getting issue in this line of code -> attn_out, attn_states = attn_layer([encoder_outputs, decoder_outputs])

[mimansha97]

Exception encountered when calling layer "tf.keras.backend.rnn" (type TFOpLambda).

You are passing KerasTensor(type_spec=TensorSpec(shape=(None, 35), dtype=tf.float32, name=None), name='tf.nn.softmax_1/Softmax:0', description="created by layer 'tf.nn.softmax_1'"), an intermediate Keras symbolic input/output, to a TF API that does not allow registering custom dispatchers, such as tf.cond, tf.function, gradient tapes, or tf.map_fn. Keras Functional model construction only supports TF API calls that do support dispatching, such as tf.math.add or tf.reshape. Other APIs cannot be called directly on symbolic Kerasinputs/outputs. You can work around this limitation by putting the operation in a custom Keras layer call and calling that layer on this symbolic input/output.

Call arguments received:
• step_function=<function AttentionLayer.call..energy_step at 0x7f4e51fe4e60>
• inputs=tf.Tensor(shape=(None, None, 256), dtype=float32)
• initial_states=['tf.Tensor(shape=(None, 35), dtype=float32)']
• go_backwards=False
• mask=None
• constants=None
• unroll=False
• input_length=None
• time_major=False
• zero_output_for_mask=False