layers.py 文件源码

def recoded_features(self, inputs, layer=-1, inverse_fn=ielu):

        hidden = self.get_hidden_values(inputs, store=True, layer=layer).eval()

        bench = self.get_reconstructed_input(np.zeros_like(hidden),
                                             layer=layer).eval().squeeze()
        if inverse_fn: ibench = inverse_fn(bench)

        results = []
        for h in range(hidden.shape[-1]):
            hidden_h = np.zeros_like(hidden)
            hidden_h[..., h] = hidden[..., h]
            feature = self.get_reconstructed_input(hidden_h, layer=layer).eval().squeeze()
            if inverse_fn:
                iresult = inverse_fn(feature) - ibench
                results.append(self.coders[0].coding(iresult).eval())
            else:
                results.append(feature - bench)

        return np.array(results), bench