ValueError:输入0与层lstm_13不兼容:预期ndim = 3,找到的ndim = 4 [英] ValueError: Input 0 is incompatible with layer lstm_13: expected ndim=3, found ndim=4
问题描述
我正在尝试进行多类别分类,这是我的训练输入和输出的详细信息:
I am trying for multi-class classification and here are the details of my training input and output:
train_input.shape =(1,95000,360)(每个95000长度的输入数组 元素是360个长度的数组)
train_input.shape= (1, 95000, 360) (95000 length input array with each element being an array of 360 length)
train_output.shape =(1,95000,22)(有22个课程)
train_output.shape = (1, 95000, 22) (22 Classes are there)
model = Sequential()
model.add(LSTM(22, input_shape=(1, 95000,360)))
model.add(Dense(22, activation='softmax'))
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
print(model.summary())
model.fit(train_input, train_output, epochs=2, batch_size=500)
错误是:
ValueError:输入0与lstm_13层不兼容:预期的ndim = 3,找到的ndim = 4 排队: model.add(LSTM(22,input_shape =(1,95000,360)))
ValueError: Input 0 is incompatible with layer lstm_13: expected ndim=3, found ndim=4 in line: model.add(LSTM(22, input_shape=(1, 95000,360)))
请帮助我,我无法通过其他答案解决.
Please help me out, I am not able to solve it through other answers.
推荐答案
我通过制作
输入大小:(95000,360,1)和 输出大小:(95000,22)
input size: (95000,360,1) and output size: (95000,22)
,然后在定义模型的代码中将输入形状更改为(360,1):
and changed the input shape to (360,1) in the code where model is defined:
model = Sequential()
model.add(LSTM(22, input_shape=(360,1)))
model.add(Dense(22, activation='softmax'))
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
print(model.summary())
model.fit(ml2_train_input, ml2_train_output_enc, epochs=2, batch_size=500)
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