Opt-einsum

`opt_einsum` is a powerful tensor contraction order optimizer for NumPy and related ecosystems.

**New Features**

- Expressions can be precompiled so that the expression optimization need not happen multiple times.
- The greedy order optimization algorithm has been tuned to be able to handle hundreds of tensors in several seconds.
- Input indices can now be unicode so that expressions can have many thousands of indices.
- GPU and distributed computing backends have been added such as Dask, TensorFlow, CUPy, Theano, and Sparse.

**Bug Fixes**

- An error affecting cases where opt_einsum mistook broadcasting operations for matrix multiply has been fixed.
- Most error messages are now more expressive.

Einsum is a very powerful function for contracting tensors of arbitrary
dimension and index. However, it is only optimized to contract two terms at a
time resulting in non-optimal scaling for contractions with many terms.
Opt_einsum aims to fix this by optimizing the contraction order which can lead
to arbitrarily large speed ups at the cost of additional intermediate tensors.

Opt_einsum is also implemented into the np.einsum function as of NumPy v1.12.

**New Features**

- Tensor contraction order optimizer.
- `opt_einsum.contract` as a drop-in replacement for `numpy.einsum`.