model.py 文件源码

def report(self,train_data,
               test_data=None,
               train_data_to=None,
               test_data_to=None,
               batch_size=1000,
               **kwargs):
        test_data     = train_data if test_data is None else test_data
        train_data_to = train_data if train_data_to is None else train_data_to
        test_data_to  = test_data  if test_data_to is None else test_data_to
        opts = {'verbose':0,'batch_size':batch_size}
        def test_both(msg, fn):
            print(msg.format(fn(train_data)))
            if test_data is not None:
                print((msg+" (validation)").format(fn(test_data)))
        self.autoencoder.compile(optimizer='adam', loss=mse)
        test_both("Reconstruction MSE: {}",
                  lambda data: self.autoencoder.evaluate(data,data,**opts))
        test_both("Reconstruction MSE (gaussian 0.3): {}",
                  lambda data: self.autoencoder.evaluate(gaussian(data),data,**opts))
        test_both("Reconstruction MSE (salt 0.06): {}",
                  lambda data: self.autoencoder.evaluate(salt(data),data,**opts))
        test_both("Reconstruction MSE (pepper 0.06): {}",
                  lambda data: self.autoencoder.evaluate(pepper(data),data,**opts))
        # self.autoencoder.compile(optimizer=optimizer, loss=bce)
        # test_both("Reconstruction BCE: {}",
        #           lambda data: self.autoencoder.evaluate(data,data,**opts))
        # test_both("Noise reconstruction BCE (gaussian 0.3): {}",
        #           lambda data: self.autoencoder.evaluate(gaussian(data),data,**opts))
        # test_both("Noise reconstruction BCE (salt 0.1): {}",
        #           lambda data: self.autoencoder.evaluate(salt(data),data,**opts))
        # test_both("Noise reconstruction BCE (pepper 0.1): {}",
        #           lambda data: self.autoencoder.evaluate(pepper(data),data,**opts))
        test_both("Latent activation: {}",
                  lambda data: self.encode_binary(train_data,batch_size=batch_size,).mean())
        return self