def loadOfficialTestSpecs(args, restoreModel, restoreModelPath, config=None):
if config is None:
config = CNNGPUConfig(load=True, args=args)
testReader = TestProcessor(qnFile=config.testOfficialDevQns,
imgPathsFile=config.testOfficialImgPaths,
config=config)
model = LSTMCNNModel(config)
model.loadTrainedModel(restoreModel, restoreModelPath)
filename = 'toSubmit{}.json'.format(restoreModelPath.split('/')[-2])
model.runTest(testReader, filename)
model.destruct()
return config
def loadOfficialTest(args):
if args.config == 'CPU':
config = CNNLapConfig(load=True, args=args)
elif args.config == 'GPU':
config = CNNGPUConfig(load=True, args=args)
testReader = TestProcessor(qnFile=config.testOfficialDevQns,
imgFile=config.testOfficialImgPaths,
config=config)
model = LSTMCNNModel(config)
model.loadTrainedModel(config.restoreModel, config.restoreModelPath)
model.runTest(testReader, config.testOfficialResultFile)
model.destruct()
testReader.destruct()
def loadOfficialTest(args, restoreModel=None, restoreModelPath=None):
if args.config == 'CPU':
config = CNNLapConfig(load=True, args=args)
elif args.config == 'GPU':
config = CNNGPUConfig(load=True, args=args)
testReader = TestProcessor(qnFile=config.testOfficialDevQns,
imgFile=config.testOfficialImgPaths,
config=config)
model = LSTMCNNModel(config)
model.loadTrainedModel(restoreModel, restoreModelPath)
model.runTest(testReader, '25AprLSTMCNNSubmission.json')
model.destruct()
testReader.destruct()
def runValTest(args):
#Val set's split -- test
print('Running Val Test')
if args.config == 'CPU':
config = CNNLapConfig(load=True, args=args)
elif args.config == 'GPU':
config = CNNGPUConfig(load=True, args=args)
valTestReader = InputProcessor(config.testAnnotFile,
config.rawQnValTestFile,
config.valImgPaths,
config,
is_training=False)
model = LSTMCNNModel(config)
model.loadTrainedModel(config.restoreModel, config.restoreModelPath)
model.runPredict(valTestReader, config.csvResults)
model.destruct()
valTestReader.destruct()
def runtrain(args):
if args.config == 'CPU':
config = CNNLapConfig(load=True, args=args)
elif args.config == 'GPU':
config = CNNGPUConfig(load=True, args=args)
trainReader = InputProcessor(config.trainAnnotFile,
config.rawQnTrain,
config.trainImgPaths,
config,
is_training=True)
valReader = InputProcessor(config.valAnnotFile,
config.rawQnValTestFile,
config.valImgPaths,
config,
is_training=False)
model = LSTMCNNModel(config)
model.construct()
model.train(trainReader, valReader, config.logFile)
model.destruct()