Added Tensorflow 1.0 compatability

[blester125]

Tensorflow v1.0 included a lot of changes to keeping up to date is important. A lot of things were fixable with the tensorflow upgrade script but changes to tf.split() caused errors.

Traceback (most recent call last):
  File "encoder.py", line 209, in <module>
    mdl = Model()
  File "encoder.py", line 143, in __init__
    cells, states, logits = model(X, S, M, reuse=False)
  File "encoder.py", line 93, in model
    inputs = [tf.squeeze(v, [1]) for v in tf.split(axis=1, num_or_size_splits=nsteps, value=words)]
  File "/Users/rupertdeese/.pyenv/versions/3.5.0/lib/python3.5/site-packages/tensorflow/python/ops/array_ops.py", line 1203, in split
    num = size_splits_shape.dims[0]
IndexError: list index out of range

This error was because nsteps is passed into tf.split as the num_os_size_splits argument but nsteps is a "Dimension" this was fine when tf.split() looked like this

def split(split_dim, num_split, value, name="split"):
    return gen_array_ops._split(split_dim=split_dim,
                          num_split=num_split,
                          value=value,
                          name=name)

in v1.0 tf.split() changed not only the order of arguments but the function is now

def split(value, num_or_size_splits, axis=0, num=None, name="split"):
    if isinstance(num_or_size_splits, six.integer_types):
        return gen_array_ops._split(
            split_dim=axis, num_split=num_or_size_splits, value=value, name=name)
    else:
        size_splits = ops.convert_to_tensor(num_or_size_splits)
        if num is None:
            size_splits_shape = size_splits.get_shape()
            num = size_splits_shape.dims[0]
        if num._value is None:
            raise ValueError("Cannot infer num from shape %s" % num_or_size_splits)
        return gen_array_ops._split_v(
            value=value,
            size_splits=size_splits,
            split_dim=axis,
            num_split=num,
            name=name)

Now when tf.split() is called, if isinstance(num_or_size_splits, six.integer_types): returns false and the code tries to get the Dimension's shape but it is an empty list so .dims[0] fails.

This pull request fixes the simple argument switching, function renaming incompatibilities in encoder.py and also fixes the above bug concerning tf.split()