def trainError(self):
"""Compute RMS error of the training set"""
trainFilepath = "{}{}".format(self.exp['directory'], self.exp['train_file'])
ret = util.readTrials(trainFilepath)
return self.rnn.error(inputs=ret['inputs'], targets=ret['targets'])
def testError(self):
"""Compute RMS error of the testing set"""
testFilepath = "{}{}".format(self.exp['directory'], "Unused_Locs.train")
ret = util.readTrials(testFilepath)
return self.rnn.error(inputs=ret['inputs'], targets=ret['targets'])
def train(self, loadW=False):
if loadW is True:
if self.exp['W'] is None:
loadW = "{}W".format(self.exp['directory'])
else:
loadW = "{}{}".format(self.exp['directory'], self.exp['W'])
if self.exp['directory'] == None or self.exp['directory'] == '':
trainFilepath = self.exp['train_file']
else:
trainFilepath = "{}{}".format(self.exp['directory'], self.exp['train_file'])
ret = util.readTrials(trainFilepath)
inputs = ret['inputs']
targets = ret['targets']
inputNames = ret["inputNames"]
targetNames = ret["targetNames"]
if not loadW:
isSuccess = train_saccade(self.num_trains, inputNames, targetNames,
inputs, targets, self.rnn)
self.num_trains += 1
if isSuccess != True:
print "Error: Overfitting in batch run"
return False
print "Training Successful \(0_0)/"
# Indicate that we finished at least one training cycle and may now load old weights
self.trained = True
else:
print "Loading weights from previous training"
print "\n\n\n(0_0)\n\n\n"
isSuccess = train_saccade(self.num_trains, inputNames, targetNames,
inputs, targets, self.rnn, load_weights=loadW)
self.num_trains += 1
if isSuccess != True:
print "Error: Overfitting in batch run"
return False
print "Training Successful \(0_0)/"
return True
def getTestInputs(self): return util.readTrials(self.exp['directory'] + "Unused_Locs.train")
def getTrainInputs(self): return util.readTrials(self.exp['directory'] + self.exp['train_file'])
