def testRun(self):
"""
A simple NetworkAPI example with three regions.
///////////////////////////////////////////////////////////////
//
// .------------------.
// | encoder |
// |(RDSEEncoderRegion)|<------ inital input
// | | (INPUT.begin)
// `-------------------'
// | --------------. sp.bottomUpIn
// |/ |
// .-----------------. |
// | sp | |
// | (SPRegion) | |
// | | |
// `-----------------' |
// | ^
// .-----------------. |
// | tm | |
// | (TMRegion) |-----' (tm.bottomUpOut)
// | |
// `-----------------'
//
//////////////////////////////////////////////////////////////////
"""
""" Creating network instance. """
config = """
{network: [
{addRegion: {name: "encoder", type: "RDSEEncoderRegion", params: {size: 1000, sparsity: 0.2, radius: 0.03, seed: 2019, noise: 0.01}, phase: [1]}},
{addRegion: {name: "sp", type: "SPRegion", params: {columnCount: 1000, globalInhibition: true}, phase: [2]}},
{addRegion: {name: "tm", type: "TMRegion", params: {cellsPerColumn: 8, orColumnOutputs: true}, phase: [2]}},
{addLink: {src: "INPUT.begin", dest: "encoder.values", dim: [1]}},
{addLink: {src: "encoder.encoded", dest: "sp.bottomUpIn", mode: "overwrite"}},
{addLink: {src: "sp.bottomUpOut", dest: "tm.bottomUpIn"}},
{addLink: {src: "tm.bottomUpOut", dest: "sp.bottomUpIn"}}
]}"""
net = Network()
net.configure(config)
net.initialize()
# for debugging: print(net.getExecutionMap())
""" Force initial data. """
net.setInputData("begin", np.array([10]))
""" Execute encoder once, the loop (sp and tm) 4 times """
net.run(1, [1]) # execute initial entry (phase 1)
net.run(4, [2]) # execute loop 4 times (phase 2)
# Here is how you access the buffers
sp_input_buffer = np.array(net.getRegion('sp').getInputArray('bottomUpIn'))
tn_output_buffer = np.array(net.getRegion('tm').getOutputArray('bottomUpOut'))
self.assertEqual(sp_input_buffer.size, tn_output_buffer.size)
def testNetwork(self):
"""
A simple NetworkAPI example with three regions.
///////////////////////////////////////////////////////////////
//
// .------------------.
// | encoder |
// sinewave data--->|(RDSEEncoderRegion)|
// | |
// `-------------------'
// |
// .-----------------.
// | sp |
// | (SPRegion) |
// | |
// `-----------------'
// |
// .-----------------.
// | tm |
// | (TMRegion) |---->anomaly score
// | |
// `-----------------'
//
//////////////////////////////////////////////////////////////////
"""
""" Creating network instance. """
config = """
{network: [
{addRegion: {name: "encoder", type: "RDSEEncoderRegion", params: {size: 1000, sparsity: 0.2, radius: 0.03, seed: 2019, noise: 0.01}}},
{addRegion: {name: "sp", type: "SPRegion", params: {columnCount: 2048, globalInhibition: true}}},
{addRegion: {name: "tm", type: "TMRegion", params: {cellsPerColumn: 8, orColumnOutputs: true}}},
{addLink: {src: "encoder.encoded", dest: "sp.bottomUpIn"}},
{addLink: {src: "sp.bottomUpOut", dest: "tm.bottomUpIn"}}
]}"""
net = Network()
net.configure(config)
# iterate EPOCHS times
x = 0.00
for e in range(EPOCHS):
# Data is a sine wave, (Note: first iteration is for x=0.01, not 0)
x += 0.01 # advance one step, 0.01 radians
s = math.sin(x) # compute current sine as data.
# feed data to RDSE encoder via its "sensedValue" parameter.
net.getRegion('encoder').setParameterReal64('sensedValue', s)
net.run(1) # Execute one iteration of the Network object
# Retreive the final anomaly score from the TM object's 'anomaly' output. (as a single element numpy array)
score = np.array(net.getRegion('tm').getOutputArray('anomaly'))
self.assertEqual(score, [1])
from htm.advanced.support.register_regions import registerAllAdvancedRegions
registerAllAdvancedRegions()
""" Creating network instance. """
config = """
{network: [
{addRegion: {name: "encoder", type: "RDSEEncoderRegion", params: {size: 1000, sparsity: 0.2, radius: 0.03, seed: 2019, noise: 0.01}}},
{addRegion: {name: "sp", type: "SPRegion", params: {columnCount: 2048, globalInhibition: true}}},
{addRegion: {name: "tm", type: "TMRegion", params: {cellsPerColumn: 8, orColumnOutputs: true}}},
{addRegion: {name: "apicalTM", type: "py.ApicalTMPairRegion", params: {columnCount : 2048, basalInputWidth : 10, cellsPerColumn: 8, implementation: ApicalTiebreak}}},
{addLink: {src: "encoder.encoded", dest: "sp.bottomUpIn"}},
{addLink: {src: "sp.bottomUpOut", dest: "tm.bottomUpIn"}},
{addLink: {src: "sp.bottomUpOut", dest: "apicalTM.activeColumns"}}
]}"""
net = Network()
net.configure(config)
# feed data to RDSE encoder via its "sensedValue" parameter.
net.getRegion('encoder').setParameterReal64('sensedValue', 100)
net.run(10) # Execute iteration of the Network object
print(net.getRegion('tm'))
print(net.getRegion('apicalTM'))
print(net.getRegion('tm').getConnections(
"")) # can be called because of this draft PR
print(
net.getRegion('apicalTM').getConnections("")
) # returns always None, it is region implemented in python, but it has not override getConnections