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nupic tests, Raspbian Stretch, attempt #2
Raw
gistfile1.txt
============================= test session starts ==============================
platform linux2 -- Python 2.7.13, pytest-3.0.7, py-1.6.0, pluggy-0.4.0
rootdir: /home/pi/nupic, inifile:
plugins: xdist-1.16.0, cov-2.5.0
collected 738 items
tests/unit/nupic/serializable_test.py ...
tests/unit/nupic/utils_test.py ......
tests/unit/nupic/algorithms/anomaly_likelihood_jeff_test.py ...ss..
tests/unit/nupic/algorithms/anomaly_likelihood_test.py .....................
tests/unit/nupic/algorithms/anomaly_test.py ..............
tests/unit/nupic/algorithms/backtracking_tm_constant_test.py *** Synapse consistency checking turned on for Cells4 ***
.*** Synapse consistency checking turned on for Cells4 ***
.*** Synapse consistency checking turned on for Cells4 ***
.
tests/unit/nupic/algorithms/backtracking_tm_cpp2_test.py *** Synapse consistency checking turned on for Cells4 ***
*** Python segment match turned on for Cells4
.
tests/unit/nupic/algorithms/backtracking_tm_cpp_test.py ....FFF
tests/unit/nupic/algorithms/backtracking_tm_test.py ....FFF
tests/unit/nupic/algorithms/connections_test.py .........
tests/unit/nupic/algorithms/inhibition_object_test.py s
tests/unit/nupic/algorithms/knn_classifier_test.py .........s...
tests/unit/nupic/algorithms/sdr_classifier_test.py ............................
tests/unit/nupic/algorithms/sp_learn_inference_test.py s
tests/unit/nupic/algorithms/sp_overlap_test.py .s.s
tests/unit/nupic/algorithms/spatial_pooler_boost_test.py ..
tests/unit/nupic/algorithms/spatial_pooler_compatability_test.py ...ss....
tests/unit/nupic/algorithms/spatial_pooler_compute_test.py ..
tests/unit/nupic/algorithms/spatial_pooler_cpp_api_test.py ............................
tests/unit/nupic/algorithms/spatial_pooler_cpp_unit_test.py .....
tests/unit/nupic/algorithms/spatial_pooler_py_api_test.py ............................
tests/unit/nupic/algorithms/spatial_pooler_unit_test.py s..............................F....
tests/unit/nupic/algorithms/temporal_memory_test.py ...............................s.....s.
tests/unit/nupic/algorithms/monitor_mixin/metric_test.py ..
tests/unit/nupic/algorithms/monitor_mixin/trace_test.py ..
tests/unit/nupic/data/aggregator_test.py .
tests/unit/nupic/data/dictutils_test.py ......
tests/unit/nupic/data/fieldmeta_test.py .....
tests/unit/nupic/data/file_record_stream_test.py ......
tests/unit/nupic/data/filters_test.py s
tests/unit/nupic/data/functionsource_test.py ......
tests/unit/nupic/data/inference_shifter_test.py ........
tests/unit/nupic/data/record_stream_test.py .......
tests/unit/nupic/data/utils_test.py .......
tests/unit/nupic/data/generators/anomalyzer_test.py ...........
tests/unit/nupic/data/generators/pattern_machine_test.py .........
tests/unit/nupic/data/generators/sequence_machine_test.py .....
tests/unit/nupic/docs/examples_test.py .xx.xxxxxx
tests/unit/nupic/encoders/adaptivescalar_test.py .......
tests/unit/nupic/encoders/category_test.py ..
tests/unit/nupic/encoders/coordinate_test.py .................
tests/unit/nupic/encoders/date_test.py .........
tests/unit/nupic/encoders/delta_test.py .....
tests/unit/nupic/encoders/geospatial_coordinate_test.py ...........
tests/unit/nupic/encoders/logenc_test.py ......
tests/unit/nupic/encoders/multi_test.py ..
tests/unit/nupic/encoders/pass_through_encoder_test.py ....
tests/unit/nupic/encoders/random_distributed_scalar_test.py ...............
tests/unit/nupic/encoders/scalar_test.py .............
tests/unit/nupic/encoders/scalarspace_test.py .
tests/unit/nupic/encoders/sdrcategory_test.py ...
tests/unit/nupic/encoders/sparse_pass_through_encoder_test.py .....
tests/unit/nupic/engine/network_test.py ......F..FF
tests/unit/nupic/engine/syntactic_sugar_test.py .F...
tests/unit/nupic/engine/unified_py_parameter_test.py ..
tests/unit/nupic/frameworks/opf/htmpredictionmodel_classifier_helper_test.py ......................
tests/unit/nupic/frameworks/opf/htmpredictionmodel_test.py ......
tests/unit/nupic/frameworks/opf/opf_metrics_test.py ...............................
tests/unit/nupic/frameworks/opf/previous_value_model_test.py .......
tests/unit/nupic/frameworks/opf/safe_interpreter_test.py ........
tests/unit/nupic/frameworks/opf/two_gram_model_test.py ......
tests/unit/nupic/frameworks/opf/common_models/cluster_params_test.py .
tests/unit/nupic/math/lgamma_test.py .
tests/unit/nupic/math/topology_test.py ....................
tests/unit/nupic/regions/anomaly_likelihood_region_test.py ...
tests/unit/nupic/regions/anomaly_region_test.py .
tests/unit/nupic/regions/knn_anomaly_classifier_region_test.py .....................
tests/unit/nupic/regions/knn_classifier_region_test.py .
tests/unit/nupic/regions/record_sensor_region_test.py ...
tests/unit/nupic/regions/regions_spec_test.py s...s......
tests/unit/nupic/regions/sdr_classifier_region_test.py ..
tests/unit/nupic/regions/tm_region_test.py ....
tests/unit/nupic/support/configuration_test.py ............s....................
tests/unit/nupic/support/custom_configuration_test.py ...................s.........................
tests/unit/nupic/support/decorators_test.py ............
tests/unit/nupic/support/group_by_test.py ......
tests/unit/nupic/support/object_json_test.py ...............
tests/unit/nupic/support/consoleprinter_test/consoleprinter_test.py .
=================================== FAILURES ===================================
_________________ BacktrackingTMTest.testSerializationLearned __________________
self = <tests.unit.nupic.algorithms.backtracking_tm_test.BacktrackingTMTest testMethod=testSerializationLearned>
@unittest.skipUnless(capnp, "pycapnp not installed")
def testSerializationLearned(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.
tmProto = BacktrackingTM.getSchema().new_message()
tm1.write(tmProto)
checkpointPath = os.path.join(self._tmpDir, 'a')
with open(checkpointPath, "wb") as f:
tmProto.write(f)
with open(checkpointPath, "rb") as f:
tmProto = BacktrackingTM.getSchema().read(f)
tm2 = BacktrackingTM.read(tmProto)
# Check that the TMs are the same.
> self.assertTMsEqual(tm1, tm2)
tests/unit/nupic/algorithms/backtracking_tm_test.py:89:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/unit/nupic/algorithms/backtracking_tm_test.py:348: in assertTMsEqual
self.assertEqual(tm1, tm2, tm1.diff(tm2))
E AssertionError: <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x734c5330> != <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x734c51f0> : [(('maxSynapsesPerSegment',), -1, -1L), (('maxSegmentsPerCell',), -1, -1L), (('seed',), 42, 42L)]
----------------------------- Captured stdout call -----------------------------
<nupic.bindings.algorithms.Cells4; proxy of <Swig Object of type 'nupic::algorithms::Cells4::Cells4 *' at 0x73f372a8> >
_____________ BacktrackingTMTest.testSerializationMiddleOfSequence _____________
self = <tests.unit.nupic.algorithms.backtracking_tm_test.BacktrackingTMTest testMethod=testSerializationMiddleOfSequence>
@unittest.skipUnless(capnp, "pycapnp not installed")
def testSerializationMiddleOfSequence(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] +
[sequences[3][:5]]))
for bottomUpInput in train:
if bottomUpInput is None:
tm1.reset()
else:
tm1.compute(bottomUpInput, True, True)
# Serialize and deserialized the TM.
tmProto = BacktrackingTM.getSchema().new_message()
tm1.write(tmProto)
checkpointPath = os.path.join(self._tmpDir, 'a')
with open(checkpointPath, "wb") as f:
tmProto.write(f)
with open(checkpointPath, "rb") as f:
tmProto = BacktrackingTM.getSchema().read(f)
tm2 = BacktrackingTM.read(tmProto)
# Check that the TMs are the same.
> self.assertTMsEqual(tm1, tm2)
tests/unit/nupic/algorithms/backtracking_tm_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/unit/nupic/algorithms/backtracking_tm_test.py:348: in assertTMsEqual
self.assertEqual(tm1, tm2, tm1.diff(tm2))
E AssertionError: <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x73ee0750> != <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x73ee07b0> : [(('maxSynapsesPerSegment',), -1, -1L), (('maxSegmentsPerCell',), -1, -1L), (('seed',), 42, 42L)]
----------------------------- Captured stdout call -----------------------------
<nupic.bindings.algorithms.Cells4; proxy of <Swig Object of type 'nupic::algorithms::Cells4::Cells4 *' at 0x73eef668> >
____________ BacktrackingTMTest.testSerializationMiddleOfSequence2 _____________
self = <tests.unit.nupic.algorithms.backtracking_tm_test.BacktrackingTMTest testMethod=testSerializationMiddleOfSequence2>
@unittest.skipUnless(capnp, "pycapnp not installed")
def testSerializationMiddleOfSequence2(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')
tmProto1 = BacktrackingTM.getSchema().new_message()
tm1.write(tmProto1)
with open(savePath1, "wb") as f:
tmProto1.write(f)
with open(savePath1, "rb") as f:
tmProto3 = BacktrackingTM.getSchema().read(f)
tm3 = BacktrackingTM.read(tmProto3)
savePath2 = os.path.join(self._tmpDir, 'tm2.bin')
tmProto2 = BacktrackingTM.getSchema().new_message()
tm2.write(tmProto2)
with open(savePath2, "wb") as f:
tmProto2.write(f)
with open(savePath2, "rb") as f:
tmProto4 = BacktrackingTM.getSchema().read(f)
tm4 = BacktrackingTM.read(tmProto4)
> self.assertTMsEqual(tm1, tm3)
tests/unit/nupic/algorithms/backtracking_tm_test.py:193:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/unit/nupic/algorithms/backtracking_tm_test.py:348: in assertTMsEqual
self.assertEqual(tm1, tm2, tm1.diff(tm2))
E AssertionError: <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x738eff70> != <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x73ee07b0> : [(('maxSynapsesPerSegment',), 32, 32L), (('maxSegmentsPerCell',), 128, 128L), (('seed',), 1960, 1960L)]
----------------------------- Captured stdout call -----------------------------
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Serializing and deserializing models.
<nupic.bindings.algorithms.Cells4; proxy of <Swig Object of type 'nupic::algorithms::Cells4::Cells4 *' at 0x73e9e5d8> >
<nupic.bindings.algorithms.Cells4; proxy of <Swig Object of type 'nupic::algorithms::Cells4::Cells4 *' at 0x73e9e710> >
_________________ BacktrackingTMTest.testSerializationLearned __________________
self = <tests.unit.nupic.algorithms.backtracking_tm_test.BacktrackingTMTest testMethod=testSerializationLearned>
@unittest.skipUnless(capnp, "pycapnp not installed")
def testSerializationLearned(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.
tmProto = BacktrackingTM.getSchema().new_message()
tm1.write(tmProto)
checkpointPath = os.path.join(self._tmpDir, 'a')
with open(checkpointPath, "wb") as f:
tmProto.write(f)
with open(checkpointPath, "rb") as f:
tmProto = BacktrackingTM.getSchema().read(f)
tm2 = BacktrackingTM.read(tmProto)
# Check that the TMs are the same.
> self.assertTMsEqual(tm1, tm2)
tests/unit/nupic/algorithms/backtracking_tm_test.py:89:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/unit/nupic/algorithms/backtracking_tm_test.py:348: in assertTMsEqual
self.assertEqual(tm1, tm2, tm1.diff(tm2))
E AssertionError: <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x73ee0190> != <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x73ee0170> : [(('maxSynapsesPerSegment',), -1, -1L), (('maxSegmentsPerCell',), -1, -1L), (('seed',), 42, 42L)]
----------------------------- Captured stdout call -----------------------------
<nupic.bindings.algorithms.Cells4; proxy of <Swig Object of type 'nupic::algorithms::Cells4::Cells4 *' at 0x73eef530> >
_____________ BacktrackingTMTest.testSerializationMiddleOfSequence _____________
self = <tests.unit.nupic.algorithms.backtracking_tm_test.BacktrackingTMTest testMethod=testSerializationMiddleOfSequence>
@unittest.skipUnless(capnp, "pycapnp not installed")
def testSerializationMiddleOfSequence(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] +
[sequences[3][:5]]))
for bottomUpInput in train:
if bottomUpInput is None:
tm1.reset()
else:
tm1.compute(bottomUpInput, True, True)
# Serialize and deserialized the TM.
tmProto = BacktrackingTM.getSchema().new_message()
tm1.write(tmProto)
checkpointPath = os.path.join(self._tmpDir, 'a')
with open(checkpointPath, "wb") as f:
tmProto.write(f)
with open(checkpointPath, "rb") as f:
tmProto = BacktrackingTM.getSchema().read(f)
tm2 = BacktrackingTM.read(tmProto)
# Check that the TMs are the same.
> self.assertTMsEqual(tm1, tm2)
tests/unit/nupic/algorithms/backtracking_tm_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/unit/nupic/algorithms/backtracking_tm_test.py:348: in assertTMsEqual
self.assertEqual(tm1, tm2, tm1.diff(tm2))
E AssertionError: <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x739c7f70> != <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x5f9a7210> : [(('maxSynapsesPerSegment',), -1, -1L), (('maxSegmentsPerCell',), -1, -1L), (('seed',), 42, 42L)]
----------------------------- Captured stdout call -----------------------------
<nupic.bindings.algorithms.Cells4; proxy of <Swig Object of type 'nupic::algorithms::Cells4::Cells4 *' at 0x73eefc50> >
____________ BacktrackingTMTest.testSerializationMiddleOfSequence2 _____________
self = <tests.unit.nupic.algorithms.backtracking_tm_test.BacktrackingTMTest testMethod=testSerializationMiddleOfSequence2>
@unittest.skipUnless(capnp, "pycapnp not installed")
def testSerializationMiddleOfSequence2(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')
tmProto1 = BacktrackingTM.getSchema().new_message()
tm1.write(tmProto1)
with open(savePath1, "wb") as f:
tmProto1.write(f)
with open(savePath1, "rb") as f:
tmProto3 = BacktrackingTM.getSchema().read(f)
tm3 = BacktrackingTM.read(tmProto3)
savePath2 = os.path.join(self._tmpDir, 'tm2.bin')
tmProto2 = BacktrackingTM.getSchema().new_message()
tm2.write(tmProto2)
with open(savePath2, "wb") as f:
tmProto2.write(f)
with open(savePath2, "rb") as f:
tmProto4 = BacktrackingTM.getSchema().read(f)
tm4 = BacktrackingTM.read(tmProto4)
> self.assertTMsEqual(tm1, tm3)
tests/unit/nupic/algorithms/backtracking_tm_test.py:193:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/unit/nupic/algorithms/backtracking_tm_test.py:348: in assertTMsEqual
self.assertEqual(tm1, tm2, tm1.diff(tm2))
E AssertionError: <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x7355dcd0> != <nupic.algorithms.backtracking_tm_cpp.BacktrackingTMCPP object at 0x73ee02f0> : [(('maxSynapsesPerSegment',), 32, 32L), (('maxSegmentsPerCell',), 128, 128L), (('seed',), 1960, 1960L)]
----------------------------- Captured stdout call -----------------------------
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Serializing and deserializing models.
<nupic.bindings.algorithms.Cells4; proxy of <Swig Object of type 'nupic::algorithms::Cells4::Cells4 *' at 0x73eef2f0> >
<nupic.bindings.algorithms.Cells4; proxy of <Swig Object of type 'nupic::algorithms::Cells4::Cells4 *' at 0x73eef050> >
_______________________ SpatialPoolerTest.testWriteRead ________________________
self = <tests.unit.nupic.algorithms.spatial_pooler_unit_test.SpatialPoolerTest testMethod=testWriteRead>
@unittest.skipUnless(
capnp, "pycapnp is not installed, skipping serialization test.")
def testWriteRead(self):
sp1 = SpatialPooler(
inputDimensions=[9],
columnDimensions=[5],
potentialRadius=3,
potentialPct=0.5,
globalInhibition=False,
localAreaDensity=-1.0,
numActiveColumnsPerInhArea=3,
stimulusThreshold=1,
synPermInactiveDec=0.01,
synPermActiveInc=0.1,
synPermConnected=0.10,
minPctOverlapDutyCycle=0.1,
dutyCyclePeriod=10,
boostStrength=10.0,
seed=42,
spVerbosity=0)
# Run a record through before serializing
inputVector = numpy.array([1, 0, 1, 0, 1, 0, 0, 1, 1])
activeArray1 = numpy.zeros(5)
sp1.compute(inputVector, True, activeArray1)
proto1 = SpatialPoolerProto_capnp.SpatialPoolerProto.new_message()
sp1.write(proto1)
# Write the proto to a temp file and read it back into a new proto
with tempfile.TemporaryFile() as f:
proto1.write(f)
f.seek(0)
proto2 = SpatialPoolerProto_capnp.SpatialPoolerProto.read(f)
# Load the deserialized proto
sp2 = SpatialPooler.read(proto2)
ephemeral = set(["_boostedOverlaps", "_overlaps"])
# Check that the two spatial poolers have the same attributes
self.assertSetEqual(set(sp1.__dict__.keys()), set(sp2.__dict__.keys()))
for k, v1 in sp1.__dict__.iteritems():
v2 = getattr(sp2, k)
if k in ephemeral:
continue
if isinstance(v1, numpy.ndarray):
self.assertEqual(v1.dtype, v2.dtype,
"Key %s has differing dtypes: %s vs %s" % (
> k, v1.dtype, v2.dtype))
E AssertionError: Key _inputDimensions has differing dtypes: int32 vs int64
tests/unit/nupic/algorithms/spatial_pooler_unit_test.py:1503: AssertionError
----------------------------- Captured stdout call -----------------------------
New seed generated as: 1163 called by run line 320 -> setUp
_______________________ NetworkTest.testOneRegionNetwork _______________________
self = <tests.unit.nupic.engine.network_test.NetworkTest testMethod=testOneRegionNetwork>
def testOneRegionNetwork(self):
n = engine.Network()
print "Number of regions in new network: %d" % len(n.regions)
self.assertEqual(len(n.regions), 0)
print "Adding level1SP"
level1SP = n.addRegion("level1SP", "TestNode", "")
> print "Current dimensions are: %s" % level1SP.dimensions
tests/unit/nupic/engine/network_test.py:103:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <nupic.engine.Region object at 0x73d56ab0>
def _getDimensions(self):
"""Dimensions of the region"""
> return Dimensions(tuple(self._region.getDimensions()))
E TypeError: 'Dimensions' object is not iterable
/usr/local/lib/python2.7/dist-packages/nupic/engine/__init__.py:475: TypeError
----------------------------- Captured stdout call -----------------------------
Number of regions in new network: 0
Adding level1SP
_______________________ NetworkTest.testTwoRegionNetwork _______________________
self = <tests.unit.nupic.engine.network_test.NetworkTest testMethod=testTwoRegionNetwork>
def testTwoRegionNetwork(self):
n = engine.Network()
region1 = n.addRegion("region1", "TestNode", "")
region2 = n.addRegion("region2", "TestNode", "")
names = [region[0] for region in n.regions]
self.assertEqual(names, ['region1', 'region2'])
print n.getPhases('region1')
self.assertEqual(n.getPhases('region1'), (0,))
self.assertEqual(n.getPhases('region2'), (1,))
n.link("region1", "region2", "TestFanIn2", "")
print "Initialize should fail..."
with self.assertRaises(Exception):
n.initialize()
print "Setting region1 dims"
r1dims = engine.Dimensions([6, 4])
region1.setDimensions(r1dims)
print "Initialize should now succeed"
n.initialize()
> r2dims = region2.dimensions
tests/unit/nupic/engine/network_test.py:307:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <nupic.engine.Region object at 0x739c7b10>
def _getDimensions(self):
"""Dimensions of the region"""
> return Dimensions(tuple(self._region.getDimensions()))
E TypeError: 'Dimensions' object is not iterable
/usr/local/lib/python2.7/dist-packages/nupic/engine/__init__.py:475: TypeError
----------------------------- Captured stdout call -----------------------------
(0,)
Initialize should fail...
Setting region1 dims
Initialize should now succeed
----------------------------- Captured stderr call -----------------------------
ERR: Network::initialize() -- unable to evaluate all links
The following links could not be evaluated:
[region1.bottomUpOut (region dims: [unspecified]) to region2.bottomUpIn (region dims: [unspecified]) type: TestFanIn2]
[/home/pi/nupic.core/src/nupic/engine/Network.cpp line 488]
____________________ NetworkTest.testTwoRegionPyNodeNetwork ____________________
self = <tests.unit.nupic.engine.network_test.NetworkTest testMethod=testTwoRegionPyNodeNetwork>
@unittest.skipIf(sys.platform.lower().startswith("win"),
"Not supported on Windows, yet!")
def testTwoRegionPyNodeNetwork(self):
n = engine.Network()
region1 = n.addRegion("region1", "py.TestNode", "")
region2 = n.addRegion("region2", "py.TestNode", "")
n.link("region1", "region2", "TestFanIn2", "")
print "Initialize should fail..."
with self.assertRaises(Exception):
n.initialize()
print "Setting region1 dims"
r1dims = engine.Dimensions([6, 4])
region1.setDimensions(r1dims)
print "Initialize should now succeed"
n.initialize()
> r2dims = region2.dimensions
tests/unit/nupic/engine/network_test.py:448:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <nupic.engine.Region object at 0x60973230>
def _getDimensions(self):
"""Dimensions of the region"""
> return Dimensions(tuple(self._region.getDimensions()))
E TypeError: 'Dimensions' object is not iterable
/usr/local/lib/python2.7/dist-packages/nupic/engine/__init__.py:475: TypeError
----------------------------- Captured stdout call -----------------------------
Initialize should fail...
Setting region1 dims
Initialize should now succeed
TestNode.initialize() here.
TestNode.initialize() here.
----------------------------- Captured stderr call -----------------------------
ERR: Network::initialize() -- unable to evaluate all links
The following links could not be evaluated:
[region1.bottomUpOut (region dims: [unspecified]) to region2.bottomUpIn (region dims: [unspecified]) type: TestFanIn2]
[/home/pi/nupic.core/src/nupic/engine/Network.cpp line 488]
_________________________ NetworkSugarTest.testRegion __________________________
self = <tests.unit.nupic.engine.syntactic_sugar_test.NetworkSugarTest testMethod=testRegion>
@unittest.skipIf(sys.platform.lower().startswith("win"),
"Not supported on Windows, yet!")
def testRegion(self):
r = net.Network().addRegion('r', 'py.TestNode', '')
print r.spec
self.assertEqual(r.type, 'py.TestNode')
self.assertEqual(r.name, 'r')
> self.assertTrue(r.dimensions.isUnspecified())
tests/unit/nupic/engine/syntactic_sugar_test.py:122:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <nupic.engine.Region object at 0x73babf50>
def _getDimensions(self):
"""Dimensions of the region"""
> return Dimensions(tuple(self._region.getDimensions()))
E TypeError: 'Dimensions' object is not iterable
/usr/local/lib/python2.7/dist-packages/nupic/engine/__init__.py:475: TypeError
----------------------------- Captured stdout call -----------------------------
Spec:
Description:
The node spec of the NuPIC 2 Python TestNode
Parameters:
failInCompute
description: For testing failure in compute()
type: Int32
count: 1
stringParam
description: String parameter
type: Byte
count: 0
real32Param
description: Real32 scalar parameter
type: Real32
count: 1
failInInit
description: For testing failure in __init__()
type: Int32
count: 1
boolArrayParam
description: bool array parameter
type: Bool
count: 0
uint32Param
description: UInt32 scalar parameter
type: UInt32
count: 1
boolParam
description: bool parameter
type: Bool
count: 1
int32Param
description: Int32 scalar parameter
type: Int32
count: 1
uint64Param
description: UInt64 scalar parameter
type: UInt64
count: 1
int64arrayParam
description: Int64 array parameter
type: Int64
count: 0
int64Param
description: Int64 scalar parameter
type: Int64
count: 1
real64Param
description: Real64 scalar parameter
type: Real64
count: 1
real32arrayParam
description: Real32 array parameter
type: Real32
count: 0
self
description: The PyObject * of the region's Python classd
type: Handle
count: 1
Inputs:
bottomUpIn
Outputs:
bottomUpOut
Commands:
============================ pytest-warning summary ============================
WC1 /home/pi/nupic/tests/unit/nupic/engine/network_test.py cannot collect test class 'TestNode' because it has a __init__ constructor
WC1 /home/pi/nupic/tests/unit/nupic/frameworks/opf/htmpredictionmodel_classifier_helper_test.py cannot collect test class 'TestOptionParser' because it has a __init__ constructor
WC1 /home/pi/nupic/tests/unit/nupic/regions/knn_anomaly_classifier_region_test.py cannot collect test class 'TestOptionParser' because it has a __init__ constructor
WC1 /home/pi/nupic/tests/unit/nupic/support/decorators_test.py cannot collect test class 'TestParentException' because it has a __init__ constructor
WC1 /home/pi/nupic/tests/unit/nupic/support/decorators_test.py cannot collect test class 'TestChildException' because it has a __init__ constructor
11 failed, 702 passed, 17 skipped, 8 xfailed, 5 pytest-warnings in 1209.20 seconds
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