I am using this autoencoder model to detect anomaly.

class AnomalyDetector(Model):
  def __init__(self):
    super(AnomalyDetector, self).__init__()
    self.encoder = tf.keras.Sequential([
      layers.Dense(32, activation="relu", name = 'layer1'),
      layers.Dense(16, activation="relu", name = 'layer2'),
      layers.Dense(8, activation="relu", name = 'layer3')])

    self.decoder = tf.keras.Sequential([
      layers.Dense(16, activation="relu", name = 'layer4'),
      layers.Dense(32, activation="relu", name = 'layer5'),
      layers.Dense(140, activation="sigmoid", name = 'layer6')])

  def call(self, x):
    encoded = self.encoder(x)
    decoded = self.decoder(encoded)
    return decoded

autoencoder = AnomalyDetector()

autoencoder.compile(optimizer='adam', loss='mae')

But While fitting it shows the following errors:

history = autoencoder.fit(X_train_credible, X_train_credible, 
          epochs=20, 
          batch_size=512,
          validation_data=(X_test, X_test),
          shuffle=True)


ValueError: Exception encountered when calling layer "sequential_12" "                 f"(type Sequential).
        
        Input 0 of layer "layer1" is incompatible with the layer: expected axis -1 of input shape to have value 140, but received input with shape (None, 1)
        
        Call arguments received by layer "sequential_12" "                 f"(type Sequential):
          • inputs=tf.Tensor(shape=(None, 1), dtype=string)
          • training=False
          • mask=None
    
    
    Call arguments received by layer "anomaly_detector_6" "                 f"(type AnomalyDetector):
      • x=tf.Tensor(shape=(None, 1), dtype=string)

The shape of X_train_credible is:

X_train_credible

<tf.Tensor: shape=(299634, 140), dtype=int32, numpy=
array([[7292, 3197, 1580, ...,  623,  659, 1117],
       [6565, 1740, 3119, ...,    0,    0,    0],
       [6565, 1740, 3119, ...,    0,    0,    0],
       ...,
       [6565, 1740, 3119, ...,    0,    0,    0],
       [7292, 3197, 1580, ...,  623,  659, 1117],
       [6565, 1740, 3119, ...,    0,    0,    0]])>

I am new to TensorFlow. Anyone, please help me how to resolve this issue.

Thank you.