[Python] Using a symbolic `tf.Tensor` as a Python `bool` is not allowed

when I add a masking layer in my model, it gives this error. works fine without the masking tho. If anyone can solve this, id be grateful ! been scratching my head for 3 days now. TensorFlow 2.17

def build_lstm(examples):
print("Building Model")
X_train = examples[:, :-1, :]
y_train = examples[:, 1:, :]
model = Sequential()
model.add(Masking(mask_value=0.0, input_shape=(X_train.shape[1], X_train.shape[2])))
model.add(LSTM(128, return_sequences=True, kernel_regularizer=l2(0.001), kernel_initializer=GlorotUniform()))
model.add(LayerNormalization())
model.add(Dropout(0.1))
model.add(LSTM(256, return_sequences=True, kernel_regularizer=l2(0.001)))
model.add(Dropout(0.1))
#model.add(Lambda(lambda x: x, mask=None))
model.add(TimeDistributed(Dense(y_train.shape[2], kernel_regularizer=l2(0.001))))
#adadelta
scheduler = ReduceLROnPlateau(monitor='loss', factor=0.5, patience=5, verbose=1)
early_stopping = EarlyStopping(monitor='loss', patience=5, restore_best_weights=True)
model.compile(loss=MeanSquaredError(), optimizer=Adam(learning_rate=0.00001, clipvalue=1.0),metrics=[MeanSquaredError(), MeanAbsoluteError(),r2_metric,'RootMeanSquaredError'])
print("Training Model")
history = model.fit(X_train, y_train, batch_size=64, epochs=30, callbacks=[scheduler, early_stopping])
print("Training complete. Returning Model")
return model, history


Here is the complete error:

OperatorNotAllowedInGraphError: Exception encountered when calling TimeDistributed.call().

Using a symbolic `tf.Tensor` as a Python `bool` is not allowed. You can attempt the following resolutions to the problem: If you are running in Graph mode, use Eager execution mode or decorate this function with @tf.function. If you are using AutoGraph, you can try decorating this function with @tf.function. If that does not work, then you may be using an unsupported feature or your source code may not be visible to AutoGraph. See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/autograph/g3doc/reference/limitations.md#access-to-source-code for more information.

Arguments received by TimeDistributed.call():
• inputs=tf.Tensor(shape=(None, 13, 256), dtype=float32)
• training=True
• mask=tf.Tensor(shape=(None, 13), dtype=bool)

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