ValueError：层“lstm_121”的输入 0 与层不兼容：预期 ndim=3，发现 ndim=2。 收到的完整形状：（无，50）

Question

我正在为时间序列数据构建 LSTM 模型，但出现此错误：

ValueError: Input 0 of layer "lstm_121" is incompatible with the layer: expected ndim=3, found ndim=2. Full shape received: (None, 50)

我的模型：

model = Sequential()
model.add(LSTM(units=50, return_sequences=True, input_shape=(X_train.shape[1], 1)))
model.add(LSTM(50, recurrent_dropout=0.3))
model.add(LSTM(50, recurrent_dropout=0.3))
model.add(LSTM(50, recurrent_dropout=0.3))
model.add(Dense(1))

X_train的维度是(1198, 60, 1)并且y_train的维度是(1198,) 。

Answer 1

问题是 LSTM 层需要 3D 输入，而您的第 3 和第 4 LSTM 层正在接收形状为(None, 50)的 2D 输入，因为return_sequences在第 2 和第 3 LSTM 层中设置为False （默认值），而它应该设置为True 。

import numpy as np
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM, Dense

X_train = np.random.normal(size=(1198, 60, 1))
y_train = np.mean(X_train, axis=1)

model = Sequential()
model.add(LSTM(50, return_sequences=True, input_shape=X_train.shape[1:]))
model.add(LSTM(50, return_sequences=True, recurrent_dropout=0.3))
model.add(LSTM(50, return_sequences=True, recurrent_dropout=0.3))
model.add(LSTM(50, recurrent_dropout=0.3))
model.add(Dense(1))

model.compile(optimizer='adam', loss='mse')
model.fit(X_train, y_train, epochs=10, batch_size=128)