def Decoder_test(*args, **kwargs):
    inputs = tf.random.uniform((64, 62), dtype=tf.int64, minval=0, maxval=200)
    enc_output = Encoder(num_layers=2, d_model=512, num_heads=8, d_ff=2048, input_vocab_size=8500, maximum_position_encoding=10000)(inputs, False, None)
    target = tf.random.uniform((64, 26), dtype=tf.int64, minval=0, maxval=200)
    sample_decoder = Decoder(*args, **kwargs)
    (output, attn) = sample_decoder(target, enc_output=enc_output, training=False, look_ahead_mask=None, padding_mask=None)
    print(output.shape)
    print(attn['decoder_layer2_attention2'].shape)
def Decoder_test(*args, **kwargs):
    inputs = tf.random.uniform((64, 62), dtype=tf.int64, minval=0, maxval=200)
    enc_output = Encoder(num_layers=2, d_model=512, num_heads=8, d_ff=2048, input_vocab_size=8500, maximum_position_encoding=10000)(inputs, False, None)
    target = tf.random.uniform((64, 26), dtype=tf.int64, minval=0, maxval=200)
    sample_decoder = Decoder(*args, **kwargs)
    (output, attn) = sample_decoder(target, enc_output=enc_output, training=False, look_ahead_mask=None, padding_mask=None)
    print(output.shape)
    print(attn['decoder_layer2_attention2'].shape)