starting to get a decent DAG
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@ -27,30 +27,40 @@ like this neural network diagram.
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\tikzstyle{annot} = [text width=4em, text centered]
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% Draw the input layer nodes
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\foreach \name / \y in {1,...,4}
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%\foreach \name / \y in {1,...,4}
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% This is the same as writing \foreach \name / \y in {1/1,2/2,3/3,4/4}
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\node[component, pin=left:Input \#\y] (I-\name) at (0,-\y) {};
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% \node[component, pin=left:Input \#\y] (I-\name) at (0,-\y) {};
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\node[component] (C-1) at (0,-1) {$C^0_1$};
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\node[component] (C-2) at (0,-3) {$C^0_2$};
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%\node[component] (C-3) at (0,-5) {$C^0_3$};
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%\node[component] (K-4) at (0,-8) {$K^0_4$};
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%\node[component] (C-5) at (0,-10) {$C^0_5$};
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%\node[component] (C-6) at (0,-12) {$C^0_6$};
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%\node[component] (K-7) at (0,-15) {$K^0_7$};
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% Draw the hidden layer nodes
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\foreach \name / \y in {1,...,5}
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\path[yshift=0.5cm]
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node[failure] (H-\name) at (\layersep,-\y cm) {};
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%\foreach \name / \y in {1,...,5}
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% \path[yshift=0.5cm]
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\node[failure] (C-1a) at (\layersep,-1) {a};
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\node[failure] (C-1b) at (\layersep,-2) {b};
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% Draw the output layer node
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\node[symptom,pin={[pin edge={->}]right:Output}, right of=H-3] (O) {};
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\node[symptom,pin={[pin edge={->}]right:Output}, right of=C-1a] (O) {};
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% Connect every node in the input layer with every node in the
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% hidden layer.
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\foreach \source in {1,...,4}
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\foreach \dest in {1,...,5}
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\path (I-\source) edge (H-\dest);
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%\foreach \source in {1,...,4}
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% \foreach \dest in {1,...,5}
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\path (C-1) edge (C-1a);
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\path (C-1) edge (C-1b);
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% Connect every node in the hidden layer with the output layer
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\foreach \source in {1,...,5}
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\path (H-\source) edge (O);
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%\foreach \source in {1,...,5}
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% \path (H-\source) edge (O);
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% Annotate the layers
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\node[annot,above of=H-1, node distance=1cm] (hl) {Hidden layer};
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\node[annot,above of=C-1a, node distance=1cm] (hl) {Hidden layer};
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\node[annot,left of=hl] {Input layer};
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\node[annot,right of=hl] {Output layer};
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\end{tikzpicture}
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