT:1>,<EOL>seed=SEED, verbosity=VERBOSITY,<EOL>checkSynapseConsistency = checkSynapseConsistency,<EOL>collectStats = True,<EOL>pamLength = pamLength,<EOL>maxInfBacktrack = maxInfBacktrack,<EOL>maxLrnBacktrack = maxLrnBacktrack,<EOL>)<EOL>cpp_tm.retrieveLearningStates = True<EOL>tms['<STR_LIT>'] = cpp_tm<EOL><DEDENT>if includePy:<EOL><INDENT>if VERBOSITY >= <NUM_LIT:2>:<EOL><INDENT>print("<STR_LIT>")<EOL><DEDENT>py_tm = BacktrackingTM(numberOfCols = numCols, cellsPerColumn = cellsPerCol,<EOL>initialPerm = initialPerm, connectedPerm = connectedPerm,<EOL>minThreshold = minThreshold, newSynapseCount = newSynapseCount,<EOL>permanenceInc = permanenceInc, permanenceDec = permanenceDec,<EOL>activationThreshold = activationThreshold,<EOL>globalDecay = globalDecay, burnIn = <NUM_LIT:1>,<EOL>seed=SEED, verbosity=VERBOSITY,<EOL>collectStats = True,<EOL>pamLength = pamLength,<EOL>maxInfBacktrack = maxInfBacktrack,<EOL>maxLrnBacktrack = maxLrnBacktrack,<EOL>)<EOL>tms['<STR_LIT>'] = py_tm<EOL><DEDENT>return tms<EOL>
Create one or more TM instances, placing each into a dict keyed by
    name.

    Parameters:
    ------------------------------------------------------------------
    retval:   tms - dict of TM instances