如何使用自定义层 Tensorflow2 保存自定义模型答案

【问题标题】：How to save a custom model with custom layer Tensorflow2如何使用自定义层 Tensorflow2 保存自定义模型
【发布时间】：2020-07-15 17:58:33
【问题描述】：

我正在尝试减轻模型的重量：model.save_weights('filepath')

我的模特是

class CLayer(Layer):
    def __init__(self, hidden_units=[]):
        super(PartCoder, self).__init__()
        # self.layers = NoDependency([])
        # self.__dict__['layers'] = []
        self.layers = []
        for u in hidden_units:
            self.layers.append(keras.layers.Dense(u))

class CModel(Model):
    def __init__(self, hidden_units):
        super(CustomModel, self).__init__()
        self.cLayers = CLayer(hidden_units=hidden_units)


model_1 = CModel(hidden_units=[2,4])  
model_1.save_weights("filepath_1")  #--> worked

model_2 = CModel(hidden_units=[2,4])
model_2.load_weights("filepaht_1")  #--> worked

#train model_2
model_2.save_weights("filepath_2") #--> Crash here

结果：

Epoch 5: Loss = 72.76963806152344
Epoch 10: Loss = 68.98507690429688
Epoch 15: Loss = 65.25872039794922
Epoch 20: Loss = 61.60311508178711
Epoch 25: Loss = 58.087005615234375

但有错误：

ValueError: Unable to save the object ListWrapper([<tensorflow.python.keras.layers.core.Dense object at 0x7f032829d4e0>, <tensorflow.python.keras.layers.core.Dense object at 0x7f032829da90>, <tensorflow.python.keras.layers.core.Dense object at 0x7f032ad38e80>, <tensorflow.python.keras.layers.core.Dense object at 0x7f0328165048>]) (a list wrapper constructed to track trackable TensorFlow objects). A list element was replaced (__setitem__, __setslice__), deleted (__delitem__, __delslice__), or moved (sort). In order to support restoration on object creation, tracking is exclusively for append-only data structures.

If you don't need this list checkpointed, wrap it in a tf.contrib.checkpoint.NoDependency object; it will be automatically un-wrapped and subsequently ignored.

在google上找到后，我尝试使用：

self.__dict__['layers'] = []
#OR: self.layers = NoDependency([])

用于保存CLayer 类中的层列表。此解决方案可行但层中的权重未更新。

Epoch 5: Loss = 76.57701873779297
Epoch 10: Loss = 76.57701873779297
Epoch 15: Loss = 76.57701873779297
Epoch 20: Loss = 76.57701873779297

链接：Tried solution

我的问题是如何将带有自定义层的模型保存为上述示例模型而不会出错。

【问题讨论】：

标签： python tensorflow deep-learning neural-network model

【解决方案1】：

经过很长时间，我尽我所能搜索和修复。然后我搬到了 Pytorch。没有错误地保存模型更容易。最后，我通过使用 Pytorch 解决了，并且成功了。

【讨论】：