10.2.5 A first recurrent baseline

[Hoda Fakharzadehjahromy]

Hello,
I am trying to run the cell LSTM for weather prediction in time series: notebook 10

inputs = keras.Input(shape=(sequence_length, raw_data.shape[-1]))
x = layers.LSTM(16)(inputs)
outputs = layers.Dense(1)(x)
model = keras.Model(inputs, outputs)

callbacks = [
keras.callbacks.ModelCheckpoint("jena_lstm.keras",
save_best_only=True)
]
model.compile(optimizer="rmsprop", loss="mse", metrics=["mae"])
history = model.fit(train_dataset,
epochs=10,
validation_data=val_dataset,
callbacks=callbacks)

model = keras.models.load_model("jena_lstm.keras")
print(f"Test MAE: {model.evaluate(test_dataset)[1]:.2f}")

I get the following error:

NotImplementedError: Cannot convert a symbolic Tensor (lstm/strided_slice:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported

I use tensorflow 2.4.1