def testCheckpointLearned(self):
# Create a model and give it some inputs to learn.
tm1 = BacktrackingTM(numberOfCols=100,
cellsPerColumn=12,
verbosity=VERBOSITY)
sequences = [self.generateSequence() for _ in xrange(5)]
train = list(itertools.chain.from_iterable(sequences[:3]))
for bottomUpInput in train:
if bottomUpInput is None:
tm1.reset()
else:
tm1.compute(bottomUpInput, True, True)
# Serialize and deserialized the TM.
checkpointPath = os.path.join(self._tmpDir, 'a')
tm1.saveToFile(checkpointPath)
tm2 = pickle.loads(pickle.dumps(tm1))
tm2.loadFromFile(checkpointPath)
# Check that the TMs are the same.
self.assertTMsEqual(tm1, tm2)
# Feed some data into the models.
test = list(itertools.chain.from_iterable(sequences[3:]))
for bottomUpInput in test:
if bottomUpInput is None:
tm1.reset()
tm2.reset()
else:
result1 = tm1.compute(bottomUpInput, True, True)
result2 = tm2.compute(bottomUpInput, True, True)
self.assertTMsEqual(tm1, tm2)
self.assertTrue(numpy.array_equal(result1, result2))
def testCheckpointMiddleOfSequence2(self):
"""More complex test of checkpointing in the middle of a sequence."""
tm1 = BacktrackingTM(2048, 32, 0.21, 0.5, 11, 20, 0.1, 0.1, 1.0, 0.0,
14, False, 5, 2, False, 1960, 0, False, 3, 10, 5,
0, 32, 128, 32, 'normal')
tm2 = BacktrackingTM(2048, 32, 0.21, 0.5, 11, 20, 0.1, 0.1, 1.0, 0.0,
14, False, 5, 2, False, 1960, 0, False, 3, 10, 5,
0, 32, 128, 32, 'normal')
with open(resource_filename(__name__, 'data/tm_input.csv'),
'r') as fin:
reader = csv.reader(fin)
records = []
for bottomUpInStr in fin:
bottomUpIn = numpy.array(eval('[' + bottomUpInStr.strip() +
']'),
dtype='int32')
records.append(bottomUpIn)
i = 1
for r in records[:250]:
print i
i += 1
output1 = tm1.compute(r, True, True)
output2 = tm2.compute(r, True, True)
self.assertTrue(numpy.array_equal(output1, output2))
print 'Serializing and deserializing models.'
savePath1 = os.path.join(self._tmpDir, 'tm1.bin')
tm1.saveToFile(savePath1)
tm3 = pickle.loads(pickle.dumps(tm1))
tm3.loadFromFile(savePath1)
savePath2 = os.path.join(self._tmpDir, 'tm2.bin')
tm2.saveToFile(savePath2)
tm4 = pickle.loads(pickle.dumps(tm2))
tm4.loadFromFile(savePath2)
self.assertTMsEqual(tm1, tm3)
self.assertTMsEqual(tm2, tm4)
for r in records[250:]:
print i
i += 1
out1 = tm1.compute(r, True, True)
out2 = tm2.compute(r, True, True)
out3 = tm3.compute(r, True, True)
out4 = tm4.compute(r, True, True)
self.assertTrue(numpy.array_equal(out1, out2))
self.assertTrue(numpy.array_equal(out1, out3))
self.assertTrue(numpy.array_equal(out1, out4))
self.assertTMsEqual(tm1, tm2)
self.assertTMsEqual(tm1, tm3)
self.assertTMsEqual(tm2, tm4)