Method forward_train

ann_class2/dropout_theano.py:124–132

(self, X)

            plt.show()

    def forward_train(self, X):
        Z = X
        for h, p in zip(self.hidden_layers, self.dropout_rates[:-1]):
            mask = self.rng.binomial(n=1, p=p, size=Z.shape)
            Z = mask * Z
            Z = h.forward(Z)
        mask = self.rng.binomial(n=1, p=self.dropout_rates[-1], size=Z.shape)
        Z = mask * Z
        return T.nnet.softmax(Z.dot(self.W) + self.b)

    def forward_predict(self, X):
        Z = X