你好，所以我有一个带有网址的熊猫df，然后下载/加载缓存，然后存储到df中。问题出现是因为熊猫将Numpy数组存储为ndarray，因此它们的形状会丢失。有什么方法可以告诉tenstorflow存储数组的形状吗？

def NN(self):
    #Trains on validation then commence batch prediction
    data = self.category_validation.agg({'URL':self.process_image,'label':self.le.fit_transform}).dropna()

    print(data['URL'].values[0])
    print(data['URL'].values[0].shape)
    print(data['URL'].values.shape)
    exit(1)


    #One of Keras' best templates
    self.nn = model(...)

    #Compile the model
    self.nn.compile(...)

    #Fit the first instance of the data
    self.nn.fit(data['URL'].values,data['label'].values)

TF.张量（...，形状=（299, 299, 3)，dtype=浮点32) (299, 299, 3) (490,)

ValueError:无法将NumPy数组转换为Tensor（不支持的对象类型tensorflow.python.framework.ops.Tensor）。

    def process_image(self,url):
        #Read image from filepath and reshape it to the appropriate shape for model 
        path = "path/"+self.clean_url(url)

        #Checks if files exists, if not it tries to download if that doesn't work
        if os.path.exists(path):
            image = tf.keras.preprocessing.image.load_img(path,target_size=(299,299))
            image = tf.keras.preprocessing.image.img_to_array(image)
        elif self.get_image(url) == 0:
            return float('nan')
        else:
            image = tf.keras.preprocessing.image.load_img(path,target_size=(299,299))
            image = tf.keras.preprocessing.image.img_to_array(image)
            
        return image/255