adversarial_tools.py 文件源码

def __init__(self, model):
        '''
        :param model: Keras model.
            This code makes a bunch of assumptions about the model:
            - Model has single input
            - Embedding is the first layer
            - Model output is a scalar (logistic regression)
        '''

        input_tensor = model.input
        embedding_tensor = model.layers[0](input_tensor)
        output_tensor = embedding_tensor
        for layer in model.layers[1:]:
            output_tensor = layer(output_tensor)
        grad_tensor, = tf.gradients(output_tensor, [embedding_tensor])
        grad_sum_tensor = tf.reduce_sum(grad_tensor, reduction_indices=2)

        self.model = model
        self.input_tensor = input_tensor
        self.grad_sum_tensor = grad_sum_tensor