Question

我在使用其功能API（继承自tf.keras.Model）定义的Keras模型时遇到此错误：

AttributeError: 'Model' object has no attribute '_output_tensor_cache'

我该如何解决？下面是重现它的最小代码片段，然后是错误的完整堆栈跟踪。调用Model.fit()时会发生错误，甚至在它进入Model.__call__()。

的实现之前

我正在使用tensorflow-gpu（1.7.0）。

import tensorflow as tf
import numpy as np


# Using Keras functional API
class Model(tf.keras.Model):
    def __init__(self):
        super(Model, self).__init__()
        self.inp = tf.keras.layers.Input(shape=(8,))
        self.fc1 = tf.keras.layers.Dense(32)
        self.fc2 = tf.keras.layers.Dense(10)

    def __call__(self, inputs, trainig=False):
        y = self.inp(inputs)
        y = self.fc1(y)
        y = self.fc2(y)
        return y


if __name__ == '__main__':
    # Just a random dataset, to try out the code
    X = np.random.rand(512, 8)
    y = np.random.randint(0, 9, size=(512,))

    model = Model()

    model.compile(loss=tf.keras.losses.categorical_crossentropy,
                  optimizer=tf.keras.optimizers.Adadelta(),
                  metric=['accuracy'])

    model.fit(X, y, batch_size=64, epochs=1, verbose=2, validation_split=.2)

错误堆栈跟踪：

Traceback (most recent call last):
  File "/home/fanta/workspace/wine-quality/minimal.py", line 29, in <module>
    model.fit(X, y, batch_size=64, epochs=1, verbose=2, validation_split=.2)
  File "/home/fanta/.local/python3.5/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/engine/training.py", line 1150, in fit
    batch_size=batch_size)
  File "/home/fanta/.local/python3.5/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/engine/training.py", line 704, in _standardize_user_data
    self._set_inputs(x)
  File "/home/fanta/.local/python3.5/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/engine/training.py", line 880, in _set_inputs
    self._symbolic_set_inputs(inputs, training=training)
  File "/home/fanta/.local/python3.5/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/engine/training.py", line 999, in _symbolic_set_inputs
    outputs = self.call(self.inputs[0], training=training)
  File "/home/fanta/.local/python3.5/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/engine/network.py", line 631, in call
    if cache_key in self._output_tensor_cache:
AttributeError: 'Model' object has no attribute '_output_tensor_cache'

Process finished with exit code 1

Answer 1

创建常规模型有什么问题吗？

def createModel():

    inputs = tf.keras.layers.Input(shape=(8,))
    outputs = tf.keras.layers.Dense(32)(inputs)
    outputs = tf.keras.layers.Dense(10)(outputs)

    return tf.keras.Model(inputs,ouptuts)

Answer 2

我收到此错误，因为我首先使用了Conv2D图层，但我没有在第一层声明input_shape参数。来自Keras：

当使用此图层作为模型中的第一个图层时，请提供关键字参数input_shape（整数的元组，不包括样本轴），例如input_shape =（128,128,3），用于data_format =＆＃34; channels_last＆＃34;中的128x128 RGB图片。

这可能对您没有帮助，但可以指向正确的方向或帮助其他人。

Answer 3

降级软件包对我有帮助：

pip install keras==2.0
pip install tensorflow==1.0

如何修复错误＆＃34;对象没有属性＆＃39; _output_tensor_cache＆＃39;＆＃34;？

3 个答案: