layers.py 文件源码

def get_output(self, input, **kwargs):
        var_shape = kwargs.get('var_shape', False)
        if var_shape:
            input_shape = None
        else:
            input_shape = self.input_shape
        lin_output = conv2d(
            input=input,
            filters=self.W,
            filter_shape=self.filter_shape,
            border_mode=self.mode,
            subsample=self.subsample,
            input_shape=input_shape
        )

        if self.batch_norm:
            lin_output = self.bn_layer.get_output(lin_output)
        elif not self.no_bias:
            lin_output += self.b.dimshuffle('x', 0, 'x', 'x')

        return self.activation(lin_output)