NeuralNet.py 文件源码

def eval(self, x, rand=False):
        """Evaluate net at locations in x."""

        if rand:

            # compile theano computation graph, if haven't already done so
            if self.eval_f_rand == None:

                n_data = tt.iscalar('n_data')
                uas = [tt.tile(self.srng.normal((n_units,), dtype=dtype), [n_data, 1]) for n_units in self.n_units[1:]]

                self.eval_f_rand = theano.function(
                    inputs=[self.hs[0], n_data],
                    outputs=self.hs[-1],
                    givens=zip(self.uas, uas)
                )

            return self.eval_f_rand(x.astype(dtype), x.shape[0])

        else:

            # compile theano computation graph, if haven't already done so
            if self.eval_f == None:
                self.eval_f = theano.function(
                    inputs=[self.hs[0]],
                    outputs=self.hs[-1],
                    givens=zip(self.zas, self.mas)
                )

            return self.eval_f(x.astype(dtype))