Build a 2D convolutional neural network, part 10: Connecting layers

Key Takeaways

so we've taken all these individual lego blocks now we've added them into structure but you can think of them as just free floating in space they're not connected yet it doesn't know which comes first and which output to connect to which input of which other block to do that we connect them so we go to our classifier we can go through and individually connect the output of each to the input of the next all the way through what is convenient to do in neural networks often there's a long train of elements where the output of one is connected to the input of the next and so we have a convenience function here connect sequence where we pass it a list of names of blocks to connect in a sequence so we connect our training data to our convolution to our bias to our activation function to the next convolution the next bias the next activation function to our pooling our flatten our linear and our bias and our logistic function and then to the prediction and then to the loss function you can see in the structure diagram how there is a line starting at the training data tracing all the way through to the loss function there are a few connections now that haven't yet been accounted for so on these we have to go through and make these individually by default the connect sequence function assumes that the zeroth port on the tail of that connection and the zeroth port on the block at the head of that connection are what's being connected each block can have as many connection ports as we want and we just have to specify when we're connecting what the index of the port is that we're connecting so for instance if we're connecting our training data to our one hot block our zeroth port on the training data is already occupied it's already connected to the convolution block so we want to use port one on the training data block so we specify i port tail so on the connection this is the tail of the connection the head of the connection is going to our one hot block it'll still go to the zeroth port so we can let it default to zero now when we want to connect our one hot block to our loss function the input port on the loss function the zeroth port there is already occupied so we want to specify i port head equals one the head of that connection is on the loss block and we want it to be port one similarly when we're connecting our prediction block so our copy of our logistic results to our hard max our zeroth port on the prediction block is already occupied so on the tail of that connection we want to make sure and use port one so we specify i port tail equals one with these three remaining connections we've completed our structure diagram as we see it here so now we have built our graph we've built our model