train.py 文件源码

def train_model(self, max_iters):
        """Network training loop."""
        last_snapshot_iter = -1
        timer = Timer()
        while self.solver.iter < max_iters:
            timer.tic()
            self.solver.step(1)     
            print 'fc9_1:',sorted(self.solver.net.params['fc9_1'][0].data[0])[-1]
            #print 'fc9:',sorted(self.solver.net.params['fc9'][0].data[0])[-1]
            #print 'fc7:',sorted(self.solver.net.params['fc7'][0].data[0])[-1]
            #print 'fc6:',sorted(self.solver.net.params['fc6'][0].data[0])[-1]
            #print 'fc9:',(self.solver.net.params['fc9'][0].data[0])[0]
            #print 'fc7:',(self.solver.net.params['fc7'][0].data[0])[0]
            #print 'fc6:',(self.solver.net.params['fc6'][0].data[0])[0]
            #print 'conv5_3:',self.solver.net.params['conv5_3'][0].data[0][0][0]
            #print 'conv5_2:',self.solver.net.params['conv5_2'][0].data[0][0][0]
            #print 'conv5_1:',self.solver.net.params['conv5_1'][0].data[0][0][0]
            #print 'conv4_3:',self.solver.net.params['conv4_3'][0].data[0][0][0]
            #print 'fc9:',self.solver.net.params['fc9'][0].data[0][0]
            timer.toc()
            if self.solver.iter % (10 * self.solver_param.display) == 0:
                print 'speed: {:.3f}s / iter'.format(timer.average_time)