def __init__(self, layer_args, input_shape, rand_state=np.random):
        # layer_args is a list of (layer_class, layer_init_args) for first through last layer
        self.layers_ = []
        self.input_shape = input_shape
        for args in layer_args:
            layer_class, args = args
            args['rand_state'] = rand_state
            layer = layer_class(input_shape, **args)
            self.layers_.append(layer)
            # get input shape for the next layer
            input_shape = layer.output_shape

        self._rand_state = rand_state
        self._cache_acts = None

        # this will keep track of how many batches and epochs have been trained
        self.num_batch = 0
        self.num_epoch = 0
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