Python Keras 错误：预计会看到 1 个数组
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Keras error : Expected to see 1 array
提问by MysticForce
I got the following error when I tried to train an MLP model in keras(I am using keras version 1.2.2)
当我尝试在 keras 中训练 MLP 模型时出现以下错误（我使用的是 keras 版本1.2.2）
Error when checking model input: the list of Numpy arrays that you are passing to your model is not the size the model expected. Expected to see 1 arrays but instead got the following list of 12859 arrays:
检查模型输入时出错：您传递给模型的 Numpy 数组列表不是模型预期的大小。预计会看到 1 个数组，但得到了以下 12859 个数组的列表：
This is the summary of the model
这是模型的总结
____________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
====================================================================================================
dense_1 (Dense) (None, 20) 4020 dense_input_1[0][0]
____________________________________________________________________________________________________
dense_2 (Dense) (None, 2) 42 dense_1[0][0]
====================================================================================================
Total params: 4,062
Trainable params: 4,062
Non-trainable params: 0
____________________________________________________________________________________________________
None
This is the first line of model
这是模型的第一行
model.add(Dense(20, input_shape=(200,), init='lecun_uniform', activation='tanh'))
For training:
为了训练：
model.fit(X,Y,nb_epoch=100,verbose=1)
where X is a list of elements and each element in turn is a list of 200 values.
其中 X 是一个元素列表，每个元素又是一个包含 200 个值的列表。
Edit :
编辑 ：
I also tried
我也试过
model.add(Dense(20, input_shape=(12859,200), init='lecun_uniform', activation='tanh'))
but I am getting the same error
但我遇到了同样的错误
回答by Marcin Mo?ejko
Your error comes from the fact that your Xfor some reason wasn't transformed to a numpy.array. In this your Xis treated as a list of rows and this is a reason behind your error message (that it expected one input instead of list which has a number of rows elements). Transformation:
您的错误来自于您X出于某种原因未转换为numpy.array. 在此您X被视为行列表，这是错误消息背后的原因（它期望一个输入而不是具有多个行元素的列表）。转型：
X = numpy.array(X)
Y = numpy.array(Y)
I would check a data loading process because something might go wrong there.
我会检查数据加载过程，因为那里可能会出错。
UPDATE:
更新：
As it was mentioned in a comment - input_shapeneed to be changed to input_dim.
正如评论中提到的 -input_shape需要更改为input_dim.
UPDATE 2:
更新 2：
In order to keep input_shapeone should change to it to input_shape=(200,).
为了保持input_shape一应改为input_shape=(200,)。
回答by rocksyne
I fixed mine by adding
我通过添加修复了我的
np.array
数组
to train_X , train_Y , valid_X and valid_Y. For example,
到 train_X 、 train_Y 、 valid_X 和 valid_Y。例如，
model.fit(np.array(train_X),np.array(train_Y),
batch_size=32,nb_epoch=20,
validation_data=(np.array(valid_X),np.array(valid_Y)),
callbacks=[early_stop])
I got the help from here. This approach is likely to have a slow run because all data features will have to be converted to numpy arrays and it could be a lot of work for your system.
我从这里得到了帮助。这种方法可能会运行缓慢，因为所有数据特征都必须转换为 numpy 数组，这可能会给您的系统带来大量工作。
