小编Hye*_*oun的帖子

我试图在没有训练的情况下在 Tensorboard 中可视化模型。

我检查了这个和那个，但即使对于最简单的模型，这仍然不起作用。

import tensorflow as tf
import tensorflow.keras as keras
# Both tf.__version__ tensorboard.__version__ are 2.5.0

s_model = keras.models.Sequential([
    keras.layers.Flatten(input_shape=(28, 28)),
    keras.layers.Dense(32, activation='relu'),
    keras.layers.Dropout(0.2),
    keras.layers.Dense(10, activation='softmax')
])

logdir = '.../logs'
_callbacks = keras.callbacks.TensorBoard(log_dir=logdir)
_callbacks.set_model(s_model) # This is exactly suggested in the link

当我执行上述操作时，我收到错误消息：

图形可视化失败。

错误：GraphDef 格式错误。有时，这可能是由于网络连接不良或难以协调多个 GraphDef 造成的；对于后一种情况，请参考 https://github.com/tensorflow/tensorboard/issues/1929。

我不认为这是一个协调问题，因为它不是自定义函数，如果我编译模型，训练，那么我可以获得我想要的图形可视化。

s_model.compile(
    optimizer='adam',
    loss='sparse_categorical_crossentropy',
    metrics=['accuracy'])

(train_images, train_labels), _ = keras.datasets.fashion_mnist.load_data()
train_images = train_images / 255.0

logdir = '.../logs'
tensorboard_callback = keras.callbacks.TensorBoard(log_dir=logdir)

s_model.fit(
    train_images,
    train_labels, …

我的 python 版本 3.6.5
tensorflow 版本 2.3.0

简单的自定义模型

import tensorflow as tf
import tensorflow.keras as keras
class x(keras.layers.Layer):
    def build(self, input_shape):
        self.add_weight()

q = keras.layers.Input(1)
o = x()(q)
model = keras.models.Model(q, o)
model.save("temp_model")

它失败了 AttributeError: 'NoneType' object has no attribute 'replace'

怎么了？

欲知详情，

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-160-d7ce2ee17e65> in <module>
      6 o = x()(q)
      7 qwer = keras.models.Model(q, o)
----> 8 qwer.save("qwer")

~\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\keras\engine\training.py in save(self, filepath, overwrite, include_optimizer, save_format, signatures, options)
   1977     """
   1978     save.save_model(self, filepath, overwrite, …