尝试在Keras中拟合一个模型,初始化和编译如下,但没有得到值错误。有什么建议的方法来调试这些错误?我是新来的。在
我能早点发现问题吗,即在初始化或编译模型时?在
model = Model((64,64,3))
opt = keras.optimizers.Adam(lr=0.001, beta_1=0.9, beta_2=0.999, epsilon=None, decay=0.0)
binLoss = "binary_crossentropy"
model.compile(optimizer = opt, loss = binLoss, metrics = ["accuracy"])
ValueError Traceback (most recent call last)
<ipython-input-15-5b61099068d8> in <module>()
1 ### START CODE HERE ### (1 line)
----> 2 happyModel.fit(x = X_train, y = Y_train, epochs = 100, batch_size = 32)
3 ### END CODE HERE ###
/opt/conda/lib/python3.6/site-packages/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)
1574 else:
1575 ins = x + y + sample_weights
-> 1576 self._make_train_function()
1577 f = self.train_function
1578
...
/opt/conda/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py in make_tensor_proto(values, dtype, shape, verify_shape)
362 else:
363 if values is None:
--> 364 raise ValueError("None values not supported.")
365 # if dtype is provided, forces numpy array to be the type
366 # provided if possible.
ValueError: None values not supported.
将opt替换为“adam”解决了这个问题,但我不清楚为什么https://keras.io/optimizers/上的指令建议两者都可以。在
更新Keras,因为在2.1.3之前,None不是epsilon的有效参数
这不是使用kerasapi的有效模型构造。您应该看看documentation,其中有一个30秒的指南,介绍了如何构建一个最小模型:
如果您仍然对文档中的内容感到不舒服,可以从一个tutorial开始,它解释了沿途的一些概念。在
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