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Convolutional neural network training.
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@@ -18,14 +18,14 @@ class VectorInput : public InputBase<T>
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deque<int> input_lengths;
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public:
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VectorInput(typename T::MAC_Check&, Preprocessing<T>&, Player& P) :
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part_input(0, P)
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VectorInput(typename T::MAC_Check& MC, Preprocessing<T>& prep, Player& P) :
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part_input(MC.get_part_MC(), prep.get_part(), P)
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{
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part_input.reset_all(P);
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}
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VectorInput(SubProcessor<T>& proc, typename T::MAC_Check&) :
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VectorInput(proc.MC, proc.DataF, proc.P)
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part_input(proc.MC, proc.DataF, proc.P)
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{
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}
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@@ -41,8 +41,10 @@ public:
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input_lengths.push_back(n_bits);
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}
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void add_other(int)
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void add_other(int player, int n_bits)
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{
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for (int i = 0; i < n_bits; i++)
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part_input.add_other(player);
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}
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void send_mine()
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