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'])