def testFeedTermReturnsTerm(self):
model = Model()
term = Term().createFromString("test")
result = model.feedTerm(term)
self.assertIsInstance(result, Term, "Result is not a Term")
def getModel(uid):
if uid in modelCache:
return modelCache[uid]
modelDir = _getModelDir(uid)
if not os.path.exists(modelDir):
os.makedirs(modelDir)
model = Model(checkpointDir=modelDir)
if model.hasCheckpoint():
model.load()
modelCache[uid] = model
return model
def test_checkpoint(self):
model1 = Model(checkpointDir=MODEL_CHECKPOINT_DIR)
term = Term().createFromString("fox")
for _ in range(5):
prediction = model1.feedTerm(term)
self.assertTrue(len(prediction.bitmap))
model1.save()
model2 = Model(checkpointDir=MODEL_CHECKPOINT_DIR)
model2.load()
prediction = model2.feedTerm(term)
self.assertTrue(len(prediction.bitmap))
def test_checkpoint(self):
model1 = Model(checkpointDir=MODEL_CHECKPOINT_DIR)
term = Term().createFromString("fox")
for _ in range(5):
prediction = model1.feedTerm(term)
self.assertTrue(len(prediction.bitmap))
model1.save()
model2 = Model(checkpointDir=MODEL_CHECKPOINT_DIR)
model2.load()
prediction = model2.feedTerm(term)
self.assertTrue(len(prediction.bitmap))
parser.add_option(
"-f",
"--format",
dest="format",
help="Format to output (ie: csv)",
metavar="FORMAT")
parser.add_option(
"-r",
"--reset-sequences",
dest="resetSequences",
action="store_true",
default=False,
help="Reset the model sequence after every line")
(options, args) = parser.parse_args()
if not len(args):
parser.print_help()
print
raise(Exception("file required"))
model = Model(checkpointDir=options.checkpoint)
try:
readFile(args[0], model,
resetSequences=options.resetSequences, format=options.format)
except KeyboardInterrupt:
if model.canCheckpoint():
print("Saving model before exiting...")
model.save()
def testSaveWithoutCheckpointDirectory(self):
model = Model()
with self.assertRaises(Exception) as e:
model.save()
self.assertIn("No checkpoint directory specified", e.exception)
def testLoadWithoutCheckpointFile(self):
model = Model(checkpointDir=MODEL_CHECKPOINT_DIR)
with self.assertRaises(Exception) as e:
model.load()
self.assertIn("Could not find checkpoint file", e.exception)
def test_training(self):
term0 = Term().createFromString("the")
term1 = Term().createFromString("fox")
term2 = Term().createFromString("eats")
term3 = Term().createFromString("rodent")
model = Model()
prediction = model.feedTerm(term0)
self.assertFalse(len(prediction.bitmap))
for _ in range(5):
model.feedTerm(term1)
model.feedTerm(term2)
model.feedTerm(term3)
model.resetSequence()
model.feedTerm(term1)
prediction = model.feedTerm(term2)
self.assertEqual(prediction.closestString(), "rodent")
def test_training(self):
term0 = Term().createFromString("the")
term1 = Term().createFromString("fox")
term2 = Term().createFromString("eats")
term3 = Term().createFromString("rodent")
model = Model()
prediction = model.feedTerm(term0)
self.assertFalse(len(prediction.bitmap))
for _ in range(5):
model.feedTerm(term1)
model.feedTerm(term2)
model.feedTerm(term3)
model.resetSequence()
model.feedTerm(term1)
prediction = model.feedTerm(term2)
self.assertEqual(prediction.closestString(), "rodent")
if resetSequences:
model.resetSequence()
s += 1
t = 1
if __name__ == '__main__':
parser = OptionParser("%prog file [options]")
parser.add_option("--checkpoint",
dest="checkpoint",
help="Directory to save model to and load model from")
parser.add_option("-r",
"--reset-sequences",
dest="resetSequences",
action="store_true",
default=False,
help="Reset the model sequence after every line")
(options, args) = parser.parse_args()
if not len(args):
parser.print_help()
print
raise (Exception("file required"))
model = Model(checkpointDir=options.checkpoint)
readFile(args[0], model, resetSequences=options.resetSequences)
