Hi, 

Could be used a independant hidden layer of mlp as a fully connected layer?

regards.

El viernes, 13 de marzo de 2015, 18:25:38 (UTC+1), Pascal Lamblin escribió:
>
> Hi, 
>
> On Fri, Mar 13, 2015, Orry Messer wrote: 
> > I don't quite understand the structure of the network after the second 
> > convolution/pooling layer and just before the hidden layer. 
> > I think what is confusing me is the batch aspect of it. 
> > With a batch size of 500, the hidden layer will have 500 units. This 
> much 
> > I'm ok with. 
>
> That's not right... by coincidence, the batch size in 500, which is 
> also the number of output units of that layer. Each of these units will 
> compute a different value for each of the examples in the batch, so the 
> output of that layer will be (batch_size, n_outputs) or (500, 500). 
>
> > But what is the input to this hidden layer? In the comments it says that 
> > the hidden layer operates on matrices of size (batch_size, pixel_size), 
> > which in the case of this code 
> > is (500, 800). 
>
> That's correct. 
>
> > Does this then mean that each hidden unit has 500*800 inputs? 
>
> Not really. Each hidden unit has 800 scalar inputs. Each of these inputs 
> will take a different value for each example of the minibatch, and the 
> neuron will also output one value for each example. 
>
> > And since there are 500 hidden units, does this then mean that there 
> > are a total of 500*(500*800) connections and as many weights to tune 
> > in this layer alone? 
>
> No, the weights are the same for all the examples of the minibatch. 
>
> -- 
> Pascal 
>

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