擅长:python、mysql、java
<p>我来晚了,你的问题是你的代码中混合了Tensorflow keras和keras API。优化器和模型应该来自同一层定义。使用Keras API进行以下所有操作:</p>
<pre><code>from keras.models import Sequential
from keras.layers import Dense, Dropout, LSTM, BatchNormalization
from keras.callbacks import TensorBoard
from keras.callbacks import ModelCheckpoint
from keras.optimizers import adam
# Set Model
model = Sequential()
model.add(LSTM(128, input_shape=(train_x.shape[1:]), return_sequences=True))
model.add(Dropout(0.2))
model.add(BatchNormalization())
# Set Optimizer
opt = adam(lr=0.001, decay=1e-6)
# Compile model
model.compile(
loss='sparse_categorical_crossentropy',
optimizer=opt,
metrics=['accuracy']
)
</code></pre>
<p>我在这个例子中使用了亚当。请按照上面的代码使用相关的优化器。</p>
<p>希望这有帮助。</p>