SdA.py 文件源码

def pretraining_function(self,train_set_x,batch_size):
        '''
        ????????????????dA???,??????????
        ?????minibatch????????minibatch???????
        train_set_x: theano.tensor.TensorType   ??dA????(????)
        batch_size: int  [mini]batch??

        '''
        #[mini]batch???
        index=T.lscalar('index')
        corruption_level=T.scalar('corruption') #corruption???
        learning_rate=T.scalar('lr') #???
        #batch??
        n_bathes=train_set_x.get_value(borrow=True).shape[0]/batch_size
        #??index?????
        # batch
        batch_begin=index*batch_size
        #??index?????batch
        batch_end=batch_begin+batch_size

        pretrain_fns=[]
        for dA in self.dA_layers: #??dA
            #???????????
            cost,updates=dA.get_cost_updates(corruption_level,
                                            learning_rate)
            #??theano??
            fn=theano.function(inputs=[index,
                            theano.Param(corruption_level,default=0.2),
                            theano.Param(learning_rate,default=0.1)],
                                outputs=cost,
                                updates=updates,
                                givens={self.x:train_set_x[batch_begin:
                                                           batch_end]})
            #?fn???????
            pretrain_fns.append(fn)

        return pretrain_fns