Unable to run

@carpedm20, after applying https://github.com/carpedm20/NAF-tensorflow/pull/6 I run into the following conflict:

```
python main.py --env=Pendulum-v0 --is_train=True --display=True
{'action_fn': 'tanh',
'action_w': 'uniform_big',
'batch_size': 100,
'clip_action': False,
'discount': 0.99,
'display': True,
'env_name': 'Pendulum-v0',
'hidden_dims': '[100, 100]',
'hidden_fn': 'tanh',
'hidden_w': 'uniform_big',
'is_train': True,
'learning_rate': 0.001,
'log_level': 'INFO',
'max_episodes': 10000,
'max_steps': 200,
'monitor': False,
'noise': 'linear_decay',
'noise_scale': 0.3,
'random_seed': 123,
'tau': 0.001,
'update_repeat': 10,
'use_batch_norm': False,
'use_seperate_networks': False,
'w_reg': 'none',
'w_reg_scale': 0.001}
2017-12-19 18:04:45.657697: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-12-19 18:04:45.657712: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-12-19 18:04:45.657717: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-12-19 18:04:45.657721: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
[2017-12-19 18:04:45,658] Making new env: Pendulum-v0
[2017-12-19 18:04:45,689] Creating prediction network...
[2017-12-19 18:04:45,691] Creating shared networks for v, l, and mu
Traceback (most recent call last):
File "main.py", line 118, in
tf.app.run()
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "main.py", line 99, in main
scope='pred_network', **shared_args
File "/Users/Victor/NAF-tensorflow/src/network.py", line 66, in __init__
row = tf.pad(tf.concat(1, (diag_elem, non_diag_elems)), ((0, 0), (idx, 0)))
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1043, in concat
dtype=dtypes.int32).get_shape(
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 676, in convert_to_tensor
as_ref=False)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 741, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 113, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 102, in constant
tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 374, in make_tensor_proto
_AssertCompatible(values, dtype)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).__name__))
TypeError: Expected int32, got list containing Tensors of type '_Message' instead.
```

I'd appreciate if you could take a look at provide an orientation about how to address this issue.