consolidate tf activation functions
e.g.
```
def gelu(x):
    """Gaussian Error Linear Unit.
    This is a smoother version of the RELU.
    Original paper: https://arxiv.org/abs/1606.08415
    Args:
        x: float Tensor to perform activation.
    Returns:
        `x` with the GELU activation applied.
    """
    cdf = 0.5 * (1.0 + tf.tanh((np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))
    return x * cdf
```
See ACT2FN for torch.

Done by @jplu ! https://github.com/huggingface/transformers/blob/master/src/transformers/activations_tf.py#L50