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Using TensorFlow backend.
Number of unique input tokens: 56
Number of unique output tokens: 62
Max sequence length for inputs: 124
Max sequence length for outputs: 206
13250
Tensor("input_1:0", shape=(?, ?, 56), dtype=float32)
[<tf.Tensor 'Fill:0' shape=(?, 256, 64) dtype=float32>, <tf.Tensor 'zeros:0' shape=(?, 256) dtype=float32>, <tf.Tensor 'zeros_1:0' shape=(?, 256, 256) dtype=float32>, <tf.Tensor 'zeros_2:0' shape=(?, 256) dtype=float32>, <tf.Tensor 'Fill_1:0' shape=(?, 256) dtype=float32>, <tf.Tensor 'Fill_2:0' shape=(?, 256, 4) dtype=float32>, <tf.Tensor 'zeros_3:0' shape=(?, 256) dtype=float32>, <tf.Tensor 'zeros_4:0' shape=(?, 256)
dtype=float32>, <tf.Tensor 'Fill_3:0' shape=(?, 64, 4) dtype=float32>]
Traceback (most recent call last):
  File "C:\Apps\sa2446\lib\site-packages\tensorflow\python\framework\ops.py", line 1659, in _create_c_op
    c_op = c_api.TF_FinishOperation(op_desc)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Shape must be rank 3 but is rank 2 for 'DNC/inputs_to_controller/concat' (op: 'ConcatV2') with input shapes: [?,?,56], [?,256], [].

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "analysis.py", line 145, in <module>
    encoder_outputs, state_h = dnc_core(encoder_inputs,initial_state)
  File "C:\Apps\sa2446\lib\site-packages\tensorflow\python\keras\engine\base_layer.py", line 554, in __call__
    outputs = self.call(inputs, *args, **kwargs)
  File "C:\ICA\dm_sample\dnc\dnc.py", line 101, in call
    input_augmented = tf.concat([inputs, read_vectors_flat], 1)
  File "C:\Apps\sa2446\lib\site-packages\tensorflow\python\util\dispatch.py", line 180, in wrapper
    return target(*args, **kwargs)
  File "C:\Apps\sa2446\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1256, in concat
    return gen_array_ops.concat_v2(values=values, axis=axis, name=name)
  File "C:\Apps\sa2446\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 1148, in concat_v2
    "ConcatV2", values=values, axis=axis, name=name)
  File "C:\Apps\sa2446\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
    op_def=op_def)
  File "C:\Apps\sa2446\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "C:\Apps\sa2446\lib\site-packages\tensorflow\python\framework\ops.py", line 3300, in create_op
    op_def=op_def)
  File "C:\Apps\sa2446\lib\site-packages\tensorflow\python\framework\ops.py", line 1823, in __init__
    control_input_ops)
  File "C:\Apps\sa2446\lib\site-packages\tensorflow\python\framework\ops.py", line 1662, in _create_c_op
    raise ValueError(str(e))
ValueError: Shape must be rank 3 but is rank 2 for 'DNC/inputs_to_controller/concat' (op: 'ConcatV2') with input shapes: [?,?,56], [?,256], [].

encoder_inputs = Input(shape=(None,num_encoder_tokens))
print(encoder_inputs)
dnc_core = dnc.DNC(output_size=latent_dim, controller_units=FLAGS.units, **memory_config)
en_bs= tf.placeholder(tf.float32,[])
initial_state = dnc_core.get_initial_state(batch_size=en_bs)
print(initial_state)
encoder_outputs, state_h = dnc_core(encoder_inputs,initial_state)