Question

我正在尝试提高EEG分类器的准确性。目前，我仅使用转换层和完全连接的层进行分类。在文献中，我发现人们在其CNN模型中使用LSTM层。我想尝试一下，但是出现以下错误。

我使用的数据是时间序列EEG数据64通道x 325个样本（以500 Hz采样，即650 ms）。 X =（1923,63,325,1）和y =（1923，）

model = Sequential()

model.add(TimeDistributed(Conv2D(64, (1, 3), input_shape=X.shape[1:])))
model.add(Activation('relu'))

model.add(TimeDistributed(Conv2D(64, (1, 3))))
model.add(Activation('relu')) 
model.add(MaxPooling2D(pool_size=(1, 2)))

model.add(TimeDistributed(Conv2D(64, (1, 3))))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(1, 2)))

model.add(TimeDistributed(Flatten()))

model.add(LSTM(128,return_sequences=True))

model.add(LSTM(128,return_sequences=True))

model.add(Dense(16))
model.add(Activation('relu'))
model.add(Dropout(0.3)) 

model.add(Dense(2))
model.add(Activation('softmax'))

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

我得到的错误：

IndexError: list index out of range

我在网上看到了有关此问题的其他一些问题，但大多数问题并没有真正适用于我的应用程序。

编辑：错误被抛出

  File "<ipython-input-8-0b3d7307ea53>", line 1, in <module>
    runfile('D:/ AA TestPrograms/LALALAL/ModelV20.py', wdir='D:/ AA TestPrograms/LALALAL')

  File "d:\anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 668, in runfile
    execfile(filename, namespace)

  File "d:\anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 108, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "D:/ AA TestPrograms/LALALAL/ModelV20.py", line 115, in <module>
    history = train_model(model, xtrain, ytrain, xval, yval)

  File "D:/ AA TestPrograms/LALALAL/ModelV20.py", line 94, in train_model
    shuffle=True

  File "d:\anaconda\lib\site-packages\keras\engine\training.py", line 950, in fit
    batch_size=batch_size)

  File "d:\anaconda\lib\site-packages\keras\engine\training.py", line 671, in _standardize_user_data
    self._set_inputs(x)

  File "d:\anaconda\lib\site-packages\keras\engine\training.py", line 577, in _set_inputs
    self.build(input_shape=(None,) + inputs.shape[1:])

  File "d:\anaconda\lib\site-packages\keras\engine\sequential.py", line 225, in build
    x = layer(x)

  File "d:\anaconda\lib\site-packages\keras\engine\base_layer.py", line 457, in __call__
    output = self.call(inputs, **kwargs)

  File "d:\anaconda\lib\site-packages\keras\layers\wrappers.py", line 248, in call
    y = self.layer.call(inputs, **kwargs)

  File "d:\anaconda\lib\site-packages\keras\layers\convolutional.py", line 168, in call
    dilation_rate=self.dilation_rate)

  File "d:\anaconda\lib\site-packages\keras\backend\tensorflow_backend.py", line 3565, in conv2d
    data_format=tf_data_format)

  File "d:\anaconda\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 779, in convolution
    data_format=data_format)

  File "d:\anaconda\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 828, in __init__
    input_channels_dim = input_shape[num_spatial_dims + 1]

  File "d:\anaconda\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 615, in __getitem__
    return self._dims[key]

IndexError: list index out of range

我是Python和Tensorflow的初学者，但我认为这是检查尺寸的最后一行？如果我在tensor_shape.py中查找，则找不到IndexError。

感谢您的帮助！

Answer 1

我尝试重现它，并在更换后出现此错误 model.add(TimeDistributed(Conv2D(64, (1, 3), input_shape=X.shape[1:]))) 有了这个 model.add(TimeDistributed(Conv2D(64, (1, 3)), input_shape=X.shape[1:]))，其中X是形状的随机数组（1923,63,325,1）。因为数组的维数必须等于4，才能对每个样本顺序应用Conv2D（或没有批处理的维数），所以会引发错误。换句话说，X必须具有形状（批处理维，时间维，行维，列维，通道维）。

将LSTM层与CNN

1 个答案: